Research And Application Of Oil Pipeline Leakage Detection Technology Based On Whale Optimization Algorithm

With the continuous development of the society and the increasing demand for material goods,the demand for oil resources in China is growing rapidly.According to statistics,the total length of oil and gas pipelines in China reached 1.65×10~5 km in 2020,and it is expected to reach 2.4×10~5 km by 2025.However,the average number of pipeline leaks per thousand kilometers in China is 3 per year,which has caused significant pollution and safety accidents.Therefore,a simple and efficient pipeline leak detection method is urgently needed.In this paper,we conducted research on petroleum pipeline leak detection technology based on whale optimization algorithm to address the above-mentioned issues.Firstly,in order to accurately describe the flow process of fluid inside the pipeline during a leak,the shear stress in the pipeline model was corrected based on the transient change of shear stress when the pipeline is leaking.Then,based on the flow parameters of petroleum pipelines,a modified shear stress-based leak model was established.Finally,the characteristic line method was used to solve the pipeline model,and the correctness of the model was verified by the Pipeline Studio simulation software.The results showed that the relative error of the pipeline model on the pressure along the pipeline did not exceed 1.5%,and the relative error of the calculated flow rate along the pipeline did not exceed 5.0%,confirming the accuracy of the model.Secondly,by analyzing the changes in flow parameters before and after the petroleum pipeline leak and combining the idea of anti-transient analysis,the pipeline leak location problem was transformed into an optimization problem,and a petroleum pipeline leak location model was established.Then,three optimization algorithms were used to solve the model,and the adaptability of the three algorithms in different working conditions was compared.Finally,the weight factor in the location model was compared and selected using the algorithm with the best adaptability.Analysis of multiple sets of data under different leak conditions showed that the whale optimization algorithm outperformed the other two algorithms in calculation time and adaptability to different working conditions.When the weight factor was set to 0.6 and 0.4,the whale optimization algorithm showed the best performance in petroleum pipeline leak location and leak aperture prediction.Finally,the influence of different parameters on the accuracy of petroleum pipeline leak location was analyzed,and based on the sensitivity of different parameters to location accuracy,the theoretical model of the small-scale pipeline leak experiment platform was modified,and the practicality of the petroleum pipeline leak detection technology based on whale optimization algorithm was verified.At the same time,a leak discrimination method based on flow imbalance was proposed.The experimental results showed that there was a delay of 4-9 seconds in the determination of whether a leak occurred using the discrimination method,and the location error ranged from 0.33%to6.67%,but there was a relatively large error in predicting the leak aperture.Based on the above research conclusions,the petroleum pipeline leak detection technology based on whale optimization algorithm has a certain feasibility in practical applications,but the location accuracy is greatly affected by noise and measurement instruments,and there is room for improvement.