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In order to ensure the reliability of the structural design, it is necessary to know the external loads acting on the structure. In this paper, we propose a novel method to identify the dynamic loads based on function principles in the time domain. Assuming the external load remains constant within one micro segment, we establish a linear relations...
Citations
... Furthermore, a recursive approach for load identification through joint input-state estimation was developed by Meas et al. [18] and Lourens et al. [19]. Li et al. [20] innovatively calculated the relationship of concentrated loads in the time domain using function principles. As described above, these methods [16][17][18][19][20] are used in the identification of concentrated loads. ...
... Li et al. [20] innovatively calculated the relationship of concentrated loads in the time domain using function principles. As described above, these methods [16][17][18][19][20] are used in the identification of concentrated loads. In the space fitting technique, shape functions [21,22], basic functions [16], and generalized orthogonal polynomials [3][4][5][6] have been widely employed. ...
... For distributed dynamic load, the utilization of polynomial function and modal analysis has proven successful in converting a dynamic load, which encompasses two dimensions of space and time, into coefficient identification for a single-degree-of-freedom (SDOF) system. Ultimately, the successful identification of distributed dynamic loads with a sufficiently long duration and diverse forms on a continuum with an infinite number of degrees of freedom is achieved in the time domain, in contrast to the frequency domain proposed in [3][4][5][6], rather than the concentrated loads proposed in [16][17][18][19][20]. Moreover, the method employs acceleration response instead of strain proposed in [21,28], making it more convenient to measure in engineering applications. ...
This paper proposes a novel approach for identifying distributed dynamic loads in the time domain. Using polynomial and modal analysis, the load is transformed into modal space for coefficient identification. This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force, thereby achieving dimensionality reduction. The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain. Firstly, the algorithm establishes a recursion scheme based on convolution integral, enabling it to identify loads with a long history and rapidly changing forms over time. Secondly, the algorithm introduces moving mean and polynomial fitting to detrend, enhancing its applicability in load estimation. The aforementioned methodology successfully accomplishes the reconstruction of distributed, instead of centralized, dynamic loads on the continuum in the time domain by utilizing acceleration response. To validate the effectiveness of the method, computational and experimental verification were conducted.
Dynamic load localization and identification technology is very important in the structural design and optimization of aircraft. This paper proposes a non-global traversal method (NTM) for the fast positioning and recognition of dynamic loads on continuous beams. This method separates the load’s position and amplitude information in the modal space. Then, it constructs an interpolation function about position information, and converts load positioning to solving the zero point of the interpolation function. After determining the position of the dynamic load, the amplitude of the dynamic load is recognized. This method does not need to traverse all the position points globally, thereby greatly improving the efficiency of load positioning. Numerical simulations and experiments show that compared with the original variable separation fast positioning method (VSRPM), this method improves the calculation efficiency by more than 80% while maintaining the same recognition accuracy. NTM is a new method of great application value.
