Research On Path Optimization Of Equipment Inspection Based On Improved Genetic Algorithm

With the further integration of industrialization and information technology,the development direction of industrial production equipment are in the direction of integration complication and large scale intelligent,therefore the equipment inspection has become such an indispensable job to guarantee the safety of produce.There are many problems in the current equipment inspection such as low implementation efficiency and too much human involvement and the like,which are mainly caused by the unreasonable inspection path and so on.Hence,the inspection path should be re-planned rational and scientific considering the actual situation of inspection work,which is using intelligence algorithm to optimize the path,which has important practical value for the stable production of enterprises.Based on the current situation of equipment inspection,the inspection path problem can be divided into the path optimization problem with and without equipment consideration,the thesis study the path optimization of equipment inspection based on the improved genetic algorithm.First of all,based on the overall analysis of the specific situations and shortcomings of the current industrial equipment inspection,the related problem and principle of path optimization is summarized,which lays the theoretical foundation of the thesis research.Secondly,combine with the actual situation of the inspection work,the inspection path problems is analyzed and its mathematical model is established.The advantages and disadvantages of path optimization solution with genetic algorithm are analyzed,several strategy improve genetic algorithms are proposed to solve the inspection path problems model,after the initial population are generated by neighborhood method,the strategy of elite individual reservation and the operation of evolution reverse are introduced to improve the performance of algorithms.The results of the simulation experiments show that the improved algorithms have more computational efficiency and can obtain the optimal path.Thirdly,evaluate the impact of inspection path caused by the equipment state level,the main factors which influent the running state of equipment are selected,the BP neural network equipment classification model optimized by genetic algorithm was established,through the MATLAB modeling and evaluation,verified that the model do have better classification effect.Based on the analysis of path optimization problem,establish inspection optimization subject considered the length of inspection path and the quality of equipments,and use improved genetic algorithm to solve the problem.The classification results of BP neural network are applied to the path optimization algorithm,and the results of MATLAB simulation show that it will meet the path plan considered the equipment statement.Finally,after the analysis of the actual business needs of inspection work of an explosion-proof Inspection Center,the sever side of inspection management system is designed and implemented with layered software architecture,the improved genetic algorithm is integrated into the system,and the main functions are described.From the aspect of actual results,the system has simple operation and clear interface,and can provide support for the assistant decision of inspection work.