本文選題：統(tǒng)計特征參數(shù) + 決策樹�。� 參考：《華北電力大學（北京）》2011年碩士論文

【摘要】：本文采用基于決策樹(C4.5算法)和模糊邏輯系統(tǒng)(FIS)相結合的智能故障診斷方法,利用汽輪機實驗室中的轉子實驗臺進行試驗研究。結合實驗設備,擬設計轉子正常運轉(GOOD);質量不平衡(RMUB);動靜碰磨(MSCF);油膜振蕩(RWOW)四種振動故障實驗,并分別設計三種工作轉速(2000rpm,4000rpm,6000rpm)的工作狀態(tài)下運行。每種故障實驗進行50組,其振動信號可從電渦流傳感器結合DASP采集分析軟件獲取,然后對各組實驗樣本數(shù)據(jù)計算出統(tǒng)計特征參數(shù),本文利用決策樹方法中C4.5算法作為故障特征選擇算法從數(shù)據(jù)樣本集中提取相關特征,再利用統(tǒng)計特征參數(shù)構建決策樹,決策樹輸出結果用來產(chǎn)生清晰、簡潔的if-then規(guī)則。然后利用Matlab模糊邏輯工具箱來產(chǎn)生的隸屬函數(shù)集并確定模糊推理分類結構。通過測試樣本對決策樹分類和模糊邏輯規(guī)則集的準確性進行檢驗,并將產(chǎn)生的模糊推理機利用Matlab中Simulink工具箱得到最終的簡化模型。 本文以4000rpm的樣本數(shù)據(jù)為例計算統(tǒng)計參數(shù)并構造決策樹,得出if-then語句規(guī)則和I隸屬函數(shù)集,最后再用基于轉子實驗臺獲得的轉子振動信號的測試樣本來評估本文使用的C4.5-FIS模型故障診斷方法,再分別評估對于2000rpm和6000rpm兩種不同轉速條件下這該診斷模型的準確性,結果表明其準確度都很高.故該C4.5-FIS模糊推理模型對于汽輪發(fā)電機組故障診斷具有很好的適用性。
[Abstract]:In this paper, an intelligent fault diagnosis method based on decision tree C4.5 algorithm and fuzzy logic system (fish) is proposed. Combined with the experimental equipment, it is proposed to design four kinds of vibration failure tests, such as normal operation of rotor, mass imbalance, dynamic and static impact grinding, oil film oscillation and RWOW, and design three kinds of rotating speed of 2000rpm 4000rpmC6000rpm respectively. The vibration signals can be obtained from eddy current sensor and DASP software, and then the statistical characteristic parameters are calculated for each group of experimental samples. In this paper, C4.5 algorithm in decision tree method is used as fault feature selection algorithm to extract relevant features from data sample set, and then statistical feature parameters are used to construct decision tree. The output result of decision tree is used to produce clear and concise if-then rules. Then the membership function set is generated by Matlab fuzzy logic toolbox and the classification structure of fuzzy reasoning is determined. The accuracy of decision tree classification and fuzzy logic rule set is verified by test samples, and the resulting fuzzy inference engine is obtained by using Simulink toolbox in Matlab to obtain the final simplified model. In this paper, taking the sample data of 4000rpm as an example, the statistical parameters are calculated and the decision tree is constructed. The rules of if-then statements and the set of I membership functions are obtained. Finally, the C4.5-FIS model fault diagnosis method used in this paper is evaluated with the test samples obtained from the rotor vibration signal obtained from the rotor test bench. The accuracy of the model is evaluated for the two different rotational speeds of 2000rpm and 6000rpm, respectively. The results show that the accuracy is very high. Therefore, the C4.5-FIS fuzzy inference model is suitable for fault diagnosis of turbogenerator.
【學位授予單位】：華北電力大學（北京）
【學位級別】：碩士
【學位授予年份】：2011
【分類號】：TH165.3

【參考文獻】

相關期刊論文 前10條

1 張紅飛;淺析大型汽輪發(fā)電機組振動及診斷[J];安徽電力職工大學學報;2002年01期

2 魏寶剛,何華燦,劉永懷;分布式人工智能的工程應用研究與實現(xiàn)[J];電力系統(tǒng)自動化;1997年06期

3 常立濤;;模糊邏輯及其應用探究[J];法制與經(jīng)濟(中旬刊);2010年05期

4 徐永禧;美國、加拿大8·14大停電[J];國際電力;2003年05期

5 曹焰 ,徐智京;汽輪發(fā)電機組摩擦振動故障的診斷與防止[J];華北電力技術;2001年12期

6 莫異周;;電站故障智能診斷技術的提高及發(fā)展方向[J];華夏星火;2004年10期

7 王可;夏立群;;基于模糊邏輯的作動器故障診斷方法研究[J];機床與液壓;2010年15期

8 劉東波;盧正鼎;;數(shù)據(jù)庫中的模糊邏輯規(guī)則發(fā)現(xiàn)[J];計算機工程與應用;2008年26期

9 鄒競;謝鯤;;C4.5算法在移動通信行業(yè)客戶流失分析中的應用[J];計算技術與自動化;2009年03期

10 李楠;段隆振;陳萌;;決策樹C4.5算法在數(shù)據(jù)挖掘中的分析及其應用[J];計算機與現(xiàn)代化;2008年12期

相關博士學位論文 前1條

1 覃鋒;模糊邏輯中若干問題的研究[D];四川大學;2004年

相關碩士學位論文 前2條

1 梁萌;汽輪機故障診斷技術研究[D];大慶石油學院;2005年

2 張聘亭;旋轉機械可組態(tài)在線監(jiān)測診斷系統(tǒng)以及手持式離線系統(tǒng)的研究[D];華中科技大學;2008年

，

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