Research On Weak Signal Detection Based On Asymmetric,Time-delayed And Improved Tristable Stochastic Resonance System

The goal of weak signal detection technology is to study how to detect weak useful signals from a strong noise environment.This technology is applied to many fields such as image processing,radar communication,bearing fault diagnosis,and biomedicine.The traditional weak signal detection method is based on the principle of noise suppression,using different methods to reduce noise to extract useful signals.It reduces the noise and weakens the useful signal at the same time.Different from traditional detection methods,the stochastic resonance method uses the mechanism of transforming part of noise energy into signal energy to detect weak signals.This unique advantage of using noise makes it a research hotspot in the field of signal detection.Firstly,the theory of stochastic resonance is described in detail.Then,three different types of tristable stochastic resonance systems,namely asymmetric,time-delayed and improved,are studied.The research contents and methods of this thesis are as follows:(1)The resonance characteristics of asymmetric tristable stochastic resonance(ATSR)system driven by ?-stable distributed noise are studied.Firstly,the characteristics and generation method of ?-stable distributed noise are introduced.Secondly,the ATSR system is used to detect weak signals in an ?-stable distributed noise environment,and the ability of the system to detect weak signals is verified.Finally,the average signal-to-noise ratio improvement(A-SNRI)as the performance index,influence laws of different parameters on the stochastic resonance output of the system are discussed in detail.These conclusions provide a theoretical basis for the reasonable selection of parameters in the ATSR system.(2)A time polo-delayed tristable stochastic resonance(TPTSR)system with the high-order term is constructed,and the stochastic resonance phenomenon of this system driven by Gaussian white noise is studied.Firstly,the effective potential function and steady-state probability density(SPD)of high-order term TPTSR system are derived by small delay approximation method,and the effects of various parameters on them are analyzed.Secondly,the output signal-to-noise ratio expression of high-order term TPTSR system is derived by adiabatic approximation theory,and the stochastic resonance characteristics of the system are studied theoretically.Finally,the high-order term TPTSR system is applied to weak signal detection and bearing fault diagnosis,and compared with the high-order time-delayed feedback tristable stochastic resonance(HTFTSR)system.The simulation results verify the effectiveness and superiority of the high-order term TPTSR system.(3)An improved tristable stochastic resonance(ITSR)system is proposed,and a linear coupled multistable stochastic resonance(LCMSR)system is constructed by linear coupling.The stochastic resonance characteristics of the LCMSR system driven by trichotomous noise are studied.The parameters of each system are optimized by a genetic algorithm,and the classical tristable stochastic resonance(CTSR)system,ITSR system,and LCMSR system are applied to bearing fault diagnosis.The simulation results show that the performance of the LCMSR system is the best,and the detection effect of the ITSR system is better than that of the CTSR system.That is,the detection effect of the ITSR system is enhanced by linear coupling.