The Vibration Parameter Fault Diagnosis for Automobile Engine Based on ANFIS

摘要：

the paper builds the fault diagnosis model and optimizes the input interface of the model by normalizing the initial data of the vibration 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 91.25％ under the test of field test data. The experiment indicates that the model enjoys reliability, strong generalization ability, and high failure recognition rate. Moreover, it can effectively detect the vibration parameter failure for the automobile engine.

关键词： ANFIS (Adaptive Neural Fuzzy Interference System) information fusion vibration parameter fault diagnosis

作者: Rong-ling Shi Ji-yun Zhao Li-fang Kong Rong-ling Shi

作者单位: School of Machine and Electrical Engineering China University of Mining and Technology Jiangsu Xuzho Xuzhou Agriculture Machinery Technique Extending Station Jiangsu Xuzhou 221002, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

会议地点: 长春

会议语种:英文

页码: 558-561

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）