本文關(guān)鍵詞： 風(fēng)力發(fā)電機(jī)組 傳動(dòng)系統(tǒng) 狀態(tài)監(jiān)測(cè) 故障診斷 專家系統(tǒng)　出處：《華北電力大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：風(fēng)力發(fā)電機(jī)組傳動(dòng)系統(tǒng)自身結(jié)構(gòu)復(fù)雜，在故障檢測(cè)和維修中都會(huì)占用很長(zhǎng)時(shí)間，對(duì)電力生產(chǎn)造成的影響也很大，因此對(duì)風(fēng)力發(fā)電機(jī)組傳動(dòng)系統(tǒng)的故障進(jìn)行預(yù)警和診斷具有重要的實(shí)際價(jià)值。論文依據(jù)信號(hào)分析和人工智能技術(shù)，，對(duì)風(fēng)力發(fā)電機(jī)組傳動(dòng)系統(tǒng)振動(dòng)監(jiān)測(cè)與故障診斷系統(tǒng)展開研究。 論文首先以某風(fēng)場(chǎng)某型號(hào)1.5兆瓦風(fēng)力發(fā)電機(jī)組齒輪箱和軸承為研究對(duì)象，計(jì)算了齒輪箱各級(jí)齒輪和軸承的故障特征頻率，分析了齒輪箱高速軸測(cè)點(diǎn)的振動(dòng)信號(hào)，提取了3種故障信號(hào)的特征，特征分析結(jié)果與開箱檢查的故障相符合，為專家系統(tǒng)的故障特征知識(shí)庫(kù)的建立奠定了基礎(chǔ)。 然后論文構(gòu)建了專家系統(tǒng)的知識(shí)庫(kù)和推理機(jī)，結(jié)合傳動(dòng)系統(tǒng)的信號(hào)處理，分析了正常和故障零件的峭度指標(biāo)值、頻譜能量分布值、信息熵值的差異。確定了峭度指標(biāo)作為監(jiān)測(cè)特征參數(shù)，以頻譜能量分布值與信息熵作為故障特征參數(shù)。以訓(xùn)練后BP神經(jīng)網(wǎng)絡(luò)作為專家系統(tǒng)故障診斷的推理機(jī)，將提取到的齒輪箱振動(dòng)信號(hào)的故障特征參數(shù)作為輸入樣本進(jìn)行仿真測(cè)試，測(cè)試結(jié)果顯示推理機(jī)能夠?qū)崿F(xiàn)故障診斷的目標(biāo)。 最后，基于LabVIEW軟件的開發(fā)環(huán)境，設(shè)計(jì)了風(fēng)力發(fā)電機(jī)組傳動(dòng)系統(tǒng)振動(dòng)監(jiān)測(cè)與故障診斷系統(tǒng)，系統(tǒng)能實(shí)現(xiàn)的功能主要包括信號(hào)的時(shí)域波形顯示、頻域分析、降噪處理、故障預(yù)警、故障診斷、數(shù)據(jù)管理等。
[Abstract]:The structure of the wind turbine transmission system is complex, which will take a long time in the fault detection and maintenance, and also has a great impact on the power production. Therefore, the early warning and diagnosis of wind turbine transmission system has important practical value. The paper is based on signal analysis and artificial intelligence technology. The vibration monitoring and fault diagnosis system of wind turbine transmission system is studied. Firstly, the gearbox and bearing of a 1.5-megawatt wind turbine in a certain wind field are studied, and the fault characteristic frequency of gear box and bearing is calculated. The vibration signals of gearbox high speed shaft measuring points are analyzed, and the characteristics of three kinds of fault signals are extracted. The results of characteristic analysis are consistent with those of open box inspection. It lays a foundation for the establishment of fault feature knowledge base of expert system. Then the knowledge base and inference machine of expert system are constructed, and the kurtosis index value and spectrum energy distribution value of normal and fault parts are analyzed in combination with the signal processing of transmission system. The kurtosis index is determined as the monitoring characteristic parameter, the spectrum energy distribution value and the information entropy as the fault characteristic parameter, and the trained BP neural network as the inference machine of expert system fault diagnosis. The fault characteristic parameters of the vibration signal of the gearbox are used as input samples for simulation test. The test results show that the inference machine can achieve the goal of fault diagnosis. Finally, based on the development environment of LabVIEW software, the vibration monitoring and fault diagnosis system of wind turbine transmission system is designed. The main functions of the system include signal display in time domain. Frequency domain analysis, noise reduction, fault warning, fault diagnosis, data management, etc.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP277;TM315

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