【摘要】：風(fēng)電作為較為發(fā)展成熟的可再生能源已經(jīng)得到廣泛利用,但是由于工作環(huán)境惡劣,風(fēng)電機(jī)組故障發(fā)生率較高。齒輪箱作為風(fēng)電機(jī)組的主要組成部分,起著傳遞動(dòng)力的作用,齒輪箱的運(yùn)行狀況如何直接關(guān)系到風(fēng)電機(jī)組運(yùn)行的好壞。加強(qiáng)齒輪箱的狀態(tài)監(jiān)測(cè),實(shí)現(xiàn)齒輪箱早期故障的預(yù)警和診斷對(duì)于提高機(jī)組運(yùn)行效率,降低維修費(fèi)用都有著重要意義。本文的研究對(duì)象時(shí)華銳SL1500機(jī)組的齒輪箱,從振動(dòng)參數(shù)和SCADA參數(shù)兩方面著手,對(duì)風(fēng)電機(jī)組齒輪箱的齒輪磨損和點(diǎn)蝕故障進(jìn)行了深入研究和分析,具體包括如下幾個(gè)方面。 首先,對(duì)齒輪箱的結(jié)構(gòu)進(jìn)行了研究和設(shè)備劃分,根據(jù)齒輪箱的詳細(xì)參數(shù),對(duì)所需頻率進(jìn)行了計(jì)算。從齒輪的振動(dòng)機(jī)理出發(fā),建立齒輪振動(dòng)模型,研究其振動(dòng)機(jī)理并簡化振動(dòng)數(shù)學(xué)模型。對(duì)于磨損和點(diǎn)蝕故障進(jìn)行深入研究,結(jié)合齒輪的FTA分析建立了故障原因庫、故障影響庫、故障征兆庫、故障措施庫,建立了完整的故障知識(shí)庫,為下一步的預(yù)警和診斷工作的開展奠定了理論基礎(chǔ)。 其次,針對(duì)SCADA參數(shù),采取了選定相關(guān)參數(shù),進(jìn)行歷史系數(shù)矩陣和實(shí)時(shí)系數(shù)矩陣計(jì)算,并計(jì)算兩者之間的偏差,通過偏差來實(shí)現(xiàn)齒輪箱一段時(shí)間內(nèi)的狀態(tài)預(yù)警。針對(duì)振動(dòng)信號(hào),本文采取了計(jì)算迅速的簡單差值方法,將經(jīng)過相同時(shí)間采樣的時(shí)域信號(hào)轉(zhuǎn)變成了經(jīng)過相同角度采樣的角域信號(hào),實(shí)現(xiàn)了信號(hào)的整周期重采樣。對(duì)所得到的角域信號(hào)進(jìn)行無量綱特征提取,通過仿真分別找出與磨損、點(diǎn)蝕故障最為匹配的無量綱特征值,對(duì)其采用K鄰近度異常檢測(cè)方法,通過求取相關(guān)距離來進(jìn)行異常點(diǎn)判定,通過計(jì)算異常點(diǎn)百分比實(shí)現(xiàn)磨損和點(diǎn)蝕的早期故障預(yù)警。另一方面,引入HHT變換和階比分析,實(shí)現(xiàn)了頻率特征值階比能量譜的提取,并將其作為早期故障診斷的故障特征值。通過研究階比能量譜的變化來實(shí)現(xiàn)齒輪磨損和點(diǎn)蝕早期故障診斷。預(yù)警和診斷相輔相成,在具體的齒輪磨損和點(diǎn)蝕故障的預(yù)警和診斷過程中,結(jié)合機(jī)理分析,提出了基于知識(shí)的診斷方法,通過特征匹配來實(shí)現(xiàn)特定故障模式的預(yù)警診斷。 最后,將早期故障預(yù)警和診斷的方法運(yùn)用的工程應(yīng)用當(dāng)中去。確定了風(fēng)電機(jī)組傳動(dòng)系統(tǒng)的振動(dòng)測(cè)點(diǎn)布置圖以及傳感器選型。根據(jù)華銳SL1500齒輪箱的詳細(xì)參數(shù),結(jié)合故障機(jī)理對(duì)點(diǎn)蝕故障進(jìn)行了故障識(shí)別工作,并形成相應(yīng)故障診斷報(bào)告,給維修工作做出指導(dǎo)。
[Abstract]:Wind power has been widely used as a more mature and mature renewable energy source, but due to the bad working environment, the fault rate of the wind power unit is high. As the main part of the wind power unit, the gear box acts as a transmission power, and the operation condition of the gear box is directly related to the operation of the wind turbine unit. It is of great significance to strengthen the state monitoring of the gear box, to realize the early warning and diagnosis of the early fault of the gear box, and to improve the operation efficiency of the unit and to reduce the maintenance cost. In this paper, the gear box, the vibration parameters and the SCADA parameters of the Huarui SL1500 unit are studied, and the gear wear and pitting faults of the gear box of the wind turbine generator set are studied and analyzed in detail, including the following aspects. First, the structure of the gear box is studied and the equipment is divided, and the required frequency is calculated according to the detailed parameters of the gear box. On the basis of the vibration mechanism of the gear, a gear vibration model is set up, its vibration mechanism is studied and the vibration mathematical model is simplified. In this paper, the fault cause library, the fault-affected library, the fault symptom library and the fault-measure library have been set up with the FTA analysis of the gear, and the complete fault knowledge base is established, and the theoretical basis for the development of the next-step early-warning and diagnosis work is established. secondly, according to the SCADA parameters, the selected relevant parameters are adopted, the historical coefficient matrix and the real-time coefficient matrix are calculated, the deviation between the two is calculated, In this paper, a simple difference method is adopted to calculate the vibration signal. The time domain signal sampled by the same time is converted into the angular domain signal sampled by the same angle, and the whole period of the signal is realized. and carrying out non-dimensional feature extraction on the obtained angular domain signal, Point determination that the early result of wear and pitting is achieved by calculating the percentage of abnormal points On the other hand, the HHT transformation and the order ratio analysis are introduced, the extraction of the frequency characteristic order energy spectrum is realized, and it is used as the fault of the early fault diagnosis The characteristics of gear wear and pitting are realized by studying the change of the energy spectrum of the order ratio. The early warning and diagnosis are mutually reinforcing. In the process of early warning and diagnosis of specific gear wear and pitting failure, based on the analysis of the mechanism, a knowledge-based diagnosis method is put forward, and the pre-warning of the specific failure mode is realized by the feature matching. The engineering of the method of early warning and diagnosis of early faults. In the application, the layout of the vibration measuring points of the transmission system of the wind turbine generator set and the layout of the vibration measuring points are Type selection of the sensor. According to the detailed parameters of the gear box of the Huarui SL1500, the fault identification of the pitting fault is carried out in combination with the fault mechanism, and the corresponding fault diagnosis report shall be formed for the maintenance man.
【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)】：TM315

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