【摘要】：隨著經(jīng)濟(jì)的迅速發(fā)展和城市建設(shè)規(guī)模的擴(kuò)大化、快速化,塔式起重機(jī)的重要作用日益突出,且機(jī)群協(xié)同作業(yè)的情況越來(lái)越普遍。與此同時(shí),塔機(jī)事故隨著機(jī)群規(guī)模的擴(kuò)大而頻繁發(fā)生,嚴(yán)重者甚至造成人員的傷亡。因此,為使整個(gè)機(jī)群有效運(yùn)行、協(xié)調(diào)工作、減少因事故造成的經(jīng)濟(jì)損失和人員傷亡,及時(shí)、準(zhǔn)確的檢測(cè)診斷出塔機(jī)的故障將具有重大的經(jīng)濟(jì)效益和學(xué)術(shù)研究?jī)r(jià)值。 首先,塔式起重機(jī)機(jī)群擁有巨大的工作數(shù)據(jù),如何利用這些數(shù)據(jù)來(lái)反映塔機(jī)的工作狀態(tài)并使相關(guān)人員及時(shí)掌握情況是故障檢測(cè)與診斷的關(guān)鍵。本文通過(guò)研究塔式起重機(jī)組成機(jī)構(gòu)的工作及檢測(cè)原理,總結(jié)出塔式起重機(jī)機(jī)群故障特點(diǎn),為機(jī)群故障檢測(cè)與診斷方法的研究和系統(tǒng)設(shè)計(jì)奠定了基礎(chǔ)。 其次,研究了基于神經(jīng)網(wǎng)絡(luò)專家系統(tǒng)的塔式起重機(jī)故障檢測(cè)與診斷方法。該方法融合了神經(jīng)網(wǎng)絡(luò)的學(xué)習(xí)能力、自適應(yīng)能力、并行推理能力及聯(lián)想記憶能力和專家系統(tǒng)知識(shí)經(jīng)驗(yàn)的豐富性和權(quán)威性優(yōu)勢(shì),確保了故障檢測(cè)診斷的準(zhǔn)確、快速性。文中以機(jī)群中最重要的四種工況為實(shí)例對(duì)神經(jīng)網(wǎng)絡(luò)專家系統(tǒng)在故障檢測(cè)與診斷中的應(yīng)用進(jìn)行了驗(yàn)證。 最后,設(shè)計(jì)了基于塔機(jī)監(jiān)控儀和監(jiān)控中心計(jì)算機(jī)通過(guò)GPRS網(wǎng)絡(luò)構(gòu)成的塔機(jī)機(jī)群故障檢測(cè)與診斷系統(tǒng)。論文介紹了塔機(jī)監(jiān)控儀的硬件部分和軟件部分的設(shè)計(jì)原理,監(jiān)控儀以單片機(jī)為核心,通過(guò)GPRS方式實(shí)現(xiàn)遠(yuǎn)程數(shù)據(jù)通信。硬件采用了模塊化結(jié)構(gòu)設(shè)計(jì),包括輸入模塊、輸出模塊、報(bào)警模塊、液晶顯示模塊和數(shù)據(jù)存儲(chǔ)模塊。在監(jiān)控中心軟件部分,采用MATLAB編制了故障檢測(cè)與診斷程序,采用Visual Basic設(shè)計(jì)了數(shù)據(jù)庫(kù)處理和人機(jī)界面,編制MATLAB與VB的接口、VB與SQL的接口程序,實(shí)現(xiàn)了機(jī)群故障檢測(cè)與診斷。 論文的創(chuàng)新之處在于,將神經(jīng)網(wǎng)絡(luò)專家系統(tǒng)應(yīng)用于塔機(jī)機(jī)群故障檢測(cè)與診斷中;塔機(jī)監(jiān)控儀采用三個(gè)單片機(jī)協(xié)同工作的設(shè)計(jì)方案,增強(qiáng)了系統(tǒng)的實(shí)時(shí)性和可靠性。
[Abstract]:With the rapid development of economy and the expansion of urban construction scale, the important role of tower crane is becoming more and more prominent, and the cooperative operation of cluster is becoming more and more common. At the same time, tower crane accidents occur frequently with the expansion of fleet size, and even cause casualties. Therefore, in order to make the whole cluster run effectively, coordinate the work, reduce the economic losses and casualties caused by the accident, timely and accurately detect and diagnose the tower crane fault will have great economic benefits and academic research value. First of all, the tower cranes have huge working data. How to use these data to reflect the working status of tower cranes and make relevant personnel know the situation in time is the key to fault detection and diagnosis. In this paper, the fault characteristics of tower crane cluster are summarized by studying the work and detection principle of the tower crane, which lays a foundation for the research of the fault detection and diagnosis method of tower crane and the design of the system. Secondly, the fault detection and diagnosis method of tower crane based on neural network expert system is studied. This method combines the learning ability, adaptive ability, parallel reasoning ability, associative memory ability and expert system knowledge and authoritative advantages of neural network, and ensures the accuracy and rapidity of fault detection and diagnosis. In this paper, the application of neural network expert system in fault detection and diagnosis is verified by taking the four most important working conditions in the cluster as examples. Finally, the fault detection and diagnosis system of tower crane group is designed based on tower crane monitor and monitor center computer through GPRS network. This paper introduces the design principle of the hardware and software parts of the tower crane monitoring instrument. The monitoring instrument takes the single chip computer as the core and realizes the remote data communication through GPRS mode. The hardware adopts modular structure design, including input module, output module, alarm module, LCD module and data storage module. In the software part of the monitoring center, the program of fault detection and diagnosis is programmed by MATLAB, the database processing and man-machine interface are designed by Visual Basic, and the interface program between VB and MATLAB and SQL is compiled, which realizes the fault detection and diagnosis of cluster. The innovation of this paper is that the neural network expert system is applied to the fault detection and diagnosis of tower crane cluster, and the tower crane monitor adopts the design scheme of three single chip computers to work together, which enhances the real-time and reliability of the system.
【學(xué)位授予單位】：沈陽(yáng)理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH213.3;TP277

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 鄭尚龍,王國(guó)棟,李學(xué)忠,吳國(guó)祥,王福山,牛占文,王樹(shù)新;基于GSM/GPRS的工程機(jī)械機(jī)群狀態(tài)監(jiān)測(cè)與故障診斷系統(tǒng)(上)[J];工程機(jī)械;2003年08期

2 劉鋒,夏春先,黃振和;基于人工神經(jīng)網(wǎng)絡(luò)的故障診斷專家系統(tǒng)[J];國(guó)外電子測(cè)量技術(shù);2004年04期

3 許玲;程小琰;;C8051 F020單片機(jī)的特點(diǎn)及其在通信系統(tǒng)中的應(yīng)用[J];河南機(jī)電高等�？茖W(xué)校學(xué)報(bào);2006年06期

4 張毅,王紅,朱永波,楊占才;一個(gè)基于神經(jīng)網(wǎng)絡(luò)故障診斷專家系統(tǒng)研究[J];測(cè)控技術(shù);2004年11期

5 張紹兵;季厭浮;高志軍;;基于神經(jīng)網(wǎng)絡(luò)專家系統(tǒng)的研究與實(shí)現(xiàn)[J];計(jì)算機(jī)工程與科學(xué);2008年04期

6 常曉華;鄭夕健;費(fèi)燁;;基于RBF神經(jīng)網(wǎng)絡(luò)的塔式起重機(jī)安全狀態(tài)模式識(shí)別[J];建筑機(jī)械化;2005年11期

7 賈永峰,谷立臣;基于函數(shù)型連接神經(jīng)網(wǎng)絡(luò)的塔機(jī)起重力矩測(cè)量方法[J];建筑機(jī)械;2005年05期

8 王濤;羅文龍;姚金柯;;群塔監(jiān)控系統(tǒng)設(shè)計(jì)[J];建筑機(jī)械;2008年13期

9 呂鈞星,吳榮光,呂俊輝;塔吊防互撞系統(tǒng)[J];三峽大學(xué)學(xué)報(bào)(自然科學(xué)版);2002年02期

相關(guān)博士學(xué)位論文 前1條

1 李增芳;基于人工智能和虛擬儀器技術(shù)的發(fā)動(dòng)機(jī)故障診斷專家系統(tǒng)研究[D];浙江大學(xué);2004年

相關(guān)碩士學(xué)位論文 前10條

1 王中海;基于GPRS數(shù)據(jù)傳輸?shù)碾娞葸h(yuǎn)程故障診斷系統(tǒng)的研究[D];天津大學(xué);2004年

2 吳杰;塔式起重機(jī)智能監(jiān)控及故障診斷系統(tǒng)[D];鄭州大學(xué);2005年

3 李健;基于天津移動(dòng)GPRS網(wǎng)絡(luò)進(jìn)行無(wú)線數(shù)據(jù)傳輸?shù)男袠I(yè)應(yīng)用[D];天津大學(xué);2004年

4 李美華;神經(jīng)網(wǎng)絡(luò)專家系統(tǒng)在汽車(chē)故障診斷中的應(yīng)用研究[D];東北林業(yè)大學(xué);2006年

5 王文斌;坦克柴油機(jī)燃油供給系統(tǒng)故障診斷研究[D];西北工業(yè)大學(xué);2006年

6 李金剛;路面銑刨機(jī)狀態(tài)監(jiān)測(cè)與故障診斷系統(tǒng)研究[D];長(zhǎng)安大學(xué);2006年

7 李愛(ài)平;基于GPRS的遠(yuǎn)程燈光控制系統(tǒng)的研究與設(shè)計(jì)[D];武漢理工大學(xué);2007年

8 鄧日青;基于神經(jīng)網(wǎng)絡(luò)專家系統(tǒng)的電噴發(fā)動(dòng)機(jī)故障自診斷研究[D];重慶交通大學(xué);2008年

9 雷鵬;基于無(wú)線網(wǎng)絡(luò)的塔式起重機(jī)運(yùn)行狀態(tài)監(jiān)測(cè)系統(tǒng)的研究與設(shè)計(jì)[D];西安建筑科技大學(xué);2008年

10 徐麗莎;基于嵌入式旋轉(zhuǎn)機(jī)械遠(yuǎn)程故障信號(hào)檢測(cè)與故障診斷系統(tǒng)的研究[D];中南大學(xué);2009年

，

本文編號(hào)：2180271