[摘要]:由于在機(jī)械系統(tǒng)中,滾動(dòng)軸承是一種故障多發(fā)的機(jī)械零部件,設(shè)計(jì)出能夠有效檢測滾動(dòng)軸承故障的診斷系統(tǒng)具有很重要的意義。本文在基于滾動(dòng)軸承常見故障下建立故障頻率分布模型,并針對干擾故障模型的噪聲信號設(shè)計(jì)了FIR高通數(shù)字濾波器來提取出有效故障頻率段。結(jié)合工程實(shí)例設(shè)計(jì)了對工程用發(fā)電機(jī)轉(zhuǎn)子軸承的故障診斷系統(tǒng),并且通過實(shí)驗(yàn)測試發(fā)現(xiàn)有很好的效果。
[關(guān)鍵詞]:滾動(dòng)軸承、故障診斷、頻譜分析、FIR濾波器
Roller bearing fault diagnosis system based on fuzzy neural network
[Abstract]: In the mechanical system, roller bearing is a failure-prone mechanical part. It is very important significance that the system detect rolling bearing fault diagnosis effectively can be designed. This paper is established the fault frequency distribution model based on the roller bearing’s common failure and designed a FIR high-pass digital filter that extract the effective failure frequency from the interference noise signal of the fault model. Fault diagnosis system has been designed for engineering generator rotor bearing with an engineering example, it was tested on experiment and was found to have a very good result .
[Key words]: rolling bearing; fault diagnosis; frequency spectrum analysis; FIR digital filter
0 引言
隨著機(jī)械工業(yè)的大力發(fā)展,滾動(dòng)軸承是應(yīng)用十分廣泛的重要機(jī)械基礎(chǔ)零件。滾動(dòng)軸承具有效率高,摩擦阻力小,裝配方便,潤滑容易等特點(diǎn),因而在旋轉(zhuǎn)機(jī)械中得到廣泛的應(yīng)用。滾動(dòng)軸承是大部分旋轉(zhuǎn)機(jī)械的組成部件,但滾動(dòng)軸承卻是易損元件,許多旋轉(zhuǎn)機(jī)械的故障都與滾動(dòng)軸承有關(guān)[1]。據(jù)有關(guān)資料統(tǒng)計(jì),機(jī)械故障的70%是振動(dòng)故障,而振動(dòng)故障中有30%是由滾動(dòng)軸承引起的[2]。
在滾動(dòng)軸承出現(xiàn)故障時(shí),直接檢測故障信號是十分困難的。一般的檢測方法是利用軸承故障產(chǎn)生的二次效應(yīng)的變化來作為故障診斷的依據(jù),比如振動(dòng)、噪聲、熱量等[3]。而根據(jù)二次效應(yīng)的不同特征,其診斷的方法各有不同。在眾多的軸承故障診斷方法中,振動(dòng)檢測方法是應(yīng)用最廣泛的一種方法,這主要是因?yàn)檎駝?dòng)信號提供的故障信息多,對早期故障軸承都具有較強(qiáng)的檢測能力。
振動(dòng)法是通過安裝在軸承座或箱體上適當(dāng)位置的振動(dòng)傳感器測量軸承振動(dòng)信號,并對該信號進(jìn)行處理和分析來判斷軸承的工況和故障。……