Research On Filtering Algorithm And Its Application For Parameters Within Natural Gas Gathering And Transmission Pipeline Under Duty Cycle Mechanism

With the advent of the "Internet+" and other intelligent times,China’s digital development has been greatly promoted.Among them,the safe transportation of oil and gas pipelines has basically realized digital management.With the increasing scale of China’s oil and gas pipeline network in recent years,digital oil and gas pipelines are gradually transforming into intelligent oil and gas pipelines.Wireless sensors installed on oil and gas pipelines such as pressure,flow,temperature,etc.transmit data of production in oil and gas pipelines in real time through wireless communication technology to ensure safe and smooth operation of the pipelines,while energy saving in the process of information transmission is also of great concern.In order to ensure the sustainability in the oil field,reduce the energy consumption in the communication process,and extend the service life of sensor node batteries,energy-saving wireless transmission is gradually being widely used in the current intelligent oil and gas pipeline information communication construction.Based on this,it is a great challenge to ensure the high accuracy of the monitored pipeline internal parameters under the low-power wireless transmission mechanism for monitoring the operating conditions of the pipeline and performing leak detection,etc.In this paper,recursive filtering is used as a key technique to investigate the above problem,and the specific work is as follows.To begin with,a continuous time state space model of the natural gas pipeline flow system under ideal conditions is given in this paper and discretized by applying control theory methods.The parameterized discrete-time state space model is obtained by combining the actual working conditions of the pipeline.Considering that the measurement and transmission process of sensors will inevitably be disturbed by noise in practical engineering applications,the paper further gives a discrete-time model of the natural gas pipeline flow system containing noise.Then,the paper considers the current low-carbon energy saving goal in intelligent oil and gas pipelines,and introduces an energy-saving wireless transmission mechanism in the communication process,i.e.,Duty Cycle Transmission Mechanism(DCTM).DCTM can also be applied to applications with low network bandwidth and limited channel capacity,which can not only reduce the energy consumption of the communication process It can also extend the lifetime of sensor nodes.On the other hand,high energy efficiency may induce increased sparsity of measurement data,which affects the filter performance.Then,for the problem of sparse measurement data,this paper introduces the Collaborative Filtering(CF)algorithm to predict the sparse data and use the compensated complete data as the measurement input of the filter.So far,this paper gives a new recursive filtering algorithm under DCTM combined with CF algorithm.To ensure the performance of the designed filter,the error covariance matrix is derived and the boundedness of its upper bound is proved.The gain matrix of the designed filter is then further obtained by minimizing the trace of the error covariance matrix.And the simulation is carried out by MATLAB to verify that the given filtering scheme can effectively estimate the internal parameters in the natural gas pipeline with energy saving,i.e.,the pressure and flow parameters of the natural gas inside the pipeline after filtering the noise are obtained.The excellent performance of the recursive filtering algorithm given in this paper is comprehensively verified.Finally,this paper analyzes the natural gas pipeline for leak detection based on the previous study.First,a set of actual measurements under normal operating conditions is given by experimental simulation,and the pressure and flow parameters of the natural gas inside the pipeline to be analyzed are further valued by using the recursive filter in this paper under known boundary conditions,and the residuals between the actual measurements and the estimated values of the model are used as a criterion to discriminate the operating conditions of the pipeline,and a threshold interval is set.Then,the pressure and flow parameters of the pipeline are collected and compared with the estimated values of the model to calculate the residuals,and when the residuals exceed the preset threshold interval,the pipeline is judged to be leaking.Therefore,the recursive filtering algorithm designed in this paper can guarantee the high accuracy of the monitored internal parameters of the pipeline under the duty cycle communication mechanism,achieve reliable monitoring of the pipeline operating conditions while saving energy,and be applied to pipeline leakage detection.