本文選題：機(jī)械學(xué) + 軸承多重故障診斷　； 參考：《兵工學(xué)報(bào)》2017年08期

【摘要】：由于復(fù)雜裝備運(yùn)行工作環(huán)境惡劣,導(dǎo)致其軸承多重故障診斷的準(zhǔn)確率不高,為此提出一種基于線性判別分析(LDA)與反向傳播(BP)神經(jīng)網(wǎng)絡(luò)協(xié)作下復(fù)雜裝備軸承數(shù)據(jù)驅(qū)動(dòng)的多重故障診斷方法。將無(wú)量綱指標(biāo)作為軸承多重故障數(shù)據(jù)的反映指標(biāo),利用LDA對(duì)軸承多重故障的無(wú)量綱指標(biāo)數(shù)據(jù)進(jìn)行線性映射降維處理;通過(guò)拉格朗日極值法獲得最佳投影向量,沿著該方向?qū)⑤S承多重故障數(shù)據(jù)投影到類別最易區(qū)分的方向;將經(jīng)投影處理后的樣本作為BP神經(jīng)網(wǎng)絡(luò)的輸入樣本,通過(guò)訓(xùn)練測(cè)試網(wǎng)絡(luò),實(shí)現(xiàn)軸承多重故障的預(yù)測(cè)分類。對(duì)某型裝備大型旋轉(zhuǎn)機(jī)械機(jī)組進(jìn)行仿真實(shí)驗(yàn),驗(yàn)證了所提方法能夠有效對(duì)軸承多重故障進(jìn)行降維映射,并且能較好地實(shí)現(xiàn)多重故障分類診斷,具有良好的有效性和實(shí)用性。
[Abstract]:Because of the bad working environment of complex equipment, the accuracy of bearing multi-fault diagnosis is not high. In this paper, a multiple fault diagnosis method based on LDA and BP neural network for complex equipment bearing data drive is proposed. The dimensionless index is used as the reflection index of bearing multi-fault data, the dimensionless index data of bearing multi-fault is reduced by using LDA, and the optimal projection vector is obtained by Lagrange extreme value method. Along this direction, the bearing multi-fault data are projected to the most easily distinguished direction, and the samples processed by projection are used as input samples of BP neural network, and the prediction and classification of bearing multiple faults are realized by training and testing network. The simulation experiments on a large rotating machine unit of a certain type of equipment show that the proposed method can effectively reduce the dimension of multiple faults of bearings, and can better realize the classification and diagnosis of multiple faults, which has good effectiveness and practicability.
【作者單位】： 重慶交通大學(xué)信息科學(xué)與工程學(xué)院;廣東石油化工學(xué)院廣東省石化裝備故障診斷重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(61663008、61573076、61473094、61304104、61004118) 教育部留學(xué)歸國(guó)人員科研啟動(dòng)基金項(xiàng)目(2015-49) 重慶市高等學(xué)校優(yōu)秀人才支持計(jì)劃項(xiàng)目(2014-18) 廣東省石化裝備故障診斷重點(diǎn)實(shí)驗(yàn)室開(kāi)放式基金項(xiàng)目(GDUPKLAB201501、GDUPKLAB201604) 重慶市研究生教育教學(xué)改革研究重點(diǎn)項(xiàng)目(yjg152011) 重慶市高等教育學(xué)會(huì)2015—2016高等教育科學(xué)研究課題項(xiàng)目(CQGJ15010C)
【分類號(hào)】：TH133.3

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