本文選題：液壓泵 + 故障診斷��； 參考：《燕山大學(xué)》2011年碩士論文

【摘要】：液壓系統(tǒng)以其功率大、響應(yīng)快等優(yōu)點(diǎn)在工程領(lǐng)域中得到了廣泛應(yīng)用,它在許多設(shè)備中起著核心控制或傳動(dòng)作用。液壓泵是液壓系統(tǒng)的“心臟”,對(duì)液壓泵的狀態(tài)監(jiān)測(cè)和故障診斷成為保證液壓系統(tǒng)正常運(yùn)行的關(guān)鍵。 現(xiàn)實(shí)中由于液壓泵故障檢測(cè)手段的不完善性、信號(hào)獲取裝置的不穩(wěn)定性,或者缺少有效的觀測(cè)工具,造成檢測(cè)到得信息不完全。本文將灰靶理論分析方法用于液壓系統(tǒng)故障診斷,利用存在的已知信息去推知含有故障模式的不可知信息的特性、狀態(tài)和發(fā)展趨勢(shì),并對(duì)液壓系統(tǒng)未來(lái)的發(fā)展做出預(yù)測(cè)和決策。 本文利用LabVIEW編制了液壓泵數(shù)據(jù)采集系統(tǒng),并驅(qū)動(dòng)NI數(shù)據(jù)采集卡,實(shí)現(xiàn)了液壓泵信號(hào)采集。借助于MATLAB小波工具編制程序,對(duì)振動(dòng)信號(hào)進(jìn)行小波包分解重構(gòu),有效去除信號(hào)中的高頻噪聲。 研究了主分量分析方法,將互相影響的液壓泵復(fù)合故障信息,經(jīng)過(guò)一系列變換后,在保留原始信號(hào)足夠多信息量的同時(shí),使各種故障相互獨(dú)立,為進(jìn)一步確定故障類(lèi)型奠定了基礎(chǔ)。 對(duì)比最大熵譜估計(jì)和經(jīng)典功率譜估計(jì),將最大熵譜估計(jì)用于液壓泵復(fù)合振動(dòng)信號(hào)分析,在樣本數(shù)據(jù)少的情況下,取得相對(duì)準(zhǔn)確的時(shí)頻信息。分析過(guò)程中沒(méi)有固定的窗函數(shù),因此可以避免傳統(tǒng)譜分析中加窗函數(shù)的能量泄漏問(wèn)題。借助MATLAB軟件編制程序,提取液壓泵松靴故障信號(hào)特征,得到故障特征頻率。 研究了灰色理論中的灰靶理論分析方法,確定信號(hào)幅值域特征為特征向量,對(duì)不同嚴(yán)重程度的液壓泵松靴滑靴磨損復(fù)合故障進(jìn)行分析,建立標(biāo)準(zhǔn)模式和故障模式,通過(guò)靶心度計(jì)算確定評(píng)估等級(jí)。
[Abstract]:Hydraulic system is widely used in engineering field because of its high power and fast response. It plays a core control or drive role in many equipments. Hydraulic pump is the "heart" of hydraulic system. The condition monitoring and fault diagnosis of hydraulic pump become the key to ensure the normal operation of hydraulic system. In reality, because of the imperfection of the fault detection method of hydraulic pump, the instability of signal acquisition device, or the lack of effective observation tools, the detected information is not complete. In this paper, the grey target theory analysis method is applied to the fault diagnosis of hydraulic system. The characteristics, status and development trend of unknowable information containing fault mode are deduced by using the known information, and the future development of hydraulic system is predicted and decided. In this paper, the hydraulic pump data acquisition system is programmed by using LabVIEW, and the NI data acquisition card is driven to realize the hydraulic pump signal acquisition. With the help of MATLAB wavelet tool, the wavelet packet decomposition and reconstruction of vibration signal are carried out, and the high frequency noise in the signal is effectively removed. In this paper, the principal component analysis (PCA) method is studied. After a series of transformations, all kinds of faults are independent of each other while retaining enough information of the original signal. It lays a foundation for further determining the fault type. Compared with the maximum entropy spectrum estimation and the classical power spectrum estimation, the maximum entropy spectrum estimation is applied to the analysis of the hydraulic pump compound vibration signal, and relatively accurate time-frequency information is obtained under the condition of less sample data. There is no fixed window function in the analysis process, so the energy leakage problem of windowed function in traditional spectral analysis can be avoided. With the help of MATLAB software, the fault signal features of hydraulic pump loose boots are extracted and the fault characteristic frequency is obtained. The grey target theory analysis method in grey theory is studied. The characteristic of signal amplitude range is determined as the characteristic vector. The wear and tear composite faults of hydraulic pump loose boots with different degrees of severity are analyzed, and the standard mode and fault mode are established. The evaluation grade is determined by the calculation of the target center.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類(lèi)號(hào)】：TH137.5

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