A study on transient electromagnetic signal acquisition and processing for exploring hidden disaster-causing factors in coalmine

By general exploration there is one or more geologic abnormal areas within Fumei No. 1 Coalmine Industrial Square and Shaft, which will affect the mine shaft construction and safety production. However, traditional methods for hidden disaster-causing factors will not meet the exploration demands because of their defects. For example, direct current electric method, geological radar and even three-dimensional seismic prospecting can not simultaneously identify geologic abnormal areas of water-bearing condition both underground and in mid-deep zone. Therefore, to explore hidden disaster-causing factors more fully, this paper puts forward a signal acquisition and processing way based on transient electromagnetic method. On the principle of transient electromagnetic method, a system of transient electromagnetic signal acquisition is built and composed of transmitter unit and receiver unit. By triggering start button, the system wirelessly triggers transmitter unit, i.e. one pulse magnetic field to the underground each time. 4ms later, two receiver coils simultaneously collect signals of the secondary pulsed magnetic field caused by underground medium. Finally the signal data are stored in CF card after RC filtering, operational amplifying, sample integral and analog-to-digital conversion. From the signal data processing and analyzing results, there are hidden disaster-causing factors in the exploration zone: one collapse column, one coalmine goaf and one underground watercourse. Compared with the geological data of pilot holes of shaft, these three geologic abnormal places are confirmed, which powerfully helps prove the reliability and efficiency of this method of signal acquisition and processing. These relevant exploration data can not only provide geologic basis for construction of industrial square buildings and structures, but also supply design and construction of shafts with instructions, and furthermore, serve as data reference for exploration of hidden disaster-causing factors in more complicated geological conditions areas.