Design of a Contactless Torque Measurement System Based on the Photoelectric Conversion Principle

Torque can intuitively reflect the working status of mechanical systems, making real-time monitoring and accurate measurement of torque essential for ensuring the safe and stable operation of mechanical devices. By analyzing various existing measurement methods, this article proposes a torque measur...

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Vydáno v:IEEE sensors journal Ročník 24; číslo 23; s. 38758 - 38766
Hlavní autoři: Xia, Kun, Li, Ruikai, Jin, Tao, Yuan, Qingqing, Du, Yao
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.12.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Closed loops
Current measurement
Deformation
Deformation effects
Detectors
Double closed-loop feedback
Error analysis
Feedback control
Light emitting diodes
Light sources
Luminous intensity
Measurement methods
Mechanical devices
Mechanical systems
Optical feedback
Particle swarm optimization
particle swarm optimization support vector regression (PSO-SVR) calibration algorithm
photoelectric conversion principle
Photoelectricity
Real time operation
Root-mean-square errors
Rotating shafts
Sensors
Shafts
Strain measurement
Support vector machines
Temperature effects
Torque
Torque measurement
torque measurement system
ISSN:1530-437X, 1558-1748
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Shrnutí:Torque can intuitively reflect the working status of mechanical systems, making real-time monitoring and accurate measurement of torque essential for ensuring the safe and stable operation of mechanical devices. By analyzing various existing measurement methods, this article proposes a torque measurement system based on the photoelectric conversion principle. The system uses an LED light source and a four-quadrant detector to capture the minute deformations of the rotating shaft. To mitigate the adverse effects of temperature and current fluctuations on the LED optical power output, a dual closed-loop feedback control circuit for light intensity and current is designed. This system establishes a correspondence between torque measurements and standard values and uses a particle swarm optimization support vector regression (PSO-SVR) algorithm to achieve measurement calibration. Experimental results show that the system has the root mean square error (RMSE) of 0.67, the mean absolute percentage error (MAPE) of 2.4%, and the mean absolute error (MAE) of 0.49, demonstrating good performance in torque measurement.
Bibliografie:ObjectType-Article-1
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content type line 14
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2024.3471622