Comparative analysis of low-cost wireless vibrating monitoring system for rotating machines

In industry, the maintenance and optimal performance of rotating machinery in factories and power plants are of paramount importance. Vibration, a pivotal factor in the operation of such systems, necessitates careftll monitoring to prevent potential damages to motor mechanisms. This study addresses this need by presenting the development of a prototype wireless vibration monitoring system tailored for rotating machines. The aim is to mitigate the risks associated with high vibration levels that can lead to machine breakdown. The research compares two computing platforms, the Raspberry Pi 4 processor and Arduino UNO microcontroller, both integrated with ADXL345 accelerometer sensor. The sensor serves as the cornerstone for the vibration monitoring system. The study evaluates the perförmance of these platforms, emphasizing their efficiency in processing and transmitting data. Additionally, MATLAB software is employed tor comprehensive graphical data analysis and visualization. Experimental testing of the prototype was conducted on a DC motor. The findings reveal that the Arduino platform outperförms the Raspberry Pi in detecting DC motor vibrations. Arduino's capability to process a higher volume of data per second positions it as a superior choice for real-time vibration monitoring applications. Originality of this project is in the development of vibration monitoring system using commercially available components that are low cost, and signal analysis of the vibration amplitude displacement and frequency at diffZTent motor speed. The developed vibration monitoring system stands as a tool, offering preventive measures for plant operators. Enabling continuous health monitoring of rotating machines empowers operators to proactively detect and address potential issues. This proactive approach significantly reduces the likelihood of unexpected machine breakdowns, thereby enhancing operational efficiency and minimizing downtime in industrial environments.