DC electric energy signal denoising method based on improved wavelet threshold and correlation detection

Abstract

A DC electric energy signal denoising method based on an improved wavelet threshold value and correlation detection comprises the steps that firstly, discrete wavelet decomposition is conducted on a signal sampled at a fixed frequency through the multi-resolution analysis theory, and therefore the high-frequency part is separated from the low-frequency part in the signal; then, an improved threshold function is designed to quantify the decomposed wavelet coefficient to reduce the influence of noise signals, and periodic mean filtering is performed on the wavelet coefficient in combination with a correlation detection method, so that the extraction effect of periodic signals is improved; and finally, wavelet inverse transformation is carried out on the reconstructed wavelet coefficient, and useful signals are recovered. Experimental results show that the denoising effect of the new threshold function is better than that of a traditional method, and the mixed algorithm has a better extraction effect on periodic signals.

Description

technical field [0001] The invention relates to a method for denoising a DC power signal based on improved wavelet threshold and correlation detection. Background technique [0002] In the process of verifying and calibrating DC watt-hour meters using the standard meter method electric energy verification device, it is usually necessary to configure the main energy standard to measure voltage and current values, and use the measured electric energy values ​​as the basis for error judgment of the tested meter. Therefore, the metrological accuracy of the master standard is critical to the results of verification and calibration. During the actual measurement process of the signal, the verification device is affected by the inherent noise source inside the electronic system or external interference, resulting in an error in the energy measurement. Therefore, it is necessary to perform noise reduction processing on the sampled signal before calculating the energy. . [0003] T...

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Problems solved by technology

[0005] Due to the constant deviation and discontinuity at the threshold of the traditional threshold function in wavelet threshold denoising, the reconstructed signal loses the edge local features of the real signal and additional oscillations appear. In order to overcome the deficiencies of the prior art, the present invention proposes a Improve the threshold function to solve the defects of the traditional function, and on the basis of the new threshold function to denoise the signal, use the correlation between the approximate coefficient after the wavelet transform and the useful signal to perform periodic mean filtering to improve the sampling accuracy of the electric energy signal

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