Fault prognostics in analog Electronic circuits using soft Computing techniques

Abstract

Analog circuits play an important role in industrial automation to newlineimprove the quality of products and amount of production. The failure in the newlinecircuit is subject to defects or errors. A fault may be described as something newlineother than the anticipated action and alteration of the characteristic aspect that newlinemay cause a breach or refusal in the operation of an entire system that causes newlinefailures. In analog circuits, the parametric fault does not generally mean newlinefailure, but variations in operational and environmental conditions may affect newlinesystem data to show anomaly, and it is much more difficult to identify and newlineevaluate faults due to complicated circuit design, the interdependence of newlinecomponent functionality, nonlinearity problems, component aging, newlinetemperature drift, and compo. However, this kind of anomaly information is newlineuseful in the health management system, since the device needs to detect a newlinefailure in a timely way so that the affected parts can be quickly changed to newlinemaintain the normal functionality of the system. newlineThe electronic system generally consists of digital circuits and newlineanalog circuits. Nevertheless, there is still research in the current state into newlinefault diagnosis techniques and prognosis for analog circuits. Different newlineappropriate smart algorithms are necessary for real-time diagnosis and newlineforecasting. Also, appropriate data for selecting and evaluating smart newlinealgorithms are required. Moreover, hard defects like open or short circuits are newlinenot normal, but parametric defects, such as parameter deviation, normally newlineincreases. Therefore it is better to simulate and collect parametric faults and newlineavoid circuit failure through diagnosis and prognosis approaches newline