Pipeline defect detection is an important aspect of safety tests.
管道缺陷的检测是安全检测的重要方面。
Use BP neural network to quantitatively recognize pipeline defect parameter, the error of recognition result is below 10%, and requirement of practical inspection can be completely fulfilled.
应用BP神经网络进行了管道缺陷参数的定量识别，识别结果的误差小于10%，完全满足实际检测的要求。
The analytical results show that this method can be applied in defect size prediction of pipeline in service.
分析结果表明，这一方法可用于在役管道缺陷尺寸的预测。
The effects of corrosion rate, defect depth, thickness of pipe and operation pressure on pipeline reliability were investigated with this model.
利用这一模型，研究了腐蚀速率、缺陷深度、管道壁厚和工作压力等因素对管线可靠性的影响。
While installation, transport and other industrial accidents of the petroleum pipeline, it is unavoidable to encounter various damage and defect, such as surface flaw, crack, etc.
石油管线在安装与油气输运过程以及其他工业事故中，难免会产生各种各样的损伤和缺陷，如出现表面凹坑、裂纹等。
The adoption of the chamfered mould, slow cooling in CC and increasing the edge and corner temperature could effectively suppressed the edge defect of pipeline steel.
采用倒角结晶器及连铸弱冷工艺、提高轧件边角部温度可以有效抑制管线钢边部缺陷的产生。
In the testing work that showed a clear shape of wall and location of the defect can be visual display pipeline status, and to improve the efficiency of inspection.
在检测工作中清晰地显示管道内部缺陷形状及其位置可直观反映管道状况，并提高检测的工作效率。
Defect categories and features of spiral seam cracking are studied based on spiral seam cracking facts in Northeastern Oil Pipeline Networks.
针对东北管网多次发生螺旋焊缝开裂事故的事实，研究了造成螺旋焊缝开裂事故的缺陷类型和特征。
In industrial ct image analysis and process, it is necessary to display the inner surface of the pipeline for subsequent analysis and defect detection.
对工业CT图像进行分析和处理的过程中，经常需要对工件管道的内表面进行显示，为后续的分析与检测做准备。
In industrial ct image analysis and process, it is necessary to display the inner surface of the pipeline for subsequent analysis and defect detection.
对工业CT图像进行分析和处理的过程中，经常需要对工件管道的内表面进行显示，为后续的分析与检测做准备。
应用推荐