Wavelet Denoising Applied to Hardware Redundant Systems for Rolling Element Bearing Fault Detection  

作　　者：Dustin Helm Markus Timusk 

机构地区：[1]Bharti School of Engineering Laurentian University,Sudbury,Ontario,Canada

出　　处：《Journal of Dynamics, Monitoring and Diagnostics》2023年第2期133-143,共11页动力学、监测与诊断学报（英文）

摘　　要：This work presents a novel wavelet-based denoising technique for improving the signal-to-noise ratio(SNR)of nonsteady vibration signals in hardware redundant systems.The proposed method utilizes the relationship between redundant hardware components to effectively separate fault-related components from the vibration signature,thus enhancing fault detection accuracy.The study evaluates the proposed technique on two mechanically identical subsystems that are simultaneously controlled under the same speed and load inputs,with and without the proposed denoising step.The results demonstrate an increase in detection accuracy when incorporating the proposed denoising method into a fault detection system designed for hardware redundant machinery.This work is original in its application of a new method for improving performance when using residual analysis for fault detection in hardware redundant machinery configurations.Moreover,the proposed methodology is applicable to nonstationary equipment that experiences changes in both speed and load.

关 键 词：fault detection hardware redundancy VIBRATION wavelet denoising 

分 类 号：TH133.33[机械工程—机械制造及自动化]