Detection of Weak Signal Via Bistable Stochastic Resonance Combining with Genetic Algorithm
In order to detect a weak periodic signal under the condition of intensive noise, the weak signal including strong background noise and adscititious additive noise were used as input of a bistable stochastic resonance (SR) system. The adscititious noise intensity and the system parameter were adjusted adaptively with genetic algorithm by examining the SR effect on output signal-to-noise ratio (SNR). An improved numerical solution for a bistable SR model based on a fourth order Runge-Kutta algorithm was presented to enhance the SR effect. The simulation results show that the weak signal in an intensive noisy background could be successfully extracted. What is more, the output SNR was increased more than 30 dB comparing with the input SNR. It can be seen that the proposed method was superior to the traditional spectra analysis and envelope demodulation methods in detecting the weak periodic signal. Such detection approach indicates a promising prospect for mechanical fault monitoring and diagnosis.
Zhefei Hou Jie Yang Yunpeng Wang
Air Force Dalian Communication Sergeant School, Dalian, China School of Information Engineering, Wuhan University of Technology, Wuhan 430063, China
国际会议
武汉
英文
37-41
2008-12-19（万方平台首次上网日期，不代表论文的发表时间）