Implementation of FFT in Industrial Induction Motor Monitoring via Mobile Phone

Abstract

Competition in the industrial world requires companies to always improve efficiency in the production process. The use of communication technology in the monitoring process is one way to reduce effort in monitoring equipment. This study aims to create a mobile phone-based online control and monitoring system for induction motor parameters in the industry without interfering with the motor's electrical network. The monitoring system is carried out by monitoring the vibration and temperature of the induction motor using the GY-521 MPU-6050 sensor connected to the NodeMCU ESP8266 as the control device. For the data computation process to obtain rotational parameters, the Fast Fourier Transform (FFT) function is applied to transform the vibration data from the accelerometer into the frequency domain. In the data collection process, 250 data samples were captured in 1 second which were formed from vibrations of the X, Y and Z direction motors. Manual ON/OFF control of the electric motor and automatic OFF was carried out when a spike in the vibration frequency of the motor was detected. The test was carried out with four variations of rotation conditions. The test results show that the rpm speed of the motor can be obtained based on the difference in the frequency of motor vibration. This data is then sent online to observer technician via the Telegram application installed on the mobile phone device. The system performance as a whole shows quite good performance both in terms of equipment placement, data processing and delivery.

Implementation in Microcontrollers of an Algorithm for the Simple Generation of Speed Profiles in a Stepper Motor and Their Associated Kinematics

“…MEMS accelerometers are devices that have undergone several controlled mechanical tests to characterize their response when exposed to vibrations [63], [65], [66]; some of their attractiveness is related to their small dimensions and low cost compared to those based on the piezoelectric phenomenon [65]. MEMS accelerometers have great potential for extensive application in fault detection or diagnostics of bearings and motors [62], [64], [67]- [78]. There are a variety of reports on MEMS accelerometers for measuring vibrations.…”

“…Some of these include circuits with analog output from the company Analog Devices such as ADXL335 [16], [63]- [65], [72], [73], [76], ADXL356 [66], ADXL322 [68], and ADXL203 [77]; those of NXP USA Inc., such as MMA6270QT of [62], and MMA7260Q [43]. Various researchers have also employed those having digital output, some from Analog Devices: ADXL345 [16], [63], [65], [67], [74], and ADXL355 [73]; those of NXP which includes the MMA8451Q [75], and the FXLS8471Q [70]; the LSM6DS3TR of STMicroelectronics [71]; and TDK's MPU-6050 [63], [65], [78]. One of the mathematical tools to analyze oscillations consists of applying to the raw signals of MEMS accelerometers the discrete Fourier transform (DFT), using the FFT (Fast Fourier Transform) algorithm [62], [70], [72], [73], [75]- [78].…”

“…Various researchers have also employed those having digital output, some from Analog Devices: ADXL345 [16], [63], [65], [67], [74], and ADXL355 [73]; those of NXP which includes the MMA8451Q [75], and the FXLS8471Q [70]; the LSM6DS3TR of STMicroelectronics [71]; and TDK's MPU-6050 [63], [65], [78]. One of the mathematical tools to analyze oscillations consists of applying to the raw signals of MEMS accelerometers the discrete Fourier transform (DFT), using the FFT (Fast Fourier Transform) algorithm [62], [70], [72], [73], [75]- [78]. An application of interest in this work involving these devices is related to the fact that they allow the estimation of the residual vibration introduced by the velocity profiles [16], [25], [29], [43].…”