本文選題：故障診斷 + 滾動(dòng)軸承　； 參考：《振動(dòng)工程學(xué)報(bào)》2017年05期

【摘要】：變轉(zhuǎn)速工況下的滾動(dòng)軸承微弱故障診斷同時(shí)面臨兩個(gè)難點(diǎn):一是滾動(dòng)軸承的故障特征信號(hào)容易被環(huán)境噪聲和干擾信號(hào)淹沒;二是滾動(dòng)軸承故障振動(dòng)信號(hào)的時(shí)變特征難以被常規(guī)頻譜方法提取。針對(duì)上述問題提出了基于時(shí)時(shí)能量階比譜的滾動(dòng)軸承故障診斷方法。首先對(duì)變轉(zhuǎn)速工況下的滾動(dòng)軸承微弱故障振動(dòng)信號(hào)進(jìn)行時(shí)時(shí)(time-time,TT)變換,在雙時(shí)域上刻畫軸承故障振動(dòng)信號(hào)的時(shí)變特征;然后利用提出的時(shí)時(shí)能量定義計(jì)算軸承故障振動(dòng)信號(hào)的時(shí)時(shí)能量,獲得軸承故障振動(dòng)信號(hào)的時(shí)時(shí)能量信號(hào);最后對(duì)時(shí)時(shí)能量信號(hào)進(jìn)行階比分析得到軸承故障振動(dòng)信號(hào)的時(shí)時(shí)能量階比譜,并根據(jù)時(shí)時(shí)能量階比譜的階次特征識(shí)別出軸承故障類型。分析了變轉(zhuǎn)速工況下的滾動(dòng)軸承故障仿真信號(hào)和實(shí)驗(yàn)測(cè)試信號(hào),結(jié)果表明:時(shí)時(shí)能量信號(hào)能夠有效追蹤軸承故障振動(dòng)信號(hào)的時(shí)變能量分布,增強(qiáng)故障特征信號(hào)的沖擊特征,時(shí)時(shí)能量階比譜較包絡(luò)階比譜抗噪能力更強(qiáng),為變轉(zhuǎn)速工況滾動(dòng)軸承微弱故障診斷提供一種有效方法。
[Abstract]:At the same time, the weak fault diagnosis of rolling bearing under variable speed is faced with two difficulties: first, the fault characteristic signal of rolling bearing is easily submerged by environmental noise and interference signal; Second, the time-varying characteristics of rolling bearing fault vibration signal are difficult to be extracted by conventional spectrum method. To solve the above problems, a fault diagnosis method for rolling bearings based on energy order spectrum is proposed. Firstly, time-time TTT transform is used to describe the time-varying characteristics of the fault vibration signals of rolling bearings in the dual time domain. Then the time energy of bearing fault vibration signal is calculated by the definition of time energy, and the time energy signal of bearing fault vibration signal is obtained. At last, the frequency spectrum of bearing fault vibration signal is obtained by order analysis of the time energy signal, and the bearing fault type is identified according to the order characteristic of the time energy order spectrum. The fault simulation signal and experimental test signal of rolling bearing under variable rotational speed are analyzed. The results show that the time-varying energy distribution of bearing fault vibration signal can be effectively tracked and the impact characteristic of fault characteristic signal can be enhanced by the time-varying energy signal. The energy order spectrum is more robust to noise than the envelope order spectrum, which provides an effective method for the weak fault diagnosis of rolling bearings under variable speed conditions.
【作者單位】： 華北電力大學(xué)能源動(dòng)力與機(jī)械工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(51307058) 河北省自然科學(xué)基金資助項(xiàng)目(E2014502052) 中央高�；究蒲袠I(yè)務(wù)專項(xiàng)資金資助項(xiàng)目(2014MS156,2017XS134)
【分類號(hào)】：TH133.33

【相似文獻(xiàn)】

相關(guān)博士學(xué)位論文 前3條

1 李永波;滾動(dòng)軸承故障特征提取與早期診斷方法研究[D];哈爾濱工業(yè)大學(xué);2017年

2 王曉龍;基于振動(dòng)信號(hào)處理的滾動(dòng)軸承故障診斷方法研究[D];華北電力大學(xué)(北京);2017年

3 劉尚坤;基于振動(dòng)信號(hào)處理的旋轉(zhuǎn)機(jī)械故障診斷方法研究[D];華北電力大學(xué)(北京);2017年

相關(guān)碩士學(xué)位論文 前2條

1 馬艷麗;基于全矢MEMD的滾動(dòng)軸承狀態(tài)退化研究[D];鄭州大學(xué);2017年

2 金兵;基于信息融合與VPMCD的滾動(dòng)軸承智能診斷研究[D];鄭州大學(xué);2017年

，

本文編號(hào)：1912563