Treffer: Design of Artificial Intelligence-Based Novel Device for Fault Diagnosis of Integrated Circuits

Title:
Design of Artificial Intelligence-Based Novel Device for Fault Diagnosis of Integrated Circuits
Authors:
Pavan Sai Kiran Reddy Pittu, Vijayalakshmi Sankaran, Paramasivam Alagu Mariappan, Gauri Pramod, Nikita, Yash Sharma
Source:
Engineering Proceedings, Vol 58, Iss 1, p 77 (2023)
Publisher Information:
MDPI AG
Publication Year:
2023
Collection:
Directory of Open Access Journals: DOAJ Articles
Subject Terms:
deep learning, fault diagnosis, object detection, temperature variation, thermal camera, YOLO algorithm, Engineering machinery, tools, and implements, TA213-215
Document Type:
Fachzeitschrift article in journal/newspaper
Language:
English
Relation:
https://www.mdpi.com/2673-4591/58/1/77; https://doaj.org/toc/2673-4591; https://doaj.org/article/7fa4432af14946e5a34ae70c3246fdb5
DOI:
10.3390/ecsa-10-16242
Availability:
https://doi.org/10.3390/ecsa-10-16242
https://doaj.org/article/7fa4432af14946e5a34ae70c3246fdb5
Accession Number:
edsbas.73075CC9
Database:
BASE

Weitere Informationen

The rapid advancement of integrated circuit (IC) technology has revolutionized various industries, but it has also introduced challenges in detecting faulty ICs. Traditional testing methods often rely on manual inspection or complex equipment, resulting in time-consuming and costly processes. In this work, a novel approach is proposed which uses a thermal camera and an Internet of Things (IoT) physical device, namely a Raspberry PI microcontroller, for the detection of faulty and non-faulty ICs. Further, a deep learning algorithm, namely You Only Look Once (YOLO), is coded inside the Raspberry PI controller using Python programming software to detect faulty ICs efficiently and accurately. Also, the various images of faulty and non-faulty ICs are used to train the algorithm and once the algorithm is trained, the thermal camera along with the Raspberry PI microcontroller is used for the real-time detection of faulty ICs and the YOLO algorithm analyzes the thermal images to identify regions with abnormal temperature patterns, indicating potential faults. The proposed approach offers several advantages over traditional methods, including increased efficiency and improved accuracy.