Testability Analysis Method of Radar Equipment Based on Dependency Model

In order to improve the testability design level of radar equipment, achieve rapid detection and isolation of faults, and reduce the life cycle cost of the system, a testability analysis method of radar equipment based on correlation model is proposed. The basic process of correlation model modeling is introduced. On this basis, the optimization method of test points for fault detection and isolation and the generation method of fault diagnosis strategy are analyzed. The effectiveness of the proposed method is verified by applying it to radar transmitting subsystem.

A Neural Network Classifier with Multi-Valued Neurons for Analog Circuit Fault Diagnosis

In this paper, we present a new method designed to recognize single parametric faults in analog circuits. The technique follows a rigorous approach constituted by three sequential steps: calculating the testability and extracting the ambiguity groups of the circuit under test (CUT); localizing the failure and putting it in the correct fault class (FC) via multi-frequency measurements or simulations; and (optional) estimating the value of the faulty component. The fabrication tolerances of the healthy components are taken into account in every step of the procedure. The work combines machine learning techniques, used for classification and approximation, with testability analysis procedures for analog circuits.

A Novel Method for Detecting Parametric Faults in Analog Circuits using Fuzzy Logic

The demand for testability analysis of analog circuits has been increased in recent years. The fault detection and fault classification method is important in detecting the parametric faults of the circuit. In this paper, Simulation Before Test (SBT) is considered as a basic mechanism for detecting the parametric faults.. The circuit Under Test (CUT) used is Sallen-Key bandpass filter. Transfer function of the CUT is used for fault detection by locating the poles and Zeros of the transfer function. Fuzzy logic is used for fault classification.