振动工程学报
振動工程學報
진동공정학보
JOURNAL OF VIBRATION ENGINEERING
2015年
2期
316-323
,共8页
李洪儒%王余奎%王冰%许葆华%李兴林
李洪儒%王餘奎%王冰%許葆華%李興林
리홍유%왕여규%왕빙%허보화%리흥림
故障诊断%滚动轴承%广义数学形态颗粒%灰色马尔科夫模型%剩余寿命预测
故障診斷%滾動軸承%廣義數學形態顆粒%灰色馬爾科伕模型%剩餘壽命預測
고장진단%곤동축승%엄의수학형태과립%회색마이과부모형%잉여수명예측
fault diagnosis%rolling bearing%generalized mathematical morphological particle%grey Markov model%remaining service life prediction
在滚动轴承状态监测与故障预测领域中,针对滚动轴承退化特征提取这一关键问题,提出了一种基于广义数学形态颗粒的特征提取新方法,该方法以数学形态颗粒分析为理论基础,在形态运算中引入腐蚀和膨胀算子,以计算出的广义数学形态颗粒值作为特征指标,定量地反映滚动轴承的性能退化程度。分别通过仿真信号和实例信号对该方法进行了有效性验证。在此基础上,为准确拟合滚动轴承性能退化过程的整体趋势与随机波动规律,将灰色马尔科夫模型应用到滚动轴承剩余寿命预测中,从而建立一种基于广义数学形态颗粒与灰色马尔科夫模型的剩余寿命预测方法。依托杭州轴承试验研究中心进行了滚动轴承疲劳寿命强化试验,以采集得到的轴承内圈全寿命试验数据验证了方法的有效性。
在滾動軸承狀態鑑測與故障預測領域中,針對滾動軸承退化特徵提取這一關鍵問題,提齣瞭一種基于廣義數學形態顆粒的特徵提取新方法,該方法以數學形態顆粒分析為理論基礎,在形態運算中引入腐蝕和膨脹算子,以計算齣的廣義數學形態顆粒值作為特徵指標,定量地反映滾動軸承的性能退化程度。分彆通過倣真信號和實例信號對該方法進行瞭有效性驗證。在此基礎上,為準確擬閤滾動軸承性能退化過程的整體趨勢與隨機波動規律,將灰色馬爾科伕模型應用到滾動軸承剩餘壽命預測中,從而建立一種基于廣義數學形態顆粒與灰色馬爾科伕模型的剩餘壽命預測方法。依託杭州軸承試驗研究中心進行瞭滾動軸承疲勞壽命彊化試驗,以採集得到的軸承內圈全壽命試驗數據驗證瞭方法的有效性。
재곤동축승상태감측여고장예측영역중,침대곤동축승퇴화특정제취저일관건문제,제출료일충기우엄의수학형태과립적특정제취신방법,해방법이수학형태과립분석위이론기출,재형태운산중인입부식화팽창산자,이계산출적엄의수학형태과립치작위특정지표,정량지반영곤동축승적성능퇴화정도。분별통과방진신호화실례신호대해방법진행료유효성험증。재차기출상,위준학의합곤동축승성능퇴화과정적정체추세여수궤파동규률,장회색마이과부모형응용도곤동축승잉여수명예측중,종이건립일충기우엄의수학형태과립여회색마이과부모형적잉여수명예측방법。의탁항주축승시험연구중심진행료곤동축승피로수명강화시험,이채집득도적축승내권전수명시험수거험증료방법적유효성。
In the domain of rolling bearing condition monitor and fault prognosis,to solve the key problem of rolling bearing de-generate feature extraction,a new approach based on generalized mathematical morphological particle is proposed in the paper, the new approach,which is founded on the mathematical morphological particle analysis,introduces corrosion and dilation op-erators in morphological calculation and takes the calculated generalized mathematical morphological particle as feature indica-tor,therefore,the performance degenerate degree could be reflected in quantity.The effectiveness of this approach is test and verified with simulation and actual signal.On this basis,in order to describe the whole tendency and random fluctuating feature for rolling bearings,grey Markov model is applied in the remaining service life prediction for rolling bearing,A method of re-maining service life prediction based on generalized mathematical morphological particle and grey Markov model is proposed thereby.Rolling bearing fatigued life testing was proceeded with Hangzhou Bearing Test & Research Center,the approach is proved effective with the collecting bearing inner race whole life data in fatigued life testing.