| 采用遗传算法优化气体探测器布局策略研究 |
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| 引用本文： | 王海清,王玉秀,宋贤生,刘祥妹.采用遗传算法优化气体探测器布局策略研究[J].中国安全生产科学技术,2016,12(9):86-91. |
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| 作者姓名： | 王海清 王玉秀 宋贤生 刘祥妹 |
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| 作者单位： | (1.中国石油大学(华东）安全科学与工程系，山东 青岛 266580; 2.劳氏瑞安咨询有限公司，上海 200001） |
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| 摘 要： | 石油石化装置具有结构复杂且危险性高的特点，所加工物料多为易燃易爆有毒物质，且工艺单元之间集成度高，一旦发生泄漏若无法及时探测到则易形成气液积聚和火灾爆炸后果强化，装置拥塞度高使人员逃生困难。火气系统FGS作为安全关键系统，其中的气体探测网络如何快速可靠的实现对气体泄漏事件的探测显得尤为重要。已知探测时间，通过引入遗传算法利用其全局搜索的特点克服传统分支定界法的缺点，实现立体空间不同高度下设置探测网络达到场景全覆盖和缩短探测时间，同时求出探测时间附近的多组最优解，为探测器放置提供多种布置方案。通过与传统等间距探测器布置方案比较，从多种布置方案中选择更符合实际的最佳方案。通过海上浮式生产储油船的生产夹板气体探测案例，验证了所提方法的有效性。
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| 关 键 词： | 火气系统 探测网络 布局优化 浮式生产储油船 遗传算法 |
Study on layout optimization strategy of gas detectors using genetic algorithm |
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| WANG Haiqing,WANG Yuxiu,SONG Xiansheng,LIU Xiangmei.Study on layout optimization strategy of gas detectors using genetic algorithm[J].Journal of Safety Science and Technology,2016,12(9):86-91. |
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| Authors: | WANG Haiqing WANG Yuxiu SONG Xiansheng LIU Xiangmei |
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| Affiliation: | (1. Department of Safety Science and Engineering, China University of Petroleum, Qingdao Shandong 266580, China;2. Lloyd’s Register Consulting - Energy Inc., Shanghai 200001, China) |
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| Abstract: | The petrochemical plant has the characteristics of complex structure and high risk, containing inflammable, explosive and toxic substances, with high integration of process units. If the leakage is not detected immediately, it will lead to gas and liquid accumulation and strengthen the consequence of fire and explosion, and the personnel evacuation is difficult because of high congestion of plant. Fire & Gas System (FGS) is a safety critical system, and it is important for gas detection network of FGS to detect the gas leakage events rapidly and reliably. With the condition of known detection time, the genetic algorithm was introduced to overcome the disadvantage of traditional branch and bound method by using its characteristic of global searching. The layout of detection network with different height in three-dimension space can realize the full coverage of all scenarios and shortening the detection time, meanwhile, multiple groups of optimal solution near the detection time can be deduced, so as to provide various layout schemes of detector. By comparing with the traditional equal spacing layout scheme of detectors, the best scheme being more appropriate to practical situation was selected from various layout schemes. Through a case study of gas detection on production deck of Floating Production Storage and Offloading (FPSO), the effectiveness of the proposed method was verified. |
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| Keywords: | FGS detection network layout optimization FPSO genetic algorithm |
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