Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Vehicle diagnosis or maintenance indication
Reexamination Certificate
1998-12-28
2001-05-29
Dombroske, George (Department: 2855)
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Vehicle diagnosis or maintenance indication
C073S117020, C701S101000
Reexamination Certificate
active
06240343
ABSTRACT:
TECHNICAL FIELD
This invention relates generally to an apparatus and method for providing engine diagnostics, and more particularly, to an apparatus and method for diagnosing one or more engine problems using computer based models in combination with a neural network.
BACKGROUND ART
Currently, a wide variety of techniques and apparatus are used for diagnosing engines, including, but not limited to, rule based expert systems and fuzzy sets. Typically, the known techniques and apparatus operate to classify machine and/or component conditions into a two state situation, i.e., normal or abnormal.
However, it has been recognized that the identification of a machine or component fault is more properly categorized as a pattern recognition problem. Problems with rule based approaches include long execution time required for the system to look for all possible fault candidates then classify them according to likelihood.
Reference for instance, Schricker et al U.S. Pat. No. 5,646,341 issued Jul. 8, 1997, and U.S. Pat. No. 5,787,378 issued Jul. 28, 1998, both to Caterpillar Inc.
It is also known to diagnose an engine by comparing actual engine parameter values with modeled values. Reference, for instance, Brown Jr. et al U.S. Pat. No. 5,377,112 issued Dec. 27, 1994 to Caterpillar Inc. However, using computer based models alone it has been found to be difficult to provide accurate fault diagnosis when multiple fault conditions are present.
Wang et al U.S. Pat. No. 5,566,092 issued Oct. 15, 1996 to Caterpillar Inc. discloses a diagnostic system and method which integrates several different technologies, including neural networks, expert systems, physical models and fuzzy logic to provide on-line, real-time monitoring of machine components for possible failures. However, the disclosed method relies on substantial training and operator updating for accurate diagnosis.
Accordingly, the present invention is directed to overcoming one or more of the problems as set forth above.
DISCLOSURE OF THE INVENTION
An apparatus and method for diagnosing an engine using computer based models in combination with a neural network which reduces the neural network training and updating required is disclosed. The method and apparatus determine modeled values for a plurality of engine parameters as a function of sensed values and a plurality of initial values; sense a plurality of actual values for the engine parameters; and determine a difference between the actual values and the modeled values for the respective engine parameters. The differences are inputted into a neural network which generates an output pattern as a function of the differences and a plurality of weight values. The weight values and the initial values are then updated as a function of a comparison between the output patterns and a desired pattern, and the engine is responsively diagnosed as a function of the output pattern.
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Sarangapani Jagannathan
Schricker David R.
Caterpillar Inc.
Dombroske George
Haverstock Garrett & Roberts
Kibby Steven G.
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