Gap Loss for Production Status Detection

In order to classify the monitoring model of the production state system more accurately and effectively, and accelerate the convergence speed of the model, a new loss function Gap Loss function is proposed. The image data and sensor data collected by the system in real time are used as feature data, the five self-defined states are the learning targets, and Gap Loss is used instead of the cross-entropy loss function for model training. Experimental verification shows that this method can more effectively classify production states compared with the cross entropy Loss function.