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| Discussion on Application of Intelligent Inspection Robots in Natural Environment Experiments |
| Received:November 08, 2023 Revised:December 01, 2023 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/issn.1672-9242.2024.01.016 |
| KeyWord:intelligent inspection robot environmental test image recognition data collection digitization |
| Author | Institution |
| HUANG Lun |
Southwest Institute of Technology and Engineering, Chongqing , China |
| ZHU Yuqin |
Southwest Institute of Technology and Engineering, Chongqing , China |
| SHU Chang |
Southwest Institute of Technology and Engineering, Chongqing , China |
| ZHOU Junyan |
Southwest Institute of Technology and Engineering, Chongqing , China |
| DAI Lu |
Southwest Institute of Technology and Engineering, Chongqing , China |
| ZHANG Zhihao |
Southwest Institute of Technology and Engineering, Chongqing , China |
| HE Dehong |
Jiangjin Atmospheric Material Corrosion Field National Observation and Research Station, Chongqing , China |
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| Abstract: |
| The work aims toexplore the establishment of an intelligent inspection system for natural environment experiments, replace some manual inspection work with robots. By analyzing the inspection work environment and inspection tasks, the functional requirements and technical parameters of the intelligent inspection robot were determined, and then the robot body structure design was carried out, integrating control backend, remote database and other equipment to achieve the construction of an intelligent inspection system. The use of intelligent inspection data collectionwas verified. The sample images collected by the inspection robot have clear focus, high resolution, reasonable position and size of the samples in the images, and clear display of corrosion characteristics. The inspection system could automatically segment and intelligently recognize sample images, and accurately identify damage features such as corrosion points and flow marks, with an accuracy of up to 0.1%. The intelligent inspection system can meet the inspection requirements of natural environment experiments, and replace manual completion of some inspection work. The intelligent inspection data is easy to store and use for mining. Ithas a positive promoting effect on the digital transformation of natural environment experiments. |
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