HYBRID WAVELET PACKET-TEAGER ENERGY OPERATOR ANALYSIS AND ITS APPLICATION FOR GEARBOX FAULT DIAGNOSIS

Based on wavelet packet decomposition （WPD） algorithm and Teager energy operator （TEO）, a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and TEO modulation are introduced respectively. The preprocessed sigaaal is interpolated with the cubic spline function, then expanded over the selected basis wavelets. Grouping its wavelet packet components of the signal based on the minimum entropy criterion, the interpolated signal can be decomposed into its dominant components with nearly distinct fault frequency contents. To extract the demodulation information of each dominant component, TEO is used. The performance of the proposed method is assessed by means of several tests on vibration signals collected from the gearbox mounted on a heavy truck. It is proved that hybrid WPD-TEO method is effective and robust for detecting and diagnosing localized gearbox faults.

Structural health monitoring of long-span suspension bridges using wavelet packet analysis

During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage, This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform （WPT）. The WPT- based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum （WPES） has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.

Influence of explosion parameters on wavelet packet frequency band energy distribution of blast vibration

Blast vibration analysis is one of the important foundations for studying the control technology of blast vibration damage.According to blast vibration live data that have been collected and the characteristics of short-time non-stationary random signals,the wavelet packet energy spectrum analysis for blast vibration signal has made by wavelet packet analysis technology and the signals were measured under different explosion parameters(the maximal section dose,the distance of blast source to measuring point and the section number of millisecond detonator).The results show that more than 95% frequency band energy of the signals s1-s8 concentrates at 0-200 Hz and the main vibration frequency bands of the signals s1-s8 are 70.313-125,46.875-93.75,15.625-93.75,0-62.5,42.969-125,15.625-82.031,7.813-62.5 and 0-62.5 Hz.Energy distributions for different frequency bands of blast vibration signal are obtained and the characteristics of energy distributions for blast vibration signal measured under different explosion parameters are analyzed.From blast vibration signal energy,the decreasing law of blast seismic waves measured under different explosion parameters was studied and the wavelet packet analysis is an effective means for studying seismic effect induced by blast.

基于压电传感器的纤维陶粒混凝土冻融损伤检测

针对纤维陶粒混凝土低温下受到冻融损伤导致影响结构安全性问题,基于压电陶瓷传感器进行损伤检测。利用压电传感技术对冻融后的纤维陶粒混凝土试件进行检测,获得不同冻融次数下的应力波信号。当冻融次数增加,试件相对动弹模量和抗弯强度下降,压电陶瓷检测到的应力波信号幅值相应减小,基于应力波的衰减,采用小波包能量分析法将其转化为损伤指数,与冻融试验评价指标损伤程度和抗弯强度损失率进行拟合,吻合度较高。结果表明,纤维陶粒混凝土损伤指数与冻融损伤程度和抗弯强度损失率相关性较强,该纤维陶粒混凝土冻融损伤无损检测方法具有良好可行性。

6kV高压电动机故障智能诊断方法

针对6 kV高压电动机故障智能诊断方法存在错诊率较高和诊断响应时间较长的问题,提出6k V高压电动机故障智能诊断方法。利用无线传感器采集电动机运行数据,利用降噪自编码网络模型对数据去噪处理,利用小波包分析技术获取数据小波包能量熵信息,提取数据特征,根据计算故障特征频率,诊断电动机故障类型,以完成6 kV高压电动机故障智能诊断。实验证明,该设计方法错诊率在1%以内,能在1s内完成故障诊断,具有良好的应用前景。

Environmental variability study on the measured responses of Runyang Cablestayed Bridge using wavelet packet analysis

The structural damage alarming method based on wavelet packet energy spectrum (WPES) for long-span cable-stayed bridges is presented through combination of ambient vibration test and wavelet packet analysis. The environmental variability in the measured WPES and damage alarming indices ERVD of the Runyang Cable-stayed Bridge are discussed in detail using the wavelet packet analysis of the measured acceleration responses of the bridge under daily environmental conditions. The analysis results reveal that the actual environmental conditions including traffic loadings, environmental temperature and typhoon loadings have remarkable correlations with the measured WPES. The changes of environmental temperature have a long-term trend influence on the WPES, while the influences of traffic and typhoon loadings on the measured WPES of the bridge present instantaneous changes because of the nonstationary properties of the loadings. The analysis results of the measured responses further reveal that the damage alarming indices ERVD can sensitively reflect the influences of environmental temperature and typhoon loadings on the dynamic properties of Runyang Cable-stayed Bridge. Therefore, the proposed structural damage alarming indices ERVD under ambient vibrations are suitable for real-time damage alarming for long-span cable-stayed bridges.

基于压电智能骨料的3D打印断续节理围岩内部损伤监测

3D打印模型试验是研究复杂地质结构损伤机制的有效手段,3D打印逐层堆积过程中定位压电骨料可有效提高埋设精确度和模型内部损伤监测精度。该文采用3D打印增减材技术制备内部埋设压电骨料的断续节理围岩模型,基于压电骨料与数字图像相关技术(digital image correlation,DIC)监测围岩模型在单轴加载下的破坏过程,研究节理连通率对围岩模型破坏机制的影响规律,验证压电骨料定位围岩模型起裂位置和监测内部裂隙损伤扩展的可行性。结果表明:1)随着节理连通率的增大,围岩模型荷载-位移曲线的峰值强度降低、延性增强,由单峰曲线变为多峰曲线;2)断续节理围岩模型的起裂位置多在临近洞口的节理尖端或顶板和底板的中部,裂纹扩展方向大多沿着节理尖端方向,表现为块体分离破坏;3)预制节理连通率增大会导致同路径的监测信号能量衰减,连通率与信号能量之间表现出抛物线相关性;4)压电骨料监测方法相比于DIC监测等宏观监测方法可以更早一步发现模型内部损伤,并能确定内部损伤的位置。

基于小波包能量与模型修正的海洋平台结构损伤识别

对于常年服役的海洋平台,准确的损伤识别是保证其安全运行的重要保障。提出了一种对损伤敏感的小波包分解方案选取原则,以结构损伤前后加速度信号的小波包能量变化率作为残差,以结构的弹性模量作为待修正参数,通过灵敏度分析构建了一种新的目标函数用于模型修正和结构的损伤识别。将上述识别方法应用于简支梁模型,能够准确地识别出损伤的存在、位置和程度,验证了方法的可行性。对被噪声污染的信号进行识别分析,证明方法具有一定的鲁棒性。对噪声污染严重的信号进行小波阈值降噪处理,识别效果较降噪前有所改善。将方法应用于海洋导管架平台模型,对不同层高、不同杆件类型的损伤工况均能有效识别,说明方法对多层复杂结构同样适用。

基于机器学习算法的船舶电气故障分类与诊断方法

为实现船舶电气故障的早发现、早解决,设计基于机器学习算法的船舶电气故障分类与诊断方法。采用Trager能量算子增强传感器采集到的船舶电气设备振动信号,利用小波包分析方法提取增强后的电气设备振动信号特征,将电气设备振动信号特征输入卷积神经网络中进行训练,得出最佳的故障分类与诊断模型,并利用该模型实现船舶电气设备的故障分类与诊断。实验表明:采用Teager能量算子可以快速准确地将传感器采集的信号放大,且放大过程没有信息损失。训练后卷积神经网络的故障分类与诊断正确率接近100%,可能够准确诊断出船舶电气设备是否存在故障,并获取对应的电气故障类型。

下穿隧道爆破振动测试及能量分布研究

依托具体的下穿隧道工程实例,对爆破施工引起的地面振动效应进行系统研究。为进一步分析隧道爆破对既有村庄带来的振动影响,引入反映高程的影响因子,通过量纲分析的方法建立反映高程影响的质点峰值振动速度的预测模型。预测结果表明,与传统的萨道夫斯基公式相比,改进公式的预测效果更佳。此外,通过小波包分析对爆破振动能量的分布特征进行研究。研究结果显示,随着最大单响药量的增大,爆破振动的低频带能量占比明显上升;随着爆心距的增加,爆破振动总能量却呈逐步衰减的趋势,且随着爆心距的逐渐增大,爆破振动能量的变化趋于平缓。爆破振动总能量的拟合结果表明,振动能量随着爆心距的增大呈指数型衰减。然而,爆破振动能量随着最大单响药量的增大却呈现增大的趋势。

Research on seasonal correlation of wavelet packet energy spectrum and temperature of Runyang Suspension Bridge

In order to establish an environmental-condition-normalized structural damage alarming method,the seasonal correlation analysis of wavelet packet energy spectrum(WPES)and temperature of Runyang Suspension Bridge is performed by means of the 236-day health monitoring data.The analysis results reveal that the measured WPES has remarkable seasonal correlation with the environmental tempera-ture.The seasonal change of environmental temperature accounts for the variation of the damage alarming parameter Ip of the dominant frequency bands with an averaged variance of 200%.The statis-tical modeling technique using a 6th-order polynomial is adopted to formulate the correlation between the WPES and temperature,on the basis of which the abnormal changes of measured damage alarming parameter Ip are detected using the mean value control chart.It is found that the proposed method can effectively eliminate temperature complications from the time series of WPES and exhibit good capa-bility for detecting the damage-induced 10% variances of the damage alarming parameter Ip.And the proposed WPES-based method is superior the modal frequency and hence is more suitable for online real-time damage alarming for long-span bridges.

基于安全监控系统CO数据的综采工作面作业工序模糊聚类模式智能识别研究

根据某煤矿综采工作面正规作业流程实际情况以及不同阶段CO涌出规律,合理划分采煤工序。通过收集煤矿安全监控系统KJ95X现场采集的上隅角CO浓度时间数据,采用小波包阈值去噪的方法对原始数据进行数据处理,利用小波包分解提取不同采煤工序数据的能量谱作为特征向量,模糊c-均值聚类和加权模糊c-均值聚类对比聚类识别准确率和计算耗时发现,加权模糊c-均值聚类耗时长,但是聚类准确度大大提升。

基于小波包能量变化率的钢桁架损伤识别研究

提出了一种基于小波包能量变化率的钢桁架结构损伤识别方法.运用Ansys软件对钢桁架结构进行数值模拟,得到结构各节点的加速度响应数据;利用Matlab对加速度响应数据进行小波包分析,然后通过小波包能量变化率指标识别损伤.主要研究了不同损伤位置、不同损伤程度、以及噪声对损伤识别的影响.数值模拟结果表明,小波包能量变化率指标能准确有效地识别损伤,该方法具有较好的鲁棒性.

基于小波包能量谱的结构损伤预警方法研究

基于小波包分析推导了结构动力系统在不同分析尺度上的状态方程和观测方程,在此基础上研究了结构动力响应在不同分析尺度上的时-频特性以及系统矩阵和测量噪声在各个分析尺度上的递推性。理论分析证明,采用结构动力响应的小波包能量谱进行结构损伤预警具有较好的损伤敏感性和噪声鲁棒性。根据瞬态激励的特性提出对激励和响应的时域互相关序列进行小波包分解得到小波包能量谱,并在此基础上计算结构损伤预警指标。通过一钢筋混凝土板静力承载力的振动试验分析,对板不同受力阶段的损伤状态进行了判别,并与实际损伤程度进行了比较。

岩石声发射Kaiser点信号频带能量分布和分形特征研究

通过单轴加载岩石破坏全过程声发射试验,根据Kaiser效应原理采用参数法确定了Kaiser点。在此基础上,首先采用小波包频带分解方法,对岩石声发射Kaiser点信号的能量分布特征进行了研究,分析了砂岩声发射信号的不同频带能量分布规律,得到了Kaiser点特征频带能量百分比大于相邻点的重要结论。其次,采用G-P算法计算了声发射过程关联分维数,结果表明声发射过程不仅具有分形特征,而且Kaiser点声发射信号关联分维数小于其相邻点,其结论可作为通过波形分析识别Kaiser点的特征。

面向结构损伤预警的小波包能量谱识别参数

对Benchmark钢框架结构试验数据和润扬大桥悬索桥监测数据进行了小波包能量谱损伤预警分析,在此基础上详细考察了不同小波函数和小波包分解层次的损伤预警效果.结果表明:Daubechies小波和Coiflets小波适用于结构损伤预警,并且实际工程中应采用较大的小波函数阶次以获取较好的时域分辨能力和损伤预警能力;小波包分解层次愈大,小波包能量谱的频域分辨能力和损伤预警能力愈强.润扬大桥悬索桥的实测分析表明,随着小波包分解层次的增加,特征频带能量比与温度保持明显的季节相关性,其年变化更为明显.因此,实际工程应用中应尽量选择较大的小波包分解层次.

声发射和小波包分析在损伤状态监测中的应用

为应用声发射技术对结构的损伤状态进行监测与识别,基于小波包分析提出了一种在线损伤监测方法。采用D-S证据理论对声发射信号的小波包能量谱进行多源信息融合得到改进的小波包能量谱,计算Mahalanobis距离构建结构损伤状态判别指标,采用t检验的概率方法考察不同损伤状态下判别指标的变化情况。旋转轴承结构的声发射信号分析结果表明,D-S证据理论能够对声发射信号的小波包能量谱识别样本抽取有效信息,结构损伤状态判别指标具有良好的结构损伤识别能力,能够准确地实现对结构不同损伤状态的识别。

基于小波包分析的结构损伤定位方法

提出了基于小波包节点能量(WPCE)相对变化量的结构损伤定位方法,采用其斜率向量和曲率向量2个指标作为损伤定位的依据,从而做到对于结构损伤的无模型定位,最后通过数值算例验证了该方法的可行性。

基于声发射检测的阀门泄漏故障模式诊断技术研究

为了实现对阀门泄漏故障更直观、准确的诊断,采用理论与试验相结合的方法,对工程实际中常见的阀门泄漏模式进行了归纳和分类,分析了典型泄漏模式下阀门漏孔处流场及能量计算方法;对具有不同泄漏模式的阀门泄漏状态进行了模拟试验研究,并对阀门泄漏声发射信号进行了小波包分析,获得不同泄漏模式下阀门泄漏产生的声发射信号能量的变化规律.结果表明:不同泄漏模式下阀门发生泄漏产生的声发射信号各子频率段能量比具有规律性差异;该诊断标准为阀门泄漏故障的可视化诊断奠定了一定的基础.