Research On Failure Mechanism And Feature Extraction Technology Of Rotating Machine

Nowadays, fault diagnosis of rotating machine is one of the quickly developed emerging technology at home and abroad. Research and application on monitoring and analyzing system of vibration for large rotating machine is significant to avoid substantive economic loss and disastrous accident. In the development of fault diagnosis technology, the information extraction of fault feature is found to be the most important and difficult problem, and is also the key of the problem. This is the bottle neck of fault diagnosis, and directly governs the accuracy of fault diagnosis and the reliability of early diagnosis. To solve this problem completely, information processing, especially the modern signal processing is the necessary academic and technical methods to explore new path of fault feature extraction of mechanical systems, and develop new theory and technology of fault diagnosis.This paper is the basic component part of the state natural science foundation(50375014,50575016). In this paper, rotating machine vibration is the object of study, and fault mechanism for common failure to mechanical rotating device & machine is researched, and the related fault simulation is accomplished through the experiment on the Bently multi-functional rotor tester, new method for the feature extraction of machine fault signals is developed based on signal purification and shaft orbit. The technology results indicate that the present method's features are high accuracy and less unknowns. The structure of the paper is as follows.Chapter 1 expatiates on the significance of condition monitoring and fault diagnosis system for large rotating machine, and introduces the current situation and all kinds of methods for the research on extraction of fault features in rotating machine, then analyses the development trend of investigation on vibration monitoring technology at home and abroad. In the end, the dissertation puts forward the research's target of the study and summarizes the content and structure of the dissertation.The second chapter makes the research on the fault mechanism of the common failures to mechanical rotating device, and fault features, which contains amplitude domain features, frequency domain features and the relationship between shaft orbit and the mechanical failure.Chapter 3 investigates the application of extraction technology of an shaft orbit in the diagnosis of rotating machine. The first part emphasizes fault feature extraction technology based on moment invariants, Fourier descriptors, geometrical characteristics. And intersections and the number of circles is introduced as the first step for foundational classification, and Slenderness, Bending degree, diameter ratio and phase breadth ratio for detail classification. A comprehensive system for fault feature extraction of rotating machine based on these three extraction technology, is established on MATLAB 7.0 platform. The second part expatiates about the concept of various filters and their effect analysis. After process of filtering of the image, the influence of high frequency component is removed, and the frequency component directly affecting the shape of shaft orbits is extracted, and this provides theoretical foundation for the establishment of the reference model of shaft orbits.Chapter 4 completes the fault simulation on the Bently multi-functional rotor tester, which contains unbalancement, misalignment, oil film eddy and oil film oscillation faults, and analyzes the sampled vibration signal to get the coincidence relation between fault features and the specific faults from the perspective of the test, The comparison of shaft orbits after and before double frequency low-pass filtering is made. Finally, the feature extraction method is applied to the sampled data to complete the fault analysis and state identification.