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Partial Discharges (PDs) are a significant factor in reducing the insulation life of traction transformers. In recent years, the Acoustic Emission (AE) method has become the most advanced method for detecting PD signals in transformers. The AE method utilizes AE sensors placed on the transformer tank to detect ultrasonic signals emitted by PD and determine the Time Of Arrival (TOA) of the head wave. The windings and cores of a traction transformer consist mainly of metal, which greatly affects the propagation of PD ultrasonic waves. This paper establishes a 110 kV "pressure acoustic, transient" physical field model of the traction transformer with dimensions of 4.63 × 1.48 × 2.84 m3. The model is used to carry out the PD pressure acoustic physical field simulation study of the traction transformer, to clarify the physical characteristics of the ultrasound of the PD defects, and to establish observation points on the transformer tanks to receive ultrasonic time-domain waveforms for PD detection. The simulation results indicate that PD ultrasonic waves exhibit complex propagation characteristics, including reflection, refraction, and reverberation, as they pass through the windings and cores to the observation points. The TOA of the head wave in the ultrasound time-domain waveform is indicated by the first maximum value of the wave crest line. Finally, this paper proposes a multi-level localization method based on the AE method to determine which winding generates the PD in the large-scale traction transformer using only four dynamically moving observation points. [ABSTRACT FROM AUTHOR]

Softness is one of the essential properties of hygiene tissue products. Reliably measuring it is of utmost importance to ensure the balance between customer expectations and cost-effective tissue production. This study presents a method for assessing softness by analyzing acoustic emissions produced while tearing a tissue specimen. The aim was to train neural network models using the corrected results of human panel tests as the ground truth labels and to predict the tissue softness in two- and three-class recognition tasks. We also investigate the possibility of predicting some production parameters related to the softness property. The results proved that tissue softness and production parameters could be reliably estimated only by the tearing noise.

The paper reports the results of a comparative assessment concerned with the effectiveness of identifying the basic forms of partial discharges (PD) measured by the acoustic emission technique (AE), carried out by application of selected machine learning methods. As part of the re-search, the identification involved AE signals registered in laboratory conditions for eight basic classes of PDs that occur in paper-oil insulation systems of high-voltage power equipment. On the basis of acoustic signals emitted by PDs and by application of the frequency descriptor that took the form of a signal power density spectrum (PSD), the assessment involved the possibility of identifying individual types of PD by the analyzed classification algorithms. As part of the research, the results obtained with the use of five independent classification mechanisms were analyzed, namely: k-Nearest Neighbors method (kNN), Naive Bayes Classification, Support Vector Machine (SVM), Random Forests and Probabilistic Neural Network (PNN). The best results were achieved using the SVM classification tuned with polynomial core, which obtained 100% accuracy. Similar results were achieved with the kNN classifier. Random Forests and Naïve Bayes obtained high accuracy over 97%. Throughout the study, identification algorithms with the highest effectiveness in identifying specific forms of PD were established. [ABSTRACT FROM AUTHOR]

Identifying precursor information to rock failure is key to rock dynamic disaster warning. To solve the problem that a single in-situ monitoring method cannot accurately identify the precursors to rock failure, this paper combined a digital image correlation method, thermal infrared radiation and acoustic emission technology to conduct a multi-physical field joint monitoring experiment of granite under three-point bending. The information about strain, thermal infrared and acoustic emission of the rock brittle failure process could be obtained, and the variations in multi-physical field indices of the rock brittle failure process were analysed. Based on the theory of critical slowing-down, the study of the multi-physical field effects of critical slowing-down characteristics in the rock failure process, and further exploration of the precursor characteristics of the brittle failure of rock were undertaken. The results indicate that the strain, infrared, and acoustic emission parameters show sudden changes during brittle failure of granite. The lag step size has little effect on the variance of changes in multi-physical field parameters and exerts a similar influence on the changes in the autocorrelation coefficient curve. The degree of influence of the window length on the variance and autocorrelation coefficient curves of multi-physical field parameters is as follows: infrared field > strain field > acoustic emission field. Compared with the autocorrelation coefficient, the variance parameter is more universal and is better when the critical slowing-down theory is used to investigate the characteristics of multi-physical fields. The four parameters of the strain field variance, infrared field variance, the variance and autocorrelation coefficient for acoustic emission field increase sharply before fracture, representing precursor information to the brittle failure of granite. The four parameters can be used as disaster warning indicators in rock. Multi-mode joint monitoring and a comprehensive analysis of multi-physical information are beneficial to accurately determine the precursor points of rock failure disaster. [ABSTRACT FROM AUTHOR]

Paper is a composite of fibers, air and additives where the fiber/fiber joints keep the network structure together. A study was undertaken to establish the link between the properties of the contact zone between fibers and paper performance under mechanical loading. The contact zone between fibers was investigated using light microscopy. A staining technique was developed for evaluating the influence of surface charge on fiber/fiber joint strength. The joint strength was linearly correlated with paper tensile strength and with the average amplitude of the acoustic events measured by acoustic emission testing. The fiber surface conformability was improved by changing the surface charge. This resulted in increased fiber/fiber joint strength as the relative contact area became larger. Increasing the molecular adhesion in the contact zone with the aid of strength additives also improved the fiber/fiber joint strength. [ABSTRACT FROM AUTHOR]

A fiber optic interferometric sensor with an intrinsic transducer along a length of the fiber is presented for ultrasound measurements of the acoustic emission from partial discharges inside oil-filled power apparatus. The sensor is designed for high sensitivity measurements in a harsh electromagnetic field environment, with wide temperature changes and immersion in oil. It allows enough sensitivity for the application, for which the acoustic pressure is in the range of units of Pa at a frequency of 150 kHz. In addition, the accessibility to the sensing region is guaranteed by immune fiber-optic cables and the optical phase sensor output. The sensor design is a compact and rugged coil of fiber. In addition to a complete calibration, the in-situ results show that two types of partial discharges are measured through their acoustic emissions with the sensor immersed in oil.

Softness is one of the essential properties of hygiene tissue products. Reliably measuring it is of utmost importance to ensure the balance between customer expectations and cost-effective tissue production. This study presents a method for assessing softness by analyzing acoustic emissions produced while tearing a tissue specimen. The aim was to train neural network models using the corrected results of human panel tests as the ground truth labels and to predict the tissue softness in two- and three-class recognition tasks. We also investigate the possibility of predicting some production parameters related to the softness property. The results proved that tissue softness and production parameters could be reliably estimated only by the tearing noise. [ABSTRACT FROM AUTHOR]

Abstract  In this study, a simplified Acoustic Emission (AE) equipment, in essence an AE signal conditioner and a USB (Universal Serial Bus) data acquisition system, is used to study what happens in paper structures during mechanical loading. By the use of such equipment, some parameters that can be extracted are e.g. the stress and strain at onset of AE, the stress and strain at the onset of rapid AE defined as some numerical factor (larger then one) times the initial emission rate, the emission rate at the first stage of loading and the stress and strain at final failure i.e. when the specimen loses its load carrying ability.In this study however, the interest is focused on one particular parameter i.e. the elastic strain energy density W c at onset of AE. This is a parameter with a clear physical meaning and in this study, the correlation between this parameter and a fracture toughness measure, is investigated.The conclusion is that when nine different paper materials (with a large span regarding properties) are considered, there is a correlation (however not linear) between these two parameters. [ABSTRACT FROM AUTHOR]

An original partial discharge generated in oil insulation identification methodology based on simultaneously conducted measurements using electrical method, ultra high frequency method and acoustic emission method is presented in the paper. Three different partial discharge model sources as well as measuring instruments commonly applied for partial discharge detection in electrical power transformers are yielded within a laboratory research. Total of 45 scenarios, including proposed spark gap configurations, selected supply voltage levels and UHF frequencies are analyzed during measurements series. Furthermore, form among total of 93 descriptors assigned for every applied partial discharge model source configuration there are 24 proposed as potentially useful for partial discharge identification applications with their 95% confidence bounds. Attempt of discriminative descriptors selection for partial discharge source analysis in on-site transformer applications as well as a proposal of unique descriptors according to every selected spark gap configuration that could be potentially useful for partial discharge identification purposes are the main purpose of the presented paper. The proposed methodology verification on a real life transformer with particular consideration of the selected descriptors potential utility in the fields of partial discharge detection and identification in electrical power industry applications confirmed a proposed methodology usefulness. [ABSTRACT FROM AUTHOR]

Cracking in dryers has long been a challenge in the pulp and paper industry. The acoustic emission (AE) technique, which is capable of supplying information regarding the cracking behaviour of metal objects, can be used to reduce or prevent dryer failure. This study applies AE testing to a paper dryer made of grey cast iron in China. To realise this task, the AE characteristics of the cast iron dryer were examined by accomplishing three main work parts: (i) in the lab part, basic AE signatures from the dryer shell material were characterised; (ii) in the artificial crack test part, AE features from the crack were obtained and the AE location of the crack in the dryer was tested; (iii) in the field part, the basic procedure for testing the paper dryer under hydrostatic test conditions was verified based on the analysis of parts I and II. The results indicate that grey cast iron is a good AE emitter. The tensile test revealed that the AE responses are active and the AE sources include the deformation of pearlite, decohesion and fracture of several graphite flakes and microcrack growth. The AE attenuation in the dryer is not severe and the cracks in the dryer during hydraulic testing exhibit an active AE response. Additionally, an accurate crack location was obtained by using the cylindrical location method. These results can provide useful information for AE inspection on structures made of cast iron. [ABSTRACT FROM AUTHOR]

The article presents the results concerning the use of clustering methods to identify signals of acoustic emission (AE) generated by partial discharge (PD) in oil-paper insulation. The conducted testing featured qualitative analysis of the following clustering methods: single linkage, complete linkage, average linkage, centroid linkage and Ward linkage. The purpose of the analysis was to search the tested series of AE signal measurements, deriving from three various PD forms, for elements of grouping (clusters), which are most similar to one another and maximally different than in other groups in terms of a specific feature or adopted criteria. Then, the conducted clustering was used as a basis for attempting to assess the effectiveness of identification of particular PD forms that modelled exemplary defects of the power transformer's oil-paper insulation system. The relevant analyses and simulations were conducted using the Matlab estimation environment and the clustering procedures available in it. The conducted tests featured analyses of the results of the series of measurements of acoustic emissions generated by the basic PD forms, which were obtained in laboratory conditions using spark gap systems that modelled the defects of the power transformer's oil-paper insulation. [ABSTRACT FROM AUTHOR]

Results of a comparative analysis of two non-dimensional coefficients, calculated based on signals emitted by partial discharges (PD) are presented in the paper. The PD were generated using setups for modeling of three basic types of PD sources, which can occur in paper-oil insulation in power transformers. The following measuring methods were considered: electrical, ultra-high frequency, acoustic emission, and optical spectrophotometry. All measurements, for each of the PD-source configuration using the various methods, were conducted simultaneously in a laboratory under same measurement conditions. Based on the gathered results it was stated that it is possible to recognize the partial discharges form based on the non-dimensional coefficients, which differ in value for all of the considered methods except for the acoustic emission. The main contribution of the research performed lies in the simplicity of the applied signal processing procedure, which can be adopted to a device or system for diagnosis of partial discharges occurring in paper-oil insulation. [ABSTRACT FROM AUTHOR]

Crack inclination and material heterogeneity have important effects on the meso-mechanical mechanism and macroscopic mechanical behavior of rock-like materials. In order to study the failure characteristics of shotcrete body during the process of using shotcrete bolt mesh support in the deep fractured rock mass of Lannigou Gold Mine, this paper combined the Digital Image Processing Technique (DIP) and RFPA2D (Rock Failure Process Analysis System) to establish a real meso-structure numerical model of concrete with different inclination angle cracks, simulating its crack propagation law and failure process, and studied the influence of crack geometry distribution and meso-heterogeneity on the effect of concrete structure. The findings reveal that the crack inclination angle has a substantial impact on concrete materials' compressive strength and elastic modulus, and both of them all show a nonlinear increase with the increase of crack angle; Because of the inhomogeneity of the materials, the inclination and propagation pathways of wing cracks are random, and the aggregate inhibits crack initiation and propagation. The wing crack's initiation position moves closer to the tip as the crack inclination angle increases, and the length gets shorter; Acoustic emission(AE) evolution characteristics are similar in samples with varying dip angles. In the early stages of loading, the AE energy is minimal, and increases rapidly when approaching the peak stress. The fractal dimension was used to describe the damage evolution process inside the material, and a damage variable index (ω) based on the fractal theory was proposed. The more the ω, the greater the material's degree of degradation. The proposed index provided a new method for quantitative study of the damage evolution characteristics of rock-like materials. It has guiding significance for the research on the stability of wet shotcrete in the deep fractured rock mass of Lannigou Gold Mine. [ABSTRACT FROM AUTHOR]

This paper addresses classifying different common partial discharge (PD) types under different acoustic emission (AE) measurement conditions. Four types of PDs are considered for the multi-class classification problem, namely; PD from a sharp point to ground plane, surface discharge, PD from a void in the insulation, and PD from semi parallel planes. The collected AE signals are processed using pattern classification techniques to identify their corresponding PD types. The measurement conditions include the influences of various PD locations, oil temperatures, and having a barrier in the line-of-sight between the PD source and the AE sensor. A recognition rate of 94% is achieved when classifying the different PD types measured at the same conditions. In addition, it has been found that the different PD source locations, oil temperatures, and barrier insertion have an impact on the recognition rate. However, by including AE samples at these different conditions in the training process, a recognition rate around 90% for all cases is achieved. [ABSTRACT FROM AUTHOR]

The article presents the discussion on Insight's current awareness service covering British and international publications, conference proceedings, and multimedia products.

Abstract: An experimental investigation is performed and analyzed in order to examine the onset and evolution of damage processes in thin isotropic paper sheets made of mechanical pulp. A microscopy technique has been used to estimate the relative fraction of bond and fibre breaks. It has been found that the active damage mechanism is bond failure, hence supporting the assumption of an isotropic scalar valued damage variable. All experiments have been performed by simultaneous with the mechanical loading monitoring the acoustic emission activity. Three different experimental setups have been designed offering the possibility to analyze the influence of stress gradients, as well as different levels of the ratios between the in-plane normal stresses, on the onset of damage. It is concluded that stress gradients in the paper specimens have a large influence on the onset of damage. When stress gradients are present a non-local theory has to be used in the analysis. In this way compliance with an isotropic damage criterion is achieved. The characteristic length, determining the gradient sensitivity, has been found to be of the same order of magnitude as some average fibre length. To study the evolution of the damage processes, wide and short specimens have been loaded in tension resulting in stable damage processes. With the assumptions made regarding the mechanical behavior of the paper material after onset of damage, the damage and the cumulative number of acoustic events curve correlates very well. The experimentally obtained data is used to determine material parameters in a proposed damage evolution law. It is found that the assumed damage evolution law can, for isotropic paper materials with bond rupture as the prevalent failure mechanism, be further simplified as only one specific material dependent damage evolution parameter has to be determined in experiments. [Copyright &y& Elsevier]

An acoustic emission technique is used to quantify and position microfracture events ahead of a growing opening mode crack in paper materials containing different amounts of added starch. A mechanical model based on gradient-enhanced elasticity, containing an intrinsic length parameter reflecting the fibre-based materials microstructure, is applied to analyse the results. It is found in experiments that the addition of starch increases the tensile strength of paper significantly while the level of onset of microfracture nucleation at the crack-tip is only slightly increased. It is also found that the height of the process zone (zone in which microfractures ahead of the crack predominantly take place), measured from the crack plane, decreases with increasing amount of starch. The experimental and analytical results suggest that adding cationic starch to paper reduces the material’s sensitivity to gradients in the stress and strain fields and making the fibre network material more ‘continuum-like’. The experimental observations are shown to be qualitatively in agreement with the numerical results and lend confidence to the applied model. [ABSTRACT FROM AUTHOR]

This research aimed to investigate the accuracy of picking of P-wave arrival times in rock fracture acoustic emission signals. In order to simulate the mining scenario, Gaussian white noise and pulse noise were added to the data collected in the laboratory. Complete ensemble empirical mode decomposition with adaptive noise + Wavelet (CEEMDAN + Wavelet) was improved in this paper, where the Spearman rank correlation coefficient was adopted to effectively select intrinsic mode functions for denoising which retained the inherent characteristics of the rock fracture signal. The absolute amplitude and energy change rate of the envelope signal, calculated based on the Hilbert transform, were used as the input of the short term average/long term average (STA/LTA) normalization algorithm to pickup the P-wave arrival time. The reliability of this method was tested on 30 groups of recorded rock fracture laboratory data and 60 groups of added noise data. Taking the manual pickup results as the standard, the errors of CEEMDAN + Wavelet + STA/LTA + AIC (Akaike information criterion) method with the absolute amplitude of the signal as the input are all within 10 ms, and 86.67% of the results are within 5 ms. The method proposed in this paper effectively addressing the issue of false pickup caused by the sensitivity of AIC and traditional STA/LTA method for strong noise, and achieving relatively high accuracy and stability in processing low signal-to-noise ratio signals. This work contributes to monitor microscopic changes in rock bodies and is of great significance for the prediction and monitoring of geological disasters. [ABSTRACT FROM AUTHOR]

The aim of this work is to assess the opportunity to use untreated waste office paper, alone and in combination with jute fabric, as a reinforcement in epoxy composites. Five different stacking sequences were manufactured and tested. Adding untreated waste office paper sheets has been revealed to increase both flexural and tensile strength of the neat resin and of the untreated jute fabric reinforced composites. The effect of the hybridization on tensile and flexural behavior has been evaluated through scanning electron microscopy observations and acoustic emission. The results confirm that waste office paper sheets can be used as a reinforcement for an epoxy resin, thus representing a viable alternative to paper recycling. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011 [ABSTRACT FROM AUTHOR]

The Niutitang Formation shale is often filled with calcite minerals, which significantly affects the physical and mechanical properties of shale reservoirs. To correctly understand the microscale fracture characteristics of the Niutitang Formation shale and the evolution of acoustic emission signals, this paper uses digital image processing technology to characterize the geometric characteristics and nonuniform distribution of calcite minerals in the shale at the microscale and then maps it to finite elements; uniaxial compression tests of different calcite vein inclination angles are carried out on a microscale. The results show that under the microscale structure, the changes in compressive strength and brittleness index of the Niutitang Formation shale with different calcite vein dip angles are all N-shaped. The calcite veins affect the distribution of the stress field, leading to significant differences in the shale fracture process and fracture mode. The shale fracture process can be divided into two types. The first type (0°, 15°, 30°, 45°) is that the shale matrix is destroyed first, and then, the calcite veins are destroyed; the second type (60°, 75°, 90°) is that the calcite veins are destroyed first, and then, the shale matrix is destroyed. Shale fracture modes can be divided into w-type, v-type, inverted v-type, and inverted z-type. The inclination angle of calcite veins has a significant influence on the AE evolution characteristics of the Niutitang Formation shale. According to the characteristics of the AE active period, it can be divided into two types: surge type and step type. The surge type has a short active period, the number of AE count surges is small, the AE peak is large, and the failure mode is relatively simple. The step type has a long active period, the number of AE count surges is large, and the AE peak is small, and the failure mode is relatively complicated. The research results provide important theoretical guidance for shale gas fracturing mining. [ABSTRACT FROM AUTHOR]

W. Zhu et al. in the review article entitled "Numerical Simulation on Damage and Failure Mechanism of Rock under Combined Multiple Strain Rates" reviewed the state of the art of rock damage and failure under different strain rates, summarized the corresponding numerical models, and presented some numerical examples to provide insights into the rock failure mechanism. The paper by B. Li et al. entitled "Discriminant Model of Coal Mining Microseismic and Blasting Signals Based on Waveform Characteristics" established a discriminant model for coal mining MS and blasting signals by using the Fisher linear discriminant method. J. Zhang in the paper entitled "Investigation of Relation between Fracture Scale and Acoustic Emission Time-Frequency Parameters in Rocks" investigated the relation between fracture scale and AE time-frequency parameters in rocks through granite uniaxial compression. [Extracted from the article]

In the petroleum and coal industries, digital image technology and acoustic emission technology are employed to study rock properties, but both exhibit flaws during data processing. Digital image technology is vulnerable to interference from fractures and scaling, leading to potential loss of image data; while acoustic emission technology is not hindered by these issues, noise from rock destruction can interfere with the electrical signals, causing errors. The monitoring errors of these techniques can undermine the effectiveness of rock damage analysis. To address this issue, this paper focuses on the restoration of image data acquired through digital image technology, leveraging deep learning techniques, and using soft and hard rocks made of similar materials as research subjects, an improved Incremental Transformer image algorithm is employed to repair distorted or missing strain nephograms during uniaxial compression experiments. The concrete implementation entails using a comprehensive training set of strain nephograms derived from digital image technology, fabricating masks for absent image segments, and predicting strain nephograms with full strain detail. Additionally, we adopt deep separable convolutional networks to optimize the algorithm's operational efficiency. Based on this, the analysis of rock damage is conducted using the repaired strain nephograms, achieving a closer correlation with the actual physical processes of rock damage compared to conventional digital image technology and acoustic emission techniques. The improved incremental Transformer algorithm presented in this paper will contribute to enhancing the efficiency of digital image technology in the realm of rock damage, saving time and money, and offering an innovative approach to traditional rock damage analysis. [ABSTRACT FROM AUTHOR]

Monitoring the condition of the grinding wheel in real-time during the grinding process is crucial as it directly impacts the precision and quality of the workpiece. Deep learning technology plays a vital role in analyzing the changes in sensor signals and identifying grinding wheel wear during the grinding process. Therefore, this paper innovatively proposes a grinding wheel wear recognition method based on Variational Mode Decomposition (VMD) denoising and Aquila Optimizer—Convolutional Neural Network—Long Short-Term Memory (AO-CNN-LSTM). The paper utilizes Acoustic Emission (AE) signals generated during grinding to identify the condition of the grinding wheel. To address noise interference, the study introduces the VMD algorithm for denoising the sample dataset, enhancing the effectiveness of neural network training. Subsequently, the dataset is fed into the designed Convolutional Neural Network—Long Short-Term Memory (CNN-LSTM) structure with AO-optimized parameters. Experimental results demonstrate that this method achieves high accuracy and performance. [ABSTRACT FROM AUTHOR]

This paper is dedicated to the memory of Dr. Miklós Iványi, who instilled in the authors an appreciation for experimental investigations, which are foundational to understanding material and structural behavior. Timber-concrete composite structures are increasingly adopted for new buildings due to their favorable sustainability parameters and the increased availability of cross laminated timber. For larger spans, however, solid timber floors lead to higher timber volumes and the use of glulam beams may become necessary for a more efficient use of wood. This paper presents laboratory tests of glulam-concrete composite beams and is the first in a series of two papers on investigating the associated failure mechanisms. Three full-scale glulam-concrete beam specimens were studied. The glulam and concrete are monolithically interconnected using a continuous layer of adhesive. Shear reinforcement was added to the glulam beams to allow for failure mode control. Static load tests to failure were conducted along with acoustic emission monitoring to track the progression of the failure. The results indicate that the shear reinforcement of the glulam layer affects the load capacity of the composite beam through shifting the failure from a shear to a tension failure mode. Similar glulam-concrete beams can enable larger span applications for buildings and bridges while maintaining an attractive sustainability performance. [ABSTRACT FROM AUTHOR]

A fiber optic interferometric sensor with an intrinsic transducer along a length of the fiber is presented for ultrasound measurements of the acoustic emission from partial discharges inside oil-filled power apparatus. The sensor is designed for high sensitivity measurements in a harsh electromagnetic field environment, with wide temperature changes and immersion in oil. It allows enough sensitivity for the application, for which the acoustic pressure is in the range of units of Pa at a frequency of 150 kHz. In addition, the accessibility to the sensing region is guaranteed by immune fiber-optic cables and the optical phase sensor output. The sensor design is a compact and rugged coil of fiber. In addition to a complete calibration, the in-situ results show that two types of partial discharges are measured through their acoustic emissions with the sensor immersed in oil. [ABSTRACT FROM AUTHOR]

Bolted joints are widely used in various engineering structures. The bolted joint may become loosening under long-term oscillating load, and cause reciprocating friction between the contact interfaces. Acoustic emission (AE) is a phenomenon of rapid release of transient elastic waves, which will be generated continuously during the reciprocating friction. The friction conditions will affect the characteristics of the contact interface and the related AE signals. Therefore, analyzing the quantitative relationship between friction conditions and AE signal is significant for applying AE technique in bolt loosening monitoring. However, researches on the relationship between AE Vrms and friction operating parameters are mostly focused on rotating machineries currently, whether the obtained conclusions are suitable for bolted joints is not clear. This paper finds that the commonly used quantitative relationship between the AE Vrms and friction operating parameters is not suitable for bolted joint structures by comparing the theoretical and experimental AE Vrms. The relationship is then modified through exponential parameter fitting and verified using the same experiments in this paper. The results show that the modified equation can accurately describe the quantitative relationship between the AE Vrms and the friction operating parameters, thus revealing the mechanism of acoustic emission signals generated during the gross-slip. [ABSTRACT FROM AUTHOR]

Deep rock are often in a true triaxial stress state. Studying the impacts of varying unloading speeds on their strain energy (SE) density is highly significant for predicting rock stability. Through true triaxial unloading principal stress experiments and true triaxial stress equilibrium unloading experiments on sandstone, this paper proposes a method to compute the SE density in a true triaxial compressive unloading principal stress test. This method aims to analyze the SE variation in rocks under the action of true triaxial unloading principal stresses. Acoustic emission is used to verify the correctness of the SE density calculation method in this paper. This study found that: (1) Unloading in one principal stress direction causes the SE density to rise in the other principal stress directions. This rise in SE, depending on its reversibility, can be categorized into elastic and dissipated SE. (2)When unloading principal stresses, the released elastic SE density in the unloading direction is influence by the stress path and rate. (3) The higher the unloading speed will leads to greater increases in the input SE density, elastic SE density, and dissipative SE density in the other principal stress directions. (4) The dissipated SE generated under true triaxial compression by unloading the principal stress is positively correlated with the damage to the rock; with an increase in unloading rate, there is a corresponding increase in the formation of cracks after unloading. (5) Utilizing the stress balance unloading test, we propose a calculation method for SE density in true triaxial unloading principal stress tests. [ABSTRACT FROM AUTHOR]

Purpose: Based on the micro-electro-mechanical system (MEMS) technology, acoustic emission sensors have gained popularity owing to their small size, consistency, affordability and easy integration. This study aims to provide direction for the advancement of MEMS acoustic emission sensors and predict their future potential for structural health detection of microprecision instruments. Design/methodology/approach: This paper summarizes the recent research progress of three MEMS acoustic emission sensors, compares their individual strengths and weaknesses, analyzes their research focus and predicts their development trend in the future. Findings: Piezoresistive, piezoelectric and capacitive MEMS acoustic emission sensors are the three main streams of MEMS acoustic emission sensors, which have their own advantages and disadvantages. The existing research has not been applied in practice, and MEMS acoustic emission sensor still needs further research in the aspects of wide frequency/high sensitivity, good robustness and integration with complementary metal oxide semiconductor. MEMS acoustic emission sensor has great development potential. Originality/value: In this paper, the existing research achievements of MEMS acoustic emission sensors are described systematically, and the further development direction of MEMS acoustic emission sensors in the future research field is pointed out. It provides an important reference value for the actual weak acoustic emission signal detection in narrow structures. [ABSTRACT FROM AUTHOR]

Aiming at the problem of fault diagnosis and classification of rolling bearing and gear of gearboxes, a novel method based on matrix distance features of Gramian angular field (GAF) image is proposed based on sliding window compressible GAF transformation. The method converts the one-dimensional fault signal into a two-dimensional feature matrix and constructs the discrimination matrix of each fault category by establishing the mean value of the feature matrix of a priori samples. For the new sampled signal, after converting it into a two-dimensional feature matrix, the feature matrix is obtained. The fault classification is carried out by using the matrix distance between feature matrix and the discrimination matrix of each category. The method is validated by the test data of Case Western Reserve University and the acoustic emission data from a gearbox test bench. The classification accuracy is 99.17% and 95.71%, which presented the feasibility and effectiveness of the novel method proposed in this paper. [ABSTRACT FROM AUTHOR]

Ignition advance angle is one of the important factors affecting the performance of the engine, when it occurs abnormally will make the engine power and economy worse, and even cause serious damage to the engine. Therefore, it is very necessary to recognize the abnormal ignition advance angle of the engine. However, the engine system is closed and has a complex structure, which makes traditional diagnostic methods difficult. This paper proposes an intelligent identification method based on acoustic emission (AE) signals, which collects the AE signals from the engine surface and divides their spectra into equal parts, and selects the frequency bands with high contribution to the classification based on the minimum distance method to construct feature maps, which is used as the input to the convolutional neural network (CNN). The extracted frequency band features of this method can better characterize the AE signals, and the constructed feature maps make the fault information more obvious. Experiments show that the accuracy of this method for abnormal ignition advance angle under normal operating conditions of piston aero-engine is 100%, which is better than the traditional methods. In addition, the recognition accuracies under the other two operating conditions are 99.75% and 98.5%, respectively, indicating that the method has a certain universality. [ABSTRACT FROM AUTHOR]

In this paper, preliminary studies on the failure analysis of hybrid composite materials utilizing acoustic emission and machine learning are presented. The main purpose of this study was to analyze the possibilities of using machine learning techniques as a way to better cluster the data obtained from acoustic emission. In this paper, we focus on data preparation, feature extraction (Laplacian score), determination of cluster number (Caliński–Harabasz, Silhouette, and Davies–Bouldin), and testing three clustering techniques, namely K-means, fuzzy C-means, and spectral clustering. The dataset was obtained by testing fiber metal laminates—composites consisting of metal and composite layers. Two experimental tests were realized on pre-cracked rectangular specimens—one with loading in mode I and one with loading in mode II (DCB—double cantilever beam and ENF—end-notch flexural test). Elastic waves were recorded during these tests via an acoustic emission system. Preliminary studies show that the proposed method can be used successfully to cluster data obtained in this way. The obtained dataset was split into 3 clusters (for the ENF test) and 5 clusters (DCB test). In the next stages of the research campaign, based on the presented results, we intend to change the approach to semi-supervised by running additional single-cause damage tests to enhance the achieved results and enable easier damage recognition. [ABSTRACT FROM AUTHOR]

Wind power is growing rapidly as a green and clean energy source. As the core part of a wind turbine, the blades are subjected to enormous stress in harsh environments over a long period of time and are therefore extremely susceptible to damage, while at the same time, they are costly, so it is important to monitor their damage in a timely manner. This paper is based on the detection of blade damage using acoustic emission signals, which can detect early minor damage and internal damage to the blades. Instead of conventional piezoelectric sensors, we use fiber optic gratings as sensing units, which have the advantage of small size and corrosion resistance. Furthermore, the sensitivity of the system is doubled by replacing the conventional FBG (fiber Bragg grating) with a π-phase-shifted FBG. For the noise problem existing in the system, this paper combines the traditional WPD (wavelet packet decomposition) denoising method with EMD (empirical mode decomposition) to achieve a better noise reduction effect. Finally, small wind turbine blades are used in the experiment and their acoustic emission signals with different damage are collected for feature analysis, which sets the stage for the subsequent detection of different damage degrees and types. [ABSTRACT FROM AUTHOR]

Due to the extremely low permeability of shale reservoirs, large-scale reservoir fracturing is required. Hydraulic fracturing is one of the most important technologies in shale gas exploration and development. In this paper, the acoustic emission energy and the number of location and fracture surface morphology of specimens before and after fracture are studied through hydraulic sand fracturing test. The test results show that: (1) the energy ratio obtained during hydraulic fracturing without proppant is the smallest, and increasing the confining pressure, as well as reducing the displacement and viscosity of the fracturing fluid will cause the energy ratio to decrease. From the perspective of acoustic emission energy, the proppant play an important role in the generation of fractures during hydraulic sand fracturing; (2) when the confining pressure increases, the number of shale specimens before and after rupture is the largest, but the total number of locating events is smaller than the sanding ratio increased; there is no proppant hydraulic fracturing, the number of specimens before and after the rupture is the largest. And the total number reached the minimum, indicating that the proppant can play an important role in the hydraulic sand fracturing test; (3) the sand is relatively large, the specific surface and standard deviation both reach the maximum, indicating that the fracture surface roughness is the largest under the test condition, and the fracturing effect is the best, but the specific surface and standard deviation are the minimum when fracturing without proppant, so indicating that the fracture surface fracturing effect is the worst at this time. [ABSTRACT FROM AUTHOR]

Wound rotor induction machine (WRIM) has been extensively used in different applications such as medium-power wind turbines and traction systems. Since these machines work under harsh and difficult conditions, condition monitoring of such systems is crucial. Different electrical and mechanical signatures of machines were used for electrical and mechanical fault detection in electrical machines such as vibration, acoustic emission, stray flux, and stator current signature. In recent years, stator current signature analysis due to simplicity, cost-effectiveness, and availability has been considered for fault detection process in comparison with previous conventional methods such as acoustic and vibration. In this paper, a high-resolution technique based on the chirp-Z transform is used for rotor asymmetry fault (RAF) detection in induction machines through stator current signature analysis. In this regard, the Teager-Kaiser energy operator (TKEO) technique for demodulation fault characteristic frequency is used as a pre-processing stage to avoid leakage of the supply frequency. The method has better accuracy due to better spectral resolution and resolvability. Furthermore, computational complexity in the proposed method will be reduced in comparison to the previous conventional ones which have used the Fast Fourier transform (FFT). The proposed technique is tested through synthetic and experimental stator current of WRIM in healthy and faulty conditions with different rotational speeds and fault severities. The results show the validity of the proposed method in rotor asymmetry fault detection through the stator current signature of WRIM. [ABSTRACT FROM AUTHOR]

Investigating the correlation between acoustic emission (AE) parameters and damage mechanisms in rock mechanics can help understand rock damage evolution under loading and provide a theoretical basis for engineering support and safety detection. Therefore, this paper presents experimental works on the correlation between AE and failure mechanisms of rock mass under uniaxial compression stress, with the aim of capturing the damage evolution leading to a new damage constitutive model. The experimental results indicate that the uniaxial compression process of shale can be divided into four stages according to AE characteristics. AE signals are minimal during the crack compaction and elastic stages. The crack initiation strength σci, which is approximately 55% of the uniaxial compressive strength, is identified when the cumulative AE counts and damage factor begin to increase slowly. When axial stress reaches the damage strength σcd, which is approximately 80% of the uniaxial compressive strength, a significant number of AE signals are generated. AE phenomena can be observed during the unstable crack development and post-crack stages. Considering the initial damage to the rock, the damage factor D initially decreases and then increases with increasing cumulative ring-down counts rather than exhibiting a monotonic increase. The damage factor D is proportional to the cumulative AE counts N in the stage before rock failure. [ABSTRACT FROM AUTHOR]

Rock cores retrieved from deep rock masses may be permanently damaged on account of the stress release occurring during the drilling process. The quantification of core damage is important for accurate evaluation of the rock strength at depth. This paper presents a laboratory simulation of the core drilling process under high in situ stress conditions. The study aims to quantitatively evaluate sampling damage from both macro and micro perspectives using mechanics tests and microscopic observations. The observed decrease in core specimen integrity with increasing sampling confining pressure is in line with practical engineering findings, thus validating the experimental method utilized in this paper. The test results show that the porosity of the core increases and P-wave velocity decreases as the sampling confining pressure increases, which indicates that the structure of the core is significantly changed by the sampling damage. The stress–strain curve exhibited increased nonlinearity and acoustic emission events at the initial stage of loading, indicating an increase in sampling damage with rising sampling pressure. The uniaxial compressive strength and Brazilian tensile strength of the cores drilled at 40 MPa are reduced by about 21% and 28%, respectively, compared to the undamaged rock, indicating that the effect of core damage on the rock strength cannot be ignored. Microstructural observations further reveal that the crack density of the cores drilled at 40 MPa is four times higher than that of the intact rock. Additionally, the development of microcracks shows obvious directionality, with microcracks preferentially developing perpendicular to the drilling direction. Stress path analysis of the cores indicates that the sampling damage may be primarily caused by tensile stresses. This study provides a better understanding of the mechanisms underlying sampling damage and core disking. [ABSTRACT FROM AUTHOR]

Cavitation is a detrimental phenomenon in hydraulic machinery, adversely impacting its performance, inducing vibration and noise, and leading to corrosion damage of overflow components. Centrifugal pump internal cavitation will lead to severe vibration and noise, and not only will the performance of hydraulic machinery be adversely affected but the impact generated by the collapse of the vacuole will also cause damage to the impeller wall structure, seriously affecting the safety of the equipment's operation. To prevent the generation and development of internal cavitation in centrifugal pumps, to prevent the hydraulic machinery from being in a state of cavitation for a long time, to avoid the failure of the unit, and to realize the predictive maintenance of centrifugal pumps, therefore, it is of great significance to research the methods for monitoring the cavitation of hydraulic machinery and the methods for suppressing the cavitation. This paper comprehensively describes the centrifugal pump cavitation mechanism and associated hazards. It also discusses the current state of centrifugal pump cavitation monitoring methods, including commonly used approaches such as the flow-head method, high-speed photography, pressure pulsation method, acoustic emission method, and vibration method. A comparative analysis of these methods is presented. Additionally, the paper explores signal characterization methods for centrifugal pump cavitation, including time-domain feature extraction, frequency-domain feature extraction, and time–frequency-domain feature extraction. The current research status is elaborated upon. Moreover, the paper presents methods to mitigate cavitation and prevent its occurrence. Finally, it summarizes the ongoing research on identifying and determining the cavitation state in centrifugal pumps and offers insights into future research directions. [ABSTRACT FROM AUTHOR]

The rates and processes that lead to non-tectonic rock fracture on the Earth's surface are widely debated but poorly understood. Few, if any, studies have made the direct observations of rock fracturing under natural conditions that are necessary to directly address this problem. An instrumentation design that enables concurrent high spatial and temporal monitoring resolution of (1) diurnal environmental conditions of a natural boulder and its surroundings in addition to (2) the fracturing of that boulder under natural full-sun exposure is described herein. The surface of a fluvially transported granite boulder was instrumented with (1) six acoustic emission (AE) sensors that record micro-crack associated, elastic wave-generated activity within the three-dimensional space of the boulder, (2) eight rectangular rosette foil strain gages to measure surface strain, (3) eight thermocouples to measure surface temperature, and (4) one surface moisture sensor. Additionally, a soil moisture probe and a full weather station that measures ambient temperature, relative humidity, wind speed, wind direction, barometric pressure, insolation, and precipitation were installed adjacent to the test boulder. AE activity was continuously monitored by one logger while all other variables were acquired by a separate logger every 60 s. The protocols associated with the instrumentation, data acquisition, and analyses are discussed in detail. During the first four months, the deployed boulder experienced almost 12 000 AE events, the majority of which occur in the afternoon when temperatures are decreasing. This paper presents preliminary data that illustrates data validity and typical patterns and behaviors observed. This system offers the potential to (1) obtain an unprecedented record of the natural conditions under which rocks fracture and (2) decipher the mechanical processes that lead to rock fracture at a variety of temporal scales under a range of natural conditions. [ABSTRACT FROM AUTHOR]