A Fast Localization Method For Radioactive Leakage Point Based On Hybrid Adaptive Grey Wolf Algorithm

Taking the damage of waste barrels in the radioactive waste repository unknown areas as the research background,and taking the rapid positioning method as the research subject.The current leak point location algorithm based on autonomous mobile robot has the problems of complex algorithm structure,slow location speed and poor accuracy.In light of existing situation.We propose a fast leak location method based on the hybrid adaptive grey wolf algorithm.The optimized grey wolf algorithm is integrated into the leak point location,and the effect of the optimization algorithm is analyzed from the aspects of convergence,stability and accuracy of the algorithm.The main research contents and conclusions of this paper are as follows.(1)Ray attenuation factor,scattering factor,travel angle guide factor and spatial discretization factor are incorporated into the leak location model based on exposure rate information to optimized the original model.The changes in the number and location conditions of different leakage points were characterized,and the change rule of the positioning model under different radioactive leakage points was clarified.(2)A Hybrid Adaptive Grey Wolf Algorithm(HAGWO)was proposed.The algorithm was optimized from the grey wolf population initialization method,the convergence function selection,and the wolf group location update strategy.The algorithms of different optimization strategies are tested through 9 benchmark functions,and the performance of the hybrid adaptive grey wolf algorithm is analyzed under the conditions of different iteration times and population numbers.The results show that the convergence speed and optimization accuracy of the hybrid adaptive grey wolf are significantly improved.(3)The characteristics of multi-nuclide and multi-point leakage radiation fields were studied by Monte Carlo method.Quantitative analysis of the G(i)parameter of the exposure rate increment function under the conditions of different nuclides and different numbers of leaks provides a technical reference for judging the number of radioactive leaks.(4)The hybrid adaptive grey wolf algorithm is superior to the other three algorithms in terms of convergence,stability and accuracy.The radioactive leakage test model in the repository is constructed by the Monte Carlo method to analyze the performance of the hybrid adaptive grey wolf algorithm.The maximum convergence speed is increased by37.93±2%,and the maximum convergence accuracy is increased by 92.42±2%.Compared with the other three gray wolf algorithms,the hybrid adaptive gray wolf algorithm has better overall stability,and the stability of the improved algorithm can be maintained above 95.3%.The hybrid adaptive gray wolf algorithm can meet the stability required in the process of leak point location in the repository.Especially for the original gray wolf algorithm,the positioning stability is nearly doubled.The hybrid adaptive grey wolf algorithm has an error of less than 1.08% for a single leak point,the double leak point error is within 8.90%.Compared with the other three algorithms,the hybrid adaptive grey wolf algorithm improves the accuracy of single leak point by up to 1.36±2%,and the double point by up to 40.35±2%.The hybrid adaptive grey wolf algorithm based on the proposed method can locate the radioactive leakage point in a short time.The improved grey wolf algorithm has higher positioning speed and accuracy.The rapid location method of leak points based on the hybrid adaptive grey wolf algorithm provides a method reference for rapid location of radioactive leak points,and has a good application prospect.