發(fā)布時(shí)間：2018-02-16 03:55

  本文關(guān)鍵詞： 工程裝備 液壓系統(tǒng) 泄漏仿真 故障診斷 AMESim 支持向量機(jī)　出處：《國防科學(xué)技術(shù)大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：工程裝備是我軍武器裝備的重要組成部分，主要用以軍隊(duì)遂行工程保障任務(wù)，其工作穩(wěn)定性、戰(zhàn)場(chǎng)生存能力將直接關(guān)系到戰(zhàn)斗工程保障任務(wù)的順利完成乃至戰(zhàn)爭(zhēng)的成敗。液壓傳動(dòng)廣泛應(yīng)用于我軍現(xiàn)役工程裝備的動(dòng)力傳遞中，而液壓泄漏一直是工程裝備技術(shù)保障的難題之一。開展液壓系統(tǒng)泄漏故障診斷和防泄漏技術(shù)研究，探尋有效降低工程裝備液壓泄漏故障的途徑和方法，對(duì)提高工程裝備保障能力具有重要的理論指導(dǎo)意義和軍事應(yīng)用價(jià)值。 本文針對(duì)液壓系統(tǒng)泄漏故障診斷手段單一、故障樣本難以獲取等問題，以典型工程裝備某重型機(jī)械化橋?yàn)檠芯繉?duì)象，采用面向?qū)ο蠼７抡婧椭С窒蛄繖C(jī)故障診斷方法，對(duì)其工作裝置液壓系統(tǒng)進(jìn)行了建模仿真和液壓泄漏故障診斷，，有效提高了小樣本事件故障診斷的準(zhǔn)確率，為液壓系統(tǒng)泄漏故障診斷提供了一種新的智能診斷方法。論文主要研究工作及成果如下： （1）系統(tǒng)概括了液壓系統(tǒng)泄漏故障診斷的研究現(xiàn)狀，對(duì)引起泄漏的原因和泄漏故障機(jī)理進(jìn)行了詳細(xì)分析，將外泄漏和內(nèi)泄漏分別等效為孔口出流和縫隙流動(dòng)，分析得到油液黏度和縫隙高度等因素對(duì)泄漏量有較大影響，提出了液壓泄漏故障診斷策略。 （2）根據(jù)上述制定的泄漏故障診斷策略，運(yùn)用液壓機(jī)械系統(tǒng)建模仿真軟件AMESim建立了某重型機(jī)械化橋首跨架設(shè)液壓系統(tǒng)工作回路模型，引入頂推液壓缸工作回路泄漏和鎖緊液壓缸內(nèi)泄漏等泄漏故障進(jìn)行仿真分析，得到不同泄漏情況下的故障特征，為泄漏故障診斷和預(yù)防提供了理論依據(jù)。 （3）從泄漏故障仿真中提取壓力、流量等特征參數(shù)，導(dǎo)入Matlab求取時(shí)域特征值，作為支持向量機(jī)進(jìn)行泄漏故障診斷的數(shù)據(jù)樣本，運(yùn)用SVM模式識(shí)別軟件包LibSVM訓(xùn)練所得模型準(zhǔn)確診斷出了泄漏故障發(fā)生的部位和引起泄漏的原因，從而驗(yàn)證了本文將泄漏故障建模仿真與支持向量機(jī)故障診斷相結(jié)合的方法的可行性和有效性。 （4）從控制液壓油黏度、控制液壓系統(tǒng)縫隙高度和液壓管路的正確裝配等環(huán)節(jié)對(duì)如何做好液壓系統(tǒng)防泄漏工作進(jìn)行了分析研究，提出了預(yù)防泄漏故障的對(duì)策和方法。
[Abstract]:Engineering equipment is an important part of our army's weapons and equipment. It is mainly used for the military to carry out engineering support tasks and its work stability. Battlefield survivability will be directly related to the successful completion of combat engineering support tasks and even the success or failure of war. Hydraulic transmission is widely used in the power transmission of our active engineering equipment. Hydraulic leakage has always been one of the difficult problems in the technical support of engineering equipment. The research on hydraulic system leakage fault diagnosis and leakage prevention technology is carried out to explore the ways and methods to effectively reduce the hydraulic leakage failure of engineering equipment. It has important theoretical guiding significance and military application value to improve the engineering equipment support ability. Aiming at the problems of single method of hydraulic system leakage fault diagnosis and difficulty in obtaining fault samples, this paper takes a heavy mechanized bridge of typical engineering equipment as research object, adopts object-oriented modeling and simulation and support vector machine fault diagnosis method. The hydraulic system of its working device is modeled and simulated and the fault diagnosis of hydraulic leakage is carried out, which effectively improves the accuracy of fault diagnosis for small sample events. This paper provides a new intelligent diagnosis method for hydraulic system leakage fault diagnosis. The main research work and results are as follows:. 1) the present situation of hydraulic system leakage fault diagnosis is summarized. The causes of leakage and the mechanism of leakage fault are analyzed in detail. The external leakage and internal leakage are equivalent to orifice outlet flow and slot flow, respectively. Based on the analysis of oil viscosity and gap height, the leakage rate is greatly affected, and the fault diagnosis strategy of hydraulic leakage is put forward. 2) according to the leak fault diagnosis strategy, a hydraulic system working loop model of a heavy-duty mechanized bridge is established by using the hydraulic mechanical system modeling and simulation software AMESim. The leakage faults such as the leakage in the working loop of the thrust cylinder and the leakage in the lock hydraulic cylinder are simulated and analyzed, and the fault characteristics under different leakage conditions are obtained, which provides a theoretical basis for the diagnosis and prevention of the leakage fault. (3) extracting characteristic parameters such as pressure and flow rate from leakage fault simulation, and importing Matlab to obtain time domain eigenvalue, which can be used as data sample for leak fault diagnosis by support vector machine (SVM). By using the LibSVM training model of SVM pattern recognition software package, the location of leakage fault and the cause of leakage are accurately diagnosed. Thus, the feasibility and effectiveness of the method combining leakage fault modeling and simulation with support vector machine fault diagnosis are verified in this paper. 4) from the aspects of controlling the viscosity of hydraulic oil, controlling the height of hydraulic system crevice and the correct assembly of hydraulic pipeline, this paper analyzes and studies how to prevent the leakage of hydraulic system, and puts forward the countermeasures and methods to prevent leakage fault.
【學(xué)位授予單位】：國防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TH137

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