Source Of Acoustic Signal Research Articles

Monitorization of crack propagation in welded aluminium assemblies

Utilizing welded assemblies of aluminum profiles presents an effective means of reducing mass in rolling stock. However, these lightweight and optimally stiffened structures might be susceptible to unexpected failure modes that were not accounted for during the design phase. This could be due to insufficient information about in-service conditions or uncertainties in the material and manufacturing processes. This study aims to assess the feasibility of monitoring welded aluminum assemblies in real-time under both static and cyclic loading conditions to evaluate their structural health. Mechanical tests were conducted on welded aluminum profile assemblies while employing piezoelectric wafer active sensors (PWAS) for continuous monitoring. The PWAS facilitated ultrasonic active and passive inspections during testing. Passive sensing involved utilizing the acoustic emission technique to locate the source of acoustic signals associated with damaging mechanisms like crack nucleation and propagation. Upon identifying a detrimental event, on-demand active inspections using Ultrasonic Guided Waves were deployed to examine the structure and gather crucial information about its current condition based on analyzing temporal signal features. Although our mechanical tests were conducted in a laboratory environment, we recorded some temperature variations. Hence, we compensated for environmental influences through a data fusion model. Additionally, repetitivity analyses were conducted to confirm the reliability of the proposed inspection technique. Encouragingly, results demonstrated consistency and reliability in this proposed method.

A flue gas velocimeter based on the hyperbolic chirp modulation method of acoustic source signal

Accurate measurement of flue gas velocity is of great significance for the safe production, energy saving, and emission reduction of coal-fired power plants. In this paper, a method of flue gas velocimetry based on a hyperbolic chirp-modulating acoustic source was proposed, and its superiority was verified by numerical simulations and field experiments. For an acoustic velocimeter, it is crucial to ensure the accuracy of the acoustic Time-of-Flight (TOF), which directly affects the flue gas velocity measurements. The improvement of the accuracy of estimation of the TOF directly determines the accuracy of the flue gas velocity measurement. Simulation on the different types of acoustic sources at different signal-to-noise ratios (SNRs) was conducted, and the results proved that the hyperbolic chirp signal is more accurate in the measurement of TOF. In the strong noise range of − 10 dB to − 20 dB, the average relative root mean square error (RRMSE) obtained using this hyperbolic chirp modulating acoustic source is 0.60 dB and 0.36 dB lower than obtained using the linear and logarithmic modulating modes, respectively. The average relative error (RE) is approximately 0.87 times that of the linear chirp. Power plant flue field experiments show that the measurement error using this hyperbolic modulating mode is about 0.52 times and 0.74 times that of using linear and logarithmic modulating modes, respectively. In harsh measurement environments with strong noise, the proposed acoustic source modulation scheme can significantly improve the measurement SNR and effectively enhance the accuracy and robustness of flue gas velocimetry.

Detection of defects in printed circuit boards by the acoustic emission method

Objectives. Defects in the form of layering may occur during lamination in the production of multilayer printed circuit boards (MPCB). These defects cannot be detected by optical and electrical methods of output control. However, they can lead to breaches of the mechanical mode of operation and failures while running radioelectronic devices. In order to detect such defects, the acoustic emission (AE) method is proposed. This is based on the occurrence and propagation of acoustic waves in MPCBs caused by the presence of defects. The aim of this study is to investigate the possibility of using the AE method to detect defects in multilayer printed circuit boards. These defects can occur, in particular, in the lamination process.Methods. A mechanical processes modeling program (for research on the MPCB model) and various samples of two-layer printed circuit boards with pre-introduced defects (for experimental studies) were used to study the propagation of acoustic signals in the MPCB in the presence of defects. A solenoid mounted on the MPCB was used as a source of acoustic signals, while a piezoelectric sensor was used to receive signals. Data processing was carried out by comparing AE signals obtained for a serviceable MPCB sample and for MPCB samples with defects.Results. Simulation of the acoustic signal propagation in MPCBs in serviceable and faulty (with a rectangular defect in the form of delamination) states was carried out to show the difference in the received signals at the sensor installation point. Experimental studies were also conducted to examine the AE method applicability for detecting defects of various sizes and quantities.Conclusions. The studies demonstrated that the AE method allows the presence of defects in MPCB occurring during the lamination process to be detected effectively and reliably. This study proposes a new approach to non-destructive testing of MPCB using the AE method. This method significantly increases the reliability of MPCBs and the efficiency of their production processes.

Acoustic Emission in Zirconium Hydrogenation Process

Acoustic emission signals occurring during the interaction of zirconium metal samples with hydrogen, as well as changes occurring in hydrogenated samples and being sources of high-amplitude acoustic signals, have been studied. The hydrogenation of pieces of compact iodide zirconium with a size from 5 to 10 mm, chips obtained from compact iodide zirconium with a linear particle size from 2 to 3 mm and a thickness of 0.2 mm, a «large» powder of electrolytic zirconium of a fraction from 80 to 550 microns and a «small» powder of electrolytic zirconium with a particle size of less than 80 microns was carried out. It has been established that the source of high-amplitude acoustic signals in all cases is the cracking of zirconium particles at the macro level, which leads to the formation of extended cracks and fractures on the surface of individual particles, as well as to the grinding of original materials. Cracking and grinding are caused by deformation and internal stresses occurring in the samples due to an increase in the volume of the solid phase during hydrogenation. It is shown for the first time that the atomic ratio [H] / [Zr] in the solid phase, corresponding to the maximum amplitude of a acoustic emission signal, naturally increases in a series: pieces of compact iodide zirconium-chips of iodide zirconium-«large» powder of electrolytic zirconium-«small» powder of electrolytic zirconium, which is in good agreement with the results of previous studies similar studies on the hydrogenation of titanium metal samples.

Graphene-based stand-alone nanomechanical membrane production and mass-acoustic hybrid-sensor application

In this article, experimental studies were carried out for the preparation, characterization, and nanomechanical membrane application of Graphene-based nanomechanical mass and acoustic hybrid sensors. The purpose of this study was to prepare facile and low-cost nanomechanical membrane-based mass-acoustic hybrid sensors by set-ups developed on the exfoliation and membrane transfer methods, and to examine their morphological, spectroscopical, and nanomechanical-vibrational properties, as well as the membrane characteristics like mass and acoustic sensitivities and durability over time. For the experiments, equipment and items such as optical, digital, atomic force and scanning electron microscopes, Raman spectroscope, acoustic signal source and amplifier, data-logger, sound pressure level meter, and laser Doppler vibrometer were used. Graphene-based nanomechanical membrane sensor chips with varying acoustic pressure levels and mass-loadings were tested. It was observed that the acoustic sensitivity of the produced 706.5 µm2 nanomechanical membranes increased with increasing sound pressure levels and decreased with increasing mass-loads. With 67.8 ± 5 nm/Pa, the unloaded nanomechanical membrane was the most sensitive sample. Experimental challenges and sensor development solutions were discussed. Existing application examples were examined and discussions were made on the current challenges and the future prospects of the nanomechanical membrane sensors.

Classification of Acoustic Emission Signal Sources Using Genetic Programming

Genetic Programming (GP) is used to classify the Acoustic Emission (AE) signal to different source of signals. GP has the ability to discover the relationship among the observed data and express them mathematically. GP based technique has an advantage over conventional statistical technique like maximum likelihood estimate, nearest neighbor classifier and etc, because they are distribution free i.e. no a priori knowledge is required about the distribution of data. The data is obtained through an AE test using pulse, pencil and spark signal source on the surface of solid steel block. The signal parameters are measured using AET 5000 system, A set of expert system like rules is extracted from the GP. These rules are used directly to classify the AE signals. Classification of AE signal using genetic programming is found to be effective.

Properties of Amplitude Distributions of Acoustic Emission Signals Generated in Pressure Vessel During Testing

In the paper, the results of investigations on the properties of acoustic emission signals generated in a tested pressure vessel are presented. The investigations were performed by repeating several times the following procedure: an increase in pressure, maintaining a given pressure level, a further increase in pressure, and then maintaining the pressure at new determined level. During the tests the acoustic emission signals were recorded by the measuring system 8AE-PD with piezoelectric sensors D9241A. The used eight-channel measuring system 8AE-PD enables the monitoring, recording and then basic and advanced analysis of signals. The results of basic analysis carried out in domain of time and the results of advanced analysis carried out in the discrimination threshold domain of the recorded acoustic emission signals are presented in the paper. In the framework of the advanced analysis, results are described by the defined by the author descriptors with acronyms ADC, ADP and ADNC. Such description is based on identifying the properties of amplitude distributions of acoustic emission signals by assigning them the level of advancement. It is shown that for signals including continoues AE or single burst AE signals descriptions of such registered signals by means of ADC, ADP and ADNC descriptors and by Upp and Urms descriptors provide identical ordering of registered acoustic emission signals. For complex signals, the description using ADC, ADP and ADNC descriptors based on the analysis of amplitude distributions of recorded signals gives the order of signals with more accurate connection with deformational processes being sources of acoustic emission signals.

Experimental Study of Identifying Emission Sources of Acoustic Signals on the Cylinder Body of a Two-Stroke Marine Diesel Engine

In this paper, an experimental method was utilized to investigate acoustic emission (AE) characteristics and to identify emission sources of the nonlinear AE signal on the cylinder body of a large low-speed two-stroke marine diesel engine in real-working conditions on the sea in misfiring and normal firing modes. Measurements focused on the AE signal acquired in a transverse direction in low-frequency (20–80 kHz), medium-frequency (100–400 kHz) and high-frequency (400–900 kHz) ranges. The collected signals were analyzed on the crank angle and crank angle-frequency domains. The results showed that all potential sources of the nonlinear AE signal could be mapped in the low-frequency range. However, only the AE signal caused by the combustion process at around the top dead center could be well-observed in the medium-to-high-frequency range. The findings also revealed that in normal firing conditions, the AE energy radiated by friction in the down-stroke period was smaller than in the up-stroke process due to gas-sealing forces. Moreover, the AE energy in the misfiring condition was higher than in the normal firing state. These outcomes considerably contributed understandings to characteristics of friction and wear around the mid-stroke area of the cylinder on a two-stroke marine diesel engine.

Mathematical modeling of a new method for processing a seismic signal on the example of a section of the Saratov right bank. Part 1

The paper presents a new method of seismic exploration, which includes two receivers of acoustic signals, deepened into the rock one under the other at some distance. These receivers record seismograms which are the acoustic signals, the source of which can be the natural seismic activity of the Earth’s crust or targeted sources of acoustic signals, such as an explosion. Simulation of the direct problem of seismic exploration was performed using the COMSOL Multiphysics and MatLab software packages. The seismograms obtained during the simulation are combined and added with each other with the on the delay time shift of the input seismic pulse between the receivers. In this case, the signals that came along the vertical, “amplify” each other on the total seismogram, and non-vertical signals are damped. The correlation function of seismograms was obtained for mathematical simulation. The results of modeling the propagation of an acoustic wave in rocks and an example of processing seismograms according to the proposed algorithm are given. The presented results show that the new method of receiver location and the method of processing seismograms make it possible to obtain a cleared seismogram that can be used to solve the inverse problem of determining the parameters of the geological environment.

Sound Range AE as a Tool for Diagnostics of Large Technical and Natural Objects.

Application of acoustic emission of the sound frequency range is under consideration. This range is of current interest for the diagnostics of the stability of mountain slopes, glaciers, ice covers, large technical constructions (bridges, dams, etc.) as well as for the detection of rock deformation anomalies preceding earthquakes. Acoustic sensors, which can be used to record and to determine the directivity of acoustic emission of the sound frequency range, are under consideration. The structure of the system for acoustic emission recording, processing and analysis is described. This system makes it possible to determine the direction to the acoustic emission source using one multi-component sensor. We also consider the algorithms for detection of acoustic emission pulses in a noisy background, and for the analysis of their structure using the Adaptive Matching Pursuit algorithm. A method for the detection of the direction to an acoustic emission signal source based on multi-component sensors is described. The results of application of sound range acoustic emission for the detection of the intensification of rock deformations, associated with earthquake preparation and development in the seismically active region of Kamchatka peninsula, are presented.

ОПТИМІЗАЦІЯ АЛГОРИТМУ ВИЗНАЧЕННЯ КООРДИНАТ ДЖЕРЕЛА АКУСТИЧНОГО СИГНАЛУ ЗА КРИТЕРІЄМ МІНІМУМУ ПОХИБКИ

This paper investigates the error of determining the coordinates of an acoustic signal source depending on various parameters of the developed software-mathematical models for training a neural network. The authors determined the optimal values of these parameters according to the criterion of minimum error. The study found that the optimal amount of data for training a neural network is 25,000 training pairs, and the number of hidden layers should not exceed 5. Among several forms of sensor arrangement, the best is the square, as it provides a smaller error and uniform filling of the microphone’s perimeter. Their number should not exceed 9, since the best algorithm for training the neural network trainlm requires significant computing resources of the system on which training is performed. An increase in the number of sensors leads to an increase in the training time of the neural network but does not lead to an improvement in accuracy. When studying the effect of the distance to the acoustic signal source and the algorithm for selecting the base sensor for calculating the time difference, it was found that changing these parameters does not affect the accuracy of the neural network. The best structure of the number of hidden neurons in each hidden layer is an expanding structure, in which the number of neurons in each layer increases from the input layer to the middle-hidden layer, then decreases to the output layer. Using the optimized parameters, the neural network was trained and its accuracy was evaluated on two data sets: those used for training and those unknown to the neural network. In both cases, the neural network demonstrated good results. According to the results of the study, it was found that the error of the optimised system is 6.7681 × 10-5 m in the Y coordinate and 6.6120 × 10-5 m in the X coordinate.

UNDERWATER ACOUSTIC SIGNAL RECOGNITION BASED ON COMBINATION OF MULTI-SCALE CONVOLUTIONAL NEURAL NETWORK AND CONSTANT-Q TRANSFORM

This article proposes a multi-scale deep learning network to classify different underwater acoustic signal sources. The proposed network is cleverly designed with multiple branches, creating a multi-scale block which allows learning various spatial features of Constant-Q Transform spectrograms. The network is trained and tested on the ShipsEAR dataset, which is augmented by the overlap segmentation technique to ensure a balance in ship label classes’ data. The experiment results show that our network achieves an average classification accuracy of up to 99.93% and an execution speed of 2.2 ms when configured with two multi-scale blocks and 32 filter channels. In comparison, our network remarkably outperforms other existing networks in terms of accuracy and execution time.

A novel time-of-flight estimation method of acoustic signals for temperature and velocity measurement of gas medium

Acoustic thermometry and velocimetry are widely recognized as promising methods for in situ measurement of gas temperature and velocity due to their non-invasive, low-cost, and high-resolution advantages. Accurate estimation of acoustic time-of-flight (TOF) is the key to improving the accuracy of acoustic thermometers and velocimeters. In this paper, a new TOF estimation method is developed based on the digital lock-in filtering (DLF) technique. The signal source is an audible sound with linearly modulated frequencies, and the relationship between the time and frequency domains of the signal is established using digital lock-in and low-pass filtering techniques. The linearity of the time–frequency series and the accuracy of the TOF are improved by using a least-squares-based linear fitting method. Experimental studies of gas temperature and velocity measurements with acoustic methods in static, dynamic, and different signal-to-noise ratio (SNR) environments have been carried out. The DLF method performs well in terms of accuracy and robustness to extract the modulated signals of known carriers in a strong noise environment. Furthermore, the very nature of the method predisposes the time-domain data of the acoustic source signal not to be repeatedly processed at each TOF calculation, which saves system resources for processing the source signal.

3-D Near-Field Source Localization Using a Spatially Spread Acoustic Vector Sensor

This article presents a new method for 3-D localization of an acoustic source signal by estimating its azimuth-angle, elevation-angle, and radial range. The proposed method exploits a spatially spread acoustic vector sensor, which is composed of a tri-axial velocity vector sensor and an isotropic pressure sensor. Unlike the spatially collocated case, the self-normalization of spatially spread acoustic vector sensor’s response is no longer independent of the source location, resulting in the inapplicability of the widely used “self-normalization” estimators (A. Nehorai <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , 1994), (V. N. Hari <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , 2012), (Y. Song <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , 2013). The present article considers the near-field propagation’s path attenuation and phase difference among the sensor components and derives a source location estimation method without resorting to the “self-normalization” operation. Also, the proposed method is applicable to any nonfree-space propagation models at arbitrarily unknown path-loss exponent. In comparison with the existing methods, where the velocity vector sensor is spatially collocated, the proposed method can offer improved performance estimation due to the inherent extension of the vector sensor’s spatial aperture in the spread structure.

Влияние амплитуды акустических сигналов на вероятность выявления источников акустической эмиссии

The article discusses the results of using a standard algorithm for linearly locating the sources of acoustic emission signals generated by a broadband acoustic emission (AE) transducer mounted on the surface of a steel plate with sizes 1000×650×7 mm. To generate AE impulses with an amplitude of um = 55–100 dB, the electronic simulator’s difference of potentials was varied in the range of 10–300 V. As a result of laboratory experiments, the reduced error γ of the standard linear location algorithm was calculated. The maximum error equal to γ = 16.3% was recorded at the coordinate X = 100 mm in locating the source of acoustic signals with an amplitude of less than 60 dB and the antenna array basic size B = 800 mm. The minimum error equal to γ = 2.69% was recorded with the electronic simulator installed at the coordinate X = 400 mm. It is shown that the maximum error of the standard algorithm is observed in locating the sources of low-amplitude AE signals situated near the antenna array receiving transducers. The AE source detection probability as a function of recorded impulse amplitude is quantified. For determining the AE source detection probability p, the flow of recorded signals was divided into three amplitude ranges: 40–60 dB, 60–75 dB, and 75–100 dB. For the sources of acoustic signals with an amplitude of less than 60 dB and located at the coordinates X = 100, 200, 600, and 700 mm, the parameter p value tends to zero. It has been revealed in processing the experimental study results that the AE source detection probability increases with a growth in the maximum amplitude of the recorded signals. For AE impulses with an amplitude above 75 dB, the parameter p value approaches unity regardless of the source location. It has been determined that the error of the standard linear location algorithm depends on the distance between the AE source and the antenna array receiving transducers. The dependence p(X, um) has been demonstrated as a numerical assessment of the way in which the above-mentioned factors influence the obtained location picture results.

Dynamic phenomena prevention management in mines of SUEK-Kuzbass

The article presents information on coal seams which are hazardous and susceptible to dynamic phenomena in mines of SUEK-Kuzbass. The current geomechanical and geophysical methods used to predict dynamic phenomena, the associated problems and the potential ways of their solutions are described. The geomechanical approach to rockburst prediction uses the analysis of yield of chippings. Coal and gas outbursts are predicted based on the initial gas emission rate in drilling. The geophysical method used to predict dynamic phenomena is based on the parameters of artificial acoustic signals from SAKSM stationary facilities. When no rockburst prediction is implemented based on the artificial acoustic signal parameters for some reasons, the forecast is carried out using portable equipment ANGEL&ndash;M. This study focuses on the improvement of the method of the artificial acoustic signal parameters in order to eliminate complications of the dynamic phenomenon hazard assessment. The first circumstance is the dependence of the hazard indicator on the spacing of the geophone and the acoustic signal source. The engineering and managerial decisions discussed in this article enable maintenance of the constant spacing at an allowable error. The second circumstance is that the hazard criterion is determined as a sum of averaged hazard indicator after not less than 30 cycles of heading and two&ndash;three values of standard deviations from the average. Such criterion fails to image actual hazard. For this reason, it is planned to check the hazard criterion procedure based on the discussed approach and on the geomechanical method which has a specified hazard criterion value from regulating documents. The third circumstance is the neglect of the gas criterion as the formation gas pressure has almost zero influence on the parameters of artificial acoustic signals. This circumstance can be avoided using the proposed algorithm of prediction with adjustment of the hazard criterion based on the control data on methane concentration in mine air and on the coal strength.The authors are grateful to SUEK-Kuzbass for the information provided under the cooperation agreement with Federal Research Center for Coal and Coal Chemistry, Siberian Branch, Russian Academy of Sciences.The study was supported by the Russian Science Foundation, Project No. 17-17-01143.

Special acoustic devices of law enforcement agencies: a short history, medical and biological effects on the hearing organ

Relevance. The introduction of special acoustic devices into the security system necessitates a medical and biological assessment of the impact of acoustic signals.Intention – To analyze domestic and foreign literature on the history of acoustic weapons and their medical and biological effects, as well as to study current ideas about sound-induced damage to operators of this equipment and exposed persons.Methodology. In this paper, we analyzed domestic and foreign publications (monographs, articles) about creation and use of special acoustic devices as non-lethal acoustic weapons. Besides, regulatory documents on safe levels of noise exposure were analyzed. PubMed, Russian Science Citation Index, Сonsultant plus database were also searched.Results and Discussion. Non-lethal acoustic weapons were developed and their effects studied mainly by foreign researchers (USA, UK). Sources of special acoustic signals (sound generators, cannons, grenades) are mainly used to disperse crowds of people and control illegal actions against law-enforcement officers. Such weapons are widely used by foreign police and military personnel (USA, Georgia, Ukraine etc.). Only a few publications in Russian describe special acoustic effects on the hearing organ of animals and humans.Conclusion. Safety assessment of acoustic effects of special devices is very important and requires further study in relation to the national legislation.

Thermodynamic Approach for the Identification of Instability in the Wood Using Acoustic Emission Technology

In order to monitor the crack growth of the wood material better and reduce failure risks, this paper studied the attenuation characteristics of acoustic emission signals in wood through pencil lead breaking (PLB) tests, in the aim of estimating the true amplitude value of the acoustic emission source signal. The tensile test of the double cantilever beam (DCB) specimens was used to simulate the crack tip growth within wood material, monitoring acoustic activity and location of crack tips within wood material using acoustic emission technology and digital image correlation (DIC). Results showed that the attenuation degree of acoustic emission signals increased exponentially as the propagation distance increased, and the relationship between relative amplitude attenuation rate and the propagation distance of the acoustic emission signal was established by the regression method, which provides the input parameters for the establishment of the crack instability prediction model in the next step. Based on a thermodynamic approach, a theoretical model for predicting crack instability was established, and the model was verified by DCB tests. The model uses acoustic emission parameters as the basis for judging whether the crack is instable. It provides theoretical support for the application of acoustic emission technology in wood health monitoring.

Remote detection of music influence with physical sensor

Goals and objectives of the study: The goal of this paper was to study the possibility of remote detection of electronic music influence with a physical sensor. Study design: Bio-Well technology with a special environmental sensor was used in the study. This sensor was developed for the analysis of the electromagnetic fields and was shown to respond to the changed in the environmental parameters. Signal of a sensor was detected for an hour in the background mode after this music was turned on for 20 minutes, and then after-effect was detected for about one hour. In experiment 5 different files of the modern electronic music “Yippi Wave 3.0” (https://yippiweb.com/what-is-wave) in *wav format and several files of Handel music have been used. Results: The statistically significant changes of sensor parameters to “Yippi Wave 3.0” music were detected in several time-series, while no response to Handel music. Conclusions: This study should be considered a pilot study and the results are preliminary. We need to conduct experiments with different sources of both acoustic and electromagnetic signals and the possibility of their registration by the Bio-Well device

Acoustic emission source localization method for high-speed train bogie

Bogie is one of the most critical parts of high-speed train and is directly related to the operation quality and safety of the train. However, currently no dynamic non-destructive testing method exists for real-time monitoring. Therefore, this paper proposes a new damage localization method for high-speed train bogie dynamic testing. The acoustic emission testing technology is applied to test the vulnerable welding parts of the bogie with time reversal localization method. Firstly, the bogie welding parts structure model based on finite element software is established. Then an acoustic emission damage signal is sent from the model and the acoustic emission source signal is received by the preset acoustic emission sensor. And the accurate localization of damage is achieved by dealing with the received signal according to the time reversal focusing principle and imaging the acoustic emission source. The simulation experiments show that the proposed method can accurately find the damaged localization. And finally, the method has been verified through experiment, and the results show it can effectively improve signal energy of the damage source, and the position of the damage source can be shown accurately through signal reconstruction and localization in the detection area.