An adaptive parameter optimization algorithm for simultaneous identification of force location and history with sparse calibration array

Abstract

An adaptive parameter optimization algorithm (APOA) is proposed for simultaneous force history and location identification in this work. Because extensive calibrations are time consuming and not suitable for real structures, the APOA is designed to work with sparse calibration array, improving the efficiency in modeling the whole plate structures. In order to verify the effectiveness of the proposed method, numerical simulations and experimental impact tests are carried out. Various force profiles and locations are considered in numerical simulations, with an 80 mm × 100 mm rectangle calibration area. Furthermore, multiple impacts and calibration areas are discussed in experimental tests, with an aluminum plate as the specimen and an impulse hammer as the impactor. An 80 mm × 80 mm area is calibrated by a 9 × 9 array. Force identification results show good performance in using the AOPA, including the stability of force locating, the accuracy of time history estimation and the adaptability under sparse calibration.