An automated flank wear measurement of microdrills using machine vision

Su, Jianbo; Huang, Chang-Yi; Tarng, Y.S.

doi:10.1016/j.jmatprotec.2006.07.001

Cited by 83 publications

(36 citation statements)

References 15 publications

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“…Another study put a drill on a rotary platform that acted in the plane of motion; the image of the drill's gauge edge was then acquired by a CCD camera, and the wear of the gauge edge could be estimated using an image processing algorithm. (5) A machine vision system was used in Ref. 6 to automatically examine the surface defects of thin metal wires (diameter, 50-2000 μm) and to verify the results through electron microscopy.…”

Section: Introductionmentioning

confidence: 99%

A Space Automatic Welding System for Space Position Measurement

Jui‐Chang¹,

Cheng‐Jen²

2017

Sensors and Materials

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Using image capturing techniques, numerical calculations, and laser measurements, an optical measurement system for welding location and distance was constructed to replace the current need to rely on human judgment. This system combines an optical measurement system, a clamping workbench for workpieces, and a device with two sets of welding guns equipped with two planar biaxial translation devices, each consisting of two screws and step motors. Two set clamping mechanisms on the arm are used to fix the laser range finders and image capturing devices. In this study, the image measurement system responsible for obtaining the location and distance for the welding bead is a laser range finder, which integrates position information to determine the location of the welding torch. All of the movement information is eventually sent to the controller to adjust the welding gun and cooperate with the cylinder holder platform for the automatic welding process, providing significantly improved production efficiency. Additionally, this system is functionally able to measure lines, outer and inner circles, angles, distances, and relative heights, and can send the data to the torch to carry out the welding process.

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Section: Introductionmentioning

confidence: 99%

A Space Automatic Welding System for Space Position Measurement

Jui‐Chang¹,

Cheng‐Jen²

2017

Sensors and Materials

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“…Localisation of inserts varies and geometry of the milling head is more complex than in [23]. Su et al [16], Kim et al [10] and Pfeifer et al [14] also localise just two cutting edges for microdrills. Other works [15,19,20] deal with face milling cutting heads, where one can set the acquisition system to easily capture images containing a single insert.…”

Section: Introductionmentioning

confidence: 99%

Cutting Edge Localisation in an Edge Profile Milling Head

Fernández-Robles

Azzopardi

Alegre

et al. 2015

Lecture Notes in Computer Science

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Abstract. Wear evaluation of cutting tools is a key issue for prolonging their lifetime and ensuring high quality of products. In this paper, we present a method for the effective localisation of cutting edges of inserts in digital images of an edge profile milling head. We introduce a new image data set of 144 images of an edge milling head that contains 30 inserts. We use a circular Hough transform to detect the screws that fasten the inserts. In a cropped area around a detected screw, we use Canny's edge detection algorithm and Standard Hough Transform to localise line segments that characterise insert edges. We use this information and the geometry of the insert to identify which of these line segments is the cutting edge. The output of our algorithm is a set of quadrilateral regions around the identified cutting edges. These regions can then be used as input to other algorithms for the quality assessment of the cutting edges. Our results show that the proposed method is very effective for the localisation of the cutting edges of inserts in an edge profile milling machine.

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“…Research using visual vision systems included the use of image processing approach to detect and measure the tool flank wear area using a microscope [13], monitoring the actual tool condition based upon the edge radius of the tool [14], condition monitoring for drilling tools using high speed camera [15] and non-contact vision system for on-line monitoring of the cutting tool without removing the tool from the machine. Gradient detection algorithm with polynomial fitting has been applied in turning [16].…”

Section: Introductionmentioning

confidence: 99%

Cutting tool tracking and recognition based on infrared and visual imaging systems using principal component analysis (PCA) and discrete wavelet transform (DWT) combined with neural networks

Elgargni

Al‐Habaibeh

Lotfi

2014

Int J Adv Manuf Technol

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The implementation of computerised condition monitoring systems for the detection cutting tools' correct installation and fault diagnosis is of a high importance in modern manufacturing industries. The primary function of a condition monitoring system is to check the existence of the tool before starting any machining process and ensure its health during operation. The aim of this study is to assess the detection of the existence of the tool in the spindle and its health (i.e. normal or broken) using infrared and vision systems as a noncontact methodology. The application of Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT) combined with neural networks are investigated using both types of data in order to establish an effective and reliable novel software program for tool tracking and health recognition. Infrared and visual cameras are used to locate and track the cutting tool during the machining process using a suitable analysis and image processing algorithms. The capabilities of PCA and Discrete Wavelet Transform (DWT) combined with neural networks are investigated in recognising the tool's condition by comparing the characteristics of the tool to those of known conditions in the training set. The experimental results have shown high performance when using the infrared data in comparison to visual images for the selected image and signal processing algorithms.

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An automated flank wear measurement of microdrills using machine vision

Cited by 83 publications

References 15 publications

A Space Automatic Welding System for Space Position Measurement

A Space Automatic Welding System for Space Position Measurement

Cutting Edge Localisation in an Edge Profile Milling Head

Cutting tool tracking and recognition based on infrared and visual imaging systems using principal component analysis (PCA) and discrete wavelet transform (DWT) combined with neural networks

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