埋地钢质管道防腐层检测关键技术研究与应用

Research and Application of Key Technologies for Detection of Anti-corrosion Layer of Buried Steel Pipeline

本文探讨了埋地钢质管道防腐层检测关键技术的研究与应用。首先阐述了防腐层的重要性,分析了其可能出现的破损、老化等问题。接着回顾了现有检测方法,如电化学、脉冲涡流、超声波等,并提出了一种基于机器学习和人工智能的检测方案。该方案包括高精度数据采集、深度学习算法和智能诊断技术。通过激光扫描和高清相机进行非接触式数据采集,卷积神经网络进行图像数据分析,支持向量机进行分类和评估。为管道维修提供依据,并对城市基础设施安全运行具有重要意义。

In this paper,the research and application of the key technology of corrosion protection layer detection for buried steel pipeline are discussed.Firstly,the importance of the anticorrosive layer is described,and the possible problems such as damage and aging are analyzed.Then the existing detection methods,such as electrochemistry,pulsed eddy current,ultrasonic,etc.are reviewed,and a detection scheme based on machine learning and artificial intelligence is proposed.The scheme includes high-precision data acquisition,deep learning algorithms and intelligent diagnosis technology.Non-contact data acquisition by laser scanning and HD cameras,image data analysis by convolutional neural networks,and classification and evaluation by support vector machines.It provides the basis for pipeline maintenance and has important significance for the safe operation of urban infrastructure.