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The article focuses on the application of participation-focused therapy in children with cerebral palsy for improvement in physical activity goal performance, satisfaction, and confidence.

Abstract During the last two decades, accelerometers on board of the CHAMP, GRACE, GOCE and Swarm satellites have provided high-resolution thermosphere density data to improve our knowledge on atmospheric dynamics and coupling processes in the thermosphere-ionosphere region. Most users of the data have focused on relative density variations. Scale differences between datasets and models have been largely neglected or removed using ad hoc scale factors. The origin of these scale differences arises from errors in the aerodynamic modelling, specifically in the modelling of the satellite outer surface geometry and of the gas-surface interactions. Therefore, the first step to remove the scale differences is to enhance the geometry modelling. This work forms the foundation for the future improvement of characterization of satellite aerodynamics and gas-surface interactions models at TU Delft, as well as for extending the use of sideways and angular accelerations in the aerodynamic analysis of accelerations and derivation of thermosphere datasets. Although work to improve geometry and aerodynamic force models by other authors has focused on CHAMP and GRACE, this paper includes the GOCE and Swarm satellites as well. In addition, it uses a density determination algorithm that is valid for arbitrary attitude orientations, enabling a validation making use of attitude manoeuvres. The results show an improvement in the consistency of density data between these four missions, and of data obtained before, during and after attitude manoeuvres of CHAMP and Swarm. The new models result in larger densities, compared to the previously used panel method. The largest average rescaling of density, by switching to the new geometry models is reached for Swarm at 32%, the smallest for GRACE at 5%. For CHAMP and GOCE, mean differences of 11% and 9% are obtained respectively. In this paper, an overview of the improvements and comparisons of data sets is provided together with an introduction to the next research phase on the gas-surface interactions. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The paper presents the applied method for indirect surface finishing measurement in aerospace manufacturing industry. • This paper introduces a method to quantify and correlate the deburring stage with the features extracted from sensors data. • This study covers signal processing, feature extraction and analytical method for surface finish quality estimation in deburring processes. • Wavelet decomposition and Welch spectrum estimate are used as a signal processing and feature extraction method. • The features are used as the basis for classification analysis by adaptive neuro-fuzzy inference system (ANFIS). Abstract Manufacturing of aerospace components consists of combination of different types of machining, finishing, and measuring processes. One of the finishing processes is deburring, i.e. a finishing process to remove burrs from work coupons after a boring hole process. Deburring is conducted to achieve required surface finish quality prior to further processes in assembly line. This paper introduces sensor data analysis as a tool to quantify and correlate the deburring stage with the features extracted from sensors data. This study covers signal processing, feature extraction and analytical method to determine its relevancy to the surface finish quality from deburring process. Wavelet decomposition and Welch's spectrum estimate is used as a signal processing and feature extraction method. Consequently, the features are used as the basis for analysis by adaptive neuro-fuzzy inference system (ANFIS). The ANFIS yields the output corresponding to the predicted surface finish quality in terms of boss hole chamfer length and the stage classification of deburring process. The results show a decreasing trend in measured vibration signal, which is qualitatively well correlated to the deburring stage and the development of chamfer length during deburring process. [ABSTRACT FROM AUTHOR]

GRACE and GRACE-FO require the reduction of non-gravitational accelerations, through an onboard accelerometer, to accurately estimate variations in the Earth's gravitational field. Accuracy in the accelerometer measurements is vital to this mass change recovery and significant errors will reduce the quality of the recovered science data. This paper describes our current characterization of error sources in the GRACE-FO accelerometers and the error mitigation strategies used in the generation of the JPL/CSR GRACE-FO Version 04 accelerometer data for public release. Our current error characterization model describes flicker noise on readings of one accelerometer plate pair on GRACE-D, impulse response limitations on both accelerometers, nonphysical once per revolution variations in the roll angular acceleration measurements on both accelerometers, significant correlated errors on all axes on GRACE-D, nominal thermal bias dependencies on both accelerometers, and expected nominal inter-measurement aliasing (cross-talk - expected as heritage from GRACE). Attitude reconstruction strategies incorporating star camera, inertial measurement unit, and magnetorquer measurements visibly improve angular acceleration recovery independent of the accelerometer. Error mitigation strategies for the linear acceleration measurements, associated with the calibrated accelerometer product provided in the version 04 release, dramatically improve estimates of the Earth's gravity field. While many of the error characterizations described here are not necessary for constructing the accelerometer transplant from GRACE-C to GRACE-D, as is currently done in the Version 04 release, the error characterizations described here lay the groundwork for future use of calibrated/corrected GRACE-D accelerometer data. [ABSTRACT FROM AUTHOR]

The paper presents the analysis of the influence of the method of accelerometers attachment to the ground on the recorded level of vibration acceleration. Measurements of vibrations were conducted using two types of accelerometers with various weights and measuring accuracy. Accelerometers were mounted to the ground in four different methods using various mounting bases anchored in the ground with one, three and four rods. The vibrations were generated using Light Falling Weight Deflectometer (LFWD) and recorded in longitudinal, transversal and vertical directions at the distance of 5 and 10 m from the source of vibrations. Measurements of vibration accelerations were carried out using 32-channel and 24-bit mobile data acquisition system - SIEMENS LMS SCADAS Recorder, as well as a set of 18 low-frequency, seismic piezoelectric accelerometers type 8340, manufactured by Brüel&Kjær, and two triaxial, high sensitivity accelerometers type TLD356B18 manufactured by PCB Piezotronics. The comparative analysis of Peak Particle Accelerations (PPA) has demonstrated that the method of attaching of accelerometers to the ground is crucial for the credibility of measurements. The best way of attaching transducers to the ground was shown in the paper. The resulting values of vibration acceleration may constitute a basis for a reliable analysis of vibration in the subsoil, which is particularly important in terms of the credibility of assessment of the impact of physical pollution in a form of vibrations propagated in the environment on the newly designed buildings and their future users. [ABSTRACT FROM AUTHOR]

In this paper we highlight a clustering algorithm for the purpose of identifying sleep and wake periods directly from actigraphy signals. The paper makes use of statistical Principal Component Analysis to identify periods of rest and activity. The aim of the proposed methodology is to develop a quick and efficient method to determine the sleep duration of an individual. In addition, a robust method that can identify sleep periods in the accelerometer data when duration, time of day varies by individual. A selected group of 10 individual’s sensor data consisting of actigraphy from an accelerometer (3-axis), near body temperature, and lux sensors from a single GENEActiv watch worn on the non-dominant hand. The actigraphy of each individual was collected 24 hours a day for a period spanning 80 days. We highlight that a simple data preprocessing stage followed with a 2 phase clustering method provides results that align with previously validated methodologies. [ABSTRACT FROM AUTHOR]

Pipe leak location estimates are commonly conducted using Vibro-Acoustic Emission (VAE) based methods, usually using accelerometers or hydrophones. Successful estimation of a leak's location is dependent on a number of factors, including the speed of sound, resonance, backfill, reflections from other sources, leak shape and size. However, despite some investigation into some of the aforementioned factors, the influence of backfill type on a leak's VAE signal has still not been experimentally quantified. A limited number of studies have attempted to quantify the effects of backfill. However, all of these studies couple other variables which could be equally responsible for their observed changes in leak signal. There have been no controlled studies where one variable can be directly compared to one another (i.e. all variables remain constant, only changing backfill type). The aim of this paper is to better characterise the influence of backfill on a leak's VAE signal by individually isolating all variables. For the first time, this paper demonstrates the influence of backfill on leak VAE signal by keeping all other variables consistent. It was found that the backfill type had a strong influence on the frequency and amplitude of leak signals, which is likely to have a significant impact on the accuracy of leak location estimates. [ABSTRACT FROM AUTHOR]

There exist numerous navigation solutions already implemented into various navigation systems. Depending on the vehicle in which the navigation system is used, it can be distinguished in most cases among; navigation, tactical, and commercial grade categories of such systems. The core of these systems is formed by inertial sensors, i.e. accelerometers and angular rate sensors/gyros. Navigation and tactical grade systems commonly rely on fiber optic/ring laser gyros and servo/quartz accelerometers with high resolution, sensitivity, and stability. In the case of cost-effective navigation systems, for example piloted light and ultralight aircraft, usually use commercial grade sensors, where the situation differs. The sensor outputs are less stable and sensitive, and suffer from manufacturing limits leading to temperature dependency, bias instability, and misalignment which introduces non-negligible disturbances. These conditions commonly limit the applicability of the navigation solution since its stand-alone operation using free integration of accelerations and angular rates is not stable. This paper addresses a cost-effective solution with commercial grade inertial sensors, and studies the performance of different approaches to obtain navigation solution with robustness to GNSS outages. A main goal of this paper is thus comparison of a nonlinear observer and two extended Kalman filter solutions with respect to the accuracy of estimated quantities and their sensitivity to GNSS outages. The performance analyses are carried out on real flight data and evaluated during phases of the flight when the solutions are challenged by different environmental disturbances. [ABSTRACT FROM AUTHOR]

The paper deals with the results of an experimental campaign carried out on a post tensioned concrete beam with the aim of investigating the possibility to detect early warning signs of deterioration based on static and/or dynamic tests. The beam was tested in several configurations aimed to reproduce 5 different phases of the ‘life’ of the beam: in the original undamaged state, under increasing loss of tension in the post tensioning cables, during and after the formation of cracks at mid span, after a strengthening intervention carried out by means of a second tension cable, during and after the formation of further cracks on the strengthened beam. Responses of the beam were measured by an extensive set of instruments consisting of accelerometers, inclinometers, displacement transducers, strain gauges and optical fibers. In this paper data from accelerometers and displacement transducers have been exploited. The paper presents the test program and the dynamic characterization of the beam in the different damage scenarios in terms of the first modal frequency, identified from dynamic tests and of the bending stiffness monitored during static tests. [ABSTRACT FROM AUTHOR]

Monitoring and analyzing floor vibrations to determine human activity has major applications in fields such as health care and security. For example, structural vibrations could be used to determine if an elderly person living independently falls, or if a room is occupied or empty. Monitoring human activity using floor vibration promises to have advantages over other methods. For example, it does not have the privacy concerns of other methods such as vision-based techniques, or the compliance challenges of wearable sensors. The analysis of the signals becomes a classification problem determining the type of human activity. Unfortunately only a few research groups are performing research of this subject even though there is a significant number of techniques that could be applied to this field. To date, no systematic study about the challenges and advantages of using different types of algorithms for this problem has been performed. This paper proposes a benchmark problem to: (i) encourage researchers to design new algorithms for monitoring human activity using floor vibrations, (ii) provide a dataset to test new algorithms, and (iii) allow the comparison of proposed methods based on a set of standard metrics. The benchmark consists of seven different cases of increasing difficulty. Each case has a specific number of sensors, calibration signals, and type of floor excitation forces to be considered. The paper also proposes specific metrics that enable the direct comparison of different techniques. Research groups interested in monitoring human activity using floor vibrations are encouraged to use the experimental data and evaluation metrics published in this paper to develop their own methodologies. This will enable the community of researchers to easily compare and contrasts techniques and better understand what type of methods will be appropriate in different applications. [ABSTRACT FROM AUTHOR]

Nowadays, the amount of elder people living alone is increasing, with all the risks that it involves, maybe the most dangerous threat that they face is fall off with nobody around to help them. A fall at an advanced age usually leads to consequences like bones and hip fracture, which in addition to the low mobility that these people present, make to stand up impossible for them. This situation can get worse if after the fall a person loses consciousness, making it impossible to contact to a third party for help by means of a mobile phone or something similar. Different solutions have been developed in order to accomplish this problem, but some of them are not realistic enough, for example some video solutions invade our privacy, and those which are based on mobile phones expect the user to go everywhere with it. In this paper, it is proposed a low cost solution based on an 9-axis IMU (Inertial Measure Unit), which counts with an accelerometer, gyroscope and magnetometer that will give us the needed information to build a fall detector supported by machine learning. This system will include a gateway, which will be responsible of the data collection and the most complex computations. [ABSTRACT FROM AUTHOR]

A redundant inertial measurement unit (IMU) is an inertial sensing device composed by more than three accelerometers and three gyroscopes. This paper analyzes the performance of redundant IMUs and their various sensors configurations. The inertial instruments can achieve high reliability for long periods of time only by redundancy. By suitable geometric configurations it is possible to extract the maximum amount of reliability and accuracy from a given number of redundant single-degree-of-freedom gyros or accelerometers. This paper gives general derivation of the optimum matrix which can be applied to the outputs of any combination of 3 or more sensors to obtain 3 orthogonal vector components based on their geometric configuration and error characteristics. Certain combinations of 4 or more instruments have the capability of detecting an instrument malfunction, those of 5 additional capabilities of isolating that malfunction to a particular sensor. [ABSTRACT FROM AUTHOR]

• We will monitor compliance with the intervention and adverse events. • Data will be analyzed following intention-to-treat principles. • A cost-effectiveness analysis will be performed. This a priori statistical analysis plan describes the methods of analysis for the Trial Of Prevention Strategies for low back pain (TOPS). TOPS aimed to investigate the effectiveness and cost-effectiveness of exercise and education classes compared with a minimal intervention control in preventing recurrence of low back pain (LBP) in people who have recently recovered from an episode of LBP. TOPS is a superiority, pragmatic, parallel-group randomized controlled trial with allocation concealment, blinded outcome assessors, and intention-to-treat analysis. Participants were randomized to a physical therapist-led exercise and education program for 12 weeks or minimal intervention. The primary outcome was days to recurrence of an episode of LBP. The three key secondary outcomes were days to recurrence of an episode of LBP resulting in (1) activity limitation, (2) care seeking for LBP; and (3) work absence of at least 1 day. Differences in survival curves for the primary (days to recurrence) and secondary outcome (days to LBP with activity limitation, days to care seeking due to LBP, and days to work absence due to LBP) will be compared using Cox regression. Hazard ratios (HRs) and median survival times with 95% confidence intervals (CI) will be calculated. The number of adverse events, including serious adverse events will be reported and the proportion of adverse events between groups will be compared using a Chi-squared test. This paper will provide a detailed description of the planned analyses for the TOPS trial. Australian New Zealand Clinical Trials Registry (ACTRN12615000939594). [ABSTRACT FROM AUTHOR]

Locomotion scoring is time consuming and is not commonly completed on farms. Farmers also underestimate their herds' lameness prevalence, a knowledge gap that impedes lameness management. Automation of lameness detection could address this knowledge gap and facilitate improved lameness management. The literature pertinent to adding lameness detection to accelerometers is reviewed in this paper. Options for lameness detection systems are examined including the choice of sensor, raw data collected, variables extracted, and statistical classification methods used. Two categories of variables derived from accelerometer-based systems are examined. These categories are behavior measures such as lying and measures of gait. For example, one measure of gait is the time a leg is swinging during a gait cycle. Some behavior-focused studies have reported accuracy levels of greater than 80%. Cow gait measures have been investigated to a lesser extent than behavior. However, classification accuracies as high as 91% using gait measures have been reported with hardware likely to be practical for commercial farms. The need for even higher accuracy and potential barriers to adoption are discussed. Significant progress is still required to realize a system with sufficient specificity and sensitivity. Lameness detection systems using 1 accelerometer per cow and a resolution lower than 100 Hz with gait measurement functions are suggested to balance cost and data requirements. However, gait measurement using accelerometers is rather underdeveloped. Therefore, a high priority should be given to the development of novel gait measures and testing their ability to differentiate lame from nonlame cows. [ABSTRACT FROM AUTHOR]

Critical strain is the strain level corresponding to the very first micro-crack in a composite layer. Current detection methods for such micro-cracks are limited to strain gage measurements, digital image correlation techniques or the Bergen ellipse [9]. With the Bergen ellipse a well-defined but non-linearly increasing strain can be applied to a strip of composite material to induce micro-cracks. In this paper a combined approach is described to measure the critical strain at which the first micro-crack occurs. The combined approach consists of 2 elements. First the Euler-Fresnel spiral is introduced as an elegant alternative to the Bergen ellipse to introduce a well-defined and linearly increasing strain to a strip of composite material secondly, since micro-cracks, caused by exceeding the critical strain values, are difficult to detect, multiple accelerometers on the composite strip are used to detect the micro-cracks by measuring the acoustic emission of the crack initiations. By measuring the time of arrival of the acoustic emission waves at the two ends of the strip, the positions of the micro-crack initiations can be determined. Using the geometrically defined relationship between strain and position on the Euler-Fresnel spiral, the strain-levels at crack initiations can be estimated. An important advantage of the approach described in this paper is that all micro-cracks are detected instantaneously during the measurement procedure. This includes the subsurface cracks that cannot be detected by the penetrant method. In this paper the proposed measuring method for critical strain in composites was successfully demonstrated. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Nocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure detection with the standard method of video electroencephalography monitoring. The goal of this paper is to propose a method for hypermotor seizure detection based on accelerometers that are attached to the extremities. Methods: Supervised methods that are commonly used in literature need annotation of data and hence require expert (neurologist) interaction resulting in a substantial cost. In this paper an unsupervised method is proposed that uses extreme value statistics and seizure detection based on a model of normal behavior that is estimated using all recorded and unlabeled data. In this way the expensive interaction can be avoided. Results: When applying this method to a labeled dataset, acquired from 7 patients, all hypermotor seizures are detected in 5 of the 7 patients with an average positive predictive value (PPV) of 53%. For evaluating the performance on an unlabeled dataset, seizure events are presented to the system as normal movement events. Since hypermotor seizures are rare compared to normal movements, the very few abnormal events have a negligible effect on the quality of the model. In this way, it was possible to evaluate the system for 3 of the 7 patients when 3% of the training set was composed of seizure events. This resulted in sensitivity scores of 80%, 22% and 90% and a PPV of 89%, 21% and 44% respectively. These scores are comparable with a state-of-the-art supervised machine learning based approach which requires a labeled dataset. Conclusions: A person-dependent epileptic seizure detection method has been designed that requires little human interaction. In contrast to traditional machine learning approaches, the imbalance of the dataset does not cause substantial difficulties. [Copyright &y& Elsevier]

Abstract: This paper presents the design of the GNC system of a ground test-bed for spacecraft rendezvous and docking experiments. The test-bed is developed within the STEPS project (Systems and Technologies for Space Exploration). The facility consists of a flat floor and two scaled vehicles, one active chaser and one “semi-active” target. Rendezvous and docking maneuvers are performed floating on the plane with pierced plates as lifting systems. The system is designed to work both with inertial and non-inertial reference frame, receiving signals from navigation sensors as: accelerometers, gyroscopes, laser meter, radio finder and video camera, and combining them with a digital filter. A Proportional-Integrative-Derivative control law and Pulse Width Modulators are used to command the cold gas thrusters of the chaser, and to follow an assigned trajectory with its specified velocity profile. The design and development of the guidance, navigation and control system and its architecture—including the software algorithms—are detailed in the paper, presenting a performance analysis based on a simulated environment. A complete description of the integrated subsystems is also presented. [Copyright &y& Elsevier]

Abstract: Touch screens as a mean for interacting with mobile applications are limited. Since the hands are already busy handling the phone or tablet, this paper proposes an innovative solution in handling digital entities with the feet. A three-axis accelerometer is arranged on a shoe in order to recognize its movement and to determine its position. Extraction of both information improves mobile interaction in different situations, especially in gaming and working in limited space. The contribution of this paper is an algorithm designed in order to extract both feet tracking (pose) and movement recognition such as kicking, sliding and rotating. [Copyright &y& Elsevier]

Abstract: Assisted living systems can help support elderly persons with their daily activities in order to help them maintain healthy and safety while living independently. However, most current systems are ineffective in actual situation, difficult to use and have a low acceptance rate. There is a need for an assisted living solution to become intelligent and also practical issues such as user acceptance and usability need to be resolved in order to truly assist elderly people. Small, inexpensive and low-powered consumption sensors are now available which can be used in assisted living applications to provide sensitive and responsive services based on users current environments and situations. This paper aims to address the issue of how to develop an activity recognition method for a practical assisted living system in term of user acceptance, privacy (non-visual) and cost. The paper proposes an activity recognition and classification method for detection of Activities of Daily Livings (ADLs) of an elderly person using small, low-cost, non-intrusive non-stigmatize wrist worn sensors. Experimental results demonstrate that the proposed method can achieve a high classification rate (>90%). Statistical tests are employed to support this high classification rate of the proposed method. Also, we prove that by combining data from temperature sensor and/or altimeter with accelerometer, classification accuracy can be improved. [Copyright &y& Elsevier]

Abstract: The dynamic response of clamped sandwich beam with aluminium alloy open-cell foam core subjected to impact loading is investigated in the paper. The face sheet and the core of the sandwich beam have the different thickness. And the sandwich beam is impacted by a steel projectile in the mid-span. The impact force is recorded by using accelerometer. The results show that tensile crack and core shear are the dominant failure modes. And the impact velocity and the thickness of the face sheet and the foam core have a significant influence on the failure modes and the impact forces. Combining with the inertia effect and experimental results, the failure mechanisms of the sandwich beams are discussed. The thickness of the foam core plays an important role in the failure mechanism of the sandwich beam. In present paper, the failure of the sandwich beam with a thin core is dominated by the bending moment, while the sandwich beam with a thick core fails by bending deformation in the front face sheet and the bottom face sheet in opposite direction due to the plastic hinges in the front face sheet. [Copyright &y& Elsevier]

Abstract: The goal of this paper is to use accelerometers as an early detection of restenosis. Restenosis (re-narrowing of the blood vessel) typically occurs within 3-6 months after the implantation of a stent. Finite element modelling of an occluded blood vessel showed that eddies along with an increase in velocity occur around the occlusion. In this paper a wireless accelerometer device was used to detect an occlusion. A human phantom model was used to mimic the wireless transmission capabilities of the system through human muscle ex-vivo. Fast Fourier transform results from the accelerometer showed that a non-occluded blood vessel had significant peaks >15Hz, whereas an occluded blood vessel had peaks <15Hz, which provides a signature template for detecting restenosis. The results of the FEM and human phantom experiments show that an accelerometer sensor is capable of detecting restenosis. [Copyright &y& Elsevier]

In the last few months of GRACE (Gravity Recovery and Climate Experiment) mission operation, the accelerometer (ACC) aboard GRACE-B was turned off due to battery problems. In order to compute a gravity field model for these months, a data processing strategy was developed to retrieve the missing information, the so called Accelerometer data transplant. The ACC data transplant uses linear accelerations as measured by the GRACE-A accelerometer to generate the missing GRACE-B ACC data. A simple method of ACC data transplant was presented by Save et al. (2006), which only applies attitude and time correction due to orbit separation. In this paper we present an improved method of the ACC data transplant, which also includes thruster spike correction. The thruster spikes are residual linear accelerations occurring at each thruster firing caused by thruster imperfections and misbalance. We provide detailed description of the thruster spike model, which was derived analytically based on the ACC transfer function and 10 Hz ACC data. Using the transplanted ACC data we computed the gravity field models for the months with missing GRACE-B ACC data (November 2016–June 2017). We show that the gravity field model based on in the improved ACC data transplant has significantly reduced noise, especially for degrees beyond the first orbital resonance, when compared to the simple transplant method. The improved ACC transplant became therefore a part of the processing standards for the upcoming JPL RL06 gravity solution. [ABSTRACT FROM AUTHOR]

Abstract The state-of-the-art electrostatic accelerometers (EA) used for the retrieval of non-gravitational forces acting on a satellite constitute a core component of every dedicated gravity field mission. However, due to their difficult-to-control thermal drift in the low observation frequencies, they are also one of the most limiting factors of the achievable performance of gravity recovery. Recently, a hybrid accelerometer consisting of a regular EA and a novel cold atom interferometer (CAI) that features a time-invariant observation stability and constantly recalibrates the EA has been developed in order to remedy this major drawback. In this paper we aim to assess the value of the hybrid accelerometer for gravity field retrieval in the context of GRACE-type and Bender-type missions by means of numerical closed-loop simulations where possible noise specifications of the novel instrument are considered and different components of the Earth's gravity field signal are added subsequently. It is shown that the quality of the gravity field solutions is mainly dependent on the CAI's measurement accuracy. While a low CAI performance (10−8 to 10−9 m/s2/Hz1/2) does not lead to any gains compared to a stand-alone EA, a sufficiently high one (10−11 m/s2/Hz1/2) may improve the retrieval performance by over one order of magnitude. We also show that improvements which are limited to low-frequency observations may even propagate into high spherical harmonic degrees. Further, the accelerometer performance seems to play a less prominent role if the overall observation geometry is improved as it is the case for a Bender-type mission. The impact of the accelerometer measurements diminishes further when temporal variations of the gravity field are introduced, pointing out the need for proper de-aliasing techniques. An additional study reveals that the hybrid accelerometer is – contrary to a stand-alone EA – widely unaffected by scale factor instabilities. [ABSTRACT FROM AUTHOR]

Abstract Optical fiber sensors (OFSs) are nowadays widely adopted in many different fields and applications. Cavitation in pipeline systems is one of the main concerns of engineers because of its serious consequences for the lifetime of pipelines and on the performance of hydraulic devices. Among other useful parameters the incipient cavitation index is one of the most important because it represents the very beginning of the phenomenon. The present paper discusses the possibility of using optical fiber technology to detect cavitation in a pipeline. The experimental system exploits an interferometric fiber optical sensor based on a coherent demodulation scheme, avoiding the need for working point stabilization systems and coping with the polarization fading. Several dispositions and geometries for the sensors have been tested to select the most efficient solution. The results are then compared with cavitation indexes calculated following the standard procedure, using accelerometer measurements, to prove the optical fiber sensors' effectiveness. Highlights • Cavitation is a harmful phenomenon. • Incipient cavitation index is the engineering quantity that expresses cavitation inception condition. • Three types of fiber optic sensors are used to detect cavitation. • Fiber optic sensors results are compared to that obtained by accelerometer measurements. [ABSTRACT FROM AUTHOR]

Abstract Quantitative fractography (QF) may be used for measuring service- and test-induced fatigue crack growth (FCG) in metallic components and structures. The QF compares progression and striation markings on fatigue fracture surfaces with known occurrences in the components' load histories. This paper concisely surveys fatigue-related QF, followed by a case study for a crack in a component from a maritime patrol aircraft. The case study illustrates how a FCG versus time history can be estimated. This was achieved using (i) knowledge of when the crack was detected, (ii) a reconstruction of the aircraft usage history from counting accelerometer (g-meter) data, (iii) an exponential FCG model of how cracking could have progressed, and (iv) QF of progression markings. Comparison of the reconstructed usage data and the QF information showed that the model provided a useful correlation. Highlights • Quantitative fractography can be a powerful post-failure forensics tool; • A step-by-step description of the analyses of a in-service aircraft crack is provide; • The example included the reconstruction of the service load history. [ABSTRACT FROM AUTHOR]

Highlights • A simple technique to estimate modal properties of a laboratory concrete girder using a single accelerometer is presented. • A numerical model considering shear deformations as well as elastic supports is introduced. • Natural vibration frequencies up to the 13th mode were observed and accurately explained by the numerical model. • Natural mode shapes up to the 6th mode were accurately captured, except for the 2nd mode. • The effect of service-level cracking on modal properties was clearly observed in the higher modes. Abstract A number of nondestructive evaluation (NDE) methods are available to detect cracks and damage in reinforced concrete structures. Methods such as ultrasonic, impact echo, or X-ray testing have high resolution but are time consuming to perform and therefore only used locally. Since the early 1970s, researchers have also studied the modal properties of structures for damage detection and identification. In this paper, we discuss the effects of elastic supports and flexural cracking on the dynamic response of a large-scale laboratory reinforced concrete girder. For this purpose, an instrumented hammer used for impulse response testing was employed to initiate vibrations and to subsequently estimate the natural frequencies and modes of a large-scale laboratory concrete girder. Natural frequencies up to the 13th mode were successfully extracted from the frequency response function (FRF). In addition, the mode shapes were extracted up to the 6th mode due to the limitation of the linearity of the FRF response. These modal properties were determined from the measured accelerations of two points on the girder using a roving hammer. The test procedure was performed on the uncracked beam and repeated after the beam had been cracked. The experimental measurements were verified with a finite element (FE) model consisting of one-dimensional beam elements that consider both flexural and shear deformations. Support flexibility was modeled as linear-elastic springs, and was found critical in order to explain experimentally-obtained measurements. The effects of cracking were found to be most obvious in the higher modes. Additionally, utilizing the modal flexibility method on the first mode (natural vibration frequency and mode shape) was an accurate predictor of flexural crack locations. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes an algorithm that uses conventional measurements found on-board ships coupled with additional Inertial Measurement Units to estimate the motions and global loads acting on them. The work is motivated by the scarce availability of full-scale load data for sea-ice operations and by the invasive instrumentation of strain gauges used to obtain global loads of all degrees of freedom. Full-scale data are key to a number of design, operational, and research aspects related to sea-ice operations. The proposed algorithm is based on four Inertial Measurement Units (IMUs) that together with position and heading measurements are used to make estimates of dynamic linear and rotational acceleration (acceleration resulting in motion). We show how to use models updated with propulsion and wind measurements to estimate propulsion, hydrodynamic, wind, and ice loads through a setup catering to real-time implementation. A case study with the Swedish icebreaker Oden is presented and discussed. The algorithm effectively yields reasonable ice load history estimations and presents great potential in its further application to real-time global ice load estimations. Highlights • A novel algorithm based on four Inertial Motion Units (IMUs) non-invasively installed on a floating structure • Estimation of the structure's motion in real-time based on IMUs' measurements the UKF algorithm • Global ice resistance calculated in real-time with known ship motion [ABSTRACT FROM AUTHOR]

Highlights • Field: Arm gesture recognition based on motion sensors. • Algorithm: deepGesture, a new arm gesture recognition method based on gyroscope and accelerometer sensors using deep neural networks. • Implementation: Wrist-type smart band device and deep learning framework. • Applications: Smart TV based entertainment platform. Abstract Recent advancement in smart phones and sensor technology has promoted research in gesture recognition. This has made designing of efficient gesture interface easy. However, human activity recognition (HAR) through gestures is not trivial since each person may pose the same gesture differently. In this paper, we propose deepGesture algorithm, a new arm gesture recognition method based on gyroscope and accelerometer sensors using deep convolution and recurrent neural networks. This method uses four deep convolution layers to automate feature learning in raw sensor data. The features of the convolution layers are used as input of the gated recurrent unit (GRU) which is based on the state-of-the-art recurrent neural network (RNN) structure to capture long-term dependency and model sequential data. The input data of the proposed algorithm is obtained through motion sequence data extracted using a wrist-type smart band device equipped with gyroscope and accelerometer sensors. The data is initially segmented in fixed length segments. The segmented data is labeled and we construct the database. Then the labeled data is used in our learning algorithm. To verify the applicability of the algorithm, several experiments have been performed to measure the accuracy of gesture classification. Compared to the human activity recognition method, our experimental results show that the proposed deepGesture algorithm can increase the average F1-score for recognition of nine defined arm gestures by 6%. [ABSTRACT FROM AUTHOR]

Abstract High-accuracy and reliable autonomous navigation is increasingly crucial for automated transfer vehicles (ATV). This paper proposes a novel strapdown inertial navigation system/celestial navigation system (SINS/CNS) tight integration scheme aided by dynamic model constraints for high-orbit ATV to realize accurate and autonomous navigation. In this scheme, the complete weightlessness constraint in orbit is used to address the divergence of position and velocity caused by inaccurate accelerometer bias estimation problem encountered in the traditional SINS/CNS integration method, and the image point position-based tight integration model is derived to handle the adverse influence of time-varying attitude measurement noise due to changes of star geometry observed by a large-view-filed star sensor. Moreover, an information filter is devised to fuse the multi-rate measurements. The proposed algorithm is evaluated by a representative high-orbit ATV trajectory simulation, which indicates significant improvements in navigation accuracy compared with its traditional counterparts. The proposed algorithm can realize navigation accuracy enhancements without introducing additional sensors, strengthening its potentials in engineering application. Highlights • Accelerometer-bias and star geometry undermine traditional SINS/CNS integration. • Accurate bias estimation can be achieved using the complete weightlessness in orbit. • Changing star geometry can be tackled using image-point-based tight model. • The proposed algorithm improves SINS/CNS navigation accuracy remarkably. [ABSTRACT FROM AUTHOR]

Abstract: This paper first gives an overview of the applications of micro-electro-mechanical systems (MEMS) in space. Microsystems are advertised for their extremely low size and mass, along with their low power consumption and in some case their improved performances. Examples of actual flown MEMS and future missions relying on MEMS are given. Microsystems are now enjoying a dynamic and expanding interest in the space community. This paper intends to give an idea about the next step in miniaturization, since the microelectronic industry is already looking at nano-electro-mechanical systems (NEMS) driven by the more-than-Moore philosophy. We show that the impact of nanosystems should not be reduced at a homothecy in size, weight and power consumption. New forces appear at this scale (Casimir force…) which have to be considered in the system design. The example of a nano-mechanical memory is developed. We also show that performances of nanosystems are not systematically better than their microscopic counterparts through the study of the impact of dimension reduction on an accelerometer resolution and sensitivity. We conclude with the idea that nanosystems will find their greatest applications in distributed intelligent networks that will allow new mission concepts for space exploration. [Copyright &y& Elsevier]

Most modern smartphones have a variety of built-in sensors, as an accelerometer, gyroscope, GPS, proximity and a magnetic sensor. The large variety of sensors makes these devices powerful measurement tools, allowing the emergence of new systems and applications. In this paper, is presented a real data stream application related to asphalt pavement evaluation using acceleration data gathered by the accelerometer sensor of smartphones. The quality of the pavement has a significant influence on the final price of goods and services, the safety of drivers, pedestrians and passengers, and driver’s comfort. Thus, it is essential the use of tools, as proposed in this work, that allows the constant monitoring of pavement conditions by the Government authorities or private entities for more precise interventions in the maintenance planning with fewer expenses. This task is mainly important in developing countries where there is a lack of technology and a reduced budget for maintenance. Due to the popularity of smartphones, this tool can make possible that different users help to monitor the pavement quality ubiquitously during driving periods without effort. The application of asphalt evaluation is modeled in this work as a multi-dimensional time series classification problem, where the time series are the data from the three-axis accelerometer sensor. Given the characteristics of the data, we discuss and propose the combination of some classical distance measure for time series as Dynamic Time Warping or Longest Common Subsequence Similarity with the Complexity Invariant Distance. A comprehensive experimental evaluation was performed on three datasets that represent different scenarios of asphalt pavement classification. The proposed approach reaches a classification accuracy of 80% to 98% in the three evaluated problems and we experimentally show that the complexity invariance substantially improves the results achieved by classical distance measures given our classification tasks. [ABSTRACT FROM AUTHOR]

The modeling of torques acting on satellites is essential for the design of satellite attitude control systems. The GOCE satellite, equipped with accurate accelerometers, star trackers and GPS receivers, presents an opportunity to validate these models. Although the forces on GOCE and other accelerometer-carrying missions have been extensively analyzed in the past, a similar analysis has so far not yet been made for the torques. In this paper, we present a set of torque models for the GOCE satellite. It consists of six main parts: (1) magnetic torquer actuators, (2) aerodynamic torque, (3) gravity gradient torque, (4) solar radiation pressure torque, (5) thruster torque, and (6) passive magnetic torque. The magnetic properties of the payload are approximated using a parametrization, of which the parameters are estimated from the observation data. Based on data recorded during selected spacecraft events, the model for the control torques can be validated and error sources are identified in the other models. The models perform best in roll and pitch, where the standard deviation is reduced to 15.2% and 2.1% of the standard deviation of the control torque around those axes respectively. In yaw the standard deviation is significantly larger at 30.5%. The remaining differences between models and observations show magnetic signatures due to electric currents and signatures of aerodynamic model errors. The latter correspond well with an increase in thermosphere density and wind speed with increased geomagnetic activity. The pitch torque is found to be a potential source of vertical wind data. [ABSTRACT FROM AUTHOR]

The dynamic effects and other related to material conveying processes phenomena have a major impact to the surrounding environment leading to material depreciation or even industrial disasters. The paper describes a new approach to analysis of gravitational solid flow. It becomes as an extension to the measurement data analysis in a manner of the frequency transform (STFT) application for ECT data processing. During experiment, each tomogram was split into five areas called rings and processed separately to obtain more precise information. Additionally, in order to test a correlation between material behaviour in silo and its impact to the container walls the juxtaposition with accelerometers data was used. The experiment results show similarity in time domain between two sensors' responses. [ABSTRACT FROM AUTHOR]

Monitoring systems for the measurement of ice action and the observation of attendant ice conditions have been in place on several piers of the Confederation Bridge since it opened in 1997. The ice-structure interaction at two of the piers, P31 and P32 have been continuously monitored and data analyzed by the ice research group at the University of Calgary. The resulting database of ice interactions at these piers is very extensive, amounting to some 26,000 discrete interaction events, many of which have been analyzed in detail. The paper presents summaries of the results of the observations related to the interaction of the ice against the instrumented piers and summarizes the ice load and ice parameter statistics associated with the ice observations. [ABSTRACT FROM AUTHOR]

Dynamic performance measurement of buildings using conventional contact sensors such as accelerometers, tilt meters and Global Positioning System (GPS) can be difficult due to accessibility restrictions, particularly during construction or retrofitting periods. This is one of the first studies using a non-contact microwave interferometry radar based system for dynamic measurement of high rise buildings. This paper presents results of a combined experimental and analytical approach to investigate modal properties of two high rise buildings in Australia. Dynamic properties of the buildings, namely Soul building and Zen Apartments, were investigated. The choices of the buildings were based on the different physical properties and plan layouts of the buildings. To capture the dynamic characteristics of the buildings, field measurements were carried out using an interferometric radar based equipment and compared with results from more conventional contact-sensors such as accelerometers and GPS. The building vibration test results were then correlated with the buildings’ respective finite element modelling (FEM) simulations to test the capability of the radar in capturing mode shapes of the buildings. Finite elements software ETABS was used for this purpose. Results show that interferometric radar system has the potential as a non-contact instrument to be effectively used to measure the dynamic properties including mode shapes of high rise buildings. [ABSTRACT FROM AUTHOR]

Ballistic projectiles accuracy depends on measurement systems for position and attitude determination. Precise rotation determination is an expensive task in aircraft, as it is usually determined by strap-down sensors such as fiber optic gyros or MEMS. Particularly in ballistic projectiles, these gyro determination devices increase their price as they need to bear enormous accelerations during the initial stages but not during the ballistic flight. A new approach to improve ballistic projectile navigation, guidance and control, which integrates hybrid attitude determination methods and gravity vector estimation method, is presented in this paper. Measurements of accelerometers, GNSS-sensors and Semi-Active photo-detectors are hybridized to get such a result. The attitude determination method, avoiding the use of gyroscopes, measures pairs of vectors, i.e., gravity, velocity and line of sight vectors, in a pair of reference systems, i.e., body fixed and north–east–down reference frames. Gravity vector estimation is based on flight mechanics and aerodynamics of a ballistic projectile, which involves a deeply nonlinear behavior, but it may be extrapolated to any aircraft, and later employed in an attitude determination algorithm. Modified proportional navigation techniques and previously developed control methods are employed during flight. The presented approach is tested on a realistic nonlinear model flight simulations to prove accuracy of proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes a novel optimization-based design methodology that can be used for mixed-domain synthesis of MEMS accelerometers. Several problems have been identified with existing methodologies and comparative experiments that demonstrate the superiority of the proposed approach are performed. Highly accurate analytical models of the MEMS accelerometer have been used for the evaluation of the MEMS sensor performances in the mixed-domain optimization. The circuit level simulations, on the other hand, are based on an electrical simulator, e.g., Hspice. The implemented methodology has been tested on the optimization of a MEMS accelerometer that includes a capacitive MEMS sensor and an analog read-out circuitry. [ABSTRACT FROM AUTHOR]

This paper presents the design of an experimental setup with a reduced number of sensors for the structural health monitoring of the historical bridge of Posadas (Córdoba, Spain), designed by the eminent engineer Eduardo Torroja in 1957. The motivation of this study stems from the need for safeguarding this piece of cultural heritage. In particular, the singularity of this historical construction, a steel–concrete composite typology consisting of a concrete deck slab and inverted bowstring steel trusses, makes continuous in-service condition assessment essential for its maintenance. Nevertheless, the application of existing continuous monitoring systems to such large-scale structures entails considerable investments as well as complex signal processing algorithms. Whereby the optimization of the number of sensors and their location is of the utmost interest. In this line, this work presents the application of an Optimal Sensor Placement (OSP) methodology to tailor an experimental setup for a cost-efficient continuous monitoring of the E. Torroja’s bridge. Due to the fact that most OSP approaches are model-based, it is essential to count on a sufficiently accurate numerical model. To this aim, an extensive vibration-based operational modal analysis is first conducted with a large number of accelerometers. Afterward, a three-dimensional finite element model of the E. Torroja’s bridge is updated on the basis of the experimentally identified dynamic properties with a genetic optimization algorithm. Finally, an optimal sensor placement methodology is utilized to design an experimental setup with a limited number of sensors for long-term monitoring purposes. The results demonstrate that few sensors are needed to accurately assess the main resonant frequencies and mode shapes. [ABSTRACT FROM AUTHOR]

This paper considers the problem of constructing a filter for estimating attitude and rate-sensor bias, that has both proven stability and close-to-optimal performance with respect to noise. The filter is based on measuring the difference in time of arrival for signals sent from three or more known, fixed positions to two or more receivers on the vehicle. An inertial measurement unit is also used, both rate-sensor and accelerometer measurements, and a position estimate is needed, generated from depth and time of arrival measurements. The vectors between receivers on the vehicle are assumed to be known in the body frame, and are calculated in the inertial frame through an algebraic transformation. These vectors are used as input for a non-linear observer along with rate-sensor and accelerometer data, estimating Euler angles and rate-sensor bias. These estimates are used as a linearization point for a Linearized Kalman Filter, taking the full non-linear system into account. Two experiments are run, and the filter is compared to an Extended Kalman Filter, and a non-implementable Linearized Kalman Filter using the true state as linearization point. [ABSTRACT FROM AUTHOR]

Wearable thermoelectric generators (TEGs) enable the conversion of human body heat into microwatts to milliwatt electricity, which can be utilized to power miniaturized electronic devices for motion detection and healthcare monitoring. This paper presents a novel wearable TEG with 52 pairs of cubic-shaped thermoelectric legs to harvest human body heat. The thermoelectric legs are made of P-type and N-type Bi 2 Te 3 -based powder materials, and are connected electrically in series through soldering. The flexible printed circuit board (FPCB) with special holes is designed and used as substrate to enhance the flexibility of the TEG for wearable applications. The performances of the TEG, including the bulk thermoelectric legs, are characterized. The results show that the TEG can generate an open-circuit voltage of 37.2 mV at Δ T  = 50 K, and the internal resistance of the TEG is quite low at a value of 1.8 Ω. Then the TEG was worn on a human wrist to harvest body heat and power a 3-axis miniaturized accelerometer for detection of body motion at Δ T  = 18 K. The results demonstrate that the developed wearable TEG features high output performance and could be utilized for powering electronics and/or sensors by harvesting human body heat. [ABSTRACT FROM AUTHOR]

The paper considers the processing technique for amplitude-frequency response of turning and boring CNC machine units. The technique developed by V.A. Kudinov is proposed as the basic one. The essence of the technique is that the use of the experimental or calculated frequency characteristics makes it possible to determine the values of the constants characterizing natural frequency of vibration, decrement factor, unit stiffness, or weight of the technological system elements. The logarithmic decrement is calculated from the resonance peak breadth by applying the formula of the vibration theory for the system with one-degree-of-freedom vibrations. The force of impulse action on the system units is determined by experiment based on measurements by accelerometer built in an impact hammer. The theoretical amplitude-response curve is plotted for the vibration displacement of the units and the logarithmic decrement is calculated in MathCAD. [ABSTRACT FROM AUTHOR]

In 2011 a first vibration monitoring system was installed on a single Belgian offshore wind turbine to research the possibility to monitor the structural integrity of the wind turbines substructure using accelerometers. From 2011 to 2017 four more wind turbines have been equipped with a similar setup. A combined total of 15 years of vibration measurements on all five turbines has been collected. In this contribution we will focus how vibration measurements using accelerometers can be used to support operators in decisions on the structural health of their assets. In the first part of this contribution the vibration behavior of a (offshore) wind turbine will be discussed using measurements obtained from the five monitored turbines. It will be shown how wind conditions, such as wind speed and turbulence, have an effect on the vibration levels of the turbine. In addition the interaction between loads and the tower dynamics will be investigated. In the second part the focus will be put on the automated operational modal analysis (OMA) that is applied to the measured accelerations. From this automated OMA a large dataset of resonance frequencies and damping values was obtained. The paper will discuss how results from monitoring the resonance frequencies can be used to detect bottom-erosion (i.e. scour) and potentially can be used to monitor the condition of the rotor. [ABSTRACT FROM AUTHOR]

Vibration testing of long span bridges is becoming a commissioning requirement. Long span bridges represent the extreme end of experimental capability, with challenges for logistics and access (due to length and location), instrumentation (due to frequency range, resolution and physical separation of accelerometers) and system identification (because of the extreme low frequencies). Similar challenges apply to other extreme structures such as tall buildings, masts, offshore lighthouses and extended geotechnical structures stretching technology requirements for both instrumentation and signal interpretation. A solution for instrumentation is autonomous ‘wireless’ recorders. The problem with signal interpretation is the reliability of the modal parameter estimates that is particularly challenged with low frequency modes, which ‘third generation’ operational modal analysis procedures offer using Bayesian approaches. The paper describes a preliminary exercise combining both these technologies in readiness for testing two very large bridges, one in China and one in Scotland. [ABSTRACT FROM AUTHOR]

Excessive vibration problems related to building floors concerning the human comfort have been reported by several researchers in the past two decades. The reason for those vibrations is mainly related with the current trend for the design of slender and flexible structural systems, with the inherent low damping. Consequently, such floors are prone to resonant motion which may reach high vibration levels once their natural frequencies lie in the same range of the human induced forces. In this sense, the human activities, such as walking, jumping or bouncing have been described in some design guides by pure forces acting on the structure. This assumption has conducted to a more or less conservative structural design depending on the chosen loading model function. Recent studies have demonstrated that the use of biodynamics models in order to represent the human behaviour may lead to a more realistic, reasonable and economical design, as they take into account the human body dynamic properties. This paper aims at evaluating the body dynamic parameters by means of a force plate and an accelerometer mounted on the human body when a rhythmic activity (jumping) is developed. This way, experimental tests are carried out both on a rigid surface and on a vibrating floor so that the mass, spring and damping of the identified human biodynamic model can be obtained through an optimisation method. [ABSTRACT FROM AUTHOR]

This paper investigates and describes the potential of mobile devices for vibration analysis, system identification and structural monitoring using a self-developed app, called “iDynamics”. It shows the differences between professional accelerometers and smartphone sensors, demonstrates the vibration measurement and evaluation capabilities using “iDynamics" and presents the application of the app using various practical examples. The application has been verified by results from vibration measurements with professional equipment and software. At the end, the application limits of the app and the requirements of the corresponding mobile devices are summarized. [ABSTRACT FROM AUTHOR]

The Baixo Sabor hydroelectric power plant, located in the northeast of Portugal, includes a reservoir with a storage capacity of 630 million m 3 of water created by a concrete double-curvature arch dam, 123 m high, which was equipped with a 20-channel vibration based structural health monitoring system. This paper, apart from describing the dam, presents the main characteristics of the monitoring system and the results obtained during the first 6 months of operation and the first filling of the reservoir. These results include in particular the characterization of the accelerations amplitude and the evolution of the dam modal parameters (natural frequencies, modal damping ratios and mode shapes). It is particular interesting to observe the influence of the water level on the modal parameters and the development of statistical models to mitigate this effect. [ABSTRACT FROM AUTHOR]

This paper presents a method that uses machine learning to detect and localize damage in railway bridges. Results of the method application to a historical bridge are presented and used to validate the proposed algorithm. For the application of this technique, both air temperature and deck accelerations data, measured under railway traffic at several locations on the bridge, are needed. The method consists of four stages: (1) collection of such data in both reference condition (i.e. when the state of preservation of the structure is known) and current one; (2) pre-processing of acceleration time histories aimed at extracting characteristics of the crossing train (i.e. running direction, speed and number of axles); (3) training of Artificial Neural Networks and Gaussian Processes using data collected in reference condition and (4) health classification of the bridge in current condition through the comparison between predicted and measured responses. During stage 3, a set of neural networks is trained to predict deck accelerations under every environmental and operational condition (i.e. air temperature and crossing vehicle characteristics, respectively) assuming the reference state of preservation. Then, in stage 4, the current response is compared with accelerations predicted under current environmental and operational conditions. Changes in the behavior of the structure due to damage are thus detected as a discrepancy between predicted and measured responses. The application of the proposed technique to data collected on San Michele Bridge (1889), in Northern Italy, has shown good agreement with results from previous studies based on mode shape variation. This shows the potential and confirms the possibility of applying the proposed technique to real bridges. This method can thus be used to detect anomalous responses that can be flagged as possible damage as well as give an indication of the location of the decayed structural region. [ABSTRACT FROM AUTHOR]

For the automotive industry, the quantification of vibratory forces is a key challenge to improve acoustic comfort. We present in this papers an original method allowing to find the optimal positioning of a set of accelerometers on a test bench and the regularisation of the inverse problem taking into account uncertainties, for the experimental reconstruction by inverse method of the blocked forces at the interface between two mechanical structures. The optimization of the sensors location is done by minimizing the mean coherence coefficient (MCC) of the rows of the matrix of transfer functions (TF). The regularization of the inverse problem is done by modal analysis and modal smoothing of the transferts functions. Finally, we use the Polynomial Chaos to take intou account uncertainties on the transfer functions and on the solution of the inverse problem. These method have been tested on a industrial test bench and validated by comparison to the direct method measurements.. [ABSTRACT FROM AUTHOR]

This paper describes an analytical approach for compensating accelerometer-based (contact-type) modal testing results for both mass loading and cable energy dissipation (damping). The inverse Receptance Coupling Substructure Analysis (RCSA) approach is implemented, where a lumped parameter model of the accelerometer-cable is decoupled from the measured receptance (or frequency response function) to isolate the structure's receptance. Experimental results are presented for a 12.7 mm diameter cantilever rod, a 6.35 mm diameter cantilever rod, and clamped-clamped-clamped-free boundary condition thin ribs. [ABSTRACT FROM AUTHOR]

The Tohoku earthquake of magnitude 9.0 occurred on March 11, 2011. As a result, the need for Structural Health Monitoring (SHM) was highlighted. To assess the health of buildings, modal parameters such as natural frequencies and damping ratios are the basic and important damage indicators. In addition, maximum inter-story drift angle is also recognized as an important indicator. If we have to estimate these indicators very precisely, we need to install accelerometers on all floors. However, it is not realistic due to the cost. In many methods to estimate the response using small number of accelerometers, the excitation (input) is assumed to be available. However, in some cases, some sensors including the input sensor may not be available. Thus, in this paper, we propose the methods for the estimating inter-story drift angle using small number of accelerometers without knowing input information. [ABSTRACT FROM AUTHOR]