Open AccessENHANCING LASER STEP DIAGONAL MEASUREMENT BY MULTIPLE SENSORS FOR FAST MACHINE TOOL CALIBRATION
Author(s) -
Philipp Dahlem,
Benjamin Montavon,
Martin Peterek,
Robert Schmitt
Publication year - 2018
Publication title -
journal of machine engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 7
eISSN - 2391-8071
pISSN - 1895-7595
DOI - 10.5604/01.3001.0012.0928
Subject(s) - machine tool , calibration , computer science , compensation (psychology) , diagonal , coordinate measuring machine , interferometry , process (computing) , measurement uncertainty , metrology , position (finance) , accuracy and precision , optics , engineering , mechanical engineering , mathematics , physics , statistics , geometry , psychology , finance , psychoanalysis , economics , operating system
The volumetric performance of machine tools is limited by the remaining relative deviation between desired and real tool tip position. Being able to predict this deviation at any given functional point enables methods for compensation or counteraction and hence reduce errors in manufacturing and uncertainties for on-machine measurement tasks. Time-efficient identification and quanitification of different contributions to the resulting deviation play a key role in this strategy. The authors pursue the development of an optical sensor system for step diagonal measurement methods, which can be integrated into the working volume of the machine due to its compact size, enabling fast measurements of the axes’ motion error including roll, pitch and yaw and squareness errors without significantly interrupting the manufacturing process. The use of a frequency-modulating interferometer and photosensitive arrays in combination with a Gaussian laser beam allow for measurements at comparable accuracy, lower cost and smaller dimensions compared to state-of-the-art optical measuring appliances for offline machine tool calibration. For validation of the method a virtual machine setup and raytracing simulation is used which enables the investigation of systematic errors like sensor hardware misalignment.