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公开(公告)号：US20100198610A1
公开(公告)日：2010-08-05
申请号：US12366472
申请日：2009-02-05
申请人： Asif Khalak , Bradley John Barton , Randy Magnuson , Qingqiu Ginger Shao , David Michael Kolbet , C. Arthur Dins
发明人： Asif Khalak , Bradley John Barton , Randy Magnuson , Qingqiu Ginger Shao , David Michael Kolbet , C. Arthur Dins
摘要： The present application relates to a method of splitting a fault condition including receiving evidence observations of a monitored system from monitors connected in a many-to-many relationship to the failure modes, generating a fault condition, computing a relative probability of failure for each failure mode in the fault condition. When there is more than one failure mode in the fault condition, the method includes computing a relative probability of each pair of failure modes in the fault condition, ranking the computed relative probabilities of the individual failure modes and the computed relative probabilities of the pairs of failure modes. If the highest ranked failure mode is a pair of failure modes, the fault condition is split based on the failure modes in the highest ranked pair of failure modes are split. If the highest ranked failure mode is an individual failure mode, a failure is isolated based on the ranking.
摘要翻译： 本申请涉及一种将故障条件分解的方法，包括从多对多关系的监视器接收监视系统的证据观察到故障模式，产生故障状况，计算每个故障的相对故障概率 模式处于故障状态。 当故障状态有多种故障模式时，该方法包括计算故障状态下每对故障模式的相对概率，对各个故障模式的计算相对概率进行排序，计算出相应故障模式的相对概率 故障模式。 如果排名最高的故障模式是一对故障模式，则基于最高排序失败模式的故障模式分为故障状态。 如果排名最高的故障模式是单个故障模式，则基于排名隔离故障。
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公开(公告)号：US08175846B2
公开(公告)日：2012-05-08
申请号：US12366472
申请日：2009-02-05
申请人： Asif Khalak , C. Arthur Dins , Bradley John Barton , Randy Magnuson , Qingqiu Ginger Shao , David Michael Kolbet
发明人： Asif Khalak , C. Arthur Dins , Bradley John Barton , Randy Magnuson , Qingqiu Ginger Shao , David Michael Kolbet
IPC分类号： G06F19/00
摘要： The present application relates to a method of splitting a fault condition including receiving evidence observations of a monitored system from monitors connected in a many-to-many relationship to the failure modes, generating a fault condition, computing a relative probability of failure for each failure mode in the fault condition. When there is more than one failure mode in the fault condition, the method includes computing a relative probability of each pair of failure modes in the fault condition, ranking the computed relative probabilities of the individual failure modes and the computed relative probabilities of the pairs of failure modes. If the highest ranked failure mode is a pair of failure modes, the fault condition is split based on the failure modes in the highest ranked pair of failure modes are split. If the highest ranked failure mode is an individual failure mode, a failure is isolated based on the ranking.
摘要翻译： 本申请涉及一种将故障条件分解的方法，包括从多对多关系的监视器接收监视系统的证据观察到故障模式，产生故障状况，计算每个故障的相对故障概率 模式处于故障状态。 当故障状态有多种故障模式时，该方法包括计算故障状态下每对故障模式的相对概率，对各个故障模式的计算相对概率进行排序，计算出相应故障模式的相对概率 故障模式。 如果排名最高的故障模式是一对故障模式，则基于最高排序失败模式的故障模式分为故障状态。 如果排名最高的故障模式是单个故障模式，则基于排名隔离故障。
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公开(公告)号：US20100198771A1
公开(公告)日：2010-08-05
申请号：US12366475
申请日：2009-02-05
申请人： Asif Khalak , C. Arthur Dins , Bradley John Barton , David Michael Kolbet , Qingqiu Ginger Shao , Randy Magnuson
发明人： Asif Khalak , C. Arthur Dins , Bradley John Barton , David Michael Kolbet , Qingqiu Ginger Shao , Randy Magnuson
CPC分类号： G05B23/024
摘要： A method for determining relative likelihood of a failure mode is provided. The method comprises receiving evidence observations of a monitored system from monitors connected in a many-to-many relationship to the failure modes, generating a fault condition including states of all failure modes that are connected to the monitors, and computing a relative probability of failure for each failure mode. The fault condition is generated for a reference model of the monitored system and is based on the received evidence observations. The relative probability of failure for each failure mode is based on a false alarm probability, a detection probability, and a ratio of prior probabilities of a candidate hypothesis to a null hypothesis of no active failure mode.
摘要翻译： 提供了一种用于确定故障模式的相对似然性的方法。 该方法包括从与许多关系的故障模式连接的监视器接收被监视系统的证据观察，产生包括连接到监视器的所有故障模式的状态的故障状况，以及计算相对故障概率 对于每个故障模式。 为监控系统的参考模型生成故障条件，并基于收到的证据观察结果。 每个故障模式的相对故障概率基于假警报概率，检测概率以及候选假设的先验概率与无主动故障模式的零假设的比率。
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公开(公告)号：US08224765B2
公开(公告)日：2012-07-17
申请号：US12366475
申请日：2009-02-05
申请人： Asif Khalak , C. Arthur Dins , Bradley John Barton , David Michael Kolbet , Qingqiu Ginger Shao , Randy Magnuson
发明人： Asif Khalak , C. Arthur Dins , Bradley John Barton , David Michael Kolbet , Qingqiu Ginger Shao , Randy Magnuson
CPC分类号： G05B23/024
摘要： A method for determining relative likelihood of a failure mode is provided. The method comprises receiving evidence observations of a monitored system from monitors connected in a many-to-many relationship to the failure modes, generating a fault condition including states of all failure modes that are connected to the monitors, and computing a relative probability of failure for each failure mode. The fault condition is generated for a reference model of the monitored system and is based on the received evidence observations. The relative probability of failure for each failure mode is based on a false alarm probability, a detection probability, and a ratio of prior probabilities of a candidate hypothesis to a null hypothesis of no active failure mode.
摘要翻译： 提供了一种用于确定故障模式的相对似然性的方法。 该方法包括从与许多关系的故障模式连接的监视器接收被监视系统的证据观察，产生包括连接到监视器的所有故障模式的状态的故障状况，以及计算相对故障概率 对于每个故障模式。 为监控系统的参考模型生成故障条件，并基于收到的证据观察结果。 每个故障模式的相对故障概率基于假警报概率，检测概率以及候选假设的先验概率与无主动故障模式的零假设的比率。
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公开(公告)号：US08347144B2
公开(公告)日：2013-01-01
申请号：US12802704
申请日：2010-06-11
申请人： Asif Khalak , Link Jaw
发明人： Asif Khalak , Link Jaw
IPC分类号： G06F11/00
CPC分类号： G06F11/0736 , G05B23/0262 , G06F11/079
摘要： A method for reducing false alarms in a monitoring system comprising the steps of: providing an initial fault set (or a preliminary fault set) and using a decision process to successively reduce this initial fault set to a fault ensemble, said decision process using increasing probability or confidence in the initial fault set to generate the fault ensemble, which is considered to reflect a true abnormal condition; the decision process comprising at least two steps: the first step is generating a preliminary fault set by using a standard anomaly detection method with the additional variable (or adaptive) thresholds or temporal filters; the second step is using the preliminary fault set to generate at least one fault ensemble, each of which comprises a reduced number of refined faults that represent a more confident explanation of the cause(s) of an abnormal condition.
摘要翻译： 一种用于减少监视系统中的假警报的方法，包括以下步骤：提供初始故障集（或初步故障集），并使用决策过程将该初始故障集合连续地减少到故障集合，所述决策过程使用增加的概率 或者设置初始故障置信度来产生故障集合，这被认为是反映真实的异常状况; 所述决策过程包括至少两个步骤：第一步骤通过使用具有附加变量（或自适应）阈值或时间滤波器的标准异常检测方法来产生初始故障集; 第二步是使用初始故障集合来生成至少一个故障集合，每个故障集合包括减少数量的精细故障，其表示对于异常状况的原因的更自信的解释。
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公开(公告)号：US20110307743A1
公开(公告)日：2011-12-15
申请号：US12802704
申请日：2010-06-11
申请人： Asif Khalak , Link C. Jaw
发明人： Asif Khalak , Link C. Jaw
CPC分类号： G06F11/0736 , G05B23/0262 , G06F11/079
摘要： A method for reducing false alarms in a monitoring system comprising the steps of: providing an initial fault set (or a preliminary fault set) and using a decision process to successively reduce this initial fault set to a fault ensemble, said decision process using increasing probability or confidence in the initial fault set to generate the fault ensemble, which is considered to reflect a true abnormal condition; the decision process comprising at least two steps: the first step is generating a preliminary fault set by using a standard anomaly detection method with the additional variable (or adaptive) thresholds or temporal filters; the second step is using the preliminary fault set to generate at least one fault ensemble, each of which comprises a reduced number of refined faults that represent a more confident explanation of the cause(s) of an abnormal condition.
摘要翻译： 一种用于减少监视系统中的假警报的方法，包括以下步骤：提供初始故障集（或初步故障集），并使用决策过程将该初始故障集合连续地减少到故障集合，所述决策过程使用增加的概率 或者设置初始故障置信度来产生故障集合，这被认为是反映真实的异常状况; 所述决策过程包括至少两个步骤：第一步骤通过使用具有附加变量（或自适应）阈值或时间滤波器的标准异常检测方法来产生初始故障集; 第二步是使用初始故障集合来生成至少一个故障集合，每个故障集合包括减少数量的精细故障，其表示对于异常状况的原因的更自信的解释。
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