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

【摘要】：本文采用基于決策樹(shù)(C4.5算法)和模糊邏輯系統(tǒng)(FIS)相結(jié)合的智能故障診斷方法,利用汽輪機(jī)實(shí)驗(yàn)室中的轉(zhuǎn)子實(shí)驗(yàn)臺(tái)進(jìn)行試驗(yàn)研究。結(jié)合實(shí)驗(yàn)設(shè)備,擬設(shè)計(jì)轉(zhuǎn)子正常運(yùn)轉(zhuǎn)(GOOD);質(zhì)量不平衡(RMUB);動(dòng)靜碰磨(MSCF);油膜振蕩(RWOW)四種振動(dòng)故障實(shí)驗(yàn),并分別設(shè)計(jì)三種工作轉(zhuǎn)速(2000rpm,4000rpm,6000rpm)的工作狀態(tài)下運(yùn)行。每種故障實(shí)驗(yàn)進(jìn)行50組,其振動(dòng)信號(hào)可從電渦流傳感器結(jié)合DASP采集分析軟件獲取,然后對(duì)各組實(shí)驗(yàn)樣本數(shù)據(jù)計(jì)算出統(tǒng)計(jì)特征參數(shù),本文利用決策樹(shù)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(guān)特征,再利用統(tǒng)計(jì)特征參數(shù)構(gòu)建決策樹(shù),決策樹(shù)輸出結(jié)果用來(lái)產(chǎn)生清晰、簡(jiǎn)潔的if-then規(guī)則。然后利用Matlab模糊邏輯工具箱來(lái)產(chǎn)生的隸屬函數(shù)集并確定模糊推理分類結(jié)構(gòu)。通過(guò)測(cè)試樣本對(duì)決策樹(shù)分類和模糊邏輯規(guī)則集的準(zhǔn)確性進(jìn)行檢驗(yàn),并將產(chǎn)生的模糊推理機(jī)利用Matlab中Simulink工具箱得到最終的簡(jiǎn)化模型。 本文以4000rpm的樣本數(shù)據(jù)為例計(jì)算統(tǒng)計(jì)參數(shù)并構(gòu)造決策樹(shù),得出if-then語(yǔ)句規(guī)則和I隸屬函數(shù)集,最后再用基于轉(zhuǎn)子實(shí)驗(yàn)臺(tái)獲得的轉(zhuǎn)子振動(dòng)信號(hào)的測(cè)試樣本來(lái)評(píng)估本文使用的C4.5-FIS模型故障診斷方法,再分別評(píng)估對(duì)于2000rpm和6000rpm兩種不同轉(zhuǎn)速條件下這該診斷模型的準(zhǔn)確性,結(jié)果表明其準(zhǔn)確度都很高.故該C4.5-FIS模糊推理模型對(duì)于汽輪發(fā)電機(jī)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(xué)位授予單位】：華北電力大學(xué)（北京）
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH165.3

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