本文選題：變工況 + 永磁風(fēng)力發(fā)電機(jī)�。� 參考：《新疆大學(xué)》2017年碩士論文

【摘要】：新疆地區(qū)風(fēng)能資源豐富,是我國重要的風(fēng)電基地。該地區(qū)風(fēng)電機(jī)組要承受高溫、冰凍、風(fēng)沙等極端環(huán)境,在其設(shè)計(jì)壽命周期內(nèi)故障頻發(fā)。風(fēng)電機(jī)組機(jī)艙常安裝于50~80m的高空,設(shè)備維護(hù)困難,且故障診斷結(jié)果受風(fēng)速、載荷、并網(wǎng)運(yùn)行狀態(tài)影響較大,診斷精度不高。因此,研究計(jì)及并網(wǎng)運(yùn)行狀態(tài)的風(fēng)電機(jī)組監(jiān)測(cè)與故障診斷技術(shù)意義重大。本論文針對(duì)永磁直驅(qū)型風(fēng)力發(fā)電機(jī)早期故障不易監(jiān)測(cè)和診斷的難題,綜合設(shè)備的電流和振動(dòng)信息,在正常、風(fēng)速突變、電網(wǎng)電壓不平衡三種工況下對(duì)永磁直驅(qū)風(fēng)力發(fā)電機(jī)正常運(yùn)行(視為特殊故障)、主軸偏心、主軸軸承磨損三種故障進(jìn)行診斷。具體內(nèi)容如下:(1)對(duì)新疆地區(qū)風(fēng)電機(jī)組故障狀況進(jìn)行了初步調(diào)研,對(duì)比了我國新疆地區(qū)和瑞典的風(fēng)電機(jī)組故障特點(diǎn)。分析了主軸偏心和軸承磨損的故障類型及故障特性,定性分析上述故障對(duì)振動(dòng)信號(hào)和電流信號(hào)的影響。對(duì)故障診斷方法進(jìn)行梳理,對(duì)比分析診斷模型的優(yōu)缺點(diǎn),選定SVM作為初步診斷模型。(2)開發(fā)了風(fēng)電機(jī)組多源信息采集系統(tǒng),搭建了變工況風(fēng)電機(jī)組故障檢測(cè)試驗(yàn)臺(tái)。實(shí)驗(yàn)采集了永磁直驅(qū)型風(fēng)力發(fā)電機(jī)在正常、風(fēng)速突變、電網(wǎng)三相電壓不平衡三種工況下正常運(yùn)行(視為特殊故障)、主軸偏心、主軸軸承磨損三種故障的定子電流和徑向振動(dòng)信號(hào)。研究了振動(dòng)和電流信號(hào)的故障特征提取方法,建立了故障特征樣本庫,并引入馬氏距離對(duì)故障特征的可分性進(jìn)行評(píng)價(jià)。(3)利用logistic回歸函數(shù)和逐對(duì)耦合方法改進(jìn)了傳統(tǒng)的SVM診斷模型,使得SVM能同時(shí)輸出故障類型和故障概率。分別基于振動(dòng)特征和電流特征建立診斷模型,在正常、風(fēng)速突變、三相不平衡三種工況下對(duì)發(fā)電機(jī)故障進(jìn)行初步診斷,并對(duì)初步診斷結(jié)果進(jìn)行評(píng)價(jià)。(4)改進(jìn)了傳統(tǒng)D-S證據(jù)理論,利用可靠性矩陣,建立了證據(jù)可靠性系數(shù)和融合權(quán)重之間的關(guān)系。綜合診斷模型的泛化能力和診斷效果,對(duì)初步診斷結(jié)果賦予不同的權(quán)重并進(jìn)行融合診斷。相比基于單一征兆的初步診斷方法,加權(quán)融合后,錯(cuò)誤診斷結(jié)果得到修正,診斷精度得到明顯提高。
[Abstract]:Xinjiang is rich in wind energy resources and is an important wind power base in China. Wind turbines in this area have to withstand extreme environments such as high temperature, freezing, wind and sand, and frequent failures occur during their design life cycle. The engine room of wind turbine is usually installed at an altitude of 50m and 80m, the maintenance of the equipment is difficult, and the result of fault diagnosis is greatly affected by wind speed, load, grid-connected operation state, and the diagnostic accuracy is not high. Therefore, it is of great significance to study the monitoring and fault diagnosis technology of wind turbine taking into account the grid-connected operation state. Aiming at the difficult problem of early fault monitoring and diagnosis of permanent magnet direct-drive wind turbine, this paper synthesizes the current and vibration information of the equipment in normal, abrupt wind speed. The fault diagnosis of permanent magnet direct drive wind turbine (PMSG) is made under three working conditions, which are considered as special fault, spindle eccentricity and spindle bearing wear. The main contents are as follows: (1) A preliminary investigation is carried out on the fault status of wind turbines in Xinjiang, and the fault characteristics of wind turbines in Xinjiang and Sweden are compared. The fault types and characteristics of spindle eccentricity and bearing wear are analyzed, and the effects of these faults on vibration signal and current signal are analyzed qualitatively. The fault diagnosis method is combed, the advantages and disadvantages of the diagnosis model are compared and analyzed, the SVM is selected as the primary diagnosis model. The multi-source information acquisition system of wind turbine is developed, and the fault detection test-bed of wind power unit under different working conditions is built. The permanent magnet direct-drive wind turbine (PMSG) is tested under three working conditions: normal operation, sudden wind speed, unbalanced three-phase voltage (considered as a special fault and eccentric spindle). Stator current and radial vibration signal of three kinds of fault of spindle bearing wear. The fault feature extraction method of vibration and current signals is studied, and the fault feature sample database is established. And the Markov distance is introduced to evaluate the separability of fault features.) the traditional logistic diagnosis model is improved by using logistic regression function and pairwise coupling method, which enables SVM to output fault types and fault probability at the same time. Based on the characteristics of vibration and current, the diagnosis model is established, and the fault diagnosis of generator is carried out under the normal condition, the sudden change of wind speed and the three-phase unbalance, and the evaluation of the preliminary diagnosis result is made. (4) the traditional D-S evidence theory is improved. The relationship between evidence reliability coefficient and fusion weight is established by using reliability matrix. By synthesizing the generalization ability and diagnostic effect of the diagnostic model, different weights are given to the preliminary diagnosis results and fusion diagnosis is carried out. Compared with the initial diagnosis method based on single symptom, the error diagnosis result is corrected and the diagnostic accuracy is improved obviously after weighted fusion.
【學(xué)位授予單位】：新疆大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM315

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本文編號(hào)：2011047