US5845272A
Expired / Lapsed
US
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System and method for isolating failures in a locomotive
Assignee: General Electric Co
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Filing: 1996-11-29
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Granted: 1998-12-01
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Expires: 2016-11-29
Abstract
Abstract The present invention discloses a system and method for isolating failures in a locomotive. In the present invention, the cause of failures occurring in the locomotive sub-systems are determined quickly and efficiently, while minimizing the need for human interaction. However, the present invention can incorporate information provided by an operator to produce a more refined diagnosis. In the present invention, incidents are recorded in an incident log and mapped to indicators, which are sent to a fault isolator for diagnosis. The fault isolator uses a diagnostic knowledge base having diagnostic information between failures occurring in locomotive and observable symptoms happening therein. A diagnostic engine then processes the mapped indicators with the diagnostic information in the diagnostic knowledge base and produces a list of the most likely causes for any failures. The present invention then provides a course of action to correct the failures. The present invention can also be used to automatically isolate and diagnose failures occurring in process having a plurality of equipment.
Inventors
- 👤 Mahesh Amritlal Morjaria
- 👤 Steven Hector Azzaro
- 👤 James Arthur Bush
- 👤 James Weston Nash
- 👤 Myron Lee Smith
- 👤 William David Smith
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-29 22:31
CPC Classifications
B; B60; B60L; B60L3/00; B60L3/12; B61; B61C; B61C17/00; B61C5/00; G; G06; G06F; G06F11/00; G06F11/22; G06F11/2257; B60L2200/00; B60L2200/26; Y; Y02; Y02T; Y02T50/00; Y02T50/60
Claims Analysis
Total Claims: 36
Claim 1
Independent Claim
252 words
A system for isolating failures in a locomotive having a plurality of sub-systems, comprising: means for supplying information on incidents occurring in each of the plurality of sub-systems during operation of the locomotive; means for mapping some of the incidents to indicators, each indicator representative of an observable symptom detected in a sub-system; a fault isolator coupled to the mapping means for determining causes for any failures associated with the incidents, the fault isolator comprising 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 sub-systems, 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, 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 network solver for recalculating the probabilities of the invoked causal networks according to the status of the mapped indicators; and means for providing a course of action to be performed for correcting the failures.
Claim 2
Independent Claim
252 words
A system for isolating failures in a locomotive having a plurality of sub-systems, comprising: means for supplying information on incidents occurring in each of the plurality of sub-systems during operation of the locomotive; means for mapping some of the incidents to indicators, each indicator representative of an observable symptom detected in a sub-system; a fault isolator coupled to the mapping means for determining causes for any failures associated with the incidents, the fault isolator comprising 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 sub-systems, 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, 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 network solver for recalculating the probabilities of the invoked causal networks according to the status of the mapped indicators; and means for providing a course of action to be performed for correcting the failures.
Claim 3
Dependent Claim
34 words
The system according to claim 1, wherein each of the root cause nodes in the causal networks has a prior probability indicating the likelihood of a failure in the absence of any additional knowledge.
Claim 4
Dependent Claim
31 words
The system according to claim 2, wherein each of the nodes in the causal networks has conditional probability information representing the strength of the relationships of the node to its causes.
Claim 5
Dependent Claim
37 words
The system according to claim 3, wherein the diagnostic engine further comprises a diagnostic evaluator for evaluating the recalculated probabilities in the invoked causal networks and providing a list of the most likely causes for any failures.
Claim 6
Dependent Claim
31 words
The system according to claim 4, wherein the diagnostic evaluator prompts an operator to check a manually examined indicator that may have a further impact on the diagnosis of the locomotive.
Claim 7
Dependent Claim
25 words
The system according to claim 5, wherein the indicator evaluator invokes the plurality of causal networks according to the status of the manually examined indicator.
Claim 8
Dependent Claim
27 words
The system according to claim 6, wherein the network solver recalculates the probabilities in the invoked causal networks according to the status of the manually examined indicator.
Claim 9
Dependent Claim
31 words
The system according to claim 7, wherein the diagnostic evaluator evaluates the recalculated probabilities in the invoked causal networks and provides a list of the most likely causes for any failures.
Claim 10
Independent Claim
221 words
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.
Claim 11
Independent Claim
221 words
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.
Claim 12
Dependent Claim
34 words
The method according to claim 9, wherein each of the root cause nodes in the causal networks has a prior probability indicating the likelihood of a failure in the absence of any additional knowledge.
Claim 13
Dependent Claim
31 words
The method according to claim 10, wherein each of the nodes in the causal networks has conditional probability information representing the strength of the relationships of the node to its causes.
Claim 14
Dependent Claim
32 words
The method according to claim 11, further comprising the steps of evaluating the recalculated probabilities in the invoked causal networks and providing a list of the most likely causes for any failures.
Claim 15
Dependent Claim
29 words
The method according to claim 12, further comprising the step of prompting an operator to check a manually examined indicator that may have a further impact on the diagnosis.
Claim 16
Dependent Claim
26 words
The method according to claim 13, further comprising the step of invoking the plurality of causal networks according to the status of the manually examined indicator.
Claim 17
Dependent Claim
28 words
The method according to claim 14, further comprising the step of recalculating the probabilities in the invoked causal networks according to the status of the manually examined indicator.
Claim 18
Dependent Claim
32 words
The method according to claim 15, further comprising the steps of evaluating the recalculated probabilities in the invoked causal networks and providing a list of the most likely causes for any failures.
Claim 19
Independent Claim
259 words
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.
Claim 20
Independent Claim
259 words
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.
Claim 21
Dependent Claim
33 words
The system according to claim 17, wherein each of the root causes in the causal networks has a prior probability indicating the likelihood of a failure in the absence of any additional knowledge.
Claim 22
Dependent Claim
30 words
The system according to claim 18, wherein each of the nodes in the causal networks has conditional probability representing the strength of the relationships of the node to its causes.
Claim 23
Dependent Claim
38 words
The system according to claim 19, wherein the diagnostic engine further comprises 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.
Claim 24
Dependent Claim
31 words
The system according to claim 20, wherein the diagnostic evaluator prompts an operator to check a manually examined indicator that may have a further impact on the diagnosis of the process.
Claim 25
Dependent Claim
25 words
The system according to claim 21, wherein the indicator evaluator invokes the plurality of causal networks according to the status of the manually examined indicator.
Claim 26
Dependent Claim
27 words
The system according to claim 22, wherein the network solver recalculates the probabilities in the invoked causal networks according to the status of the manually examined indicator.
Claim 27
Dependent Claim
32 words
The system according to claim 23, wherein the diagnostic evaluator evaluates the recalculated probabilities in the invoked causal networks and provides a list of the most likely causes for any equipment failures.
Claim 28
Independent Claim
221 words
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.
Claim 29
Independent Claim
221 words
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.
Claim 30
Dependent Claim
34 words
The method according to claim 25, wherein each of the root cause nodes in the causal networks has a prior probability indicating the likelihood of a failure in the absence of any additional knowledge.
Claim 31
Dependent Claim
31 words
The method according to claim 26, wherein each of the nodes in the causal networks has conditional probability information representing the strength of the relationships of the node to its causes.
Claim 32
Dependent Claim
33 words
The method according to claim 27, further comprising the steps of evaluating the recalculated probabilities in the invoked causal networks and providing a list of the most likely causes for any equipment failures.
Claim 33
Dependent Claim
29 words
The method according to claim 28, further comprising the step of prompting an operator to check a manually examined indicator that may have a further impact on the diagnosis.
Claim 34
Dependent Claim
26 words
The method according to claim 29, further comprising the step of invoking the plurality of causal networks according to the status of the manually examined indicator.
Claim 35
Dependent Claim
25 words
The method according to claim 30, further comprising the step of recalculating the probabilities in the invoked causal networks according to the manually examined indicator.
Claim 36
Dependent Claim
33 words
The method according to claim 31, further comprising the steps of evaluating the recalculated probabilities in the invoked causal networks and providing a list of the most likely causes for any equipment failures.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2001-11-30 | 2002-06-01 | 2002-12-01 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2005-11-30 | 2006-06-01 | 2006-12-01 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2009-11-30 | 2010-06-01 | 2010-12-01 | $7700.00 | Window Closed / Lapsed |