SCI和EI收录∣中国化工学会会刊

中国化学工程学报 ›› 2023, Vol. 56 ›› Issue (4): 169-179.DOI: 10.1016/j.cjche.2022.06.033

• Full Length Article • 上一篇    下一篇

Optimization of sensor deployment sequences for hazardous gas leakage monitoring and source term estimation

Jikai Dong, Bing Wang, Xinjie Wang, Chenxi Cao, Shikuan Chen, Wenli Du   

  1. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • 收稿日期:2021-11-11 修回日期:2022-06-21 出版日期:2023-04-28 发布日期:2023-06-13
  • 通讯作者: Bing Wang,E-mail:wangb07@ecust.edu.cn;Wenli Du,E-mail:wldu@ecust.edu.cn
  • 基金资助:
    This work was supported by National Natural Science Foundation of China (61988101), National Natural Science Fund for Distinguished Young Scholars (61725301), and Fundamental Research Funds for the Central Universities.

Optimization of sensor deployment sequences for hazardous gas leakage monitoring and source term estimation

Jikai Dong, Bing Wang, Xinjie Wang, Chenxi Cao, Shikuan Chen, Wenli Du   

  1. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • Received:2021-11-11 Revised:2022-06-21 Online:2023-04-28 Published:2023-06-13
  • Contact: Bing Wang,E-mail:wangb07@ecust.edu.cn;Wenli Du,E-mail:wldu@ecust.edu.cn
  • Supported by:
    This work was supported by National Natural Science Foundation of China (61988101), National Natural Science Fund for Distinguished Young Scholars (61725301), and Fundamental Research Funds for the Central Universities.

摘要: Nowadays, chemical safety has attracted considerable attention, and chemical gas leakage monitoring and source term estimation (STE) have become hot spots. However, few studies have focused on sensor layouts in scenarios with multiple potential leakage sources and wind conditions, and studies on the risk information (RI) detection and prioritization order of sensors have not been performed. In this work, the monitoring area of a chemical factory is divided into multiple rectangles with a uniform mesh. The RI value of each grid node is calculated on the basis of the occurrence probability and normalized concentrations of each leakage scenario. A high RI value indicates that a sensor at a grid node has a high chance of detecting gas concentrations in different leakage scenarios. This situation is beneficial for leakage monitoring and STE. The methods of similarity redundancy detection and the maximization of sensor RI detection are applied to determine the sequence of sensor locations. This study reveals that the RI detection of the optimal sensor layout with eight sensors exceeds that of the typical layout with 12 sensors. In addition, STE with the optimized placement sequence of the sensor layout is numerically simulated. The statistical results of each scenario with various numbers of sensors reveal that STE is affected by sensor number and scenarios (leakage locations and winds). In most scenarios, appropriate STE results can be retained under the optimal sensor layout even with four sensors. Eight or more sensors are advised to improve the performance of STE in all scenarios. Moreover, the reliability of the STE results in each scenario can be known in advance with a specific number of sensors. Such information thus provides a reference for emergency rescue.

关键词: Gas leakage, Source term estimation, Sensor layout, Risk information, Numerical simulation, Optimization

Abstract: Nowadays, chemical safety has attracted considerable attention, and chemical gas leakage monitoring and source term estimation (STE) have become hot spots. However, few studies have focused on sensor layouts in scenarios with multiple potential leakage sources and wind conditions, and studies on the risk information (RI) detection and prioritization order of sensors have not been performed. In this work, the monitoring area of a chemical factory is divided into multiple rectangles with a uniform mesh. The RI value of each grid node is calculated on the basis of the occurrence probability and normalized concentrations of each leakage scenario. A high RI value indicates that a sensor at a grid node has a high chance of detecting gas concentrations in different leakage scenarios. This situation is beneficial for leakage monitoring and STE. The methods of similarity redundancy detection and the maximization of sensor RI detection are applied to determine the sequence of sensor locations. This study reveals that the RI detection of the optimal sensor layout with eight sensors exceeds that of the typical layout with 12 sensors. In addition, STE with the optimized placement sequence of the sensor layout is numerically simulated. The statistical results of each scenario with various numbers of sensors reveal that STE is affected by sensor number and scenarios (leakage locations and winds). In most scenarios, appropriate STE results can be retained under the optimal sensor layout even with four sensors. Eight or more sensors are advised to improve the performance of STE in all scenarios. Moreover, the reliability of the STE results in each scenario can be known in advance with a specific number of sensors. Such information thus provides a reference for emergency rescue.

Key words: Gas leakage, Source term estimation, Sensor layout, Risk information, Numerical simulation, Optimization