【摘要】：近年來,隨著環(huán)境污染和能源危機(jī)的日益加劇,風(fēng)能等可再生清潔能源因具有儲(chǔ)量豐富和無污染等特點(diǎn)而備受世界各國(guó)的青睞和重視。我國(guó)風(fēng)電行業(yè)發(fā)展迅速,風(fēng)力發(fā)電機(jī)作為一種旋轉(zhuǎn)的機(jī)械設(shè)備,所具有的零件較多,結(jié)構(gòu)也相對(duì)復(fù)雜;同時(shí),風(fēng)電機(jī)組工作于人煙稀少,自然條件惡劣的環(huán)境中,導(dǎo)致風(fēng)機(jī)在運(yùn)行過程中故障頻繁發(fā)生,頻繁的故障維修致使風(fēng)電場(chǎng)的運(yùn)營(yíng)成本提高。因此,如何利用智能監(jiān)控手段減少風(fēng)機(jī)故障次數(shù)以達(dá)到節(jié)約風(fēng)電場(chǎng)的運(yùn)營(yíng)成本的目的,是目前大部分風(fēng)電場(chǎng)亟需要解決的重要課題�；诖吮尘跋�,開展智能手段的風(fēng)機(jī)故障預(yù)警及遠(yuǎn)程監(jiān)控研究具有重大意義。本文首先研究國(guó)內(nèi)外專家學(xué)者針對(duì)風(fēng)力發(fā)電機(jī)的故障預(yù)警和故障診斷的研究現(xiàn)狀;其次分析了風(fēng)機(jī)的工作原理、組成部分及典型故障,總結(jié)了故障發(fā)生的原因;最后,利用數(shù)據(jù)挖掘技術(shù)中的相關(guān)性提取相關(guān)規(guī)則,并將相關(guān)規(guī)則保存在數(shù)據(jù)庫(kù),通過查詢功能實(shí)現(xiàn)故障的匹配。重點(diǎn)針對(duì)風(fēng)力發(fā)電機(jī)故障預(yù)警進(jìn)行了研究,通過采集SCADA系統(tǒng)的監(jiān)控?cái)?shù)據(jù),計(jì)算了數(shù)據(jù)之間的相關(guān)系數(shù),分析了影響風(fēng)力發(fā)電機(jī)溫度的相關(guān)參量,并組建相關(guān)變量集。在此基礎(chǔ)上,建立了基于風(fēng)力發(fā)電機(jī)溫度的故障預(yù)警模型。通過預(yù)測(cè)值與實(shí)際值的殘差分析驗(yàn)證了風(fēng)機(jī)溫度故障預(yù)警模型的有效性。本文結(jié)合遼寧龍?jiān)达L(fēng)力發(fā)電有限公司法庫(kù)風(fēng)電場(chǎng)的實(shí)際情況,簡(jiǎn)要說明風(fēng)機(jī)遠(yuǎn)程監(jiān)控的設(shè)計(jì)思路,并詳細(xì)說明如何實(shí)現(xiàn)此方法,其中包括數(shù)據(jù)挖掘、數(shù)據(jù)采集、數(shù)據(jù)傳輸方法、數(shù)據(jù)存儲(chǔ)、數(shù)據(jù)發(fā)布和監(jiān)控,以及整個(gè)通訊的框架,最終實(shí)現(xiàn)在用戶的手機(jī)APP上監(jiān)控風(fēng)電場(chǎng)運(yùn)行并實(shí)施安全保護(hù)。對(duì)設(shè)計(jì)其他的監(jiān)控系統(tǒng)起到了指導(dǎo)作用,同時(shí)為以后開發(fā)相關(guān)軟件奠定了基礎(chǔ)。
[Abstract]:In recent years, with the worsening of environmental pollution and energy crisis, renewable clean energy, such as wind energy, has attracted much attention from all over the world because of its rich reserves and no pollution. Wind turbine is developing rapidly in our country. As a kind of rotating mechanical equipment, wind turbine has more parts and more complicated structure. At the same time, the wind turbine works in the environment with few people and bad natural conditions, which leads to frequent faults and frequent maintenance of the wind farm. Therefore, how to use intelligent monitoring means to reduce the number of fan failures to achieve the purpose of saving the operating costs of wind farms is an important issue that most wind farms need to solve. Based on this background, it is of great significance to carry out the research of fan fault warning and remote monitoring by intelligent means. This paper firstly studies the research status of wind turbine fault early warning and fault diagnosis at home and abroad, then analyzes the working principle, components and typical faults of the fan, and summarizes the causes of the fault. Finally, the correlation in data mining technology is used to extract the relevant rules, and the relevant rules are saved in the database, and the fault matching is realized by the query function. By collecting the monitoring data of the SCADA system, the correlation coefficient between the data is calculated, the related parameters affecting the temperature of the wind turbine are analyzed, and the relevant variable sets are set up. On this basis, a fault warning model based on wind turbine temperature is established. The validity of the early warning model of fan temperature fault is verified by the residual analysis of the predicted value and the actual value. Based on the actual situation of Faku wind farm in Liaoning Longyuan Wind Power Co., Ltd, this paper briefly explains the design idea of remote monitoring fan, and explains in detail how to realize this method, including data mining, data acquisition, data transmission, etc. Data storage, data release and monitoring, as well as the framework of the entire communication, the final implementation of the user's mobile phone APP to monitor the operation of wind farms and the implementation of security protection. It plays a guiding role in the design of other monitoring systems and lays a foundation for the development of related software in the future.
【學(xué)位授予單位】：沈陽工程學(xué)院
【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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