Study On The Dynamic Weighing System And Data Processing Methods Of Electronic Quantitative Packaging Machine

Electronic weighing technology is an important basis for the modern measurement and control system engineering. Electronic packaging machine is an application of the quantitative system with electronic weighing technology. It has been a difficulty for the enterprises to improve the dynamic weighing accuracy in electronic weighing. Meanwhile, it has been a difficulty in the field of measurement to get a high weighing accuracy with high weighing speed.The thesis mainly studied the digital filtering technology, neural network and Proportional-Integral-Differential (PID) control technology in the application of the dynamic weighing system of electronic quantitative packaging machine. Through digital signal processing, digital filtering algorithms, and DSP hardware design, signal noise was eliminated and dynamic measurement accuracy was improved. Meanwhile, based on the idea of complex control theory, using neural network and PID as the key control technology, the contradiction between accuracy and speed of the dynamic weighing was solved well. Thus, the accuracy and speed of the dynamic weighing can be improved.The main contents of the thesis are summarized as follows:1. Author summarized the research in the technical principles of dynamic weighing, dynamic weighing technology and electronic packaging machine.2. The structure of packaging machine and the basic theory of electronic weighing technology were studied in the thesis. After analyzing the main factors that influence the weighing accuracy and speed, author decided to use digital filtering technology, neural networks and PID control as the main method to improve the weighing system.3. Author analyzed the sampling signal in the time domain and frequency domain and got the effective distribution of the signal. After studying different digital filtering algorithms that are fit for weighing system, author finished the digital signal processing with those algorithms.4. According to the specification requirement of the weighing system, a FIR filter and an elliptic IIR filter were designed with optimal theory. Meanwhile, a digital filter was realized using TMS320C5416 DSP chip.5. According to the control characteristics of the weighing system, a PID control system was designed based on RBF neural networks, combining the advantages of both PID and neural networks.