The Internet of Things (IoT) have play an important role in our life and have facilitated us in many ways. One of the most prominent are is the condition monitoring. Compared to regular schedule-based maintenance, condition-based maintenance through IoT have greater advantages for providing continuous monitoring with a warning alarm in the case of failure at an incipient stage. In an induction, bearing accounts for 41% of the failure. Thus, it is a vital important to diagnose these faults to at early stage before it reaches to devastating level. In this research, an experimental setup is designed with respect to real industrial environment using condition monitoring applications. For the sake of ease the health of the motor with inner race distributive defects were analysed through motor current without involving other complicated parameters. In the designed setup, a NI_DAQ platform used as a system brain, a current is directly measured by the CT mounted on the three main cables leading to the motor. Which was transferred to the PC through miscellaneous sensors such as CT that senses the current signature of the motor, and a motion sensor heled to transfer data to remote user android smartphone using Wi-Fi. Based on the feature extraction for a health and faulty bearing when the data exceeds a set threshold, the alarm for a fault motor is triggered and a notification is sent to related maintenance team with the Android smartphone. Moreover, it was obvious for the analysis of the results that the proposed method is more pertinent to diagnose the health of the motor remotely
Internet of Things, Condition Monitoring, Bearing, wireless Wi-Fi; and mobile communication.
Cite this paper
Muhammad Aman Sheikh, Sheikh Tahir Bakhsh, Muhammad Tahir, M.irfan. (2021) New Non-Invasive Hardware and Software Ingetrated Method to Diagnose Motors Fautls Via Remote Access. International Journal of Circuits and Electronics, 6, 1-6
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