本文關鍵詞：模糊診斷法在風機故障診斷中的研究與應用　出處：《遼寧科技大學》2012年碩士論文　論文類型：學位論文

  更多相關文章： 風機 模糊理論 故障診斷 輔助系統(tǒng)

【摘要】：風機廣泛應用于國民生產(chǎn)的各個部門,對國家經(jīng)濟發(fā)展起重要作用,因此對風機開展故障診斷和狀態(tài)監(jiān)測工作,保證風機良好的運行,具有重大的理論意義和現(xiàn)實意義 本論文將模糊理論應用到風機故障診斷中,依據(jù)風機故障的模糊癥狀進行狀態(tài)識別并進行模糊推理,從而做出診斷。此方法克服了傳統(tǒng)診斷法需要獲取精確信息的困難,適應了風機在連續(xù)運行過程中,由于受到工藝參數(shù)、溫度變化、周圍環(huán)境等因素影響,導致其運行狀態(tài)和故障表象的隨機性和模糊性。 通過對風機故障機理的研究,確定以振動烈度和倍頻峰值作為待檢故障的征兆庫,利用Matlab曲線擬合法和模糊分布法得出隸屬函數(shù)。參考專家經(jīng)驗與大量診斷實例結果,初步建立模糊矩陣,選擇加權平均型模型完成模糊方程。使用大連理工大學研制的PDM2000數(shù)據(jù)采集分析儀對故障風機進行振動信號采集,然后進行時域和頻域分析,得出所需數(shù)值進行模糊故障診斷。經(jīng)實例診斷結果對比,此方法是可行的。 采用C++語言開發(fā)出風機模糊故障診斷系統(tǒng),輔助求解隸屬函數(shù)和模糊方程并實現(xiàn)模糊矩陣的自學習功能,不斷對模糊診斷矩陣加以修正,逐步提高模糊診斷矩陣的適應能力和準確性。 使用該模型對某鋼廠內引風機和鼓風機進行測試診斷,經(jīng)信號采集、數(shù)據(jù)提取、參照選定、模糊診斷系統(tǒng)診斷等步驟,確定引風機正常,鼓風機為轉軸裂紋故障。停機進行檢修,顯示診斷結果正確,證明了此模型的實用性。
[Abstract]:The fan is widely used in various departments of national production and plays an important role in the development of national economy . Therefore , it is of great theoretical and practical significance to carry out fault diagnosis and state monitoring on the fan so as to ensure the good operation of the fan . In this paper , the fuzzy theory is applied to the fault diagnosis of the fan , the state recognition is carried out according to the fuzzy symptom of the fan fault and fuzzy reasoning is carried out , so that the diagnosis is made . The method overcomes the difficulty that the traditional diagnosis method needs to acquire accurate information , and the method overcomes the influence of the factors such as process parameters , temperature changes and the surrounding environment in the continuous operation process of the fan , and leads to the randomness and the ambiguity of the operation state and the fault appearance . By studying the mechanism of fan failure , it is determined that the vibration intensity and the frequency doubling peak are used as the symptom database of the fault to be detected . The fuzzy matrix is obtained by using the Matlab curve fitting method and the fuzzy distribution method . The fuzzy matrix is established by using the PDM2000 data acquisition analyzer developed by Dalian University of Technology . The fuzzy fault diagnosis is carried out by using the PDM2000 data acquisition analyzer developed by Dalian University of Science and Technology . In this paper , the fuzzy fault diagnosis system of the fan is developed by using C ++ language , the membership function and the fuzzy equation are solved , the self - learning function of the fuzzy matrix is realized , the fuzzy diagnosis matrix is corrected , and the adaptability and the accuracy of the fuzzy diagnosis matrix are gradually improved . This model is used to diagnose the induced draft fan and blower in a steel plant . After signal acquisition , data extraction , reference selection and diagnosis of the fuzzy diagnosis system , it is determined that the fan is normal and the blower is the crack fault of the rotating shaft . The shutdown is repaired , the diagnosis result is correct , and the practicability of the model is proved .

【學位授予單位】：遼寧科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TH165.3

【參考文獻】

相關期刊論文 前10條

1 張遠軍;;風機故障機理及診斷方法[J];包鋼科技;2009年04期

2 鄭君;張冬泉;;故障診斷技術[J];電氣時代;2008年05期

3 黃永東;;轉子不平衡現(xiàn)象的分析[J];發(fā)電設備;2009年03期

4 劉朝山,張繼華;油膜渦動和油膜振蕩的特征頻率[J];風機技術;2001年06期

5 王靜;郭九梅;王胤龍;;離心壓縮機轉子彎曲故障分析[J];風機技術;2009年06期

6 扶名福;謝明祥;饒泓;;模糊聚類分析法在抽風機故障診斷中應用[J];工程力學;2007年S1期

7 汪光陽;周義蓮;;風機振動故障診斷綜述[J];安徽工業(yè)大學學報(自然科學版);2006年01期

8 王宇飛;謝永鵬;;旋轉機械轉子不平衡故障的診斷與分析[J];湖南工業(yè)職業(yè)技術學院學報;2009年05期

9 付波;周建中;彭兵;安學利;;固定式剛性聯(lián)軸器不對中彎扭耦合振動特性[J];華中科技大學學報(自然科學版);2007年04期

10 崔保;;滑動軸承油膜渦動和油膜振蕩的機理與診斷[J];機械工程師;2006年06期

，

本文編號：1432975