A multi-sensor data fusion system for assessing the integrity of gas transmission pipelines

Accurate and reliable characterization the pipe-wall condition of gas transmission pipelines requires inspection using more than one method of non-destructive testing. A suite of sensor data fusion algorithms that aims to synergistically combine information that is present not in heterogeneous sensors (e.g., magnetic, ultrasonic, and thermal) was presented. The objective of the data fusion algorithms is to improve the accuracy and reliability of pipeline monitoring by providing the location, size, and shape of pipe-wall anomalies. The multi-sensor data fusion algorithms are used in two stages, i.e., data from multiple inspection modalities are fused to identify and separate pipe-wall anomalies from benign indications, and the multisensor data is fused to predict the size and shape of those indications that are identified as anomalies. The best results are obtained for the fusion of ultrasonic testing and magnetic flux leakage data, and the poorest performance results from combining thermal imaging with any other method.