导　　师： 马春燕;张清华

学科专业： 0811

授予学位： 硕士

作　　者： ;

机构地区： 太原理工大学

摘　　要： 频谱分析技术通过分析采集到的振动信号,来判断机械设备的运转状态,达到故障诊断的目的,但目前一般的频谱分析技术是基于单一的谱进行故障诊断分析,虽然此类故障诊断分析技术有了一定的诊断准确率,但不是很高。在旋转机械轴承的故障诊断中大部分依靠经验模态分解方法,但在其分解过程中需要提前求出数据函数的极值点,并且保证完整提取出极值点信号,这限制了经验模态分解的应用。 本文研究基于多频谱分析算法和GEMD的分析算法的故障诊断,具体工作如下： /(1/)针对目前的频谱分析技术多为单一频谱分析且诊断精度不高的现象,研究得出多频谱分析算法。此算法基于排除分析法的原理,利用单一频谱分析时,会出现干扰故障,此时采用诊断结果两两相结合,排除干扰的信号,进行故障诊断。 /(2/)针对经验模态分解时的极值点求解问题,利用遗传算法在目标函数无法求导或者导数不存在的情况下仍能进行最优化求解的特性,首先求出数据函数的极值点,保证得到完整的极值点,然后进行经验模态分解,最后构造包络谱,进行故障诊断分析。 /(3/)将多频谱分析算法应用在旋转机械轴的故障诊断中,实验验证了该算法的可行性,并较单一频谱分析的故障诊断,提高了诊断准确率。旋转机械轴承故障信号多为高频信号,GEMD的包络谱分析算法能够很好的提取出高频信号,因此将此算法应用在滚动轴承的故障诊断中,通过试验验证了该算法的可行性和有效性。 In order to judge the running state of the equipment, it analyzing the vibration signals which were collected, last diagnosing fault, this is spectrum analysis. But now spectrum analysis technique is based on single spectrum analysis on fault diagnosis, the diagnosis of such technology is not high. Rely on empirical mode decomposition for the fault diagnosis of rotating machinery bearing, but need to calculate the extreme point of function first of all. Ensure to collect the extreme value point of all signal, this limits the application of empirical mode decomposition. In this paper, we study multiple spectrum analysis algorithm and GEMD analysis algorithm of fault diagnosis, specific work is as follows: /(1/) In view of the current spectrum analysis technique for a single frequency spectrum analysis and diagnosis accuracy is not high phenomenon, this paper main research multiple spectrum analysis algorithm. The principle of the algorithm is to diagnose fault rely on the method of exclusion. /(2/) Need to solve the problem of extreme value point when using empirical mode decomposition. Genetic algorithm can find out the function extreme value point when the function not guide or derivative does not exist. First calculates the extreme point of function and ensures acquiring all the extreme value point of function. Secondly carries on the empirical mode decomposition, finally structures spectrum envelope and analysis of the fault. /(3/) Applies multiple spectrum analysis algorithm in fault diagnosis of rotating machinery shaft, through Experiments verify the feasibility of the algorithm, it have a high accuracy than a single spectrum analysis technology. Most of rotating machinery bearing fault signal are high frequency signal. Envelope spectrum analysis of GEMD can extract the high frequency signal very well, Applies the algorithm in fault diagnosis of rolling bearing and Applies the algorithm in fault diagnosis of rolling bearing, Verifies the feasibility of this method.

关 键 词： 振动信号 频谱分析 遗传算法 经验模态分解 故障诊断

分 类 号： [TH165.3]

领　　域： [机械工程]