Development of a method for noise suppression of a signal from pressure sensors on main gas pipelines using wavelet transformation

N. Darsalia, S. Kitaev, V. Muratova, R. Farukhshina
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Abstract

Natural gas produced in the Russian Federation is transported through main gas pipelines united into the Unified Gas Supply System of the Russian Federation. The system of main gas pipelines the most important link in the unified gas supply system – is a large, complex and continuously developing technological system. Maximum internal pressure is one of the key characteristics for any pipeline. This indicator helps to set the limit for the capacity of the pipeline (maximum volume of pumped gas per unit of time), its level of reliability, as well as the level of hazard and potential risk (the higher the pressure inside the pipeline, the more potential threat it carries). In order to increase the reliability of determining the pressure in the gas pipeline, it is proposed to perform noise suppression using a wavelet transform in the work. Noise reduction in the wavelet transform is carried out due to the fact that the signal is decomposed into approximating and detailing coefficients. After removing the detailing component, the decomposition is restored and the output is a slightly distorted signal. Thus, when you remove an insignificant part of the original signal, the graphs of the change in values become more visual. This paper compares the efficiency of wavelet based thresholding techniques in the presence of noise for various wavelet family. For comparison, the trend processing was performed by two types of wavelets recommended for noise reduction Symlet and Daubechies wavelets.
提出了一种利用小波变换对输气管道压力传感器信号进行噪声抑制的方法
俄罗斯联邦生产的天然气通过主要天然气管道输送到俄罗斯联邦统一天然气供应系统。燃气主管道系统是统一供气系统中最重要的环节,是一个庞大、复杂、不断发展的技术系统。最大内压是任何管道的关键特性之一。该指标有助于设定管道容量的限制(单位时间内泵送气体的最大体积),其可靠性水平,以及危害和潜在风险水平(管道内压力越高,其潜在威胁越大)。为了提高燃气管道压力检测的可靠性,提出了在工作中采用小波变换进行噪声抑制的方法。在小波变换中,由于信号被分解为近似系数和细节系数,因此进行了降噪。去除细节分量后,恢复分解,输出为微失真信号。因此,当您删除原始信号中不重要的部分时,值变化的图形变得更加直观。本文比较了不同小波族在噪声存在下基于小波的阈值分割技术的效率。为了比较,趋势处理是由两种类型的小波推荐的降噪Symlet和Daubechies小波。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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