Research On Guided Wave Detection Of Small Defects In Polyurea Anti-corrosion Pipelines Based On Stochastic Resonance Properties Of Duffing System

In recent years,oil and gas pipelines have been widely used in the distribution of natural gas,petrochemical gas,oil and other energy sources in our country,which has promoted the rapid development of the national economy.However,the systematic oil and gas pipeline network is often buried for a long time,coupled with complex environmental factors,lead to the inner and outer layers of the pipeline are prone to corrosion or falling off to varying degrees,which have hidden great pipeline accidents such as gas or liquid leakage,resulting in serious pipeline accidents and significant economic damage or casualties.it is necessary to select reasonable anti-corrosion pipelines combined with efficient pipeline detection technology,which can effectively reduce the risk of accidents.In recent years,as a new type of anti-corrosion material,polyurea coatings have attracted much attention due to its excellent characteristics such as anti-corrosion and wear-resistant,green and harmless,which are widely used in the anti-corrosion coatings of pipe surface;At present,the detection of anti-corrosion pipelines mostly adopts the traditional ultrasonic pointby-point detection method,which takes a long time and requires a large amount of work.The ultrasonic guided wave detection technology propagates along the extension direction of the pipeline by exciting the signal at the end of the pipeline,which is very suitable for the detection of long-distance pipelines.However,the attenuation speed of ultrasonic guided wave propagation in polyurea anti-corrosion pipes is faster,coupled with the complexity of the detection environment and the influence of its own propagation characteristics.When detecting small defects in long-distance polyurea anti-corrosion pipelines,the guided wave signal tends to become very weak,and it is very likely to be overwhelmed by environmental noise,which makes it difficult to identify the defect features in the guided wave signal.Therefore,it is necessary to carry signal processing for the guided wave signal.Using the stochastic resonance effect of the nonlinear system can not only transfer the energy of the noise signal to the guided wave signal,reduce the interference effect of noise on the guided wave signal,but also can increase the amplitude of the output characteristic signal of the system,improve the intuitive identification ability of the characteristic signal of small defects,and beneficial to further research on the location of small defects.Therefore,this thesis proposes a guided wave detection method for small defects in polyurea anti-corrosion pipelines based on the stochastic resonance effect of the Duffing system.The main research contents of this thesis is as follows:(1)The basic principle of stochastic resonance characteristic of Duffing system and the preconditions to be satisfied.Since the stochastic resonance effect of the Duffing system is also limited by small parameters,it is necessary to quote the method of variable-scale stochastic resonance of the Duffing system,so that the stochastic resonance effect can still occur in the Duffing system under the condition of large parameters,and which provides the basis for the solution of the subsequent response to the Duffing system;In order to quantitatively describe the stochastic resonance effect produced by the Duffing system,a measure of the stochastic resonance effect was subsequently quoted.(2)Proposed a synchronous parameter tuning method based on the stochastic resonance effect of the Duffing system.In order to overcome a series of problems such as excessive dependence on human subjectivity in the adjustment and selection of parameters of the system in the current extensive research,which is not conducive to the interactive correlation between the parameters in the nonlinear system.Therefore,proposed a synchronous parameter tuning method based on the stochastic resonance effect of the Duffing system.At the same time,the relationship between the generation of the stochastic resonance effect of the Duffing system and the interaction of various parameters in the system is taken into account.Several groups of reasonably optimized parameter groups are selected,and then they are entered into the Duffing system one by one.After processing and analyzing the numerical signal in the system,and the optimal parameter group is selected.(3)Select the best fit parameter group for the Duffing system.Theoretical analysis is carried out through the analytical model of polyurea anti-corrosion pipeline,and the two-layer three-dimensional cylinder model of viscoelastic-elastic composite material is established by means of the finite element analysis software ABAQUS,and simulated the propagation state in which the L(0,2)modal guided wave with the different excited frequencies,processed by the Duffing system that produces the stochastic resonance effect,solved the characteristic signal of the output response.After that,the numerical signal,the mixed signal after adding white noise and the characteristic signal output by the system are compared with the timehistory curve and the power spectral density analysis respectively,and the optimal parameter set of the Duffing system is preliminarily selected.(4)A method for detecting small defect signals based on stochastic resonance characteristics of Duffing system based on windowed time-shift scanning.In order to analyze the feasibility of simulating the propagation of ultrasonic guided waves in polyurea anticorrosion pipelines by numerical simulation,and further realize the identification and location of small defects in the actual detection signal.The numerical simulation results are verified by means of experiments.At the same time,due to the conversion mode waveform that may exist in actual detection signal will cause identification interference to small defects,thus,proposed the method for dectecting small defects signal by using stochastic resonance effect of Duffing system based on time-moving window function scanning.This method mainly adopts the method of window function time-shift scanning to perform progressive segmental scanning on the collected experimental signals,and also performs synchronous power spectral density analysis on the segmented signals in the window,and marks output of the peak value of power in each segmented signal.Then arrange each segmented signal in the original time domain order,and connect the power peak points in each segmented signal through a broken line,showing the change relationship between the output power and time of the entire characteristic signal to achieve the purpose of positioning and identifying the defect signal.