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Since 1991, Measurement Science and Technology has awarded a Best Paper prize. The Editorial Board of this journal believes that such a prize is an opportunity to thank authors for submitting their work, and serves as an integral part of the on-going quality review of the journal. The current breadth of topical areas that are covered by MST has made it advisable to expand the recognition of excellent publications. Hence, in 2005 the Editorial Board decided to present 'Outstanding Paper Awards' in four subject categories: Fluid Mechanics; Measurement Science; Precision Measurements; and Sensors and Sensing Systems. 2005 Award Winners?Fluid Mechanics The Fluid Mechanics working group, chaired by Professor John Foss, was unanimous in its recommendation for the paper authored by J Chen and J Katz (Johns Hopkins University, USA) 'Elimination of peak-locking error in PIV analysis using the correlation mapping method', published in volume 16, issue 8, pp 1605?1618. The essence of the following citation was provided by Board Member Dr Mark Wernet: The paper of Chen and Katz describes a technique for eliminating the 'peak locking' bias error endemic to estimating the PIV correlation peak location. Particle image velocimetry (PIV) is used widely in both fundamental and applied fluid mechanics. In essence, a two-dimensional velocity map is extracted from two successive high-resolution images of light scattered by minute tracer particles. The incident light is derived from two laser beams which have been expanded into sheets. A precise time delay is imposed between the two laser light sheets. The cross-correlation of the scattered light intensity within corresponding small interrogation regions in the two images gives the displacement of the particles and hence the local velocity. Typically, in PIV processing, the correlation peak location is determined by fitting a curve through the correlation peak. This process is known to suffer from a bias error where the estimated displacements are grouped around integer pixel values. Background subtraction can help reduce the tendency for peak locking, but does not completely remove the bias. Other techniques for eliminating the bias are available, but require time-consuming, iterative processing. The paper of Chen and Katz describes a processing technique that removes this 'peak locking' bias by avoiding the curve fitting process altogether. Instead, the displacement necessary to map the first exposure into the second exposure is determined via a correlation mapping operation. Several example cases using synthetic data and actual PIV data are presented. The new approach is also compatible with the Subregion Image Distortion technique to further improve the quality of the PIV displacement estimates. 2005 Award Winners?Measurement Science The 2005 Measurement Science and Technology Outstanding Paper Award in the Measurement Science category has been awarded to M E Webber, T MacDonald, M B Pushkarsky (Pranalytica, Inc., USA), C K N Patel (UCLA, USA), Y Zhao, N Marcillac and F M Mitloehner (University of California, Davis, USA) for the article 'Agricultural ammonia sensor using diode lasers and photoacoustic spectroscopy', published in volume 16, issue 8, pp 1547?1553. In making their recommendation the Measurement Science working group chaired by Professor Richard Dewhurst gave the following endorsement: This paper provides an excellent description of a novel instrumentation system used to detect agricultural ammonia. The sensor system has been designed for use in dusty and humid conditions, and a portable prototype was field-tested on several days over an eight-week period, with encouraging results. In this paper, a short theoretical section is followed by instrumentation details, with a description of the optical system, the electronics, embedded programming and algorithm development. An erbium-doped fibre amplifier was used to enhance the photoacoustic signal by boosting the laser's output power, whilst maintaining the linewidth of the seed laser source. Careful laboratory calibration tests are then described, showing benchmark results of sub-ppm sensitivity, and excellent system linearity up to 100 ppm. The final section describes the condition under which field tests were conducted, and validates the photoacoustic method by cross reference with both a Draeger sensor and an ion chromatograph. Overall, the paper possesses several innovative ideas. It is a well-structured paper, containing details of the instrumentation and techniques used. It has a careful discussion of the data and its validation, in order to realize the precision demonstrated. It is an innovative system required for a topical need within environmental protection. 2005 Award Winners?Precision Measurement The 2005 Measurement Science and Technology Outstanding Paper Award in the Precision Measurement category has been awarded to Ichiko Misumi, Satoshi Gonda, Qiangxian Huang, Taeho Keem, Tomizo Kurosawa (National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology (NMIJ/AIST), Japan), Akihiro Fujii, Nahoko Hisata, Takeshi Yamagishi, Hirohisa Fujimoto (Olympus Corporation, Japan), Ken Enjoji (Olympus Systems Corporation, Japan), Sunao Aya and Hiroaki Sumitani (Mitsubishi Electric Corporation, Japan) for the article 'Sub-hundred nanometre pitch measurements using an AFM with differential laser interferometers for designing usable lateral scales', published in volume 16, issue 10, pp 2080?2090. In making their recommendation the Precision Measurements working group chaired by Dr Kenichi Fujii gave the following endorsement: This paper describes a new instrument developed for measuring the pitches of one-dimensional grating standards. In the field of nanotechnology and in the semiconductor industry, reliable one-dimensional grating standards have been solicited for calibrating length measurement in nanometre regions. In the instrument described here, an atomic force microscope (AFM) is combined with differential laser interferometers so that the atomic scale resolution of the AFM is accurately calibrated by optical interferometry, achieving an unprecedented uncertainty of 0.2 nm in measuring the pitches of about 50 nm. The instrument also calibrates the pitches in a wide scanning range. This paper analysed the uncertainty of the measurement in detail, helping to provide users with reliable certified reference materials for one-dimensional grating standards. 2005 Award Winners?Sensors and Sensing Systems The 2005 Measurement Science and Technology Outstanding Paper Award in the Sensors and Sensing Systems category has been awarded to Nicola Bowler and Yongqiang Huang (Iowa State University, USA) for the article 'Electrical conductivity measurement of metal plates using broadband eddy-current and four-point methods', published in volume 16, issue 11, pp 2193?2200. In making their recommendation the Sensors and Sensing Systems working group chaired by Professor Paul Regtien gave the following endorsement: The paper addresses two methods to measure the electrical conductivity of metal plates of various materials. In particular for ferromagnetic plates, traditional methods show relatively large measurement uncertainties. In this paper, the origins of these large inaccuracies are studied, and two alternative methods are presented that yield much better accuracies. Both methods?a broadband eddy-current and a four-point contact scheme?are extensively analysed theoretically as well as experimentally. The results are compared with other published data, for plates of brass, stainless steel and spring steel. An uncertainty analysis reveals the superiority of the newly introduced methods in the case of steel. The four-point method has the advantage of being easy to use. The paper is well-structured, with a good balance between theory and experiments, and a clear presentation of the measurement data and associated uncertainties, both in tables and graphs. The paper concludes with a convincing discussion and outlook for further research. The results are of great value in the field of non-destructive testing. The Outstanding Paper Awards, comprising a cash honorarium and certificate, will be presented to the authors of the winning papers at suitable venues in the near future. The Editorial Board would like to congratulate the winning authors and would like to encourage all researchers to think of Measurement Science and Technology as the home for your best submissions.

Microscopic hyperspectral imaging technology has been widely used in pathological analysis as it can obtain both spatial and spectral information of samples. However, most hyperspectral imaging systems can only capture images in a single field of view. Therefore, an image mosaic is one of the most important steps in a large-scale microscopic hyperspectral imaging system. This paper proposes a microscopic hyperspectral image (HSI) mosaic method based on Speeded-Up Robust Features (SURF) and linear synthesis to achieve large-scale HSIs. In contrast to other SURF-based image mosaic methods, the proposed method leverages both image content and coordinate information to improve the accuracy and stability of the image mosaic. In addition, multiple bands of HSIs with different texture information and grayscale are applied in image matching to take full advantage of spatial redundancy. Simultaneously, a blank microscopic HSI screening method is introduced in this paper to pick out a clearer blank image for better preprocessing, i.e. removing interference in the optical path and the interference of dust on slides. Finally, the preprocessed images are synthesized by linear-based synthesis methods due to their simple synthesis structure and better universality. Additionally, a file format, i.e. hyperslide, is defined for large-scale HSIs and can be browsed with HyperViewer software. Experimental results show that the proposed microscopic HSI mosaic method can obtain high-quality large-scale microscopic HSIs of tissue sections.

Non-intrusive, reliable and precise torque measurement is critical to dynamic performance monitoring, control and condition monitoring of rotating mechanical systems. This paper presents a novel, contactless torque measurement system consisting of two shaft-mounted zebra tapes and two optical sensors mounted on stationary rigid supports. Unlike conventional torque measurement methods, the proposed system does not require costly embedded sensors or shaft-mounted electronics. Moreover, its non-intrusive nature, adaptable design, simple installation and low cost make it suitable for a large variety of advanced engineering applications. Torque measurement is achieved by estimating the shaft twist angle through analysis of zebra tape pulse train time shifts. This paper presents and compares two signal processing methods for torque measurement: rising edge detection and cross-correlation. The performance of the proposed system has been proven experimentally under both static and variable conditions and both processing approaches show good agreement with reference measurements from an in-line, invasive torque transducer. Measurement uncertainty has been estimated according to the ISO GUM (Guide to the expression of uncertainty in measurement). Type A analysis of experimental data has provided an expanded uncertainty relative to the system full-scale torque of ±0.30 % and ±0.86 % for the rising edge and cross-correlation approaches, respectively. Statistical simulations performed by the Monte Carlo method have provided, in the worst case, an expanded uncertainty of ±1.19 %.

The paper addresses the issue of online diagnosis and prognosis of emerging faults in human-engineered complex systems. Specifically, the paper reports a dynamic data-driven analytical tool for early detection of incipient faults and real-time estimation of remaining useful fatigue life in polycrystalline alloys. The algorithms for fatigue life estimation rely on time series data analysis of ultrasonic signals and are built upon the principles of symbolic dynamics, information theory and statistical pattern recognition. The proposed method is experimentally validated by using 7075-T6 aluminium alloy specimens on a special-purpose fatigue test apparatus that is equipped with ultrasonic flaw detectors and an optical travelling microscope. The real-time information, derived by the proposed method, is useful for mitigation of widespread fatigue damage and is potentially applicable to life extending and resilient control of mechanical structures.

This paper presents a new mechatronic approach of using infrared thermography combined with image processing for the quality control of a laser sealing process for food containers. The suggested approach uses an on-line infrared system to assess the heat distribution within the container seal in order to guarantee the integrity of the process. Visual image processing is then used for quality assurance to guarantee optimum sealing. The results described in this paper show examples of the capability of the condition monitoring system to detect faults in the sealing process. The results found indicate that the suggested approach could form an effective quality control and assurance system.

Non-acoustic speech sensors have a long history of clinical applications but have only recently been applied to the problem of measuring speech signals in the presence of strong background noise. These sensors typically provide measurements of one or more aspects of the speech production process, such as glottal activity, as a proxy for the actual speech and tend to be highly immune to acoustic noise. In this paper, a new non-acoustic speech sensor based on a tuned electromagnetic resonator collar is proposed. The collar is designed to be worn around the talker's neck and is sensitive to small changes in the dielectric properties of the glottis as well as subglottal and supraglottal systems that result from voiced speech. Unlike the majority of previously developed non-acoustic speech sensors, the proposed sensor does not require skin contact or precise alignment to effectively measure glottal activity. This paper develops the sensor concept and provides analytical, simulated and experimental results that demonstrate the potential of the new speech sensor.

The paper introduces a novel enabling step toward the widespread exploitation of the multi-dimensional process sensing offered by process tomography (PT) technology that has demonstrated a unique insight into many processes. Most current applications are laboratory or pilot-plant based. Generic system integration tools are proposed that deal systematically with PT data to accelerate the assessment and application of PT sensing, and hence deliver the large benefits expected to arise from large-scale exploitation of multi-dimensional sensing. Where multi-dimensional PT sensor data are available, a suite of enabling tools, reality visualization modelling (RVM), are proposed as the complementary generic set of processing methods needed to take internal process state data and yield directly usable process information, either for design model confirmation or for effective plant control, or monitoring. A further step: generic-RVM (GRVM) extends this concept through a generically defined process topology, complete with method and model set, to expedite mass-market application. The paper offers a practical illustration through a small pilot trial.

Presented here are 11 noteworthy papers selected from the Fifth International Conference on Inverse Problems in Engineering: Theory and Practice held in Cambridge, UK during 11–15 July 2005. The papers have been peer-reviewed to the usual high standards of this journal and the contributions of reviewers are much appreciated. The conference featured a good balance of the fundamental mathematical concepts of inverse problems with a diverse range of important and interesting applications, which are represented here by the selected papers. Aspects of finite-element modelling and the performance of inverse algorithms are investigated by Autrique et al and Leduc et al. Statistical aspects are considered by Emery et al and Watzenig et al with regard to Bayesian parameter estimation and inversion using particle filters. Electrostatic applications are demonstrated by van Berkel and Lionheart and also Nakatani et al. Contributions to the applications of electrical techniques and specifically electrical tomographies are provided by Wakatsuki and Kagawa, Kim et al and Kortschak et al. Aspects of inversion in optical tomography are investigated by Wright et al and Douiri et al. The authors are representative of the worldwide interest in inverse problems relating to engineering applications and their efforts in producing these excellent papers will be appreciated by many readers of this journal.

This special issue of Measurement Science and Technology provides an overview of current developments in the field of optical fibre sensors. The papers presented here are more detailed versions of those presented at the 17th Optical Fibre Sensors conference (OFS-17) held at the Oud St-Jan Art and Congress Centre in Bruges, Belgium, from 23–27 May 2005. The first OFS conference was held in London in 1983 and the conference series is now held in international locations every 18 months and is the recognized venue for presentations of papers describing recent developments in the field of fibre optic sensing. The conference in Bruges was the largest to date of the OFS series with approximately 450 attendees and consisted of a plenary talk, describing photonic crystal gas sensors, ten invited contributions, 51 oral presentations and 197 posters. A third of the papers in this special issue are concerned with fibre Bragg and long period gratings, reflecting the widespread interest in this technology. Papers describe new laser based fabrication and processing techniques, signal processing methods, and applications to the measurement of physical parameters such as radiation detection, hydrogen sensing, load monitoring in wind turbines and stress measurement for geotechnical applications. Other non-grating sensing methodologies are presented for the measurement of gases, refractive index, colour and electric field/voltage. In addition to the descriptions of optical fibres sensors and signal processing schemes there are a number of contributions describing developments in enabling technologies such as sources for use with fibre sensors including, for example, quantum dots for temperature sensing. Developments in emerging technologies such as nanostructured fibres for sensing and investigating the sensing properties of carbon nanotubes using fibre sensor techniques are described along with the use of coherent imaging fibre bundles for flow measurement applications. We hope that this special issue helps to further developments in the field of optical fibre sensors and would like to thank all the contributing authors and reviewers for making this special issue possible. We would also like to thank the staff at IOPP for their support and in ensuring timely publication.

Surface filtering algorithms using Fourier, Gaussian, wavelets, etc, are well-established for simple Euclidean geometries. However, these filtration techniques cannot be applied to today's complex freeform surfaces, which have non-Euclidean geometries, without distortion of the results. This paper proposes a new multi-scale filtering algorithm for freeform surfaces that are represented by triangular meshes based on a mesh relaxation scheme. The proposed algorithm is capable of decomposing a freeform surface into different scales and separating surface roughness, waviness and form from each other, as will be demonstrated throughout the paper. Results of applying the proposed algorithm to computer-generated as well as real surfaces are represented and compared with a lifting wavelet filtering algorithm.

This study presents a method for detecting contamination events of sources of drinking water based on the Dempster?Shafer (D-S) evidence theory. The detection method has the purpose of protecting water supply systems against accidental and intentional contamination events. This purpose is achieved by first predicting future water-quality parameters using an autoregressive (AR) model. The AR model predicts future water-quality parameters using recent measurements of these parameters made with automated (on-line) water-quality sensors. Next, a probabilistic method assigns probabilities to the time series of residuals formed by comparing predicted water-quality parameters with threshold values. Finally, the D-S fusion method searches for anomalous probabilities of the residuals and uses the result of that search to determine whether the current water quality is normal (that is, free of pollution) or contaminated. The D-S fusion method is extended and improved in this paper by weighted averaging of water-contamination evidence and by the analysis of the persistence of anomalous probabilities of water-quality parameters. The extended D-S fusion method makes determinations that have a high probability of being correct concerning whether or not a source of drinking water has been contaminated. This paper's method for detecting water-contamination events was tested with water-quality time series from automated (on-line) water quality sensors. In addition, a small-scale, experimental, water-pipe network was tested to detect water-contamination events. The two tests demonstrated that the extended D-S fusion method achieves a low false alarm rate and high probabilities of detecting water contamination events.

With the trend of textile antennas development, ultra high frequency (UHF, 865–868 MHz) radio frequency identification (RFID) devices using textile materials are expected to be developed in many areas for replacing or simplifying some complex RFID devices on a PCB. In this paper, we present a textile UHF-RFID tag with two sensing positions ('radiation parts' and 'loop part') for exploring the feasibility of sucrose solutions measurements and the relationship between variables of the proposed design and the sucrose solutions. The simulated and measured resonance curves of the designs both match well (-20 dB in the simulation and -15.8 dB in the measurement at 868 MHz) and the read range measured by the RFID reader (M6e kit) is 1.71 m in air. Before the tests by the solutions on the proposed designs, a test board is developed as a preparation work for confirming the relative dielectric constants of the sensing substrate area in the real measurements. Compare the results of the simulation and the real tests, the proposed design shows good feasibility by comparing the simulated and measured results in confirmed relative dielectric constants. Moreover, its two sensing positions have different sensing features. The sensing 'radiation parts' position shows a stable frequency operation performance but sensing range is from 1.71 m (dry) to 2.3 m, while the sensing 'loop part' position has a wide sensing range from 0.4 m to 1.71 m (dry) but a lower frequency operation performance. This work was supported by Spanish Government-MINECO under Project TEC2016- 79465-R and China Scholarship Council No.201908440233.

In relation to the industrial need and to the progress of technology, Laboratoire National de M´etrologie et d’Essais (LNE) would like to improve the measurement of its primary pressure standards, spherical and flick standards. The spherical and flick standards are, respectively, used to calibrate the spindle motion error and the probe, which equip commercial conventional cylindricity-measuring machines. The primary pressure standards are obtained using pressurebalances equipped with rotary pistons. To reach a relative uncertainty of 10−6 in the pressure measurement, it is necessary to know the diameters of both the piston and the cylinder with an uncertainty of 5 nm for a piston diameter of 10 mm. Conventional machines are not able to reach such an uncertainty level. That is why the development of a new machine is necessary. The purpose of this paper is to present the concepts and the architecture adopted in the development of the new equipment dedicated to cylindricity measurement at a nanometric level of a accuracy. The choice of these concepts is based on the analysis of the uncertainty sources encountered in conventional architectures. The architecture of the new ultra-high equipment as well as the associated calibration procedures will be described and detailed.; International audience; In relation to the industrial need and to the progress of technology, Laboratoire National de M´etrologie et d’Essais (LNE) would like to improve the measurement of its primary pressure standards, spherical and flick standards. The spherical and flick standards are, respectively, used to calibrate the spindle motion error and the probe, which equip commercial conventional cylindricity-measuring machines. The primary pressure standards are obtained using pressurebalances equipped with rotary pistons. To reach a relative uncertainty of 10−6 in the pressure measurement, it is necessary to know the diameters of both the piston and the cylinder with an uncertainty of 5 nm for a piston diameter of 10 mm. Conventional machines are not able to reach such an uncertainty level. That is why the development of a new machine is necessary. The purpose of this paper is to present the concepts and the architecture adopted in the development of the new equipment dedicated to cylindricity measurement at a nanometric level of a accuracy. The choice of these concepts is based on the analysis of the uncertainty sources encountered in conventional architectures. The architecture of the new ultra-high equipment as well as the associated calibration procedures will be described and detailed.

Magnetic material properties of an electromagnetic device can be recovered by solving an inverse problem where measurements are adequately interpreted by a mathematical forward model. The accuracy of these forward models dramatically affects the accuracy of the material properties recovered by the inverse problem. The more accurate the forward model is, the more accurate recovered data are. However, the more accurate ‘fine’ models demand a high computational time and memory storage. Alternatively, less accurate ‘coarse’ models can be used with a demerit of the high expected recovery errors. This paper uses the Bayesian approximation error approach for improving the inverse problem results when coarse models are utilized. The proposed approach adapts the objective function to be minimized with the a priori misfit between fine and coarse forward model responses. In this paper, two different electromagnetic devices, namely a switched reluctance motor and an EI core inductor, are used as case studies. The proposed methodology is validated on both purely numerical and real experimental results. The results show a significant reduction in the recovery error within an acceptable computational time.

Sensor systems are one the most requested topics in the field of engineering. The importance of sensors, their technologies and their applications is self-evident through their impact on daily life. The features of sensors can still be improved and this is a matter of increasing research in the international scientific community. Several papers have been selected and reviewed to constitute a recipe for understanding advances in the area of sensors. Although they are few in number, the papers accepted for publication in this special feature of Measurement Science and Technology reflect current trends in the related areas, that is to say, resistive chemical sensing, new transducers, and applications in robotics, in olfaction and in image processing. In addition to these topics, the concept of the functionalization of nanotubes is also of great interest, as is the subject of nanowires. We thank the authors of this special feature for their contributions with dedicated papers in the areas of sensors and sensor systems. We also thank MST for hosting this special feature in order to give further expression to authors from ICST2010, the International Conference on Sensing Technology that took place in Lecce (Italy) in 2010.

This paper introduces a method for the substantial reduction of heading errors in inertial navigation systems used under GPS-denied conditions. Presumably, the method is applicable for both vehicle-based and personal navigation systems, but experiments were performed only with a personal navigation system called 'personal dead reckoning' (PDR). In order to work under GPS-denied conditions, the PDR system uses a foot-mounted inertial measurement unit (IMU). However, gyro drift in this IMU can cause large heading errors after just a few minutes of walking. To reduce these errors, the map-matched heuristic drift elimination (MAPHDE) method was developed, which estimates gyro drift errors by comparing IMU-derived heading to the direction of the nearest street segment in a database of street maps. A heuristic component in this method provides tolerance to short deviations from walking along the street, such as when crossing streets or intersections. MAPHDE keeps heading errors almost at zero, and, as a result, position errors are dramatically reduced. In this paper, MAPHDE was used in a variety of outdoor walks, without any use of GPS. This paper explains the MAPHDE method in detail and presents experimental results.

The detection of marginal pressure fluctuations in a high-pressure environment is not trivial. The resolutions of data acquisition systems and telemetric systems as well as the accuracy of pressure transducers with respect to small fluctuation amplitudes complicate reliable measurements. Via the technique of dithering, small pressure fluctuations are detectable even if they are below the resolution of the measuring section. Dithering is a well applied technique in fields like audio and video technology to digitize data and randomize quantization error, preventing large-scale patterns. This paper deals with the capability of dithering to increase the resolution of analog–digital converters and how experimenters in the field of fluid mechanics may benefit from dither. A comprehensive parameter study is presented to point out the potential as well as the limits of this technique. The findings of the parameter study are experimentally validated in the second part of the paper. Finally, an example of a real measuring task is briefly presented, where the method of dithering improves the results.

The selective intensity technique is a powerful tool for the localization of acoustic sources and for the identification of the structural contribution to the acoustic emission. In practice, the selective intensity method is based on simultaneous measurements of acoustic intensity, by means of a couple of matched microphones, and structural vibration of the emitting object. In this paper high spatial density multi-point vibration data, acquired by using a scanning laser Doppler vibrometer, have been used for the first time. Therefore, by applying the selective intensity algorithm, the contribution of a large number of structural sources to the acoustic field radiated by the vibrating object can be estimated. The selective intensity represents the distribution of the acoustic monopole sources on the emitting surface, as if each monopole acted separately from the others. This innovative selective intensity approach can be very helpful when the measurement is performed on large panels in highly reverberating environments, such as aircraft cabins. In this case the separation of the direct acoustic field (radiated by the vibrating panels of the fuselage) and the reverberant one is difficult by traditional techniques. The work shown in this paper is the application of part of the results of the European project CREDO (Cabin Noise Reduction by Experimental and Numerical Design Optimization) carried out within the framework of the EU. Therefore the aim of this paper is to illustrate a real application of the method to the interior acoustic characterization of an Alenia Aeronautica ATR42 ground test facility, Alenia Aeronautica being a partner of the CREDO project.

Banknote security is an issue that has led in the last decades to insert, inside the banknote itself, a very high number of controlling methods with the aim of verifying possible tampering attempts. In order to distinguish the false banknotes, sophisticated means (i.e. watermark, feel of the paper, raised print, metallic threads, quality of the printing, holograms, ultraviolet features, micro-lettering, etc) are often used. The purpose of this paper is to show a new approach and related method to protect banknotes and to verify their originality, based on the idea of hylemetry (methodology conceptually similar to biometry) applied to banknotes. Specifically, the hylemetric feature used in this paper is the random distribution pattern of the metallic security fibers set into the paper pulp. The outcome of the proposed solution is to identify an original banknote using a binary sequence derived from the banknote itself.

This paper reviews possible strategies to increase the operational frequency range of vibration-based micro-generators. Most vibration-based micro-generators are spring-mass-damper systems which generate maximum power when the resonant frequency of the generator matches the frequency of the ambient vibration. Any difference between these two frequencies can result in a significant decrease in generated power. This is a fundamental limitation of resonant vibration generators which restricts their capability in real applications. Possible solutions include the periodic tuning of the resonant frequency of the generator so that it matches the frequency of the ambient vibration at all times or widening the bandwidth of the generator. Periodic tuning can be achieved using mechanical or electrical methods. Bandwidth widening can be achieved using a generator array, a mechanical stopper, non-linear (e.g. magnetic) springs or bi-stable structures. Tuning methods can be classified into intermittent tuning (power is consumed periodically to tune the device) and continuous tuning (the tuning mechanism is continuously powered). This paper presents a comprehensive review of the principles and operating strategies for increasing the operating frequency range of vibration-based micro-generators presented in the literature to date. The advantages and disadvantages of each strategy are evaluated and conclusions are drawn regarding the relevant merits of each approach.

This paper presents a novel calibration algorithm to be used with a gyro-free inertial measurement unit (GF-IMU) based on the use of linear accelerometers (AC). The analytical approach can be implemented in two calibration procedures. The first procedure (P-I) is articulated in the conduction of a static trial, to compute the sensitivity and the direction of the sensing axis of each AC, followed by a dynamic trial, to determine the AC locations. By contrast, the latter procedure (P-II) consists in the calculation of the previously indicated calibration parameters by means of a dynamic trial only. The feasibility of the two calibration procedures has been investigated by testing two GF-IMUs, equipped with ten and six bi-axial linear ACs, with an ad hoc instrumented double-pendulum apparatus. P-I and P-II were compared to a calibration procedure used as a reference (P-REF), which incorporates the AC positions measured with an optoelectronic system. The experimental results we present in this paper demonstrate that (i) P-I is able to determine the calibration parameters of the AC array with a higher accuracy than P-II; (ii) consequently, the errors associated with translational (a0 ? g) and rotational () acceleration components for the two GF-IMUs are significantly greater using P-II than P-I and (iii) the errors in (a0 ? g) and obtained with P-I are comparable with the ones obtainable by using P-REF. Thus, the proposed novel algorithm used in P-I, in conjunction with the double-pendulum apparatus, can be globally considered a viable tool in GF-IMU calibration.

We introduce an image based algorithmic tool for analyzing multi-component shapes here. Due to the generic concept of multi-component shapes, our method can be applied to the analysis of a wide spectrum of applications where real objects are analyzed based on their shapes - i.e. on their corresponded black and white images. The method allocates a number to a shape, herein called a multi-component shapes measure. This number/measure is invariant with respect to affine transformations and is established based on the theoretical frame developed in this paper. In addition, the method is easy to implement and is robust (e.g. with respect to noise). We provide two small but illustrative examples related to aerial image analysis and galaxy image analysis. Also, we provide some synthetic examples for a better understanding of the measure behavior.

The calibration of error coefficients for accelerometers and laser gyros is an effective way to improve the navigation precision of strapdown inertial navigation systems. The calibration parameters often change with temperature. This paper proposes a system-level calibration method including temperature-related error coefficients. The method includes an improved 18-step calibration scheme with temperature being changed by using a thermal chamber. A 42-dimensional Kalman filter is applied to estimate the error parameters including the bias, scale factor errors, installation errors and temperature-related error coefficients of accelerometers. This method has the great advantage of simplifying the calibration procedure and is widely applicable to all temperature-related error coefficients. Compared with the traditional calibration method at different temperature points, the calibration time of the proposed method is shortened by 24 h. The feasibility of this method is verified by simulations and navigation experiments. The results of navigation experiments show that the maximum positioning errors in pure inertial navigation decrease by approximately 30% after temperature compensation.

In order to solve the difficulty of compound fault diagnosis of rolling bearings, a novel rolling bearings fault diagnosis method based on improved tunable Q-factor wavelet transform (TQWT) is proposed in this paper. Firstly, a new evaluation index of signal decomposition called KR is defined by summing kurtosis and root mean square (RMS) with weight. KR is the compromise between impulse factor and energy factor, which can better represent the fault characteristics of sub-bands obtained by TQWT. Secondly, the KR is used to improve the TQWT. The improved TQWT can adaptively determine the parameters Q-factor and decomposition level. Thirdly, the bearing vibration signal is decomposed by the improved TQWT and the sub-bands are sorted descending according to the KR. Finally, the Hilbert envelope analysis is carried out and the fault types are determined by comparing the fault characteristic frequencies obtained from the Hilbert envelopes to the fault characteristic frequencies calculated by formula. The proposed fault diagnosis method is fully evaluated by simulation and experiments. The results demonstrate that the KR takes advantage of kurtosis and RMS and can be better used to optimize the parameter of TQWT. And the compound fault features of rolling bearings can be accurately separated into different sub-bands by the improved TQWT, which is helpful to improve the accuracy of compound fault diagnosis of rolling bearings.

The global navigation satellite systems (GNSS) carrier phase measurements form the basis of high-precision satellite positioning. These measurements are often accompanied by their code counterparts to enable one to compute single-epoch ambiguity-resolved positioning solutions. To avoid unwanted code modelling errors, such as code multipath, one may opt for a phase-only solution and take recourse to carrier phase measurements of two successive epochs. In this paper we study the ambiguity resolution performance of a dual-epoch phase-only model, upon which the unknown positioning parameters are assumed to be completely unlinked in time. With the aid of closed-form analytical results, it is investigated how ambiguity resolution performs when dealing with high-rate phase data. It is thereby shown that multi-GNSS integration makes near real-time centimetre-level phase-only positioning possible. Our analytical analysis is supported by means of numerical results.

Wideband excitation signals are essential in bioimpedance spectroscopy for measurements in a time ensuring a quasi-stable measurement condition. In particular, for wearable biomedical systems, due to limited system resources, several aspects regarding measurement time, crest factor, slew rate requirements, frequency distribution, amplitude spectrum, and energy efficiency need to be thoroughly investigated. In this paper, we present an investigation of excitation signals, which includes not only the theoretical aspects but also aspects of real implementation on microcontroller-based systems. At a fixed number of samples and sampling rate, we investigate the implementability of signal frequencies and the resulting spectral efficiency. We focus on sources of signal distortion due to timer and amplitude deviations. The results show that for 4096 samples and a sampling frequency of 1 MHz, wideband signals are 2.76 times faster than a stepped frequency sweep. The multisine signal provides a better energy efficiency and has a lower slew rate requirement on hardware (around 0.3 V µs−1), but has a relatively high crest factor, even after optimization. An exemplary investigation of the distortion of the time/frequency and amplitudes following implementation on a standard industrial advanced RISC machines microcontroller has shown that a sampling rate compensation is required to overcome timer inaccuracies. Furthermore, non-return-to-zero binary signals are more sensitive to distortion due to hardware-related issues and have a lower signal-to-distortion-and-noise (SINAD) ratio than 24 dB, which is lower than the multisine signal, having a SINAD of 31 dB.

Terrestrial laser scanners (TLSs) are increasingly used in several applications such as reverse engineering, digital reconstruction of historical monuments, geodesy and surveying, deformation monitoring of structures, forensic crime scene preservation, manufacturing and assembly of engineering components, and architectural, engineering, and construction applications. The tolerances required in these tasks range from few tens of millimeters (for example, in historical monument digitization) to few tens of micrometers (for example, in high precision manufacturing and assembly). With numerous TLS instrument manufacturers, each offering multiple models of TLSs with idiosyncratic specifications, it is a considerable challenge for users to compare instruments or evaluate their performance to determine if they meet specifications. As a result, considerable efforts have been made by research groups across the world to model TLS error sources and to develop specialized performance evaluation test procedures. In this paper, we review these efforts including recent work to develop documentary standards for TLS performance evaluation and discuss the role of these test procedures in establishing metrological traceability of TLS measurements.

Phase-shifting profilometry (PSP) has been widely used in structured-light (SL) systems for three-dimensional (3D) shape measurements, but the speed of the PSP technique is limited by increased phase-shifting patterns. This paper proposes an accurate and dynamic 3D shape measurement method by projecting only four patterns, including three-step phase-shifting patterns and one speckle pattern. Three-step phase-shifting images are used to obtain the initial unwrapped phase map with phase ambiguity. Based on the principle of digital image correlation and multi-view geometry, the absolute phase can be recovered reliably without requiring any embedded features or pre-defined information of the object. To improve the measurement accuracy, the projector coordinate is used as the measuring coordinate to establish a novel stereo SL system model. By solving a least square solution using the triple-view information, accurate 3D surface data can be reconstructed. The experimental results indicate that the proposed method can perform high-speed and accurate 3D shape measurements with an accuracy of 10.64 μm, which is superior to conventional methods and has certain instructive significance for 3D profilometry and measurement engineering.

For rotary laser scanning measurement systems, the rotation speed uniformity of the measurement part directly affects the system’s measurement accuracy. To monitor the details of the rotation speed changes within a cycle, this paper proposes a rotation speed uniformity evaluation method for rotary laser scanning measurement systems, which can both detect the rotation speed change within a cycle and obtain the speed change with the angular position. This method is expounded in detail, including the calibration of the rotary encoder gratings, the acquisition of the real-time rotation speed change sequence, and the post-processing of the rotation speed change sequence. The feasibility of the novel processing method is verified by comparison experiments: the novel method is compared with a speed signal processing method based on measuring of rotational periodicity to verify the feasibility. The measurement accuracy of the novel method was analyzed based on the theory of uncertainty propagation. Based on the verification results, the novel method was utilized to evaluate the speed uniformity of the transmitter at different speeds and analyzes the influence of rotation speed uniformity on the angular accuracy of the system, and the experimental results reveal that the novel method is able to detect the fluctuation of the rotation speed within a circle at different speeds, and for the transmitter, the higher working speeds has less relative speed changes and less angle measurement errors.

Fingerprinting localization based on Wi-Fi received signal strength (RSS) is the most widely used indoor localization method. It typically includes offline training and online matching phases. The selection of the RSS characteristic value is a key step. The weighted K nearest neighbor (WKNN) algorithm is the most commonly used position-determination algorithm. The mean value of the RSS data collected over a time interval is usually taken as its characteristic value. However, the RSS measurements contain Gaussian and non-Gaussian noise, which cannot be filtered out effectively by the mean value method. The traditional WKNN algorithm adopts a fixed K . However, reference points far away from the test point (TP) may be selected as the nearest neighbors to participate in the position calculation, which may result in accuracy degradation. This paper proposes the weighted dynamic K nearest neighbor algorithm (WDKNN-HF), which utilizes a hybrid of particle filtering and Kalman filtering to extract the RSS characteristic value. In the online matching phase, a dynamic K matching algorithm based on Euclidean distances is developed to determine the coordinates of TPs. Two experiments are conducted in two different indoor scenes. Experimental results demonstrate that the proposed algorithm can obtain better positioning accuracy than existing algorithms, such as KNN, WKNN, enhanced-WKNN (EWKNN) and self-adaptive weighted K nearest neighbor (SAWKNN).

High-frequency oscillations and high surface aeration, induced by the strong turbulence, make water depth measurement for hydraulic jumps a persistently challenging task. The investigation of the hydraulic jump behaviour persists as an important research theme, especially with regards to the stilling basin design. Reliable knowledge of time-averaged and extreme values along a depth profile can help develop an adequate design of a stilling basin, improve safety and aid the understanding of the jump phenomenon. This paper presents an attempt of mitigating certain limitations of existing depth measurement methods by adopting a non-intrusive computer vision-based approach to measuring water depth profile of a hydraulic jump. The proposed method analyses video data in order to detect the boundary between the air-water mixture and the laboratory flume wall. This is achieved by coupling two computer vision methods: (1) analysis of the vertical image gradients, and (2) general-purpose edge detection using a deep neural network model. While the gradient analysis technique alone can provide adequate results, its performance can be significantly improved in combination with a neural network model which incorporates a "human-like" vision in the algorithm. The model coupling reduces the likelihood of false detections and improves the overall detection accuracy. The proposed method is tested in two experiments with different degrees of jump aeration. Results show that the coupled model can reliably and accurately capture the instantaneous depth profile along the jump, with low sensitivity to image noise and flow aeration. The coupled model presented fewer false detections than the gradient-based model, and offered consistent performance in regions of high, as well as low aeration. The proposed approach allows for automated detection of the free-surface interface and expands the potential of computer vision-based measurement methods in hydraulics.

Nanopositioning and nanomeasuring machines (NPM-machines), developed at Technische Universität Ilmenau, have provided high-precision measurement and positioning of objects across ten decades, from 20 pm resolution up to 200 mm measuring range. They work on the basis of the error-minimal, extended six degrees of freedom Abbe-comparator principle, with high-precision fibre-coupled laser interferometers and optical or atomic force probes. These machines are suitable not only for measuring but also for positioning with an outstanding sub-nanometre performance. Measurements on precision step heights up to 5 mm show a repeatability of 20 pm. Consecutive step positioning of 80 pm can be demonstrated. With the new approach of an atomic clock-stabilized He–Ne-laser via a high-stable-frequency comb, we achieve a frequency stability of less than 300 Hz, respectively 0.6 ċ 10−12 relative frequency stability within 1 h at an integration time of 1 s. For the first time, we can demonstrate a direct, permanent and unbroken chain of traceability between the laser interferometric measurement within an NPM-machine and a GPS satellite-based atomic clock. This paper presents a closer insight into the scientific and metrological background as well as unrivalled measurement results, and discusses the great possibilities of this new technology.

In recent years, there has been growth in the development of high-speed AFMs, which offer the possibility of video rate scanning and long-range scanning over several hundred micrometres. However, until recently these instruments have been lacking full traceable metrology. In this paper traceable metrology, using optical interferometry, has been added to an open-loop contact-mode high-speed AFM to provide traceability both for short-range video rate images and large-area scans made using a combination of a high-speed dual-axis scanner and long-range positioning system. Using optical interferometry to determine stages’ positions and cantilever displacement enables the direct formation of images, obviating the need for complex post-processing corrections to compensate for lateral stage error. The application of metrology increases the spatial accuracy and linearisation of the high-speed AFM measurements, enabling the generation of very large traceable composite images.

Soft metrology has been defined as a set of measurement techniques and models that allow the objective quantification of properties usually determined by human perception such as smell, sound or taste. The development of a soft metrology system requires the measurement of physical parameters and the construction of a model to correlate them with the variables that need to be quantified. This paper presents a review of indirect measurement with the aim of understanding the state of development in this area, as well as the current challenges and opportunities; and proposes to gather all the different designations under the term soft metrology, broadening its definition. For this purpose, the literature on indirect measurement techniques and systems has been reviewed, encompassing recent as well as a few older key documents to present a time line of development and map out application contexts and designations. As machine learning techniques have been extensively used in indirect measurement strategies, this review highlights them, and also makes an effort to describe the state of the art regarding the determination of uncertainty. This study does not delve into developments and applications for human and social sciences, although the proposed definition considers the use that this term has had in these areas.

Particle image velocimetry (PIV) has become the chief experimental technique for velocity field measurements in fluid flows. The technique yields quantitative visualizations of the instantaneous flow patterns, which are typically used to support the development of phenomenological models for complex flows or for validation of numerical simulations. However, due to the complex relationship between measurement errors and experimental parameters, the quantification of the PIV uncertainty is far from being a trivial task and has often relied upon subjective considerations. Recognizing the importance of methodologies for the objective and reliable uncertainty quantification (UQ) of experimental data, several PIV-UQ approaches have been proposed in recent years that aim at the determination of objective uncertainty bounds in PIV measurements. This topical review on PIV uncertainty quantification aims to provide the reader with an overview of error sources in PIV measurements and to inform them of the most up-to-date approaches for PIV uncertainty quantification and propagation. The paper first introduces the general definitions and classifications of measurement errors and uncertainties, following the guidelines of the International Organization for Standards (ISO) and of renowned books on the topic. Details on the main PIV error sources are given, considering the entire measurement chain from timing and synchronization of the data acquisition system, to illumination, mechanical properties of the tracer particles, imaging of those, analysis of the particle motion, data validation and reduction. The focus is on planar PIV experiments for the measurement of two- or three-component velocity fields. Approaches for the quantification of the uncertainty of PIV data are discussed. Those are divided into a-priori UQ approaches, which provide a general figure for the uncertainty of PIV measurements, and a-posteriori UQ approaches, which are data-based and aim at quantifying the uncertainty of specific sets of data. The findings of a-priori PIV-UQ based on theoretical modelling of the measurement chain as well as on numerical or experimental assessments are discussed. The most up-to-date approaches for a-posteriori PIV-UQ are introduced, highlighting their capabilities and limitations. As many PIV experiments aim at determining flow properties derived from the velocity fields (e.g. vorticity, time-average velocity, Reynolds stresses, pressure), the topic of PIV uncertainty propagation is tackled considering the recent investigations based on Taylor series and Monte Carlo methods. Finally, the uncertainty quantification of 3D velocity measurements by volumetric approaches (tomographic PIV and Lagrangian particle tracking) is discussed.

Adaptive sampling strategies in PIV have been shown to efficiently combine the need for limited user-dependence with increased performances in terms of spatial resolution and computational effort, thus rendering such approaches of great interest. The allocation of correlation windows across the spatial image domain is dependent on the interpretation of an underlying objective function, and the distribution of windows accordingly. It is important that such allocation is computationally efficient, robust to changing objective functions and conditions, and conducive to high quality sampling. In this paper, an alternative sample distribution method, based on adaptive incremental stippling, is presented and shown to combine the speed of PDF-based methods with the quality of ‘ideal’ spring-force methods. Case-dependent parameter tuning is no longer necessary, thus improving robustness. In addition, an algorithm to adaptively size initial correlation windows is proposed to further minimise user dependence.

This study presents a new strategy of retrieving displacement fields from two different images or two video frames obtained at different times using an iterative optical flow method. First, illumination modeling and image preprocessing are required before the displacement calculations can be performed. Due to the displacement continuity assumption, the displacement differences between the neighboring points are small. Then, the initial displacements of the unprocessed points are determined by the displacements of the processed neighboring points. Next, an iterative optical flow method is performed with a small window size to obtain the displacement offsets between the matching point pairs. The calculation is performed at the subpixel level in each iteration, and thus image interpolation is necessary. In this paper, image upsampling of the deformed image is applied using bi-cubic spline interpolation to achieve the subpixel intensity before all the calculations. This improvement avoids the requirement for image interpolation to be in all iterations. Several numerical tests and real image datasets were used to validate the performance of the proposed method. The results were compared with those obtained by a traditional digital image correlation method using the traditional forward additive Newton–Raphson algorithm and the iterative least square algorithm. Both tests showed that the proposed algorithm exhibits excellent performance regarding computational accuracy and speed.

This work demonstrates how the interaction between particle image velocimetry (PIV) and robotics can massively increase measurement efficiency. The interdisciplinary approach is shown using the complex example of an automated, large scale, industrial environment: a typical automotive wind tunnel application. Both the high degree of flexibility in choosing the measurement region and the complete automation of stereo PIV measurements are presented. The setup consists of a combination of three robots, individually used as a 6D traversing unit for the laser illumination system as well as for each of the two cameras. Synchronised movements in the same reference frame are realised through a master-slave setup with a single interface to the user. By integrating the interface into the standard wind tunnel management system, a single measurement plane or a predefined sequence of several planes can be requested through a single trigger event, providing the resulting vector fields within minutes. In this paper, a brief overview on the demands of large scale industrial PIV and the existing solutions is given. Afterwards, the concept of RoboPIV is introduced as a new approach. In a first step, the usability of a selection of commercially available robot arms is analysed. The challenges of pose uncertainty and importance of absolute accuracy are demonstrated through comparative measurements, explaining the individual pros and cons of the analysed systems. Subsequently, the advantage of integrating RoboPIV directly into the existing wind tunnel management system is shown on basis of a typical measurement sequence. In a final step, a practical measurement procedure, including post-processing, is given by using real data and results. Ultimately, the benefits of high automation are demonstrated, leading to a drastic reduction in necessary measurement time compared to non-automated systems, thus massively increasing the efficiency of PIV measurements.

Electrical impedance tomography (EIT) is an imaging method that could become a valuable tool in multimodal applications. One challenge in simultaneous multimodal imaging is that typically the EIT electrodes cover a large portion of the object surface. This paper investigates the feasibility of rotational EIT (rEIT) in applications where electrodes cover only a limited angle of the surface of the object. In the studied rEIT, the object is rotated a full 360◦ during a set of measurements to increase the information content of the data. We call this approach Limited Angle Full Revolution rEIT (LAFR-rEIT). We test LAFR-rEIT setups in two-dimensional geometries with computational and experimental data. We use up to 256 rotational measurement positions, which requires a new way to solve the forward and inverse problem of rEIT. For this, we provide a modification, available for EIDORS, in the supplementary material. The computational results demonstrate that LAFR-rEIT with eight electrodes produce the same image quality as conventional 16-electrode rEIT, when data from an adequate number of rotational measurement positions are used. Both computational and experimental results indicate that the novel LAFR-rEIT provides good EIT with setups with limited surface coverage and a small number of electrodes. publishedVersion

We describe an efficient algorithm that computes a segmented reconstruction directly from x-ray projection data. Our algorithm uses a parametric curve to define the segmentation. Unlike similar approaches which are based on level-sets, our method avoids a pixel or voxel grid; hence the number of unknowns is reduced to the set of points that define the curve, and attenuation coefficients of the segments. Our current implementation uses a simple closed curve and is capable of separating one object from the background. However, our basic algorithm can be applied to an arbitrary topology and multiple objects corresponding to different attenuation coefficients in the reconstruction. Through systematic tests we demonstrate a high robustness to the noise, and an excellent performance under a small number of projections.

This paper is concerned with the development of a new system identification based approach for pulsed eddy current non-destructive evaluation. The new approach regards the relationship between the eddy current probe excitation and sensor response as a system, uses the system identification techniques to establish a transfer function model for the system from the excitation and response data, and extracts the features of inspected structures from the identified transfer function model parameters for non-destructive evaluations. The use of the new approach in experimental studies verifies its effectiveness and demonstrates its potential in engineering applications.

Permittivity monitoring for quality control in fluid-related industrial applications requires difficult procedures and the process control frequently limits the use of traditional sensing technologies. In this paper is reported a combined approach, based on time-domain reflectometry (TDR) and frequency-domain analysis, in order to appropriately improve the measurement of the frequency-dependent dielectric characteristics over a wide range of fluid materials, even when lossy liquids are involved. For this purpose, we have developed a robust algorithm for the time-to-frequency-domain dielectric characterization that suitably compensates the error contribution caused by several effects such as signal dissipation, multiple reflections, impedance mismatching, time-domain truncation and data fitting procedure. In order to assess the combined approach in the time and frequency domain, experimental measurements have been made with both a TDR and vector network analyser (VNA), using the same probe system. Results obtained through the use of such an algorithm on TDR data have been compared with those directly measured in the frequency domain by the VNA, and good agreement has been observed. Substantial improvements are attained in accuracy, high sensitivity and flexibility of the detection method and, most importantly, in the possibility of using low-cost instrumentation directly operating in the time domain.

For several years road vehicle autonomous cruise control (ACC) systems as well as anti-collision radar have been developed. Several manufacturers currently sell this equipment. The current generation of ACC sensors only track the first preceding vehicle to deduce its speed and position. These data are then used to compute, manage and optimize a safety distance between vehicles, thus providing some assistance to car drivers. However, in real conditions, to elaborate and update a real time driving solution, car drivers use information about speed and position of preceding and following vehicles. This information is essentially perceived using the driver's eyes, binocular stereoscopic vision performed through the windscreens and rear-view mirrors. Furthermore, within a line of vehicles, the frontal road perception of the first vehicle is very particular and highly significant. Currently, all these available data remain strictly on-board the vehicle that has captured the perception information and performed these measurements. To get the maximum effectiveness of all these approaches, we propose that this information be shared in real time with the following vehicles, within the convoy. On the basis of these considerations, this paper technically explores a cost-effective solution to extend the basic ACC sensor function in order to simultaneously provide a vehicle-to-vehicle radio link. This millimetre wave radio link transmits relevant broadband perception data (video, localization...) to following vehicles, along the line of vehicles. The propagation path between the vehicles uses essentially grazing angles of incidence of signals over the road surface including millimetre wave paths beneath the cars.

In this paper a polarimetric fibre-optics current sensor in a new highly versatile all-fibre configuration is described. The optical configuration is particularly simple and is based on a back-and-forth propagation through a twisted sensing fibre. This results in a very flexible sensing cable which can be adapted to a great number of existing power installations, by simply winding the fibre around the uninterrupted electrical conductor. The prototype presented here is designed to measure ac and dc currents with an excellent accuracy over more than three decades. © 2004 IOP Publishing Ltd.

A force sensor, for use with an artificial hand, needs to be small, robust, low power, cheap and easily interfaced to a controller using digital techniques. The prototype featured in this paper uses capacitance effects to measure the strain on an elastic polymer foam. Low power consumption results in a device that can be supplied from a miniature battery thereby requiring only signal wires to the controller. A non-linear model accurately describes the characteristic of the sensor, requiring the estimation of only three parameters. The device has been tested up to 20 N but is capable of measuring greater forces.

The work described in the present paper will deal with the mathematical and empirical analysis of the properties of different ways of performing the reduction of data gathered through a complex measurement instrument; the specific case of a probe for the time-resolved measurement of skin friction absolute value and direction will be studied in order to deduce a general conclusion about the matter. It will be shown that different mathematical formulations of the data reduction variables and/or functions can cause important differences in the results, especially when the features of the instrument to be used must be pushed to their limit. Comparison will be performed between various techniques of data reduction in order to highlight their respective properties; these results will be interpreted in relation to the physical nature and properties of the example instrument, showing the underlying factors leading to these properties and the way this understanding can lead to better applications of an instrument.

Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup.

Pavement markings provide an important foundation as they help to keep roads users safe. Accurate and comprehensive information about pavement markings assists the road regulators and is useful in developing driverless technology. Mobile light detection and ranging (LiDAR) systems offer new opportunities to collect and process accurate pavement markings' information. Mobile LiDAR systems can directly obtain the three-dimensional (3D) coordinates of an object, thus defining spatial data and the intensity of (3D) objects in a fast and efficient way. The RGB attribute information of data points can be obtained based on the panoramic camera in the system. In this paper, we present a novel method process to automatically extract pavement markings using multiple attribute information of the laser scanning point cloud from the mobile LiDAR data. This method process utilizes a differential grayscale of RGB color, laser pulse reflection intensity, and the differential intensity to identify and extract pavement markings. We utilized point cloud density to remove the noise and used morphological operations to eliminate the errors. In the application, we tested our method process on different sections of roads in Beijing, China, and Buffalo, NY, USA. The results indicated that both correctness (p) and completeness (r) were higher than 90%. The method process of this research can be applied to extract pavement markings from huge point cloud data produced by mobile LiDAR.

This paper scrutinises the general suitability of image mapping for particle image velocimetry (PIV) applications. Image mapping can improve PIV measurement accuracy by eliminating overlap between the PIV interrogation windows and an interface, as illustrated by some examples in the literature. Image mapping transforms the PIV images using a curvilinear interface-fitted mesh prior to performing the PIV cross correlation. However, degrading effects due to particle image deformation and the Jacobian transformation inherent in the mapping along curvilinear grid lines have never been deeply investigated. Here, the implementation of image mapping from mesh generation to image resampling is presented in detail, and related error sources are analysed. Systematic comparison with standard PIV approaches shows that image mapping is effective only in a very limited set of flow conditions and geometries, and depends strongly on a-priori knowledge of the boundary shape and streamlines. In particular, with strongly curved geometries or streamlines that are not parallel to the interface, the image-mapping approach is easily outperformed by more traditional image analysis methodologies invoking suitable spatial relocation of the obtained displacement vector.

This paper reports on an in-depth analysis of ISO 5436 part 2 type F2 reference software for the calculation of profile surface texture parameters that has been performed on the input, implementation and output results of the reference software developed by the National Physical Laboratory (NPL), the National Institute of Standards and Technology (NIST) and Physikalisch-Technische Bundesanstalt (PTB). Surface texture parameters have been calculated for a selection of 17 test data files obtained from the type F1 reference data sets on offer from NPL and NIST. The surface texture parameter calculation results show some disagreements between the software methods of the National Metrology Institutes. These disagreements have been investigated further, and some potential explanations are given.