scholarly journals Determining Surface Topography of a Dressed Grinding Wheel Using Bio-Inspired DNA-Based Computing

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1899
Author(s):  
Akihiko Kubo ◽  
Roberto Teti ◽  
AMM Sharif Ullah ◽  
Kenji Iwadate ◽  
Tiziana Segreto
Keyword(s):  
Image Processing ◽  
Surface Topography ◽  
Processing System ◽  
Computational Effort ◽  
Grinding Wheel ◽  
Abrasive Grains ◽  
Long Duration ◽  
Regular Time ◽  
Grinding Operations ◽  
Processing Techniques

Grinding is commonly used for machining parts made of hard or brittle materials with the intent of ensuring a better surface finish. The material removal ability of a grinding wheel depends on whether the wheel surface is populated with a sufficiently high number of randomly distributed active abrasive grains. This condition is ensured by performing dressing operations at regular time intervals. The effectiveness of a dressing operation is determined by measuring the surface topography of the wheel (regions and their distributions on the grinding wheel work surface where the active abrasive grains reside). In many cases, image processing methods are employed to determine the surface topography. However, such procedures must be able to remove the regions where the abrasive grains do not reside while keeping, at the same time, the regions where the abrasive grains reside. Thus, special kinds of image processing techniques are needed to distinguish the non-grain regions from the grain regions, which requires a heavy computing load and long duration. As an alternative, in the framework of the “Biologicalisation in Manufacturing” paradigm, this study employs a bio-inspiration-based computing method known as DNA-based computing (DBC). It is shown that DBC can eliminate non-grain regions while keeping grain regions with significantly lower computational effort and time. On a surface of size 706.5 μm in the circumferential direction and 530 μm in the width direction, there are about 7000 potential regions where grains might reside, as the image processing results exhibit. After performing DBC, this number is reduced to about 300 (representing a realistic estimate). Thus, the outcomes of this study can help develop an intelligent image processing system to optimize dressing operations and thereby, grinding operations.

Methodology for Evaluation of Treated Steels and Alloys in Abrasive Processing

2021 ◽  
Vol 410 ◽  
pp. 262-268
Author(s):  
Vyacheslav M. Shumyacher ◽  
Sergey A. Kryukov ◽  
Natal'ya V. Baidakova
Keyword(s):  
Physical And Mechanical Properties ◽  
Metals And Alloys ◽  
Grinding Wheel ◽  
Measuring Instruments ◽  
Abrasive Machining ◽  
Machining Performance ◽  
Abrasive Grains ◽  
Abrasive Tools ◽  
Composition Structure ◽  
Grinding Operations

One of the critical physical and mechanical properties of metals and alloys is the suitability for abrasive machining. Machining by abrasive tools is the final operation that sets the desired macro-geometry parameters of processed blanks and microgeometry parameters of processed surfaces such as roughness and length of a bearing surface. Abrasive machining determines the most important physical and mechanical parameters of a blank surface layer, i.e. stresses, phase composition, structure. Machinability by abrasive tools depends on the machining performance affected both by the blank material properties and various processing factors. In our previous studies, we proved that during abrasive machining the metal microvolume affected by abrasive grains accumulates energy. This energy is used for metal dispersion and is converted into heat. According to the theoretical studies described herein, one may note the absence of a reliable and scientifically valid method as well as measuring instruments to determine the machinability of metals and alloys by abrasive tools. For this reason, we suggested a method simulating the effect the multiple abrasive grains produce in a grinding wheel, and enabling us to identify machinability of metals and alloys, select the most efficient abrasive materials for machining of the same, and form the basis for development of effective grinding operations.

In-process detection of grinding wheel truing and dressing conditions using a flapper nozzle arrangement

1997 ◽  
Vol 211 (5) ◽  
pp. 335-343 ◽  
Author(s):  
T M A Maksoud ◽  
A A Mokbel ◽  
J E Morgan
Keyword(s):  
Surface Topography ◽  
Ground Surface ◽  
Grinding Wheel ◽  
Grinding Forces ◽  
Accurate Identification ◽  
Wheel Topography ◽  
On Line ◽  
Sharp Edges ◽  
Process Detection ◽  
Grinding Operations

The spatial distribution of sharp cutting edges around the active periphery of a grinding wheel has an important effect on the surface finish of ground components. In addition, random protrusion of sharp edges can result in a random distribution of grinding forces acting on the ground surface. A uniformly dressed and accurately trued wheel is essential for successful grinding. Since these conditions will alter during use, monitoring of them during grinding must be a requirement for critical grinding operations. This paper describes a new system for achieving on-line detection of the grinding wheel condition. The system uses a small air flapper nozzle-transducer arrangement which detects in-process changes of the grinding wheel surface topography, where external triggering of the data-acquisition system ensures a highly accurate identification of the wheel's surface topography irrespective of wheel speed. The benefits of this system are illustrated by experimental results that correlate the measurement of wheel topography by two means: flapper nozzle and stylus.

An Investigation of Grinding Wheel Cutting Edges

1964 ◽  
Vol 86 (4) ◽  
pp. 371-382 ◽  
Author(s):  
H. Tsuwa
Keyword(s):  
Electron Microscope ◽  
Microscopic Observation ◽  
Phase Contrast ◽  
Grinding Wheel ◽  
Grinding Wheels ◽  
Abrasive Grains ◽  
Contrast Microscope ◽  
New Apparatus ◽  
Grinding Operations ◽  
Dressing Action

A new apparatus for microscopic observation and tracing of cutting edges of a wheel has been developed. The use of this apparatus allows us to visually witness the behavior of abrasive grains during the grinding operation. A phase-contrast microscope, as well as an electron microscope has been used with the new apparatus in this investigation. A method of calculating effective grain spacing to show distribution of cutting edges, as well as the cutting edge ratio to known worn conditions of grains has been completed. These aforementioned values for various grinding wheels have been studied in grinding operations and the changing aspects of them have been noted. Through these experiments, we have had helpful suggestions about grinding mechanisms; there is no self-dressing action of grains in the usual grinding work; sliding of the cutting edges takes place in the grinding, and wear of the grinding is increased by this action.

Real-Time Detection of the Repose Angle of Solids in Rotating Drum Based on Image Processing

2011 ◽  
Vol 301-303 ◽  
pp. 748-751
Author(s):  
Xiao Yan Liu ◽  
Yao Yao Zhang
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Dynamic Change ◽  
Surface Profile ◽  
Processing System ◽  
Automatic Monitoring ◽  
Measuring Method ◽  
Rotating Drum ◽  
Rotary Kilns ◽  
Processing Techniques

Rotating drum is the main part of industrial rotary kilns. The repose angle is one of the most important parameters describing the solids motion inside the drum. A real-time monitoring system is developed in this paper to detect the repose angle based on image processing techniques. The video of the solids motion is taken by a camera and transferred to a computer via an image-sampling box. With a VC++ program, the image of the solids is captured and processed through segmentation, morphology processing and edge detection. The repose angle is determined by linear fitting of the surface profile of the solids bed. With the image processing system, the dynamic change of repose angle with time can be measured and displayed automatically. The effectiveness of the measuring method is proved on a testing drum of 250mm partially filled with rice particles. Results of the present work can be expanded to the automatic monitoring of solids motion in industrial rotary kilns.

Development of Three-Dimensional Measurement System of a Grinding Wheel Surface with Image Processing

2011 ◽  
Vol 325 ◽  
pp. 294-299 ◽  
Author(s):  
Akihiro Sakaguchi ◽  
Tomoyuki Kawashita ◽  
Shuji Matsuo
Keyword(s):  
Image Processing ◽  
Measurement System ◽  
Three Dimensional ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Wheel Surface ◽  
Dimensional Measurement ◽  
Abrasive Grains ◽  
Three Dimensional Measurement ◽  
The One

Grinding process is a very efficient machining technology because innumerable abrasive grains are fixed on the surface of grinding wheel. Especially, the distribution and shape of cutting edges which directly affect grinding process have a big influence on accuracy. Thus, it is very important to measure a wheel surface topography from a viewpoint of evaluating the wheel life and the performance and a relation between the one and the roughness. In this study, a three-dimensional measurement system of a grinding wheel surface with image processing is developed. In this system, the distribution and height of cutting edges are analyzed because only cutting edges can be selected from among all abrasive grains.

Analysis of Blend Irregularity in Yarns Using Image Processing: Part I: Fundamental Investigation of Model Yarns

1992 ◽  
Vol 62 (11) ◽  
pp. 690-696 ◽  
Author(s):  
Akira Watanabe ◽  
Shi-Nya Kurosaki ◽  
Fujio Konda ◽  
Yoshiro Nishimura
Keyword(s):  
Image Processing ◽  
Processing System ◽  
Sample Length ◽  
Blend Ratio ◽  
Short Sample ◽  
Black And White ◽  
Fundamental Investigation ◽  
Computer Image Processing ◽  
Blend Ratios ◽  
Processing Techniques

In this research, a computer image processing system is used to evaluate the blend state (fiber arrangement) or uneven distribution in blended yarns. Part I presents an investigation of the precision and effectiveness of the system using three kinds of model yarns, whose numbers of component filaments, blend ratios, and blend states have been predetermined. The method of image input, various image processing techniques, and a statistical analysis are examined based on the model yarns. The results show clearly that with this system, the diameter and area of one fiber can be measured, the blend ratio of black and white fibers in a short sample length can be accurately determined, and the size of a cluster can be quantitatively evaluated.

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