钢轨裂纹伤损声发射源的建模仿真与特征分析

高速铁路的发展对钢轨的安全性提出了特殊要求,因此对钢轨内部裂纹的特征分析具有重要意义。为了研究钢轨内部裂纹声发射源特征,对钢轨中不同类型、深度和传导距离的裂纹声发射源进行了分析.采用有限元方法建立了钢轨模型并通过实验验证,然后结合小波方法和瑞利-兰姆方程分析了裂纹声发射源的特征。结果表明:钢轨中不同类型和不同频率特征的声发射源能够利用声发射模态之间的强度比率来识别;轨腰深度上的声发射源具有统一的模态特征,而轨头和轨底的声发射源则具有复杂的模态特征;同时,不同类型声发射源在钢轨中的传导特征差异明显。研究结果对利用声发射技术进行钢轨裂纹检测提供了指导,可作为实际应用的重要参考。      

钢轨裂纹伤损声发射源的建模仿真与特征分析

高速铁路的发展对钢轨的安全性提出了特殊要求,因此对钢轨内部裂纹的特征分析具有重要意义。为了研究钢轨内部裂纹声发射源特征,对钢轨中不同类型、深度和传导距离的裂纹声发射源进行了分析.采用有限元方法建立了钢轨模型并通过实验验证,然后结合小波方法和瑞利-兰姆方程分析了裂纹声发射源的特征。结果表明:钢轨中不同类型和不同频率特征的声发射源能够利用声发射模态之间的强度比率来识别;轨腰深度上的声发射源具有统一的模态特征,而轨头和轨底的声发射源则具有复杂的模态特征;同时,不同类型声发射源在钢轨中的传导特征差异明显。研究结果对利用声发射技术进行钢轨裂纹检测提供了指导,可作为实际应用的重要参考。     

基于多基因遗传规划的储层岩石静态模量预测

声发射技术作为一种动态无损检测手段,主要实现对材料产生的缺陷进行动态监测及损伤位置的预测。微机电系统声发射传感器在检测材料疲劳裂纹位置和扩展方向上应用广泛,实现其对材料裂纹的3-D动态位移检测,对于无损检测技术的发展具有重要意义。该文提出了一种新型3-D微机电系统声发射传感器,首先对3-D微机电系统声发射传感器进行了结构设计和性能分析,结构方面主要包括z方向响应传感单元和x、y方向响应传感单元设计;其次通过传感器的阻尼、谐振点处灵敏度计算,证明传感器的性能良好;最后采用有限元软件ANSYS对z方向响应传感单元做了模态和谐响应分析,x、y方向响应传感单元做了模态分析和谐响应分析,仿真结果与理论值吻合较好,验证了结构设计的合理性,对实现材料裂纹的三维动态检测具有一定的参考意义。     

三维微机电系统声发射传感器设计及性能分析

声发射技术作为一种动态无损检测手段,主要实现对材料产生的缺陷进行动态监测及损伤位置的预测。微机电系统声发射传感器在检测材料疲劳裂纹位置和扩展方向上应用广泛,实现其对材料裂纹的3-D动态位移检测,对于无损检测技术的发展具有重要意义。该文提出了一种新型3-D微机电系统声发射传感器,首先对3-D微机电系统声发射传感器进行了结构设计和性能分析,结构方面主要包括z方向响应传感单元和x、y方向响应传感单元设计;其次通过传感器的阻尼、谐振点处灵敏度计算,证明传感器的性能良好;最后采用有限元软件ANSYS对z方向响应传感单元做了模态和谐响应分析,x、y方向响应传感单元做了模态分析和谐响应分析,仿真结果与理论值吻合较好,验证了结构设计的合理性,对实现材料裂纹的三维动态检测具有一定的参考意义。     

基于光声信号的高铁钢轨表面缺陷检测方法

针对传统的基于超声信号的高铁钢轨无损检测方法对于表面微裂纹检测效果不佳的问题,提出了一种基于光声信号的高铁钢轨表面缺陷检测方法.首先,使用有限元及K-wave方法建立了钢轨模型并获得了模拟光声信号;然后利用时间反演的方法对钢轨表面的光声图像进行了重建,并研究了不同传感器中心频率对成像结果的影响;最后设计实验采集了钢轨表面的光声信号并进行了处理和分析.实验结果表明,基于光声信号的高铁钢轨表面缺陷检测方法对于表面微裂纹有很好的检测效果,该方法在钢轨探伤领域有较大的可行性及发展潜力.     

声发射技术在全尺寸飞机疲劳试验中的应用

过去九年,,在对两类三代机的全尺寸疲劳试验中实施了全程声发射监测。采用了以声发射为中心的裂纹综合监、检测方法,对一些关键构件的疲劳裂纹实施早期预报,并用其它无损检测方法加以验证,为试验的顺利进行奠定了重要基础,为确定和延长这两类飞机的机群寿命发挥了重要作用。在对第一类三代机的试验中,发展了过去所用的声发射信号处理技术,在大量获取试验中的声发射信号时,有意识地将信号分成一系列有序的信号子集,分别反映一定的飞机受力(载荷)状态,在此基础上再采用空间滤波等技术获得感兴趣结构位置处的信号子集。对子集再采取基于统计分析原理的趋势分析和相关分析技术,获取监测位置的状态,以及试验机的“健康状态”。这一方法在另一类三代机的试验中再次发挥作用,显示了生命力。最终结果是两类三代机的机群寿命均有50%以上的提高,说明声发射技术具有广阔的应用前景。     

高速铁路轮轨滚动噪声的分形描述及分形维估计

提出基于分形分析的轮轨滚动噪声研究方法,研究了不同尺度下轮轨滚动噪声增量的统计特性,证明轮轨滚动噪声具有分形特性,可由分形布朗运动描述。在此基础上,利用分形布朗运动的小波系数方差与分形维的幂律关系估计了轮轨滚动噪声的分形维,并估计了以裂纹扩展为代表的钢轨伤损声发射信号的分形维,对比研究发现:轮轨滚动噪声分形维本身具有随机性,不同车速下的轮轨滚动噪声分形维估计以1.5666为均值随机分布在小于2的小区间内;分形维是轮轨滚动噪声的固有特征,与车速无关,不同车速的轮轨滚动噪声可由统一的分形布朗运动模型描述;裂纹扩展信号与轮轨滚动噪声不同,其分形维估计大于2,不满足分形布朗运动模型的要求,但分形维可作为二者的区别特征。研究提取了轮轨滚动噪声的分形维作为固有特征,为高速轮轨滚动噪声描述及轮轨伤损检测提供了有效的分析方法。      

钢轨踏面的空气耦合超声检测方法*

该文针对钢轨踏面浅表面裂纹提出非接触空气耦合超声类瑞利波的检测方法。首先利用半有限元法求解了CHN60型钢轨的振动模式,抽出了钢轨轨头踏面的振动模态结构和频散曲线,并搭建实验系统,根据Snell法则和声源在空气中的声场分布确定了检测参数,最后从理论和实验两方面着手对钢轨踏面浅表面裂纹的有无及裂纹大小进行了实验分析和数值计算,其结果非常吻合,证明了空气耦合超声导波检测方法的可行性和可靠性。     

SPV490Q钢焊接冷裂纹声-磁定位方法研究

声发射源定位方法可以精准判断信号发生时间及位置,但由于其检测数据量大,难以进行实时评价,而磁记忆定位方法能实时观察数据结果,所以用声-磁结合的方法对冷裂纹进行定位分析。焊后即进行声发射监测,待焊缝冷却后,按一定时间间隔用磁记忆技术进行检测,这样既能精确得到冷裂纹起裂时间及其位置,又能实时观察冷裂纹扩展走向。同时,通过SPV490Q钢斜Y型坡口焊接冷裂纹实验验证了该方法的可行性。     

Q235钢板局部腐蚀声发射信号特性研究

为解决腐蚀声发射源特征提取和识别的难题,直接从理论上证明了腐蚀声发射监测的有效性并推导出声发射信号特征。气泡破裂声发射信号幅值近似与气泡半径平方和液位高度成正比,频率与气泡半径成反比;钢板及其腐蚀产物开裂声发射信号幅值与开裂位置局部应力强度成正比,频率与裂纹扩展速度成正比,与裂纹扩展距离成反比。用低频和高频两套声发射系统,同时长时间监测Q235钢板在10%FeCl_3·6H_2O、10%FeCl_3·6H_2O加0.01 mol/L HCl混合液、5%CuSO_4·5H_2O溶液中的腐蚀情况,辅以监测钢板及钢板腐蚀产物开裂作为验证实验。通过对声发射信号的参数及谱分析,得出不同声发射源可以通过撞击数及功率谱在频域的分布来有效区分。实验结果与理论分析相吻合,研究结果对腐蚀声发射监测技术具有重要指导意义。     

Roller bearing acoustic signature extraction by wavelet packet transform,applications in fault detection and size estimation

Continuous online monitoring of rotating machines is necessary to assess real-time health conditions so as to enable early detection of operation problems and thus reduce the possibility of downtime. Rolling element bearings are crucial parts of many machines and there has been an increasing demand to find effective and reliable health monitoring technique and advanced signal processing to detect and diagnose the size and location of incipient defects. Condition monitoring of rolling element bearings, comprises four main stages which are, statistical analysis, fault diagnostics, defect size calculation, and prognostics. In this paper the effect of defect size, operating speed, and loading conditions on statistical parameters of acoustic emission (AE) signals, using design of experiment method (DOE), have been investigated to select the most sensitive parameters for diagnosing incipient faults and defect growth on rolling element bearings. A modified and effective signal processing algorithm is designed to diagnose localized defects on rolling element bearings components under different operating speeds, loadings, and defect sizes. The algorithm is based on optimizing the ratio of Kurtosis and Shannon entropy to obtain the optimal band pass filter utilizing wavelet packet transform (WPT) and envelope detection. Results show the superiority of the developed algorithm and its effectiveness in extracting bearing characteristic frequencies from the raw acoustic emission signals masked by background noise under different operating conditions. To experimentally measure the defect size on rolling element bearings using acoustic emission technique, the proposed method along with spectrum of squared Hilbert transform are performed under different rotating speeds, loading conditions, and defect sizes to measure the time difference between the double AE impulses. Measurement results show the power of the proposed method for experimentally measuring size of different fault shapes using acoustic emission signals.     

基于激光多普勒频移的钢轨缺陷监测

针对现阶段我国铁路上应用的探伤设备只能在天窗时间进行人工巡检,无法在线监测的问题,提出一种基于超声导波的激光多普勒频移法钢轨内部缺陷监测方法。首先,引入环境温度作为变量改进了半解析有限元方法,并应用该方法获得了我国无缝线路CHN60钢轨在特定温度下的频散曲线。通过分析振型并结合激励响应算法确定了适于检测缺陷的模态及其激励方式,从而激励该超声导波模态使其在钢轨中传播。然后,应用半反半透玻璃镜将激光分为参考光和测量光,测量光通过Bragg Cell进行频偏照射钢轨表面,通过反射光产生的多普勒频移与参考光干涉得到光强度变化曲线,经过信号处理及标定测得钢轨内部缺陷的回波速度信号,再经过数字化处理和计算得到缺陷的位置。最后,在北京环形铁路试验基地进行了现场实验,以钢轨接地孔模拟钢轨内部核伤,得到缺陷定位误差均小于0. 5 m,验证了该方法的可行性。使用激光多普勒频移方法检测导波信号从而定位缺陷的方法可以有效避免由于换能器接触性测量而产生的误差。该方法在不影响列车的正常运营的同时,实现了全天候无间断的在线监测,提高了检测效率。     

Laser ultrasonic surface wave inspection of alumina ceramics of varying density

In this paper, the surface acoustic wave velocity results acquired from the inspection of specially manufactured and characterised alumina ceramic materials are presented. Ultrasonic velocity data of alumina-based ceramics in the range 60-100% theoretical density was generated utilising non-contacting laser-ultrasonic measurements based on laser generation and detection of surface acoustic waves with the objective of creating a routine technique for industrial advanced alumina inspection. With linear fitting the surface acoustic wave velocity data serves as a calibration graph for using laser ultrasonics for routine monitoring of alumina. A second laser ultrasonic technique based on the laser generation and foil transducer detection of surface acoustic waves was used to validate the surface acoustic wave velocities measured by the laser generation/detection technique.     

A new synthetic detection technique for trackside acoustic identification of railroad roller bearing defects

The detection of railroad roller bearing defects is of great importance for railway traffic. The acoustic defective bearing detector (ADBD) via a trackside acoustic detection system (TADS) is a popular and reliable tool for trackside identification of railroad bearing incipient defects. However, the defective trackside acoustic signal of bearing is confronted with three challenges: demodulation of acoustic signal, removal of Doppler effect and enhancement of defect frequency. This paper proposes a synthetic detection technique to overcome these difficulties successively. In the technique, the signal envelope is first extracted by a new variable-resolution ridge demodulation (VRRD) method. Then the Doppler effect is removed in the envelope via a dynamic signal resampling method. Finally, the rectified defect frequency is enhanced through the means of logarithmic transformation and piecewise linear detrending. The VRRD technique extracts the envelope from the signal time–frequency distribution (TFD) along the Doppler shift curve of resonance frequency traced by an improved ridge extraction algorithm. The resampling method is carried out on the envelope according to the Doppler shift curve of defect frequency obtained by the same ridge extraction algorithm. The sidebands around defect frequency can be suppressed by the logarithmic transformation and the low-frequency non-linear trend can be removed by the detrending method. The signal amplitude is unified at the same time. Two practical bearing signals with inner-race and outer-race defects separately verify the effectiveness of proposed technique.     

An analysis of the simulated acoustic emission sources with different propagation distances,types and depths for rail defect detection

Acoustic Emission (AE) technique is an effective nondestructive detecting method, and has a promising application for rail defect detection. So far, little attention has been paid to propagation distances, types, and depths of AE sources, which are important for rail defect detection accurately. This paper presents an experimental study on the simulated AE sources with different propagation distances, types and depths for rail defect detection. Three simulated AE sources with different frequencies are seeded on the cross section of rail, and the depths of AE sources are changed in the vertical direction. After receiving AE signals, wavelet transform and Rayleigh–Lamb equations are utilized to extract time–frequency features and modes. Based on the wavelet transform with corresponding group-velocity curves, the influences of different propagation distances, the features of different source types and the rules of different source depths are examined. It is concluded that the features of AE sources with different propagation distances, types and depths can be obtained by AE technique for rail defect detection. It is very useful to analyze and detect defects in rail defect detection.     

Lock-in thermographic inspection of squats on rail steel head

The development of squat defects has become a major concern in numerous railway systems throughout the world. Infrared thermography is a relatively new non-destructive inspection technique used for a wide range of applications. However, it has not been used for rail squat detection. Lock-in thermography is a non-destructive inspection technique that utilizes an infrared camera to detect the thermal waves. A thermal image is produced, which displays the local thermal wave variation in phase or amplitude. In inhomogeneous materials, the amplitude and phase of the thermal wave carries information related to both the local thermal properties and the nature of the structure being inspected. By examining the infrared thermal signature of squat damage on the head of steel rails, it was possible to generate a relationship matching squat depth to thermal image phase angle, using appropriate experimental/numerical calibration. The results showed that with the additional data sets obtained from further experimental tests, the clarity of this relationship will be greatly improved to a level whereby infrared thermal contours can be directly translated into the precise subsurface behaviour of a squat.     

电磁声实验平台的研制与实验研究

研制了一个多功能的电磁声实验平台,在此实验平台,进行了"减小盲区"、"钢层下多层橡胶层脱粘检测"、"线性调频脉冲压缩"等方面的实验研究。实验结果表明,该平台可精确控制实验参数,提供单一频率脉冲串和线性调频脉冲两种激励波形,具有信噪比高盲区小的优点和线性调频脉冲压缩的功能。将该实验平台应用在钢层与多层橡胶层粘接件的脱粘检测,取得了与压电检测相当的结果。作为一个电磁声方法和技术研究的工具,该实验平台对开展电磁声检测方法和技术研究以及实际检测应用都是有意义的。      

Fatigue behaviour and structural health monitoring by acoustic emission of E-glass/epoxy laminates with piezoelectric implant

This paper represents the continuation of our research on built-in piezoelectric sensor for structural health monitoring of composite materials. Experimental research is focused on examining the effects of the embedded sensors on the structural integrity of composite laminates subjected to mechanical tests. A series of composite specimens with and without embedded sensor are tested in fatigue loading while constantly monitoring the response by acoustic emission technique. The acoustic signals are analysed using the classification k-means method in order to identify the different damage mechanisms and to follow the evolution of these mechanisms for both types of composite materials (with and without sensor). The mechanical behaviour of composites with and without embedded sensor shows no difference in the form. The incorporation of piezoelectric sensor causes low degradation of mechanical properties of composites. Comparing embedded sensor to sensor mounted on the surface, the embedded sensor showed a much higher sensitivity. It is thus verified that the embedded acoustic emission sensor had great potential for acoustic emission monitoring in fibre reinforced composite structures.