Gesture Recognition Based on EEMD and Cosine Laplacian Eigenmap

Li, Yue; Li, Junhuai; Tu, Pengjia; Wang, Huaijun; Wang, Kan

doi:10.1109/jsen.2023.3279555

Cited by 8 publications

(1 citation statement)

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“…[25] proposed an accurate location method of stacker track damage based on integrated empirical mode decomposition empirical mode decomposition and density-based noise application spatial clustering (DBSCAN). A gesture recognition method based on manifold learning is proposed on the basis of signal noise reduction [26]. Ref.…”

Section: Introductionmentioning

confidence: 99%

Noise Reduction Method for the Vibration Signal of Reactor CRDM Based on CEEMDAACN-SK

Liu,

Li,

Zhu

et al. 2023

Electronics

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The reactor control rod drive mechanism (CRDM) controls the startup, shutdown and power of the reactor; it is one of the key pieces of equipment to ensure the normal operation of the reactor. CRDM is complex, mainly composed of stator, rotor, bearing, roller, etc. The characteristic analysis of the vibration monitoring signal is one of the important methods of the CRDM state evaluation. In view of the characteristics of large noise interference and the difficulty in analyzing the vibration monitoring signal of CRDM, this paper proposes a noise reduction method for the vibration signal of CRDM based on complete ensemble empirical mode decomposition with adaptive amplitude correction noise and spectral kurtosis (CEEMDAACN-SK), which can deeply reduce the vibration signal of CRDM. Firstly, the proposed CEEMDAACN algorithm is used to decompose the vibration signal of CRDM to obtain multiple intrinsic mode functions (IMF). Then, the spectral kurtosis of each IMF component is analyzed to obtain the spectral kurtosis map of each IMF component, which is compared with the spectral kurtosis map of the original signal. Finally, the denoising reconstruction of the signal is carried out to obtain the final denoising signal. Through experimental analysis, the performance of the proposed CEEMDAACN-SK denoising algorithm is better than the complete ensemble empirical mode decomposition with adaptive noise and spectral kurtosis (CEEMDAN-SK) algorithm in terms of results. The method proposed in this paper can be applied not only to the vibration signal noise reduction of CRDM, but also to other equipment and fields, such as nuclear power main circulation pump and the chemical industry.

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Section: Introductionmentioning

confidence: 99%