Title
Detection And Recognition Method Of Misfire For Chamber (Deep-Hole) Blasting Based On Rfid
Abstract
Deep-hole blasting and chamber blasting technology are widely used in mining and large-scale earth-rock excavation or landfill projects, due to their advantages of high efficiency and low cost. However, their use is often accompanied by misfire accidents, and generally misfire is relatively hidden, as well as difficult to quickly detect and identify, making misfire the greatest potential safety hazard in blasting construction. This paper presents a method and system of frequency division multiple access (FDMA) detection and recognition for blasting misfire, based on electromagnetic wave propagation theory and radio frequency identification technology. Next, the feasibility of frequency division multiple access (FDMA) misfire detection method is analyzed by means of theoretical deduction. Combining field and laboratory tests, it is concluded that the existence of underground misfire with a linear distance of 225 m can be detected. In addition, the detection frequency range is 9755025 Hz, and the recognition accuracy of multi-frequency signal can reach 2 Hz. The stability of the electric detonator in an electromagnetic environment is discussed, and the danger criterion of the electric detonator in the electromagnetic environment is obtained. When the power of the signal transmitter is less than 120 W and the induction area of the electric detonation network is less than 0.5 m(2), then the electric detonator is safe. The misfire detection and recognition system has been successfully applied in a deep-hole blasting of an open-pit quarry. It is observed that when the distance between millisecond blasting holes is equal to greater than 5 m, the detection signals between holes will not interfere with each other. This paper provides a reliable, systematic and complete research method for remote wireless detection and identification of misfire, and also provides a basis for the safety of blasting construction and misfire detection in related projects.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2953548
IEEE ACCESS
Keywords
DocType
Volume
Mining, blasting, misfire, detection and identification, safety
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Liansheng Liu100.34
Lei Yan200.34
Binbin Dong300.34
Wei Liu400.34
Wenhua Yi500.34
Kui Zhao600.68