Study On Methods And System For Fault Characteristics Extraction Of Rotating Machines Based On Local Mean Decomposition

In recently decade years, fault diagnosis technology has been deep researched and some important development has been gotten. Time-frequency analysis method based on Local Mean Decomposition (LMD) is a signal process method appeared in recent years. Through this method we can acquire the instantaneous frequency of the signal, which always has physical meaning in any time. The instantaneous frequency may be an important characteristic of rotating machine fault diagnosis. Based on the 'Study on the new method for rotating machine faults diagnosis based on independent component analysis' (National Nature Science Fund Project, No: 50205025) and 'Study on the new method of noise source recognition of complex system based on ICA-EMD analysis' (National Nature Science Fund Project, No: 50505016), the basic principle and algorithm of LMD, and its application in the rotating mechanic faults diagnosis is discussed in this paper. The main research content is as follows:In chapter one, we discuss the importance and the main method of rotating mechanic faults diagnosis. A survey of faults diagnosis of machines and a summary of recently development are presented. LMD based time-frequency method and the state-of-the art in home and abroad are introduced.In chapter two, we introduce some basic concept of LMD -based time-frequency analysis method. After that, the theory and the algorithm of LMD are presented. Then examples are given to show the application of LMD in the rotating mechanic faults diagnosis. In the end, the difference between LMD and EMD (Empirical Mode Decomposition) is described to point out the advantage of LMD.In chapter three, we discuss the direct method acquiring instantaneous frequency from a signal. We apply a smooth method to improve the direct method. A limit of direct method is given out. We also discuss the relationship between instantaneous frequency of the purely frequency modulation signal and instantaneous frequency of the PF(Product Function). By simulation signal and practice signal, the validity of the instantaneous frequency which is received by the direct method is testified. The direct method, Hilbert transform and Teager energy method are compared. The result shows that as to the signal instantaneous frequency, the extreme value of signal must be±1. For AM-FM signal, the direct method can gain the variation of frequency and amplitude. The direct method can reflect the intra-wave modulation phenomena.In chapter four, we discuss the sampling effect of LMD and the judge of purely frequency modulation signal. Aiming at the non-convergent problem of LMD algorithm, the new selection method of moving averaging span is provided, which can make LMD convergent in the case the distances between neighboring extreme points have great variety. A kind of evaluation index of LMD end effect is provided. The difference of the EMD end effect and LMD end effect is analyzed and compared, and we provide a new kind of signal extend technology to reduce LMD end effect. The conclusion is that the selection method of moving averaging span will influence the convergence of LMD algorithm. Compared to EMD, the degree of end effect of LMD is very light and the influence range is small.In chapter five, we apply the LMD-based time-frequency analysis method at vibration signal analysis of rotating machine. Firstly, we introduce the experiment device and the LMD-based faults diagnosis prototype system. Then we discuss the time-frequency character of three kinds of faults such as rotor crack, oil film whirling and shaft-misalignment, which testified the feasibility of LMD-based time-frequency analysis method in the faults diagnosis of rotating machine.In chapter six, we discuss the framework of the faults diagnosis system, the overall scheme of embedded faults diagnosis system is provided, and the new keyphase signal preconditioning circuit is developed which has been applied in a power unit. The practice testifies that reliability of data acquiring system can be greatly increased. The new circuit has obtained the Chinese invention patent authorization. Keyphase signal frequency multiplied technology is improved and the resampling-based integer period sample method is improved. The simulation shows that testing pulse period using gravity method will have higher noise-resistant ability than that using zero-cross method which is always used in the past. In this paper, relative detailed test result is given.In chapter seven, we summarized the research content of the whole paper. The prospect is given on the research direction and possible research content in the future.