Impact load identification and response reconstruction based on updating-combination regularization
Hong YIN1(),Yonghe SHI1,Zhenrui PENG1,*(),Zenghui WANG2
1. School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China 2. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
An impact load identification and structural response reconstruction method based on the updating-combination regularization was proposed aiming at the problems of low accuracy in identifying peak impact loads, oscillation in identifying non loading areas, and susceptibility to noise interference in traditional regularization methods for structural response reconstruction. The reconstruction equations for the impact load and structure response were derived based on the state space model. The difference between the denoised response and the identification response was used to update the L2 regularization solution. Then higher accuracy peak identification results were obtained combining with the L1 regularization solution that had sparsity advantage while ensuring the stability of the identification of impact load in unloaded region, which realized the reconstruction of structural dynamic responses. The proposed method was verified through numerical and experimental cases, and the effect of response reconstruction based on the transfer matrix method and the particle filter method was compared. Results show that the proposed method has good anti-noise performance. The method can accurately recognize the impact load, and effectively reconstruct the dynamic response of the structure.
Hong YIN,Yonghe SHI,Zhenrui PENG,Zenghui WANG. Impact load identification and response reconstruction based on updating-combination regularization. Journal of ZheJiang University (Engineering Science), 2024, 58(5): 1029-1039.
Fig.2Flow chart for load identification and response reconstruction
Fig.3Finite element model of wheelset
Fig.4Picard diagram
Fig.5GCV function diagram
Fig.6Impact load identification results by different regularization methods
噪声因子
RPEf
L2正则化
L1正则化
Luc正则化
0.03
11.40
10.28
4.45
0.05
13.19
11.40
3.60
0.10
17.31
16.53
3.65
0.30
26.63
31.08
7.86
Tab.1Load recognition errors under different noises %
Fig.7Response reconstruction results of D and E nodes
Fig.8Response reconstruction errors by different regularization methods
重构方法
正则化方法
RPEY
D节点 速度
D节点 加速度
E节点 速度
E节点 加速度
传递 矩阵法
L2
6.15
8.12
6.01
8.14
L1
4.46
10.04
4.35
10.05
Luc
0.90
1.44
0.88
1.44
粒子 滤波法
L2
6.15
8.12
6.01
8.13
L1
4.47
10.04
4.35
10.05
Luc
0.90
1.45
0.89
1.45
Tab.2Reconstruction errors by different methods %
Fig.9Extending beam
Fig.10Framework diagram of modal test on extending beam
Fig.11Picard diagram
Fig.12GCV function diagram
Fig.13Impact load identification results by different regularization methods
Fig.14Results of response reconstruction
重构方法
正则化方法
RPEY
第8节点加速度
第17节点加速度
传递矩阵法
L2
17.34
17.47
L1
14.67
14.37
Luc
17.59
11.72
粒子滤波法
L2
4.93
5.61
L1
5.86
5.87
Luc
17.39
8.02
Tab.3Comparison of reconstruction errors under different regularization methods %
重构方法
正则化方法
RPEY
第8节点加速度
第17节点加速度
传递矩阵法
L2
14.93
17.89
L1
12.43
15.15
Luc
9.15
8.61
Tab.4Comparison of reconstruction errors by different regularization methods without considering model errors %
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