基于设备结构分解的可视化故障推理与诊断技术研究
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摘要
针对复杂设备故障诊断与装备本身结构无法直观对应进行故障原因的自动推理和快速定位问题,研究了基于设备结构分解的可视化故障推理与诊断技术;通过定义热区和热区索引,将故障推理与诊断同设备结构分解相对应,在诊断的过程中构建了故障自动推理编码规则,可将故障树转换成一系列可操作的且具有一定逻辑关系的编码,并通过软件编程将编码以故障现象的表现形式呈现给排故人员,实现故障的自动推理与实际装备部件图相互结合;该方法能够按照推理步骤逐层对装备进行LRU级分解展开,真正实现可视化故障自动推理和诊断;通过某型电子装备进行故障推理实例验证,表明该方法层次结构清晰,推理简单有效,能够实现装备可视化的LRU级分层故障诊断和故障的快速定位。
Aiming at complex equipment fault diagnosis and equipment structure cannot directly corresponding to the cause of the problem of automatic reasoning and rapid positioning problem,studies a visual fault reasoning and diagnosis technology based on equipment structure decomposition.By defining the hot zone and hot zone index,corresponds the fault reasoning and diagnosis to equipment structure decomposition,constructs the fault automatic reasoning coding rules in the process of diagnosis,which can convert the fault tree to a series of operational and certain logical code,and through software programming code appears in the form of fault phenomenon for troubleshooting,which realizes automatic fault reasoning chart combined with the actual equipment parts.This method can according to the reasoning step by step to LRU level decomposition equipment,and to realize visual automatic reasoning and diagnosis.An example for the electronic equipment fault reasoning is presented to illustrate the feasibility and effectiveness of the proposed approach,can achieve equipments' visual LRU hierarchical fault diagnosis and rapidly position the faults.
Aiming at complex equipment fault diagnosis and equipment structure cannot directly corresponding to the cause of the problem of automatic reasoning and rapid positioning problem,studies a visual fault reasoning and diagnosis technology based on equipment structure decomposition.By defining the hot zone and hot zone index,corresponds the fault reasoning and diagnosis to equipment structure decomposition,constructs the fault automatic reasoning coding rules in the process of diagnosis,which can convert the fault tree to a series of operational and certain logical code,and through software programming code appears in the form of fault phenomenon for troubleshooting,which realizes automatic fault reasoning chart combined with the actual equipment parts.This method can according to the reasoning step by step to LRU level decomposition equipment,and to realize visual automatic reasoning and diagnosis.An example for the electronic equipment fault reasoning is presented to illustrate the feasibility and effectiveness of the proposed approach,can achieve equipments' visual LRU hierarchical fault diagnosis and rapidly position the faults.
引文
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[13]孙庆生,杨飞飞,王克峰.电气设备红外热像图谱分类编码与故障树研究[J].水电能源科学,2012,30(5):161-163.
[2]Zhang Y,Wang Z,Zhang J,et al.Fault detection based on discriminant analysis theory in power systems[J].ICIC Express Letters,2010,4(3):809-814.
[3]王子玲,许爱强,杨智勇.装备故障诊断和预测技术综述[J].火力与指挥控制,2008,33(s2):8-10.
[4]Wu L,Su X,Shi P.Mixed H_2/H_∞approach to fault detection of discrete linear repetitive processes[J].Journal of Franklin Institute,2011,348(2):393-414.
[5]纪伯公,石海滨,张博,等.复杂武器电气系统故障诊断技术综述[J].火炮发射与控制学报,2006,(增1):33-36.
[6]倪绍徐,张裕芳,易宏,等.基于故障树的智能故障诊断方法[J].上海交通大学学报,2008,42(8):1372-1375.
[7]Bokor J,Zabo S.Fault detection and isolation in nonlinear systems[J].Annual Reviews in Control,2009,33(2):113-123.
[8]Vojtech V,Danica R.Sequential design of robust output model predictive control[J].International Journal of Innovative Computing,Information and Control,2010,6(10):4743-4754.
[9]郭兴吉.不规则图形热区技术研究[J].计算机应用与软件,2013,30(5):295-297.
[10]Zhai Y,Liu B.Extracting Web Data Using Instance Based Learning[A].Proc.of the 6th Intl.Conf.on Web Information Systems Engineering(WISE 05)[C].2005:318-331.
[11]胡良明,徐诚,李万平.基于案例推理的自行火炮故障诊断专家系统[J].火炮发射与控制学报,2006(2):53-57.
[12]Zhang X,Jiang Y,Chen A,et al.A gradual approach for modelbased diagnosis[J].Journal of Software,2008,19(3):584-593.
[13]孙庆生,杨飞飞,王克峰.电气设备红外热像图谱分类编码与故障树研究[J].水电能源科学,2012,30(5):161-163.