机械制造与自动化2024，Vol.53Issue(2)：67-70,4.DOI:10.19344/j.cnki.issn1671-5276.2024.02.013
基于开关卡尔曼滤波的叶轮故障振动信号特征提取
Feature Extraction of Impeller Fault Vibration Signal Based on Switched Kalman Filter
摘要
Abstract
In order to improve the effective information extraction ability of fault signal time-domain waveform under filter,a switched Kalman filter algorithm was designed and applied to the feature extraction field of impeller fault vibration signal.The most likely state of monitoring data at all time points was predicted,the noise was removed and each impact component was effectively distinguished,and the signal to noise ratio was further strengthened.The simulation signal results show that the signal to noise ratio after filtering should be close to the noise ratio after adding noise,and the pulse discrimination effect is remarkable.The experimental verification results indicate that there is a significant noise in the measured signal,and the components of the signal judged at every moment are consistent with the reality.This research can be extended to other fields of mechanical transmission and has good market application value.关键词
叶轮/开关卡尔曼滤波/特征提取/噪声信号Key words
rolling bearing/switched Kalman filter/feature extraction/noise sign分类
机械制造引用本文复制引用
袁艳,李峰,王东..基于开关卡尔曼滤波的叶轮故障振动信号特征提取[J].机械制造与自动化,2024,53(2):67-70,4.基金项目
西安交通工程学院中青年基金项目(2022KY-09) （2022KY-09）
