Print Counting, Status Inspection and Type Identification of Printing Devices based on Smart Sensor

Most of the factories still employ traditional equipment without interfaces of status parameters transmission and standard communication protocol. The inspection of traditional equipment has become a difficult and key point in the development of manufacture. The present study aimed to count printing, inspect status and identify types of traditional printing devices. A smart sensor-based system is proposed in this work. Variational mode decomposition (VMD) is utilized to extract feature values, and back-propagation neural network (BPNN) models are built for type identification and status inspection of the printing devices. Experiment results show that: the accuracy of print counting, status inspection and type identification of printing devices were 100%, 86.6% and 93.3% respectively. The methodologies and system proposed in the present study can be adapted to other industrial equipment identification and inspection, which can significantly facilitate the development of industrial technologies.