Lingli Cui

Research on the selection of wavelet function for the feature extraction of shock fault in the bearing diagnosis

For the rolling bearing diagnosis, how to identify the fault feature effectively is the key issue. Due to the resonance modulation characteristic induced by shock fault of the rolling bearings, the wavelet transform technology can extract the modulation information effectively. On the other hand, as there are no fixed kernel functions in wavelet analysis, the transform results are closely related to the wavelet base function types. According to shock and modulation characteristic of localized fault, how to select the proper wavelet base function is discussed in this article. Through analyzing the simulation signal of outer race fault, the base functions for the discrete wavelet transform are optimized. The results have shown that dmey wavelet mother function is prior to other wavelet functions in the shock fault feature extraction. Furthermore, demodulation technology based on Hilbert transform is used to analyze the detailed wavelet decomposition coefficient which contains the modulation phenomenon. And the fault feature can be identified obviously. Finally, the vibration signal collected from fault bearing in the wire rolling mill is decomposed using optimized dmey wavelet. The further FFT analysis on low frequency wavelet decomposition coefficient can also identify the incipient fault feature successfully.

Research on the demodulation method based on the wavelet analysis

Based on wavelet analysis method and Hilbert envelop demodulation, a method for the fault diagnosis of rolling bearings is proposed in this paper. The local Hilbert demodulation and local wavelet transform are introduced respectively. The wavelet transform is used to translate vibration signals into time-scale representation. Then, an envelope signal can be obtained by envelop spectrum analysis of wavelet coefficients of high scales from which the faults in a roller bearing could be diagnosed. Vibration signals measured from roller bearings test rig with outer race faults are analyzed by the proposed method. The results show that the proposed method can diagnose the faults in a roller bearing and fault patterns can be identified.

A Robust Controller of a Flexible Manipulator Using Genetic Algorithm

This paper addresses the issues related to the design of robust controller using genetic algorithms (GA) for lightweight, one-link flexible manipulators working under dynamic environments and other uncertain influences. By selecting sensitivity weight functions properly using the GA method, a mixed sensitivity Hinfin controller is developed to ensure robustness of manipulator control systems for varying payloads and other modeling uncertainties. Numeric simulation has been conducted and the results have demonstrated the effectiveness of the proposed method

Experiment research on the Metal Magnetic Memory in gear micro crack detection

Based on the magnetic flux leakage detection principle of magnetic dipole, a model of magnetic flux leakage signal of gears early local micro crack is derived. The characters of the crack area that include the peak in the tangential component of magnetic flux leakage signal, pass zero point in normal component and the peak in the gradient of it are analyzed. The analysis results provide the basic theoretical foundation of the Metal Magnetic Memory application. Then based on the theory above, the detection of micro crack on the side of an actual gear is applied which includes static testing and dynamic detection with load. The detection position and load effect on detection results is analyzed. The detection results show the effectiveness of the peak in the gradient of normal component magnetic flux leakage signal normal component in the gear magnetic flux leakage signal model and the feasibility of the magnetic memory testing on gear fault.

Intelligent Control of a Flexible Manipulator Using a Robust Controller

This paper addresses the issues related to the design of robust controller using intelligent optimization algorithms for lightweight, one-link flexible manipulators working under dynamic environments and other uncertain influences. By selecting the controller coefficients properly using the intelligent genetic method, an improved robust controller design is developed to ensure robustness of manipulator control systems for varying payloads and other modeling uncertainties. Numeric simulation has been conducted and the results have demonstrated the effectiveness of the proposed method.

Comprehensive Diagnosis of Gear-Box Typical Fault in the High Speed Wire Rolling Mills

Gearbox vibration signal of high-speed wire rolling mills is complex and has much complex frequency structure and various disturb. It leads to the difficulty of diagnosis work especially some or other early impulse fault hidden in existence. The paper presents a new comprehensive analysis method which integrates the statistical analysis, the frequency analysis and the time-frequency analysis organically. First, time domain wave analysis, frequency analysis, statistical trend analysis and characteristic frequency amplitude trend analysis are used to judge the status of the machine and fault parts primarily, and then precision diagnosis of wavelet packets decomposition and reconstruction based on the multi-resolution analysis is used to make certain the fault quality and fault position quantitatively. The diagnosis analysis results of one application example indicate the validity and the practicability of the method proposed here