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二维联合模糊的液压系统故障诊断专家系统

DOI: 10.3969/j.issn.1674-0696.2012.06.31, PP. 1227-1231

Keywords: 小波分析,联合权重分配法,模糊故障诊断,专家系统,waveletanalysis,unitedweightingallocationmethod,fuzzyfaultdiagnosis,expertsystem

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Abstract:

:?提出了基于二维联合模糊评判的液压系统故障在线诊断方法;用MATLAB小波分析与模糊评判相结合的双重故障诊断模式,运用联合权重分配法构建故障诊断专家系统模糊矩阵;采用复杂样本方差估计,得出一个客观合理的故障征兆向量,实现了液压系统故障诊断的实时性,精确性;建立了起重机液压系统故障诊断专家系统。

References

[1]  [1] 张平格,杨志刚. 液压系统故障诊断专家系统研究[J]. 液压与气动, 2010( 5) : 22-23.
[2]  Zhang Pingge,Yang Zhigang. Research on expert system for faultdiagnoses of hydraulic system [J]. Chinese Hydraulics & Pneumatics,2010( 5) : 22-23.
[3]  [2] 赵懿冠,苏欣平. 基于故障树分析法的汽车起重机液压系统故障诊断研究[J]. 液压与气动,2010( 3) : 29-31.
[4]  Zhao Yiguan,Su Xinping. Research on hydraulic fault diagnosissystem of automobile crane based on fault tree analysis [J]. ChineseHydraulics & Pneumatics,2010( 3) : 29-31.
[5]  [3] 陈维,陈永革,赵强. 基于BP 神经网络的装备故障诊断专家系统研究[J]. 指挥控制与仿真,2008( 4) : 35-38.
[6]  Chen Wei,Chen Yongge,Zhao Qiang. Research on hydraulic faultdiagnosis system of equipment based on the BP neural network[J]. Command Control & Simulation,2008( 4) : 35-38.
[7]  [4] 李连峰. 基于RBF 网络的游梁抽油机减速箱轴承故障诊断[J]. 科技资讯,2010( 35) : 57-58.
[8]  Li Lianfeng. Fault diagnosis of the reducer bearing of a beampumper based on RBF network [J]. Science & Technology Information,2010 ( 35) : 57-58.
[9]  [11] Kong Z,Ceglarek D,Huang W. Multiple fault diagnosis method inmulti-station assembly processes using orthogonal diagonalization analysis[J]. ASME Transactions Journal of Manufacturing Scienceand Engineering,2008,130( 1) : 11-14.
[10]  [12] Wu J,Liu C. An expert system for fault diagnosis in internal combustionengines using wavelet packet transform and neural network[J]. Expert System with Applications,2010( 36) : 4278-4286.
[11]  [13] 杨纶标,高英仪. 模糊数学原理及应用[M]. 广州: 华南理工大学出版社, 2008.
[12]  [14] 穆瑞. 基于质量功能配置和欧氏范数的产品方案评价[J]. 同济大学学报: 自然科学版, 2011, 39( 1) : 147-148.
[13]  Mu Rui. Evaluating product scheme method based on QFD and Euclidnorm [J]. Journal of Tongji University: Natural Science,2011,39( 1) : 147-148.
[14]  [15] Du Shichang,Xi Lifeng. Fault diagnosis in assembly processesbased on engineering-driven rules and PSOSAEN algorithm [J].Computers & Industrial Engineering,2011( 60) : 77 – 88.
[15]  [16] 金勇进,谢佳斌. 复杂样本的方差估计———基于逆抽样设计的方法[J]. 数据,2009( 11) : 58-59.
[16]  Jin Yongjin,Xie Jiabin. Complex sample variance estimation basedon inverse sampling design method [J]. Academic World,2009( 11) : 58-59.
[17]  [17] Altab H,Ataur R. Power consumption prediction for an intelligentair-cushion track vehicle: Fuzzy Expert System[J]. Journal of Energyand Power Engineering,2010,4( 5) : 10-12.
[18]  [18] 李宁,郭化平,田铖,等. 参数测量法在装备液压系统故障诊断中的应用[J]. 机床与液压, 2009( 11) : 81-82.
[19]  Li Ning,Guo Huaping,Tian Cheng,et al. The application of parametermeasuring methods in the fault diagnosis of equipment hydraulicsystem [J]. Machine Tool & Hydraulics,2009( 11) : 81-82.
[20]  [5] Verron S,Tiplica T,Kobi A. Fault diagnosis of industrial systemsby conditional Gaussian network including a distance rejection criterion[J]. Engineering Applications of Artificial Intelligence,2010 ( 23) : 1229-1235.
[21]  [6] Chen Chinsheng,Chen Jianshiu. Rotor fault diagnosis system basedon SGA-based individual neural networks [J]. Expert Systems withApplications,2011( 38) : 10822-10830.
[22]  [7] Verron S,Tiplica T,Kobi A. Fault detection with Bayesian network[J]. Automation and Control,2008( b) : 341-356.
[23]  [8] Wu Jianda,Liu Chiuhong. An expert system for fault diagnosis ininternal combustion engines using wavelet packet transform andneural network [J]. Expert Systems with Applications,2009( 36) : 4278-4286.
[24]  [9] 王红君,刘冬生,岳有军. 基于小波分析和神经网络的电机故障诊断方法研究[J]. 电气传动,2010,40( 3) : 70-71.
[25]  Wang Hongjun,Liu Dongsheng,Yue Youjun. Study of the faultdiagnosis method based on Wavelet time and frequency analysis andthe neural network in the motor [J]. Electric Drive,2010,40( 3) : 70-71.
[26]  [10] Zeng L,Jin N,Zhou S. Multiple fault signature integration and enhancingfor variation source identification in manufacturing processes[J]. IIE Transactions,2008,40( 10) : 919-930.

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