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

Volume

2

fYear

2009

fDate

10-11 Oct. 2009

Firstpage

495

Lastpage

498

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICICTA.2009.354

Filename

5287738