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Updated: May 6, 2026

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
Published on: June 16, 2014
Denoising of ceramic detection signals based on the combination of variational modal decomposition optimized by
Jianping Luan1,2, Liping Liu3,4, Bo Cui1
1School of Artificial Intelligence, North China University of Science and Technology, 063210 Tangshan, China.
Abstract:
In response to the problem of noise interference in the knock detection signal received by the pickup in the ceramic sheet knock non-destructive testing, a noise removal method is proposed based on the improved secretary bird optimization algorithm (ISBOA) optimized variational mode decomposition (VMD) combined with wavelet thresholding. First, the secretary bird optimization algorithm is improved by using the Newton-Raphson search rule and smooth exploitation variation strategy. Second, the ISBOA is used to select the key parameters in the VMD. Third, the signal is subjected to the VMD decomposition to obtain the intrinsic mode functions (IMFs), and permutation entropy of each IMF component is calculated to divide it into effective signal component or noise component. Finally, the effective signal component is denoised by using improved wavelet thresholding, and the processed IMFs components are reconstructed to obtain the denoised signal. The denoising of simulated signal with 5 dB signal-to-noise ratio shows that the signal-to-noise ratio of the signal is improved by 11.59 dB and the root mean square error is reduced by 73.6%, which is the most significant denoising effect of the method compared to other similar algorithms. In addition, tests on the knock detection signals of ceramic pieces with different types of defects also show that the method has wide applicability and an excellent denoising effect.
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