Abstract:

Ultrasonic detection is one of the important ways to inspect the wall-loss defects and cracks in-line for oil pipeline. Because of the complicated condition in pipeline the recognition of ultrasonic detection echoes is difficult. This is a high-dimensional classification problem. An effective method based on support vector machine（SVM），which is suitable for small-sample，non-linear and high-dimensional recognition for classification and recognition of pipeline corrosion defects was presented. The ultrasonic A-scan time-series were considered characteristic vectors. By unifying the characteristics extraction and pattern recognition of pipeline corrosion defects the classified decision function of ultrasonic detection echo signals was established. Experiments showed that the classified recognition of break interfaces of pipelines was accurate and clear and the method was suitable for in-line detection of pipeline corrosion defects.