Pipeline integrity detection method of oil and gas station based on image processing
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摘要: 结合图像处理技术,提出了一种油气站场管道完整性检测方法。检测时通过管道机器人采集油气站场管道图像。为提高图像质量,需对采集到的原始图像进行处理。针对预处理好的图像,标记图像缺陷区域,提取缺陷面积、周长、圆形度、长轴与短轴之比、梯度等5个几何特征参数。以这5个几何特征参数为输入,通过DBN (深度置信网络)构建分类器进行油气站场管道完整性检测。结果显示缺陷识别质量指数均大于8.0,说明该方法的检测结果较为准确,可以用于实际油气站场管道的完整性检测。Abstract: Combined with image processing technology, a pipeline integrity detection method for oil and gas station is proposed. In the research, the pipeline image of oil and gas station is collected by pipeline robot. In order to improve the image quality, the collected original image is processed. For the preprocessed image, the image defect area was marked and the following five geometric feature parameters were extracted, which were the defect area, defect perimeter, defect roundness, the ratio of defect long axis to short axis, and defect gradient. Taking these five geometric characteristic parameters as inputs, the classifier is constructed by DBN (depth confidence network) to detect the pipeline integrity of oil and gas stations. The results show that the quality index of defect identification is greater than 8. 0, which shows that the integrity detection result of this method is more accurate and can be used in the integrity detection of pipelines in actual oil and gas stations.
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[1] 张梅,张双双,袁宏永,等.燃气管道泄漏的次声源定位算法研究[J].电子测量与仪器学报,2020,34(3):187-194. [2] 郑晓亮,王强,薛生.输气管道泄漏的线性阵列两步定位方法[J].仪器仪表学报,2020,41(6):171-178. [3] 许少波,罗琪.超声波流量计在输油管道泄露监测系统中的应用[J].电视技术,2019,43(10):68-70. [4] 杨辉,王富祥,王婷,等.基于漏磁内检测的管道补口失效识别与判定方法[J].油气储运,2019,38(5):516-521. [5] 王贵愚,方睿,孙凯,等.基于STA/LTA的输油管道泄漏检测方法[J].北京理工大学学报,2020,40(7):760-764. [6] 王振,赵霞,孙震,等.基于光纤传感的长输管道破坏预警技术研究[J].工业安全与环保,2019,45(11):27-30. [7] 梁凤勤,高媛,刘功银,等.基于AutoEncoder的油气管道控制系统异常状态监测方法[J].电子测量与仪器学报,2019,33(12):10-18. [8] 李平,梁丹,梁冬泰,等.自适应图像增强的管道机器人缺陷检测方法[J].光电工程,2020,47(1):190304. [9] 陈宁,陈本均,白冰.基于红外视频的加油枪油气泄漏检测方法[J].激光与红外,2019,49(10):1217-1222. [10] 袁明道,谭彩,李阳,等.基于图像融合和改进阈值的管道机器人探测图像增强方法[J].煤田地质与勘探,2019,47(4):178-185. [11] 王拯洲,李刚,王伟,等.基于邻域向量主成分分析图像增强的弱小损伤目标检测方法[J].光子学报,2019,48(7):75-86. [12] 李万润,张建斐,王雪平,等.基于图像处理技术的风电叶片表面划痕特征提取方法研究[J].太阳能学报,2020,41(12):278-287. [13] 刘祚时,周继雯,俞跃,等.油气管道聚乙烯层粘接缺陷的红外热成像检测方法和信号增强技术研究[J].中国测试,2019,45(11):1-8. [14] 高一凡,蔡静,张学聪,等.基于NETD的红外热像仪图像预处理方法研究[J].计量学报,2019,40(6):1020-1024. [15] 冯维一,刘礼华,张旭苹,等.基于BOFDA的PE管道微弯变形检测方法[J].光通信技术,2020,44(12):33-36. [16] 刘路民根,张耀宗,栾琳,等.一种基于形状的红外图像泄漏气体检测方法[J].应用光学,2019,40(3):468-472.
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