Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Vehicle diagnosis or maintenance indication
Reexamination Certificate
2002-04-12
2003-12-09
Beaulieu, Yonel (Department: 3661)
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Vehicle diagnosis or maintenance indication
C701S014000, C340S945000, C340S963000
Reexamination Certificate
active
06662089
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to maintenance and service of complex systems and more specifically methods and apparatus for improving fault classifications for such systems.
BACKGROUND OF THE INVENTION
Complex systems comprising tens or hundreds of inter-related and inter-operating systems and subsystems, many which may be complex in there own right, present unique maintenance and service challenges. Examples of such complex systems include factories, major buildings, ocean-going vessels, power generation plants, and aircraft to name a few. Complex systems and the inter-related and inter-operational nature of the systems and subsystems thereof often require equally complex and disciplined maintenance and service programs. These programs usually include documentation or records of observed or indicated irregularities or discrepancies and actions taken or services performed pursuant to resolution or prevention of such irregularities and discrepancies. This documentation is usually filled out, completed, or recorded by service and maintenance personnel. Expert systems and tools that can standardize service and maintenance diagnoses, procedures, cost estimates and so on are highly desirable for the time savings and precision they can offer to an overall maintenance and operational support program.
In the aircraft industry, for example, fault models that include, among other parameters and information, fault codes as a means to summarize the set of symptoms or standard observations that are expected to be present for each distinct fault condition in a particular type of aircraft have more recently come to be used. A fault code typically corresponds to a fault condition in a single system on the aircraft and is often used as the basis of diagnostic endeavors, including fault classification and fault isolation, material planning, cost estimation, and deferral/criticality analysis. Thus Fault Codes are a critical element of the Fault Model for an aircraft where a model is used to support an automated diagnostic and maintenance support system. Equally critical therefore is determining the proper fault code for the aircraft when presented with a discrepancy and set of symptoms or a given fault condition. Finding or determining or selecting the proper fault code based on readily apparent symptoms or observations is referred to as fault classification.
Presently airline personnel or technicians often determine the Fault Code for a fault condition by means of paper or electronic charts that provide a multiplicity of decision trees each consisting of observations states where each possible state of the observation is a branch of the tree. The leaves of the tree are the Fault Codes. This process is difficult to use since it is difficult to know which of the 100's of trees that are defined for an aircraft will best address the current situation. The static trees represented by the diagrams are also difficult to update and as such they do not reflect experience gained by the airline or airlines personnel.
Other systems for automated support of Fault Classification such as those available from Boeing, often referred to as PMA in the industry and Airbus, typically referred to as CATS, help to identify the diagram (tree) to use but do not provide a mechanism for incorporating experience into this decision or to effectively modify the decision tree itself based on this experience. Thus fault classification remains a very time consuming and error prone activity that adds complexity to the diagnostic and service procedures, increases costs, and reduces the precision of planning and cost analysis activities. Clearly a need exists for methods and apparatus for improving fault classification for complex systems, such as aircraft, preferably methods and apparatus that incorporate experience into such methods and apparatus.
SUMMARY OF THE INVENTION
The present invention in varying scope is a method and apparatus for improving fault classifications for failure modes in complex systems. One aspect of the invention is a software program comprising software instructions arranged to run on a processor to improve fault classification for failure modes in a complex system, the software program when installed and operating on a processor resulting in the processor performing an inventive method of fault classification. Another aspect according to the invention is a computer based aircraft maintenance and operations diagnostic system for improved assistance with fault classification for a fault condition within an aircraft based on a fault model for the aircraft, the computer utilizing an inventive embodiment of a fault classification software program to performs another inventive method of fault classification.
In one aspect the method includes the steps of: capturing an observation that is consistent with a discrepancy of the complex system; identifying a set of failure modes of the complex system that are consistent with the observation; ranking, when the set includes more than one failure mode, the failure modes according to a degree of support the observation provides for each failure mode, the degree of support including a historical component; determining additional possible observations that are consistent with any failure mode included in the set; and ranking the possible observations according to how rapidly they reduce a number of failure modes included in the set.
In narrower scope one aspect of the method will include a step of selecting a further observation from the possible observations and repeating, using the observation, the further observation and any additional possible observations that will be selected, the steps of identifying, ranking the failure modes, determining the additional possible observations, ranking these additional possible observations and selecting further possible observations until the set includes only one failure mode and then reporting that failure mode. The step of capturing the observation further preferably includes converting an observed discrepancy into one or more standard observations selected from a standard observations list and wherein the possible observations are possible standard observations that are members of the standard observation list. The process of identifying the set of the failure modes, preferably, includes identifying a standard failure mode selected from a standard failure mode list, the standard failure mode representing a set of observations consistent with the standard failure mode. Ranking the failure modes further uses an assessment of experience with the observation occurring with the failure mode to increase the degree or relative degree of support. Ranking the possible observations uses an algorithm to rank the possible observations according to the degree to which each possible observation divides the set of failure modes in half.
The software program is particularly suitable for use within a diagnostic tool for application to complex systems. In one aspect, using an embodiment of the software program, the invention is an aircraft maintenance and operations diagnostic system for improved assistance with fault classification for a fault condition within an aircraft based on a fault model for the aircraft, where the system comprises: a user interface; a computer, coupled to the user interface, having memory for storing software instructions and databases and a processor for; executing the software instructions to process information to facilitate the fault classification for the fault condition according to the fault model, the software instructions resulting in the computer: capturing a standard observation from an observation list that is part of the fault model and that is consistent with the fault condition; identifying a set of fault codes for the aircraft that are consistent with the standard observation; ranking, when the set includes more than one fault code, the fault codes according to a degree of support the standard observation provides for the fault code, the degree of support including a historical co
Felke Timothy J.
Kolbet David M.
Magnuson Randy R.
van der Zweep Jeff J.
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