Auxiliary intelligent operating system for dragline stripping equipment in surface mining

• Autorzy: Sun J.-D. , Zhang R.-X.

Identyfikatory

DOI

10.5277/msc172413

• Języki publikacji: EN

Abstrakty

EN

In order to improve operation skill of the operators, the design of the auxiliary intelligent operating system of the dragline was studied. Whereby the gyroscopes incorporated in smartphone and data sequence filter algorithm, the automatic collection function of operation cycle, the rotation angle and other parameters of the dragline are attained. In line with the relations among the rotation angle of equipment operation, time-spent and the acceleration, the ratio of the acceleration and deceleration rotation angle in full load rotation and non-loaded return stage are acquired respectively. The function of bucket in rotation was realized. Comprehensive score calculation standard of the technique level of the dragline-based operation was developed, and the function of automatic checking the operation level was effectuated. Field experiment results indicated that the operators’ faults are markedly reduced as the auxiliary intelligent operating system is employed. By using the system the operation behavior of low power slow rotation in rain, snow, low atmospheric pressure and other severe weather conditions can be reduced, assuring all-weather efficient and safe operation of dragline.

Słowa kluczowe

EN

dragline stripping; intelligent operating system; operational efficiency

• Wydawca: Wydział Geoinżynierii, Górnictwa i Geologii, Instytut Górnictwa Politechniki Wrocławskiej
• Czasopismo: Mining Science
• Rocznik: 2017
• Tom: Vol. 24
• Strony: 251--266
• Opis fizyczny: Bibliogr. 18 poz., rys., tab.

Twórcy

autor

Sun J.-D.

• State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing)

autor

Zhang R.-X.

• North China Institute of Science and Technology

Bibliografia

• B. ERDEM, BULENT DUZGUN, H. SEBNEM BASKAN, 2005, Dragline cycle time analysis, Journal of Scientific and Industrial Research, 64 (1), 19–29.
• B. ERDEM, F. KORKMAZ, 2012, Analysis of dragline cycle time components, Journal of Mining Science, 48 (3), 545–558.
• CHEN CHUN-YANG, GUO YING, BI JING-XUE, 2014, Experimental analysis of positioning based on smart phone MEMS, Journal of Navigation and Positioning, Beijing, China, 2 (4), 74–82.
• CHEN YAN-LONG, CAI QING-XIANG, ZHOU WEI et al., 2009, Operational efficiency of dragline in surface coal mine, Journal of Mining and Safety Engineering, Xuzhou, China, 26 (2), 221–224.
• COSTELLO M., KYLE J., 2004, A Method for Calculating Static conditions of a Dragline Excavation System using Dynamic Simulation, Mathematical and Computer Modelling, 40, 233–247.
• DEMIREL N., 2011, Effects of the rock mass parameters on the dragline excavation performance, Journal of Mining Science, 47 (4), 441–449.
• GILEWICZ P., 2000, International Dragline Population Matures, Coal Age, 6, 30–32.
• KOMLJENOVIC D., BOGUNOVIC D., KECOJEVIC V., 2010. Dragline operator performance indicator, International Journal of Mining, Reclamation and Environment, 24(1): 34–43.
• LIU TONG, LI KE-MIN, XIAO SHUANG-SHUANG, 2014, Study on operational efficiency of dragline based on grey correlation analysis, Mining Machinery, Harbin, China, 42 (9), 18–21.
• LIU ZHI-CHENG, CHEN XIANG-GUANG, LI YU-FENG et al., 2007, Real time wavelet filtering methods for sensor output time series. Journal of Beijing University of Chemical Technology, Beijing, China, 34(1): 71-75.
• MA XIN-GEN, SUN JIAN-DONG, 2015, Analysis on dragline rotation time-spent and efficient division. Coal Science and Technology, Beijing, China, 47 (s1), 51–54.
• PAN QUAN, MENG JIN-LI, ZHANG LEI et al., 2007, Wavelet filtering method and its application, Journal of Electronics and Information Technology, 29 (1), 236–242.
• RAI P., RATNESH TRIVEDI, NATH R., 2000, Cycle time and idle time analysis of draglines for productivity – A case study, Indian Journal of Engineering and Materials Sciences, 7 (2), 77–81.
• RIDLEY P., CORKE P., 2001, Dragline automation, Robotics and Automation. Proceedings 2001 ICRA, IEEE International Conference, 4, 3742–3747.
• SUN JIAN-DONG, 2016, Research on System Optimization and Application of Dragline Stripping Technology in Surface Mine, China University of Mining and Technology (Beijing).
• SUN JIAN-DONG, ZHANG RUI-XIN, HAO QIANG et al., 2016, Research on Appraisal Standard with Dragline Operation Technique, Coal Mine Machinery, Harbin, China, 9, 23–26.
• SUN JIAN-DONG, ZHANG RUI-XIN, MA XIN-GEN et al., 2016, Study on Efficiency Promotion of Dragline With Single-operation Cycle, Journal of Mining and Safety Engineering, Xuzhou, China, (4), 721–727.
• WANG GUI-LIN, 2012, Research on Efficiency Promotion of Dragline, Surface Mining technology, Liaoning, China, 6, 16–18.