Exchanged ridge demodulation of time-scale manifold for enhanced fault diagnosis of rotating machinery

The vibration or acoustic signal from rotating machinery with localized fault usually behaves as the form of amplitude modulation (AM) and/or frequency modulation (FM). The demodulation techniques are conventional ways to reveal the fault characteristics from the analyzed signals. One of these techniques is the time-scale manifold (TSM) ridge demodulation method with the merits of good time–frequency localization and in-band noise suppression properties. However, due to the essential attribute of wavelet ridge, the survived in-band noise on the achieved TSM will still disturb the envelope extraction of fault-induced impulses. This paper presents an improved TSM ridge demodulation method, called exchanged ridge demodulation of TSM, by combining the benefits of the first two TSMs: the noise suppression of the first TSM and the noise separation of the second TSM. Specifically, the ridge on the second TSM can capture the fault-induced impulses precisely while avoiding the in-band noise smartly. By putting this ridge on the first TSM, the corresponding instantaneous amplitude (IA) waveform can represent the real envelope of pure faulty impulses. Moreover, an adaptive selection method for Morlet wavelet parameters is also proposed based on the smoothness index (SI) in the time-scale domain for an optimal time-scale representation of analyzed signal. The effectiveness of the proposed method is verified by means of a simulation study and applications to diagnosis of bearing defects and gear fault.     

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。     

De-noising of wayside acoustic signal from train bearings based on variable digital filtering

In the wayside Acoustic Defective Bearing Detector (ADBD) system, the recorded signal usually includes both the sound from train bearings and the other disturbance sources. The fact of heavy noise corruption and the Doppler Effect of multi-source acoustic signals would badly reduce the effectiveness of online defect detection of the ADBD system. In order to extract useful information from the multi-source signal with Doppler Effect, this paper proposes an effective de-noising method based on the variable digital filter (VDF) for the ADBD system. Specifically, the ridge extraction based on Short-Time Fourier Transform (STFT) is applied to estimate the instantaneous frequencies (IFs), with which the fitting IF curves based on the Morse theory of theoretical acoustics could be achieved by using the nonlinear curve-fitting so that the parameters of the initial position of the acoustic sources could be calculated. By the aid of these parameters, the IFs according to the target train bearing could be then extracted. After that, the FIR variable digital filters could be designed with all the IFs which match the Morse theory with Doppler Shift so that the noise from the other parts could be effectively restrained after filtering the original signal. The effectiveness of this method is verified by means of a simulation with multi-frequency signals and applications to diagnosis of train roller bearing defects. Results indicate that the proposed method is effective.     

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.     

Cyclic statistics in rolling bearing diagnosis

Mechanical signals with amplitude modulated are characterized by periodic time-varying ensemble statistics and can be considered as cyclostationary. In this paper, the second order cyclic statistics, i.e. cyclic autocorrelation and cyclic spectrum, are introduced. A method of demodulation based on cyclic autocorrelation is derived from a signal model. The modulators and carrier are exhibited, respectively, in low- and high-frequency band of cyclic frequency domain. The three-dimensional spectral correlation figure, which represents cyclic frequency, frequency and spectral correlation strength simultaneously, is developed to express the demodulation results clearly. The method is tested by simulation signal and applied to diagnose rolling bearing faults. It obtained more information than other conventional methods, such as the frequency domain and the envelop detection. Furthermore, its effect is demonstrated by comparing with the wavelet envelope demodulation.     

基于Hilbert变换的水下多源声信号频率的相干探测

为实现水下中低频声信号的探测识别,通过研究水下多声源相干探测信号的特征,理论上给出了相干探测信号频谱混叠情况下的特征表达式,并提出了一种基于Hilbert变换的信号解调处理方法,实现了水下多声源相干探测信号频谱混叠情况下各声源发声频率的解调.该方法将探测信号经过滤波平滑处理之后进行Hilbert变换,得到信号的解析形式,然后对解析信号模值的平方进行二次滤波平滑等处理,分离混叠在一起的频带,将得到的信号进行频谱分析,根据频移值计算得到水下各个声源的发声频率.在光学暗室下搭建激光相干探测系统,对2~6kHz的水下声信号进行实验,实验结果表明,该方法可以有效分离探测信号中混叠在一起的信号频带,并准确提取各水下声信号的发声频率,频率提取重复性不大于2.5Hz.     

Wayside acoustic defective bearing detection based on improved Dopplerlet transform and Doppler transient matching

The diagnosis of train bearing defects plays a significant role in maintaining the safety of railway transport. However, the phenomenon of Doppler Effect in the acoustic signal recorded by the wayside Acoustic Defective Bearing Detector (ADBD) system leads to the difficulty for fault diagnosis of train bearings with a high moving speed. This paper proposes a double-searching solution based on improved Dopplerlet transform and Doppler transient matching to overcome the difficulty in wayside acoustic bearing diagnosis. In the solution, the first searching procedure is to extract necessary parameters of Doppler Effect under the situation with very low signal-to-noise ratio (SNR) based on an improved Dopplerlet transform. Using the obtained parameters, the Doppler Effect can be embedded into the constructed periodic Laplace wavelet transient models. Subsequently, the second searching procedure is conducted to search fault impact period of the defective bearing through an operation, called Doppler transient matching, which is to calculate the correlation coefficient between the Doppler transient model and the filtered raw signal with the Doppler Effect. The proposed double-searching algorithm can adapt to the real Doppler Effect situation and extract the exact fault impact period from the Doppler distorted signal, and thus shows powerful capability to analyze wayside acoustic signals from train bearings. The proposed wayside acoustic diagnostic scheme is verified by means of a simulated Doppler distorted signal with a very low SNR (−20 dB) and the experiments conducted on train bearings. The results indicate that the proposed algorithm is effective and has obvious advantages for ADBD system.     

改进的信道稀疏度检测正交多载波多普勒估计方法

针对正交频分复用水声移动通信中频域变采样技术联合信道稀疏度检测的多普勒估计算法在冰水混合区复杂信道环境下多普勒估计效果欠佳且计算量大的问题,提出了一种改进的多普勒估计算法。采用时域重采样技术对信号进行不同压缩因子的补偿,避免了频域变采样技术中的高阶快速傅里叶变换运算,从而降低了算法复杂度。利用梳状导频位置向量结合时域变采样技术更准确提取的导频子载波,进而获得更加精确的信道估计和信道稀疏度检测结果,提高了多普勒估计精度。仿真结果和冰下试验结果表明,与原始算法相比,改进的方法在冰水混合水域复杂多径时变信道环境下可以有效实现对信号多普勒畸变的跟踪并且计算量显著下降,能够保障正交频分复用水声移动实时通信。     

扬声器异常音的快速检测方法及其实验研究

提出了一种对扬声器声响应中的低阶次谐波失真与高阶次谐波失真和进行综合分析的方法,以实现对扬声器异常音的快速检测。文章分析了扬声器异常音的时域和频域特征,并对人耳听测异常音的机理进行了讨论。通过对扬声器系统Volterra建模并选择连续对数扫频信号作为激励信号,推导出了该模型在此激励下的响应表达式.该表达式揭示了提取各阶冲激响应的方法,由该表达式给出一种可以快速提取各阶次谐波失真的跟踪滤波器,以实现对扬声器异常音的检测。实验室测试和多次工厂生产线测试初步验证了该方法的准确性、快速性和可行性。     

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.     

Continuous-scale mathematical morphology-based optimal scale band demodulation of impulsive feature for bearing defect diagnosis

Integer-scale structuring element is usually used in the traditional mathematical morphology (MM) for signal processing. When applied for impulsive feature demodulation of vibration signal of rolling element bearings, the integer-scale MM (ISMM) may lead to low resolution result and thus undermines its defect diagnosis capability. For this reason, this paper proposes a continuous-scale MM (CSMM) scheme by interpolation and re-sampling to improve scale resolution for more reliable fault signature extraction. Based on the frequency domain kurtosis criterion, a narrowband merging operation is employed to locate the optimal scale band that best reflects the impulsive feature from the CSMM analysis results. The demodulated components in the optimal scale band are employed to detect the existence of the bearing fault. The proposed optimal CSMM demodulation technique is evaluated using both simulated and experimental bearing vibration signals. The results show that, the CSMM is capable of generating demodulation signals with higher resolution, and the optimal scale band demodulation based on the CSMM can reliably extract impulsive features for bearing defect diagnosis.     

水下声辐射激励水表面声波的特征参数测量

采用激光干涉方法对水下声辐射激励水表面声波的特征参数频率和振幅进行了测量研究。从理论上对水表面声波激光相干测量信号的频谱构成进行了分析,在此基础上提出了水表面声波两个重要声学参数频率和振幅的解算方法,并通过数值仿真进行了验证。搭建了一套简单的激光干涉测量实验系统,对不同频率和声压激励的水表面声波进行了测量实验,验证了水表面声波频率和振幅解调方法的准确性。对水表面声波横向传播的振幅衰减现象进行了初步的实验研究,结果表明水表面声波的频率越高,振幅的横向衰减越快。研究表明激光相干检测方法能够准确地实现水表面声波振幅和频率的测量。     

接触缺陷的振动调制超声导波检测技术研究

针对常规线性超声检测方法无法实现板结构接触类缺陷(如微裂纹、脱粘等)检测问题,将超声导波技术与振动声调制技术相结合,利用稀疏分布传感器发展了一种板结构中接触缺陷非线性超声检测方法。通过低频振动改变缺陷的接触状况,使得通过接触面的高频导波信号的相位和幅值受到调制。对受低频振动调制的超声导波二维时间序列进行时频分析,由于接触类缺陷的存在,在振动调制超声导波序列的时频分布上出现明显的低频振动频率分量。利用提取出的低频振动频率下的超声导波信号,进行了结构接触缺陷成像处理。检测试验表明,基于振动声调制的超声导波缺陷成像方法可以实现结构中的接触类缺陷检测。     

基于光频调节的干涉型光纤水听器相位补偿检测方法

提出了一种基于光源频率调节的干涉型光纤水听器主动相位补偿的信号检测方法。详细介绍了该方法的基本检测原理,对信号解调误差进行了理论分析与仿真。为了验证该方法的可行性,搭建了实验系统,并编写了实时的信号采集、处理程序,对某一干涉型光纤水听器的声压灵敏度进行了测试。在频带20 Hz-1.3 kHz上,平均声压灵敏度为-162.2 dB(0 dB=1 rad/μPa),波动小于±0.8 dB,与采用相位载波调制解调方法测量的结果基本吻合。实验结果证明该方法是有效的。由于传感部分不含有源器件,便于实现全光纤化,且解调算法简单、检测频带宽,该方法能被广泛应用到各种干涉型光纤传感器的信号检测当中。     

研究激光激发的声表面波与材料近表面缺陷的振荡效应

根据激光激发声表面波的热弹运动方程及热传导方程, 采取有限元技术对方程进行求解, 得到声表面波传播波形图. 当声表面波经过近表面缺陷时, 声表面波与近表面缺陷之间产生一种振荡效应, 通过近表面缺陷的振荡波形幅值存在一个逐渐增加后又逐渐减小的过程. 当声表面波经过不同深度的近表面缺陷时, 振荡信号中心频率存在一定的变化规律. 数值仿真结果表明: 当近表面缺陷深度从0.1 mm到0.5 mm变化时, 振荡效应产生的振荡信号中心频率从0.4 MHz到0.76 MHz变化, 振荡信号中心频率与近表面缺陷深度呈近似线性关系, 这为近表面缺陷的定量检测提供了一种理论基础.     

激光多普勒微振动信号的直接强度解调

在传统的激光多普勒测振方法中,频移信号的检测通常需要具有比较复杂的频率或相位解调系统。从激光多普勒频移和干涉理论出发,提出了一种测量振幅小于纳米量级的方法———直接强度解调法。分析了直接强度解调法的适用范围。实验中利用了迈克尔逊干涉仪结构,采用了直接强度解调的方法。对振幅约为1nm的振动信号来说,其信噪比为23dB。     

Vibro-modulation and Guided wave techniques for contact defect detection in plate

A nonlinear acoustic technique for detection of contact defects in plates was developed associating guided waves with vibro-modulation techniques.The low frequency vibration varies the interface area within the contact defect;then the amplitude and phase of high frequency guided waves reflected from the contact defect will be modulated.Due to the exiting of contact defects,there was obvious low frequency component in the time-frequency distribution of modulated guided wave series.Furthermore the nonlinear responses at frequency of vibration were extracted out and used for defect imaging.It was shown that the nonlinear guided wave imaging method based on vibration modulation can effectively characterize and locate the nonlinear contact defects.     

声发射技术在铁路系统检测中的研究和应用

高速铁路的快速发展,给我国经济和社会发展带来了巨大的推动作用,同时对铁路系统的安全性提出了更高的要求。针对声发射技术在铁路系统安全检测中的研究和应用,介绍了声发射技术及其在检测应用中的优点,综述了目前国内外声发射技术在铁路系统检测研究中的情况,包括钢轨伤损检测、车轮伤损检测、轮轴轴承伤损检测、铁路结构安全监测以及车体材料安全监测等,特别针对钢轨裂纹伤损引起的钢轨断裂这一铁路安全中的主要事故,着重分析了声发射技术在钢轨裂纹伤损检测研究中的情况,并介绍了在高速铁路方面的应用探索。最后在上述分析总结的基础上,指出了声发射技术在铁路系统特别是高速铁路检测研究中的前景及研究难点。     

滚动轴承声信号特征提取和诊断试验研究

为解决振动检测方法不能有效识别低速旋转机械滚动轴承故障问题,利用声发射检测方法,建立了滚动轴承低速声发射信号采集试验装置,对模拟人工缺陷滚动轴承声发射信号进行了采集,进而对滚动轴承声发射信号进行总体平均经验模式分解,结合能量矩及相关系数法综合判断分解后各模态分量的真伪,据此提取出特征信号并做出其局部Hilbert边际谱,最后对滚动轴承各种故障模式进行诊断。试验结果表明该诊断方法能准确识别滚动轴承声发射信号故障频率,依据特征频率及幅值大小可对低速滚动轴承故障进行有效诊断。     

双边缘技术多普勒测风激光雷达标准具的优化

 优化了基于双边缘技术的直接测风多普勒激光雷达中F-P标准具的工作参数。确定激光谱宽后，选择适当的F-P标准具自由谱间距，可正确消除瑞利背景噪声的影响。分析了标准具镜面缺陷、非严格平行和入射光束发散角对其透过率曲线的影响。将标准具透过率函数表达为唯一系统参数，即反射精细度的函数；通过计算散粒噪声极限时的相对测量误差，可确定最优反射精细度以及激光频率相对标准具透过率中心频率的最佳偏置；由最优反射精细度可得到入射到标准具光束的最大发散角和标准具的最小通光口径。