Tue, 18 February, 2025
Congratulations to the authors of the paper: A New Multi-sensor, Partial Domain Adaptation Method for Machinery Fault Diagnosis Under Different Working Conditions, which has won the IEEE Instrumentation and Measurement Society Andy Chi Best Paper Award 2024.
In the paper, authors Darren Williams, Director of the Joining 4.0 Innovation Centre (J4IC): a strategic partnership between Lancaster University and TWI, Jun Zhu and Yuanfan Wang, both of Northwestern Polytechnical University, Min Xia, Lancaster University and Clarence W de Silva of the University of British Columbia propose a new method of multi-sensor, partial domain adaptation (DA) fault diagnosis.
As explained in the paper, which was published in IEEE Transactions on Instrumentation and Measurement, Vol. 72, a journal of the IEEE Instrumentation & Measurement Society, “Cross-domain fault diagnostic methods based on DA have been developed for single-sensor monitoring scenarios, in which the source and target domains fall into the same categories. However, in real-world situations, faults are usually mixed with each other, and the target health category is a subspace of the source health category, posing challenges to the current cross-domain fault diagnostic approaches.”
The annual prize, presented for the first time in 1984 and named after Mr Andrew (Andy) R Chi who was Editor-in-Chief of the publication from 1978 to 1983, awards a range of criteria including the importance of the subject matter and how it is communicated to non-experts, timeliness, organisation and having a logical structure, utilisation of illustrative materials, tables and figures, and the ability to stimulate interest in the IEEE Transactions on Instrumentation and Measurement journal.
Professor Darren Williams, Director of the J4IC, who also oversaw the paper, expressed his, and his co-authors, delight at winning this prestigious award, which will be presented at 12MTC 2025, the flagship conference of the IEEE Instrumentation and Measurement Society, dedicated to advancing measurement methodologies, measurement systems, instrumentation and sensors in all areas of science and technology.
Read an Abstract of the paper: A New Multi-sensor, Partial Domain Adaptation Method for Machinery Fault Diagnosis Under Different Working Conditions.