| With the rapid development of social economy,people pay more and more attention to the utilization of green energy.As one of the representatives of green energy,natural gas is widely used.The effective supply of natural gas has become the key demand of many families and enterprises.Buried gas transmission pipelines are intricately distributed in various areas of the city.With the passage of time,the problems of pipeline aging and damage become more and more serious,and pipeline safety accidents occur frequently.Unlike oil pipeline leakage,natural gas leakage is often hidden and highly destructive because it is colorless and tasteless.Therefore,the society urgently needs a set of gas transmission pipeline monitoring system to realize effective pipeline leakage monitoring and accurate positioning.To solve the above problems,this paper designs a gas transmission pipeline leakage monitoring system based on VMD-SSA noise reduction and 1+N element linear array joint positioning method,which can monitor the pipeline information in real time and accurately locate the leakage when it occurs.The work done and corresponding achievements achieved in completing the system research are as follows:Firstly,this paper introduces the background of natural gas pipeline transportation,comprehensively compares the advantages and disadvantages of various detection methods,and selects the detection and positioning method based on leakage sound wave in combination with the future development trend and the needs of monitoring system.By analyzing the generation mechanism and noise source of pipeline leakage acoustic signal,combined with the characteristics of leakage acoustic wave and the limitations of traditional wavelet threshold noise reduction,a joint noise reduction algorithm of variational modal decomposition and singular spectrum analysis(VMD-SSA)is proposed.By introducing energy entropy and energy contribution rate,the problem that it is difficult to determine the number of modes and singular values in VMD method reconstruction is solved.The improved method is verified by experiments.The verification results show that the improved method has excellent performance in the noise reduction of leakage acoustic signal.The denoised signal can retain the characteristics of the original leakage signal to the greatest extent.Compared with wavelet soft threshold and VMD noise reduction methods,the average SNR increment of the improved method is increased by32.3% and 21.9% respectively;The reduction of RMSE increased by 17.6% and 10.1%respectively.Then,in the traditional 1+1 element linear array positioning model,the propagation speed of leakage acoustic signal is difficult to calculate,and most of them are replaced by theoretical values,resulting in high final positioning error.To solve this problem,a pipeline leakage location model based on 1+N element linear array and time delay estimation is proposed in this paper.The model can accurately calculate the leakage acoustic wave velocity and time delay,and improve the location accuracy by using the idea of taking the mean value of multiple calculations.The improved model is verified by experiments.The results show that the positioning effect is the best when N=4.Compared with the traditional 1+1-element linear array,the average error rate of 1+4element linear array in pipeline leakage positioning is reduced by 75.7%,which is a method with better positioning performance.Finally,this paper integrates the research contents of noise reduction and positioning algorithm,monitoring technology and software and hardware design,and designs a set of remote on-line monitoring system of gas transmission pipeline based on STM32 chip and NB-Io T technology.The hardware terminal of the system mainly includes MCU and its peripheral circuit module,sensor module for data acquisition,NB-Io T communication module,power supply module,program download circuit and GPS module.The improved joint positioning algorithm is embedded in the system,and the basic functions and accurate positioning performance of the designed system are verified by testing.Figure [101] Table [9] Reference [99]... |