發(fā)布時間：2018-01-02 04:37

  本文關(guān)鍵詞：基于灰色神經(jīng)網(wǎng)絡(luò)的液壓泵故障診斷研究　出處：《燕山大學(xué)》2011年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 故障診斷 軸向柱塞泵 灰色神經(jīng)網(wǎng)絡(luò) 灰色關(guān)聯(lián)度 Hilbert變換

【摘要】：隨著液壓技術(shù)的不斷發(fā)展,液壓系統(tǒng)在各種領(lǐng)域使用的頻率不斷增加,其功能也不斷的增多,結(jié)構(gòu)越來越復(fù)雜,相應(yīng)的也增加了液壓系統(tǒng)出現(xiàn)故障的可能性。液壓泵屬于連續(xù)工作元件,其結(jié)構(gòu)比較復(fù)雜,容易發(fā)生故障,在近年的研究中,液壓泵的故障診斷越來越受到人們的重視,隨著新技術(shù)的出現(xiàn),液壓泵的故障診斷技術(shù)朝著自動化,智能化的方向發(fā)展,應(yīng)用此類方法對液壓泵進(jìn)行有效地故障診斷是目前的研究熱點(diǎn)。本文提出一種將神經(jīng)網(wǎng)絡(luò)理論和灰色理論結(jié)合的方法對泵的故障進(jìn)行診斷。 神經(jīng)網(wǎng)絡(luò)和灰色理論都是在故障診斷領(lǐng)域應(yīng)用比較成熟的理論方法,將兩種理論結(jié)合進(jìn)行的研究也越來越多。本文將神經(jīng)網(wǎng)絡(luò)理論和灰色理論中的灰色關(guān)聯(lián)度理論進(jìn)行結(jié)合,應(yīng)用Matlab軟件的神經(jīng)網(wǎng)絡(luò)工具箱設(shè)計(jì)了一個自定義的灰色神經(jīng)網(wǎng)絡(luò)模型,對該網(wǎng)絡(luò)的傳輸函數(shù)等屬性進(jìn)行自定義,使得該網(wǎng)絡(luò)模型能夠?qū)崿F(xiàn)液壓泵的未知故障模式和已知故障模式之間的灰色關(guān)聯(lián)度并行計(jì)算,并且可以由網(wǎng)絡(luò)計(jì)算結(jié)果判斷出未知故障模式的故障類型,直接將診斷結(jié)果進(jìn)行輸出。 本文基于材料試驗(yàn)機(jī)的液壓油源系統(tǒng),以軸向柱塞泵為對象,進(jìn)行狀態(tài)監(jiān)測并對泵在多種工作狀態(tài)下端蓋部位的振動加速度信號進(jìn)行采集,應(yīng)用小波理論和Hilbert變換方法對信號進(jìn)行處理,提取幅值域和時頻域的特征向量,以特征向量作為灰色神經(jīng)網(wǎng)絡(luò)模型的輸入,對此類泵的幾種典型故障進(jìn)行診斷,并通過Matlab軟件進(jìn)行仿真,證明了灰色神經(jīng)網(wǎng)絡(luò)故障診斷新方法的有效性。
[Abstract]:With the development of hydraulic technology, the frequency of hydraulic system in various fields is increasing, its function is increasing, and the structure is becoming more and more complex. It also increases the possibility of hydraulic system failure. Hydraulic pump is a continuous working component, its structure is more complex, prone to failure, in recent years in the study. People pay more and more attention to the fault diagnosis of hydraulic pump. With the emergence of new technology, the fault diagnosis technology of hydraulic pump is developing towards the direction of automation and intelligence. The application of this method to the effective fault diagnosis of hydraulic pumps is a hot topic at present. In this paper, a method combining neural network theory with grey theory is proposed to diagnose the faults of hydraulic pumps. Neural network and grey theory are mature theory methods in the field of fault diagnosis. There are more and more researches on the combination of the two theories. In this paper, we combine the neural network theory with the grey relational degree theory. A self-defined grey neural network model is designed by using the neural network toolbox of Matlab software, and the transmission function and other attributes of the network are customized. The network model can realize the parallel calculation of grey correlation degree between unknown fault mode and known fault mode of hydraulic pump, and can judge the fault type of unknown fault mode from the result of network calculation. The diagnosis results are directly outputted. In this paper, based on the hydraulic oil source system of the material testing machine, the axial piston pump is taken as the object to monitor the state and collect the vibration acceleration signal of the end cover of the pump in various working conditions. Wavelet theory and Hilbert transform are used to process the signal and extract the eigenvector of amplitude range and time-frequency domain. The eigenvector is used as the input of the grey neural network model. Several typical faults of this kind of pump are diagnosed and simulated by Matlab software, which proves the validity of the new method of fault diagnosis based on grey neural network.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2011
【分類號】：TH165.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 馬曉建,陳瑞琪,吳文英,周保堂,賀世正;機(jī)械故障診斷中常用解調(diào)方法的比較及應(yīng)用[J];東華大學(xué)學(xué)報(自然科學(xué)版);2001年05期

2 張雄希;劉振興;;共振解調(diào)與小波降噪在電機(jī)故障診斷中的應(yīng)用[J];電機(jī)與控制學(xué)報;2010年06期

3 羅躍綱,陳長征;旋轉(zhuǎn)機(jī)械故障的灰色網(wǎng)絡(luò)診斷分析[J];風(fēng)機(jī)技術(shù);2001年04期

4 焦衛(wèi)東;朱有劍;;基于小波變換的滾動軸承故障信號包絡(luò)譜分析[J];蘭州理工大學(xué)學(xué)報;2008年06期

5 趙洋;;有關(guān)液壓系統(tǒng)的故障分析與診斷的研究[J];河南科技;2010年12期

6 張琦,邵立福;基于Elman神經(jīng)網(wǎng)絡(luò)的液壓泵故障診斷模型研究[J];機(jī)床與液壓;2004年10期

7 張力;項(xiàng)輝宇;趙罘;袁柳櫻;;斜盤式軸向柱塞泵摩擦副分析[J];機(jī)床與液壓;2007年06期

8 竺瑩;童，

本文編號：1367741