Minimizing Off-Axis Bending Effects on Flexible Surface Acoustic Wave Sensing Powered by Integrated Machine Learning Algorithms

• Published in: IEEE transactions on industrial electronics (1982) Vol. 72; no. 3; pp. 3194 - 3201
• Main Authors: Ji, Zhangbin, Zhou, Jian, Guo, Yihao, Xia, Yanhong, Liang, Dongfang, Fu, Richard
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antiinterference; Bending; Bending machines; Deformation effects; flexible SAW detection; Jet engines; Machine learning; Monitoring; off-axis bending; Parameters; Resonant frequency; Sensors; Strain; Surface acoustic wave devices; Surface acoustic waves; temperature; Temperature sensors
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2024.3436600

Flexible surface acoustic wave (SAW) sensors have gained significant attention due to their favorable attributes such as conformability to curved surfaces, wireless/passive functions, and digital outputs. However, bending, especially complex off-axis bending deformation, often causes severe interference to the targeted detection signals with flexible SAW sensors, limiting their accurate monitoring on the curved/deformed surfaces. To address such a critical issue, we selected AlScN/ultrathin flexible glass-based SAW devices as an example, chose temperature as the targeted sensing parameter, and developed a model based on machine learning algorithms to minimize complex off-axis bending effects in temperature monitoring. Response characteristics of the flexible SAW devices to temperature variations and off-axis deformations were experimentally and theoretically investigated. Correlations between device's responsive features and target parameter (temperature) were established using eight machine -learning algorithms. The optimized model was established with a normalized root mean square error of less than 1% and the determination coefficient R 2 was larger than 0.997 for temperature predictions subject to complex off-axis strain perturbations. Finally, the flexible SAW sensor showed a highly consistent temperature sensing capability under arbitrary off-axis bending conditions on a curved surface of a jet engine model.