Diagnostics of machine tool linear axes via separation of geometric error sources

Abstract

Manufacturers need automated, efficient, and robust methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. Recently, a method was developed to use data from an inertial measurement unit (IMU) to measure changes in geometric error motions. A linear axis testbed, established for verification and validation purposes, revealed that the IMU-based method was capable of measuring translational and angular deviations with acceptable test uncertainty ratios. In this study, a rail of the linear axis testbed was mechanically degraded to simulate spalling, a common degradation mechanism that can occur during machine tool operations. The rail was degraded in discrete steps from its nominal state (no degradation) to its final state (a failure state of the rail), and IMU and laser-based reference data was collected at each test stage. The contribution of geometric errors from the rail-based degradation were then separated with a technique that utilizes the various data for each run. Diagnostic metrics can then be defined for use with the IMU to facilitate industrial applications by informing the user of the magnitude and location of wear and any violations of performance tolerances.