Machine vision micro-milling tool wear inspection by image reconstruction and light reflectance

Szydłowski, Michał; Powałka, B.; Matuszak, Marcin; Kochmański, P.

doi:10.1016/j.precisioneng.2016.01.003

Cited by 72 publications

(18 citation statements)

References 17 publications

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“…Image feature extraction methods based on machine vision include: statistical analysis methods and frequency domain analysis methods. The main statistical methods for analyzing the gray value characteristics of the wear region image include: gray-level threshold method [14], edge detection [15,16,17], and histogram method [18]; analysis methods based on spatial frequency domain feature extraction include: Fourier transform [19], wavelet transform [20] [21] and homomorphic filtering [22]. Statistical analysis methods are widely used basic methods.…”

Section: Chinamentioning

confidence: 99%

Multi-Dimension Tool Wear State Assessment Criterion on the Spiral Edge of Milling Cutter

Tian¹,

Yang²

2021

Preprint

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In the assessment of the tool wear state for the spiral edge of milling cutter based on machine vision, the traditional assessment criterion is often inaccurate due to the problem of information missing or incomplete especially near the tip area. In order to deal with this problem, different lighting-condition setting and additional non-image information compensation techniques are needed . In view of this, an integration tool wear detection method combined line laser edge detection and machine vision is proposed. Subsequently, the combined data acquirement experimental system is designed and built, which can simultaneously acquires two types of parameters: diameter and images under the same detection condition. Then, based on the above information, a multi-dimension series assessment criterion is proposed consisting of three dimensions index: The one-dimensional assessment index gives the average wear value of the spiral side, which mainly used as data ordination and characterizes the rule of tool wear degradation; the two-dimensional assessment index describes the contour of the wear region and calculates the area value, which can predict the change of the tool wear stage more precisely; the three-dimensional assessment index gives the 3D morphology by adding depth information within the wear region and quantified the volume of the worn-off part, which provides clues for early warning of the deterioration caused by the tool worn. Experiments proved that the multi-dimension series assessment criterion is helpful to reflect the trend of tool life and give a more accurate assessment of the tool wear state for the spiral edge of milling cutter.

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Section: Chinamentioning

confidence: 99%

Multi-Dimension Tool Wear State Assessment Criterion on the Spiral Edge of Milling Cutter

Tian¹,

Yang²

2021

Preprint

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“…The reliability of the inspection accuracy is ensured by designing the mechanical design and electrical system design of the tool detector. Based on the original manual vision tool detector, research and development of automatic, higher precision, more stable and reliable, low cost tool detector products [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

A Design of Camera Adjustment Mechanism Based on Automatic Visual NC tool Detector

Yu¹,

Leimeng²,

Tang³

et al. 2019

Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturin

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Aiming at the camera adjustment mechanism of the automatic NC tool detector based on automatic vision affects the measurement accuracy of the tool parameters, the camera adjustment mechanism is designed. The geometric nature of the camera adjustment mechanism is studied, and the camera rotation and its linear motion in the XZ direction are given; analyzes and contrast the accuracy, structure and cost, the structural scheme is obtained; according to the requirements of the itinerary and accuracy requirements, the selection and design of related components were carried out; finally, the strength and stiffness analysis of the main components was carried out. It provides hardware guarantee for improving the detection accuracy of the vision system's tool parameters.

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“…Other works are based on direct measures, which means that they measure the wear of the tool without using intermediate variables. New approaches use machine vision to estimate the tool wear, mainly from bottom view images of the milling tool [ 14 , 15 , 16 ]. They proved to be able to successfully locate the workpiece references [ 17 ], along with the cutting edges of the employed tools [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Stereo Vision System on an Innovative 6DOF Single-Edge Machining Device for Tool Tip Localization and Path Correction

López-Estrada

Fajardo-Pruna

Sánchez-González

et al. 2018

Sensors

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In the current meso cutting technology industry, the demand for more advanced, accurate and cheaper devices capable of creating a wide range surfaces and geometries is rising. To fulfill this demand, an alternative single point cutting device with 6 degrees of freedom (6DOF) was developed. Its main advantage compared to milling has been the need for simpler cutting tools that require an easier development. To obtain accurate and precise geometries, the tool tip must be monitored to compensate its position and make the proper corrections on the computer numerical control (CNC). For this, a stereo vision system was carried out as a different approach to the modern available technologies in the industry. In this paper, the artificial intelligence technologies required for implementing such vision system are explored and discussed. The vision system was compared with commercial measurement software Dino Capture, and a dedicated metrological microscope system TESA V-200GL. Experimental analysis were carried out and results were measured in terms of accuracy. The proposed vision system yielded an error equal to ±3 µm in the measurement.

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Machine vision micro-milling tool wear inspection by image reconstruction and light reflectance

Cited by 72 publications

References 17 publications

Multi-Dimension Tool Wear State Assessment Criterion on the Spiral Edge of Milling Cutter

Multi-Dimension Tool Wear State Assessment Criterion on the Spiral Edge of Milling Cutter

A Design of Camera Adjustment Mechanism Based on Automatic Visual NC tool Detector

Design and Implementation of a Stereo Vision System on an Innovative 6DOF Single-Edge Machining Device for Tool Tip Localization and Path Correction

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