Selective Disassembly Sequence Planning For Wind Turbines Based On The Improved Immune Algorithm

Selective disassembly sequence planning(SDSP)is an important technology for maintenance,recycling,and remanufacturing of wind turbines.SDSP is a combinatorial optimization problem,and for large components of wind turbines,the search space for the optimal disassembly sequence is huge.Disassembly constraints are crucial for reducing the search space for the optimal disassembly sequence,but manually identifying them is labor-intensive and inefficient.Traditional methods for extracting and expressing disassembly constraints have low automation levels.Additionally,the generated disassembly information model does not consider the impact of process knowledge on the disassembly sequence,leading to a large search space and disassembly sequences that do not meet actual requirements.Currently,there is little research on the problem of SDSP.To address the shortcomings of traditional disassembly sequence planning methods,research on SDSP is conducted,with the following main research contents:(1)We conducted research on CAXA 3D solid design software and ICAPI.Using ICAPI,we wrote C++program code in Visual Studio,and then integrated the generated application program into the CAXA 3D solid design software.Based on a 3D assembly model,we implemented several functions,including information retrieval for components,calculation of bounding boxes for parts in the assembly coordinate system,extraction of disassembly constraint information between components,and dynamic disassembly simulation of the assembly according to the disassembly sequence of parts planned by the algorithm.(2)We extracted disassembly constraint information including part contact information,part support information,and part interference information based on CAXA secondary development,and combined these information with fastener disassembly priority rules and disassembly process knowledge to express them as four types of disassembly constraint matrices.The four types of disassembly constraint matrices are the functional parts contact matrix,functional parts support matrix,fasteners and functional parts priority matrix,and functional parts priority matrix.We identified various factors that affect disassembly costs and constructed an objective function for the selective disassembly sequence planning model.We established a selective disassembly sequence planning model to provide a framework for optimizing algorithms to search for the optimal disassembly sequence.(3)The Improved Immune Algorithm(IIA)is proposed based on the Immune Algorithm(IA)to solve the Selective Disassembly Sequence Planning(SDSP)problem,aiming to search for the optimal or near-optimal selective disassembly sequence and provide technical support for wind turbine maintenance and recycling.The IIA mainly consists of four steps:vaccination,immune operation,antibody evaluation,and immune metabolism.All four steps are improved for the SDSP problem,enhancing the algorithm’s local and global search capabilities while maintaining population diversity.Finally,the experimental results are used to verify the advantages of the proposed model in reducing the search space for the optimal disassembly sequence and the performance of the IIA.