CAJ | 학술논문

采用改进的小波分解和重构算法与包络分析相结合的方法，提取滚动轴承振动信号的故障特征频率。改进的小波分解和重构方法避免了 Mallat 算法频率混淆的缺陷，通过对重构信号特定频带进行包络分析，更加准确地提取了滚动轴承的故障特征频率。通过对无故障滚动轴承和内圈、外圈有故障的滚动轴承振动信号的分析，说明这种方法能够有效诊断滚动轴承的故障，并将该方法成功应用于某型航空发动机主轴承故障诊断。
채용개진적소파분해화중구산법여포락분석상결합적방법，제취곤동축승진동신호적고장특정빈솔。개진적소파분해화중구방법피면료 Mallat 산법빈솔혼효적결함，통과대중구신호특정빈대진행포락분석，경가준학지제취료곤동축승적고장특정빈솔。통과대무고장곤동축승화내권、외권유고장적곤동축승진동신호적분석，설명저충방법능구유효진단곤동축승적고장，병장해방법성공응용우모형항공발동궤주축승고장진단。
Fault characteristic frequency components of rolling bearing vibration signals were extracted by the method of combining an improved wavelet decomposition and reconstruction algorithm and envelope a-nalysis. The improved wavelet decomposition and reconstruction approach avoids the defects of Mallat algo-rithm′s confusion in frequencies. Extracting the rolling bearing fault characteristic frequencies are more accu-rate. Analysis of normal rolling bearing and inner ring and the outer ring failure rolling bearing vibration sig-nals indicate that the method can effectively diagnose the fault of rolling bearings. Furthermore,using this method succeeded in diagnosing the faults of aero-engine main bearings.