Investigation on sawing performance of diamond frame saw based on reciprocating swing in processing hard stone

Dong, Peng; Zhang, Jinsheng; Ouyang, Congsen; Sun, Depeng; Wu, Junjie

doi:10.1016/j.jmatprotec.2021.117171

Cited by 12 publications

(7 citation statements)

References 23 publications

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“…The Vickers hardness of minerals was measured experimentally and it was determined that a small increase in hardness leads to a large decrease in the sawing speed. A similar result was obtained by Dong et al [9] who developed an innovative method for sawing hard rocks and demonstrated that the sawing force correlates with the properties of the rock.…”

Section: Introductionsupporting

confidence: 83%

Influence of Mineral Composition in Natural Granite Rocks on Microhardness

Kelemen-Cserta¹,

Gyurika²

2021

Hung. J. Ind. Chem.

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Granites are becoming increasingly popular and, as a result, their areas of use are expanding. In addition to their colour and particle size, the surface roughness of the machined material is becoming an important aspect of their application. In order to create a suitable surface roughness, the type of rocks located on the surface, elemental composition and microhardness of the minerals are important, because knowledge of these characteristics can be used to determine the machining parameters. Microhardness is affected by the atomic percentage values of Si, Al and Na. In addition, for some minerals, a correlation can also be established between the Si, Al and Na components.

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Section: Introductionsupporting

confidence: 83%

Influence of Mineral Composition in Natural Granite Rocks on Microhardness

Kelemen-Cserta¹,

Gyurika²

2021

Hung. J. Ind. Chem.

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“…The wear of diamond particles. According to existing literature, [31][32][33][34] the state of diamond particles can be divided into six types: Fresh, Whole, Micro-fracture, Macrofracture, Blunt, Fall-out, as shown in Figure 5. The states and proportions of diamond particles, which are determined by loads controlled by operating parameters, are believed to reflect the working conditions in a convincing way.…”

Section: Wear Characteristics Of Diamond Segmentsmentioning

confidence: 99%

“…Similarly, extensive studies have been conducted on related area like wear characteristics of the cutting tool, [16][17][18][19][20] sawability, 21,22 and sawing performance. 23,24 Existed literatures have proved the complexity of wear mechanism of diamond tools. Except for randomness in the brittle material processing, varies of factors can make impacts on diamond tools wear.…”

Section: Introductionmentioning

confidence: 99%

Wear mechanisms of diamond segmenta in cutting of carbon fiber reinforced cement-based composite and optimizing in parameters

Wang,

Zhang,

Zhang

et al. 2024

Advances in Mechanical Engineering

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Carbon fiber reinforced cement-based composite material (CFRC) is a novel type of composite material that involves the incorporation of carbon fibers into ordinary concrete. This addition effectively enhances the tensile strength, deformation performance, and dynamic load resistance of reinforced concrete structures. Consequently, CFRC has found increasing applications in the construction industry. The objective of this research is to investigate the wear mechanisms of diamond tools during the sawing process of CFRC and offer guidance on cost reduction through the optimization of processing parameters. The wear analysis of diamond segments can be divided into two categories: matrix wear and diamond particle wear. The diamond particles can exist in different states, and the formation of voids resulting from the detachment of diamond particles is considered as a reference point. The analysis reveals that abrasive wear is the main mechanisms of matrix wear in CFRC sawing. The wear resistance is strongly influenced by the proportion of diamond particles in favorable states, which is determined by the applied loads and operating parameters. The proportion of diamond particles exhibits a clear variation with adjustments made to the feeding speed. Notably, an increase in feeding rate results in a significant decrease in the percentage of blunt particles, reducing it from 28% to 6%. To achieve a lower wear rate, a predictive model was established using Design Expert software based on the experimental results. The model demonstrated that a wear rate as low as 268.5 mm/m2 can be achieved with a flywheel speed of 78 r/min and a feeding speed of 90 mm/h. The optimization process, aimed at minimizing wear rate, was successfully carried out without compromising productivity.

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“…The application of robotic manipulators for the SNS products can make up for the shortcomings of traditional numerical control machining, such as the small working range, the inability to machine large and extremely large sculptures, and poor machining posture [1] . Additionally, diamond grinding tools have been widely used in the field of stone grinding because of their long tool life and strong wear resistance [2] . However, due to the weak stiffness structure of the robotic manipulators and the hard brittleness and complex structure characteristics of SNS, the natural stone blank is easy to collapse or fracture, so the selection of grinding process parameters is put forward higher requirements with the accurate prediction of the trend of processing quality, so as to effectively guide the selection and adjustment of process parameters to ensure the stability of processing quality of SNS products, which is an effective and low-cost way to promote the large-scale application of mechanical arm in the field of stone grinding [3,4] .…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Modeling and Prediction Analysis for Surface Roughness of Special-Shaped Stone by Robotic Grinding

Yin

Cui

2022

IEEE Access

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This paper aims to accurately predict the surface quality of the special-shaped stone by robotic grinding and effectively guide the adjustment of process parameters to ensure stable grinding quality, applies a support vector machine model based on improved whale optimization algorithm (IWOA-SVR), so as to establish a prediction model of surface roughness of special-shaped stone and a selection method of process parameters. The proposed IWOA-SVR was used to improve the prediction accuracy of support vector machine regression model, and a prediction model of surface roughness (R a ) for stone was established. On this basis, the relationship between the output parameters (surface roughness) and inutput parameters (spindle speed, feed speed, cutting depth and cutting width)was explored to obtain more suitable process parameters. Combining the grinding experiment data of special-shaped stone, the comparison was carried out between IWOA-SVR and the SVR model optimized by the commonly used optimization algorithms (grid-search optimization algorithm (GS) and whale optimization algorithm (WOA)). Under the same sample condition, the prediction error of GS-SVR is the most large, and the average prediction error of IWOA-SVR is only 86.1% if that of WOA-SVR, the training time is shortened by 54.4%. The influence of process parameters on surface roughness obtained by IWOA-SVR can effectively guide the selection and adjustment of process parameters. It has good guiding significance for maintaining the excellent grinding quality of specialshaped stone.

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Investigation on sawing performance of diamond frame saw based on reciprocating swing in processing hard stone

Cited by 12 publications

References 23 publications

Influence of Mineral Composition in Natural Granite Rocks on Microhardness

Influence of Mineral Composition in Natural Granite Rocks on Microhardness

Wear mechanisms of diamond segmenta in cutting of carbon fiber reinforced cement-based composite and optimizing in parameters

Data-Driven Modeling and Prediction Analysis for Surface Roughness of Special-Shaped Stone by Robotic Grinding

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