Title :
Application of PNN to Fault Diagnosis of IC Engine
Author :
Du Danfeng ; Yan, Ma ; Xiurong, Guo
Author_Institution :
Coll. of Traffic, Northeast Forestry Univ., Harbin, China
Abstract :
In order to simplify data stream of automobile diagnosing instruments, a fault diagnostic method for internal combustion (IC) engine based on probability neural network (PNN) was presented. At first a PNN model was established, and then based on the sample of Jetta ATK engine, the model was trained and simulated by a number of sample sets of symptoms and troubles. Simultaneously, the comparison has been done between PNN and backpropagation (BP) network.The simulation experimental results demonstrated that PNN model is more feasible and successful than BP network model and could make data stream of diagnosing instruments easier.
Keywords :
automobiles; backpropagation; fault diagnosis; internal combustion engines; neural nets; probability; BP network; IC engine; Jetta ATK engine; PNN; automobile diagnosing instrument; backpropagation; data stream; fault diagnosis; internal combustion engine; probability neural network training; Application specific integrated circuits; Artificial neural networks; Educational institutions; Fault diagnosis; Feedforward neural networks; Forestry; Instruments; Internal combustion engines; Multi-layer neural network; Neural networks; BP network; IC engine; PNN; data stream; fault diagnosis;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.354
