TY - GEN
T1 - Expert System for Comprehensive Transmission Fault Diagnosis Based on Oil Sensor
AU - Li, Yingshun
AU - Li, Tingyang
AU - Yi, Xiaojian
AU - Liu, Haiyang
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8/5
Y1 - 2020/8/5
N2 - When armored vehicles are fighting in high-intensity environments, their integrated transmission systems are under tremendous pressure. The traditional method only detects the oil temperature and metal abrasive particles to determine whether the integrated transmission system is working properly, it is difficult to quickly locate the cause. This paper builds on the integrated oil sensor, analysis of physical and chemical indexes such as lubricating oil temperature, water mixing, pollution degree and viscosity collected by sensors. In the traditional fault diagnosis system, a new fault diagnosis system is established, which can find the fault source faster, determine the fault level of the machine, and make it easier for maintenance personnel to judge whether the machine needs to be shut down for maintenance. Fault diagnosis mainly through inference rules and a combination of qualitative and quantitative fault tree analysis, can clearly reflect the relationship between each fault and the parameters detected by abnormality. Integrated oil sensor and fault diagnosis system are appropriate for multi-model armored vehicles. In the future innovation, technical parameters can be inserted or reduced according to user need, and it has a good adaptability.
AB - When armored vehicles are fighting in high-intensity environments, their integrated transmission systems are under tremendous pressure. The traditional method only detects the oil temperature and metal abrasive particles to determine whether the integrated transmission system is working properly, it is difficult to quickly locate the cause. This paper builds on the integrated oil sensor, analysis of physical and chemical indexes such as lubricating oil temperature, water mixing, pollution degree and viscosity collected by sensors. In the traditional fault diagnosis system, a new fault diagnosis system is established, which can find the fault source faster, determine the fault level of the machine, and make it easier for maintenance personnel to judge whether the machine needs to be shut down for maintenance. Fault diagnosis mainly through inference rules and a combination of qualitative and quantitative fault tree analysis, can clearly reflect the relationship between each fault and the parameters detected by abnormality. Integrated oil sensor and fault diagnosis system are appropriate for multi-model armored vehicles. In the future innovation, technical parameters can be inserted or reduced according to user need, and it has a good adaptability.
KW - Fault tree
KW - Integrated oil sensor
KW - Troubleshooting
KW - expert system
UR - http://www.scopus.com/inward/record.url?scp=85102151018&partnerID=8YFLogxK
U2 - 10.1109/SDPC49476.2020.9353188
DO - 10.1109/SDPC49476.2020.9353188
M3 - Conference contribution
AN - SCOPUS:85102151018
T3 - Proceedings of 2020 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2020
SP - 49
EP - 54
BT - Proceedings of 2020 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2020
A2 - Qin, Yong
A2 - Zuo, Ming J.
A2 - Yi, Xiaojian
A2 - Jia, Limin
A2 - Gjorgjevikj, Dejan
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2020
Y2 - 5 August 2020 through 7 August 2020
ER -