Development of a laser-based measurement system for evaluation of the scraping workpiece quality

Hsieh, Tsung‐Hsun; Jywe, Wen-Yuh; Huang, Hsuan‐Jung; Chen, Shang Liang

doi:10.1016/j.optlaseng.2011.04.005

Cited by 28 publications

(12 citation statements)

References 17 publications

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“…As shown in Figure 7, the measurement path was inspired by previous study [13]. The straightness variation of the moving working table is detected by PSDs.…”

Section: Measurement Principlementioning

confidence: 99%

“…The triangulation laser was mounted on the spindle head (i.e., Z-axis) of the machine tool, which was utilized for ball-screw profile detection and flatness measurement in previous study [13,14]. Up to the present, there is no commercial instrument capable of conducting dual-axis straightness measurements on the proposed system, therefore, the feasibility of the proposed system is determined according to the repeatability of the flatness measurement.…”

Section: Verification Of the Flatness Measurement Systemmentioning

confidence: 99%

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An Online Simultaneous Measurement of the Dual-Axis Straightness Error for Machine Tools

et al. 2018

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Vertical straightness errors are the key factor that affects the flatness of the workpiece during vertical machining. Traditionally, the individually measured and fitted vertical straightness errors of the X and Y axes are used to compensate the Z axis and, thus, obtain the flatness of the working table of the machine tool. However, it is difficult to measure and compensate the vertical straightness error of the desired position on the working table, not to mention the centroid variation effect of the working table on the measured data. In this study, an online dual-axis measurement system with repeatability (3σ) of 2.46 μm is developed to simultaneously measure X-axis and Y-axis straightness errors of the desired position of a working table. Furthermore, the measured data are utilized to establish a flatness error model to reduce the vertical straightness error of the working table such that the repeatability (3σ) of the measured flatness may be kept within a range of 0.65 μm.

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“…As shown in Figure 7, the measurement path was inspired by previous study [13]. The straightness variation of the moving working table is detected by PSDs.…”

Section: Measurement Principlementioning

confidence: 99%

Section: Verification Of the Flatness Measurement Systemmentioning

confidence: 99%

An Online Simultaneous Measurement of the Dual-Axis Straightness Error for Machine Tools

et al. 2018

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“…Many research groups imitate the procedure of hand scraping by detecting dark and bright spots on the rubbed surface using cameras [11][12][13][14][15]19,20]. Fan et al scanned the surface using a dedicated system based on a DVD pick-up head [21], while Hsieh et al used a laser triangulation sensor [22]. Generally, measuring the workpiece surface with sufficient precision and in reasonable time remains a challenge to be solved for the implementation of automated scraping.…”

Section: Overview and Literaturementioning

confidence: 99%

Investigation into Hand Scraping: A Microanalysis

Oßwald

Lochmahr

Bagci

et al. 2018

JMMP

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Hand scraping is a manual surface finishing process that, despite its low productivity and high cost, is still applied in many industries because of its advantages concerning accuracy and tribology. In the presented microanalysis forces, movement patterns and tool orientation of individual hand scraping strokes were measured using a test stand, specifically designed for this purpose. It utilizes a camera, a three dimensional dynamometer, and an inertial measurement unit (IMU). The results show the basic characteristics of hand scraping. Typical courses of relevant quantities like cutting force, passive force, clearance, and directional angle are shown. In addition, the movement pattern of the tool during individual scraping strokes is analyzed. This research aims to contribute to a later implementation of automated scraping. The conducted research creates a base for future research regarding different scraping methods and achieved results.

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“…This concept was implemented for automation by several research groups and transferred into a task of an automated camera-based system [10,11]. An alternative approach was taken by Hsieh et al [12] who used a scanning triangulation sensor to obtain a model of the workpiece surface.…”

Section: Introductionmentioning

confidence: 99%

Macroanalysis of Hand Scraping

Oßwald

Gissel

Lochmahr³

2020

JMMP

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Hand scraping is a manual metalworking method that is still used in many industries to obtain good planarity, low friction and good gliding properties of metal and plastic surfaces. However, it is characterized by low productivity and requires skilled and well-trained workers. This macroanalysis focuses on the strategy and procedure of the workers during the scraping operation. Forces and tool positions were acquired simultaneously and the resulting surfaces were measured after each scraping pass. Results show that in most instances differences between individual workers’ scraping styles are more significant than between consecutive scraping passes. This research was conducted in order to gather sufficient insight into the hand scraping method to take steps towards its automation.

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Development of a laser-based measurement system for evaluation of the scraping workpiece quality

Cited by 28 publications

References 17 publications

An Online Simultaneous Measurement of the Dual-Axis Straightness Error for Machine Tools

An Online Simultaneous Measurement of the Dual-Axis Straightness Error for Machine Tools

Investigation into Hand Scraping: A Microanalysis

Macroanalysis of Hand Scraping

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