机械工程学报
機械工程學報
궤계공정학보
Journal of Mechanical Engineering
2015年
19期
93-100
,共8页
滚动轴承%数学形态学%多尺度自互补Top-Hat变换%特征幅值能量比
滾動軸承%數學形態學%多呎度自互補Top-Hat變換%特徵幅值能量比
곤동축승%수학형태학%다척도자호보Top-Hat변환%특정폭치능량비
rolling bearing%mathematical morphology%multi-scale self-complementary Top-Hat transformation%feature amplitude energy radio
针对实际工程中滚动轴承冲击性故障特征难以提取的问题,提出一种自适应多尺度自互补Top-Hat(Adaptive multi-scale self-complementary Top-Hat, AMSTH)变换方法用于轴承故障的增强检测。自互补Top-Hat变换在消除信号中背景噪声的同时,能有效增强故障振动信号的冲击特性,而构造的多尺度自互补Top-Hat变换方法,可以较有效地兼顾抗噪性能和信号的细节保持。在分析形态学滤波的基础上,提出采用特征幅值能量比(Feature amplitude energy radio, FAER)的方法自适应确定最优结构元素的尺度,并应用于轴承的故障增强检测。通过对仿真信号和实测轴承滚动体、内圈故障信号进行分析,结果表明该方法可有效增强滚动轴承的故障检测,并且在运算效率和提取效果方面优于基于信噪比标准的多尺度形态学开-闭和闭-开组合变换方法。
針對實際工程中滾動軸承遲擊性故障特徵難以提取的問題,提齣一種自適應多呎度自互補Top-Hat(Adaptive multi-scale self-complementary Top-Hat, AMSTH)變換方法用于軸承故障的增彊檢測。自互補Top-Hat變換在消除信號中揹景譟聲的同時,能有效增彊故障振動信號的遲擊特性,而構造的多呎度自互補Top-Hat變換方法,可以較有效地兼顧抗譟性能和信號的細節保持。在分析形態學濾波的基礎上,提齣採用特徵幅值能量比(Feature amplitude energy radio, FAER)的方法自適應確定最優結構元素的呎度,併應用于軸承的故障增彊檢測。通過對倣真信號和實測軸承滾動體、內圈故障信號進行分析,結果錶明該方法可有效增彊滾動軸承的故障檢測,併且在運算效率和提取效果方麵優于基于信譟比標準的多呎度形態學開-閉和閉-開組閤變換方法。
침대실제공정중곤동축승충격성고장특정난이제취적문제,제출일충자괄응다척도자호보Top-Hat(Adaptive multi-scale self-complementary Top-Hat, AMSTH)변환방법용우축승고장적증강검측。자호보Top-Hat변환재소제신호중배경조성적동시,능유효증강고장진동신호적충격특성,이구조적다척도자호보Top-Hat변환방법,가이교유효지겸고항조성능화신호적세절보지。재분석형태학려파적기출상,제출채용특정폭치능량비(Feature amplitude energy radio, FAER)적방법자괄응학정최우결구원소적척도,병응용우축승적고장증강검측。통과대방진신호화실측축승곤동체、내권고장신호진행분석,결과표명해방법가유효증강곤동축승적고장검측,병차재운산효솔화제취효과방면우우기우신조비표준적다척도형태학개-폐화폐-개조합변환방법。
Aiming at the difficulty of extracting impulsive fault feature of rolling element bearings in practical engineering, a novel method named adaptive multi-scale self-complementary Top-Hat (AMSTP) transformation is proposed to enhance detection of bearing faults. It can enhance the impulsiveness of the bearing fault vibration signal and depress strong background noise, and constructing multi-scale is better to depress noise and retain detail of signal. The most optimal structure element (SE) scale is selected by using a novel method of feature amplitude energy radio (FAER), and it is applied in detecting fault feature of impulsive signal successfully. The performance of the proposed method is validated by both simulated signal and vibration signals of defective rolling element bearings with ball and inner faults. In addition the method could achieve better effect on feature extraction and have more operation efficiency than open-closing and close-opening combined morphological method based on signal noise ratio (SNR) criterion.