AbstractThe spindle rotational accuracy is one of the important issues in a machine tool which affects the surface topography and dimensional accuracy of a workpiece. This paper presents a machine-vision-based approach to radial error measurement of a lathe spindle using a CMOS camera and a PC-based image processing system. In the present work, a precisely machined cylindrical master is mounted on the spindle as a datum surface and variations of its position are captured using the camera for evaluating runout of the spindle. TheCircular Hough Transform(CHT) is used to detect variations of the centre position of the master cylinder during spindle rotation at subpixel level from a sequence of images. Radial error values of the spindle are evaluated using the Fourier series analysis of the centre position of the master cylinder calculated with the least squares curve fitting technique. The experiments have been carried out on a lathe at different operating speeds and the spindle radial error estimation results are presented. The proposed method provides a simpler approach to on-machine estimation of the spindle radial error in machine tools.

Denis Ashok S

Department of Design and Automation

School of Mechanical Engineering

Vellore Campus

Kavitha C

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Metrology and Measurement Systems

Radial error measurement of a high speed spindle is commonly affected by speed variations, centring error, form error of master cylinder and thermal drift of the spindle. This paper presents a least square curve fitting technique for processing the high speed spindle data using a mathematical model consisting of a second-order polynomial and sum of sinusoidal functions. Re-sampling method is proposed for accounting the spindle speed variations. Performance of the proposed method is compared with Fourier transform based frequency domain filtering method. Simulation and experimental results confirm the accuracy of the proposed method for analysing the time sampled spindle data. Copyright © 2011 Inderscience Enterprises Ltd.

International Journal of Manufacturing Research

Least square curve fitting technique for processing time sampled high speed spindle data

The measurement and evaluation of spindle errors is an important task in the assessment of the accuracy of machine tools. The commonly followed capacitive-sensor-based measurement technique requires a comprehensive error separation method for the identification of the unwanted contributions of centering error, the form error of the artifact and thermal drift. This paper presents a method for form error separation that is suitable for the evaluation of the radial error of high-speed spindles. In the present work, a fixed sensitive radial error motion test is conducted using a capacitive sensor and a cylindrical artifact at different spindle speeds. A mathematical model consisting of a second-order polynomial and Fourier series function is used to interpret the data measured in the time domain. The form profile of the artifact is measured separately in a roundness tester using a capacitive sensor. A harmonic analysis method is proposed to identify and separate the dominant harmonic components in the form profile of the artifact. A mathematical description of the proposed method is described and experimental results are presented. Application of the proposed method to the evaluation of the synchronous radial error of a high-spindle is provided for measured data. The proposed method analyzes the data measured in the time domain and is suitable for the identification of the spindle errors at high-speed conditions. © IMechE 2012.

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Harmonic-analysis-based method for separation of form error during evaluation of high-speed spindle radial errors

Miniaturized machine tools have been established as a promising technology for machining the miniature components in wider range of materials. Spindle of a miniaturized machine tool needs to provide extremely high rotational speed, while maintaining the accuracy. In this work, a capacitive sensor-based measurement technique is followed for assessing radial errors of a miniaturized machine tool spindle. Accuracy of spindle error measurement is affected by inherent error sources such as sensor offset, thermal drift of spindle, centering error, and form error of the target surface installed in the spindle. In the present work, a model-based curve-fitting method is proposed for accurate interpretation and analysis of spindle error measurement data in time domain. Experimental results of the proposed method are presented and compared with the commonly followed discrete Fourier transform-based frequency domain-filtering method. Proposed method provides higher resolution for the estimation of fundamental frequency of spindle error data. Synchronous and asynchronous radial error values are evaluated in accordance with ANSI/ASME B89.3.4M [9] standard at various spindle speeds and number of spindle revolutions. It is found that the spindle speed and number of spindle revolutions does not have much influence on synchronous radial error of the spindle. On the other hand, asynchronous radial error motion exhibits a significant speed-dependant behavior with respect to the number of spindle revolutions. © Springer-Verlag London Limited 2011.

International Journal of Advanced Manufacturing Technology

Modeling, measurement, and evaluation of spindle radial errors in a miniaturized machine tool

Surface roughness parameter prediction and evaluation are important factors in determining the satisfactory performance of machined surfaces in many fields. The recent trend towards the measurement and evaluation of surface roughness has led to renewed interest in the use of newly developed non-contact sensors. In the present work, an attempt has been made to measure the surface roughness parameter of different machined surfaces using a high sensitivity capacitive sensor. A capacitive response model is proposed to predict theoretical average capacitive surface roughness and compare it with the capacitive sensor measurement results. The measurements were carried out for 18 specimens using the proposed capacitive-sensor-based non-contact measurement setup. The results show that surface roughness values measured using a sensor well agree with the model output. For ground and milled surfaces, the correlation coefficients obtained are high, while for the surfaces generated by shaping, the correlation coefficient is low. It is observed that the sensor can effectively assess the fine and moderate rough-machined surfaces compared to rough surfaces generated by a shaping process. Furthermore, a linear regression model is proposed to predict the surface roughness from the measured average capacitive roughness. It can be further used in on-machine measurement, on-line monitoring and control of surface roughne ss in the machine tool environment. © 2011 Polish Academy of Sciences. All rights reserved.

Journal	Data powered by TypesetMetrology and Measurement Systems
Publisher	Data powered by TypesetWalter de Gruyter GmbH
ISSN	08608229
Open Access	No