故障参数下齿轮系统非线性动力学行为

为分析齿轮系统在故障条件下的非线性动力学变化机理,对不同故障参数下非线性齿轮系统的动力学行为进行了研究;建立了单齿冲击、单齿刚度、单齿磨损及全齿磨损的非线性动力学模型,采用齿轮混沌振子方法对其进行了分析;探讨了上述4种故障激励产生后齿轮系统吸引子的变化.研究表明,利用齿轮混沌振子能够较好地区分故障信号的大小,为更好地进行故障诊断提供了理论支持,也为旋转机械的故障诊断提供了一种新方法.     

基于倒谱和包络解调的齿轮箱故障诊断

齿轮箱是设备上重要的传动部件,齿轮故障诊断对设备的长期安全运行起着至关重要的作用.根据齿轮振动机理及谱分析来进行振动信息处理和特征提取,是目前齿轮故障诊断中的一种有效方法.分析了齿轮箱的振动故障特性,提出了用解调谱和倒谱两种分析法相结合来对系统的输出信号进行故障诊断的方法.最后在齿轮故障模拟实验台上采集了故障下的振动信...     

故障诊断中的多重分形分析

建立了模拟实际故障的实验装置,采集了碰摩故障、油膜振荡及碰摩和油膜振荡相互作用的耦合故障振动信号。运用多重分形理论,对实测故障信号计算出多重分形广义维数,重点讨论广义分形维数谱和奇异谱,并提出广义维数谱能和奇异谱能的概念,并以两谱能作为特征量,实现对故障特征的提取与识别。研究表明:将广义维数谱能和奇异谱能结合使用,有利于分析识别故障信号,增强可靠性。该研究为复杂旋转机械故障诊断提供了一种识别方法。     

近代机械非线性动力学与优化设计技术的若干问题

简述了混沌学(近代非线性动力学)的形成和发展及其对应用科学和工程科学发展的重要意义。依据混沌理论的发展史介绍了确定性动力系统中的不规则振动(现代科学中最伟大的发现之一)以及周期和拟周期振动,同时也涉及到了作为非线性科学的重要组成部分的分岔理论和奇异性理论。列举了装备制造、能源工业、交通运输、建筑工业以及航空航天等工程技术领域中存在的大量非线性问题。简要叙述了在大型旋转机械和振动机械的非线性动力学研究方面的成果,包括大型旋转机械非线性转子系统的失稳机理、分岔解与混沌运动、故障诊断及其综合治理技术;大型共振筛的非线性振动及其动力学设计方法等。希望能促进我国机械非线性动力学的更大发展,为我国装备制造业的自主创新提供理论支撑。     

基于非线性多参数的旋转机械故障诊断方法

应用关联维数、李亚谱诺夫指数等非线性多参数对旋转机械故障诊断进行研究。对所采集的模拟旋转机械振动故障信号,运用相空间重构理论对其时间序列重构。为使重构相空间能充分地反映系统运动特征,对不同故障信号的时间延迟与嵌入维数确定问题进行研究,计算出不同故障信号的关联维数、李亚谱诺夫指数、复杂度和近似熵四个非线性特征量。在此基础上对四个非线性参数进行融合,并定义为非线性度,用这一特征量对故障信号特征进行提取与识别。由于非线性度是关联维数、李亚谱诺夫指数、复杂度和近似熵多参数的综合,更有利于分析识别故障信号,增强可靠性。研究表明:故障类型不同,非线性度指数不同,验证了这一非线性特征量是表征不同故障信息的有效参数。此研究为复杂旋转机械故障诊断提供一种识别方法。     

基于粒子滤波和自回归谱的液压泵故障诊断

针对飞机轴向柱塞式液压泵的工作状态监控问题,提出了一种基于液压泵振动信号分析处理的故障诊断新方法。通过对加速度传感器的原始数据序列进行信号建模,利用粒子数优化后的粒子滤波算法进行降噪;根据滤波后信号的自回归谱提取特征值,结合液压泵的故障机理分析其工作状态,实现对液压泵的故障分析和诊断。实验及仿真结果表明,粒子滤波可有效跟随原始信号并滤除噪声干扰,基于粒子滤波和自回归谱的液压泵故障诊断方法能有效地提取故障特征值,实现故障诊断和识别。     

基于Hilbert谱奇异值的轴承故障诊断

针对机械故障振动信号时频特征提取问题,提出一种基于Hilbert谱奇异值的特征提取方法,并将其应用于轴承故障诊断。该方法首先利用经验模式分解方法将振动信号分解为若干个内蕴模式函数之和,接着对每个内蕴模式函数进行Hilbert变换得到振动信号的Hilbert谱,然后对Hilbert谱进行奇异值分解,得到反映机械状态特征的奇异值序列,最后利用奇异值作为特征向量,使用支持向量机进行轴承故障诊断。轴承正常、内圈故障、滚动体故障、外圈故障实测信号实验结果表明,该方法能有效地提取轴承故障振动信号特征。
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滚动轴承故障诊断机理研究

滚动轴承是常用机械组件,对其故障机理和诊断方法进行研究,能有效提高其安全性和可靠性。通过建立滚动轴承非线性动力学模型,计算出轴承故障振动响应。在模型计算结果中添加谐波分量和白噪声干扰,通过EEMD分解和峭度分析方法,抑制噪声干扰,突显故障特征信号。以深沟球轴承6205为例验证了故障诊断方法的有效性和动力学模型的正确性。首先建立非线性动力学模型,通过计算分析,揭示故障机理。利用基于EEMD的故障诊断方法,有效地突显故障信号,并验证动力学模型正确性。     

油膜失稳的非线性振动征兆

基于线性振动理论故障诊断技术 ,当故障系统非线性特征明显时常常造成误诊。滑动轴承支撑的转子系统的油膜失稳故障是最常见的非线性振动故障。本文建立轴承转子系统的非线性振动模型和状态方程 ,应用 Matlab系统的 Rounge- kutta法求状态方程的特征乘数 ,编程求解 L yapunov指数。根据 Floquet理论和 L yapunov指数判定系统运动状态 ,求解一系列参数条件下系统响应的数值解 ,以数值解与状态转迁集所表明的系统状态一致证明状态转迁集可以用于指示系统运动状态 ,指导故障诊断。     

一类非线性系统的故障诊断与实现

非线性系统的Volterra级数模型是系统的一种非参数模型,为非线性系统的故障诊断提供了一种新颖的方法.这里阐述了基于Volterra级数模型故障诊断方法的工作原理,介绍了使用单片机实现诊断系统的方法.     

Fault diagnosis for a class of nonlinear systems via ESO

In this paper, a novel fault detection and identification (FDI) scheme for a class of nonlinear systems is presented. First of all, an augment system is constructed by making the unknown system faults as an extended system state. Then based on the ESO theory, a novel fault diagnosis filter is constructed to diagnose the nonlinear system faults. An extension to a class of nonlinear uncertain systems is then made. An outstanding feature of this scheme is that it can simultaneously detect and identify the shape and magnitude of the system faults in real time without training the network compared with the neural network-based FDI schemes. Finally, simulation examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

基于灰关联信息熵的SVM决策树轴承故障分类

为提高轴承故障诊断的准确率,以灰色关联理论和信息熵理论为基础,提出了基于灰关联信息熵提取属性特征的支持向量机决策树多故障分类器.该分类器可以实现对轴承的多故障类型的分类,并对轴承的各类故障进行了分类实验.验证结果表明,该方法可有效地进行故障状态识别,达到了准确进行机械系统多故障诊断的目的.     

粗糙集理论在旋转机械实时故障诊断中的应用

根据旋转机械实时故障诊断的实际需求,引入粗糙集理论中的决策模型,作为典型故障诊断规则的发现工具。并针对故障信号的非平稳性和诊断分析的实时性要求,采用小波包分析(WPA)作为现场数据的频域段特征的提取工具。并首次将小波包分析(WPA)与粗糙集理论的决策模型相结合,提出了适应于现代机械设备在线诊断的故障分析模型WRS。并通过实例,验证了全过程。     

Fault diagnosis of complex system based on nonlinear frequency spectrum fusion

A novel fault detection and diagnosis approach is proposed for nonlinear complex systems by combining nonlinear frequency spectrum characteristics and evidence theory. In order to overcome the problem of calculated amount expansion of generalized frequency response functions, single-dimensional nonlinear output frequency response functions are used to obtain nonlinear frequency spectrum, from which, features of nonlinear frequency spectrum are extracted. The fault diagnosis model of multiple faults is given based on evidence theory. The mass functions of evidences are obtained according to the similarity among different modes. In order to solve the problem of evidence fusion in the situation of evidence confliction, a dynamic parameter conflicting evidence combination method is proposed based on the average credibility. Fault diagnosis of the transmission system of numerical control machine tool is studied through nonlinear frequency spectrum. Simulations indicate that the proposed approach has simple calculation and high recognition rate for faults.     

Auditory-model-based Feature Extraction Method for Mechanical Faults Diagnosis

It is well known that the human auditory system possesses remarkable capabilities to analyze and identify signals. Therefore, it would be significant to build an auditory model based on the mechanism of human auditory systems, which may improve the effects of mechanical signal analysis and enrich the methods of mechanical faults features extraction. However the existing methods are all based on explicit senses of mathematics or physics, and have some shortages on distinguishing different faults, stability, and suppressing the disturbance noise, etc. For the purpose of improving the performances of the work of feature extraction, an auditory model, early auditory(EA) model, is introduced for the first time. This auditory model transforms time domain signal into auditory spectrum via bandpass filtering, nonlinear compressing, and lateral inhibiting by simulating the principle of the human auditory system. The EA model is developed with the Gammatone filterbank as the basilar membrane. According to the characteristics of vibration signals, a method is proposed for determining the parameter of inner hair cells model of EA model. The performance of EA model is evaluated through experiments on four rotor faults, including misalignment, rotor-to-stator rubbing, oil film whirl, and pedestal looseness. The results show that the auditory spectrum, output of EA model, can effectively distinguish different faults with satisfactory stability and has the ability to suppress the disturbance noise. Then, it is feasible to apply auditory model, as a new method, to the feature extraction for mechanical faults diagnosis with effect.     

基于现代非线性理论的汽轮发电机组故障诊断技术研究

运用小波理论、分形理论和混沌理论等非线性理论,对汽轮发电机组转子故障进行了综合分析和研究。对 所测某28 MW发电机组转子在三种不同工作状态下的时间序列进行了关联维数计算、小波包分解以及最大李雅 普诺夫指数计算,并结合其相轨迹图和庞加莱截面进行了分析与研究。结果表明,小波包分解重构技术具有很强 的消噪和非平稳信号提取能力;发电机组转子在不同工作状态下其时间序列的关联维数、李雅普诺夫指数具有明 显差别,且两量值相互补充、相互对应。由此提出:关联维数、最大李雅普诺夫指数可以作为刻画发电机组机械 故障特征的综合量化指标。该研究为非线性运动系统的在线监测、故障诊断和状态预测开辟了有效途径。     

液压AGC系统故障诊断专家系统的实现

针地板带轧机液压ＡＧＣ系统,根据专家系统基本原理,结合古典信号处理方法、模糊理论、神经网络理论,建立了系统故障诊断系统的结构形式和学习算法。利用模糊诊断理论进行模糊推理以解决系统故障的实时诊断,利用神经网络对模糊推理模型进行训练以提高诊断的准确率,并可对未知的知识进行了学习和补充。开发了液压厚度自动控制（ＡＧＣ）系统故障诊断专家系统软件,通过实验证明所用方法有效。     

Fault detection observer design for 2-D continuous nonlinear systems with finite frequency specifications

This research studies the problem of fault detection observer design for two-dimensional (2-D) continuous-time nonlinear systems in Takagi–Sugeno (T–S) form. Finite frequency (FF) specifications are used to design the observers, which makes observer designing different from previously proposed 2-D detection observers. Faults and disturbances are considered to be dominated in two different FF domain intervals. Fault sensitivity and disturbance robustness are measured by two FF performance indices, respectively. The aim of this paper is to design fault detection observers such that the residual error system has the sensitivity to faults and the desired robustness to disturbances. Sufficient conditions for the existence of a desired fault detection fuzzy observer are established in terms of linear matrix inequalities (LMIs). Simulation results indicate that faults can be detected effectively using the proposed method.     

Dynamic characteristics of multi-degrees of freedom system rotor-bearing system with coupling faults of rub-impact and crack

Extensive studies on rotor systems with single or coupled multiple faults have been carried out. However these studies are limited to single-span rotor systems. A finite element model for a complex rotor-bearing system with coupled faults is presented. The dynamic responses of the rotor-bearing system are obtained by using the rotor dynamics theory and the modern nonlinear dynamics theory in connection with the continuation-shooting algorithm（commonly used for obtaining a periodic solution for a nonlinear system） for a range of rub-impact clearances and crack depths. The stability and Hopf instability of the periodic motion of the rotor-bearing system with coupled faults are analyzed by using the procedure described. The results indicate that the finite element method is an effective way for determining the dynamic responses of such complex rotor-bearing systems. Further for a rotor system with rub-impact and crack faults, the influences of the clearances are significantly different for different rub-impact stiffness. On the contrary, the influence of crack depths is rather small. The instability speeds of the rotor-bearing system increase due to the presence of the crack fault. The results obtained using the new finite element model, presented for computation and analysis of dynamic responses of the rotor-bearing systems with coupled faults, are in accordance with measurements in experiment. The formulations given can be used for diagnosis of faults, vibration control, and safe and stable operations of real rotor-bearing systems.