摘要
为了减少A/D转换器测试集的冗余度,及其在故障诊断时的工作量大,征兆混淆等问题。文中建立了故障A/D转换器的输入输出模型,并采用最大相异性模型算法生成A/D转换器固定逻辑"0"故障和固定逻辑"1"故障的最小完备测试集。同时,提出了将A/D转换器数字输出向量在二元域GF(2N)空间中正交分解后分别提取特征量的方法来完成无噪声影响位和噪声影响位的故障识别。通过仿真验证表明:输入A/D转换器的测试电平数量减少了99.9%。本文生成的最小完备测试集不仅能够满足紧凑性条件和完备性条件,而且极大降低了测试向量的冗余度。本文提出的故障诊断方法提高了故障诊断的时间效率和准确度,解决了A/D转换器噪声影响位由于征兆混淆而无法完成故障识别的问题。
To reduce the redundancy of A/D converter test set and to deal with the problem of heavy workload and confounding syndromes in fault diagnosis, this paper establishes the input and output model for the fault A/D convert- er, and adopts the biggest dissimilarity model algorithm to generate A/D converter of minimum complete test set for the fixed logic ＂0＂ fault and fixed logic ＂1＂ fault. Meanwhile, The A/D converter digital output vector is orthogonally decomposed in GF （2N） for feature extraction, which is further used to complete the fault identification with and with- out noise bit. Simulation results show that the number of the test level for the input A/D converter is reduced by 99.9%. The minimum complete test set generated by this paper can not only satisfy the compactness completeness condition, but also greatly reduce redundant test vectors. The proposed fault diagnosis method improves diagnosis effi- ciency and accuracy, and solves the problem that the A/D converter under the influence of noise caused by confoun- ding syndromes cannot complete the fault identification.
出处
《电测与仪表》
北大核心
2014年第3期27-32,共6页
Electrical Measurement & Instrumentation
