本文選題：聲發(fā)射 + 疲勞裂紋　； 參考：《昆明理工大學(xué)》2014年碩士論文

【摘要】：滾動(dòng)軸承旋轉(zhuǎn)機(jī)械中最易損壞的部件之一,其運(yùn)行狀態(tài)嚴(yán)重影響整個(gè)設(shè)備的運(yùn)行。因此,滾動(dòng)軸承的狀態(tài)監(jiān)測(cè)與故障診斷對(duì)于工程人員有重要意義�，F(xiàn)有檢測(cè)手段,如振動(dòng)信號(hào)分析、油液分析、溫度診斷分析等并不能有效地診斷出關(guān)鍵部位軸承的早期故障。 起重機(jī)是廣泛應(yīng)用的八大特種設(shè)備之一。由于數(shù)量巨大,結(jié)構(gòu)復(fù)雜,非正常的使用使得安全事故日益頻發(fā)。起重機(jī)的常規(guī)無(wú)損檢測(cè)方法既耗時(shí)費(fèi)力,又需要起重機(jī)停止作業(yè),最重要的是無(wú)法及時(shí)發(fā)現(xiàn)關(guān)鍵部位的微弱結(jié)構(gòu)缺陷,導(dǎo)致即便起重機(jī)檢測(cè)合格仍然有較大的安全隱患。故亟需解決起重機(jī)安全檢測(cè)的有效性,并對(duì)起重機(jī)中的結(jié)構(gòu)缺陷源進(jìn)行粗略定位,再結(jié)合其他無(wú)損檢測(cè)手段對(duì)可能的缺陷位置進(jìn)行仔細(xì)檢測(cè)。另外,聲發(fā)射對(duì)于活性缺陷極其敏感,可以對(duì)運(yùn)行中的起重機(jī)進(jìn)行整體性檢測(cè)。 本文以聲發(fā)射檢測(cè)技術(shù)為手段,對(duì)健康滾動(dòng)軸承和起重機(jī)主梁進(jìn)行了理論和試驗(yàn)研究,著重對(duì)滾動(dòng)軸承和起重機(jī)主梁早期疲勞缺陷和聲發(fā)射檢測(cè)的有效性進(jìn)行了詳細(xì)研究。研究工作主要包括以下四個(gè)方面： 1)滾動(dòng)軸承聲發(fā)射信號(hào)的特征參數(shù)及信息熵分析。采用了峭度、有效值、峰值和信息熵等對(duì)運(yùn)行中健康滾動(dòng)軸承聲發(fā)射信號(hào)的特征進(jìn)行了分析,并與振動(dòng)信號(hào)進(jìn)行了對(duì)比分析,得出了聲發(fā)射信號(hào)的參數(shù)及信息熵趨勢(shì)能更好地反應(yīng)當(dāng)前軸承疲勞磨損狀況。 2)通過(guò)軸承聲發(fā)射包絡(luò)頻譜與振動(dòng)頻譜對(duì)比分析,證明聲發(fā)射信號(hào)中故障特征頻率比振動(dòng)信號(hào)更為突出,也說(shuō)明聲發(fā)射信號(hào)比振動(dòng)信號(hào)具有更高的信噪比,能更有效地進(jìn)行狀態(tài)監(jiān)測(cè)和故障診斷。 3)通過(guò)后期對(duì)實(shí)驗(yàn)采集的起重機(jī)主梁聲發(fā)射數(shù)據(jù)波形進(jìn)行仔細(xì)分析,結(jié)合聲發(fā)射波形的定義及一些相關(guān)的特征參數(shù),從而設(shè)定一定的閾值條件,篩選出了可能的裂紋產(chǎn)生及擴(kuò)展時(shí)的聲發(fā)射特征信號(hào)。 4)通過(guò)對(duì)對(duì)這些篩選后的聲發(fā)射信號(hào)進(jìn)行峭度、有效值、峰值、波峰系數(shù)、能量等特征參數(shù)分析,結(jié)果表明：聲發(fā)射檢測(cè)手段可以準(zhǔn)確地監(jiān)測(cè)起重機(jī)主梁這類大型構(gòu)件中的疲勞裂紋形成及擴(kuò)展的整個(gè)過(guò)程。這里還嘗試了缺陷聲發(fā)射源的定位,但是定位精度不是很高。
[Abstract]:One of the most easily damaged parts in rolling bearing rotating machinery, its running state seriously affects the operation of the whole equipment. Therefore, the condition monitoring and fault diagnosis of rolling bearings is of great significance to engineers. The existing detection methods, such as vibration signal analysis, oil analysis, temperature diagnosis and so on, can not effectively diagnose the early failure of bearings in key parts. Crane is one of the eight widely used special equipment. Due to the large number, complex structure and abnormal use, safety accidents are more and more frequent. The conventional nondestructive testing method of crane is time-consuming and laborious, and it also needs the crane to stop its operation. The most important thing is that the weak structural defects of the key parts can not be found in time, which leads to a great potential safety hazard even if the crane is qualified for inspection. Therefore, it is urgent to solve the effectiveness of crane safety inspection, and to roughly locate the structural defect source in the crane, and then combine other non-destructive testing means to carefully detect the possible defect position. In addition, acoustic emission (AE) is very sensitive to active defects and can be used to detect the whole of crane in operation. In this paper, the healthy rolling bearings and crane main beams are studied theoretically and experimentally by means of acoustic emission detection technology. The effectiveness of early fatigue defects and acoustic emission detection of rolling bearings and crane main beams is studied in detail. The research work mainly includes the following four aspects: 1) characteristic parameters and information entropy analysis of acoustic emission signal of rolling bearing. Using kurtosis, effective value, peak value and information entropy, the characteristics of acoustic emission signals of healthy rolling bearings in operation are analyzed and compared with vibration signals. It is concluded that the parameters and information entropy trend of acoustic emission signals can better reflect the current fatigue wear of bearings. 2) by comparing and analyzing the spectrum of acoustic emission envelope and vibration spectrum of bearings, It is proved that the fault characteristic frequency is more prominent than the vibration signal in the acoustic emission signal, and it also shows that the acoustic emission signal has a higher signal-to-noise ratio than the vibration signal. It can more effectively carry out the condition monitoring and fault diagnosis. 3) through the careful analysis of the acoustic emission data waveform of the crane main beam collected in the later stage, combining the definition of the acoustic emission waveform and some relevant characteristic parameters, By setting certain threshold conditions, the acoustic emission characteristic signals of possible crack generation and propagation are screened. 4) by means of kurtosis, effective value, peak value and peak coefficient of these filtered acoustic emission signals, The analysis of energy and other characteristic parameters shows that the acoustic emission detection method can accurately monitor the whole process of fatigue crack formation and propagation in large components such as crane girder. The localization of defective acoustic emission sources is also tried, but the positioning accuracy is not very high.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TH133.33;TH165.3

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