Misalignment Detection on Linear Feed Axis with FFT and Statistical Analysis using Motor Current
1
Institute of Production Science, Karlsruhe Institute of Technology, Germany
Submission date: 2021-12-16
Final revision date: 2022-03-23
Acceptance date: 2022-03-25
Online publication date: 2022-04-05
Publication date: 2022-06-28
Corresponding author
Mustafa Demetgül
Institute of Production Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
Institute of Production Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
Journal of Machine Engineering 2022;22(2):31-42
KEYWORDS
TOPICS
ABSTRACT
The linear feed axes are critical subsystems in many production machines and have important responsibilities such as transporting workpieces and tools in the process. Therefore, the component’s working condition is crucial for the production of high-quality products. Because these systems gradually deteriorate, it is necessary to detect these changes and occurring faults with condition monitoring systems. In this study, the motor current of feed axes is monitored for axis misalignment that occurs during or after assembly. We conduct diagnosis with Fast Fourier Transform (FFT) and statistical methods in order to differentiate different misalignment scenarios and operating constraints of the feed axis. Different states are achieved by simulating left and right axis misalignment and operating the table at different speeds and strokes.
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CITATIONS (3):
1.
Misalignment detection on linear feed axis using sensorless motor current signals
Mustafa Demetgul, Ma Zihan, Imanuel Heider, Jürgen Fleischer
The International Journal of Advanced Manufacturing Technology
Mustafa Demetgul, Ma Zihan, Imanuel Heider, Jürgen Fleischer
The International Journal of Advanced Manufacturing Technology
2.
Comprehensive health assessment of faulty and repaired linear axis components through multi-sensor monitoring
Andres Hurtado Carreon, Jose Mario DePaiva, Stephen C. Veldhuis
The International Journal of Advanced Manufacturing Technology
Andres Hurtado Carreon, Jose Mario DePaiva, Stephen C. Veldhuis
The International Journal of Advanced Manufacturing Technology
3.
CNC linear axis condition-based monitoring: a statistics-based framework to establish a baseline dataset and case study
Andres Hurtado Carreon, Jose Mario DePaiva, Rohan Barooah, Stephen C. Veldhuis
Journal of Intelligent Manufacturing
Andres Hurtado Carreon, Jose Mario DePaiva, Rohan Barooah, Stephen C. Veldhuis
Journal of Intelligent Manufacturing
| eISSN: | 2391-8071 |
| ISSN: | 1895-7595 |
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