Data-Driven Optimization Control of Industrial Label Printer Process Parameters

For industrial label printers, it is difficult to describe the dynamic characteristics between the long-term printing quality and the output of the control loop with a mathematical model, and the printing quality is easily affected by the lack of details of the ribbon or thermal label, which is difficult to detect online; through research data Based on the optimization idea of driving operation mode, a method of data-driven industrial label printer process parameter optimization control is proposed; this method establishes the model between the input parameters of the print head and the output print quality and print head temperature prediction by the method of neural network, and predicts Set the input parameters to obtain the expected print quality and print head temperature through the model, and then optimize the print quality and reduce the temperature rise as the goal to feedback and optimize the input parameters, iteratively obtain the best input that is as close to the optimal target as possible under the current print head temperature parameter. Through practical application, this method can indeed reduce the temperature rise of the print head, and on the premise of ensuring the printing quality, optimize the input parameters so that the temperature of the print head rises slowly, ensuring that the printing can last for a longer time.