本文關鍵詞： 流場分析 齒輪泵失效 最優(yōu)分數(shù)階 階次譜 故障決策　出處：《山東理工大學》2017年碩士論文　論文類型：學位論文

【摘要】：齒輪泵作為液壓系統(tǒng)的基礎元件,其工作狀況將直接影響整個液壓系統(tǒng)乃至設備的平穩(wěn)運行和可持續(xù)生產,故對齒輪泵故障機理及故障診斷研究具有重要意義。本文以齒輪泵為研究對象,綜合流體動力學、動力學、信號處理以及信息融合等多學科理論對齒輪泵輪齒的工作狀態(tài)進行分析,達到故障診斷和狀態(tài)分析的目的。具體研究內容如下:(1)綜合考慮齒輪泵內部流場與結構的特點,建立齒輪泵內部流場模型,通過內部流場參數(shù)特點分析流動特性,分析內部流場激勵條件下常見沖擊形式;研究齒輪泵輪齒結構特征,建立輪齒的動力學模型,在模態(tài)分析的基礎上對齒輪副固有頻率進行計算;結合流場模型和齒輪副動力學模型,對內部流場中常見的沖擊誘導產生的輪齒失效進行相關的仿真和數(shù)值計算研究,分析在激勵條件下齒輪齒面應力應變的分布,進一步對內部流場產生的激勵誘導輪齒的失效機理進行分析研究,得到齒輪副在內部流場中的失效形式和誘導因素。(2)將基于最優(yōu)分數(shù)階傅里葉變換的階次譜分析方法對齒輪泵啟動過程的非平穩(wěn)振動信號進行降噪和特征提取,并研究故障特征分量的特點。在利用分數(shù)階傅里葉變換對振動信號進行降噪的過程中,提出利用粒子群算法進行分數(shù)階階次尋優(yōu)的方法,與步長搜尋法相比,得到更加精確的數(shù)據(jù)結果,并大大減少階次尋找過程的計算量。在特征分量分數(shù)階域進行以能量聚集中心為濾波中心的帶通濾波處理,較好的改善信號的信噪比。針對齒輪泵啟動過程中的振動信號的非平穩(wěn)特征,選用階次譜分析對降噪后的信號進行分析,得到能夠準確反映齒輪泵工作狀態(tài)的特征信息。(3)針對齒輪泵故障決策過程中證據(jù)間沖突問題,對證據(jù)源中證據(jù)間的沖突程度問題進行改善,對證據(jù)間的沖突進行重新分配,并對證據(jù)模型進行相應的修正,解決證據(jù)間強烈沖突問題,保留證據(jù)中的有用信息。對齒輪泵的狀態(tài)信息特征進行決策研究,與經(jīng)典的證據(jù)理論的融合結果相對比,得到具有較高可信度的結論,為齒輪泵的故障診斷研究提供理論研究基礎。通過對齒輪泵的故障機理研究,使齒輪泵失效分析更加明確、全面;利用振動信號對齒輪泵的故障進行研究,達到齒輪泵故障診斷及狀態(tài)監(jiān)測的目的。通過試驗研究表明本文所提出的方法有效可行,與其他方法相比具有一定優(yōu)勢。
[Abstract]:Gear pump as the basic component of hydraulic system, its working condition will directly affect the smooth operation and sustainable production of the whole hydraulic system and even the equipment. Therefore, it is of great significance to study the fault mechanism and fault diagnosis of gear pump. In order to achieve the purpose of fault diagnosis and state analysis, the multi-disciplinary theories such as signal processing and information fusion are used to analyze the working state of gear pump teeth. The specific research contents are as follows: 1) considering the characteristics of internal flow field and structure of gear pump, Establish the internal flow field model of gear pump, analyze the flow characteristic through the characteristic of internal flow field parameter, analyze the common impact form under the internal flow field excitation condition, study the gear tooth structure characteristic of gear pump, establish the dynamics model of gear tooth. On the basis of modal analysis, the natural frequency of gear pair is calculated, combined with the flow field model and the gear pair dynamics model, the simulation and numerical calculation of the common impingement induced tooth failure in the internal flow field are carried out. The distribution of stress and strain on gear tooth surface under excitation condition is analyzed, and the failure mechanism of induced gear tooth induced by excitation in internal flow field is analyzed. The failure form and inductive factors of gear pair in internal flow field are obtained. The order spectrum analysis method based on optimal fractional Fourier transform is applied to de-noise and feature extraction of non-stationary vibration signal in gear pump starting process. In the process of using fractional Fourier transform to reduce the noise of vibration signal, a particle swarm optimization method for fractional order optimization is proposed, which is compared with step size search method. More accurate data results are obtained, and the computation of order finding process is greatly reduced. In the fractional order domain of characteristic components, a bandpass filter with the energy aggregation center as the filter center is carried out. Aiming at the non-stationary characteristic of vibration signal during gear pump start-up, the noise reduction signal is analyzed by order spectrum analysis. The characteristic information which can accurately reflect the working state of gear pump is obtained. Aiming at the conflict of evidence in the process of gear pump fault decision, the conflict degree of evidence in evidence source is improved, and the conflict between evidence is redistributed. The evidence model is modified to solve the problem of strong conflict between the evidence, and the useful information in the evidence is retained. The research on the characteristics of the gear pump's state information is compared with the fusion result of the classical evidence theory. A conclusion with high reliability is obtained, which provides a theoretical basis for the research of gear pump fault diagnosis. Through the research on the fault mechanism of gear pump, the failure analysis of gear pump is more clear and comprehensive. The fault diagnosis and condition monitoring of gear pump are achieved by using vibration signal. The experimental results show that the method proposed in this paper is effective and feasible and has some advantages compared with other methods.
【學位授予單位】：山東理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TH137.51

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