Intelligent measurement and control system of mine water level based on Raspberry Pi

Abstract

The current water level monitoring methods have the problems of low precision, susceptibility to environmental impact, weak real-time performance, high requirements for machine computing power, and high hardware costs. In order to solve the above problems, a Raspberry Pi-based intelligent water level measurement and control system for underground water storage is proposed. The system collects water level images around the water tank scale through explosion-proof monitoring cameras, and uses raspberry pie as the image processing platform. Firstly, the method converts the collected color images into grayscale images, and uses the Otsu method to perform threshold segmentation on the images. The method removes noise and enhances image edge information through morphological operations, and then separates the ruler contour from the background. Secondly, the Canny operator is used to detect the edge of the scale, and the Hough transform method is used to extract the intersection line between the water level line and the vertical edge of the scale, obtaining the coordinates of the water level line in the image space. Thirdly, threshold segmentation and filtering enhancement processing are performed on the digital image of the scale within a certain range of the area near the water level line. Then, the template matching method is used to achieve the recognition of the scale number, thereby obtaining the water level line value. Finally, the method converts the numerical value of the water level line in the water tank into a current analog quantity, and uses Raspberry Pi to send the water pump controller to control the start and stop of the water pump based on the current magnitude. The method achieves intelligent control of the mine water level. This system has the advantages of low cost, convenient deployment, high precision, and good real-time performance. It can achieve rapid and accurate recognition and control of mine water level.

Keywords

• mine water tank
• water level measurement and control
• raspberry pi
• edge detection
• hough transform
• number recognition