In field of rolling bearing fault diagnosis, the sampled bearing vibration signals will be generally disturbed with noise. In noisy environment, the conventional blind source separation method is not good for diagnosi...In field of rolling bearing fault diagnosis, the sampled bearing vibration signals will be generally disturbed with noise. In noisy environment, the conventional blind source separation method is not good for diagnosing bearing faults. In this paper, wavelet de-noising method and blind source separation technology have been combined. In order to achieve fault diagnosis of rolling bearing, firstly wavelet soft threshold de-noising method has been applied on sampled signals. Then the better robust JADE algorithm has been applied in signals blind source separation. At last, vibration signals bearing inner and outer faults of have been analyzed in this paper, and the corresponding bearing faults have been diagnosed successfully. The proposed research methods provide a new way for diagnosing rolling bearing＇s mixed faults under noise展开更多
The problem of the robust fault detection filter design for time-varying delays switched systems is considered in the framework of mixed H-/H∞. Firstly, the weighted H∞ performance index is utilized as the robustnes...The problem of the robust fault detection filter design for time-varying delays switched systems is considered in the framework of mixed H-/H∞. Firstly, the weighted H∞ performance index is utilized as the robustness performance, and the H- index is used as the sensitivity performance for obtaining the robust fault detection filter. Then a novel multiple Lyapunov-Krasovskii function is proposed for deriving sufficient existence conditions of the robust fault detection filter based on the average dwell time technique. By introducing slack matrix variable, the coupling between the Lyapunov matrix and system matrix is removed, and the conservatism of results is reduced. Based on the robust fault detection filter, residual is generated and evaluated for detecting faults. In addition, the results of this paper are dependent on time delays,and represented in the form of linear matrix inequalities. Finally,the simulation example verifies the effectiveness of the proposed method.展开更多
文摘In field of rolling bearing fault diagnosis, the sampled bearing vibration signals will be generally disturbed with noise. In noisy environment, the conventional blind source separation method is not good for diagnosing bearing faults. In this paper, wavelet de-noising method and blind source separation technology have been combined. In order to achieve fault diagnosis of rolling bearing, firstly wavelet soft threshold de-noising method has been applied on sampled signals. Then the better robust JADE algorithm has been applied in signals blind source separation. At last, vibration signals bearing inner and outer faults of have been analyzed in this paper, and the corresponding bearing faults have been diagnosed successfully. The proposed research methods provide a new way for diagnosing rolling bearing＇s mixed faults under noise
基金supported by the National Natural Science Foundation of China(6127316261403104)
文摘The problem of the robust fault detection filter design for time-varying delays switched systems is considered in the framework of mixed H-/H∞. Firstly, the weighted H∞ performance index is utilized as the robustness performance, and the H- index is used as the sensitivity performance for obtaining the robust fault detection filter. Then a novel multiple Lyapunov-Krasovskii function is proposed for deriving sufficient existence conditions of the robust fault detection filter based on the average dwell time technique. By introducing slack matrix variable, the coupling between the Lyapunov matrix and system matrix is removed, and the conservatism of results is reduced. Based on the robust fault detection filter, residual is generated and evaluated for detecting faults. In addition, the results of this paper are dependent on time delays,and represented in the form of linear matrix inequalities. Finally,the simulation example verifies the effectiveness of the proposed method.
