DocumentCode
1784503
Title
Health monitoring of controller area network in hybrid excavator based on the message response time
Author
Dahui Gao ; Qingfeng Wang
Author_Institution
State Key Lab. of Fluid Power Transm. & Control, Zhejiang Univ., Hangzhou, China
fYear
2014
fDate
8-11 July 2014
Firstpage
1634
Lastpage
1639
Abstract
The work environment of the controller area network (CAN) in hybrid excavator is very harsh. Health monitoring of the CAN is of great importance. This work proposes a method to assess the performance of CAN and identify the faults base on the statistical characteristics of the message response time. This method can be easily embedded into a node to on-line monitor the health condition of CAN without using a special device. Firstly, we use the message response time to generate a feature to assess the health condition of CAN by comparing the difference between feature´s probability density functions under different conditions base on the Bhattacharyya distance. Then, we propose a method to detect the fault on CAN and determine the fault type and fault duration. Finally, experiments are carried out on a hybrid excavator to verify the effectiveness of the proposed method, and the results show that the proposed method is applicable for the health monitoring of CAN.
Keywords
condition monitoring; controller area networks; excavators; fault diagnosis; inspection; mechanical engineering computing; probability; statistical analysis; Bhattacharyya distance; CAN performance assessment; controller area network; fault detection; fault duration; fault identification; fault type; health condition assessment; hybrid excavator; message response time; online health condition monitoring; probability density functions; statistical characteristics; Degradation; Delays; Fault diagnosis; Feature extraction; Grounding; Monitoring; Time factors;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Intelligent Mechatronics (AIM), 2014 IEEE/ASME International Conference on
Conference_Location
Besacon
Type
conf
DOI
10.1109/AIM.2014.6878318
Filename
6878318
Link To Document