Real-time quantitative risk evaluation of bag dedust system based on deviation degree-FCE

doi:10.16265/j.cnki.issn1003-3033.2024.10.1969

Abstract

Abstract:

In order to ensure the safe operation of bag dedust system and prevent the occurrence of dust explosion accident, a real-time quantitative risk evaluation model of bag dedust system was proposed based on deviation degree-FCE. Firstly, based on the monitoring data of the pressure difference between inlet and outlet of the dust, box temperature and lock-in ash discharge fault signal collected by the industrial Internet of Things sensor, the deviation degree was introduced to characterize the risk status of the monitoring parameters of the bag dedust system. Then, FCE was used to calculate the risk status of the bag dedust system. The analytic hierarchy process(AHP) and variable weight theory were combined to assign weights to the evaluation indicators. Based on the membership function and weighted average principle of membership degree, the risk of the bag dedust system was quantified by deviation degree, and the risk evaluation result for the bag dedust system was obtained. Finally, the monitoring data of a certain type of bag dedust system was used to verify the effectiveness of the model. The findings demonstrate that when the monitoring value of the evaluation indicators of the bag dedust system gradually approaches the alarm threshold, and the number of indicators approaching the alarm threshold increases, the risk level is higher. The evaluation results are correlated with the actual operation situation, thus validating the efficacy of the model.

Key words: deviation degree, fuzzy comprehensive evaluation (FCE), bag dedust system, quantitative risk evaluation, variable weight theory

CLC Number:

X964工业防尘

HOU Yuao, WANG Qiang, LIU Qing, LIN Yamin, ZHANG Shaofeng. Real-time quantitative risk evaluation of bag dedust system based on deviation degree-FCE[J]. China Safety Science Journal, 2024, 34(10): 30-38.

Figures/Tables 11

Table 1

Table 2

Table 3

Fig.1

Fig.2

Table 4

Table 5

Fitting function of deviation degree of each evaluation index

评价指标	偏离度拟合函数
U₂₁、U₂₄	$R (x) = 1, (x = 0) 0, (x = 1)$
U₂₂、U₂₃、U₂₆	$R (x) = 0, (x = 0) 1, (x = 1)$
U₁₁	$R (x) = 4.406 × 10 - 5 x 2 + 0.007 32 x - 0.004 58, 0 ≤ x 90 1, x ≥ 90$
U₁₂	$R (x) = 0.017 42 - 0.524 0 x + 1.256 7, 0.5 ≤ x ≤ 2.622 - 0.050 6 x 3 + 0.311 4 x 2 + 0.272 6 x - 1.924, 2.622 x ≤ 4.5 1, 0.5 x 或 x 4.5$
U₁₃	$R (x) = - 1.287 l n (x) + 8.343, 290 ≤ x ≤ 640.6 - 5.062 × 10 - 6 x 2 + 0.011 83 x - 5.527, 640.6 x ≤ 900 1, 290 x 或 900 x$
U₁₄	$R (x) = 4.728 × 10 - 5 x 2 + 0.007 18 x - 0.011 42, 0 ≤ x 90 1, x ≥ 90$
U₂₅	$R (x) = 5.198 × 10 - 9 x 3 - 8.776 × 10 - 6 x 2 + 0.001 35 x + 0.949 6, 100 ≤ x ≤ 517 - 1.802 × 10 - 8 x 3 + 4.161 × 10 - 5 x 2 - 0.028 54 x + 6.128, 517 x ≤ 900 1, x 100 或 x 900$

Table 5

Table 6

Fig.3

Fig.4

Fig.5

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等级	区间
轻度	[0,0.25)
中度	[0.25,0.5)
高度	[0.5,0.75)
重度	[0.75,1]

指标 (模拟量) 类型	越小越优型		中间型
报警值	高报阈值	高高报阈值	低低报阈值	低报阈值	高报阈值	高高报阈值
R	0.75	1	1	0.75	0.75	1

监测指标	低低报阈值	低报阈值	高报阈值	高高报阈值
U₁₁/℃	—	—	70	90
U₁₂/kPa	0.5	1.0	3.5	4.5
U₁₃/kPa	290	390	800	900
U₁₄/℃	—	—	70	90
U₂₅/kPa	100	300	800	900

时刻	U₁₁/℃	U₁₂/kPa	U₁₃/kPa	U₁₄/℃	U₂₁	U₂₂	U₂₃	U₂₄	U₂₅/kPa	U₂₆
t₁	28.7	2.281	667.5	30.7	1	0	0	1	395.6	0
t₂	28.9	2.286	667.3	30.7	1	0	0	1	395.4	0
t₃	29.1	2.436	667.2	30.7	1	0	0	1	395.6	0
t₄	28.6	2.302	667.8	30.7	1	0	0	1	395.6	0
t₅	28.9	2.312	666.9	30.1	1	0	0	1	395.3	0
︙	︙	︙	︙	︙	︙	︙	︙	︙	︙	︙
t_{2 057}	23.3	2.426	646.4	30.1	1	0	0	1	523.4	0
t_{2 058}	23.3	2.519	571.8	30.1	1	0	0	1	491.0	0
t_{2 059}	22.8	2.308	605.2	30.1	1	0	0	1	518.0	0