基于自适应最优Morlet小波的滚动轴承故障诊断

滚动轴承早期故障信号中故障信息比较微弱常常被强噪声所掩盖,增加了对滚动轴承故障诊断的难度。针对这一问题,笔者提出了基于自适应最优Morlet小波变换的滚动轴承故障诊断方法。首先,利用粒子群优化算法对Morlet小波变换的核心参数进行自适应寻优,在获得最优Morlet小波的同时保证了良好的带通滤波性能;然后,将最优Morlet小波对滚动轴承早期故障信号进行滤波去噪,提高信号的信噪比;最后,对最优Morlet小波滤波信号进行包络谱分析,通过包络谱中的主导频率成分与滚动轴承各元件的故障特征频率对比从而判断轴承的故障位置。仿真数据和实测数据分析结果证明,笔者所提方法能够有效提取故障信号中的特征信息,具有一定的有效性。     

小波基函数在故障诊断中的最佳选择

通过定性与定量的分析,提出了在对冲击信号进行连续小波变换时选择最佳小波基函数的方法和小波变换 后故障特征提取效果优劣的检验手段,并且得出了对于冲击性信号的连续小波变换,小波基函数的最佳选择为 Morlet函数的结论。     

Wavelet excited measurement of system transfer function

This article introduces a new method, which is referred to as the wavelet excitation method (WEM), for the measurement of the system transfer function. Instead of commonly used impulse or sine wave excitations, the method uses a sequential excitation by biorthogonal symmetric wavelets. The system transfer function is reconstructed from the output measurements. In the WEM the signals can be designed so that if N different excitation sequences are used and the excitation rate is f, the sampling rate of the analog-to-digital converter can be reduced to f/N. The WEM is especially advantageous in testing systems, where high quality impulse excitation cannot be applied. The WEM gave consistent results in transfer function measurements of various multistage amplifiers with the linear circuit analysis (SPICE) and the sine wave excitation methods. The WEM makes available new high speed sensor applications, where the sampling rate of the sensor may be considerably lower compared with the system bandwidth.     

自适应小波应用于回转类零部件的初期裂纹识别

介绍了基于kurtosis最大化准则的自适应Morlet小波分析方法，它能够根据kurtosis值自动调节小波函数参数以获得最佳滤波子小波，将其应用于处理染噪的周期性脉冲信号，以识别裂纹故障发展的初期征兆。与其它分析方法如离散小波变换和小波降噪进行了比较，结果表明自适应Morlet小波分析方法对于提取噪声中的周期性脉冲是非常有效的。     

基于Morlet小波与最大似然估计方法的降噪技术

采用与冲击信号匹配的Morlet小波作为小波基对信号进行小波变换,利用冲击信号的概率密度特征,结合最大似然估计的阈值方法进行降噪,以提取周期性的冲击信号。通过对减速箱故障信号进行降噪,提取出周期性的故障特征信号,表明该方法可以有效地去除强噪声干扰,提取振动冲击信号     

ON THE USE OF THE GAUSS FILTER IN MODAL PARAMETER ESTIMATION

The paper deals with the modal parameter estimation from the instantaneous envelope and phase—achievable by the Hilbert transform—of a single mode filtered from a frequency response function by the Gauss filter. It is possible, modulating the Gauss function, to put its maximum on the desired frequency, for instance on the peak of the mode of interest. Then a suitable choice of the parameter, which determines the sharpness of the Gauss function, permits to face the problem of modes with different damping, also in the highest frequencies of the band. This last point has been the major drawback of similar estimation methods based on the Gauss–Morlet wavelet. The results presented have been obtained both from numerical simulations and from experimental tests: the first ones achieved from synthesised impulse response functions of single and multiple lumped degree of freedom systems, and the second ones carried out on a simple structure (clamped aluminium plate).     

LS-SVM在基于小波变换的模态分析中端部效应的应用

系统地阐述了运用改进的Morlet小波进行模态参数识别的方法。运用小波熵对小波参数进行了优化选择从而可以进行密频模态的识别,针对小波分析时产生的端部效应问题,提出了运用最小二乘支持向量机（LS-SVM）对小波骨架进行预测延拓的方法,经预测分析后可获取较准确的模态参数。通过仿真及实验信号的验证分析,表明基于LS-SVM方法可以有效地消除端部效应,且其准确效果优于基于RBF的神经网络和时变自回归的预测方法。     

PARAMETERS OPTIMIZATION OF CONTINUOUS WAVELET TRANSFORM AND ITS APPLICATION IN ACOUSTIC EMISSION SIGNAL ANALYSIS OF ROLLING BEARING

Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform (CWT) has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm,an opti-mization strategy for the waveform parameters of the mother wavelet is proposed with wavelet en-tropy as the optimization target. Based on the optimized waveform parameters,the wavelet scalogram is used to analyze the simulated acoustic emission (AE) signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT.     

Electromechanical system frequency response equilization using three different methods

The frequency response of different electromechanical systems like sensors and actuators is in many cases the most important parameter for their evaluation. In some cases, when a short time delay does not play an important role and the flatness of frequency response is more important, an approximate of inverse system for frequency response compensation can be used. We equalized the frequency response of a non-minimum phase linear time-invariant electromechanical system using a digital finite impulse response (FIR) filter. Three different deconvolution methods for determination of the approximate of inverse filter impulse response were used and the results of the compensation using three different inverse filters are compared. The first method is based on the solution of the system of linear equations, while the second method is based on a simple direct inverse Fourier transformation. The third method uses an active noise control algorithm based on a least mean square adaptive algorithm. The results of all three methods can be applied in a FIR filter realized on DSP boards to perform real time compensation. The theoretical simulations are compared with experiments. Compensation of arbitrary systems is an interesting subject and it can be applied in numerous different fields from sensors and actuators to measurement and acoustics.     

Rolling element bearing faults diagnosis based on optimal Morlet wavelet filter and autocorrelation enhancement

The fault diagnosis of rolling element bearing is important for improving mechanical system reliability and performance. When localized fault occurs in a bearing, the periodic impulsive feature of the vibration signal appears in time domain, and the corresponding bearing characteristic frequencies (BCFs) emerge in frequency domain. However, in the early stage of bearing failures, the BCFs contain very little energy and are often overwhelmed by noise and higher-level macro-structural vibrations, an effective signal processing method would be necessary to remove such corrupting noise and interference. In this paper, a new hybrid method based on optimal Morlet wavelet filter and autocorrelation enhancement is presented. First, to eliminate the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter determined by a Morlet wavelet whose parameters are optimized by genetic algorithm. Then, to further reduce the residual in-band noise and highlight the periodic impulsive feature, an autocorrelation enhancement algorithm is applied to the filtered signal. In the enhanced autocorrelation envelope power spectrum, only several single spectrum lines would be left, which is very simple for operator to identify the bearing fault type. Moreover, the proposed method can be conducted in an almost automatic way. The results obtained from simulated and practical experiments prove that the proposed method is very effective for bearing faults diagnosis.     

基于组合正弦函数的机器人轨迹规划方法

提出了一种加速度函数为组合正弦函数的轨迹规划方法,它由两种不同频率的正弦曲线组合而成,本方法不但可以降低速度和加速度的峰值,而且还可以减少运行时间,使机器人运动平稳,避免振动和过冲现象,减少机械零件的磨损,延长机器人的使用寿命,可以使机器人能够精确、稳定、快速、高效地到达预定位置,完成拾放操作.     

五自由度农业采摘机器人轨迹规划

为解决所设计的五自由度农业采摘机器人的轨迹规划问题,通过DH参数建模建立了其运动学模型,提出了一种基于代数法和几何法的综合应用的算法,成功推导了此类机器人的逆运动学解析解。在此基础上,采用一种加速度函数为组合正弦函数的轨迹规划方法对其进行关节空间的轨迹规划,并进行了仿真实验分析。研究结果表明,该规划方法不仅具有操作时间短的特点,而且使得机器人运动平稳,无振动和过冲现象,满足机器人准确、快速完成采摘任务的要求。     

基于最优Morlet小波的滚动轴承故障诊断

将最优Morlet小波和阈值降噪法相结合,进行强噪声背景下滚动轴承故障诊断.依据峭度最大准则确定最优Morlet小波基.利用连续小波变换和软阈值法对振动信号降噪.试验表明,该方法具有良好的去噪性能,并能更好地提取滚动轴承振动信号中的故障特征.     

任意连续梁内力包络图的自动绘制法

根据内力包络图设计梁的断面,可以保证满足安全和经济两方面的要求。但是按传统方法绘制梁的内力包络图手续十分繁琐,对于连续梁之类的多跨梁尤其如此。介绍一种利用奇异函数对连续梁进行力学分析的新方法及其智能分析软件。该方法利用奇异函数与拉普拉斯变换相结合的方法导出连续梁变形和内力的普遍表达式,利用变形和内力的边界条件确定约束反力,然后再在内力普遍表达式的基础上建立一种内力包络图的自动绘制方法。该方法和程序对承受任意恒载和活载、具有任意跨数的连续梁具有普遍的适用性。     

钢轨-扣件耦联系统的动力特性试验

为了从源头抑制轨道交通产生的振动噪声,采用力锤激励法实测了扣件 钢轨耦联系统的加速度阻抗,从加速度阻抗曲线上得到了钢轨的振动模态及相应固有频率处的加速度阻抗幅值,通过不平顺波长与激振频率关系推出了不同行车速度下最不利不平顺波长。对钢轨进行了频率响应分析、脉冲响应分析和脉冲响应函数的时频分析,分离出了钢轨振动优势频率,其值与从加速度阻抗曲线识别得到的结果一致,同时还得到了优势频率的振动持续时间。试验说明,优势频率是钢轨振动与辐射噪声的主要频率,只要能控制优势频率的振动,就可以抑制钢轨的全频域振动与噪声     

An algorithm for the continuous Morlet wavelet transform

This article consists of a brief discussion of the energy density over time or frequency that is obtained with the wavelet transform. Also an efficient algorithm is suggested to calculate the continuous transform with the Morlet wavelet.The energy values of the wavelet transform are compared with the power spectrum of the Fourier transform. Useful definitions for power spectra are given.The focus of the work is on simple measures to evaluate the transform with the Morlet wavelet in an efficient way. The use of the transform and the defined values is shown in some examples.     

基于自适应复平移Morlet小波的轴承包络解调分析方法

针对滚动轴承的传统包络解调分析技术需要人工选择参数的缺点,提出一种自适应包络解调分析方法。该方法针对轴承故障在振动信号中表现为冲击衰减波形的特点,采用复平移Morlet小波实现冲击特征波形的自动提取。同时,基于小波系数峭度值最大的优化策略,给出Morlet小波基函数的中心频率和包络因子的优化方法,从而实现与冲击特征成分的最优匹配,获得较好的包络信号。对模拟信号和实际轴承故障数据的应用分析表明,该方法通过对基函数波形的优化匹配,可以有效地解调出弱故障特征分量,效果优于普通的复平移Morlet小波变换,适合于轴承的早期故障特征提取。     

基于Morlet小波的滚动轴承故障信号奇异性分析

针对滚动轴承故障信号分析中单一频域表征的问题,提出了将Morlet连续小波变换应用于故障信号奇异性提取和分析的新方法。在分析了滚动轴承故障信号的奇异性特征和奇异性信号小波检测机理的基础上,将Morlet连续小波用于对滚动轴承故障信息的提取与分析。试验证明,该方案能有效地对滚动轴承故障信号在时间和尺度平面进行分析,可以同时表征奇异性信号的时间和频率信息。     

Adaptive multiwavelets via two-scale similarity transforms for rotating machinery fault diagnosis

Fault diagnosis of rotating machinery is very important and critical to avoid serious accidents. However, the complex and non-stationary vibration signals with a large amount of noise make the fault detection to be challenging, especially at the early stage. Based on the inner product principle, fault detection using wavelet transforms is to match fault features most correlative to basis functions, and its effectiveness is determined by the construction and choice of wavelet basis function. In this paper, a new method based on adaptive multiwavelets via two-scale similarity transforms (TSTs) is proposed. Multiwavelets can offer multiple wavelet basis functions and so have the possibility of matching various fault features preferably. TSTs are simple and straightforward methods to design a series of new biorthogonal multiwavelets with some desirable properties. Using TSTs, a changeable and adaptive multiwavelet library is established so as to provide various ascendant multiple basis functions for inner product operation. By the rule of kurtosis maximization principle, optimal multiwavelets most similar to the fault features of a given signal are searched for. The applications to a rolling bearing of outer-race fault and a flue gas turbine unit of rub-impact fault show that the proposed method is an effective approach to detecting the impulse feature components hidden in vibration signals and performs well for rotating machinery fault diagnosis.     

采煤机摇臂齿轮传动系统振源定位分析方法

为了研究采煤机摇臂传动齿轮的振动分析方法并进行实机振源定位验证,首先,采用小波分析对采煤机摇臂振动信号进行降噪处理和频谱分析,依据特征频率下的振幅结果确定故障齿轮的啮合频率;然后,通过Morlet小波包络解调分析获取边频带信号频谱特征,依据边频带特征频率下的振幅结果确定故障齿轮的转动频率;最后,对频谱分析和Morlet小波包络解调分析的结果进行综合分析,锁定故障齿轮的准确位置。对一台国产采煤机摇臂齿轮传动系统进行了振动测试与信号分析,结果表明,基于小波分析、频谱分析和Morlet小波包络解调分析相结合的振动分析方法可以实现对采煤机摇臂故障齿轮的准确定位,为强噪声环境下复杂齿轮传动系统的故障快速定位和现场定点维修提供了方法支持。