發(fā)布時(shí)間：2018-01-03 05:38

  本文關(guān)鍵詞：散熱風(fēng)扇軸承故障診斷與狀態(tài)評(píng)估　出處：《電子科技大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 散熱風(fēng)扇 故障診斷與狀態(tài)評(píng)估 狀況監(jiān)測 小波分析 MED濾波 EMD分解 SVM

【摘要】：隨著信息技術(shù)和微電子技術(shù)的迅猛發(fā)展，電子器件的熱流密度不斷增加，功耗不斷增大，電子設(shè)備也向著更輕、更薄的方向發(fā)展，使得電子設(shè)備的散熱問題變得越來越突出。散熱風(fēng)扇作為電子設(shè)備散熱系統(tǒng)的關(guān)鍵部件，在保證系統(tǒng)平穩(wěn)可靠運(yùn)行上起著至關(guān)重要的作用。根據(jù)統(tǒng)計(jì)，散熱風(fēng)扇的大部分機(jī)械失效主要集中在軸承故障上。因此，對(duì)散熱風(fēng)扇軸承開展故障診斷和狀態(tài)評(píng)估能夠有效保證電子設(shè)備運(yùn)行的可靠性和延長電子設(shè)備的使用壽命。 本文針對(duì)散熱風(fēng)扇軸承的振動(dòng)機(jī)理和運(yùn)行方式，對(duì)其開展了一系列故障診斷和狀態(tài)評(píng)估的相關(guān)研究，主要內(nèi)容包括：分析了散熱風(fēng)扇的結(jié)構(gòu)特征，回顧了滾動(dòng)軸承的振動(dòng)機(jī)理和信號(hào)特征；利用EMD分解、小波分析、AR自回歸線性預(yù)測和MED濾波等信號(hào)處理技術(shù)對(duì)散熱風(fēng)扇軸承的振動(dòng)信號(hào)進(jìn)行分析，實(shí)現(xiàn)了散熱風(fēng)扇軸承的故障診斷；同時(shí)，構(gòu)造了一個(gè)特殊的梳齒形濾波器，從信號(hào)的頻域建立了一種健康指數(shù)，對(duì)軸承的健康狀態(tài)進(jìn)行監(jiān)測；此外，本文還利用SVM技術(shù)對(duì)散熱風(fēng)扇軸承的運(yùn)行狀態(tài)進(jìn)行了分類和識(shí)別，，并且基于分類結(jié)果構(gòu)造了散熱風(fēng)扇軸承的退化指數(shù)，實(shí)現(xiàn)了散熱風(fēng)扇軸承的退化評(píng)估。
[Abstract]:With the rapid development of information technology and microelectronic technology, the heat flux of electronic devices is increasing, the power consumption is increasing, and the electronic equipment is developing towards lighter and thinner direction. The heat dissipation problem of electronic equipment becomes more and more prominent. As a key component of heat dissipation system of electronic equipment, heat dissipation fan plays an important role in ensuring the smooth and reliable operation of the system. According to statistics. Most of the mechanical failures of the cooling fan are concentrated on the bearing failure. Fault diagnosis and condition evaluation of heat dissipation fan bearings can effectively guarantee the reliability of electronic equipment and prolong the service life of electronic equipment. Aiming at the vibration mechanism and operation mode of heat dissipation fan bearing, a series of related researches on fault diagnosis and condition evaluation are carried out in this paper. The main contents include: analyzing the structural characteristics of heat dissipation fan. The vibration mechanism and signal characteristics of rolling bearings are reviewed. Using EMD decomposition, wavelet analysis, AR autoregressive linear prediction and MED filter signal processing technology, the vibration signal of heat dissipation fan bearing is analyzed, and the fault diagnosis of heat dissipation fan bearing is realized. At the same time, a special comb filter is constructed, and a health index is established from the frequency domain of the signal to monitor the health status of the bearing. In addition, the SVM technology is used to classify and identify the running state of the cooling fan bearing, and based on the classification results, the degradation index of the heat dissipation fan bearing is constructed. The degradation assessment of cooling fan bearings is realized.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TH165.3

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