Abstract: Methods, systems and computing devices are provided for using a completed corrective action as evidence of a fault. The methods, systems and computing devices receive equipment status evidence and determine an equipment fault based on the equipment status evidence. The methods, systems and computing devices also create and rank a list of potential failure modes based at least in part on the determined equipment fault, recommend a corrective action to correct the equipment fault based at least in part on the ranking of the potential failure modes and receiving additional equipment status evidence indicating that the recommended corrective action failed to correct the equipment fault. The methods, systems and computing devices then associate a detection probability and a false negative rate with the failed corrective action to create additional status evidence, and re-rank the list of potential failure modes for subsequent performance based on the additional status evidence.

Abstract: Methods, systems and computing devices are provided for using a completed corrective action as evidence of a fault. The methods, systems and computing devices receive equipment status evidence and determine an equipment fault based on the equipment status evidence. The methods, systems and computing devices also create and rank a list of potential failure modes based at least in part on the determined equipment fault, recommend a corrective action to correct the equipment fault based at least in part on the ranking of the potential failure modes and receiving additional equipment status evidence indicating that the recommended corrective action failed to correct the equipment fault. The methods, systems and computing devices then associate a detection probability and a false negative rate with the failed corrective action to create additional status evidence, and re-rank the list of potential failure modes for subsequent performance based on the additional status evidence.

Abstract: A method of detecting and diagnosing system faults, includes detecting the noisy status of a monitor during operations and incorporating a quantified monitor uncertainty level to support fault isolation reasoning. A sequential probability ratio test is used to statistically test the noisy status of a monitor and Shannon's entropy theory is used to quantify the uncertainty levels of the monitor to support the use of the monitor values in fault isolation.

Abstract: 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.

Abstract: 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.

Abstract: A method for determining a probabilistic loss of function of a system includes the steps of determining a plurality of failure mode probabilities, ranking a plurality of functions pertaining to the failure mode probabilities, and identifying a likely function at least substantially lost by the system based at least in part on the plurality of failure mode probabilities and the ranking.

Abstract: A method of detecting and diagnosing system faults, includes detecting the noisy status of a monitor during operations and incorporating a quantified monitor uncertainty level to support fault isolation reasoning. A sequential probability ratio test is used to statistically test the noisy status of a monitor and Shannon's entropy theory is used to quantify the uncertainty levels of the monitor to support the use of the monitor values in fault isolation.

Abstract: Provided are methods and systems distributing a data message to an unknown destination device across at least one spatial boundary and at least one administrative domain boundary from an originating device. The system includes at least one distributor module that exists within each administrative domain of a network through which the data message may originate, may terminate or may traverses in route from the originating device to the unknown destination device. Each administrative domain within each of a plurality of equipment platforms has at least one distributor module. The system also includes a domain bridge spanning the at least one administrative domain boundary within an equipment platform of the plurality through which the data message traverses in route to the unknown destination device. The system operates using a network discovery service whereby an advertisement is published for a specific type of data by the unknown destination device. The advertisement is promulgated throughout the network.

Abstract: A system for monitoring the health of a component includes a memory configured to store a health management system for evaluating the health of the component. The health management system includes a first prognostic module, a first diagnostic module, a first failure mode module, and a first functional module. A processor is coupled to the memory and configured to retrieve the health management system from the memory; receive a first prognostic indicator associated with the health of the component; determine a first predicted diagnostic indicator based on the prognostic indicator with the prognostic module; determine a first failure mode probability based on the first predicted diagnostic indicator with the diagnostic module; determine a first failure mode vector based on the first failure mode probability with the failure mode module; and generate a first functional output based on the first failure mode vector with the first functional mode module.

Abstract: 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.

Abstract: 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.

Abstract: A method for determining a probabilistic loss of function of a system includes the steps of determining a plurality of failure mode probabilities, ranking a plurality of functions pertaining to the failure mode probabilities, and identifying a likely function at least substantially lost by the system based at least in part on the plurality of failure mode probabilities and the ranking.

Abstract: A method for diagnostic reasoning of faults appearing in a vehicle health monitoring system (VHM) is provided. One of alternatively a signal mode or a failure mode state is identified based on an input. If a signal is identified, the signal is queried to determine if the signal indicts a failure mode. If the signal indicts the failure mode, an intermittent watch flag is set for the failure mode. A count representing a number of occurrences of the signal as an intermittent fault is incremented. It is determined if the count exceeds a predetermined threshold. If the count exceeds the predetermined threshold, the intermittent fault is determined to be a permanent fault.