Sensor Fusion in Analogue Circuit Fault Diagnosis Using Transferable Belief Model
- https://doi.org/10.2991/iccsee.2013.325How to use a DOI?
- analog circuit, fault diagnosis, transferable belief model, k-nearest neighbor rule from TBM, fault location, data fusion
In fault diagnosis of circuit fault diagnosis system using multi-sensor data fusion may not give reliable fault diagnosis result in cases when processing on inconsistent data carry inconsistent. In order to deal with such problems, This paper has developed an analog-circuit fault diagnostic system based on transferable belief model (TBM) and K-nearest neighbor rule from TBM. The proposed system has the capability to detect and identify fault components in an analog electronic circuit by analyzing its working temperature and testable voltage. Using K-nearest neighbor(KNN) rule to process the working temperature of component drastically enhances the testable information for fault detect, satisfying the need of fusing data from distinct evidence sources. The experimental results show that this system performs significantly better in fault diagnosis of analog circuits due to the proposed techniques.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Youhui Chen AU - Dong Cheng AU - Yimin Yang AU - Zan Xiao PY - 2013/03 DA - 2013/03 TI - Sensor Fusion in Analogue Circuit Fault Diagnosis Using Transferable Belief Model BT - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) PB - Atlantis Press SP - 1297 EP - 1301 SN - 1951-6851 UR - https://doi.org/10.2991/iccsee.2013.325 DO - https://doi.org/10.2991/iccsee.2013.325 ID - Chen2013/03 ER -