AUTOMATIC DAMAGE IDENTIFICATION TECHNOLOGY FOR INFRARED THERMOGRAPHY METHOD

Abstract

The infrared thermography method takes a thermal image of the concrete surface and detects internal defects. However, the thermal image diagnosis results may vary from person to person depending on the experience of the investigator, and improving the reliability of the inspection results is an issue.

In this study, we report on the technique for automatically identifying by statistical machine learning damage candidates extracted from thermal images. And report on the study results of automatic damage identification technology for infrared thermography method for bridge superstructure concrete and utilization status of thermal imaging diagnostic cloud service.