Design of Embedded System with Edge Computing Applications for Industrial Internet of Things and Real-time Monitoring of Bearing Condition

Abstract

Under the vigorous industrial internet of things (IoT) and big data cloud a method of data processing named “Edge-Computing” has developed As the name suggests the method processes the data in the equipment’s side by the edge resources It can not only help us doing data preprocessing but making some preliminary judgment timely without transmitting data to the terminal The edge computing is beneficial for solving the considerable data transfer problems congestion in bandwidth caused by too many IoT transmission devices and extended response time Bearings play a significant role in the operation of rotating electrical machines and they are also one of the most easily damaged parts If the machine is forced to shut down due to undetected defects the cost of the loss will not be unexpected This thesis dedicates to designing the embedded systems and interactive human-machine interfaces for real-time monitoring of bearing conditions By using MEMS(Micro-Electro-Mechanical-System) sensors which has the characteristics of mass production low cost modularization and high integration and STM microcontrollers to simulate programmable smart sensor modules and apply edge-computing on it Thereby the bearing condition monitoring process designed and the writing of the microcontroller and the human-machine interface in this paper The embedded system can monitor the bearing status in real-time and independently determine whether the bearing is abnormal Besides the human-machine interface will alert the user and present a detailed analysis of the bearing condition when the bearing is abnormal Finally we verify that the system has an excellent performance in real-time bearing monitoring condition analysis and data transmission reduction by the self-made defective bearings and rotating motor

Date of Award	2020
Original language	English
Supervisor	Cheng-Chi Tai (Supervisor)