首页|Patent Issued for Systems for assessment of weld adjacent heat affected zones (U SPTO 12072319)

Patent Issued for Systems for assessment of weld adjacent heat affected zones (U SPTO 12072319)

扫码查看
From the background information supplied by the inventors, news correspondents o btained the following quote: “The present disclosure relates to robotic inspecti on and treatment of industrial surfaces.” Supplementing the background information on this patent, NewsRx reporters also o btained the inventors’ summary information for this patent: “Previously known in spection and treatment systems for industrial surfaces suffer from a number of d rawbacks. Industrial surfaces are often required to be inspected to determine wh ether a pipe wall, tank surface, or other industrial surface feature has suffere d from corrosion, degradation, loss of a coating, damage, wall thinning or wear, or other undesirable aspects. Industrial surfaces are often present within a ha zardous location-for example in an environment with heavy operating equipment, o perating at high temperatures, in a confined environment, at a high elevation, i n the presence of high voltage electricity, in the presence of toxic or noxious gases, in the presence of corrosive liquids, and/or in the presence of operating equipment that is dangerous to personnel. Accordingly, presently known systems require that a system be shutdown, that a system be operated at a reduced capaci ty, that stringent safety procedures be followed (e.g., lockout/tagout, confined space entry procedures, harnessing, etc.), and/or that personnel are exposed to hazards even if proper procedures are followed. Additionally, the inconvenience , hazards, and/or confined spaces of personnel entry into inspection areas can r esult in inspections that are incomplete, of low resolution, that lack systemati c coverage of the inspected area, and/or that are prone to human error and judge ment in determining whether an area has been properly inspected.

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Sep.12)