RetComm 1.0: Real Time Condition Monitoring of Rotating Machinery Failure

Abstract

The breakdown of motor proves to be very expensive as it increases downtime on the machines. Development of cost-effective and reliable condition monitoring system for the protection of motors to avoid unexpected breakdowns is necessary. Therefore, RetComm 1.0 is developed as assistant tool for bearing condition diagnosis system. The smartphone accelerometer is used to collect the vibration signal data and send it to computer by using the Android application named Matlab Mobile. The Matlab software is used to implement a program which is the RetComm 1.0 system to analyse the vibration signal and monitor the condition of the bearing. The algorithm used to observe the condition of bearing is trained by using Artificial Neural Network (ANN). In this project, the ANN is trained by using Matlab software. This proposed method is implemented for early diagnosis purposes. The diagnosis process can be done by just attached the smartphone onto the bearing for data collection. In conclusion, the bearing condition can be identified with this system. The bearing condition are shown in text to let the user know the bearing conditions. The raw data and power spectrum graph plotting are to let the user more further to understand the health condition of the bearing.