DocumentCode
2846281
Title
Safety Prediction of Coalface Stray Current Based on BP ANN
Author
Ma-Caoyuan ; Li-Guoxin ; Liang-rui ; Zhang-dongliang ; Dong-xinwei ; Tang-Jiejie
Author_Institution
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
In order to realize safety prediction of workface stray current, it´s important to confirm the characteristic indexes of workface stray current so as to insure the time margin and reliability of prediction. By analyzing the resistance distribution network of the system, the paper confirms the four parameters as follows to be the characteristic indexes of coalface stray current safety prediction: the leakage current of contacting line, resistance of insulating splint, the distance between workface and subtraction substation and the stray voltage of contacting line. After that, the thesis built safety prediction model of coalface stray current danger grade with ANN as its core, chose the field measured data to do the training and prediction of safety prediction model and complete the designing and development of monitoring and predicting system of stray current. The results indicate that the proposed safety prediction model and the prediction system has strong applicability, it shows good effect.
Keywords
backpropagation; coal; mining industry; neural nets; reliability theory; safety systems; artificial neural network; characteristic index; coalface stray current; contacting line leakage current; insulating splint resistance; prediction reliability; resistance distribution network; workface stray current safety prediction; workface-substation distance; Contact resistance; Current measurement; Electrical resistance measurement; Insulation; Leakage current; Monitoring; Predictive models; Railway safety; Substations; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5365093
Filename
5365093
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