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Real-time systems are the canonical class of applications in signal processing. They drive the development of algorithms for approaching theoretical results within demanding practical constraints, and provide opportunities for devising clever ways to take advantage of hardware capabilities. State-of-the-art contributions are presented on three topics in this field.The first contribution is the hardware, firmware, and software co-design of a wearable hearing aids research system. The system is open-source, easy to develop for, and much more powerful than traditional hearing aids. Its audio performance matches that of standard hearing aids and it can run custom DSP algorithms in usermode with only 2.4 ms of latency. The system also includes local web-based user control and wearable electrophysiology.The second contribution describes using GPU "Tensor Core" matrix multiply hardware to accelerate the computation of discrete Fourier transforms of sizes which are prime or have large prime factors. This includes mapping these sizes to the power-of-2-size Tensor Cores and emulating higher-precision arithmetic with lower-precision floating point numbers. For large batch sizes and for certain transform sizes which are odd or an odd number times 2 or 4, this approach produced state-of-the-art Fourier transform throughput.Finally, two papers on algorithms design in real-time acoustic modeling for an audio spatialization system are presented. Two perceptually relevant types of diffraction are simulated with ray-based models of sound propagation. Existing methods have accuracy or performance limitations, especially in dynamic applications. A set of algorithms called Volumetric Diffraction and Transmission (VDaT) is introduced to approximate shadowed or near-shadowed diffraction by an occluding object. Similarly, Spatially Sampled Near-Reflective Diffraction (SSNRD) handles near-reflective diffraction involving the edges of reflecting objects. Both methods use ray tracing to spatially sample the scene, approximate ground truth results to within 1-3 dB,and have fast performance suitable for real-time applications. SSNRD also incorporates path generation algorithms, uses a small deep neural network (DNN) to compute the response of each acoustical path, and applies the GPU "RT core" real-time ray tracing hardware to spatial computing tasks beyond traditional ray tracing.

Vibration measurement is a crucial task in industrial systems, where vibration characteristics reflect health conditions and indicate anomalies of the devices. Previous approaches either work in an intrusive manner or fail to capture the micrometer-level vibrations. In this work, we propose mmVib, a practical approach to measure micrometer-level vibrations with mmWave radar. First, we derive a metric called Vibration Signal-to-Noise Ratio (VSNR) that highlights the directions of reducing measurement errors of tiny vibrations. Then, we introduce the design of mmVib based on the concept of Multi-Signal Consolidation (MSC) for the error reduction and multi-object measurement. We implement a prototype of mmVib, and the experiments show that it achieves 3.946% relative amplitude error and 0.02487% relative frequency error in median. Typically, the average amplitude error is only 3.174um when measuring the 100um-amplitude vibration at around 5 meters. Compared to two existing mmWave-based approaches, mmVib reduces the 80th-percentile amplitude error by 69.21% and 97.99% respectively.

The detection of minerals (mines) or rocks would have been extremely difficult without the expansion of the Sound Navigation Ranging methodology, which uses specific parameters to determine if a barrier or a surface is a mine or rock. Hence, this proposed work is concerned with the progression of distinctive among metal cylinder which is named as mines and cylindrical shape material which is named as rocks using deep learning based algorithms. Moreover, this work introduced novel technique as Rock or mine Detection Neural Network for performing rock/mine prediction and classification in underwater acoustics. The proposed RDNN method outperforms the outcomes by attaining high accuracy as 92.85% mean accuracy that makes better model performance.

This research paper is proposed to cater the design requirements of phased array antenna with side lobes pertaining for radio frequency (RF) wireless domain applications. As wireless communications have become an inevitable part of our lives as-on- date, designing smaller and lighter mobile terminals is one of the critical requirements for the development of wireless systems. A single antenna gives only a small directivity, whereas in terms of increased directivity an antenna array can be a possible candidate. Considerable optimization methods for synthesizing array pattern have started to emerge thereby achieving a pattern of desired one related to the application we work in. The major factor which drives the far field structure in phased array antenna with an allowable side lobe level is the power distribution among the array of elements. This paper presents a novel method for side lobe level (SLL) suppression in amplitude tapered planar array structure and it is compared with different distribution methods relating to array coefficients with prime focus on Taylor, Chebyshev and Gaussian distributions. CST Microwave Studio software is used to simulate various distributions and it is compared with characteristics such as gain, directivity, beam width and side lobe level suppression.

Summary Laryngeal images obtained via high-speed videoendoscopy are an invaluable source of information for the advancement of voice science because they can capture the true cycle-to-cycle vibratory characteristics of the vocal folds in addition to the transient behaviors of the phonatory mechanism, such as onset, offset, and breaks. This information is obtained through relating the spatial and temporal features from acquired images using objective measurements or subjective assessments. While these images are calibrated temporally, a great challenge is the lack of spatial calibration. Recently, a laser-projection system allowing for spatial calibration was developed. However, various sources of optical distortions deviate the images from reflecting the reality. The main purpose of this study was to evaluate the effect of the fiberoptic flexible endoscope distortions on the calibration of images acquired by the laser-projection system. Specifically, it is shown that two sources of nonlinear distortions could deviate captured images from reality. The first distortion stems from the wide-angle lens used in flexible endoscopes. It is shown that endoscopic images have a significantly higher spatial resolution in the center of the field of view than in its periphery. The difference between the two could lead to as high as 26.4% error in calibrated horizontal measurements. The second distortion stems from variation in the imaging angle. It is shown that the disparity between spatial resolution in the center and periphery of endoscopic images increases as the imaging angle deviates from the perpendicular position. Furthermore, it is shown that when the imaging angle varies, the symmetry of the distortion is also affected significantly. The combined distortions could lead to calibrated horizontal measurement errors as high as 65.7%. The implications of the findings on objective measurements and subjective visual assessments are discussed. These findings can contribute to the refinement of the methods for clinical assessment of voice disorders. Considering that the studied phenomena are due to optical principles, the findings of this study, especially those related to the effects of the imaging angle, can provide further insights regarding other endoscopic instruments (eg, distal-chip and rigid endoscopes) and procedures (eg, gastroendoscopy and colonoscopy).

International audience; This paper uses the recent glottal flow model for iterative adaptive inverse filtering to analyze recordings from dysfunctional speakers, namely those with larynx-related impairment such as laryngectomy. The analytical model allows extraction of the voice source spectrum, described by a compact set of parameters. This single model is used to visualize and better understand speech production characteristics across impaired and nonimpaired voices. The analysis reveals some discriminative aspects of the source model which map to a physiological class description of those impairments. Furthermore, being based on analysis of source parameters only, it is complementary to any existing techniques of vocal-tract or phonetic analysis. The results indicate the potential for future automated speech reconstruction systems that adapt to the method of reconstruction required, as well as being useful for mainstream speech systems, such as ASR, in which front-end analysis can direct back-end models to suit characteristics of impaired speech.

The standard 1.2/50 lightning impulse test has been important for factory testing equipment and evaluating their performance in electrical systems. In practice, however, such equipment is subject to non-standard waveform (NSW) of high frequencies, which may not be covered by standard tests. To overcome this difficulty, the present article outlines a method that simulates NSW in laboratory tests. Based on multi-resolution wavelet analysis, the method considers the correlation between amplitude and entropy in the decomposition levels between waveforms. To that end, changes are proposed to the following parameters of standard impulse tests: amplitude, cut-off instant, and front time. The results show that, mostly, the combination of a lightning impulse waveform (LIW) with impulse waves cut at different times, sufficiently represent the NSW. Only when the NSWs density falls predominantly in a frequency range above 3.125 MHz, will there be need for a complementary LIW with a steep front time. The methods application allows manufacturers and concessionaires to subject the equipment to conditions that properly represent the NSW effects, through lightning impulse tests carried out at the factory.

In this paper, a novel optical rotary sensor based on laser self-mixing interferometry is developed for the full-circle rotation measurement. The proposed sensor is convenient to use for it does not need any contact with the target or a cooperative mirror. A prototype is fabricated and tested. The measured results demonstrate a good performance compared with other optical rotary sensors, in terms of the 0.1 μrad resolution, the 2.33×10-4 linearity and 2 μrad stability over one hour. Additionally, the repeatability error is below 14.66 mrad under 9-group full-circle tests, which exhibits the potential to be instrumentalized reliably. Error analysis and limitation discussion have been also carried out. Although the accuracy needs further improvement compared with the best rotary sensor, this method has its unique advantages of high resolution, non-cooperative target sensing and electromagnetic immunity. Hence, the proposed optical rotary sensor provides a promising alternative in precise rotation measurement, tremor tracing and nano-motion monitoring.In this paper, a novel optical rotary sensor based on laser self-mixing interferometry is developed for the full-circle rotation measurement. The proposed sensor is convenient to use for it does not need any contact with the target or a cooperative mirror. A prototype is fabricated and tested. The measured results demonstrate a good performance compared with other optical rotary sensors, in terms of the 0.1 μrad resolution, the 2.33×10-4 linearity and 2 μrad stability over one hour. Additionally, the repeatability error is below 14.66 mrad under 9-group full-circle tests, which exhibits the potential to be instrumentalized reliably. Error analysis and limitation discussion have been also carried out. Although the accuracy needs further improvement compared with the best rotary sensor, this method has its unique advantages of high resolution, non-cooperative target sensing and electromagnetic immunity. Hence, the proposed optical rotary sensor provides a promising alternative in precise rotation measurement, tremor tracing and nano-motion monitoring.

Three-dimensional (3D) profile scanning plays a crucial role in the inspection of assembled large aircraft. In this paper, to achieve noncontact automatic measurements of the high-reflective profiles of large-scale curved parts and components, an automated noncontact system and method with high accuracy and high efficiency are presented. First, a hybrid 3D coordinate measurement system based on proximity sensors and cameras is proposed to obtain noncontact measurements while avoiding the influence of high reflection on the measurement accuracy. A hybrid measurement model that combines the one-dimensional distances measured by the proximity sensors and the 3D information obtained by cameras is proposed to determine high-accuracy 3D coordinates of the measured points. Then, a profile-driven 3D automated scanning method and strategy are designed to rapidly scan and reconstruct the profile within the effective range without scratching the profile or exceeding the measurement range of the proposed system. Finally, experiments and accuracy analyses are performed in situ on an assembled tailplane panel (approximately 1760 mm × 460 mm). The automated scanning process is completed in a timeframe of 208 s with an average error of less than 0.121 mm for profile reconstruction. Therefore, the proposed method is promising considering both the high accuracy and high efficiency requirements of profile inspections for large aircraft.

This paper presents the design of flexible trapezoidal radiating patch antenna array with FR4 substrate for onbody low frequency medical applications. The array resonates at 1.89 GHz with impedance bandwidth of 80 MHz and low return loss of -26.19 dB. The VSWR of 1.103 validate the activeness of the proposed antenna array having maximum surface current 133.1 (A/m) and directivity of 4.48 dBi. The antenna array exhibit the H-Field strength of 160.52 (A/m) and E-Field of 36093.4 (V/m) prove the radiation capability at low frequency on body application. These properties demonstrate the suitability of proposed array antenna for on body medical wireless applications.

As an increasingly recognized optical interferometric technique for nondestructive testing and evaluation, shearography has attracted extensive interest in various industrial applications. However, it suffers from the ignorance of the whole process of dynamic surface deformation and the difficulty in determining the depth-resolved information of inhomogeneities. In this regard, a novel speckle pattern interferometric modality named photothermal radar shearography is proposed. Unlike the differential mode of conventional shearography, the present work focuses on the dynamic surface displacement field channel technique with more comprehensive understanding of the subsurface structural information. With the utilization of frequency modulated photothermal excitation, the depth-distributed information of subsurface structures and inhomogeneities is encoded into the induced dynamic surface deformation. Using Hilbert transform and least-square method solved by discrete cosine transform, the time-domain interference signal of each pixel from the recorded speckle patterns sequence is demodulated and unwrapped to obtain the transient full-field shearographic phase distribution which indicates the dynamic surface deformation. In the meanwhile, incrementally delayed cross-correlation matched filtering allows for the localization of axial energy distribution to generate depth-selective structural display for tomography. This proposed transient-based interferometric methodology thus enables depth-tomographic profiles and three-dimensional visualization of subsurface anomalies for the first time, which significantly improves the superiority and attractiveness of shearography in providing insight into the status, performance and reliability of industry.

Summary The goal of this study is to compare and combine different acoustic features in discriminating subjects with and without voice disorders. A database of 484 adult patients participated in the research. All subjects recorded a sustained vowel /Ɛ/ and underwent a laryngoscopic examination of the larynx. From the results of the laryngeal examination performed by a physician and the auditory-perceptual judgment performed by a Speech-Language Pathologist, the subjects were allocated to the group with (n = 52) and without (n = 432) voice disorder. Four types of acoustic features were used: traditional measures, cepstral measures, nonlinear measures, and recurrence quantification measures. Recordings comprised the emission of the vowel /e/. Quadratic discriminant analysis was used as classifier. Individual features in the context of traditional, cepstral, and recurrence quantification measures achieved an acceptable performance of ≥70%. Combination of measures improved the classifier performance. The best classification result (86.43% accuracy) was obtained by combining traditional linear and recurrence quantification measures. Results shown that Traditional, Cepstral, and recurrence quantification measures are promising features that capture meaningful information about voice production, which provides good classification performances. The findings of this study can be used to develop a computational tool for voice disorders diagnosis and monitoring.

Confronting the challenge of replacing or recharging batteries for numerous low-power devices in IoT, the harvesting of ambient electromagnetic (EM) energy is considered a promising approach. Since EM energy is randomly distributed in the environment, omnidirectional antennas or multibeam antennas are better choices for their large coverages which enable them to collect as much energy as possible. However, omnidirectional antennas usually have low gains resulting in low receiving energy, and most multibeam antennas with high gains require complicated feeding networks. To address these issues, a six-beam antenna without a complex feeding network is proposed in this paper. It consists of a triangular patch array layer and a surface waveguide layer. A peak gain of 8.3 dBi, as well as a 3-dB beamwidth of 620 in H-plane and 560 in E-plane have been achieved, affording full azimuthal coverage within a certain elevation angle range. For demonstration, an EM energy harvester is constructed based on the proposed antenna. It can be observed that the implemented device can harvest almost the same amount of EM energy in different horizontal orientations, and acquire multi-fold DC power in the case of multiple EM transmitters.

Doppler ultrasound techniques are currently employed in several industrial, consumer, and biomedical applications. They are implemented in electronic systems of different complexity: from simple low-cost embedded boards to high-end echographs. The development, implementation, and periodic verification of such systems involve complex tests carried out through flow-rigs and phantoms. Unfortunately, these hydraulic circuits are affected by several issues, like the huge dimensions and the lack of an accurate reference for the velocity distribution developed by the fluid. In this work we present an innovative Flow Emulator Board (FEB). The FEB is compact and does not need moving fluids or pumps. Moreover, it produces a signal that mimics a programmable velocity profile with known characteristics. The FEB can replace the flow-rigs in most of the tests where Pulsed Wave Doppler (PWD) methods and PWD electronics systems are involved. The presented experiments show that the proposed FEB synthetizes arbitrary flow velocity profiles with programmable clutter, white noise, propagation attenuation, and sample volume extension; and show how FEB is employed for testing an industrial sensor and a research echograph.

This paper extends the simplified airport noise model Rapid Aviation Noise Evaluator (RANE) [Torija et al., Journal of the Acoustical Society of America, Vol. 141, No. 2, 2017, pp. 981–995], adding capability of including fully nonisotropic noise sources. This extended tool, RANE v2, is developed as a part of multidisciplinary acoustic assessment of novel aircraft, in order to produce ground contours around airports and helipads. Version 2 extends the capability of RANE to accommodate predictions of future air vehicles implementing propulsion systems solution with inherent directional properties. The model uses three-dimensional noise emission surfaces around a series of discretized segments that represent the aircraft flightpath. The main inputs are the sources’ sound power level, the distance from the flightpath at which a level is observed, and the source three-dimensional directivity. The directivity function may take analytical or numerical form, allowing for experimental data inputs. This paper demonstrates the use of spherical harmonics as a form of directivity function with a closed-form analytical solution for calculating the noise exposure contours. Results and comparison against the Federal Aviation Administration’s Aviation Environmental Design Tool module for helicopter community noise indicate that exposure contour coordinates can be estimated for high and low noise exposure levels. The incorporation of source directivity allows for the assessment of lateral attenuation, engine installation effects, and transition operations (for vertical to horizontal flight and vice versa) via the assumption of individual source directivities and, therefore, complex noise surfaces. As a consequence of the analytical nature of the model, low computational requirements allow for fast exploration of the design space and parametric studies, with minimal input requirements. The capabilities of RANE v2 are demonstrated by predicting noise footprints for three helicopters, each of different size, performance, and directivity characteristics.

OBJECTIVE: Absorbance measured using wideband tympanometry (WBT) has been shown to be sensitive to changes in middle- and inner-ear mechanics, with potential to diagnose various mechanical ear pathologies. However, artifacts in absorbance due to measurement noise can obscure information related to pathologies and increase inter-measurement variability. Published reports frequently present absorbance that has undergone smoothing to minimize artifact; however, smoothing changes the true absorbance and can destroy important narrow-band characteristics such as peaks and notches at different frequencies. Because these characteristics can be unique to specific pathologies, preserving them is important for diagnostic purposes. Here, we identify the cause of artifacts in absorbance and develop a technique to mitigate artifacts while preserving the underlying WBT information. DESIGN: A newly developed Research Platform for the Interacoustics Titan device allowed us to study raw microphone recordings and corresponding absorbances obtained by WBT measurements. We investigated WBT measurements from normal hearing ears and ears with middle and inner ear pathologies for the presence of artifact and noise. Furthermore, it was used to develop an artifact mitigation procedure and to evaluate its effectiveness in mitigating artifacts without distorting the true WBT information. RESULTS: We observed various types of noise that can plague WBT measurements and that contribute to artifacts in computed absorbances, particularly intermittent low-frequency noise. We developed an artifact mitigation procedure that incorporates a high-pass filter and a Tukey window. This artifact mitigation resolved the artifacts from low-frequency noise while preserving characteristics in absorbance in both normal hearing ears and ears with pathology. Furthermore, the artifact mitigation reduced inter-measurement variability. CONCLUSIONS: Unlike smoothing algorithms used in the past, our artifact mitigation specifically removes artifacts caused by noise. It does not change frequency-response characteristics, such as narrow-band peaks and notches in absorbance at different frequencies that can be important for diagnosis. Also, by reducing inter-measurement variability, the artifact mitigation can improve the test-retest reliability of these measurements.

Depth, proximity and tactile sensors are often used in robotic object manipulation. The three types of sensors are combined to address each sensor limitation: depth use is limited by blind spots and measurable range, proximity sensor is limited to millimetric distances, and the tactile sensor requires direct contact with the object. Here we present a novel sensor that can simultaneously measure millimetric distance and surface tilt, as well as contact force. We demonstrated the advantage of this novel sensor during a contact task. There, we implemented an admittance control and succeeded in achieving smooth transition from zero- to infinite-impedance contact condition and vice-versa. This novel sensor affords the realization of advanced interactions between robot and objects and contrary to previous approaches - limited by distance, blind spots, and impact force during initial contact - demonstrated good performance at all times with smooth and continuous measurements during contact.

Objective: Considering the knee as a fluid-lubricated system, articulating surfaces undergo different lubrication modes and generate joint acoustic emissions (JAEs) while moving. The goal of this study is to compare knee biomechanical signals against synchronously recorded joint sounds and assess the hypothesis that these JAEs are attributed to tribological origins. Methods: JAE, electromyography, ground reaction force signals, and motion capture markers were synchronously recorded from 10 healthy subjects while performing two-leg and one-leg squat exercises. The biomechanical signals were processed with standard inverse dynamic analysis through musculoskeletal modeling, and a tribological parameter, lubrication coefficient, was calculated from these signals. Besides, JAEs were divided into short windows, and 64 time-frequency features were extracted. The lubrication coefficients and joint sound features of the two-leg squats were used to label the windows and train a classifier that discriminates the knee lubrication modes only based on JAE features. Then, the classifier was used to predict the label of one-leg squat JAE windows. To evaluate these results, the predicted joint sound labels were directly compared against the associated lubrication coefficients. Results: The trained classifier achieves a high test-accuracy of 84% distinguishing lubrication modes of the one-leg squat JAE windows. The Pearson correlation coefficient between the estimated friction coefficient and the predicted JAE scores was 0.830.08. Furthermore, the lubrication coefficient threshold, separating two lubrication modes, was calculated from joint sound labels, and it decreased by half from two-leg to one-leg squats. This result was consistent with the tribological changes in the knee load as it was inversely doubled in one-leg squats. These results verify that JAEs contain salient information on knee tribology. Significance: This study supports the potential use of JAEs as a quantitative digital biomarker to extract tribological information about joint lubrication modes and loading conditions. Since arthritis and many other conditions impact the roughness of cartilage and other surfaces within the knee, the use of JAEs in clinical applications could thereby have broad implications for studying joint frictions and monitoring joint structural changes with wearable devices.

From sirens to lane markings, the urban environment is full of sounds that are designed to navigate the attention of the driver towards events that require special care. Microphone-equipped autonomous vehicles can also use these acoustic cues for increasing safety and performance. This article explores auditory perception in the context of autonomous driving and smart vehicles in general, examining the potential of exploiting acoustic cues in driverless vehicle technology. With a journey through the literature, we discuss various applications of auditory perception in driverless vehicles, ranging from the identification and localisation of external acoustic objects to leveraging ego-noise for motion estimation and engine fault detection. In addition to solutions already proposed in the literature, we also point out directions for further investigations, focusing in particular on parallel studies in the areas of acoustics and audio signal processing that demonstrate the potential for improving the performance of driverless cars.

In order to solve the problem of non-invasive diagnosis and monitoring of women during pregnancy, a piezoelectric film pulse sensing system combined with the mode energy ratio (MER) analysis is utilized to detect human pulses to reveal pregnant conditions. Inspired by traditional Chinese medicine (TCM), pulse diagnosis has a history of more than 2,500 years. The life energy of the human body helps the diagnosis of the disease through the circulation of blood vessels connected to the organs. A PVDF piezoelectric film sensor is used to emulate the pulse taking process in TCM to record the pulse signals. And the algorithm of MER is proposed based on empirical mode decomposition (EMD). Through the MER analysis of 83 female volunteers with different pregnancy statuses, the identification and warning of pregnancy status and physical health indicators are realized.

The clinical use of microwave tomography (MT) requires addressing the significant mismatch between simulated environment, which is used in the forward solver, and real-life system. To alleviate this mismatch, a calibrated tomography, which uses two homogeneous calibration phantoms and a modified distorted Born iterative method (DBIM), is presented. The two phantoms are used to derive a linear model that matches the forward solver to real-life measurements. Moreover, experimental observations indicate that signal quality at different frequencies varies between different antennas due to inevitably inconsistent manufacturing tolerance and variances in radio-frequency chains. An optimum frequency, at which the simulated and measured signals of the antenna present maximum similarity when irradiating the calibrated phantoms, is thus calculated for each antenna. A frequency-division DBIM (FD-DBIM), in which different antennas in the array transmit their corresponding optimum frequencies, is subsequently developed. A clinical brain scanner is then used to assess performance of the algorithm in lab and healthy volunteers' tests. The linear calibration model is first used to calibrate the measured data. After that FD-DBIM is used to solve the problem and map the dielectric properties of the imaged domain. The simulated and experimental results confirm validity of the presented approach and its superiority to other tomographic method.

Nowadays, the piezoelectric transduction mechanism has a great concern to be used in the (micro-electromechanical systems) MEMS microphones. In piezoelectric microphones, the thickness, length, width of the piezoelectric and electrode materials are key parameters that need to be optimized in the design loop. The sensitivity is also another vital design factor for MEMS microphones. One common scenario in modeling the sensitivity is to build an electrical equivalent model from lumped components in any simulator. This approach generally requires specialist design expertise and substantial time to build a complete equivalent model. In this paper, a powerful simulation platform to design high-performance cantilever piezoelectric MEMS microphones with sensitivity estimation has been presented. This simulation platform, called MEMS microphone optimizer platform (MMOP), can predict a wide range of key issues related to the successful design of a MEMS Microphone such as the optimum values of piezoelectric material thickness, electrode material thickness, and the length of a cantilever. MMOP offers also the capability to simulate sensitivity directly from the input parameters of the designed model. To validate the proposed simulation platform, a real model of a cantilever MEMS microphone has been studied. In the performed simulations and analysis, sweeping dimensions in micrometer have been considered to predict the best performance. In the proposed model, Aluminum nitride (AlN) and molybdenum (Mo) were utilized as the piezoelectric material and electrode materials, respectively. A high agreement has been found between the theoretical results and the output of the MMOP platform. The platform opens the door for a fast optimized design with accurate results. Finally, MMOP enables a designer to simulate key issues that are specific to cantilever MEMS microphones, including optimized thickness values and predicted sensitivity.

A mathematical study on the traveling waves (TWs) propagation phenomena on three-phase power lines under fault conditions is presented in this work. This paper is divided into two parts, and this part focuses on the analytical development of expressions that describe fault-launched TWs as functions of line and fault parameters. From the obtained mathematical representation of TWs launched by faults, TW-based applications can be designed in a more reliable way, justifying the relevance of the presented study.

As more compact designs and more assembled function modules are utilized in modern electronic devices, radio-frequency interference (RFI) source reconstruction is becoming more challenging because different noise sources may contribute simultaneously. This article presents a novel methodology to reconstruct multiple random noise sources on a real-world product, including several double-data-rate (DDR) memory modules and a high-speed connector. The DDR modules located beneath a heatsink cause random noise-like signals, which renders phase measurements challenging. An approach based on the tuned-receiver mode of a vector network analyzer is developed to measure the field phase from the random DDR signals, which can be further modeled with a Huygens’ box using the measured field magnitude and phase. Moreover, the connector can be modeled using an equivalent magnetic dipole. Furthermore, the total RFI power from the DDR memory modules and the high-speed connector, which generate uncorrelated RFI noise, is found to equal the summation of the individual power values obtained by an root mean square detector, which can be mathematically corroborated. Using the proposed method, the reconstructed source model can predict RFI values close to measurement results with less than 5 dB deviation.

Insertion into delicate tissue, such as retina vein occlusion, cell manipulation and vitreoretinal injection, poses challenges to surgeons and biomedical researchers due to the high resolution, large movement range, compact structure and multi-DOF output requirements. In order to meet these requirements, a 2-DOF arched needle insertion device driven by inertial piezoelectric actuator was proposed in this work. This device could perform theoretical unlimited translational movement and full rotation with high step resolution. A prototype was fabricated with compact structure, the length and diameter were 230 mm and 32 mm, respectively. The experimental tests were carried out, the insertion device output 2.47 m and 0.56 mrad step distance with maximum velocity of 382 m/s and 200.9 mrad/s under 120 V driving signals, the maximum insertion force of 32 mN was measured. Additionally, a handheld controller with friendly user interface was also developed for open-loop control utilization, which could automatically calculate and generate the required control signals according to the motion command. This device explores the biomedical application of inertial piezoelectric actuator within a compact size, providing a new choice for numerous innovative treatment and biological research involving precision operation.

Holographic acoustic field has shown great potential for non-contact robotic manipulations of millimeter or sub-millimeter size objects to effectively deliver acoustic power. The latest technology for generating dynamic holographic acoustic field is through phased transducer array, where relative phases of emitted acoustic waves from transducers are independently controlled to modulate the acoustic interference field. While the forward kinematics of a phased array based robotic manipulation system is simple and straightforward, the inverse kinematics (i.e., the mapping from a given holographic acoustic field to array phases for control purpose), however, is mathematically non-linear and unsolvable, presenting challenges in developing wider applications of holographic acoustic field for robotic manipulation. Considering, thus far, there are still no effective solutions reported, the authors put intensive efforts to solve this problem using a machine learning approach, which we refer to as AcousNet. Experimental results demonstrate the effectiveness of the proposed method for dynamic holographic acoustic field generation from phased transducer array.

This paper proposes a new diagnostic and prognostic approach that integrates joint time-frequency reflectometry (JTFDR), continuous wavelet transform (CWT), and particle filter to estimate the degradation of insulation and predict the remaining useful life of coaxial cables. In the proposed approach, the degradation process of the insulation is monitored by using an optimized JTFDR incident signal in an accelerated thermal aging test. CWT is adopted to obtain the time-frequency scalogram of the reflected JTFDR signals. The features are then extracted from the CWT magnitude scalogram to represent the degradation level of the insulation. A particle filter-based fault diagnostic and prognostic approach is developed. A series of experiments are conducted, and the results demonstrate the effectiveness of the proposed method.

Safety in coastal areas such as beaches, ports, pontoons, etc., is a current problem with a difficult solution and on which many organizations are putting efforts in terms of technological innovation. In this work the design of a possible solution based on magnetic sensors is presented. First, a study has been made of the type of sensors that best suit the application based on parameters such as sensitivity, the allowed bandwidth of excitation, price or physical construction. Then the system of excitation of the sensors and signal measurement is presented. To justify the design, a series of simulations of magnetic field variations have been carried out in the presence of large objects of conductive material, in the vicinity of the measuring points. With these data a mathematical model has been established that allows the identification of the dimensions and position of the object through triangulation and knowing only the data of the magnetic field. It was found that although this method seems quite effective, it has a significant error, so another method based on neural networks was developed also using data from the simulations. This method seems to yield much better and more reliable results.

A method for measuring de-embedded antenna parameters of wearable and implanted antennas for on-body communications is presented. It consists of a tapered flat phantom in order to characterize an antenna’s general ability to excite surface waves travelling along the boundary between body tissue and free space expressed by an angular on-body antenna gain. The design offers a test zone large enough for most typical Wireless Body Area Network devices up to smartphone-size while minimizing the required amount of tissue-simulating material. The designed antenna test range is validated in the 2.4 GHz ISM-band. In order to showcase the applicability to a realistic application, different designs of antennas integrated into an implanted pacemaker are characterized by their on-body gain patterns. A comparison of their performance in in-situ path-loss measurements reveals a clear relation to the on-body gain patterns and indicates that this parameter is a suitable measure for enabling educated antenna design for on-body applications.

Range-dependent clutter suppression is a challenging problem in non-sidelooking (NSL), bistatic, and conformal antenna array airborne radar, especially in the presence of range ambiguity. Superimposed stepped frequency (SSF) radar employs a small frequency increment across the stepped signals in each pulse, which induces a dimension related to slant range. In this paper, an airborne radar framework is established with SSF signal as the transmit waveform. Thus, a two-stage adaptive clutter suppression method is proposed which utilizes the degrees of freedom in range, space and time domains provided by airborne SSF radar. In the first stage, the secondary range dependence compensation (SRDC) approach is adopted to distinguish the clutter of each range region in the carrier frequency domain. Then, a target-free covariance matrix is estimated by the compensated data, and the covariance matrix is used for the range-ambiguous clutter separation in the carrier frequency domain. Thus, the space-time snapshot of each range region can be extracted. In the second stage, a clutter segmentation processing method is devised for residual clutter suppression.

A unidirectional microelectromechanical system (MEMS) microphone single module for handsfree and voice recognition systems in automobiles is presented. Because in-cabin noise and temperature variation affect the reduction in the handsfree and voice recognition system performance, noise suppression and increasing the signal-to-noise ratio (SNR) of the microphone are required. In this study, a capacitive MEMS microphone module with a high SNR and a unidirectional characteristic is achieved by designing the structure, package, and module of the MEMS microphone. To improve the SNR, the microphone is developed using a slit-edged membrane. The slit structure is designed to release the residual stress of the membrane to achieve improved sensitivity and SNR. The unidirectional characteristic of the microphone enables suppression of noise signals from undesired directions. The directional characteristic of the microphone is realized by attaching a porous SU-8 filter to delay the time to one of the two acoustic ports on the package. Tests on the proposed unidirectional MEMS microphone package and module show that an SNR of 62.4 dB and a front-back ratio of 27.1 dB are achieved.

The accuracy of traffic noise prediction models (TNMs) is impaired by affecting factors and system errors. In addition, the traditional traffic noise source cannot be tested as the sound source is generated in the centreline of the road. To address these limitations, a TNM based on the equivalent sound source at the road shoulder was developed. First, the equivalent traffic flow based on the acoustic-equivalent conversion coefficient was calculated and the traffic noise source intensity model was deduced. The shoulder's sound pressure level (SPL) data were then used to formulate a single-vehicle equivalent SPL model and correct the traffic noise source intensity model. The propagation model was fitted according to the attenuation law that traffic noise strength attenuates gradually from the shoulder to the road outside and fluctuates periodically. The results of a case study showed that the absolute percentage error of the proposed model's prediction was 2·3% compared with the measured value, which was better than the performance of the current model suggested in the Chinese specification. The proposed prediction model provides a friendly and less time-consuming approach for city planners and traffic engineers to conduct freeway traffic noise prediction and assessment.

Concentric push–pull robots (CPPR) combine the simplicity, miniaturization potential, and open lumen of concentric-tube robots with the kinematic advantages and stability of push–pull multibackbone designs. A CPPR segment is made from a pair concentric tubes with notches asymmetrically cut into their sides in opposing directions. The two tubes are attached to one another at their tips, and push–pull translation of the tube bases relative to each other changes the curvature along the length of the combined tube pair. Custom, variable-curvature shapes are possible by varying the notch parameters along the tubes. In this article, we present a planar, variable-curvature mechanics model for the actuated segment shape and a method for designing the notch pattern to achieve a desired planar, variable-curvature shape with maximal stiffness within specified strain limits. Experiments validate accuracy for various shapes, materials, and cross sections, showing that the design method achieves a variety of desired shapes. We also demonstrate a multisegment robot made from multiple tube pairs that can independently rotate and actuate, increasing the robot DOF.

In synthetic aperture imaging, the interpulse Doppler shift is commonly used, while the intrapulse Doppler shift is ignored. However, for the linear frequency modulation signal, the intrapulse Doppler shift can cause an additional range cell migration (ARCM) and a phase error term. Additionally, the ARCM may exceed a range resolution cell in certain cases of multireceiver synthetic aperture sonar (SAS), which will result in image defocus. Therefore, the intrapulse Doppler shift in multireceiver SAS should not be ignored in such cases. In this study, the condition of the negligible intrapulse Doppler shift is presented, that is, the moving distance of the sonar platform within a pulse should be much less than an azimuth resolution cell. Based on the multireceiver accurate time-delay model, a multireceiver SAS intrapulse Doppler shift signal model is developed by introducing the intrapulse Doppler frequency into the echo signal. After simplifying the accurate range history under the narrow-beam assumption, the range-Doppler spectrum is derived. Finally, a multireceiver SAS chirp scaling algorithm considering the intrapulse Doppler shift (IDS-CSA) is derived. The proposed algorithm can correct the ARCM and compensate the phase error (although not required), and then obtain a well-focused synthetic aperture image. The effectiveness of the proposed model and algorithm is verified by simulations and field data. The results show that the proposed algorithm provides a better image quality than the conventional multireceiver CSA when the condition of the negligible intrapulse Doppler shift is not met.