Using Frequency B-Splines for an accurate and faster calculation of adaptive transforms for electric machines diagnosis

Pons-Llinares, Joan; Quijano-López, Alfredo; Bonet-Jara, Jorge; Vedreño-Santos, Francisco

Abstract

Early detection of faults in electric motors is crucial to prevent unplanned downtime and expensive repairs. Transient analysis through time-frequency transforms reveals important information on the motor condition. Computational time of these transforms becomes a problem when dealing with thousands of motors in just one industry. Researchers focus on obtaining the best quality results, usually using Gabor functions as t-f atoms. This paper shows how Frequency B-Splines can reach the same quality with nearly 40% less computational time. To achieve this goal, the slope criterion is applied to select the optimal atoms parameters. A formula that relates the slope of the Heisenberg Box of a FBS with its parameters is deduced. The proper time interval where the FBS must be defined is also determined. Results are shown not only with lab tests, but also through a field case.

Citation

Pons-Llinares, J., Quijano-López, A., Bonet-Jara, J., & Vedreño-Santos, F. (2024, May). Using Frequency B-Splines for an accurate and faster calculation of adaptive transforms for electric machines diagnosis. Presented at Electrimacs 2024, Castellón de la Plana, Spain

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Electrimacs 2024
• Start Date: May 27, 2024
• End Date: May 30, 2024
• Acceptance Date: Mar 18, 2024
• Deposit Date: Mar 18, 2024
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Series Title: Lecture Notes in Electrical Engineering
• Series ISSN: 1876-1100
• Book Title: ELECTRIMACS 2024: Selected Papers – Volume 1
• ISBN: 978-3-031-73920-0
• Public URL: http://researchrepository.napier.ac.uk/Output/3568658
• Publisher URL: https://link.springer.com/book/9783031739200
• Related Public URLs: https://electrimacs2024.uji.es/