Diagnosis in Analog Electronic Circuits, Electrical Power Systems and Smart Grids

• Published in: Electronics (Basel) Vol. 11; no. 13; p. 2008
• Main Authors: Piccirilli, Maria Cristina, Luchetta, Antonio
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2022
• Subjects: Analog circuits; Automation; Circuits; Conflicts of interest; Electric power systems; Electronic circuits; Error correction; Fault diagnosis; Frequency measurement; Machine learning; Neural networks; Radiation; Smart grid; Testability; Tolerances
• DOI: 10.3390/electronics11132008
• ISSN: 2079-9292

[...]in terms of a machine, it is important tracing back to the causes that have produced an anomaly, typically a fault, or possibly a design error; in any case something that, once identified, must be corrected. If automatic diagnosis tools are common in the digital world, in the analog field, dominated by more complex phenomena, the same level of automation has not yet been reached and the development of this kind of tools is still an open research subject, on which researchers and industrial engineers are intensively working [2]. The technique is based on three sequential steps: the first one is the calculation of testability and ambiguity groups of the circuit under test; the second one is the location of the failure and its correct fault class via multi-frequency measurements; the third step is the estimation of the value of the faulty component, taking into account the fabrication tolerances of the components.