System and method for isolating failures in a locomotive

A method for isolating failures in a locomotive having a plurality of sub-systems, comprising the steps of:

• recording incidents occurring in each of the plurality of sub-systems during operation of the locomotive;
• mapping some of the recorded incidents to indicators, each indicator representative of an observable symptom detected in each sub-system;
• determining causes for any failures associated with the incidents with a diagnostic knowledge base having diagnostic information about failures occurring in each of the plurality of sub-systems and the indicators, wherein the diagnostic information comprises a plurality of causal networks, each causal network having a plurality of nodes for each of the plurality of subsystems, each causal network having a cause and effect relationship between some of the plurality of nodes, wherein some of the nodes represent root causes associated with failures in each of the plurality of sub-systems and some of the nodes represent observable manifestations of the failures and a diagnostic engine for processing the mapped indicators with the diagnostic information in the diagnostic knowledge base;
• invoking the plurality of causal networks according to the mapped indicators and evaluating the mapped indicators with the probabilities in the invoked networks;
• recalculating the probabilities of the invoked causal networks according to the status of the mapped indicators;
• and
• providing a course of action to be performed for correcting the failures.

A system for automatically isolating failures occurring in a process having a plurality of equipment, comprising:

• a plurality of sensors located about the process for measuring physical phenomena associated with the plurality of equipment;
• means for mapping some of the sensor measurements to indicators, each indicator representative of an observable symptom detected in a piece of equipment;
• a fault isolator coupled to the mapping means for determining causes for any failures associated with the equipment, the fault isolator comprising a diagnostic knowledge base having diagnostic information about failures occurring in each of the plurality of equipment and the indicators, the diagnostic information comprising a plurality of causal networks each having a plurality of nodes for each of the plurality of equipment, each causal network having a cause and effect relationship between some of the plurality of nodes, wherein some of the nodes represent root causes associated with failures in each of the plurality of equipment and some of the nodes represent observable manifestations of the failures, and a diagnostic engine for processing the mapped indicators with the diagnostic information in the diagnostic knowledge base, wherein the diagnostic engine comprises an indicator evaluator for invoking the plurality of causal networks according to the mapped indicators and evaluating the mapped indicators with the probabilities in the invoked causal networks and a diagnostic evaluator for evaluating the recalculated probabilities in the invoked causal networks and providing a list of the most likely causes for any equipment failures;
• and
• means for providing a course of action to be performed for correcting the failures.

A method for isolating failures occurring in a process having a plurality of equipment, comprising the steps of:

• providing a plurality of causal networks each having a plurality of nodes for each of the plurality of equipment, each causal network having a cause and effect relationship between some of the plurality of nodes, wherein some of the nodes represent root causes associated with failures in each of the plurality of equipment and some of the nodes represent observable manifestations of the failures;
• transforming the causal networks into a knowledge base having diagnostic information about failures occurring in each of the plurality of equipment and observable symptoms detected in each of the plurality of equipment;
• coupling a diagnostic engine to the knowledge base;
• measuring physical phenomena associated with the equipment;
• mapping some of the measurements to indicators, each indicator representative of an observable symptom detected in a piece of equipment;
• using the diagnostic information and the diagnostic engine to determine causes for any failures associated with the mapped indicators;
• invoking the plurality of causal networks according to the mapped indicators and evaluating the mapped indicators with the probabilities in the invoked causal networks;
• recalculating the probabilities of the invoked causal networks according to the status of the mapped indicators;
• and
• providing a course of action to be performed for correcting the failures.