DocumentCode
1442359
Title
A low-cost diagnostic tool for stepping motors
Author
Flammini, Alessandra ; Marioli, Danielle ; Taroni, Andrea
Author_Institution
Dept. of Electron. for Autom., Brescia Univ., Italy
Volume
50
Issue
1
fYear
2001
fDate
2/1/2001 12:00:00 AM
Firstpage
157
Lastpage
162
Abstract
This paper presents a low-cost diagnostic tool to point out if an anomalous no-motion condition occurs when stepping motors are used in machine-tool industrial applications. The method is based on current sensing. By evaluating the second derivative of the current in the switched on windings, it is possible to determine if motion takes place. The proposed method has been implemented using a 16-b microcontroller. Since this diagnostic tool is based mainly on the internal resources of the microcontroller and takes about 10 μs every 26 μs, it could be integrated into the digital motor drive. Experimental results show that under heavy-load working conditions about 90% of the anomalous waveforms are detected, while spurious alarms are negligible (0.001% measured with respect to over half a million analyzed waveforms)
Keywords
condition monitoring; electric current measurement; fault diagnosis; machine testing; machine tools; microcomputer applications; microcontrollers; signal processing equipment; stepping motors; waveform analysis; 10 mus; 16 bit; 16-b microcontroller; anomalous no-motion condition; anomalous waveform detection; current second derivative; current sensing; current signal processing; digital motor drive; heavy-load working conditions; low-cost diagnostic tool; machine-tool industrial applications; stepping motors; switched on windings; voltage signal processing; Brushless DC motors; DC motors; Employee welfare; Microcontrollers; Open loop systems; Optical sensors; Optical signal processing; Pulse width modulation; Resonance; Rotors;
fLanguage
English
Journal_Title
Instrumentation and Measurement, IEEE Transactions on
Publisher
ieee
ISSN
0018-9456
Type
jour
DOI
10.1109/19.903894
Filename
903894
Link To Document