Error detection/correction and fault detection/recovery – Data processing system error or fault handling – Reliability and availability
Reexamination Certificate
1999-10-28
2001-11-27
Le, Dieu-Minh (Department: 2184)
Error detection/correction and fault detection/recovery
Data processing system error or fault handling
Reliability and availability
C714S047300
Reexamination Certificate
active
06324659
ABSTRACT:
BACKGROUND OF THE INVENTION
This invention generally relates to a method and system for predicting malfunctions or breakdowns of machines, such as locomotives, and, more particularly, this invention relates to a method and system for identifying critical faults in machines. For example, the critical faults may be used by a remote monitoring and diagnostic service center (MDSC) to initiate prompt corrective action upon detection of the critical faults.
A locomotive is one example of a complex electromechanical system comprised of several complex subsystems. Each of these subsystems is built from components which over time will fail. When a component does fail, it is difficult to identify the failed component because the effects or problems that the failure has on the subsystem are often neither readily apparent in terms of their source nor unique. The ability to automatically diagnose problems that have occurred or will occur in the locomotive systems has a positive impact on minimizing locomotive downtime.
Previous attempts to diagnose problems occurring in a locomotive have been performed by experienced personnel who have in-depth individual training and experience in working with locomotives. Typically, these experienced individuals use available information that has been recorded in a log. Looking through the log, the experienced individuals use their accumulated experience and training in mapping incidents occurring in locomotive systems to problems that may be causing the incidents. If the incident-problem scenario is simple, then this approach works fairly well. However, if the incident-problem scenario is complex, then it is very difficult to diagnose and correct any failures associated with the incidents.
Currently, computer-based systems are being used to automatically diagnose problems in a locomotive in order to overcome some of the disadvantages associated with relying completely on experienced personnel. Typically, a computer-based system utilizes a mapping between the observed symptoms of the failures and the equipment problems using techniques such as table look ups, a symptom-problem matrices, and production rules. These techniques work well for simplified systems having simple mappings between symptoms and problems. However, complex equipment and process diagnostics seldom have such simple correspondences. In addition, not all symptoms are necessarily present if a problem has occurred, thus making other approaches more cumbersome.
The above-mentioned approaches either take a considerable amount of time before failures are diagnosed, or provide less than reliable results, or are unable to work well in complex systems. There is a need to be able to quickly and efficiently determine the cause of any failures occurring in the locomotive systems, while minimizing the need for human intervention.
U.S. Pat. No. 5,845,272 discloses an on-board locomotive diagnostic system. The system is useful for identifying locomotive systems problems and proposing remedial measures to repair or correct the problems. On-board diagnostic systems, however, do not presently communicate with a rail carrier's maintenance or scheduling centers. Consequently, those centers do not have direct access to subsystems data from remote locomotives which would be helpful in optimizing locomotive maintenance scheduling and route planning while minimizing locomotive downtime and mission failures arising from unexpected breakdowns.
Accordingly, it would be desirable to provide a communication data management system that will download files from and upload files to respective ones of the locomotives based on predetermined schedule and criteria, such as may be received and/or retrieved from a suitable database. It will be further desirable that, upon downloading the appropriate files from any respective locomotive, the communication data management system be able to readily format and store the downloaded files in appropriate directories on a predetermined server, and update any relevant records in the database. It will also be desirable that for uploading into a given locomotive, the system be able to retrieve the appropriate upload files from the server and then format and transmit the files to the locomotive while updating relevant records in the database. It is also desirable that the system be able to monitor any communication-enabling resources available to it (e.g., modems, transceivers, satellite links, wireless links, etc.) and utilize the appropriate resource for a specific type of download. It would also be desirable that the system be able to manage “locomotive call home” cases, such as may occur upon detection by the onboard diagnostics, of critical faults that are known to cause locomotive road failures due to, for example, loss of locomotive power. It is especially desirable to proactively manage such critical faults that could result in unscheduled shutting down or substantially slowing down vehicle operation, since such shutdowns or slowdowns are costly and highly inconvenient. It is also desirable to provide a system that automatically schedules diagnostics using the downloaded data for detecting incipient failures and dealing with any predicted failures before they occur.
BRIEF SUMMARY OF THE INVENTION
Generally speaking, the present invention fulfills the foregoing needs by providing a method for identifying a plurality of critical faults in machines. The method generally includes collecting from a predetermined plurality of the machines respective machine data indicative of each fault logged over a predetermined period of time. The method further includes respective identifying steps that allow for identifying in the collected machine data respective faults most frequently occurring relative to one another and for identifying in the most frequently occurring faults, respective faults that, relative to one another, affect a higher number of machines. A classifying step allows for classifying the faults identified in the last-recited identifying step based on an expected level of machine degradation associated with the identified faults. A storing step allows for storing any faults classified as likely to result in an imminent machine mission failure in a predetermined database of critical faults.
The present invention further fulfills the foregoing needs by providing a system for identifying a plurality of critical faults in machines. The system includes means for collecting from a predetermined plurality of the machines respective machine data indicative of each fault logged over a predetermined period of time. The system further includes means for identifying in the collected machine data respective faults most frequently occurring relative to one another. There is also provided means for identifying in the most frequently occurring faults, respective faults that, relative to one another, affect a higher number of machines. Classifying means allows for classifying the faults identified with the last-recited identifying means based on an expected level of machine degradation associated with the identified faults. A database is coupled to the means for classifying to store any faults classified as likely to result in an imminent machine mission failure, the stored faults comprising the plurality of critical faults.
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Beusse Brownlee Bowdoin & Wolter PA
General Electric Company
Le Dieu-Minh
Mora, Esq. Enrique J.
Rowold, Esq. Carl A.
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