摘要：Since leaks in high-pressure pipelines transporting crude oil can cause severe economic losses, a reliable leak risk assessment can assist in developing an effective pipeline maintenance plan and avoiding unexpected incidents. The fast and accurate leak detection methods are essential for maintaining pipeline safety in pipeline reliability engineering. Current oil pipeline leakage signals are insufficient for feature extraction, while the training time for traditional leakage prediction models is too long. A new leak detection method is proposed based on time-frequency features and the Genetic Algorithm-Levenberg Marquardt (GA-LM) classification model for predicting the leakage status of oil pipelines. The signal that has been processed is transformed to the time and frequency domain, allowing full expression of the original signal. The traditional Back Propagation (BP) neural network is optimized by the Genetic Algorithm (GA) and Levenberg Marquardt (LM) algorithms. The results show that the recognition effect of a combined feature parameter is superior to that of a single feature parameter. The Accuracy, Precision, Recall, and F1score of the GA-LM model is 95%, 93.5%, 96.7%, and 95.1%, respectively, which proves that the GA-LM model has a good predictive effect and excellent stability for positive and negative samples. The proposed GA-LM model can obviously reduce training time and improve recognition efficiency. In addition, considering that a large number of samples are required for model training, a wavelet threshold method is proposed to generate sample data with higher reliability. The research results can provide an effective theoretical and technical reference for the leakage risk assessment of the actual oil pipelines. ? 2023 The Authors

ISSN号：1672-5107

卷、期、页：卷20期5：3194-3209

发表日期：2023-10-01

影响因子：0.000000

期刊分区（SCI为中科院分区）：二区

收录情况：SCI（科学引文索引印刷版）,CSCD（中国科技引文期刊）（核心）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：Petroleum Science

参与作者：李昱奇

通讯作者：孙海波,林泽庆

第一作者：王莹莹,杨进,吴世德,王文明

论文类型：期刊论文

论文概要：王莹莹,孙海波,杨进,吴世德,王文明,李昱奇,林泽庆，A reliability-oriented genetic algorithm-levenberg marquardt model for leak risk assessment based on time-frequency features，Petroleum Science，2023，卷20期5：3194-3209

论文题目：A reliability-oriented genetic algorithm-levenberg marquardt model for leak risk assessment based on time-frequency features