Replacement study of dump-trucks in an opencast mine in India

1985 ◽  
Vol 3 (4) ◽  
pp. 311-317 ◽  
Author(s):  
S. C. Ray ◽  
I. N. Sinha
Keyword(s):  
Opencast Mine ◽  
Dump Trucks ◽  
Replacement Study

EVALUA TION OF DUST EMISSIONS DURING TRANSPORTA TION OF ROCK MASS AT DEPOSITS DEVELOPED OPEN PIT MINE

2020 ◽  
Vol 2 (1) ◽  
pp. 78-87
Author(s):  
S.V. KOVSHOV ◽  
◽  
A.V. PASYNKOV ◽  
Keyword(s):  
Rock Mass ◽  
Comprehensive Analysis ◽  
Open Pit Mine ◽  
Dust Control ◽  
Open Pit ◽  
Dust Formation ◽  
Dust Suppression ◽  
Dust Emissions ◽  
Opencast Mine ◽  
Dump Trucks

The issues of dust formation and dust suppression in quarries during transportation of rock mass are considered. Foreign and Russian techniques and methods of dust control in open pit mine are analyzed. The limit number of equipment units for the Noyon-Tologoi opencast mine is established, and the dependence of the gross emission of inorganic dust on the number of dump trucks is determined. As a result of a comprehensive analysis, dust suppression methods for a polymetallic open pit mine are proposed.

Stop Control Method of Electrically Driven Mining Dump Trucks

2016 ◽  
Vol 136 (12) ◽  
pp. 978-984
Author(s):  
Akira Kikuchi ◽  
Naoshi Sugawara ◽  
Tomohiko Yasuda
Keyword(s):  
Control Method ◽  
Dump Trucks

Assessment of maintenance schedule uniformity for Belaz dump trucks in Chernogorsky open pit mine

2018 ◽  
pp. 127-133
Author(s):  
E. A. Vakulin ◽  
V. A. Ivashkevich ◽  
E. I.I. Gnitsak ◽  
V. S. Baikin ◽  
S. P. Maslyukov
Keyword(s):  
Open Pit Mine ◽  
Open Pit ◽  
Time Loss ◽  
Maintenance Schedule ◽  
Monthly Average ◽  
Dump Trucks ◽  
Maintenance Personnel ◽  
Productive Time ◽  
Assessment Results

Uniform schedule maintenance of mining and haulage machines is one of the key conditions for increasing productive time of maintenance personnel and decreasing monthly average servicing time. Currently, Russian mines infringe regulated maintenance schedule aimed to improve output per shift. The loss of time of maintenance personnel and equipment as a consequence maintenance irregularity is never assessed. This article presents assessment results on maintenance schedule uniformity in terms of dump trucks BelAZ-7513 and BelAZ-7530 at Chernogorsky open pit mine, SUEK-Khakassia. A variant of calculation of time loss owing to inconsistent maintenance schedule for dump trucks is proposed. The loss of time by maintenance personnel and by mining/haulage machines is assessed. The fleet of dump trucks BelAZ-7513 and BelAZ-7530 is analyzed depending on overtime of operation between maintenance periods. It is recommended to improve uniformity of maintenance schedule for mining and haulage equipment.

Designing of engines for mine dump trucks with due account for mining and operation conditions

2017 ◽  
Vol 136 (6) ◽  
pp. 60-63
Author(s):  
P. Tarasov ◽  
M. Khazin ◽  
E. Fefelov ◽  
V. Furzikov
Keyword(s):  
Operation Conditions ◽  
Dump Trucks ◽  
Mine Dump

scholarly journals Deep Learning Model Comparison for Vision-Based Classification of Full/Empty-Load Trucks in Earthmoving Operations

2019 ◽  
Vol 9 (22) ◽  
pp. 4871 ◽  
Author(s):  
Quan Liu ◽  
Chen Feng ◽  
Zida Song ◽  
Joseph Louis ◽  
Jian Zhou
Keyword(s):  
Deep Learning ◽  
Model Comparison ◽  
Surveillance Systems ◽  
Comparison Study ◽  
Learning Models ◽  
The Core ◽  
Dump Trucks ◽  
Deep Learning Model ◽  
Contact Field

Earthmoving is an integral civil engineering operation of significance, and tracking its productivity requires the statistics of loads moved by dump trucks. Since current truck loads’ statistics methods are laborious, costly, and limited in application, this paper presents the framework of a novel, automated, non-contact field earthmoving quantity statistics (FEQS) for projects with large earthmoving demands that use uniform and uncovered trucks. The proposed FEQS framework utilizes field surveillance systems and adopts vision-based deep learning for full/empty-load truck classification as the core work. Since convolutional neural network (CNN) and its transfer learning (TL) forms are popular vision-based deep learning models and numerous in type, a comparison study is conducted to test the framework’s core work feasibility and evaluate the performance of different deep learning models in implementation. The comparison study involved 12 CNN or CNN-TL models in full/empty-load truck classification, and the results revealed that while several provided satisfactory performance, the VGG16-FineTune provided the optimal performance. This proved the core work feasibility of the proposed FEQS framework. Further discussion provides model choice suggestions that CNN-TL models are more feasible than CNN prototypes, and models that adopt different TL methods have advantages in either working accuracy or speed for different tasks.

Mining Dump Trucks Electrical Traction Equipment Improvement

2020 ◽  
Author(s):  
Anatoliy B. Vinogradov ◽  
Nikolay E. Gnezdov ◽  
Valeriy L. Chistoserdov ◽  
Alexander A. Korotkov
Keyword(s):  
Dump Trucks ◽  
Traction Equipment

Heart and Estrogen/progestin Replacement Study (HERS)

1998 ◽  
Vol 19 (4) ◽  
pp. 314-335 ◽  
Author(s):  
Deborah Grady ◽  
William Applegate ◽  
Trudy Bush ◽  
Curt Furberg ◽  
Betty Riggs ◽  
...  
Keyword(s):  
Replacement Study
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