Stochastic Resonance Theory Based On Asymmetric Potential Function Systems And Its Application In Weak Signal Detection

Weak signal detection technology is important for eliminating rotating machinery accidents and promoting safety and stability in rotating machinery manufacturing.Stochastic resonance has become a hot research topic in weak signal detection in recent years.In the field of stochastic resonance research,the stochastic resonance of symmetric systems is usually studied,however the stochastic resonance of asymmetric systems is relatively rare researched.In this thesis,we investigate the effect of asymmetric stochastic resonance systems to detect weak signals based on the knowledge of stochastic resonance and intelligent algorithms.The specific work is as follows:1.Stochastic resonance of asymmetric joint potential function systems and its application in weak signal detection are studied.Firstly,we combine Gaussian potential function with asymmetric bistable state function to form a new asymmetric potential function system.Secondly,based on the two-state theory and the adiabatic approximation theory,the signalto-noise ratio of the system is derived,and we discusse the influence of system parameters on the signal-to-noise ratio.Then,the simulation experiment verifies that stochastic resonance of the system can accurately detect various types of weak signals with noise,such as periodic signals,digital signals,etc.Finally,the proposed stochastic resonance system based on particle swarm optimization algorithm is applied to detect the actual bearing fault signals,and compares with the classical stochastic resonance system.Simulation results show that the proposed system can detect weak signal characteristics more effectively.2.Stochastic resonance of nonlinear coupled asymmetric systems based on adaptive weighted particle swarm optimization algorithm and its application in weak signal detection are studied.Firstly,we establish the nonlinear coupling asymmetric system by coupling the asymmetric bistable system with the monostable system.Secondly,the probability density function,the mean first passage time and signal-to-noise ratio of the system are derived based on the adiabatic approximation theory,and we analyze the influence of system parameters on them.Thirdly,simulation experiments show that the proposed system stochastic resonance can detect weak signals with Lévy noise.Finally,the nonlinear coupling asymmetric stochastic resonance system optimized by adaptive weighted particle swarm optimization algorithm is applied to detect the bearing fault signal,and the results are compared with the optimized classical stochastic resonance system,which proves that stochastic resonance of the nonlinear coupling asymmetric system is beneficial to detect bearing fault signals.