|
|
|
| Soft-Fault Detection and Location for Circuits With Tolerance |
| Peng Minfang1, Shen Meie2, He Jianbiao3, Xie Hong1, He Yigang1 |
| 1. Hunan University Changsha 410082 China; 2. Beijing University of Information Science and Technology Beijing 100101 China; 3. Central South University Changsha 410083 China |
|
|
|
|
Abstract Based on statistics theory, neural network and data fusion, a new fault diagnosis method capable of soft-fault detection and location in analog circuits with tolerance is proposed. The proposed diagnosis strategy consists of fault detection and fault location. By monitoring accessible node voltages, on-line fault detection is performed based on the proposed fault threshold function and the fault criterion. Then circuit gains are measured under selected test frequencies. Based on circuit gains and accessible node voltages, off-line fault location is performed by the proposed data fusion method and improved BP algorithm. The simulation results show that the proposed approach has the capability to detect and locate not only catastrophic faults but also parametric faults in tolerance circuits with a small quantity of accessible nodes, and the diagnosis accuracy is satisfactory.
|
|
Received: 15 August 2008
Published: 12 February 2014
|
|
|
|
|
|
[1] Cannas Barbara, Fanni Alessandra, Manetti Stefano, et al. Neural network-based analog fault diagnosis using testability analysis[J]. Neural Computing & Applications, 2004, 13(4): 288-298.
[2] Catelani M, Fort A．Soft fault detection and isolation in analog circuits: some results and a comparison between a fuzzy approach and radial basis function networks[J]. IEEE Transactions on Instrumentation and Measurement, 2002, 51(2): 196-202.
[3] Wang Peng, Yang Shiyuan. A new diagnosis approach for handling tolerance in analog and mixed-signal circuits by using fuzzy math[J]. IEEE Trans. on CAS 1, 2005, 52(10): 2118-2127.
[4] 陈光, 李为民.一种基于神经网络的ICCAT专家系统测试方法的研究[J]. 电子学报, 1994, 22(8): 24- 29.
[5] 蔡一兵, 蔡金燕, 杨士元. 一种基于贝叶斯决策理论的模糊集划分方法[J]. 计算机学报, 1998, 21(11): 1053-1056.
[6] 崔莼, 罗先觉, 邱关源. 故障诊断交流字典法的前向神经网络实现方法[J]. 微电子学, 1996, 26(5): 313-318.
[7] 王淑娟, 陈博, 赵国良. 基于小波包变换预处理的模拟电路故障诊断方法[J]. 电工技术学报, 2003, 18(4): 118-122.
[8] 朱大奇, 于盛林. 基于D-S证据理论的数据融合算法及其在电路故障诊断中的应用[J]. 电子学报, 2002, 30(2): 221-223.
[9] 孙永奎, 陈光, 李辉. 基于可测性分析和支持向量机的模拟电路故障诊断[J]. 仪器仪表学报, 2008, 29(6): 1182-1186.
[10] 唐静远, 师奕兵, 张伟. 基于支持向量机集成的模拟电路故障诊断[J]. 仪器仪表学报, 2008, 29(6): 1216-1220.
[11] 彭敏放, 何怡刚, 王耀南, 等. 模拟电路的融合智能故障诊断[J]. 中国电机工程学报, 2006, 26(3): 19-24.
[12] 彭敏放, 何怡刚, 沈美娥, 等. 基于多目标遗传优化的容差电路故障屏蔽诊断[J]. 电工技术学报, 2006, 21(3): 118-122.
[13] Guo Zhen, Savir Jacob. Coefficient-based test of parametric faults in analog circuits[J]. IEEE Transactions on Instrumentation and Measurement, 2006, 55(1): 150-157.
[14] 蔡金锭, 马西奎, 黄东泉. 电子电路故障诊断的一种新方法[J]. 通信学报, 2001, 22(9): 43-49.
[15] Liu Fang, Ozev S. Statistical test development for analog circuits under high process variations[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2007, 26(8): 1465-1477.
[16] Grasso F, Luchetta A, Manetti S, et al. A method for the automatic selection of test frequencies in analog fault diagnosis[J]. IEEE Transactions on Instrumentation and Measurement, 2007, 56(6): 2322 -2329.
[17] Voorakaranam R, Akbay S S, Bhattacharya S, et al. Signature testing of analog and RF circuits: algorithms and methodology[J]. IEEE Trans. on CAS Ⅰ, 2007, 54(5): 1018-1031.
[18] Pengminfang, Heyigang. A new fault dictionary method for diagnosis of tolerance circuit[C]. Proceedings IIIS International Conf. on CCCT, U S A, 2004, 1: 378- 382.
[19] Verma B. Fast training of multilayer perceptrons [J]. IEEE Trans. on Neural Networks, 1997, 8(6): 1314- 1320.
[20] 杨建刚. 人工神经网络实用教材[M]. 浙江: 浙江大学出版社, 2002.
[21] 阎平凡, 张长水. 人工神经网络与模拟进化算 法[M]. 北京: 清华大学出版社, 2005. |
|
|
|
2009, Vol. 24 
