基于贝叶斯网络的水电机组振动故障诊断研究
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摘要
水电站的状态监测系统积累了大量的监测数据,但由于现场专家缺乏,目前这些数据没有得到很好的利用,如何挖掘这些数据并结合专家经验对水电机组进行故障诊断是本文研究的重点。本文提出了一种基于贝叶斯网络的水电机组振动故障诊断模型。根据专家经验获得贝叶斯网络结构和部分节点参数,通过SOM神经网络对数据信号进行离散化处理,利用EM算法参数学习获得其他节点的概率分布,搭建基于贝叶斯网络的子系统模型,并将子系统模型整合成完整的系统模型。文章最后通过设计试验,验证了所建模型诊断结果的正确性和合理性。
A huge mass of on-site monitor data of hydropower stations has accumulated, but its practical use is quite limited due to lack of on-site experts. How to mine these data and combine with expert experiences in fault diagnosis is our focus. This paper describes a vibration fault diagnosis model for hydropower units based on a Bayesian network that integrates subsystem models constructed through formulating the network structure and certain node parameters using expert experiences, discretizing data signals with a self-organizing map(SOM) neural network, and determining the probability distribution of the rest of the nodes via learning parameters of the expectation-maximization(EM) algorithm. This model is verified by examining the effect and rationality of its diagnosis results in design tests.
A huge mass of on-site monitor data of hydropower stations has accumulated, but its practical use is quite limited due to lack of on-site experts. How to mine these data and combine with expert experiences in fault diagnosis is our focus. This paper describes a vibration fault diagnosis model for hydropower units based on a Bayesian network that integrates subsystem models constructed through formulating the network structure and certain node parameters using expert experiences, discretizing data signals with a self-organizing map(SOM) neural network, and determining the probability distribution of the rest of the nodes via learning parameters of the expectation-maximization(EM) algorithm. This model is verified by examining the effect and rationality of its diagnosis results in design tests.
引文
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[8]WONG M L,LEE S Y,LEUNG K S.Data mining of Bayesian networks using cooperative coevolution[J].Decision Support Sysems,2004,38(3):451-459.
[9]宋辉,李昌平,蔡忠春,等.基于贝叶斯网络的故障诊断与维修决策研究[J].航空维修与工程,2011(1):32-34.SONG Hui,LI Changping,CAI Zhongchun,et al.Fault diagnosis and maintenance decision based on bayesian network[J].Aviation Maintenance&Engineering,2011(1):32-34.(in Chinese)
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[12]曹惠玲,杜鹏.基于贝叶斯网络的航空发动机燃油泵故障诊断[J].天津:中国民航大学学报,2016,34(4):27-30.CAO Huiling,DU Peng.Failure diagnosis of aero-engine fuel pump assembly based on Bayesian network[J].Journal of Civil Aviation University of China,2016,34(4):27-30.(in Chinese)
[13]王占伟,王林,梁坤峰,等.基于融合的贝叶斯网络的冷水机组故障诊断[J].化工学报,2018,69(7):3167-3173.WANG Zhanwei,WANG Lin,LIANG Kunfeng,et al.Chiller fault diagnosis based on fusional Bayesian network[J].CIESC Journal,2018,69(7):3167-3173.(in Chinese)
[14]王双成.贝叶斯网络学习、推理与应用[M].上海:立信会计出版社,2010.WANG Shuangcheng.Bayesian network learning,reasoning and application[M].Shanghai:Lixin Accounting Press,2010.(in Chinese)
[15]PEARL B J.Probabilistic reasoning in intelligent systems:Network of plausible inference[M].San Francisco:Morgan Kaufmann Publishers,Inc,1988.
[16]OLESEN K G,LAURITZEN S L,JENSEN F V.aHUGIN:a system creating adaptive causal probabilistic networks[C]//UAI'92:Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence,Stanford University,Stanford,Ca,Usa,July.DBLP,1992:223-229.
[17]SPIEGELHALTER D J,DAWID A P,LAURITZEN SL,et al.Bayesian analysis in expert systems[J].Statistical Science,1993,8(3):219-247.
[18]LIAO W,JI Q.Learning Bayesian network parameters under incomplete data with domain knowledge[J].Pattern Recognition,2009,42(11):3046-3056.
[19]ABBASZADEH S,GORDJI M E,PAP E,et al.Jensen-type inequalities for Sugeno integral[J].Information Sciences,2017,376:148-157.
[20]杨优军.基于水电机组状态监测的水电厂机电设备运行管理[D].北京:清华大学,2013.YANG Youjun.Operation and maintenance of mechanical and electrical equipments based on condition monitoring of hydropower units[D].Beijing:Tsinghua University,2013.(in Chinese)
[2]LU N,XIAO Z H,MALIK O P.Feature extraction using adaptive multiwavelets and synthetic detection index for rotor fault diagnosis of rotating machinery[J].Mechanical Systems and Signal Processing,2015,52/53:393-415.
[3]宋媛,彭利鸿,赖冠文,等.基于小波包和样本熵的水泵机组振动特征提取[J].中国农村水利水电,2017(3):146-152.SONG Yuan,PENG Lihong,LAI Guanwen,et al.Vibration feature extraction of pump unit based on wavelet packet and sample entropy[J].China Rural Water and Hydropower,2017(3):146-152.(in Chinese)
[4]毛成,刘洪文,李小军,等.基于知识库的水电机组故障诊断专家系统[J].华电技术,2015,37(9):25-28.MAO Cheng,LIU Hongwen,LI Xiaojun,et al.Expert system for fault diagnosis of hydropower unit based on knowledge base[J].Huadian Technology,2015,37(9):25-28.(in Chinese)
[5]刘长良,武英杰,甄成刚.基于变分模态分解和模糊C均值聚类的滚动轴承故障诊断[J].中国电机工程学报,2015,35(13):3358-3365.LIU Changliang,WU Yingjie,ZHEN Chenggang.Rolling bearing fault diagnosis based on variational mode decomposition and fuzzy C means clustering[J].Proceedings of the CSEE,2015,35(13):3358-3365.(in Chinese)
[6]李辉,王毅,杨晓萍,等.基于多小波和PSO-RBF神经网络的水电机组振动故障诊断[J].西北农林科技大学学报(自然科学版),2017,45(2):227-234.LI Hui,WANG Yi,YANG Xiaoping,et al.Vibration fault diagnosis for hydropower generating unit based on multiwavelet and PSO-RBF neural network[J].Journal of Northwest A&F University(Natural Science Edition),2017,45(2):227-234.(in Chinese)
[7]付文龙,周建中,李超顺,等.基于模糊K近邻支持向量数据描述的水电机组振动故障诊断研究[J].中国电机工程学报,2014,34(32):5788-5795.FU Wenlong,ZHOU Jianzhong,LI Chaoshun,et al.Vibrant fault diagnosis for hydro-electric generating unit based on support vector data description improved with fuzzy K nearest neighbor[J].Proceedings of the CSEE,2014,34(32):5788-5795.(in Chinese)
[8]WONG M L,LEE S Y,LEUNG K S.Data mining of Bayesian networks using cooperative coevolution[J].Decision Support Sysems,2004,38(3):451-459.
[9]宋辉,李昌平,蔡忠春,等.基于贝叶斯网络的故障诊断与维修决策研究[J].航空维修与工程,2011(1):32-34.SONG Hui,LI Changping,CAI Zhongchun,et al.Fault diagnosis and maintenance decision based on bayesian network[J].Aviation Maintenance&Engineering,2011(1):32-34.(in Chinese)
[10]NILSSON N J.Artificial intelligence:A new synthesis[M].Morgan Kaufmann Publishers Inc,1998.
[11]赵月南.基于贝叶斯网络的电机故障诊断研究[D].杭州:浙江大学,2016.ZHAO Yuenan.The research of motor fault detection based on Bayesian Network[D].Hangzhou:Zhejiang University,2016.(in Chinese)
[12]曹惠玲,杜鹏.基于贝叶斯网络的航空发动机燃油泵故障诊断[J].天津:中国民航大学学报,2016,34(4):27-30.CAO Huiling,DU Peng.Failure diagnosis of aero-engine fuel pump assembly based on Bayesian network[J].Journal of Civil Aviation University of China,2016,34(4):27-30.(in Chinese)
[13]王占伟,王林,梁坤峰,等.基于融合的贝叶斯网络的冷水机组故障诊断[J].化工学报,2018,69(7):3167-3173.WANG Zhanwei,WANG Lin,LIANG Kunfeng,et al.Chiller fault diagnosis based on fusional Bayesian network[J].CIESC Journal,2018,69(7):3167-3173.(in Chinese)
[14]王双成.贝叶斯网络学习、推理与应用[M].上海:立信会计出版社,2010.WANG Shuangcheng.Bayesian network learning,reasoning and application[M].Shanghai:Lixin Accounting Press,2010.(in Chinese)
[15]PEARL B J.Probabilistic reasoning in intelligent systems:Network of plausible inference[M].San Francisco:Morgan Kaufmann Publishers,Inc,1988.
[16]OLESEN K G,LAURITZEN S L,JENSEN F V.aHUGIN:a system creating adaptive causal probabilistic networks[C]//UAI'92:Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence,Stanford University,Stanford,Ca,Usa,July.DBLP,1992:223-229.
[17]SPIEGELHALTER D J,DAWID A P,LAURITZEN SL,et al.Bayesian analysis in expert systems[J].Statistical Science,1993,8(3):219-247.
[18]LIAO W,JI Q.Learning Bayesian network parameters under incomplete data with domain knowledge[J].Pattern Recognition,2009,42(11):3046-3056.
[19]ABBASZADEH S,GORDJI M E,PAP E,et al.Jensen-type inequalities for Sugeno integral[J].Information Sciences,2017,376:148-157.
[20]杨优军.基于水电机组状态监测的水电厂机电设备运行管理[D].北京:清华大学,2013.YANG Youjun.Operation and maintenance of mechanical and electrical equipments based on condition monitoring of hydropower units[D].Beijing:Tsinghua University,2013.(in Chinese)
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