Proposed method of partial discharge allocation with acoustic emission sensors within power transformers

Employing acoustic emission sensors for detection of partial discharge, PD, introduces many advantages. Besides easy installation and replacement, they are non-invasive and immune to electromagnetic noise and interference and their sensitivity does not vary with object capacitance. For PD allocating utilizing AE sensors, distance calculations are based on the arrival time of acoustic waves to the sensors. Considering structure-borne waves of higher speed, the peaks of some of indirect path AE signals with significant contribution are mistakenly considered as peaks of direct path AE signals. Furthermore, the acoustic signals are propagating through certain parts of the transformer, such as the windings, and this complicates the partial discharge detection and allocation. These would imply an incorrect distance between the source and sensor. A method based on a heuristic algorithm has been proposed which considering all possible indirect paths with the relevant propagation times and all the barriers on the travel path of acoustic signal, calculates the more precise arrival times to sensors. A test chamber has been utilized and artificial PD signals are produced at various points. Output results of algorithm have been compared with results of classic method. It has been shown that proposed method significantly reduces the positioning errors.     

Identification of two simultaneous partial discharge sources in an oil-pressboard insulation system using acoustic emission techniques

Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharge (PD) causes insulation degradation and premature failure of insulation. In power apparatus, more than one PD source may be active simultaneously. The nature of insulation degradation for multiple PD sources is different from that due to single PD source. Therefore, it will be helpful for severity assessment of insulation degradation, if the number of active PD sources are identified and classified. This paper presents a method for identification and classification of two simultaneously active PD sources using acoustic emission techniques. The acoustic emission (AE) signals are measured for laboratory simulated PD in an oil-pressboard insulation system for three different electrode systems. The measurements of partial discharge acoustic emission (PDAE) signals are carried out for single PD source and for two simultaneous PD sources. The measured signals are analyzed using discrete wavelet transform (DWT), box counting fractal dimension and lacunarity. Box counting fractal dimension and lacunarity are calculated for DWT decomposed signal of major frequency band. Energy distribution in different frequency bands of DWT decomposed signal along with box counting fractal dimension and lacunarity is used for classification of two simultaneous PD sources.     

Defect detection and location in switch rails by acoustic emission and Lamb wave analysis: A feasibility study

An acoustic emission (AE) based approach is proposed in this study to identify and locate newly initiated defects or the propagation of existing defects in railroad switch rails. Defect-induced AE signals are identified through frequency analysis, as frequencies of these signals are much higher than those induced by structural vibration. Continuous wavelet transform (CWT) is employed to analyze the Lamb wave dispersion of the detected signal, so that two characteristic points can be selected on the CWT contour map to locate the defect. Using this approach, defects in a damaged switch rail can be located using a single sensor.     

基于三点弯曲试验的聚丙烯塑料颗粒混凝土 声发射分析*

为探讨掺入聚丙烯塑料颗粒(PP)对混凝土疲劳损伤的影响,以不同塑料颗粒掺量Wf (0、10%和20%)混凝土为研究对象,采用声发射技术,开展一系列三点弯曲疲劳试验。试验结果表明：掺入塑料颗粒后,混凝土疲劳寿命增大,断裂能增大,可承受的最大荷载降低,但挠度增大,塑性变形能力增强;AE（Acoustic Emission）定位的损伤源主要集中在跨中,首次峰值荷载前,AE事件偏少,AE定位可识别的内部疲劳损伤点较少,当接近疲劳破坏阶段,AE信号源急剧增加,且随着Wf越大,AE事件数量明显减少,AE事件主要出现在循环荷载波谷处;掺入塑料颗粒后,声发射信号次数显著降低,持续时间更短,且随着Wf的增加,声发射信号次数进一步降低。掺入PP塑料颗粒有助于缓解混凝土内部疲劳损伤,延长其疲劳寿命。     

声发射监测隧道围岩活动性

目的是确定隧道围岩变形破裂的活动性，保证上方近距离高层大楼的安全使用，采用EAE－04声电测试系统，以测试大楼及隧道围岩的活动性，采用声发射（AE）和电磁辐射（EME）信号上升沿时间和持续时间的关系，排除噪音等的影响，确定有效信号；采用AE频度和能量率的变化规律，EME脉冲数的变化规律，来分析隧道周围岩体的活动性并进行实时检测，为大楼及隧道的稳定性评价提供了依据。     

Dynamics of the peel front and the nature of acoustic emission during peeling of an adhesive tape

We investigate the peel front dynamics and acoustic emission (AE) of an adhesive tape within the context of a recent model by including an additional dissipative energy that mimics bursts of acoustic signals. We find that the nature of the peeling front can vary from a smooth to a stuck-peeled configuration depending on the values of dissipation coefficient, inertia of the roller, and mass of the tape. Interestingly, we find that the distribution of AE bursts shows power law statistics with two scaling regimes with increasing pull velocity as observed in experiments. In these regimes, the stuck-peeled configuration is similar to the "edge of peeling" reminiscent of a system driven to a critical state.     

Investigation of fatigue failure prediction of Fe-Cr alloy coatings under rolling contact based on acoustic emission technique

The rolling contact fatigue (RCF) failure prediction of the coating Fe-Cr alloy coatings was investigated. The acoustic emission (AE) technique was used to monitor RCF tests of the coatings. The failure mechanism was investigated. Results showed AE signals sensitively detected the initiations and propagations of the fatigue cracks within the coatings before the obvious surface material losses. AE signals also reflected the cumulate damage procedure. So the coming RCF failures can be predicted by AE signal responses. Moreover, the micro-defects within the coatings were considered to be the fatigue crack origins.     

Al2O3陶瓷涂层尖端受载下的声发射信号参量分析

为了考察再制造零件涂层结合强度检测仪评价涂层结合强度的可行性,以Al₂O₃陶瓷涂层为研究对象,在涂层表面进行压入试验,提取并分析了试验过程中声发射信号中的幅度、计数、能量与有效值电压(RMS)特性参数的时间分布曲线,读取了声发射信号突变点的波形,观测了压痕处涂层截面微观形貌。结果表明,声发射信号出现明显突变时,涂层界面确实产生了开裂失效。采用此检测设备可以有效诱导、界定涂层界面的断裂失效,声发射信号可以作为涂层开裂的临界判据,其中幅度的时间分布更能体现出Al₂O₃陶瓷涂层在压入过程中的裂纹萌生至涂层断裂的扩展过程;能量值对涂层的失效更为敏感,最为适合评价涂层的结合强度。     

船舶辐射噪声的混沌现象研究

水下弱信号的检测和识别是当今水声信号处理领域中存在的难题.应用混沌、分形理论,从根空间轨迹、Lyapunov指数和关联维等方面研究了船舶辐射噪声的混饨现象,发现船舶辐射噪声信号的确存在混沌吸引子,且不同类别的信号具有不同的吸引子维数.这一结果将为水声信号处理,为水下目标探测和识别提供崭新的理论手段。     

高强度钢手工焊接后过程的声发射实时监测研究

本针对实际工艺中使用的高强度钢，重点对手工焊接的冷却过程利用声发射技术进行实时监测。本次试验是和先前在不同型号的钢板在手工焊接过程中所产生的声发射信号进行比较的基础上进行的，主要目的是寻找高强度钢在手工焊接的冷却中所产生的活性裂纹在冷却阶段的声信号特征。     

Analysis of acoustic emission signals originating from bainite and martensite formation

In this paper the characteristics of acoustic signals generated during bainite and martensite formation are studied. The results are discussed in a semi-quantitative manner, since a thorough quantitative analysis of the signals is not feasible because of the limited frequency bandwidth of the system and the effect of internal sample reflections on the signal. The frequency spectra of acoustic emission signals are interpreted using a dislocation source model adopted from acoustic emission studies of plastic deformation. It is assumed that the predominant source of acoustic emission (AE) during displacive transformations is the movement of dislocations, i.e. the slip taking place during growth in order to relieve internal stresses. The results show that the mean frequency of AE signals generated during bainite formation is significantly larger than that of martensitic AE signals. This difference in the spectral density of the AE signals can be attributed to the difference in interface motion of the two transformations, and the consequent different behaviour of the dislocations involved.     

金刚石单晶生长的声发射实时检测初探

采用声发射检测技术,对高温高压下人造金刚石单晶的生长过程进行了检测和分析。利用由PCI-8型声发射仪和LMD-800型铰链式六面顶压机组成的声发射检测系统,检测了金刚石单晶的生长过程。将金刚石单晶生长和不生长过程中检测到的声发射信号进行对比和频谱分析,结果表明:声发射信号与金刚石单晶生长过程存在对应关系;金刚石单晶生长对应的声发射信号是一种低频信号,可以利用声发射信号的变化规律研究金刚石单晶在高温高压条件下的原位反应机理。     

A non-iterative partial discharge source location method for transformers employing acoustic emission techniques

Partial discharge (PD) causes premature insulation failure of transformers. It is essential to detect PD to avoid unwanted failure of transformers. Only detection of PD is not sufficient for a transformer of huge size, unless it is possible to locate. Acoustic partial discharge measurement is advantageous for PD source location. There are different algorithms for PD source location. These are iterative and require large number of acoustic emission (AE) sensors. This paper presents a non-iterative source location algorithm employing four AE sensors. This algorithm is applied to experimental data. Proposed algorithm is also applied to published data and compared with existing iterative methods. Main error for source location is due to arrival time calculation. In order to reduce the error in AE signal arrival time calculation, different arrival time calculation methods are discussed and a comprehensive method is proposed. By applying these methods, arrival time is calculated from measured signal.     

Measurements and modeling of long range 3He diffusion in the lung using a "slice-washout" method

In healthy lung tissue, pulsed-gradient-spin-echo (PGSE) methods reveal apparent diffusion coefficients (ADC) of the order 0.20 cm2 s(-1); for diffusion times of approximately 2 ms. For these short diffusion times the ADC is only sensitive to structures approximately (2Dt)1/2 approximately 0.6mm in size. Recent work, using magnetic tagging of the longitudinal magnetization has revealed much smaller ADC values for longer length scales. In this work, the in vivo ADC from within the air-spaces, was measured using a new technique. The signal from a series of images was analyzed from a slice that was repeatedly imaged. Diffusion tends to "top-up" the non-renewable polarization within the slice, which leads to a non-exponential decay in image signal. Image data were compared to 1D finite-difference simulations of diffusion to calculate a long range ADC value. The results yield values of the order 0.034 cm2 s(-1), which are nearly an order of magnitude smaller than those reported by PGSE measurements at shorter diffusion times.     

Assessment of in vitro vs. in vivo lung structure using hyperpolarized helium-3 diffusion magnetic resonance imaging

The purpose of this study was to assess the properties of a model system for hyperpolarized He-3 (HHe) diffusion MR imaging created from the lungs of New Zealand white rabbits by drying the lungs while inflated at constant pressure. The dried lungs were prepared by sacrificing the animal, harvesting the lungs en bloc and dehydrating the lungs for several days using dry compressed air. In four rabbits, the apparent diffusion coefficient (ADC) of HHe gas was measured in vivo and, within 1 week, in vitro in the dried lungs. To assess long-term repeatability, in vitro ADC values were measured again 3 months later. Dried lungs from four additional rabbits were imaged twice on the same day to assess the short-term repeatability of ADC measurements, and tissue samples from these lungs were then removed for histology. In vivo and in vitro ADC maps showed similar features and similar distributions of ADC values; mean in vivo and in vitro ADC values differed by less than 12%. The in vitro mean ADC values were highly reproducible, with no more than 5% difference between measurements for the short-term repeatability and less than 17% difference between measurements for the long-term repeatability. Histological samples from the dried lungs demonstrated that the lung structure remained intact. These results suggest that the dried lungs are a useful and inexpensive alternative to human or in vivo animal studies for HHe diffusion MR sequence development, testing and optimization.     

Apparent diffusion coefficient (ADC) measurements may be more reliable and reproducible than lesion volume on diffusion-weighted images from patients with acute ischaemic stroke-implications for study design

Early ischemic change after stroke can be demonstrated with diffusion-weighted imaging (DWI) and quantified by measuring the apparent diffusion coefficient (ADC) and/or lesion volume. We examined the reliability and reproducibility of lesion volume and ADC measurement on DWI images, and discuss the implications for clinical studies. Using 38 DWI scans from 15 stroke patients, two observers (a physicist and a neuroscience graduate) blind to each other, recorded the lesion volume on DWI sequences, measured the ADC values in this volume and calculated the ratio of ischemic: control ADC (ADCr). One observer repeated his measurements blind to his first, and also examined the effect on lesion volume and ADC of deliberately varying by only one pixel, the outline of the visible boundary of the lesion. The inter and intra-rater reliability were worse for lesion volume than ADC or ADCr measurements: lesion volume, inter-rater coefficient of variation (CoV) 85 +/- 130%, intra-rater CoV 20+/-SD80% (p < 0.05); ADC inter-rater CoV 7.7 +/- SD 19%, intra-rater CoV 0.2 +/- SD 12% (p = NS); and ADCr inter-rater CoV 8 +/- SD27%, intra-rater CoV 0.8 +/- SD73% (p = NS). Altering the position of the outline tracing of the lesion boundary by one pixel altered the measured volumes by 22 +/- SD25% (p < 0.05), but ADC values were altered by only 2.9 +/- SD4.9% and ADCr by 2.7 +/- SD4.8% (p = NS). ADC and ADCr values are more reliable and reproducible than DWI lesion size in acute ischemic stroke because altering where the lesion boundary is measured has a much greater impact on lesion volume than on the ADC or ADCr. This effect is greatest in large lesions.     

基于小波变换的低场核磁共振信号去噪方法的研究进展

低场核磁共振（low-field Nuclear Magnetic Resonance,low-field NMR）技术因其自身具有的独特优越性常被应用于极端条件下的测量,而且由于其采用的是永磁体,因而采集到的信号信噪比常常较低,在很大程度上影响了测量值的准确性.因此,如何去除混杂在信号中的加性高斯白噪声增加测量值的可靠性显得尤为重要.针对这一问题,国内外学者相继提出了众多优秀的去噪方法,其核心都是在不损失含噪信号中有效信息的基础上滤除掉夹杂在其中的噪声信号.本文在基于对小波变换理论分析的基础上,介绍了3种目前较为流行的用于低场核磁共振信号去噪的方法,分别是小波阈值去噪、模极大值去噪和小波系数相关性去噪,并给出了用于评价去噪效果的四个参数及其计算方法.     

基于集合经验模态分解和奇异值分解的激光雷达信号去噪

为了提高差分光柱像运动激光雷达(DCIM雷达)探测信噪比,提出了一种基于集合经验模态分解(EEMD)和奇异值分解(SVD)的混合降噪法.由EEMD获得含噪信号多层模态分量,根据各模态分量之间互相关系数的差分量确定主要噪声并予以滤除,利用奇异值分解识别模态分量中的残余噪声并提取有用信号.利用混合降噪法EEMD-SVD和EEMD方法分别对模拟仿真信号和实测激光雷达信号进行降噪处理.结果表明,当模拟噪声标准差在0.05~0.2之间时,相比与未降噪直接反演的湍流廓线,EEMD-SVD方法降噪后反演的湍流廓线信噪比提高了2.718 7dB~6.921 5dB,相应的EEMD方法提高了1.446 1dB~3.366 1dB;两个不同时段DCIM雷达降噪前后反演廓线与探空廓线的对比发现,EEMD-SVD和EEMD两种方法降噪后反演廓线较之于未降噪的反演廓线,信噪比最大提高了2.526 5dB和2.155 6dB.EEMD-SVD的降噪效果优于EEMD,能够更有效地识别和滤除噪声,较大地提高了原始信号的信噪比,获得更准确的大气湍流廓线反演结果.