Identification of nonlinear hysteretic parameters by enhanced response sensitivity approach |
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| Institution: | 1. Department of Materials Science, Tampere University of Technology, P.O. Box 589, 33101 Tampere, Finland;2. Research & Development, Wärtsilä Finland Oy, P.O. Box 244, 65101 Vaasa, Finland;1. School of Architecture, Chonnam National University, Gwangju, Republic of Korea;2. Department of Architectural Engineering, Dankook University, Yongin, Republic of Korea;3. Department of Civil Engineering & Geological Sciences, Notre Dame University, IN, USA;1. CLP Power Wind/Wave Tunnel Facility, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;1. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China;2. Metals and Chemistry Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China;3. Ningxia University, Yinchuan 750021, China;1. University of Stuttgart, Stuttgart, Germany;2. Rice University, Houston TX, USA;3. University of Kassel, Kassel, Germany;4. École Centrale de Lyon, Lyon, France;5. Aix Marseille University, CNRS, Centrale Marseille, LMA, Marseille, France;6. École Nationale Supérieure d’Arts et Métiers Lille – LISPEN, Lille, France |
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| Abstract: | Hysteresis is a ubiquitous phenomenon describing the special nonlinear memory-based relation between the input and the output in many physical systems. Identifying the hysteretic parameters is the first step towards practical application of hysteretic models. In this paper, a general framework for parameter identification of nonlinear hysteretic models is developed based on the enhanced response sensitivity approach. To do so, three typical hysteretic models—Bouc–Wen model, bilinear model with kinematic hardening and bilinear model with equal yielding force are analyzed at first and the general way to model a structure with such hysteretic components is established thereafter. Then, the enhanced response sensitivity approach is presented for inverse parameter identification where the key lies in the sensitivity analysis and the trust-region constraint. Particularly, smoothing procedure is introduced to overcome the non-differentiability of bilinear hysteretic functions for sensitivity analysis of bilinear models. Numerical examples are studied to testify the feasibility and performance of the proposed approach. |
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| Keywords: | Enhanced response sensitivity approach Parameter identification Bouc–Wen hysteresis Bilinear hysteresis Smoothing procedure |
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