Analysis on sensitive indicators of gas outburst based on improved gray prediction method

doi:10.16265/j.cnki.issn1003-3033.2022.11.0326

Abstract

Abstract:

In order to clarify the relationship between the sensitive indexes of coal and gas outburst, firstly, the grey relational model was adopted, combined with the initial velocity method of drilling gas and the drilling cutting index method, the initial gas emission velocity q_m of drilling gas was selected as the reference sequence, and the analysis index of drilling cuttings gas Δh₂, K₁ and the amount of drilling cuttings S were selected as the comparison sequences to carry out the correlation analysis of the sensitive indexes of coal and gas outburst and determine the key factors affecting the coal and gas outburst accidents. Then the classical Gray Prediction model (GM (1,1)) was improved by introducing buffer weakening operators and automatic optimization and weighting method. The model was built, and the correlations among the q_m, Δh₂, K₁ and S were quantitatively analyzed. Finally, each index parameter was calculated using the measured gas data from a coal mining face in Shanxi, China. Results show that in the mentioned coalmine, the order of influence of coal and gas outburst sensitive indexes on outburst risk is followed as Δh₂ > S > K₁. And there is a crossing relation between Δh₂ K₁, S and q_m. The small error probability value of the improved grey prediction model increased from 0.69 to 0.87, the ratio of the posterior error decreased from 0.500 0 to 0.431 7, and the prediction grade was improved from pass to good.

Key words: coal and gas outburst, sensitive indicators, gray prediction, gray correlation analysis, analysis index of drilling cuttings gas

LU Jintao, JIA Xiaorong, GUO Xinyao. Analysis on sensitive indicators of gas outburst based on improved gray prediction method[J]. China Safety Science Journal, 2022, 32(11): 74-81.

Figures/Tables 7

Tab.1

Fig.1

Tab.2

Tab.3

Normalized processing results

序号	q_m/ (mL·s^-1)	K₁/(mL· g^-1·min^-1/2)	$Δ h 2$ / Pa	S/ (kg·m^-1)
1	0.368	1.000	1.000	0.000
2	1.000	0.538	0.750	0.964
3	0.000	0.692	0.000	0.571
4	1.000	0.846	1.000	1.000
5	0.526	0.308	0.500	0.464
6	0.053	0.615	0.250	0.107
7	0.579	0.000	1.000	0.250
8	0.000	0.077	0.000	0.071
9	0.474	0.769	0.750	0.179
10	0.053	0.692	0.500	0.357

Tab.3

Tab.4

Difference sequence of reference sequence qm

序号	$K 1 - q m$	$Δ h 2 - q m$	$S - q m$
1	0.632	0.632	0.368
2	0.170	0.382	0.596
3	0.324	0.368	0.203
4	0.478	0.632	0.632
5	0.061	0.132	0.096
6	0.247	0.118	0.261
7	0.368	0.632	0.118
8	0.291	0.368	0.297
9	0.401	0.382	0.190
10	0.324	0.132	0.011

Tab.4

Tab.5

Coal and gas outburst index Grey correlation degree

序号	$q m$	$γ 1$	$γ 2$	$γ 3$
1	1.00	0.60	0.70	0.64

Tab.5

Tab.6

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预测精度等级	p	q
优	>0.95	<0.35
较好	>0.80	<0.50
及格	>0.70	<0.65
不及格	≤0.70	≥0.65

序号	q_m/ (mL·s^-1)	K₁/ (mL·g^-1·min^-1/2))	Δh₂/ Pa	S/ (kg·m^-1)
1	6.00	0.26	80	3.0
2	7.20	0.20	70	5.7
3	5.30	0.22	40	4.6
4	7.20	0.24	80	5.8
5	6.30	0.17	60	4.3
6	5.40	0.21	50	3.3
7	6.40	0.13	80	3.7
8	5.30	0.14	40	3.2
9	6.20	0.23	70	3.5
10	5.40	0.22	60	4.0

类型	1	2	3	4	5	6	7	8	9	10
原始数据	6.00	7.20	5.30	7.20	6.30	5.40	6.40	5.30	6.20	5.40
原始数据优化	6.00	6.92	5.34	7.28	6.00	5.12	6.32	4.91	6.00	5.65
预测数据	5.90	6.94	5.46	7.32	5.94	5.16	6.28	4.77	5.91	5.82