基于模糊Petri网的船闸故障诊断模型研究
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摘要
为提高船闸系统的协调性与实时性,建立高精度的船闸故障诊断系统,使用具有更强推理性的Petri网对船闸系统进行建模,分析其各点状态从而能对船闸状态有更好的了解,使控制及检修策略更具有针对性。算例分析证明该方法实现了网络的数据关联分析,提高了故障诊断的快速准确性。
Lock control system is a typical distributed control system with good flexibility and coordination.However,distributed control system has hysteresis effect in diagnosis and treatment,which has a great negative effect on lock state control.Therefore,it is necessary to improve the coordination and timeliness of lock system.In this paper,Petri net with stronger reasoning power is used to model the lock system,and the state of each point can be analyzed to have a better understanding of the lock state and make the actions more targeted.The example analysis also proves that this method realizes the network data association analysis and improves the accuracy of fault diagnosis.
Lock control system is a typical distributed control system with good flexibility and coordination.However,distributed control system has hysteresis effect in diagnosis and treatment,which has a great negative effect on lock state control.Therefore,it is necessary to improve the coordination and timeliness of lock system.In this paper,Petri net with stronger reasoning power is used to model the lock system,and the state of each point can be analyzed to have a better understanding of the lock state and make the actions more targeted.The example analysis also proves that this method realizes the network data association analysis and improves the accuracy of fault diagnosis.
引文
[1]师海风.基于神经网络的北溪南港船闸故障诊断专家系统研究[M].福州:福州大学.2003.
[2]冒刘燕.基于可靠性理论的内河船闽维修决策研巧[D].南京:东南大学.2015.
[3]李明华,屈彦明,周孟戈,等.基于多Agent及Petri网的变压器故障诊断系统[J].西安交通大学学报,2006(02):223-227.
[4]Gong M F,Song H H,Tan J W,et al.Fault diagnosis of motor based on mutative scale back propagation net evolving fuzzy Petri nets[C].2017IEEE.2017:3826-3829.
[5]甘正佳,甘正宁,成新明.基于概率Petri网的柴油机故障诊断方法研究[J].长沙铁道学院学报,2003,21(1):79-83.
[6]Gao M M,Zhou M C,Huang X G,et al.Fuzzy reasoning petri nets[J].IEEE Transactions on Systems,Man,and Cybernetics-Part A:Systems and Humans,2003,33(3):314-324.
[7]Liu H C,You J X,Tian G.Determining truth degrees of input places in fuzzy petri nets[J].IEEE Transactions on Systems Man&Cybernetics Systems,2016,(99):1-7.
[8]Gong M,Zhang Y,Liu Y,et al.Fault diagnosis of power transformers based on back propagation algorithm evolving fuzzy Petri nets[J].Power System Protection&Control,2015,43(3):113-117.
[9]Basile F,Cabasino M P,Seatzu C.Marking estimation of Time Petri nets with unobservable transitions[C]//IEEE Conference on Emerging Technologies&Factory Automation.2013..
[10]Liu H C,Lin Q L,Ren M L.Fault diagnosis and cause analysis using fuzzy evidential reasoning approach and dynamic adaptive fuzzy Petri nets[J].Computers&Industrial Engineering,2013,66(4):899-908.
[2]冒刘燕.基于可靠性理论的内河船闽维修决策研巧[D].南京:东南大学.2015.
[3]李明华,屈彦明,周孟戈,等.基于多Agent及Petri网的变压器故障诊断系统[J].西安交通大学学报,2006(02):223-227.
[4]Gong M F,Song H H,Tan J W,et al.Fault diagnosis of motor based on mutative scale back propagation net evolving fuzzy Petri nets[C].2017IEEE.2017:3826-3829.
[5]甘正佳,甘正宁,成新明.基于概率Petri网的柴油机故障诊断方法研究[J].长沙铁道学院学报,2003,21(1):79-83.
[6]Gao M M,Zhou M C,Huang X G,et al.Fuzzy reasoning petri nets[J].IEEE Transactions on Systems,Man,and Cybernetics-Part A:Systems and Humans,2003,33(3):314-324.
[7]Liu H C,You J X,Tian G.Determining truth degrees of input places in fuzzy petri nets[J].IEEE Transactions on Systems Man&Cybernetics Systems,2016,(99):1-7.
[8]Gong M,Zhang Y,Liu Y,et al.Fault diagnosis of power transformers based on back propagation algorithm evolving fuzzy Petri nets[J].Power System Protection&Control,2015,43(3):113-117.
[9]Basile F,Cabasino M P,Seatzu C.Marking estimation of Time Petri nets with unobservable transitions[C]//IEEE Conference on Emerging Technologies&Factory Automation.2013..
[10]Liu H C,Lin Q L,Ren M L.Fault diagnosis and cause analysis using fuzzy evidential reasoning approach and dynamic adaptive fuzzy Petri nets[J].Computers&Industrial Engineering,2013,66(4):899-908.