title: The recovery of weak impulsive signals based on stochastic resonance and moving least squares fitting.
abstract: In this paper a stochastic resonance (SR)-based method for recovering weak impulsive signals is developed for quantitative diagnosis of faults in rotating machinery. It was shown in theory that weak impulsive signals follow the mechanism of SR, but the SR produces a nonlinear distortion of the shape of the impulsive signal. To eliminate the distortion a moving least squares fitting method is introduced to reconstruct the signal from the output of the SR process. This proposed method is verified by comparing its detection results with that of a morphological filter based on both simulated and experimental signals. The experimental results show that the background noise is suppressed effectively and the key features of impulsive signals are reconstructed with a good degree of accuracy, which leads to an accurate diagnosis of faults in roller bearings in a run-to failure test.
authors: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. jiangkuosheng333@stu.xjtu.edu.cn.
authors: Kuosheng
authors: K
authors: Jiang
authors: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. ghxu@mail.xjtu.edu.cn.
authors: Guanghua
authors: G
authors: Xu
authors: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. lianglin@mail.xjtu.edu.cn.
authors: Lin
authors: L
authors: Liang
authors: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China. taotangfei@mail.xjtu.edu.cn.
authors: Tangfei
authors: T
authors: Tao
authors: School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK. F.Gu@hud.ac.uk.
authors: Fengshou
authors: F
authors: Gu
mesh_terms: D016018:Least-Squares Analysis; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013269:Stochastic Processes