Study on an Integral Algorithm of Load Identification Based on Displacement Response

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 19; p. 6403
• Main Authors: Xu, Xun, Zhu, Yashan, Tian, Kejing, Lin, Tingcan, Li, Yunyu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 25.09.2021; MDPI
• Subjects: basis function type; Genetic algorithms; Identification; integral algorithm; Load; load identification; noise robustness; Optimization
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s21196403

Load identification is a very important and challenging indirect load measurement method because load identification is an inverse problem solution with ill-conditioned characteristics. A new method of load identification is proposed here, in which a virtual function was introduced to establish integral structure equations of motion, and partial integration was applied to reduce the response types in the equations. The effects of loading duration, the type of basis function, and the number of basis function expansion items on the calculation efficiency and the accuracy of load identification were comprehensively taken into account. Numerical simulation and experimental results showed that our algorithm could not only effectively identify periodic and random loads, but there was also a trade-off between the calculation efficiency and identification accuracy. Additionally, our algorithm can improve the ill-conditionedness of the solution of load identification equations, has better robustness to noise, and has high computational efficiency.