A New Optimal Test Node Selection Method for Analog Circuit

Abstract

The existing test node selection methods of analog dictionary technique assume that the voltage gap of ambiguity group is 0.7 V. However, this technique is not always accurate to determine the right ambiguity gap for each fault mode. As the probability density of the circuit output approximately satisfies the normal distribution, an accurate technique is introduced to determine the ambiguity gap. Then, this paper proposes a new test node selection method with an extended fault dictionary and the overlapped area values. Firstly, the fault dictionary is constructed with the mean and standard variance values of node voltage. Then, the area detection table is generated by the overlapped area values under normal curves for ambiguity faults, which represent the failure probability of ambiguity faults. Finally, the optimal test node set is selected by fusing fault isolation and overlapped area information. The results show that the proposed method is effective to select the optimal test node set and improve the performance of analog fault diagnosis.

Test Point Selection Method for Analog Circuit Fault Diagnosis Based on Similarity Coefficient

“…If is rounded to 2 decimal places, = 1 and the fault-pair ( 1 , 2 ) can be isolated. Table. According to Luo's method [2], a fault dictionary is constructed with the mean and standard variance values of fault samples. If the fault dictionary is composed of fault modes and test points, the proposed fault-pair similarity coefficient criterion information table has 2 = ( ⋅ ( − 1))/2 rows of fault-pairs on the basis of combination formula and columns of test points.…”

“…Assume that a test point of the th column is and the fault-pair of the th row is and in the table; the mean and standard variance of and samples of a CUT on the test point can be found in the th column of the fault dictionary. And then, the similarity coefficient criterion ( ) of the normal distribution curves ( ) and ( ) on the test point can be calculated by formula (2). Therefore, the data in cells of the table is similarity coefficients' criterion of all fault-pairs.…”

“…The total test cost of the CUT can be reduced greatly. Although the exhaustive search method can select a global minimum test point set, the papers [1][2][3] pointed out that the method is NPhard and only suitable for small scale analog systems because of its high computational cost. Now, test point selection for analog circuit has become very difficult due to the high dense packages of chips and complex electronic system.…”

“…In order to discriminate these ambiguous faults and construct an integer-coded dictionary for analog circuit, the ambiguity set and the ambiguity gap (i.e., a diode drop 0.7 V) between ambiguity sets were introduced by Hochwald and Bastian firstly [5]. Subsequently, most of test point selection algorithms employ 0.7 V as the ambiguity gap, but it is proved by many practical test results that 0.7 V is not always effective and accurate [2,3]. In paper [14], 0.2 V was chosen as the ambiguity gap and an accurate fault-pair Boolean table technique for the test point selection was proposed, which overcame the shortcoming of the traditional integer-coded table that only a part of the faults can be isolated.…”

“…In paper [14], 0.2 V was chosen as the ambiguity gap and an accurate fault-pair Boolean table technique for the test point selection was proposed, which overcame the shortcoming of the traditional integer-coded table that only a part of the faults can be isolated. In paper [2], ambiguity gaps were determined by means and variances of the circuit responses because the tolerances of component parameters obey the normal distribution. According to the normal distribution characteristics, an overlapped area method was proposed to improve the accuracy of selecting the optimal test point set.…”