Inertial Measurement Unit for On-Machine Diagnostics of Machine Tool Linear Axes

Gregory W. Vogl, M. Alkan Donmez, Andreas Archenti, and Brian A. Weiss
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_16_023.pdf1.43 MBAugust 30, 2016 - 10:45am

Machine tools degrade during operations, yet knowledge of degradation is elusive; accurately detecting degradation of machines’ components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated, efficient, and robust methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. Towards this end, a method was developed to use data from an inertial measurement unit (IMU) for identification of changes in the translational and angular errors due to axis degradation. The IMU-based method uses data from accelerometers and rate gyroscopes to identify changes in linear and angular errors due to axis degradation. A linear axis testbed, established for the purpose of verification and validation, revealed that the IMU-based method was capable of measuring geometric errors with acceptable test uncertainty ratios. Specifically, comparison of the IMU-based and laser-based results demonstrate that the IMU-based method is capable of detecting micrometer-level and microradian-level degradation of linear axes. Consequently, an IMU was created for application of the IMU-based method on a machine tool as a proof of concept for detection of linear axis error motions. If the data collection and analysis are integrated within a machine controller, the process may be streamlined for the optimization of maintenance activities and scheduling, supporting more intelligent decision-making by manufacturing personnel and the development of self-diagnosing smart machine tools.

Publication Year: 
2016
Publication Volume: 
7
Publication Control Number: 
023
Page Count: 
7
Submission Keywords: 
wear
degradation
sensor
diagnostics
maintenance
Machine tool
Linear Axis
Error
Submission Topic Areas: 
Component-level PHM
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