@inproceedings{382c25780b8b4e5aa34d3b90628cce7d,
title = "Uncertainty analysis based geometric error detection for heavy-duty machine tools",
abstract = "In order to measure the geometric errors of heavyduty machine tools with high efficiency and high precision, an uncertainty analysis method based on Monte Carlo theory is presented to determine the detection of geometric errors for heavy-duty machine tool. It is found that 4-station orderly multilateral method is the preferred method for heavy-duty machine tool geometric error detection through the comparison among the measurement uncertainty of single station method, multilateral method and different station numbers sequentially multilateral method. The experimental results show that 4-stations sequentially multilateral method can improve the detection efficiency, and the errors are similar to the direct measurement of the laser interferometer.",
keywords = "Geometric errors detection, Heavy-duty machine tools, Laser tracker, Measurement, Uncertainty",
author = "Zhongxi Shao and Shilei Wu and Han Wang and Hui Jiang and Hongya Fu",
year = "2016",
month = dec,
day = "5",
doi = "10.1109/IMCCC.2016.79",
language = "英语",
series = "Proceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "262--265",
editor = "Junbao Li",
booktitle = "Proceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016",
address = "美国",
note = "6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016 ; Conference date: 21-07-2016 Through 23-07-2016",
}