CAJ | 학술논문

经验模态分解（EMD）方法可使滚动轴承振动信号根据自身尺度自适应地分解为若干个内禀模态分量（IMF），滚动轴承发生故障会导致振动能量在各IMF分量上的分布发生变化，结合灰色关联模型建立IMF能量分布与轴承状态之间的对应关系，可实现轴承的状态识别。为改善传统灰关联分析在模式识别方面的缺陷，基于斜率相似的原理构造了能反映曲线形状信息的相似关联度模型，结合传统的接近关联度模型建立了能同时反映曲线位置与形状特性的灰色综合关联度诊断模型。算例结果表明，该方法能准确有效地实现滚动轴承的故障诊断。
경험모태분해（EMD）방법가사곤동축승진동신호근거자신척도자괄응지분해위약간개내품모태분량（IMF），곤동축승발생고장회도치진동능량재각IMF분량상적분포발생변화，결합회색관련모형건립IMF능량분포여축승상태지간적대응관계，가실현축승적상태식별。위개선전통회관련분석재모식식별방면적결함，기우사솔상사적원리구조료능반영곡선형상신식적상사관련도모형，결합전통적접근관련도모형건립료능동시반영곡선위치여형상특성적회색종합관련도진단모형。산례결과표명，해방법능준학유효지실현곤동축승적고장진단。
A rolling bearing vibration signal can be decomposed into a number of intrinsic mode functions (IMF) adaptively according to its own scale with the empirical mode decomposition (EMD)method.A rolling bearing failure will change distributions of IMF energy,and a bearing fault diagnosis can be realized by establishing the relationship between IMF energy distributions and bearing conditions based on the gray relational grade theory.Here,in order to improve the defects of the traditional gray analysis in pattern recognition,a gray similar relational grade model reflecting a curve's shape features was proposed based on the similarity of slope.Then,combined with the traditional approaching relativity model,a gray comprehensive relativity diagnosis model reflecting both a curve's position and its shape features was constructed.The simulation results showed that the new model can be used to recognize rolling bearing faults more effectively and accurately.