A distributed and intelligent system approach for the automatic inspection of steam-generator tubes in nuclear power plants

The inspection of steam-generator (SG) tubes in a nuclear power plant (NPP) is a time-consuming, laborious, and hazardous task because of several hard constraints such as a highly radiated working environment, a tight task schedule, and the need for many experienced human inspectors. This paper presents a new distributed intelligent system architecture for automating traditional inspection methods. The proposed architecture adopts three basic technical strategies in order to reduce the complexity of system implementation. The first is the distributed task allocation into four stages: inspection planning (IF), signal acquisition (SA), signal evaluation (SE), and inspection data management (IDM). Consequently, dedicated subsystems for automation of each stage can be designed and implemented separately. The second strategy is the inclusion of several useful artificial intelligence techniques for implementing the subsystems of each stage, such as an expert system for IP and SE and machine vision and remote robot control techniques for SA. The third strategy is the integration of the subsystems using client/server-based distributed computing architecture and a centralized database management concept. Through the use of the proposed architecture, human errors, which can occur during inspection, can be minimized because the element of human intervention has been almost eliminated; however, the productivity of the human inspector can be increased equally. A prototype of the proposed system has been developed and successfully tested over the last six years in domestic NPP's.