Research And Implementation Of Comprehensive Performance Evaluation Method For In-Oil Inspection Robot

The safety of large oil storage tanks is related to the construction of national strategic oil reserves,and directly affects national energy security and people’s livelihood security.Metal tanks are often corroded and damaged by oil or external forces during long-term use,resulting in defects such as holes,cracks,and pits.However,the oil detection robot can directly enter the tank where oil is being stored to detect defects in the tank wall and bottom plate,enabling safety inspections without emptying the contents of the tank,and saving maintenance costs while ensuring the safe operation of the tank.The complex technology and diverse types of oil detection robots make it difficult to judge the performance of such robots,which is not conducive to the continuous improvement and development of robots.However,there is currently no relevant evaluation method to systematically evaluate it.Therefore,it is necessary to establish a comprehensive performance evaluation method for oil detection robots as soon as possible.The main content of this article is as follows:The process of establishing evaluation methods is general and can be summarized as follows: first,propose an indicator system to express performance,and then select a comprehensive evaluation method to build a complete evaluation model based on this.(1)After analyzing the structure of various oil detection robot products both at home and abroad,various performance indicators were extracted and selected,and a universal performance indicator system was constructed,with a three-level hierarchy of 37 underlying indicators.At the same time,the scoring criteria and value taking principles of indicators have been reasonably determined,and a set of indicator testing specifications has been developed.(2)According to the index system structure and the actual situation of the robot,the evaluation method of subjective and objective combination weighting is adopted.The subjective weighting method selects the weights by the order relationship analysis(G1)method which can handle the hierarchical structure of indicators and is easy to operate without error,while the objective weighting method selects the criteria importance though intercriteria correlation(CRITIC)which can solve the problem of few samples and complex indicator relationship in this paper.The subjective and objective weights are combined by the comprehensive weighting method with simple operation.The aggregation of indicators and weights selects the cloud model evaluation method that can maintain the coexistence of quantitative and qualitative indicators.In order to avoid the distortion of the evaluation results caused by the unreasonable standardization of individual indicators when assembling,the efficacy coefficient method is introduced to weight the indicators to resolve the contradiction,and the virtual cloud is added to improve the cloud model to achieve a complete comprehensive evaluation process.(3)The tank wall inspection robot developed in this project is taken as the evaluation object,and six different data samples of oil inspection robots are selected to apply the discussed method as an example.The evaluation results and performance evaluation of the tank wall in oil detection robot are obtained.In order to verify the effectiveness of the methods in this paper,five commonly used and reasonable evaluation methods are selected to evaluate the same sample.This paper uses the ordinal sum theory and mode theory to measure the effectiveness of the results of all evaluation methods.(4)After comparing the measurement results,it can be seen that the cloud model evaluation method in this article has the highest correlation coefficient,which is the closest to the optimal solution for performance evaluation.The comprehensive results show that the comprehensive evaluation method established in this paper for the performance of oil detection robots has good feasibility and rationality,and can successfully complete the evaluation task of the robot.Using the cloud model evaluation method,it is concluded that the performance evaluation conclusion of the tank wall inspection robot is at a medium level.Through the analysis of the results,it can be seen that there is still much room for improvement in various indicators of the robot,and suggestions for improvement are proposed.Finally,based on the method in this paper,a set of performance evaluation software for oil detection robots is developed,which has the functions of storing and managing relevant information.Only by inputting indicator data,can the evaluation results of the object be obtained,providing assistance for related evaluation work.