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Optimal Path Planning of Steam Generator Tube Inspection System’s Robotic Manipulator Using Genetic Algorithm
Joseph Winston S.,
Published in Springer Science and Business Media Deutschland GmbH
2021
Pages: 541 - 549
Abstract
Prototype Fast Breeder Reactor (PFBR) has eight Steam Generators (SG) that transfers the heat from molten sodium to the water and converts the water into super-heated steam. SG is a shell and tube type counter flow heat exchanger, which has 547 steam tubes connecting the top and bottom headers of the SG. These steam tubes are surrounded by Sodium and water/steam will be flowing in the tubes. (i.e. sodium is present in the shell side and water/steam in the tube side). The water/steam pressure will be 172 bar and any breach in one of the tubes (due to crack) will eventually result in water coming in contact with sodium and leading to violent reaction. Hence, all mitigation efforts are to be taken proactively to isolate a degrading tube(s) through proper Pre-Service inspection (PSI) and In-Service inspections (ISI) using Remote Field Eddy Current technique (RFEC). Though PSI is a comprehensive inspection, ISI is generally carried out on 10% of the total heat transfer area, i.e. about 54 tubes, through periodic inspections. A two-axis robotic system called PFBR SG Inspection System (PSGIS) is used to position the probe/cable pusher end effector system to perform the tube inspection with RFEC probe. Since there is no straight forward scheme available to optimally choose the inspection sequence, Genetic Algorithm (GA) is used to optimize the tube inspection order to reduce the duty cycle and total inspection time. In this work, we have developed a genetically evolved optimal inspection algorithm to reduce overall inspection time and the results of the investigations are presented. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetLecture Notes in Mechanical Engineering
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH
ISSN21954356
Open AccessNo