Abstract
RAPID (reconstruction algorithm for the probabilistic inspection of damage) is a new promising tomography approach for the detection and monitoring of critical areas in a structure. With the sensors permanently installed on or embedded in structures, changes in effective thickness and material properties caused by structural damage can be detected and mapped to the tomogram. However, in this method, the tomographic feature SDC (signal difference coefficient) captures the overall change of the received ultrasonic signals, which makes it sensitive to environmental factors (e.g. rain, changes in temperature and humidity). As a result, the approach is restricted in the laboratory environment. In this paper, the influence of measurement data length on the SDC and the tomogram are investigated, and a new strategy is established on how to choose the measurement data to obtain good reconstruction by matching the coverage zone of each transmitter–receiver pair with the corresponding affected zone. The proposed method is then applied to identify defects of the specimen in the presence of external sources of interference, such as water droplets and structural variations outside the critical area. The results demonstrate its capability of improved robustness in the presence of external sources of interference.
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