Analyzing the dangers posed by Chrome Extensions

NS

Research and Development of Intelligent Cleaning and Mud Content Detection Technology for Machine-Made Sand

In this paper, an improved method of sand and mud content detection for concrete is proposed, and a set of sand and mud content detection device for concrete is designed. In this paper, a concrete gas content meter and a bubble parameter analysis system were used to study the effect of sand clay content on the gas content of commercial concrete, the loss rate of gas content in warp time, the bubble spacing coefficient and the distribution of hardened appearance pores. The pore structure test shows that the increase of mud content will appropriately reduce the proportion of harmless pores in machine-made sand concrete, and play a role in refining the pore structure in machine-made sand concrete. By using PLC controller and automatic detection device of liquid level and turbidity, the problems of complicated operation, inconvenient carrying and poor repeatability of test data are solved. It reduces the influence of human operation error and improves the accuracy of test data

Research and Development of Intelligent Drying Detection Technology for Machine-Made Sand

This paper aims to develop a high precision variable dielectric constant capacitor detector for mechanical sand water content testing. The non-contact on-line test method can effectively solve the problems of low repeatability of test data, large hysteresis error and poor linearity due to the non-uniform water content. In terms of hardware, CAV444 is a high-precision integrated chip, which matches the corresponding test circuit. The system communicates with PC through serial interface and implements the man-machine interface of PC system based on VS. Secondly, the distribution map method is used to measure the water content of machine-made sand, and the error analysis is carried out. The test shows that the output of the capacitive hygrometer is 0-5 V. The delay time should not exceed 0.15%. The repetition rate was within 0.33%. The measurement accuracy of this method is less than 3.52%