The Design And Implementation Of The Iot-based Equipment Monitoring System

The concept of “Internet of Thing” was emerging from last century, and it caused the big wave on the information industry after the Internet business. And most of countries promote the research and development of this new technology into the strategic stage, as to take the lead during the new wave of industrial revolution. With the development of the information and Internet technology, the IOT business already achieved significant development in many fields, especially for the manufactory perspective.During the using process of mechanical equipment and electric systems, fault diagnosis is inevitable. The traditional fault diagnosis technology is mainly limited to fault detect and diagnosis. In addition, the fault detecting methods only focuses on certain equipment, which makes it not so systematic and stay within preventive maintenance stage. The internet technology applied in traditional methods is confined to data transmission, unable to achieve real-time data collecting on site. Not to mention the real-time monitoring the equipment critical parameters.According to the drawbacks and limitation existed in the current fault diagnosis system, equipment monitor and diagnose system has been studied in three aspects in this paper. The system scheme has been established based on the model of the internet of things, and the technology of sensors has been analyzed and studied from the perspective of theory. With respect to data transmission, the transmission schemes based on networking protocol and wireless data transition have been designed. And the related program code has been adopted and applied in the system software base-on Intel Edison platform. In terms of system software, the software structure based on “browser/server” mode has been adopted; and developed through Visual Studio IDE and C# programing language. As to the equipment fault diagnosis and prediction, the algorithm of industrial control limit was applied for fault detecting and predicting. Also function checking and testing have been conducted for the system by setting up simulated testing environment in the laboratory.All above software tools and hardware are free and open to the entire world. The equipment fault detection system is with many features like quick-response, friendly interface, lean service mode. The expansibility was considered during the initial development phase, the detection coverage and predictive maintenance algorithm can be adjusted base on the end user like factories’ customized upgrade and conversion request. It may cover more comprehensive critical equipment parameters like temperature, and mechanical movement, current and voltage matrix for future. With this design model, it will be easy to be upgraded to support more intelligent and complex tool fault detection and monitoring, and all of these will benefit to more accurate and efficient IOT-based predictive maintenance.