基于代数网络和混沌参数的碰摩声发射源定位方法研究

针对时差定位法受不同模式波速度差异及波形传播畸变等因素影响的问题,将神经网络技术应用到声发射源定位中.为了克服传统BP算法训练时间长和精度不够高的缺点,提出代数神经网络概念,在网络训练阶段引入代数算法.将复杂的非线性优化问题转化为简单的代数方程组求解问题,直接获得最优点,大大缩短了网络的学习时间.同时作为定位特征研究分析了转子碰摩声发射信号的非线性动力学特性,提出了关联维数、最大Lyapunov指数和Kolmogoroy熵等声发射源的非线性动力学新特征,并将其作为神经网络的输入定位特征.实验结果表明,利用这些声发射源的非线性动力学特征和神经网络结合能较好地解决了碰摩声发射源定位问题,为转子碰摩故障诊断提供依据,具有良好的应用前景和进一步研究的价值.     

基于声信号三维谱分析的转子复合碰摩故障特征提取

转子在运行过程中的声音包含了大量的转子运行状态信号,变速过程中故障声信号特征的提取及其识别对于旋转机械故障诊断是极其必要的,目前基于声信号三维谱分析的转子故障特征提取还不多,在对转子旋转机械中的一些典型产生的碰摩故障及复合碰摩故障进行了试验模拟,对故障发生过程中的声信号进行采集的基础上,对转子故障声信号的三维谱特性进行了分析。提取和总结出由故障造成的声信号突变和对应的声谱特征。分析结果表明:采用声信号对转子的碰摩故障进行诊断是有效的。声信号三维谱图丰富旋转机械碰摩故障诊断系统知识库中的特征信息,可以用于更准确地诊断转子中的碰摩故障。     

AE信号快速辨识

根据煤岩声发射监测特性以及声发射信号推断声发射源的技术,提出一种利用近场MUSIC算法快速识别煤岩声发射信号的方法。在煤矿AE信号监测中,利用该算法对声发射信号的空间位置进行估计,将该算法估计的结果与巷道形状及工作面相适配,可以基本定位声发射源的位置。仿真实验结果证明了该算法的有效性。     

基于定子振动的转子碰摩故障诊断方法研究

转子碰摩会引发转子和定子的振动,但由于转子系统的很多常见故障(如不对中、不平衡等)与碰摩故障的转子振动特征多有重复之处,在很大程度上限制了故障的有效诊断.于是以定子振动信号为诊断源,研究了碰摩故障的诊断技术.首先分析了定子振动的机理,认为碰摩时定子受到冲击力作用,会引发定子固有频率振动,提出可采用共振解调法进行碰摩故障的诊断.利用IFFT方法进行了定子固有振动信号的分离,再进行希尔伯特变换,得到其包络信号,并对其进行谱分析,从而完成分析诊断过程.最后进行了单点碰摩和局部碰摩的故障模拟实验,结果表明定子高频固有振动包络信号可以揭示碰摩故障的发生,结合角度定位信号,可以对转子碰摩故障进行定位.     

基于近场声阵列的旋转机械噪声源识别

为了有效控制旋转机械噪声,利用信号处理技术对整机或部件进行噪声源识别是十分必要的,噪声源准确识别可以为故障诊断和结构优化提供依据。首先论述建立均匀线性近场声阵列模型以获得空间声场数据的方法。其次,在传统波束形成结果基础上,利用反卷积法从中提取所需声场信息以实现对声源面可视化重构。接着,在所搭建转子噪声试验台上,利用近场声阵列提取各种工况下噪声信号,并识别出轴承以及盘轴连接处为转子主要噪声源,验证了基于声源成像反卷积法均匀线性近场声阵列在旋转机械噪声源识别方面的可行性。     

一种新的声发射信号消噪及故障诊断方法

在旋转机械故障诊断中,声发射信号极易受到噪声的干扰。针对经验模态分解(EMD)易产生模态混叠现象,提出了一种基于经验小波变换(Empirical Wavelet Transform,EWT)的消噪和旋转机械声发射碰摩故障诊断的方法。利用了EMD和小波变换的优点,通过对傅里叶频谱进行自适应划分,并构建小波滤波器组来提取声发射信号所包含的不同固有模态分量,可有效消除模态混叠现象,同时对分量进行Hilbert变换从而实现声发射信号的消噪和故障诊断。采用该方法对仿真信号进行加噪声和消噪处理,在同信号源下,对比基于d B4全阈值消噪、d B4默认软阈值消噪、d B4对高频系数处理消噪和EMD消噪效果。并将该方法应用到实际的声发射碰摩信号中。仿真和实验分析结果表明:EWT方法可以有效地分解出信号的固有模态,分解出的模态少,并且不存在难以解释的虚假模态,消噪效果优于其他方法,并且在声发射故障诊断中也有较大的优势。     

基于小波变换与统计分析的转子碰摩声发射特性研究

为解决转子碰摩损伤声发射信号分类及解释难题,应用PCI-2声发射系统和WS-ZHT1型多功能转子实验台组成转子碰摩声发射检测系统,采集转子局部碰摩声发射信号,通过理论分析声发射信号特征和小波基函数性质,dB8小波适合提取声发射信号特征;碰摩产生大量声发射信号,大量声发射信号的统计特性蕴涵较多碰摩信息。对不同转速条件下不同检测位置碰摩声发射信号的统计分析表明,声发射信号的功率谱密度集中在100～400 kHz。声发射信号平均幅值、平均能量可作为区分转子碰摩程度特征参数;功率谱主频可作为区分声发射相对位置特征参数,结论与碰摩类型无关。     

基于EMD与相关系数原理的故障声发射信号降噪研究

声发射信号经常受到许多非平稳非线性噪声的干扰,这给对有用声发射信号的识别增加了困难。依据相关系数原理提出了一种基于经验模态分解的旋转机械碰摩声发射信号的去噪方法,通过求出含噪信号经过经验模态分解后所得到的各阶本征模态函数与含噪信号自身的相关系数,根据其变化规律并结合经验模态分解的滤波特性,选取被噪声污染程度较低的本征模态函数对信号重构以达到去噪目的。该方法应用于被不同种类噪声污染的碰摩声发射信号的去噪,实验结果表明此方法能有效的去除噪声,并具有不受主观参数影响,结果稳定,自适应等优点。     

基于声发射原理的螺栓连接状态辨识方法研究

振动环境中螺栓连接结构会发生碰摩现象,产生声发射信号。利用声发射参数分析方法对声发射检测信号进行时域分析,结果表明：振铃计数率随振动台加速度的提高而提高;螺栓连接结构在碰摩作用下产生出的能量与施加给螺栓的预紧扭矩的取值呈现一定的规律性。基于上述结果可以利用声发射进行螺栓连接结构的状态辨识。     

基于小波变换降噪的声发射源定位方法

选取最优小波基对声发射信号进行小波变换降噪处理,采用阈值法确定不同传感器接收声发射信号时间以提高各向异性材料中声发射源定位精度。在钢板和木板上进行断铅模拟声发射源实验,利用Geiger算法分别计算出降噪前后的声发射源定位结果以验证该定位方法的有效性。结果表明该定位方法能有效减小噪声信号的影响,提高各向异性材料中声发射源定位精度。采用该定位方法对氧化铝陶瓷试件压缩破坏过程中的声发射源进行定位,定位结果有效地反映了材料内微裂纹产生和扩展而导致试件破坏的动态过程。     

滚动轴承故障非接触多传感器声信号融合方法

摘　要：针对移动滚动轴承非接触声发射检测中,一个故障源信号可能被多个传感器采集,致使这些声信号包含故障信息不完整且存在重叠的问题,综合考虑声波传播理论、多传感器声信号时差关系、滚动轴承典型故障撞击频率等,建立滚动轴承故障非接触多传感器声信号融合方法。建立滚动轴承故障非接触多传感器声发射检测试验台,分别采集移动滚动轴承滚动体、外圈和内圈故障声信号。采用融合方法对同声源信号进行处理,利用信号相似理论证明了融合信号与故障源信号的相似程度高于各传感器声信号。采用声发射累计撞击计数法对融合处理后的滚动轴承不同故障声信号进行分析。结果表明,该融合算法能有效地处理多传感器接收的同声源信号,可利用融合后信号进行准确的故障识别。     

Simulation of Acoustic Emission in Planar Carbon Fiber Reinforced Plastic Specimens

The simulation of acoustic emission waveforms resulting from failure during mechanical loading of carbon fiber reinforced plastic structures is investigated using a finite element simulation approach. For this investigation we focus on the dominant failure mechanisms in fiber reinforced structures consisting of matrix cracking, fiber breakage and fiber-matrix interface failure. To simulate the failure process accurately, we present a new acoustic emission source model that is based on the microscopic source geometry and micromechanical properties of fiber and resin. We demonstrate that based on this microscopic source model these failure mechanisms result in excitation of macroscopic plate waves. The propagation of these plate waves is described using a macroscopic three-dimensional model geometry which includes contributions of reflections from the specimen boundaries. We further present a model of the acoustic emission sensors used in experiments to simulate the influence of aperture effects. To enhance the understanding of correlation between macroscopically detectable acoustic emission signals and microscopic failure mechanisms we simulate the response to different source excitation times, crack surface displacements and displacement directions. The results obtained show good agreement with fundamental assumptions about the crack process reported by various other authors. The simulated acoustic emission signals obtained are compared to experimentally measured waveforms during four-point bending experiments of carbon fiber reinforced plastic structures. The simulated signals of fiber-breakage, matrix-cracking and fiber-matrix interface failure show systematic agreement with the respective experimental signals.     

Detectability of Crack Lengths from Acoustic Emissions Using Physics of Wave Propagation in Plate Structures

This paper presents a study to understand the physical nature of fatigue crack growth as an acoustic emission source and detectability of the crack length form the recorded acoustic emission signal in plate structures. For most of the thin walled engineering structures, the acoustic emission detection through sensor network has been well established. However, the majority of the research is focused on prediction of the acoustic emission due to fatigue crack growth using stochastic methods. Where, stochastic models are used to predict the criticality of the damage. The scope of this research is to use predictive simulation method for acoustic emission signals and extract the damage related information from acoustic emission signals based on physics of material. This approach is in contrast with the traditional approach involving statistics of acoustic emissions and their relation with damage criticality. In this article, first, we present our approach to understand fatigue crack growth as source of acoustic emission using physics of guided wave propagation in FEM. Then, using this physical understanding, we present our investigation on detectability of crack lengths directly from crack-generated acoustic emission signals. Finally, we present our method to extract fatigue crack length information from acoustic emission signals recorded during fatigue crack growth.     

Acoustic emission location on aluminum alloy structure by using FBG sensors and PSO method

Acoustic emission location is important for finding the structural crack and ensuring the structural safety. In this paper, an acoustic emission location method by using fiber Bragg grating (FBG) sensors and particle swarm optimization (PSO) algorithm were investigated. Four FBG sensors were used to form a sensing network to detect the acoustic emission signals. According to the signals, the quadrilateral array location equations were established. By analyzing the acoustic emission signal propagation characteristics, the solution of location equations was converted to an optimization problem. Thus, acoustic emission location can be achieved by using an improved PSO algorithm, which was realized by using the information fusion of multiple standards PSO, to solve the optimization problem. Finally, acoustic emission location system was established and verified on an aluminum alloy plate. The experimental results showed that the average location error was 0.010 m. This paper provided a reliable method for aluminum alloy structural acoustic emission location.     

Fracture source location in thin plates using the wavelet transform of dispersive waves

A new signal processing approach was presented for acoustic emission source location using the dispersive waves in a thin plate. For wave propagation in dispersive media, the accuracy of source location can be improved by using the arrival times of a single frequency component in the output signals at an array of sensors. The wavelet transform (WT) was used to resolve this problem. By utilizing the time-frequency data of the WT, the frequency-dependent arrival time traveling with the group velocity was shown to be easily determined. Experiments were performed using a lead break as the simulated fracture source on the surface of an aluminum plate. Two plate modes corresponding to the S(0) and A(0) Lamb waves were identified, and their group velocities were accurately measured. The source location results based on the WT method agreed well with the true locations. The WT method was also compared with the cross correlation technique, and both methods provide similar results.     

一种声发射源的新型平面定位方法研究

声发射现象中产生的弹性波在传播时声压遵从指数衰减规律,文中提出一种利用声衰减特性对声发射源进行平面定位的能量定位新方法。从理论上导出了该方法的定位计算公式,并用AE21C型声发射仪在高分子合成纤维平板上以铅笔芯折断产生信号为模拟源进行了实验测量,证明这种新的源定位方法可行,并具有无须测量传声媒质的声衰减和声速等优点。     

提高被动声纳宽带检测性能的一种新方法

宽带能量检测是被动声纳实现目标探测功能的常用方法,常规能量检测(Conventional Energy Detection,CED)方法在复杂环境下的检测性能迅速降低.子带峰值能量检测(Subband Peak Energy Detection,SPED)可以有效改善常规能量检测方法的性能,提高时间方位历程显示(BTR...     

碳纤维增强复合材料层合板Lamb波衰减特性研究

为提取适用于碳纤维增强复合材料层合板声发射故障诊断的模态信号,利用三维弹性理论及传递矩阵法获得Lamb波的频散曲线。以碳纤维增强复合材料层合板为研究对象搭建实验平台,改变断铅激励位置从而获得不同声发射信号。对采集的声发射信号进行小波尺度谱分析,结合频散曲线分离出不同模式的Lamb波,分别研究其不同频率的幅度及能量衰减特性。实验结果表明,较其它信号,低频率S0波幅度信号衰减速度较低,对碳纤维增强复合材料层合板的声发射故障诊断研究具有较大优势。     

基于声发射和长短时记忆神经网络的端对端燃气高压调压器故障诊断

在燃气输配系统中燃气调压器处于关键位置,及时有效地诊断其故障类型具有重要意义。文章提出了一种基于声发射信号和长短时记忆神经网络的端到端故障诊断方法,直接利用时域声发射信号对调压器的运行状态进行诊断。首先,设计一个二阶巴特沃斯高通滤波器对采集的声发射信号进行预处理;其次,利用长短时记忆网络（LongShort Term Memory networks,LSTMs）的记忆特性,构建长短时记忆网络端到端（e2e-LSTM）故障诊断模型。实验结果表明,该模型根据输入的高压调压站采集的声发射信号,能够以端到端模式一次性地诊断五种高压调压器故障。