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
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;
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2014 IEEE/ASME International Conference on
Conference_Location :
Besacon
DOI :
10.1109/AIM.2014.6878318