Detecting hazardous sources of acoustic-emission signals using the estimated energy of clusters

A method for detecting hazardous sources of acoustic-emission (AE) signals by the level of their energy activity using clustering by digitized signal shape was considered. The influence of the distance between a source and an AE transducer on the energy of recorded AE signals was analyzed. The energy distribution median of signals in a cluster was proposed for evaluating the hazard of an AE signal source. The application of the developed method was tested based on the example of the analysis of AE inspection data on the welding of steel specimens with incomplete fusion and a crack at the root of a weld seam. This testing confirms the results of the fractographic inspection of a defective weld seam.     

钢板声发射时间反转聚焦增强定位方法

声发射检测方法具有实时动态监测优点,应用越来越广泛,但是对声源的定位始终没有更大的突破。在钢板声发射检测中,提出一种基于时间反转理论的声发射源准确定位的方法。由于声发射检测是一种被动检测技术,结合时间反转聚焦理论,推导出对声源信号实现时间反转聚焦增强处理方法,可增强检测信号中声源幅值,提高信噪比;然后根据声源信号到达时间推算出声源聚焦时刻,利用弹性波传播理论对传感器监测区域重建信号传播波动图,显示出声源位置和区域;最后通过实验测试对该方法进行验证,结果表明该方法能有效提高损伤声源信号的能量,对检测区域的信号重建和定位显示准确地给出损伤声源位置。     

Application of the Spectral Analysis of Acoustic Emission Signals to Studies of Vulnerability of TiN Coatings on Steel Substrates

A technique has been suggested for processing spectra of acoustic emission (AE) signals based on a signal classification using shapes of normalized spectral density curves. This enables one to calculate averaged spectral images of AE signal groups, which characterize specific types of AE sources, and to estimate intensities of various emission sources on various stages of deformation. The suggested technique has been used in estimating the TiN vulnerability when it is strained concurrently with the substrate.     

Acoustic emission mapping of diesel engines for spatially located time series—Part II: Spatial reconstitution

In this study the characteristics of AE wave transmission around and through the cylinder head of a small four-stroke fuel injection diesel engine are investigated. Two sets of measurements have been carried out, one with simulated sources at various points on the cylinder head and one with the engine running, using a nine-sensor array. Propagation of AE waves from the simulated sources to the array sensor positions indicates attenuation factors of around 8.5. It is important to be able to estimate source–sensor distance accurately and this has been done using a threshold technique to identify the arrival time of a low frequency high amplitude wave at the sensors, then to deduce the wave speed from that information and hence calculate the source–sensor distance (transmission path length). Engine running tests were carried out and analysis focused on reconstitution of injector and exhaust valve opening events using signal mapping techniques. For injector events, the attenuation factors were similar to those measured from the simulated sources. For exhaust valve-opening events the attenuation factors varied between 5 and 7 with relatively poor correlation. This difference is thought to be due to variation in the actual source position during valve opening because the exhaust valve actuation involves a cam, push rod and rocker design. The results can be used to reconstitute the timing and amplitude of the AE emitted at the source which enables much more focussed monitoring of specific components and processes identified in the signals.     

RETRACTED ARTICLE: Development and application of intensified envelope analysis for the condition monitoring system using acoustic emission signal

The application of the high-frequency acoustic-emission (AE) technique in the condition monitoring of rotating machinery has been increasing of late. It has a major drawback, though, the attenuation of the signal, and as such, the AE sensor has to be close to its source. Two signal-processing methods, envelope analysis and wavelet transform, were found to be useful for detecting faults in the rolling element bearing and gearboxes. These methods have a disadvantage, though: their application is focused only on a component of the assembled machine. For example, envelope analysis is a powerful method for detecting faults in the bearing system, but it is not proper for use in the gear system. Thus, these methods could not be used to detect combined faults in the common assembled machines. Therefore, we propose a signal-processing method consisting of envelope analysis and DWT (discrete wavelet transform). In addition, a novel mother function optimized for the AE signal for DWT was extracted through a fatigue crack growth test, and is also proposed herein. Then the proposed method, called intensified envelope analysis (IEA), was used to detect the faults in the rolling element bearing and rotating shaft. According to the results, IEA can be a better signal processing method for the condition monitoring system using AE technique.     

无须测量声速的声发射源定位方法研究

为消除声速测量偏差给声发射系统带来的定位误差，本文提出一种多探头定位方法。从理论上导出了该方法的线定位和平面定位计算公式，并用AE21C型四通道声发射仪在碳钢管道和平板上以铅笔芯折断产生信号为模拟源进行了实验验证，结果表明用这种新的方法具有较高的定位精度，且定位时只要利用原系统的门槛跨越技术测量各探头接收到信号的时差即可，不必测量传声媒质的声速。     

Analysis of acoustic emission in precision and high-efficiency grinding technology

Current demands of machining hard and brittle materials at very small tolerances have predicated the need for precision and high-efficiency grinding. In situ monitoring systems based on acoustic emission (AE) provide a new way to control the surface damage and integrality of the components. However, a high degree of confidence and reliability in characterizing the manufacturing process is required for AE to be utilized as a monitoring tool. The authors established AE based online monitoring system and studied technique parameters versus the waveforms of AE under different working conditions. The results show that there are obvious mapping relations between the technique parameters of grinding and the effective values of the AE signals. Grinding along different directions would result in different strength of AE signal. Comparing with grinding along first longitude, fewer AE signal is released when grinding along latitude and better surface quality is generated. Similar variation tendency is observed no matter between AE root mean square (RMS) and linear speed or between surface roughness and linear speed which justify some kind of correlation may exist between AE RMS and surface roughness. The distance between the AE transducer and the AE source should be less than 80 mm while monitoring the process of grinding composite ceramics.     

基于小波分析的声发射源定位技术

声发射全波形采集技术为基于波形分析的声源定位方法提供了可能。在板状构件中声波的传播模式较为复杂,且不同模式的波到达时间和波速均不相同,从而带来了声源定位误差。将时频幅度分析方法引入声发射源定位技术：从接收到的信号中提取出某一频率的柔性波随时间变化的规律,在理论分析的基础上证明,这个分离信号的最大幅值点所对应的时间就是该频率柔性波群速度的到达时间。根据这个到达时间,以及实际测量出的群速度就可以实现声发射源更精确的定位,试验结果也证明了这种方法的可靠性。     

Using a probabilistic model to estimate the reliability of locating acoustic emission sources

A probabilistic model for estimating the error in determining the coordinates of acoustic emission (AE) sources based on experimental data is considered. A spherical indentor was pressed in a test object to obtain a large number of AE signals. Processing of signal parameters has made it possible to reveal the dependence of the likelihood of determining the coordinate with a prescribed accuracy on the maximum amplitude and AE-signal rise time. The possibility for choosing the method of detection of the AE-signal time of arrival at receivers depending on the signal parameters has also been examined.     

A study of acoustic emission generated during orthogonal metal cutting—1: Energy analysis

The application of acoustic emission (AE) sensing in metal cutting process monitoring requires a knowledge of the signal dependence on the variables encountered in the process and an understanding of the source mechanisms responsible for AE generation. In this paper, we study the dependence of the AE signal energy on orthogonal machining variables such as cutting velocity, uncut chip thickness and the chip-tool contact length. Controlled contact length tools were used in orthogonal machining of tubular 6061-T6 aluminum, at varying cutting velocities and feed rates (the feed rate in this case is equal to the uncut chip thickness). The root mean square (RMS) value of the AE signal was found to be linearly proportional to the cutting velocity. Based on this observation, the damping of dislocation motions is proposed as a possible AE source mechanism at the high strain rates encountered in metal cutting. The validity of the dislocation damping based model for AE generation is supported by experimental results and observations.     

A Study on Incipient Damage Monitoring in Rolling Contact Fatigue Process Using Acoustic Emission

Acoustic emissions (AE) technique was applied to rolling contact fatigue tests of two radially loaded rollers running under constant load and velocity to detect the incipient damage and damage location. Signals detected from contacts were processed using signal conditioning and enhancement techniques by an AE source locator to bring out the difference between the signals from the sound and damaged rollers. It was found that AE hit count pulse observations by the AE source locator can provide an indication of the damage at its initial stage. The conventional AE parameters and the AE signal features were studied and correlated with the AE source locator counts. The results demonstrated the successful use of the combination of the AE monitoring and the AE source locator as a new technique for detecting the incipient damage and forecasting the position of the damage in the roller, and this technique could allow the user to monitor the rate of deterioration of the rolling elements.     

Detection of faults in gearboxes using acoustic emission signal

Vibration analysis is widely used in machinery diagnosis, and wavelet transform and envelope analysis have also been implemented in many applications to monitor machinery condition. Envelope analysis is well known as a useful tool for the detection of rolling element bearing faults, and wavelet transform is used in research to detect faults in gearboxes. These are applied for the development of the condition monitoring system for early detection of the faults generated in several key components of machinery. Early detection of the faults is a very important factor for condition monitoring and a basic component to extend CBM (Condition-Based Maintenance) to PM (Prediction Maintenance). The AE (acoustic emission) sensor has a specific characteristic on the high sensitivity of the signal, high frequency and low energy. Recently, AE technique has been applied in some studies for the early detection of machine fault. In this paper, a signal processing method for AE signal by envelope analysis with discrete wavelet transforms is proposed. Through the 15 days test using AE sensor, misalignment and bearing faults were observed and early fault stage was detected. Also, in order to find the advantage of the proposed signal processing method, the result was compared to that of the traditional envelope analysis and the accelerometer signal.     

Model development for tool wear effect on AE signal generation in micromilling

A model for the relation between the acoustic emission signal generation and tool wear was established for cutting processes in micromilling by considering the acoustic emission (AE) generation and propagation mechanisms. In addition, the effect of tool wear on the AE signal generation in frequency and amplitude was studied. In the model development, the finite element analysis was first used to calculate the shear strain rate distribution on the shear plane based on the orthogonal cutting assumption. Conversely, the contact stress distribution of workpiece on the flank wear face was established based on the Waldorf model. Following the finite element method, the dislocation density in materials was calculated based on Orowan’s law with the calculated stress rate. Finally, the AE signal detected by the sensor was calculated by considering the Gaussian probability density function for the distribution of AE source on the shear plane and the one-dimension wave equation for AE signal propagation. Based on the developed model, the effect of tool wear on the AE signal generation was investigated and compared to the experimental results. The results obtained from these investigations indicate that the proposed model can be used to predict the effect of tool wear on the AE signal generation.     

The influence of the coordinate errors of setting sensors of a piezoelectric antenna on the accuracy of localizing sources of acoustic-emission signals

The main factors that affect the error of determining the coordinates of an acoustic-emission (AE) signal source are considered. The influence of errors of determining coordinates ±Δx _i and ±Δy _i of piezoelectric-antenna transducers on the AE-signal localization accuracy are analyzed. It is theoretically and experimentally proven that the errors in the coordinates of the transducers substantially influence the AE-signal localization accuracy, especially at a low sampling frequency of the analog-to-digital converter of the AE system’s measuring channel and when low-frequency AE transducers are used.     

Face Rub-Impact Monitoring of a Dry Gas Seal Using Acoustic Emission

Face rub-impact of a dry gas seal was investigated using acoustic emission (AE) technology. A force applicator was designed and mounted on the seal test rig to provide controlled misalignment and thus induce rub-impact of the seal faces. Two types of AE sensor were mounted at different positions on the seal. For the PICO AE sensor mounted directly on the seal ring, the root mean square (RMS) of the original AE signal was sensitive to face rub-impact of the seal. When force was applied, the AE RMS of the PICO sensor gave a distinct periodic waveform with a period consistent with the rotational period above an initial noise signal. The magnitude and shape of the waveform changed as the applied force increased. For the R15α AE sensor mounted on the housing of the seal, no obvious changes could be found from the RMS of the original AE signal synchronously obtained during loading. Two kinds of signal processing methods were tried to eliminate noise. After band-pass filtering, the RMS of the AE signals of the R15α sensor indicated face rub-impact when the misalignment was relatively large. The empirical mode decomposition method using masking signals was found to be more effective than band-pass filtering in eliminating the noise but took much more computational time. The results indicate that the AE technology is a potentially effective tool in monitoring and investigating face rub-impact of dry gas seals.     

Application of the acoustic-emission and strain-gaging methods to testing of the residual strength of airplanes

The use of acoustic-emission (AE), optical, and strain-gaging methods in cyclic tests of an airplane has been considered. During tests, before the failure of an airplane, three zones were inspected. For this purpose, saw cuts were made in the lower planes of the left and right wings and in the load-carrying structure on the right side. The AE method allowed detection of growing flaws at a 10% load relative to the rated load, when the length of a fatigue crack was at most 1 mm and was not detected via the optical method.     

Application of acoustic emission technique for the detection of defects in rolling element bearings

The usefulness of acoustic emission (AE) measurements for the detection of defects in roller bearings has been investigated in the present study. Defects were simulated in the roller and inner race of the bearings by the spark erosion method. AE of bearings without defect and with defects of different sizes has been measured. For small defect sizes, ringdown counts of AE signal has been found to be a very good parameter for the detection of defects both in the inner race and roller of the bearings tested. However, the counts stopped increasing after a certain defect size. Distributions of events by ringdown counts and peak amplitudes are also found to be good indicators of bearing defect detection. With a defect on a bearing element, the distributions of events tend to be over a wider range of peak amplitudes and counts.     

Real-time detection of the breakage of small diameter drills with wavelet transform

This paper presents a real-time tool breakage detection method for small diameter drills using acoustic emission (AE) and current signals. Using the transmitted properties of the AE signal, apparatus for detecting the AE signal for tool breakage monitoring was developed for a machine centre. The features of tool breakage were obtained from the AE signal using typical signal processing methods. The continuous wavelet transform (CWT) and the discrete wavelet transform (DWT) were used to decompose the spindle current signal and the feed current signal, respectively. The tool breakage features were extracted from the decomposed signals. Experimental results show that the proposed monitoring system possessed an excellent real-time capability and a high success rate for the detection of the breakage of small diameter drills using combined AE and current signals.     

Acoustic emission source localization in plate-like structures using least-squares support vector machines with delta t feature

To deal with the difficulties of current acoustic emission (AE) source location methods, such as classical approaches based on times of arrival and artificial neural networks based on AE signal features, the least squares support vector machines (LS-SVM) approach was attempted in acoustic emission (AE) source location of plate-like structures. The AE events were produced by pencil lead breaks, and the response wave was received by piezoelectric sensors. The time of arrival, determined through the conventional threshold-crossing technique, was used to prepare delta t feature for the input to LS-SVM. Training and testing data sets were generated for the case of plates monitored by four transducers and were adopted to validate the source location methodology using LS-SVM with delta t feature. Experimental tests were carried out, with the source positioned at predetermined points evenly distributed within the plate area. A satisfactory correlation was found between the actual source locations and those predicted by the trained LS-SVM model. The results of the experiments show that the LS-SVM-based location method, with delta t feature, permits an alternative effective positioning in plate-like structures.     

基于光纤光栅阵列和MVDR算法的声发射定位

基于光纤光栅(FBG)传感器网络构建了声发射检测系统,并提出了最小方差无失真响应(MVDR)的声发射源定位方法。构建的系统由7个FBG传感器组成传感器线阵列,采用未经平坦的放大自发辐射(ASE)光源边缘滤波实现信号解调。利用Shannon小波变换从频散复杂的声发射信号中提取窄带信号,并基于MVDR算法扫描整个监测区域获取空间谱。根据空间谱函数计算输出值,并将计算的输出值作为像素值。最后,通过提取空间谱中的最大值的坐标确定声发射源的位置。在LY12铝合金板上进行了实验验证。结果表明,该方法在400mm×400mm的区域内,声发射定位的最大误差为9.4mm,平均误差为7.2mm,耗时小于3s。该系统具有较高的实时性和定位精度,是一种声发射源定位的新方法。