DocumentCode :
3128876
Title :
Teaching research on sensor diagnosis based on information Syncretic Technology
Author :
Mingjiang, Hu ; Liqiao, Qi
Author_Institution :
Dept. of Thermal Energy Eng., Henan Univ. of Urban Constr., Pingdingshan, China
Volume :
2
fYear :
2011
fDate :
4-7 Aug. 2011
Firstpage :
103
Lastpage :
106
Abstract :
The diesel engine sensor fault diagnosis teaching model was established based on the fuzzy Reasoning logic and sensor work. Fuzzy reasoning logic of the sensor malfunction diagnosis was put forward according to the sensor signal wave. Based on the different malfunction signal of the sensors, the hard malfunction, soft malfunction and the fault type of the sensors were diagnosed by information Syncretic Technology, the on-line teaching diagnostic strategy of sensors malfunction was put forward. Using the simulative teaching control equipments of the diesel engine, the malfunction tests on the hard malfunction and soft malfunction of the sensors, such as, MAP, RPS and TPS, were made by fuzzy neural network syncretic strategy, The test result showed that the sensors fault diagnosis teaching model was reasonable; the teaching diagnostic strategy had the good resolving power and could be much fitted for the sensors teaching diagnosis in the diesel engine.
Keywords :
computer aided instruction; condition monitoring; diesel engines; engineering education; fault diagnosis; fuzzy neural nets; fuzzy reasoning; mechanical engineering computing; teaching; diesel engine sensor fault diagnosis teaching model; fuzzy neural network syncretic strategy; fuzzy reasoning logic; hard malfunction; information syncretic technology; online teaching diagnostic strategy; sensor malfunction diagnosis; sensor signal wave; sensors malfunction; simulative teaching control equipments; soft malfunction; Calibration; Circuit faults; Diesel engines; Education; Fault diagnosis; Fuzzy reasoning; Sensitivity; Fuzzy reasoning logic; Information technology; Neural network; On-line diagnosis; Sensor; Teaching research;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Uncertainty Reasoning and Knowledge Engineering (URKE), 2011 International Conference on
Conference_Location :
Bali
Print_ISBN :
978-1-4244-9985-4
Electronic_ISBN :
978-1-4244-9984-7
Type :
conf
DOI :
10.1109/URKE.2011.6007919
Filename :
6007919
Link To Document :
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