Early bearing faults can generate a series of weak impacts. All the influence factors in measurement may degrade the vibration signal. Currently, bearing fault enhanced detection method based on stochastic resonance...Early bearing faults can generate a series of weak impacts. All the influence factors in measurement may degrade the vibration signal. Currently, bearing fault enhanced detection method based on stochastic resonance（SR） is implemented by expensive computation and demands high sampling rate, which requires high quality software and hardware for fault diagnosis. In order to extract bearing characteristic frequencies component, SR normalized scale transform procedures are presented and a circuit module is designed based on parameter-tuning bistable SR. In the simulation test, discrete and analog sinusoidal signals under heavy noise are enhanced by SR normalized scale transform and circuit module respectively. Two bearing fault enhanced detection strategies are proposed. One is realized by pure computation with normalized scale transform for sampled vibration signal, and the other is carried out by designed SR hardware with circuit module for analog vibration signal directly. The first strategy is flexible for discrete signal processing, and the second strategy demands much lower sampling frequency and less computational cost. The application results of the two strategies on bearing inner race fault detection of a test rig show that the local signal to noise ratio of the characteristic components obtained by the proposed methods are enhanced by about 50% compared with the band pass envelope analysis for the bearing with weaker fault. In addition, helicopter transmission bearing fault detection validates the effectiveness of the enhanced detection strategy with hardware. The combination of SR normalized scale transform and circuit module can meet the need of different application fields or conditions, thus providing a practical scheme for enhanced detection of bearing fault.展开更多
Aiming at the detection failure of strong noise interference in the dual channel of the dual-sequence frequency hopping(DSFH),the scale transformation stochastic resonance(STSR)is applied for the first time,and the ou...Aiming at the detection failure of strong noise interference in the dual channel of the dual-sequence frequency hopping(DSFH),the scale transformation stochastic resonance(STSR)is applied for the first time,and the output signal to noise ratio(SNR)is raised effectively,at the same time,the symbol reception is completed for DSFH at low input SNR.Firstly,the radio frequency(RF)and intermediate frequency(IF)signals are analyzed based on the super-heterodyne reception of DSFH;secondly,the equations of probability density function(PDF),output power spectrum and SNR of the STSR output are derived for the IF signal;finally,the algorithm of the optimal matching STSR is proposed with the optimal matching parameters.The simulation results show that the algorithm can effectively solve the detection failure,as the global output SNR of DSFH is strongly improved that the output SNR can reach-17.72 d B when the input SNR is-20 d B after the processing of the optimal matching STSR.展开更多
基金supported by National Natural Science Foundation of China(Grant Nos. 51075391, 51105366)
文摘Early bearing faults can generate a series of weak impacts. All the influence factors in measurement may degrade the vibration signal. Currently, bearing fault enhanced detection method based on stochastic resonance（SR） is implemented by expensive computation and demands high sampling rate, which requires high quality software and hardware for fault diagnosis. In order to extract bearing characteristic frequencies component, SR normalized scale transform procedures are presented and a circuit module is designed based on parameter-tuning bistable SR. In the simulation test, discrete and analog sinusoidal signals under heavy noise are enhanced by SR normalized scale transform and circuit module respectively. Two bearing fault enhanced detection strategies are proposed. One is realized by pure computation with normalized scale transform for sampled vibration signal, and the other is carried out by designed SR hardware with circuit module for analog vibration signal directly. The first strategy is flexible for discrete signal processing, and the second strategy demands much lower sampling frequency and less computational cost. The application results of the two strategies on bearing inner race fault detection of a test rig show that the local signal to noise ratio of the characteristic components obtained by the proposed methods are enhanced by about 50% compared with the band pass envelope analysis for the bearing with weaker fault. In addition, helicopter transmission bearing fault detection validates the effectiveness of the enhanced detection strategy with hardware. The combination of SR normalized scale transform and circuit module can meet the need of different application fields or conditions, thus providing a practical scheme for enhanced detection of bearing fault.
基金the Natural Science of Foundation of Hebei Province(No.F2017506006)
文摘Aiming at the detection failure of strong noise interference in the dual channel of the dual-sequence frequency hopping(DSFH),the scale transformation stochastic resonance(STSR)is applied for the first time,and the output signal to noise ratio(SNR)is raised effectively,at the same time,the symbol reception is completed for DSFH at low input SNR.Firstly,the radio frequency(RF)and intermediate frequency(IF)signals are analyzed based on the super-heterodyne reception of DSFH;secondly,the equations of probability density function(PDF),output power spectrum and SNR of the STSR output are derived for the IF signal;finally,the algorithm of the optimal matching STSR is proposed with the optimal matching parameters.The simulation results show that the algorithm can effectively solve the detection failure,as the global output SNR of DSFH is strongly improved that the output SNR can reach-17.72 d B when the input SNR is-20 d B after the processing of the optimal matching STSR.
