Monitoring Cloud Platform for Testing Laboratories Based on Improved YOLOv5s Algorithm
In order to develop a core intelligent algorithm to supervise the cloud platform system the intelligent supervision of the testing process in engineering laboratories.Taking the concrete block compression test as an example,the improved YOLO(You Only Look Once)v5s algorithm is used to recognize the whole laboratory image in real time to ensure the seamless monitoring of the whole process of concrete test block.By establishing the concrete test block target detection model of YOLOv5s and adding the SE(Squeeze-and-excitation)channel attention module to the network,the model is able to monitor the position and state of the concrete test block in real time and cope with the complexity of the laboratory environment,which significantly improves the accuracy and robustness of the intelligent recognition.The experimental results show that the improved YOLOv5s algorithm performs well in concrete specimen block recognition,and the performance indexes are significantly improved.Through the combination of intelligent algorithms and cloud platform technology,an advanced supervision solution for laboratory testing activities is provided,realizing the intelligent supervision of the whole testing process.This method ensures the objectivity and reliability of the testing results and a new way for the intelligent supervision of engineering testing quality is provided.
国家科技期刊平台
NSTL
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