本文關(guān)鍵詞：主元分析法在火電廠故障檢測(cè)中的應(yīng)用及效果研究　出處：《華北電力大學(xué)》2016年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 主元分析方法 故障檢測(cè) 自適應(yīng)控制限 綜合效益評(píng)價(jià)

【摘要】：火電企業(yè)技術(shù)改造是當(dāng)今技術(shù)創(chuàng)新及應(yīng)用研究的主流方向之一,其中,技術(shù)改造主要是通過(guò)改進(jìn)物理結(jié)構(gòu)或加裝新設(shè)備來(lái)實(shí)現(xiàn),如加裝脫硫裝置、對(duì)磨煤機(jī)改進(jìn)等。然而,技術(shù)改造并非只有物理改造,還應(yīng)包括電子技術(shù)的改進(jìn),如對(duì)控制算法、檢測(cè)方法的改進(jìn)。在這些方面,國(guó)內(nèi)相關(guān)研究并不多。本文通過(guò)研究火電企業(yè)運(yùn)行過(guò)程,發(fā)現(xiàn)在故障檢測(cè)方面,國(guó)內(nèi)絕大部分火電廠均使用固定的控制限來(lái)報(bào)錯(cuò),而火電廠實(shí)際運(yùn)行過(guò)程卻并非持續(xù)穩(wěn)態(tài)運(yùn)行,這就導(dǎo)致了在火電廠增減負(fù)荷時(shí)系統(tǒng)出現(xiàn)誤報(bào)或數(shù)據(jù)的丟失,嚴(yán)重影響監(jiān)測(cè)的穩(wěn)定性,從而影響火電企業(yè)的經(jīng)濟(jì)性。主元分析方法(PCA)作為多元統(tǒng)計(jì)方法的一種,其對(duì)過(guò)程控制的故障檢測(cè)與診斷方法不依賴(lài)于系統(tǒng)的數(shù)學(xué)模型,因此是廣泛應(yīng)用在工業(yè)領(lǐng)域的統(tǒng)計(jì)檢測(cè)方法�；谥髟治龇椒ǖ倪^(guò)程檢測(cè)方法,由于充分的利用了主元分析算法在處理線(xiàn)性相關(guān)數(shù)據(jù)時(shí)降維的功能,使得對(duì)多變量生產(chǎn)過(guò)程的檢測(cè)可在低維變量控件實(shí)現(xiàn)。因此,考慮在火電企業(yè)故障檢測(cè)中使用主元分析方法。故障檢測(cè)中的PCA方法原理是在穩(wěn)態(tài)過(guò)程中收集數(shù)據(jù),用固定控制限的SPE、T_2和T_H~2來(lái)監(jiān)測(cè)。然而,對(duì)于那些過(guò)程暫態(tài)值必須考慮的系統(tǒng)(如火電廠運(yùn)行系統(tǒng)),用固定控制限會(huì)引起誤報(bào)和丟失數(shù)據(jù),這會(huì)嚴(yán)重影響監(jiān)測(cè)系統(tǒng)的穩(wěn)定性,并帶來(lái)不必要的經(jīng)濟(jì)損失。本文立足于這一點(diǎn),對(duì)主元分析方法進(jìn)行改進(jìn),使得其能應(yīng)用在動(dòng)態(tài)穩(wěn)態(tài)經(jīng)常切換的火電廠運(yùn)行系統(tǒng)。本文總結(jié)了在火電廠故障檢測(cè)領(lǐng)域在的國(guó)內(nèi)外的研究成果,指出了該領(lǐng)域需要深入研究的問(wèn)題;針對(duì)目前存在的問(wèn)題,提出了基于方差的自適應(yīng)控制限的改進(jìn)方法,從而來(lái)克服暫態(tài)過(guò)程中因條件改變而產(chǎn)生的誤報(bào)問(wèn)題;選取某火電廠的相關(guān)數(shù)據(jù),利用matlab軟件對(duì)該方法進(jìn)行了仿真,驗(yàn)證了該技術(shù)改造的可行性;通過(guò)建立評(píng)價(jià)指標(biāo),運(yùn)用層次分析法確定指標(biāo)權(quán)重,運(yùn)用模糊評(píng)價(jià)法來(lái)對(duì)方案進(jìn)行綜合評(píng)價(jià)。結(jié)果表明,該技術(shù)改造可以為火電企業(yè)獲得經(jīng)濟(jì)效益與技術(shù)上的改進(jìn)。
[Abstract]:Technical transformation of thermal power enterprises is one of the main direction of the technology innovation and application of the technology is mainly realized through the improvement of the physical structure or the installation of new equipment, such as the installation of desulfurization equipment for mill improvement. However, technological transformation is not only a physical transformation, but also should include the improvement of electronic technology, such as the control algorithm, the improvement of the detection method. In these areas, not many domestic research. Through the research of thermal power enterprise operation process, found in fault detection, most of the domestic thermal power plants are used to control limit fixed error, while the actual operation process of power plant is not sustained steady operation. This resulted in the the system of thermal power plant load changes when the loss of false positives or data, seriously affect the stability of monitoring, thus affecting the economy of power enterprises. Principal component analysis (PCA) as a multivariate system A kind of design method, the mathematical model of the method of fault detection and diagnosis process control is not dependent on the system, so the statistical detection methods are widely used in industrial field. The process of PCA detection method based on the full use of the principal component analysis algorithm for dimensionality reduction in data processing of linear correlation the function, which makes the detection of the multi variable production process can be realized in low dimension control. Therefore, consider using principal component analysis method in fault detection in thermal power enterprises. The principle of PCA method in fault detection is to collect data in the steady state in the process of using the fixed control limits of SPE, T_2 and T_H~2 to monitor. However, for the transient value must be considered in the system (such as power plant operation system), with the loss of data will cause false positives and fixed control, which will seriously affect the stability of the monitoring system, and bring economic loss is not necessary Lost. Based on this, the principal component analysis method was improved, so it can be used frequently in the dynamic steady state switching power plant operation system. This paper summarizes the fault detection in the field of thermal power plant in the domestic and foreign research results, pointed out that the field needs to be further studied aiming at the existing problems; and put forward the improved method based on variance adaptive control limit, the problem of false positives due to changing conditions to overcome in transient process; selecting the relevant data of a thermal power plant, the method was simulated by using MATLAB software, to verify the feasibility of the technical transformation; through the establishment of evaluation index, using the analytic hierarchy process the weights of the indexes, using fuzzy evaluation method to comprehensive evaluation of the program. The results show that the technology can obtain improved economy benefit and technology of thermal power enterprises.

【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】：2016
【分類(lèi)號(hào)】：TM621

【引證文獻(xiàn)】

相關(guān)期刊論文 前1條

1 王軍;;火力發(fā)電廠運(yùn)行的安全管理及故障處理工作思考[J];經(jīng)營(yíng)管理者;2017年13期

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本文編號(hào)：1421296