cutting pattern
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2021 ◽  
Vol 11 (19) ◽  
pp. 9081
Author(s):  
Changpeng Li ◽  
Tianhao Peng ◽  
Yanmin Zhu

When the shearer is cutting, the sound signal generated by the cutting drum crushing coal and rock contains a wealth of cutting status information. In order to effectively process the shearer cutting sound signal and accurately identify the cutting mode, this paper proposed a shearer cutting sound signal recognition method based on an improved complete ensemble empirical mode decomposition with adaptive noise (ICCEMDAN) and an improved grey wolf optimizer (IGWO) algorithm-optimized support vector machine (SVM). First, the approach applied ICEEMDAN to process the cutting sound signal and obtained several intrinsic mode function (IMF) components. It used the correlation coefficient to select the characteristic component. Meanwhile, this paper calculated the composite multi-scale permutation entropy (CMPE) of the characteristic components as the eigenvalue. Then, the method introduced a differential evolution algorithm and nonlinear convergence factor to improve the GWO algorithm. It used the improved GWO algorithm to realize the adaptive selection of SVM parameters and established a cutting sound signal recognition model. According to the proportioning plan, the paper made several simulation coal walls for cutting experiments and collected cutting sound signals for cutting pattern recognition. The experimental results show that the method proposed in this paper can effectively process the cutting sound signal of the shearer, and the average accuracy of the cutting pattern recognition model reached 97.67%.



2021 ◽  
Vol 8 ◽  
Author(s):  
Hesameddin Khosravi ◽  
Steven M. Iannucci ◽  
Suyi Li

Soft pneumatic actuators have become indispensable for many robotic applications due to their reliability, safety, and design flexibility. However, the currently available actuator designs can be challenging to fabricate, requiring labor-intensive and time-consuming processes like reinforcing fiber wrapping and elastomer curing. To address this issue, we propose to use simple-to-fabricate kirigami skins—plastic sleeves with carefully arranged slit cuts—to construct pneumatic actuators with pre-programmable motion capabilities. Such kirigami skin, wrapped outside a cylindrical balloon, can transform the volumetric expansion from pneumatic pressure into anisotropic stretching and shearing, creating a combination of axial extension and twisting in the actuator. Moreover, the kirigami skin exhibits out-of-plane buckling near the slit cut, which enables high stretchability. To capture such complex deformations, we formulate and experimentally validates a new kinematics model to uncover the linkage between the kirigami cutting pattern design and the actuator’s motion characteristics. This model uses a virtual fold and rigid-facet assumption to simplify the motion analysis without sacrificing accuracy. Moreover, we tested the pressure-stroke performance and elastoplastic behaviors of the kirigami-skinned actuator to establish an operation protocol for repeatable performance. Analytical and experimental parametric analysis shows that one can effectively pre-program the actuator’s motion performance, with considerable freedom, simply by adjusting the angle and length of the slit cuts. The results of this study can establish the design and analysis framework for a new family of kirigami-skinned pneumatic actuators for many robotic applications.



2021 ◽  
Vol 833 (1) ◽  
pp. 012128
Author(s):  
H Copur ◽  
A Shaterpour-Mamaghani ◽  
A Gumus ◽  
D Tumac ◽  
C Balci ◽  
...  


Author(s):  
Hiroki Takahashi ◽  
Seiji Takanashi ◽  
Hori Tomohito ◽  
Ohdo Katsutoshi ◽  
Hino Yasumiti

When walls and columns are demolished during the demolition of buildings in Japan, the lower parts of the walls and columns are cut, after which they are pulled down. This method is called the fall-down method. However, the amount of cutting required is unknown. If a worker cuts the columns too deeply, the walls and columns will collapse and may crush the worker. In this study, the fall-down test of columns was carried out to assess the safety of cutting the lower part of columns. The parameters of the test included the pattern of cutting the lower part of columns and the material properties of the model. In addition, the position of the neutral axis was examined by numerical analysis. The results showed that the cutting pattern involving leaving the main reinforcement at the front of the fall-down and cutting the concrete near the neutral axis is safe at demolition sites. In contrast, the cutting pattern with one row of main reinforcement at the front was unsafe and could potentially lead to premature collapse. Columns at demolition sites should not be cut by this latter cutting pattern. The test and the analysis in this study reproduce the demolition site, and the results of these be widely applied in the actual demolition site.



2021 ◽  
Vol 6 (1) ◽  
pp. 8
Author(s):  
Putra Bahtera Jaya Bangun ◽  
Sisca Octarina ◽  
Laila Hanum ◽  
Ranti Sawitri ◽  
Endro Sastro Cahyono

Cutting Stock Problem (CSP) determines the cutting of stocks with standard length and width to meet the item’s demand. The optimal cutting pattern will minimize the usage of stocks and trim loss. This research implemented the pattern generation algorithm to form the Gilmore-Gomory and Column Generation model in two-dimensional CSP. The CSP in this research had three periods of cutting with different capacities in each period. The Column Generation model added the pattern set-up cost as the constraint. The Gilmore-Gomory model ensured that the first stage’s strips were used in the second stage and met the item’s demand. Based on the Column Generation model’s solution, the 1st period used the 2nd, 4th, and 5th patterns, the 2nd period used 4th and 5th patterns, and the 3rd period did not use any patterns. The first and second periods fulfilled all of the demands.



2021 ◽  
Vol 11 (1) ◽  
pp. 464
Author(s):  
Dmitriy Shishlyannikov ◽  
Ivan Zvonarev

The creation of modern machines and improvement of existing designs of rock cutting bodies of combines is constrained by the lack of experimental studies of the process of separation of successive elementary cleavages during the potash ore cutting with cutters of winning machines. The potential of the cross cutting pattern of potash ore is shown, since the formation of zones of localization of weakening and induced fractures on the surface of layer-by-layer cutting face determines the separation of the elementary cleavages with stable geometric parameters. The verification of the conclusions obtained theoretically was carried out during laboratory tastings on a specially designed bench. The research procedure provided for comparative tests of the potash block ore cutting, staggered and cross cuttings. It has been proven that the use of the cross pattern for set cutting parameters makes it possible to reduce the specific energy costs of the cutting of potash mass, to reduce the average load on the cutter, to reduce the root-mean-square deviation, and to reduce the number of fractions that are hard to enrich in the crushing products, compared to the traditional staggered cutting pattern.



2020 ◽  
Vol 5 (4) ◽  
pp. 121
Author(s):  
Sisca Octarina ◽  
Devi Gusmalia Juita ◽  
Ning Eliyati ◽  
Putra Bahtera Jaya Bangun

Cutting Stock Problem (CSP) is the determination of how to cut stocks into items with certain cutting rules. A diverse set of stocks is called multiple stock CSP. This study used Pattern Generation (PG) algorithm to determine cutting pattern, then formulated it into a Gilmore and Gomory model and solved by using Column Generation Technique (CGT). Set Covering model was generated from Gilmore and Gomory model. Based on the results, selected cutting patterns in the first stage can be used in the second stage. The combination of patterns generated from Gilmore and Gomory model showed that the use of stocks was more effective than Set Covering model.  



2020 ◽  
Vol 68 ◽  
pp. 101761
Author(s):  
Mohamed Elkarmoty ◽  
Stefano Bonduà ◽  
Roberto Bruno


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