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基于小波能量熵和鄰域粗糙集的電磁閥故障診斷研究
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中國民航大學(xué)電子信息與自動(dòng)化學(xué)院

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TP277.3

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國家自然科學(xué)基金(62173331)


Research on Fault Diagnosis of Solenoid Valve Based on Wavelet Energy Entropy and Neighborhood Rough Set
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    摘要:

    液體電磁閥是航空變量柱塞泵系統的關(guān)鍵控制元件,準確診斷電磁閥的故障類(lèi)型是系統安全運行的重要保證;為了對航空變量柱塞泵系統中電磁閥進(jìn)行檢測與診斷,提出了一種基于小波能量熵和鄰域粗糙集相結合的方法;研究了液體電磁閥驅動(dòng)端的電流故障特征;采用AMEsim多學(xué)科領(lǐng)域仿真軟件建立仿真模型,分析驅動(dòng)端電流與閥體位移的關(guān)系,搭建實(shí)驗系統,采集正常狀態(tài)和故障狀態(tài)的電流信號,分析不同狀態(tài)的電流特性;然后利用小波包分解重構信號,提取對應的頻帶能量作為特征向量;最后,引入變精度模糊鄰域粗集約簡(jiǎn)算法簡(jiǎn)化數值屬性,提高了系統的效率;簡(jiǎn)化的屬性集用于構建決策樹(shù),經(jīng)過(guò)迭代訓練,該模型診斷準確率達90%,達到了預期效果,實(shí)現了對液體電磁閥的快速診斷。

    Abstract:

    The liquid solenoid valve is the key control component of the variable displacement piston pump system in aviation. Accurate diagnosis of the fault type of the solenoid valve is an important guarantee for the safe operation of the system; In order to detect and diagnose the solenoid valve in the aviation variable displacement piston pump system, a method based on wavelet energy entropy and neighborhood rough set is proposed; The current fault characteristics of liquid solenoid valve driver are studied; The AMEsim multidisciplinary simulation software is used to establish the simulation model, analyze the relationship between the drive end current and the valve body displacement, build an experimental system, collect the current signals in normal and fault states, and analyze the current characteristics in different states; Then the wavelet packet decomposition is used to reconstruct the signal, and the corresponding band energy is extracted as the feature vector; Finally, variable precision fuzzy neighborhood rough set reduction algorithm is introduced to simplify the numerical attributes, which improves the efficiency of the system; The simplified attribute set is used to build the decision tree. After iterative training, the diagnostic accuracy of the model reaches 90%, achieving the desired effect, and realizing the rapid diagnosis of the liquid solenoid valve.

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詹湘琳,劉洪越,荊濤.基于小波能量熵和鄰域粗糙集的電磁閥故障診斷研究計算機測量與控制[J].,2023,31(10):13-20.

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歷史
  • 收稿日期:2022-10-30
  • 最后修改日期:2022-12-02
  • 錄用日期:2022-12-05
  • 在線(xiàn)發(fā)布日期: 2023-10-26
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