Simulation And Application Of Detecting Air Tightness Of Sealed Container

With the development of the industries of automobiles, motorcycles, gas applications, food, pharmaceutical, the air tightness detection for airtight cubage products has become increasingly important. To ensure the quality of products, the air tightness of the products must be detected. Therefore, to develop a set of high accuracy, automatic and low-price air tightness detecting system is of great practical significance in improving production efficiency and reducing the labor loads and improving product quality.This paper introduces the principle of the airtight detection system based on differential pressure, establishes the mathematical model of the system, and presents the simulation based on the model with Simulink. Though the simulation results of the detecting process, it clearly shows that the changes of the pressure and the temperature of the inner airtight containers and those differences of measured parameters have influence on differential pressure. Finally, the amount of leakage formula is derived from the existing formulas.As air tightness detecting system is a multi-sensor acquisition system, in the acquisition process, the linear nonlinear errors are inevitable, and these errors will directly have influence on the accuracy of the measure results. To improve the accuracy of the acquired data and the measure results, the data fusion can reduce the disruption of the factors influencing on the measure results as much as possible. Furthermore the data fusion model of the detecting system is established.To validate the validity of the data fusion in the detecting system, we develop an air tightness detecting system. The hardware of system consists of gas path frame and circuit. The design purpose of the gas path frame is to design loops based on the differential pressure, and eliminates the disturbance factors which impact on the measurement results. Singlechip is the control center in the circuit, which mainly consists of keyboard unit, data acquisition unit, power unit, LCD driver unit, network unit. For data acquisition unit in order to reduce the sensors' own error, the pressure sensors produced by Honeywell are used, which own small temperature drift, high sensitivity and great repeatability. To improve detection accuracy of the system, an A/D converter is used with the∑??conversion technology, 24bits, low-noise, high reliability. The system software is designed in MPLAB-IDE environment and programmed with modularized C language. The detecting system debugged is simple in operation, with high precision, low price, and the interactive graphical interface.Based on the debugged detection system, new data is obtained using the neural network data fusion method to process the measured data. Comparing the measured with new results, the conclusion is reached that the data fusion methods is practically valuable and significant to improve the accuracy of the detecting system.