Dimensionality reduction and reconstruction method of dummy biomechanics response based on adaptive autoencode

doi:10.3969/j.issn.1674-8484.2024.03.006

Abstract

Abstract:

A adaptive autoencoder was proposed to solve the problem of reducing and reconstructing the biomechanics response curve of collision dummy. The adaptive autoencoder method was constructed based on the standard autoencoder principle and the dummy biomechanics-response-curve characteristics with adding some constraints. The synthetic acceleration curve data were selected as sample data after data cleaning and sampling for the dummy-head gravity-center. The correlation number and the reconstruction mean square error of the standard autoencoder and the adaptive autoencoder are calculated; while the linear and nonlinear reduction and reconstruction ability were compared and verified for the adaptive autoencoder. The results show that the adaptive autoencoder has a reconstruction error of 2.6% for linear dimensionality and 2.4% for nonlinear dimensionality, while the covariance value is close to 0 for the low-dimensional data. Therefore, the adaptive autoencoder proposed in this paper implements linear and nonlinear dimensionality reduction and dimensionality reconstruction with a highly independent for the low-dimensional data.

Key words: vehicle safety, vehicle collision tests, dummy biomechanics response, dimensionality reduction technology, autoencoders

CLC Number:

U467

HOU Zhiping, ZHU Haitao, LIU Cancan, YANG Jialin. Dimensionality reduction and reconstruction method of dummy biomechanics response based on adaptive autoencode[J]. Journal of Automotive Safety and Energy, 2024, 15(3): 337-343.

Figures/Tables 10

References 16

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p	均方误差	低维数据间互相关系数
p	均方误差	最大值	最小值
50	0.032	5 152	0.180
40	0.050	4 209	0.004
30	0.130	2 401	0.030
20	0.350	1 402	0.580
10	1.480	2 004	7.780

p	均方误差	低维数据间互相关系数
p	均方误差	最大值	最小值
50	0.032	5 152	0.180
40	0.050	4 209	0.004
30	0.130	2 401	0.030
20	0.350	1 402	0.580
10	1.480	2 004	7.780

p	均方误差	低维数据间互相关系数
p	均方误差	最大值	最小值
50	0.026	0.035	0.000
40	0.130	0.071	0.000
30	0.440	0.099	0.000
20	0.930	0.135	0.000
10	1.750	0.017	0.000

p	均方误差	低维数据间互相关系数
p	均方误差	最大值	最小值
50	0.026	0.035	0.000
40	0.130	0.071	0.000
30	0.440	0.099	0.000
20	0.930	0.135	0.000
10	1.750	0.017	0.000

激活函数	标准自编码器均方误差	自适应自编码器均方误差
Leaky ReLU	0.016	0.024
Linear	0.032	0.026
SeLU	0.200	20.090
ReLU	0.750	16.280
Tanh	52.650	52.650