﻿ 大型舰船舱室火灾实时决策方法研究
 舰船科学技术  2022, Vol. 44 Issue (5): 50-53    DOI: 10.3404/j.issn.1672-7649.2022.05.010 PDF

Real-time decision making method of compartment fire on capital ships
XIE Tian-hua, FU Xue-qing
Dalian Naval Academy, Dalian 116018, China
Abstract: As capital ships have complex structure of compartments, a great amount of inflammables and explosives and high fire load density. Compartment fire becomes the main factor of threatening the survivability and combat effectiveness of capital ships. In most previous work, there are some problems for firefighting command of navy ships such as the validity of fire recognition, the accuracy of simulation prediction, and the real-time of fire decision plan. Firstly, design philosophy of compartment fire real-time decision making of capital ships is proposed. Secondly, intelligent identification technology, fire simulation technology, and synthesis reasoning method are discussed. Lastly, the applicability and validity of the real-time decision model are verified by an application example. The research can promote intelligent level of damage control supervisory control system, which can further enhance the ability of commanding decision response to resist the threat by the ships.
Key words: capital ships     compartment fire     real-time decision making
0 引　言

1 实时决策的设计思想

 图 1 舱室火灾的智能决策过程 Fig. 1 Intelligent decision process of compartment fire

2 实时决策的方法和模型

2.1 基于贝叶斯网络的舱室火灾识别方法

 $B = (S{\text{,}}P) = (V,L,P)。$ (1)

 $P(F = f|E = e) = \frac{{P(F = f,E = e)}}{{P(E = e)}}。$ (2)

 图 2 智能识别的拓扑结构 Fig. 2 Overall structure of identification method

 \begin{aligned} P((X,Y) = N|({T_{\text{U}}},{T_{\text{L}}},{C_{{\text{CO}}}},{C_{{\text{C}}{{\text{O}}_{\text{2}}}}},{C_{{{\text{O}}_{\text{2}}}}},D) = M) =\\ \dfrac{{P(({T_{\text{U}}},{T_{\text{L}}},{C_{{\text{CO}}}},{C_{{\text{C}}{{\text{O}}_{\text{2}}}}},{C_{{{\text{O}}_{\text{2}}}}},D) = M,(X,Y) = N)}}{{P(({T_{\text{U}}},{T_{\text{L}}},{C_{{\text{CO}}}},{C_{{\text{C}}{{\text{O}}_{\text{2}}}}},{C_{{{\text{O}}_{\text{2}}}}},D) = M)}}。\end{aligned} (3)

2.2 基于区域模拟的舱室火灾预测模型

 $\dot{m}_{L 1}=\rho_{\mathrm{f}} A_{1} \frac{{\rm{d}} z_{1}}{{\rm{d}} t}=\dot{m}_{t 1}-\dot{m}_{\mathrm{eu} 2, H} ，$ (4)

 $\dot{m}_{e 1}=\rho_{e 1} A \frac{{\rm{d}}\left(H_{1}-z_{1}\right)}{{\rm{d}} t}=-\dot{m}_{\nu 1}+\dot{m}_{e d A_{v} H}，$ (5)

 $c_{\theta} \rho_{v 1} A_{1}\left(H_{1}-z_{1}\right) \frac{{\rm{d}} T_{u}}{{\rm{d}} t}=\dot{Q}_{f, e}-c_{\theta} m_{\theta 1}\left(T_{v}-T_{0}\right)-\dot{Q}_{A, B} ，$ (6)

 $\dot{m}_{U 2}=\rho_{U 2} A_{2} \frac{{\rm{d}}\left(H_{2}-z_{2}\right)}{{\rm{d}} t}=-\dot{m}_{e d 1, H}-\dot{m}_{v 2}，$ (7)

 $\dot{m}_{L 2}=\rho_{L 2} A_{2} \frac{{\rm{d}} z_{2}}{{\rm{d}} t}=\dot{m}_{\Delta 2}+\dot{m}_{\mathrm{e} A 2, H}，$ (8)

 $c_{\theta} \rho_{v 2} A_{2}\left(H_{2}-z_{2}\right) \frac{{\rm{d}} T_{U}}{{\rm{d}} t}=0.7 \dot{Q}_{\omega A H I}-c_{B} \dot{m}_{\partial 2}\left(T_{U}-T_{0}\right)。$ (9)

2.3 基于黑板专家系统的灭火方案生成方法

 图 3 灭火方案的综合推理结构 Fig. 3 Synthesis reasoning architecture of firefighting decision-making plan
3 案例分析

 图 4 上层温度变化 Fig. 4 Variation of upper temperature

 图 5 烟气层高度变化 Fig. 5 Variation of inteface height

 图 6 O2浓度变化 Fig. 6 Variation of O2 concentration

 图 7 CO2浓度变化 Fig. 7 Variation of CO2 concentration

 图 8 CO浓度变化 Fig. 8 Variation of CO concentration

 图 9 OD值变化 Fig. 9 Variation of OD value

 图 10 限制火灾蔓延的TIPN预测结构模型 Fig. 10 TIPN prediction model of preventing fire spread
4 结　语

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