Surface Distortion Mapping System Narrowing Down Existence Probability via Touch Scanning

This study proposes and develops a surface-scanning tactile sensor and mapping system that amplifies strain gauge signals to enable the detection of minute defects. The research objectives include: (1) developing high-strength, high-sensitivity sensing for distortions of tens of micrometers; (2) constructing a system capable of rapidly scanning a large inspection area; and (3) visualizing and digitizing defect locations. To achieve these objectives, three key approaches were implemented. First, we developed a tactile sensor with a simple, flexible structural design. By arranging pins parallel to the strain gauges, the sensor effectively amplifies mechanical deformation to increase output. Experiments showed that the proposed sensor achieves signal amplification of approximately 7.6 times compared to a strain gauge-only sensor and produces an output approximately 3.3 times greater than that of a conventional sensor. Second, because the sensor cannot independently determine positional information, we estimated positions using a marker-based approach. Specifically, we measured the distance between a target marker attached to the sensor and a reference marker during scanning. The accuracy was evaluated using a dimensionless error metric normalized by the 60 mm gauge length, and the system yielded an error of 7.6% with a standard deviation of 5.5 mm. Third, we developed a system capable of probabilistically estimating the precise location of micro-surface distortions. The strain gauges used in current tactile sensors have a gauge length of 60 mm, which introduces the limitation that the exact location of a micro-surface distortion cannot be determined from a single measurement. To address this limitation, we developed a method that increases the probability of detecting micro-surface distortions through repeated scanning, thereby progressively narrowing the estimated detection range.