[특허]Fault detection system and method using augmented data and fuzzy logic

Honeywell International Inc.

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특허 상세정보

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Fault detection system and method using augmented data and fuzzy logic

특허상세정보
국가/구분	United States(US) Patent 등록
국제특허분류(IPC7판)	G06F-019/00
미국특허분류(USC)	701/054; 701/100; 701/057; 318/564
출원번호	UP-0628085 (2003-07-24)
등록번호	US-7734400 (2010-06-29)
발명자 / 주소	Gayme, Dennice F. Menon, Sunil K. Nwadiogbu, Emmanuel O. Mukavetz, Dale W. Ball, Charles M.
출원인 / 주소	Honeywell International Inc.
대리인 / 주소	Ingrassia Fisher & Lorenz, P.C.
인용정보	피인용 횟수 : 17 인용 특허 : 15

초록
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A system and method that provides improved fault detection in turbine engines is disclosed. The fault detection system provides the ability to detect symptoms of engine faults based on a relatively limited number of engine parameters that are sampled relatively infrequently. The fault detection system includes a sensor data processor that receives engine sensor data during operation and augments the sensor data. The augmented data set is passed to a fuzzy logic inference system that determines the likelihood that a fault has occurred. The inference syste...

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The invention claimed is: 1. A fault detection system for detecting faults in a turbine engine, the fault detection system comprising: a sensor data processor, the sensor data processor configured to receive sensor data from the turbine engine and determine a difference between the sensor data and expected values of the sensor data to generate residuals from the sensor data and determine a rate of change of the residuals, the residuals from the sensor data and the rate of change of the residuals providing an augmented data set; and a fuzzy logic inference system, the fuzzy logic inference system configured to receive the augmented data set, and wherein the fuzzy logic inference system includes a plurality of membership functions and wherein each of the plurality of membership functions is associated with at least one data type in the residuals from the sensor data and the rate of change of the residuals, and wherein the fuzzy logic system is configured to fuzzify the residuals from the sensor data and the rate of change of the residuals using the plurality of membership functions and analyze the residuals from the sensor data and the rate of change of the residuals to determine a likelihood that a fault has occurred in the turbine engine. 2. The system of claim 1 wherein the sensor data processor is further configured to compute a margin for the sensor data. 3. The system of claim 1 wherein the sensor data comprises engine speed data, fuel flow data and exhaust gas temperature data. 4. The system of claim 1 wherein the sensor data processor is configured to receive exhaust gas temperature data and wherein the sensor data processor is further configured to determine exhaust gas temperature margin data corresponding to a difference between the exhaust gas temperature data and a maximum safe temperature. 5. The system of claim 1 wherein the fuzzy logic inference system includes a plurality of rules, and wherein the fuzzy logic system is configured to evaluate the fuzzified residuals from the sensor data and the rate of change of the residuals according to the plurality of rules. 6. The system of claim 5 wherein the fuzzy logic inference system is further configured to aggregate outputs of the plurality of rules and defuzzify the aggregated output for input into a diagnostic system. 7. The system of claim 6 wherein the sensor data comprises exhaust gas temperature data, engine speed data, and fuel flow data, and wherein the sensor data processor is configured to generate residuals from the exhaust gas temperature data, engine speed data, and fuel flow data, and wherein the sensor data processor is configured to determine a rate of change of the residuals from the exhaust gas temperature data, engine speed data, and fuel flow data, and wherein the sensor data processor is configured to determine a margin for the exhaust gas temperature data corresponding to a difference between the exhaust gas temperature data and a maximum safe exhaust gas temperature for the turbine engine. 8. An apparatus comprising: a) a processor; b) a memory coupled to the processor; c) a fault detection program residing in memory and being executed by the processor, the fault detection program including: i) a sensor data processing program, the sensor data processing program configured to receive sensor data from a turbine engine and determine a difference between the sensor data and expected values of the sensor data to generate residuals from the sensor data and determine a rate of change of the residuals, the residuals from the sensor data and the rate of change of the residuals providing an augmented data set; and ii) a fuzzy logic inference program, the fUzzy logic inference program configured to receive the augmented data set, and wherein the fuzzy logic inference program includes a plurality of membership functions and wherein each of the plurality of membership functions is associated with at least one data type in the residuals from the sensor data and the rate of change of the residuals, and wherein the fuzzy logic program is configured to fuzzify the residuals from the sensor data and the rate of change of the residuals using the plurality of membership functions and analyze the residuals from the sensor data and the rate of change of the residuals to determine a likelihood that a fault has occurred. 9. The apparatus of claim 8 wherein the sensor data comprises engine speed data, fuel flow data and exhaust gas temperature data. 10. The apparatus of claim 8 wherein the sensor data processing program is configured to receive exhaust gas temperature data and wherein the sensor data processor is further configured to determine exhaust gas temperature margin data corresponding to a difference between the exhaust gas temperature data and a selected maximum safe exhaust gas temperature for the turbine engine. 11. The apparatus of claim 8 wherein the fuzzy logic inference program includes a plurality of rules, and wherein the fUzzy logic system is configured to evaluate the fuzzified residuals from the sensor data and the rate of change of the residuals according to the plurality of rules. 12. The apparatus of claim 11 wherein the fuzzy logic inference program is further configured to aggregate outputs of the plurality of rules and defuzzify the aggregated output for input into a diagnostic system. 13. The apparatus of claim 8 wherein the sensor data comprises exhaust gas temperature data, engine speed data, and fuel flow data, and wherein the sensor data processing program is configured to generate residuals from the exhaust gas temperature data, engine speed data, and fuel flow data, and wherein the sensor data processing program is configured to determine a rate of change of the residuals from the exhaust gas temperature data, engine speed data, and fuel flow data, and wherein the sensor data processing program is configured to determine a margin for the exhaust gas temperature data corresponding to a difference between the exhaust gas temperature data and a maximum safe exhaust gas temperature for the turbine engine. 14. A fault detection system for detecting faults in a turbine engine, the fault detection system comprising: a sensor data processor, the sensor data processor configured to: receive sensor data from the turbine engine, the sensor data including exhaust gas temperature data, engine speed data, and fuel flow data; generate exhaust gas temperature residuals by determining differences between the exhaust gas temperature data to expected values of exhaust gas temperature; generate engine speed residuals by determining differences between the engine speed data to expected values of engine speed; generate fuel flow residuals by determining differences between the fuel flow data and expected values of fuel flow; determine a rate of change of the exhaust gas temperature residuals; determine a rate of change of the engine speed residuals; determine a rate of change of the fuel flow residuals; and a fuzzy logic inference system, the fuzzy logic inference system configured to receive the exhaust gas temperature residuals, the engine speed residuals, the fuel flow residuals, the rate of change of the exhaust gas temperature residuals, the rate of change of the engine speed residuals, and the rate of change of the fuel flow residuals, and wherein the fuzzy logic inference system includes a plurality of membership functions, and wherein the fuzzy logic system is configured to fuzzify the exhaust gas temperature residuals, the engine speed residuals, the fuel flow residuals, the rate of change of the exhaust gas temperature residuals, the rate of change of the engine speed residuals, and the rate of change of the fuel flow residuals using the plurality of membership functions to determine a likelihood that a fault has occurred in the turbine engine. 15. The system of claim 14 wherein the plurality of membership functions include a low membership function, a medium membership function, and a high membership function. 16. The system of claim 15 wherein the low membership function comprises a first sigmoid function, and wherein the medium membership function comprises a trapezoid function, and wherein the high membership function comprises a second sigmoid function. 17. The system of claim 15 wherein the fuzzy logic inference system is configured to fuzzify the exhaust gas temperature residuals, the engine speed residuals, the fuel flow residuals, the rate of change of the exhaust gas temperature residuals, the rate of change of the engine speed residuals, and the rate of change of the fuel flow residuals using the plurality of membership functions by generating an aggregated output function from the plurality of membership functions. 18. The system of claim 17 wherein the fuzzy logic inference system is configured to determine a likelihood that a fault has occurred in the turbine engine by determining a centroid of area under the aggregated output function. 19. The system of claim 18 wherein the fault comprises a high pressure spool fault. 20. The system of claim 14 wherein the sensor data processor is configured to determine the rate of change of the exhaust gas temperature residuals using a linear fit of the exhaust gas temperature residuals, and wherein the sensor data processor is configured to determine the rate of change of the engine speed residuals using a linear fit of the engine speed residuals, and wherein the sensor data processor is configured to determine the rate of change of the fuel flow residuals using a linear fit of the fuel flow residuals.

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