發(fā)布時(shí)間：2018-04-24 23:24

  本文選題：異步電動(dòng)機(jī) + 故障診斷�。� 參考：《曲阜師范大學(xué)》2016年碩士論文

【摘要】：電動(dòng)機(jī)作為一種可以將電能轉(zhuǎn)化為機(jī)械能的裝置,在工業(yè)生產(chǎn)中有著舉足輕重的地位,特別是異步電動(dòng)機(jī)作為工業(yè)生產(chǎn)中最主要的原動(dòng)力和驅(qū)動(dòng)裝置,其重要性是毋庸置疑的。在煤礦、能源、化工等工業(yè)領(lǐng)域當(dāng)中,大型異步電機(jī)更是其核心設(shè)備,一旦異步電機(jī)出現(xiàn)故障,整個(gè)工業(yè)運(yùn)行系統(tǒng)可能會(huì)面臨全面癱瘓的風(fēng)險(xiǎn),造成不可預(yù)料的經(jīng)濟(jì)損失,甚至危及現(xiàn)場(chǎng)工作人員的生命安全。因此異步電動(dòng)機(jī)的故障檢測(cè)及故障診斷具有重要的研究意義。本文針對(duì)異步電動(dòng)機(jī)的狀態(tài)監(jiān)測(cè),以PT100、電流互感器、電壓互感器、加速度傳感器及研華PCI1711等為硬件基礎(chǔ),應(yīng)用LabVIEW與MATLAB混合編程、C語(yǔ)言編程,開(kāi)發(fā)出異步電機(jī)實(shí)時(shí)狀態(tài)監(jiān)測(cè)與故障診斷專家系統(tǒng)。系統(tǒng)的數(shù)據(jù)采集功能主要由現(xiàn)場(chǎng)傳感器及研華數(shù)據(jù)采集卡PCI1711完成,PCI1711是基于PCI總線的高速多功能數(shù)據(jù)采集卡,可以實(shí)現(xiàn)對(duì)數(shù)字量、模擬量輸入輸出的控制。信號(hào)通過(guò)數(shù)據(jù)采集系統(tǒng)在上位機(jī)LabVIEW開(kāi)發(fā)的信號(hào)分析系統(tǒng)中進(jìn)行分析與處理。信號(hào)分析系統(tǒng)利用異步電機(jī)的轉(zhuǎn)子繞組與定子繞組的感應(yīng)關(guān)系,通過(guò)Park變換法對(duì)異步電機(jī)的三相定子電流進(jìn)行數(shù)據(jù)處理,得到定子電流Park變換圖,并通過(guò)MATLAB編程提取出故障的特征信號(hào)。同時(shí),針對(duì)轉(zhuǎn)子故障信號(hào)微弱時(shí)Park變換圖不明顯的弱點(diǎn),使用最優(yōu)抵消法對(duì)定子電流作去噪處理,然后進(jìn)行頻譜分析,提取故障頻譜的特征信號(hào),得到定子電流頻譜圖進(jìn)行輔助判斷。對(duì)于振動(dòng)信號(hào),利用虛擬濾波器進(jìn)行了濾波處理,然后借助MATLAB進(jìn)行Hilbert變換,并對(duì)其做包絡(luò)分析,得到相應(yīng)的波形圖,提取包絡(luò)圖中的故障特征信號(hào)。信號(hào)分析系統(tǒng)提取的故障特征信號(hào)的數(shù)據(jù)存放在系統(tǒng)數(shù)據(jù)庫(kù)中,通過(guò)故障診斷專家系統(tǒng)與知識(shí)庫(kù)中的規(guī)則進(jìn)行比較,最終確定故障結(jié)果。專家系統(tǒng)數(shù)據(jù)庫(kù)使用Access軟件進(jìn)行開(kāi)發(fā),通過(guò)故障樹(shù)分析建立知識(shí)庫(kù),最終由C語(yǔ)言編程完成專家系統(tǒng)的設(shè)計(jì),通過(guò)LabVIEW的CIN(Code Interface Node)功能節(jié)點(diǎn)來(lái)實(shí)現(xiàn)對(duì)專家系統(tǒng)的調(diào)用。本課題設(shè)計(jì)的異步電機(jī)智能故障診斷系統(tǒng)經(jīng)過(guò)兗礦集團(tuán)鮑店煤礦儲(chǔ)運(yùn)車間測(cè)試證明,具有良好的實(shí)時(shí)數(shù)據(jù)監(jiān)測(cè)和準(zhǔn)確的故障診斷能力。設(shè)計(jì)達(dá)到了預(yù)期的目標(biāo),對(duì)煤炭倉(cāng)儲(chǔ)車間的生產(chǎn)安全和優(yōu)化管理起到了重要的實(shí)際意義。
[Abstract]:As a kind of device which can convert electric energy into mechanical energy, motor plays an important role in industrial production, especially asynchronous motor as the main driving force and driving device in industrial production, its importance is beyond doubt. In the coal mine, energy, chemical and other industrial fields, large asynchronous motors are the core equipment. Once the asynchronous motors fail, the entire industrial operation system may face the risk of total paralysis, resulting in unpredictable economic losses. It even endangers the safety of the workers on the spot. Therefore, the fault detection and fault diagnosis of asynchronous motor is of great significance. Based on the hardware of PT100, current transformer, voltage transformer, acceleration sensor and PCI1711, this paper uses LabVIEW and MATLAB to program in C language for the condition monitoring of asynchronous motor. A real-time condition monitoring and fault diagnosis expert system for asynchronous motor is developed. PCI1711 is a high speed multifunction data acquisition card based on PCI bus, which can control the input and output of digital quantity and analog quantity. The signal is analyzed and processed by the data acquisition system in the signal analysis system developed by LabVIEW. The signal analysis system makes use of the induction relation between rotor winding and stator winding of asynchronous motor, and processes the three-phase stator current of asynchronous motor by Park transform method, and obtains the Park transform diagram of stator current. The characteristic signal of fault is extracted by MATLAB programming. At the same time, aiming at the weakness of the Park transform diagram when the rotor fault signal is weak, the stator current is de-noised by the optimal cancellation method, and then the spectrum analysis is carried out to extract the characteristic signal of the fault spectrum. The stator current spectrum diagram is obtained for auxiliary judgment. For the vibration signal, the virtual filter is used to filter the signal, and then the Hilbert transform is carried out with the help of MATLAB, and the corresponding waveform is obtained by the envelope analysis, and the fault characteristic signal is extracted from the envelope diagram. The data of fault feature signals extracted by signal analysis system are stored in the database of the system. The fault results are determined by comparing the fault diagnosis expert system with the rules in the knowledge base. The database of expert system is developed with Access software, and the knowledge base is established by fault tree analysis. Finally, the design of expert system is accomplished by C language programming, and the expert system is called by CIN(Code Interface Node of LabVIEW. The intelligent fault diagnosis system of asynchronous motor designed in this paper is proved to have good real-time data monitoring and accurate fault diagnosis ability by testing the storage and transportation workshop of Baodian Coal Mine of Yankuang Group. The design achieves the expected goal and plays an important practical significance to the production safety and optimization management of the coal storage workshop.
【學(xué)位授予單位】：曲阜師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TM343

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