摘要：模糊聚類(lèi)是通過(guò)模糊數(shù)學(xué)方法對(duì)已知類(lèi)別的各參數(shù)進(jìn)行比較，找出規(guī)律來(lái)推斷和預(yù)報(bào)未知類(lèi)別的屬性。本文以轉(zhuǎn)子故障數(shù)據(jù)為對(duì)象，運(yùn)用了模糊聚類(lèi)方法和C-均值聚類(lèi)方法對(duì)轉(zhuǎn)子故障數(shù)據(jù)進(jìn)行了處理，利用Matlab工具對(duì)轉(zhuǎn)子故障診斷的系統(tǒng)進(jìn)行了仿真和調(diào)試，并進(jìn)行了可行性驗(yàn)證。
完成設(shè)計(jì)內(nèi)容如下：
1、用模糊聚類(lèi)方法對(duì)轉(zhuǎn)子故障數(shù)據(jù)進(jìn)行處理，建立模糊矩陣，從而求得相似系數(shù)，來(lái)進(jìn)行數(shù)據(jù)的標(biāo)定。然后使用傳遞閉包法對(duì)標(biāo)定的模糊相似矩陣用平方法計(jì)算，利用Matlab求得傳遞閉包，最后進(jìn)行聚類(lèi)。
2、用C-均值聚類(lèi)方法利用公式計(jì)算轉(zhuǎn)子故障數(shù)據(jù)的相似矩陣，利用Matlab從初始矩陣算出迭代次數(shù)，得到模糊矩陣，并對(duì)此進(jìn)行聚類(lèi)。將方法應(yīng)用于抽風(fēng)機(jī)故障數(shù)據(jù)，再次進(jìn)行驗(yàn)證。

關(guān)鍵詞：轉(zhuǎn)子故障診斷；模糊聚類(lèi)；相似矩陣；傳遞閉包


Rotor Fault Diagnosis and Analysis
Based on Fuzzy clustering Method
Abstract: Fuzzy clustering is comparing the parameters of the known types through fuzzy mathematics to find out the laws which could be used in indentifying and forecasting the properties of the unknown categories. As rotor fault data as the object, this thesis has used both fuzzy clustering method and C-means clustering method to process the rotor fault data. At the same time, the system of rotor fault diagnosis has been simulated and debugged by Matlab, which has verified the feasibility of fuzzy clustering method.
Its basic design process is as follows:
1, Using fuzzy clustering method for rotor fault data processing, fuzzy matrix, and thus achieve a similar coefficient to the calibration data. Then use the transitive closure method of calibration of the fuzzy similarity matrix calculated using Matlab to seek transitive closure, the final cluster.
2, Using C-means clustering method of rotor fault using a formula similar to the data matrix, use of Matlab matrix calculated from the initial iteration, the fuzzy matrix, and this cluster. Method has been applied to fault data exhaust fan once again to verify.

Keywords: Rotor fault diagnosis; Fuzzy clustering; Similarity matrix; Transitive closure.

Classification:TP2


目 次
摘 要 II
目 錄 III
1.引言 1
1.1國(guó)內(nèi)外研究現(xiàn)狀 1
1.1.1模糊聚類(lèi)應(yīng)用領(lǐng)域 2
1.1.2 其他用于故障診斷的方法 3
1.2 研究思路 3
1.2.1 理論基礎(chǔ)和分析 3
1.2.2 研究設(shè)想、方法 6
1.3研究的意義 6
2. 模糊聚類(lèi)的原理 7
2.1 模糊聚類(lèi) 7
2.1.1模糊聚類(lèi)的理論基礎(chǔ) 7
2.1.2 聚類(lèi)的方法 9
2.2 模糊邏輯原理 12
3.轉(zhuǎn)子故障的診斷與分析 14
3.1模糊聚類(lèi)法對(duì)故障數(shù)據(jù)進(jìn)行診斷與分析 17
3.1.1聚類(lèi)步驟 18
3.1.2 利用Matlab程序得到的聚類(lèi)譜系圖 19
3.2模糊C-均值聚類(lèi)方法對(duì)故障數(shù)據(jù)進(jìn)行診斷分析 19
3.2.1 模糊C-均值聚類(lèi)步驟 20
3.2.2 聚類(lèi)譜系圖的獲得 22
3.3 聚類(lèi)與分析 24
3.3.1二十組數(shù)據(jù)測(cè)試 24
3.3.2四十組數(shù)據(jù)測(cè)試 25
3.3.3應(yīng)用于抽風(fēng)機(jī)故障數(shù)據(jù)驗(yàn)證 26
4.總結(jié) 29
參考文獻(xiàn) 29
附錄 主要程序和矩陣 31



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