油气管道缺陷检测的数据处理方法回顾与展望

A Review on Processing Approaches about Defect Data in Inspection of the Oil and Gas Pipeline

油气管道缺陷检测中的数据处理方法主要包括传统的数据处理方法,如谱分析、统计分析,以及后来发展起来并广泛应用的小波分析、自适应滤波处理、支持向量机、人工神经网络、模式识别、数据融合等新方法。本文分析了各种用于管道缺陷检测的数据处理方法的优缺点,并指出当前研究中所存在的问题。最后探讨了这一领域中可能的发展方向。

The processing approaches about defect data in inspection of the oil and gas pipeline are reviewed, which comprise the traditional data processing, such as spectral analysis, statistical analysis, and wavelet analysis, adaptive filtering technique, statistical processing, support vector machine, artificial neural network, pattern reogntion, data fusion, et al, which are developed. After analyseing their advantages and disadvantages, the paper provides the problems of the processing approaches about defect data in inspection of the oil and gas pipeline. Finally, some research tendencies in this field are presented.