Abstract
Industry 4.0 offers a radical transformation to increase cost-effective, flexible, and efficient production of higher-quality fully automated systems by collecting and analyzing data across machines. From the last few decades, power industry has started to focus on real-time systems instead of using static methodology in periodical boiler inspection. The power plant undergoes sudden break down due to cracks and foreign bodies causing huge economic loss to the plant as well as the country. To avoid such unforeseen breakdown, most of the power plants has adopted inspection and monitoring system as a regular solution. Visual inspection is one of the most popular techniques for such inspections using a tiny camera with high-power LEDs (Known as Borescope). But it has several limitations for circumferential (360°) and longitudinal (2000mm) coverage and also equidistance inspection from the center of the header is not possible using a conventional Borescope. A specific Digital Video Recorder (DVR) used for the inspection and monitoring is not sufficient to resolve multipurpose requirements such as position of the foreign body and crack, feature of magnification, and more important is data log including plant information and crack details with images. A real-time inspection module has been developed integrated with robotic (AI) based on computer vision to make the inspection dynamic and fully automated.
