IoT based Predictive Maintenance of Electrical Machines in Aircraft

Airways are the fast-growing mode of transportation; millions of people travel in airplanes around the world. Airways are elevating its progress steeply, where safety is the main concern. There are a lot of safety measures implemented to detect the fault and use alternatives to ensure the safety of passengers. But what if it could be predicted the fault before it occurs and rectify the same. In this paper, a model for IoT based preventive maintenance of the alternators and motors inside the aircraft to ensure more safety before every take off. The research work aims to predict the fault before occurrence and protect the machines from damage. The machines are continuously monitored using sensors such as vibration sensors, current, temperature sensors, and the data is stored in the cloud for further analysis. The data stored in the cloud is analyzed using the required algorithms and the health condition of the machine is examined for maintenance. The entire system is deployed in Node-red (flow-based simulation); data is stored in Thing speak (cloud storage) and analyzed using MATLAB. The visualization charts are displayed for better understanding.

I. Introduction

It is highly visualized how Internet of Things (IOT) upgrades our normal life to smart lifestyle by increasing efficiency, reliability and reducing man power. Currently, IOT is gaining more fame in the aviation industry. Chances are there for a machine to get damaged or repaired during the fly hours. For example, when machine bears current more than its rated current, over heating occurs and insulation degrades rapidly, this lowers the lifetime of the machine associated with increase in faults. There are methods to overcome those faults, but passengers won’t prefer to travel with a chaotic situation like that. When machine is monitored frequently, its state becomes observable. IoT based condition monitoring of generators is presented in [1]. Fault-tolerance of PM brushless DC drive for aerospace application is discussed in [2], [3]. Thermal analysis of fault-tolerant electrical machines for aircraft applications is detailed in [4]–[5]. Real time condition monitoring system for industrial motors is elaborated in [6]. IOT based electrical power generation in aircraft is presented in [7]. IOT based Misalignment detection is discussed in [8]. IoT based predictive maintenance architecture is discussed in [9]. In this article, to ensure high protection and best time of flight, preventive measures are to be taken beforehand. IOT uses a simple mechanism of collecting data from different sensors, sending it to the cloud using gateway, processing details in the cloud and displaying the information to the end users to monitor even if the machine is in remote location. Here, IoT based application is used to analyze both flap motor and generator of an airplane. In this prognosis monitoring system, collecting data and delivering the materials to the cloud is done using node-red platform. Gathered information (current, vibration level, temperature parameters) of the flap motor and the generator using various sensors are dispatched to Thing-speak cloud server and using MATLAB analysis, average value is calculated and monitored whether the mean data crosses the particular threshold value. A vigil message will be then sent from the cloud to the control room, if necessary.