Ultrasonic Guided Wave Testing Signal Analysis Processing And Recognition

The pipeline is the lifeline of oil and natural gas transportation, so the safe operation of the pipeline is directly related to the normal transportation of oil and gas. The inevitable corrosion which brought by the working environment of the pipeline and Increasing service life of pipeline is the main risks which affect the safe operation of pipelines.Timely detection of these corrosion and measuring preventively are technical problems of non-destructive testing of long-distance pipeline. Researching the basic principles.detection methods,signal analysis,data processing and identification of defects of non-destructive testing of long-distance pipeline, achieving quickly scanning the status of the pipeline and Identification and location of defects have great significance to maintain safe operation of pipelines.The method of ultrasonic guided wave inspection is an emerging pipeline non-destructive testing method. It overcomes the deficiencies of conventional detection methods, it can quickly scan the pipeline and achieve a comprehensive assessment of the pipeline operating conditions. In this paper, the ultrasonic guided wave detection technology, database technology and artificial neural network are used to implement automatic identification of pipeline defects and proper management of test data.The main research contents are as follows:1. An advantage of the guided wave ultrasonic testing equipment for nondestructive testing of pipelines.analysis working principle of guided wave inspection equipment. selecting the appropriate probe ring, guided wave excitation frequency and the guided wave modes.2. Analysis of the information about waveform which collected from guided wave inspection equipment, different pipeline defects corresponding to the different waveform characteristics, finding the best characteristics which can characterize of the type of defect. Researching the main factors which affecting test results of pipeline ultrasonic guided wave, including coating, pipe work environment and so on, different situations to take different measures,in order to improve the detection range and sensitivity of ultrasonic guided waves;3. C#and SQL Server2008are used to establish a database so that it has entered. modify, delete, and view, interface clarity, operation is simple, achieving the effective management of test data and test results;4. MATLAB neural network toolbox is used to establish of two layers of BP neural network.analysis of waveform data in order to determine the neural network input vector, output vector, the structure of neural network, the number of neuron from each layers transfer function for each layers and the BP algorithm, then training,and testing BP neural network. The experimental results show that:the BP neural network which has been trained well has pipeline defect recognition ratere of81.7%.