频带熵方法及其在滚动轴承故障诊断中的应用

发布时间：2018-01-05 18:06

本文关键词：频带熵方法及其在滚动轴承故障诊断中的应用　出处：《上海交通大学》2012年硕士论文　论文类型：学位论文

【摘要】：随着科学技术的日益进步与现代工业的飞速发展,机械设备不断向大型、复杂、高速、高效及重载的方向发展;与此同时,其工作和运行环境也更加复杂和苛刻。这些设备一旦突然发生故障,不仅会增加企业的维护成本,降低企业的生产效率,还可能造成巨大的经济损失,甚至导致严重的人员伤亡,产生不良的社会影响。因此,如何对设备进行有效的状态监测和故障诊断,是当前亟需解决的问题。如何有效提取反映设备运行状态的特征,以及准确判断故障类别,一直是故障诊断领域的研究热点,新方法和新理论的研究也层出不穷,对丰富和完善机械故障诊断技术起到了重要作用。本文以滚动轴承为研究对象,提出频带熵方法,并对其在故障诊断中的应用进行了研究,旨在为滚动轴承状态监测提供一个新指标,为故障诊断信号预处理提供一种新方法,论文主要包括以下几个方面的内容: (1)从理论分析与工程应用的角度出发,阐述了论文的选题背景和研究意义。分析了机械设备故障诊断方法、滚动轴承故障诊断、时频分析与信息熵理论等方面的国内外研究现状,确立了本文的研究内容。 (2)介绍了作为本文理论基础的几种时频分析方法及信息熵理论,借鉴谱峭度方法提出频带熵概念,定义频带熵为某一频率上(频带内)信号的复杂度,或者说不确定性,给出了频带熵的基本算法,最后从滤波的角度对频带熵概念进行了扩展。 (3)介绍了滚动轴承的振动机理和故障特征。讨论了频带熵指标用于滚动轴承状态监测的可能性,对其鲁棒性进行了研究,证明其对奇异点的不敏感性。基于频带熵的上述特性,将其应用于滚动轴承全寿命周期数据分析,探讨了频带熵指标在性能退化各阶段的表现。介绍了为上述理论提供数据支撑的滚动轴承故障试验和加速疲劳寿命试验,通过对试验数据的分析,表明频带熵可作为状态监测指标的有效补充。 (4)针对共振解调带通滤波中心频率难以确定的问题,提出了频带熵确定中心频率的方法。对基于STFT的频带熵,讨论了频率离散点数、时频分析窗长、窗函数类型等参数对频带熵的影响;对基于小波包变换的频带熵,讨论了小波包分解层数和小波包函数的选择对频带熵的影响。最后将两种方法应用于仿真和实际的滚动轴承故障诊断。分析结果证明,频带熵能够准确确定信号的共振频带,提升带通滤波和包络解调后的诊断效果。 (5)提出频带熵与遗传算法相结合的方法,用于共振解调带通滤波器的优化设计。以频带熵最小为遗传算法的优化目标,通过选择、交叉、变异等操作,在取值范围内寻找最优的中心频率和带宽组合,设计优化滤波器。通过对仿真信号和不同信噪比实验数据的分析,证明此方法能够有效确定滤波中心频率和带宽,从而提高信号的信噪比,实现对轴承故障的诊断。
[Abstract]:Along with the rapid development of science and technology and the rapid development of modern industry , the machinery and equipment continue to develop in the direction of large , complex , high speed , high efficiency and heavy load . At the same time , its work and operating environment are more complex and severe . Once the equipment suddenly fails , it will not only increase the maintenance cost of the enterprise , reduce the production efficiency of the enterprise , but also can cause great economic loss , even lead to serious casualties and bad social impact . Therefore , how to carry on the effective state monitoring and fault diagnosis of the equipment is a problem that needs to be solved urgently . How to efficiently extract the characteristics reflecting the running state of the equipment and accurately judge the fault category has been a hot topic in the field of fault diagnosis . The new method and the new theory have been studied in this paper . The application of the new method and the new theory has been studied in this paper . The application of the new method and the new theory in fault diagnosis has been studied . The purpose of this paper is to provide a new index for the monitoring of rolling bearing status . ( 1 ) From the angle of theoretical analysis and engineering application , the background and significance of the thesis are described . The research status of fault diagnosis method , fault diagnosis , time - frequency analysis and information entropy theory are analyzed , and the research contents of this paper are established . ( 2 ) This paper introduces several time - frequency analysis methods and information entropy theory , which is the base of this paper . The concept of frequency band entropy is proposed by using the method of spectrum . The frequency band entropy is defined as the complexity of the signal in a certain frequency ( in - band ) signal , or the uncertainty is given . The basic algorithm of frequency band entropy is given . Finally , the concept of frequency band entropy is expanded from the angle of filtering . ( 3 ) The vibration mechanism and fault characteristics of rolling bearing are introduced . The possibility of using frequency band entropy index to monitor the state of rolling bearing is discussed , and its robustness is studied . Based on the above mentioned characteristics of frequency band entropy , the performance of the frequency band entropy index in all stages of performance degradation is discussed . The fault test and accelerated fatigue life test of the rolling bearing supported by the theory are introduced . The analysis of the test data shows that the frequency band entropy can be used as the effective complement of the state monitoring index . ( 4 ) Based on the frequency band entropy of STFT , the influence of frequency discrete point number , time frequency analysis window length and window function type on frequency band entropy is discussed . The frequency band entropy based on STFT is discussed . ( 5 ) The method of combining the frequency band entropy with the genetic algorithm is proposed for the optimization design of the resonant demodulation band - pass filter . The optimal filter is designed by selecting , crossing , mutation and so on . The optimal filter is designed by selecting , crossing , mutation and so on . By analyzing the experimental data of the simulation signal and the different signal - to - noise ratio , this method can effectively determine the center frequency and bandwidth of the filter , thereby improving the signal - to - noise ratio of the signal and realizing the diagnosis of the bearing fault .

【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH165.3

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