ESTIMATION OF THE AMPERE CONSUMPTION OF DIMENSION STONE SAWING MACHINE USING THE ARTIFICIAL NEURAL NETWORKS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ARYAFAR AHMAD; MIKAEIL REZA

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF MINING AND GEO-ENGINEERING Year:2016 | Volume:50 | Issue:1 Page(s): 121-130

Download Full-Text

View:

316

Download:

209

Cites:

Information Journal Paper

Title

ESTIMATION OF THE AMPERE CONSUMPTION OF DIMENSION STONE SAWING MACHINE USING THE ARTIFICIAL NEURAL NETWORKS

Author(s)

ARYAFAR AHMAD | MIKAEIL REZA | Issue Writer Certificate

Keywords

AMPERE CONSUMPTION

MACHINE CHARACTERISTIC

NEURAL NETWORK

ROCK CHARACTERISTIC

Abstract

Nowadays, estimating the ampere consumption and achievement of the optimum condition from the perspective of energy consumption is one of the most important steps in reducing the production costs. In this research, we tried to develop an accurate model for estimating the ampere consumption using the artificial neural networks (ANN).In the first step, experimental studies were carried out on 7 carbonate rock samples in different conditions at particular feed rates (100, 200, 300 and 400) and depth of cut (15, 22, 30 and 35mm) using a fully instrumented laboratory rig that is able to change the machine parameters and to measure the ampere consumption. In the next step, a retro-propagation neural network was designed for modelling the sawing process to predict the ampere consumption. The input network consists of two parts: machine, work piece characteristics and the output of neural network was ampere consumption. This research evaluated the competencies of neural networks to estimate the ampere consumption in sawing process. The correlation coefficient between measured and predicted data in training and testing data is 0.95 and 0.97, respectively. The Root Mean Square Error (RMSE) for train and test data is 1.2 and 0.7, respectively. The results of this study show that the ANNs can be used to estimate the ampere consumption with high ability and low error for industrial applications. Moreover, the cost of sawing machine ampere consumption can be accurately estimated using this neural model from some important physical and mechanical properties of rock.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

ARYAFAR, AHMAD, & MIKAEIL, REZA. (2016). ESTIMATION OF THE AMPERE CONSUMPTION OF DIMENSION STONE SAWING MACHINE USING THE ARTIFICIAL NEURAL NETWORKS. INTERNATIONAL JOURNAL OF MINING AND GEO-ENGINEERING, 50(1), 121-130. SID. https://sid.ir/paper/329959/en

Vancouver: Copy

ARYAFAR AHMAD, MIKAEIL REZA. ESTIMATION OF THE AMPERE CONSUMPTION OF DIMENSION STONE SAWING MACHINE USING THE ARTIFICIAL NEURAL NETWORKS. INTERNATIONAL JOURNAL OF MINING AND GEO-ENGINEERING[Internet]. 2016;50(1):121-130. Available from: https://sid.ir/paper/329959/en

IEEE: Copy

AHMAD ARYAFAR, and REZA MIKAEIL, “ESTIMATION OF THE AMPERE CONSUMPTION OF DIMENSION STONE SAWING MACHINE USING THE ARTIFICIAL NEURAL NETWORKS,” INTERNATIONAL JOURNAL OF MINING AND GEO-ENGINEERING, vol. 50, no. 1, pp. 121–130, 2016, [Online]. Available: https://sid.ir/paper/329959/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops