VISION BASED SMART SYSTEMS FOR RELIABLE NUCLEAR FUEL PIN MANUFACTURING
13th International Conference on CANDU Fuel - 2016 Aug. 15-18


Presented at:
13th International Conference on CANDU Fuel
2016 Aug. 15-18
Location:
Kingston, ON Canada
Session Title:
Session 10: Fuel Fabrication and Core Design

Authors:
S.N.V. Kumar (Nuclear Fuel Complex, India)
S.K. Pathak (Nuclear Fuel Complex, India)
D.S. Setty (NUCLEAR FUEL COMPLEX)
G. Kalyanakrsihnan (Nuclear Fuel Complex, India)
N. Saibaba (NUCLEAR FUEL COMPLEX)
  

Abstract

Nuclear Fuel Complex, the world’s largest producer of PHWR fuel bundles, carries out various specialised procedures leading to manufacture of high quality fuel bundles for nuclear reactors. Manufacturing activity involves loading of sintered UO2 pellets into Zircaloy fuel tubes and encapsulating them with Zircaloy end caps on both the sides through resistance welding process. The fuel pins thus formed are then made into 19-element and 37-element fuel bundles. At fuel assembly plants, a variety of components like fuel tubes, appendages viz., spacer pads & bearing pads, end caps, end plates are handled in very large numbers on a daily basis for carrying out uninterrupted production activities. For getting good quality fuel pin, the tube to end cap weld joint is very critical. For obtaining a reliable weld joint, it is very important to have precise geometry and dimensions for the fuel tubes and end caps. Accordingly, individual components need to be subjected to stringent inspection and defective components need to be positively filtered out. Carrying out manual inspection with precision and consistency is a very difficult task considering the volume of the components being handled and considering manual fatigue. In order to avoid such occurrences of defective components entering into production stream, automatic machine vision systems are now being introduced before end cap welding process. These systems employ vision based inspection systems to identify and separate defective tubes. Images captured by the cameras are processed and a decision making algorithm embedded into the system identifies and separates out acceptable components from defective ones. The systems thus employed carry out multiple tasks like identifying the orientation, axial location & number of appendages, checking the tube diameter, tube end chamfer, surface defects like dents, pits etc on the OD of the Zircaloy fuel tube. The system is accompanied by an LED based illumination system, lens and operates through PLC using suitable hardware and software that includes a PC and MMI. System has been provided enough flexibility to allow periodic calibration and redefine the acceptability criterion through different levels of software authentication. The system has also been provided with an automated tube feeding & positioning systems. Features of these machine vision systems are described in the full paper in more detail.

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