The client needed a system of monitoring the production of crushed stone in a quarry. We implemented this with the help of sensors connected to a computer using LoRa wireless data transmission.
The objectives of the monitoring were voltage supply, oil pressure, belt rate, prediction of bearing wear and individual components of units under the influence of an aggressive environment.
Information transmission occurs with the sufficiently strong low-frequency electromagnetic interference, arising during the operation of powerful electric motors.
We applied sensors that monitor temperature, humidity, smoke, vibration, and distance. The processed information is represented on the operator’s display with alerts about any malfunctions. Using ML predictive modelling, operator can know the expected time of next failure, best time for the maintenance work and replacement of accessories.
Technology stack:
STM32F103, F407, Esp32, Altium Designer, C++, MicroPython, EsPy, Cube, Python 3.8, Keil, Django, PostgreSql.
