Design of Measurement and Control Robots for Dust Monitoring

Aiming at the problem of accurate recognition of measurement and control robots for dust monitoring, a dust image recognition method based on ResNet50 network is proposed. The results show that the convergence speed and accuracy of the improved ResNet50 network are greatly improved, and the accuracy of dust recognition is about 97%. It is applied to the dust monitoring system, and the accuracy of the dust image recognition is 98%. In summary, the designed image recognition model for the measurement and control robots of dust monitoring is feasible and has high accuracy, which can be applied to measurement and control robots for dust monitoring.