The Performance Parameter Fault Diagnosis for Automobile Engine Based on ANFIS
This paper builds the fault diagnosis model and optimizes the input interface of the model by normalizing the initial data of the performance parameter for the automobile engine, carrying on information fusion and adopting the Adaptive Neural Fuzzy Interference System (ANFIS). The recognition rate of the model reaches 94.38％ under the test of field test data. Corresponding BP neural network modeling and fuzzy recognition modeling, the model enjoys reliability, strong generalization ability, and high failure recognition rate. Moreover, it can effectively detect the performance parameter failure for the automobile engine.
fault diagnosis Performance Parameter fuzzy recognkation ANFIS
Li-Fang Kong Jun Wang Zhong-Hua Wang
Basic Departments Xuzhou Air Force College Jiangsu Xuzhou 221002, China Management Science Department Xuzhou Institute of Technology Jiangsu Xuzhou 221002, China
国际会议
长春
英文
554-557
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）