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- Vogl, Gregory, et al.
(författare)
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Identification of machine tool geometric performance using on-machine inertial measurements
- 2017
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Ingår i: 6th International Conference on Virtual Machining Process Technology (VMPT 2017).
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Konferensbidrag (refereegranskat)abstract
- Machine tools degrade during operations, yet accurately detecting degradation of machine components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. Towards this goal, a method was developed to use accelerometer and rate gyroscope data from an inertial measurement unit (IMU) for identification of changes in the translational and angular errors due to axis degradation. An IMU was created for application of the method on a machine tool. As a proof of concept for detection of translational error motions, IMU data was collected on a machine tool with experimentally simulated degradation; as the worktable moved along its nominal path, a cross-axis moved along a swept sinusoidal pattern with micrometer-level amplitudes. In another experiment, data was collected at three different locations on a worktable for the same axis motion. These experiments showed that the IMU detected micrometer-level and microradian-level degradation of linear axes, revealing that the IMU-based method is plausible for use in smart machine tools.
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| 3. |
- Vogl, Gregory W., et al.
(författare)
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Inertial Measurement Unit for On-Machine Diagnostics of Machine Tool Linear Axes
- 2016
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 4. |
- Vogl, G. W., et al.
(författare)
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Identification of machine tools linear axes performance using on-machine embedded inertia measurement units
- 2017
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Ingår i: Laser Metrology and Machine Performance XII - 12th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2017. - : euspen. - 9780956679093 ; , s. 65-74
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Konferensbidrag (refereegranskat)abstract
- The current trend in manufacturing industry is from mass production towards flexible and adaptive manufacturing systems and cloud manufacturing. Self-learning machines and robot systems can play an essential role in the development of intelligent manufacturing systems and can be deployed to deal with a variety of tasks that can require flexibility and accuracy. However, in order for the machine tool (physical and control system) to deal with the desired task in a cognitive and efficient manner, the system must be "aware" of its capability and,most importantly,its limitations in order to avoid them and adjust itself to the desired task. Thus, characterization of machine tool accuracy and capability is necessary to realize that. In this study,data from a machine-embedded inertial measurement unit (IMU), consisting of accelerometers and rate gyroscopes,was used for identification of changes in linearand angular errormotions due to changes in operational conditionsor component degradation.The IMU-based results were validated against laser-based measurement results,demonstratingthat the IMU-based method is capable of detecting micrometer-level and microradian-level degradation of machine tool linearaxes.Thus, manufacturers could use themethod to efficientlyand robustly diagnose the condition of their machine tool linear axeswith minimal disruptions to production.
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