Research on Denoising Method of Metal Magnetic Memory Signal

Abstract

As the main transportation mode of oil and gas, oil and gas pipelines play an irreplaceable role in energy transportation. Metal magnetic memory detection technology can detect early stress concentration and invisible damage, and can be detected under the action of the geomagnetic field, without the need to magnetize the pipeline in advance. Since the magnetic memory signal is relatively weak, the actual detected signal will be affected by environmental noise, sensor jitter, and pipeline surface deposits. Therefore, the magnetic memory signal needs to be denoised. In this paper, the translation invariant wavelet denoising method, which is improved based on wavelet threshold denoising method, is used to denoise the collected pipeline magnetic memory signals. The experimental results show that the signal-to-noise ratio (SNR) obtained by this method is 4.97 % higher than the unmodified wavelet threshold denoising, and 3.18 % higher than the SNR obtained by the particle swarm optimization wavelet threshold denoising.