TY - GEN
T1 - Investigating Torsional Vibration Monitoring Using Optical Sensors and Encoder Wheels
AU - Cassim, Abdool Sattar
AU - Madyira, Daniel Makundwaneyi
AU - Tebeta, Ronny Thapelo
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Torsional vibrations are unwanted phenomena induced by varying torque in power transmission systems. This study investigated torsional vibration measurements using optical sensors and encoder wheels. To achieve this, a test rig was built utilizing a motor, a gearbox with varying speed, a shaft, two bearings, an encoder wheel mounted onto the shaft, an optical sensor, and an Arduino Uno to power the optical sensor and a sensor mount. A National Instruments Data Acquisition System was also used to obtain voltage signals from the optical sensor. These signals were measured at 25, 50, and 75 rpm shaft speeds. The measurements showed a peak at the frequency of the running speeds of 0.42 Hz, 0.83 Hz, 1.25 Hz, and an anomalous signal of 610 Hz. Dividing the 610 Hz signal by the input motor speed of 22 Hz, gave a value of 27, which corresponded to the number of teeth of the gear in the gearbox. Therefore, the 610 Hz signal was caused by gear meshing in the gearbox. Common sources of error induced are Analog-to-Digital conversion errors, encoder wheel defects, or low sensor sensitivity. However, optical sensors and encoder wheels successfully measured torsional vibration signals. This method can be improved by using a higher sensitivity sensor, a high-quality encoder wheel, and a machine learning model to reduce inaccuracies in the data.
AB - Torsional vibrations are unwanted phenomena induced by varying torque in power transmission systems. This study investigated torsional vibration measurements using optical sensors and encoder wheels. To achieve this, a test rig was built utilizing a motor, a gearbox with varying speed, a shaft, two bearings, an encoder wheel mounted onto the shaft, an optical sensor, and an Arduino Uno to power the optical sensor and a sensor mount. A National Instruments Data Acquisition System was also used to obtain voltage signals from the optical sensor. These signals were measured at 25, 50, and 75 rpm shaft speeds. The measurements showed a peak at the frequency of the running speeds of 0.42 Hz, 0.83 Hz, 1.25 Hz, and an anomalous signal of 610 Hz. Dividing the 610 Hz signal by the input motor speed of 22 Hz, gave a value of 27, which corresponded to the number of teeth of the gear in the gearbox. Therefore, the 610 Hz signal was caused by gear meshing in the gearbox. Common sources of error induced are Analog-to-Digital conversion errors, encoder wheel defects, or low sensor sensitivity. However, optical sensors and encoder wheels successfully measured torsional vibration signals. This method can be improved by using a higher sensitivity sensor, a high-quality encoder wheel, and a machine learning model to reduce inaccuracies in the data.
KW - Encoder Wheels
KW - Frequency Signal
KW - Instantaneous Angular Speed
KW - Optical Sensors
KW - Voltage Signal
UR - http://www.scopus.com/inward/record.url?scp=85199577951&partnerID=8YFLogxK
U2 - 10.1109/ICMIMT61937.2024.10585646
DO - 10.1109/ICMIMT61937.2024.10585646
M3 - Conference contribution
AN - SCOPUS:85199577951
T3 - 2024 15th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2024
SP - 74
EP - 79
BT - 2024 15th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2024
Y2 - 17 May 2024 through 19 May 2024
ER -