Chapter 16
Research on Extraction Method
of Fatigue State Magneto Acoustic
Emission Characteristic Parameters
Based on CEEMD
Sha Wu, Gongtian Shen, Zenghua Liu, Yongna Shen, and Zhinong Li
Abstract In view of the strong background interference of (MAE) signal and
the unique advantage of complementary ensemble empirical mode decomposition
(CEEMD), CEEMD is introduced into magneto acoustic emission signal processing.
A feature extraction method of MAE signal based on CEEMD algorithm is proposed.
In the proposed method, the signal is decomposed by the method of CEEMD, the
correlation coefficients of the decomposed eigenmode function (IMF) components
and the original signal are analyzed, and the IMF component with a large correlation coefficient with the original signal is retained. Then the components with large
correlation coefficients are reconstructed, and the feature parameters are extracted,
so that the interference can be effectively suppressed. The CEEMD algorithm can
reduce the energy difference between the reconstructed signal and the original signal
while maintaining the signal characteristics of the original signal. Finally, when the
characteristic parameter curve obtained from the reconstructed signal reaches the
yield strength of the material, the trend of the whole graph becomes smooth and
stable which accords with the actual situation and verifies the effectiveness of the
method.
16.1 Introduction
Ferromagnetic metal materials are often subjected to repetitive loads during longterm service. Even if the load stress on a single cycle is safe, plastic deformation,
creep and fatigue will often occur in the stress concentration area along with the
S. Wu · G. Shen (B) · Z. Liu · Z. Li
College of Mechanical Engineering and Applied Electronics Technology, Beijing University of
Technology, Beijing 100124, China
e-mail: shengongtian@csei.org.cn
S. Wu
e-mail: 597265536@qq.com
G. Shen · Y. Shen
China Special Equipment Inspection and Research Institute, Beijing 100029, China
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
G. Shen et al. (eds.), Advances in Acoustic Emission Technology, Springer Proceedings
in Physics 259, https://doi.org/10.1007/978-981-15-9837-1_16
171
Research on Extraction Method
of Fatigue State Magneto Acoustic
Emission Characteristic Parameters
Based on CEEMD
Sha Wu, Gongtian Shen, Zenghua Liu, Yongna Shen, and Zhinong Li
Abstract In view of the strong background interference of (MAE) signal and
the unique advantage of complementary ensemble empirical mode decomposition
(CEEMD), CEEMD is introduced into magneto acoustic emission signal processing.
A feature extraction method of MAE signal based on CEEMD algorithm is proposed.
In the proposed method, the signal is decomposed by the method of CEEMD, the
correlation coefficients of the decomposed eigenmode function (IMF) components
and the original signal are analyzed, and the IMF component with a large correlation coefficient with the original signal is retained. Then the components with large
correlation coefficients are reconstructed, and the feature parameters are extracted,
so that the interference can be effectively suppressed. The CEEMD algorithm can
reduce the energy difference between the reconstructed signal and the original signal
while maintaining the signal characteristics of the original signal. Finally, when the
characteristic parameter curve obtained from the reconstructed signal reaches the
yield strength of the material, the trend of the whole graph becomes smooth and
stable which accords with the actual situation and verifies the effectiveness of the
method.
16.1 Introduction
Ferromagnetic metal materials are often subjected to repetitive loads during longterm service. Even if the load stress on a single cycle is safe, plastic deformation,
creep and fatigue will often occur in the stress concentration area along with the
S. Wu · G. Shen (B) · Z. Liu · Z. Li
College of Mechanical Engineering and Applied Electronics Technology, Beijing University of
Technology, Beijing 100124, China
e-mail: shengongtian@csei.org.cn
S. Wu
e-mail: 597265536@qq.com
G. Shen · Y. Shen
China Special Equipment Inspection and Research Institute, Beijing 100029, China
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
G. Shen et al. (eds.), Advances in Acoustic Emission Technology, Springer Proceedings
in Physics 259, https://doi.org/10.1007/978-981-15-9837-1_16
171