Number of Points for Roundness Measurement - Measured Results Comparison

Görög, Augustín

doi:10.2478/v10186-010-0035-x

Cited by 4 publications

(3 citation statements)

References 1 publication

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“…The behavior of the mechanism when positioning the camera along a circular path can also be described by the geometric tolerances prescribed by STN EN ISO 1101:2006. These geometric tolerances are divided into 4 categories according to the standard: geometric tolerances of shape, position, orientation, and throw [28,29].…”

Section: Processing the Results By Moving Along The Circle R20mentioning

confidence: 99%

Mechatronic Device Control by Artificial Intelligence

Bohušík

Stenchlák

Císar

et al. 2023

Sensors

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Nowadays, artificial intelligence is used everywhere in the world and is becoming a key factor for innovation and progress in many areas of human life. From medicine to industry to consumer electronics, its influence is ever-expanding and permeates all aspects of our modern society. This article presents the use of artificial intelligence (prediction) for the control of three motors used for effector control in a spherical parallel kinematic structure of a designed device. The kinematic model used was the “Agile eye” which can achieve high dynamics and has three degrees of freedom. A prototype of this device was designed and built, on which experiments were carried out in the framework of motor control. As the prototype was created through the means of the available equipment (3D printing and lathe), the clearances of the kinematic mechanism were made and then calibrated through prediction. The paper also presents a method for motor control calibration. On the one hand, using AI is an efficient way to achieve higher precision in positioning the optical axis of the effector. On the other hand, such calibration would be rendered unnecessary if the clearances and inaccuracies in the mechanism could be eliminated mechanically. The device was designed with imperfections such as clearances in mind so the effectiveness of the calibration could be tested and evaluated. The resulting control of the achieved movements of the axis of the device (effector) took place when obtaining the exact location of the tracked point. There are several methods for controlling the motors of mechatronic devices (e.g., Matlab-Simscape). This paper presents an experiment performed to verify the possibility of controlling the kinematic mechanism through neural networks and eliminating inaccuracies caused by imprecisely produced mechanical parts.

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Section: Processing the Results By Moving Along The Circle R20mentioning

confidence: 99%

Mechatronic Device Control by Artificial Intelligence

Bohušík

Stenchlák

Císar

et al. 2023

Sensors

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“…It solved the problem of nonlinear phase of the 2RC and could be implemented digitally quite easily. Commission for approval of ISO standards introduced Gauss filter for filtering the measurement data of 2D profiles as a standard [4].…”

Section: Filtering Datamentioning

confidence: 99%

Number of Points for Roundness Measurement - Measured Results Comparison

Görög¹

2011

Research Papers Faculty of Materials Science and Technology Slovak University of Technology

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Number of Points for Roundness Measurement - Measured Results Comparison Paper deals with filtering roundness. It presents experimental results measured for roundness turning and cylindrical grinding. Roundness was measured using Prismo Navigator 5 coordinate measuring machine. Evaluation was done by four methods: Minimum zone reference circles (MZCI), Least squares reference circle (LSCI), Minimum circumscribed reference circle (MCCI) and Maximum inscribed reference circle (MICI). The filters used were: Gauss, Spline and no filter.

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“…However, the method is mainly useful when a small number of measured points and their location on a complex uneven surface. In conclusion, complex and time-consuming operations are needed to obtain sufficient measurement data by these methods, and the specific form error of microspheres obtained only by fitting the contour from several points instead of scanning or the sphericity evaluated by the LSS method is proved inaccurate [43]. Although tactile measurement obviously cannot cover the complete surface profile of the measured sphere as optical measurement, its measurement accuracy and reliability are more advantageous.…”

Section: Introductionmentioning

confidence: 99%

High-precision radius and sphericity measurement for microspheres of micro-CMM probe tip

Zhao

Duan

et al. 2023

Meas. Sci. Technol.

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The microsphere profile of probe tips has to be measured and compensated to improve the measurement accuracy of micro-coordinate measuring machines (micro-CMMs) to less than several hundred nanometers. A high-precision radius and sphericity measurement method for the microsphere of the CMM probe tip is proposed in this article. Different circumferences of the tested microsphere are measured, and the true radius of any measuring point on the surface can be obtained after separating the runout errors. Then the sphericity of the tested microsphere can be evaluated by the minimum zone sphere (MZS) method. A corresponding measuring system is developed based on the analysis of the primary error model and mechanical model, and verification experiments are conducted using a ruby microsphere (A-5000-7801, Renishaw Corporation) as the reference, whose claimed diameter and sphericity are 700 µm and 130 nm, respectively. Six groups of repeated experiments are performed, and 18000 measurement points on 15 circumferences are recorded in each group of experiments. Results show that the average radius of the tested microsphere is 350.003 µm, and the average sphericity error is 208 nm with a standard deviation of 5.3 nm. Finally, the expanded uncertainty of the measurement results of the developed system is calculated as 209 nm (k=1.96, normal distribution). The proposed method and system can be used in the precision measurements and compensations for probe tips of micro-CMMs and other parts, such as microspheres used in micro-bearings and micro-manufacturing machines.

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Number of Points for Roundness Measurement - Measured Results Comparison

Cited by 4 publications

References 1 publication

Mechatronic Device Control by Artificial Intelligence

Mechatronic Device Control by Artificial Intelligence

Number of Points for Roundness Measurement - Measured Results Comparison

High-precision radius and sphericity measurement for microspheres of micro-CMM probe tip

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