A capacitive imaging algorithm for signal separation: Defects vs. lift-off disturbances

Capacitive imaging (CI) technology is extensively utilized in various industries, including aerospace, oil transportation, automobile manufacturing, and construction engineering, with its significance continually increasing. A critical factor in ensuring the reliability of detection results in CI technology is the accurate differentiation between defect signals and lift-off disturbance signals. This paper uses COMSOL to establish a three-dimensional simulation model of CI sensors detecting insulated cladding components and obtains the influence of different lift-off heights on the surface defects of the insulation layer, hidden defects of the insulation layer, and surface defects of the metal layer. The Measurement Sensitivity Distribution (MSD) diagram is used to analyze the detection of sensitive areas of different types of defects. Using a CI system to experimentally detect three different types of defects and reveal the impact patterns of unidirectional and multidirectional lift-off disturbances on different types of defects. Based on the differences in detection trends between lift-off disturbances and three different types of defects, a Normalized Variation Ratio (NVR)-integral double-threshold algorithm is proposed. The effectiveness of the algorithm is verified through experimental results.