Hebei Zhongwei Mining Machinery Co, Ltd

Li Yue, Zhou Yaoqi

(Dongying 257061, Shandong Province, open laboratory of Geochemistry and lithospheric dynamics, China University of Petroleum (East China))

Introction to the author: Li Yue, female, born in Cangzhou, Hebei Province in December 1979, graated from petroleum geology, China University of petroleum in 2002, with a bachelor's degree and a doctoral degree. Research direction: geological resources and geological engineering, Email: lyysy_ [email protected]

key words: MEMS technology fracturing micro fracture coal mine disaster

Application of MEMS in forecast of gas disaster of coalmine

Li Yue, Zhou Yaoqi

(geochemistry & Lithosphere dynamic open laboratory, China University of petroleum, Dongying 257061

Abstract：Based on the monitoring to the fracturing process of the granitic sample by MEMS，applying the monitoring principle，we discussed the application of MEMS in forecasting the gas blowing up.In this experiment，continually forcing to the sample， we observed four series of micro-fracture.The anterior three series of microfracture before the main fracture were because of the crack in the sample centralizing and connecting，which was regarded as the portent of the earthquake.The main-fracture proced the crack in macro.Based on the beforementioned principle， it was concluded that the forecast of mine blast resulted from the mining and crude earthquake had the good effect by this technology.

Keywords：MEMS fracturing micro-fracture MEMS (micro electro mechanical systems) is usually called micro electro mechanical system technology, which means that it can be mass proced, including micro mechanism, micro sensor, micro actuator, signal processing and control circuit, including interface, communication and power supply< Sup > [1] < / sup >

mine accidents account for a considerable proportion of major casualties in recent years, and gas explosion and earthquake inced by construction bring great threat to the workers. This paper mainly discusses the application of MEMS technology in the prediction of coal mine disasters on the basis of experiments

1 experiment

the experiment mainly uses the sensitive characteristics of MEMS technology to observe the instantaneous response of the sensor when micro fracture occurs by monitoring the fracture process of granite

1.1 brief introction of samples and observation system. Processed into 50 × fifteen × 5 cm < sup > 3 < / sup >. Granite has uniform grain structure, mainly composed of quartz, feldspar, biotite and a small amount of heavy minerals. The maximum phenocryst size of feldspar is about 5mm, and the average grain size is 0.5-3mm. Biotite is usually linear along the edge of quartz feldspar grains (see Figure 1)

Fig. 1 microstructure of granite (orthogonal polarization) × The sensor adopts four single component acceleration sensors of me ms-1221 l proced by Dongying micro technology development company. The sensitivity is 2 V / g, the resolution is 10 < sup > - 4 < / sup > G, and the frequency range is 0 ~ 1000Hz. The data acquisition and analysis system is a general data monitoring and analysis software RBH general developed by dongyinggan micro technology development company

WE-300 press was used in the fracturing experiment (Fig. 2). The observation system is shown in Figure 2 (b) and figure 3

Fig. 2 experimental press and observation system

A is WE-300 experimental press, B is the sensor placement and compression support position of rock sample observation system

Fig. 3 head up view of observation system

in which No. 1, 2, 3 and 4 are four sensors, and sensors 1 and 4 are close to the edge of rock block. Four sensors are on a horizontal line. The distance between the center of sensor 1 and sensor 2 is 10 cm, and that between sensor 3 and sensor 4 is the same. The radius of the sensor is 2.5cm

1.2 discussion on the experimental process and data; Then, the four sensors are placed on the rock sample in turn (Fig. 3), and their respective positions are recorded. At the same time, the sensors are connected with the data acquisition and analysis system, so as to record the signals from different parts of the micro fracture

time recording starts from 0 seconds, and the sampling frequency is 4000Hz. The application process of pressure is graal. The pressure increases graally from 0 kn. The spectrum of noise is recorded when the data changes. When the pressure increases to such an extent that the internal structure of rock sample changes, the spectrum changes immediately. The change process of spectrum will be discussed in the following section. Red represents the spectrum of sensor 1, black represents the spectrum of sensor 2, Blue represents the spectrum of sensor 3 and yellow represents the spectrum of sensor 4. In the nearly 360 second fracturing process, the real sample fracture is completed in the last minute, that is, 302.290 ~ 303.826 s, respectively; 305.599～307.135 s Four batches of microfractures occurred in 316.793-318.329 s and 357.923-360.258 s. Except for the last batch of microcracks lasting more than 2S, the previous three batches of microcracks lasted less than 1.5 s. Each batch of microcracks is composed of a group of dense microcracks, and the ration of a single microcrack is generally less than 50 ms

1.2.2 data recording and analysis of fracturing process

next, the spectrum characteristics recorded in 10 representative time periods are selected for discussion in chronological order. Due to technical reasons, the accuracy of the sensors currently used is not enough to distinguish the accurate time of the received signal when the fracture occurs. We will graally solve this problem in the future work

(1) noise spectrum after 0.291-31.826s compression (Fig. 4): shortly after the beginning of compression, although the noise received by each sensor is different, generally speaking, the main frequency of noise is concentrated in the low frequency region of 50-300hz and the high frequency region of 400-750hz. The amplitude of sensor 4 is slightly lower than the other three because it is far away from the oil pump, The frequency difference is distributed in two lower and higher regions between 20 and 200Hz and 600 to 750Hz. The difference of noise recorded by different sensors is mainly related to their simultaneous interpreting. p>

(2) 31.990-33.526s noise spectrum (Fig. 5): compared with the noise spectrum after 0.291-31.826s compression, the amplitude of the noise is nearly doubled, but the frequency is still concentrated in the low frequency region, and the high frequency amplitude is suppressed compared with the low frequency region, which indicates that the internal structure of the rock sample is affected by the pressure, The sudden increase of noise amplitude may be the result of uneven pressure exerted by oil pump

Fig. 4 0.291-31.826s noise spectrum after compression start

Fig. 5 31.990-33.526s noise spectrum

(3) 300.665-302.201 s noise spectrum (Fig. 6): near the occurrence of micro fracture, the noise level further decreased, especially the position of sensors 2, 1 and 4 decreased significantly. The noise level of position 3 is relatively high

Fig. 6 300.665-302.201s noise spectrum

(4) 302.290-303.826s frequency spectrum of microcracks (Fig. 7): This is the frequency spectrum characteristics of the first batch of microcracks. It is obvious that the amplitude is abnormal, and the data obtained by different sensors are different: the frequency range of sensors 1 and 2 is about 700-800hz, while sensors 3 and 4, especially sensor 3, are greatly affected by noise, and their response to micro fracture is not obvious. The frequency range of sensor 3 is about 500-600hz, and that of sensor 4 is about 650-750hz. The first batch of microcracks only changed the fine structure of the rock sample, but there was no change in the macro

Fig. 7 frequency spectrum of 302.290-303.826s microcrack occurrence

(5) frequency spectrum of 305.599-307.135s microcrack occurrence (Fig. 8): compared with the frequency spectrum of 302.290-303.826s microcrack occurrence, the frequency range is about 650-750hz

Fig. 9 307.612 ~ 309.147s noise spectrum

(7) 316.793 ~ 318.329s frequency spectrum of microcracks (FIG. 10): the third batch of microcracks has higher strength and amplitude than the first two batches of microcracks. With the increase of pressure, on the basis of the previous fracture, when the internal fracture of rock sample develops and penetrates again, the rock sample will fracture. The frequency range of micro fracture recorded by sensor 1 is about 350-500hz, the frequency range recorded by sensor 2 is about 450-550hz, and the frequency range recorded by sensor 3 is about 400-500hz, The frequency range recorded by sensor 4 is about 650-750hz

Fig.10 frequency spectrum of 316.793 ~ 318.329s micro fracture occurrence

(8) 326.534 ~ 328.070s noise spectrum (Fig.11): after the occurrence of the third batch of micro fracture, because the rock sample has proced cracks, the continuous pressure will not have a great impact on the rock sample in a very short time, so it still shows the frequency spectrum characteristics of press noise

Fig. 11 326.534 ~ 328.070s noise spectrum

(9) 358.723 ~ 360.258s frequency spectrum of main fracture (Fig. 12): after continuous pressurization, the rock sample has stronger fracture on the basis of previous micro fracture, namely main fracture. From the data we collected, we can see that the rupture amplitude is much larger than the previous rupture, and the peak value has an obvious trend of moving to the low frequency region. The frequency range of each sensor also has obvious differences: the frequency range of sensor 1 is 300-500hz, the frequency range of sensor 2 is 200-300hz, the frequency range of sensor 3 is 350-550hz, and the frequency range of sensor 4 is 500-700hz. Because the final fracture surface is located between sensors 2 and 3, and the final fracture extends to sensor 2, the amplitude and frequency of micro fracture recorded by sensors 2 and 3 are relatively low, especially sensor 2. However, the microseismic amplitude and frequency recorded by sensors 1 and 4 far away from the fracture surface are much higher. This may be related to the smaller rock sample, the farther away from the fracture surface, the greater the displacement of the sensor<

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