Temperature data-driven fire source estimation algorithm of the underground pipe gallery

Sun, Bin; Liu, Xiaojiang; Xu, Zhao‐Dong; Xu, Dajun

doi:10.1016/j.ijthermalsci.2021.107247

Cited by 37 publications

(6 citation statements)

References 34 publications

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“…Liang [32] introduced a spatial data matching method based on similarity calculations of underground pipeline data, which is highly significant for UUP informatization management. In promoting the high-precision detection of UUPs, multi-source data from ground-penetrating radar [33], point cloud data [34], and underground pipe gallery temperature data [35] are widely used to map pipelines with varying materials, spacings, or…”

Section: Literature Reviewmentioning

confidence: 99%

Tripartite Social Roles of Urban Underground Pipeline Informatization in China

Xie,

Liu,

Feng

et al. 2024

Sustainability

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Urban underground pipelines (UUPs) are critical infrastructure, and their safe operation has become a key concern in Chinese society. Currently, the tripartite social roles of the local people’s government, pipeline management departments, and the public are crucial in the informatization of urban underground pipelines. In this study, a survey was conducted among 126 professionals and technical personnel involved in underground pipeline informatization across eight cities in different regions of China. A quantitative weighted evaluation model was established using the Project Quantitative Index (PQI) and principal component analysis (PCA) to investigate the value of the tripartite aforementioned social groups in UUP informatization. The results indicate: (1) There is a significant positive correlation between the tripartite social roles and the promotion of UUP informatization. Moreover, the indicators with the highest PQI value are “Establishment of UUP informatization management departments” and “Support the work of the UUP informatization industry association” under the role of the local people’s government. (2) The informatization work of underground pipelines in different cities is affected differently by the tripartite social roles. This suggests that the local people’s government and professional management departments in different cities can proactively leverage their unique advantages in UUP informatization based on their specific circumstances. (3) PCA results showed that the indicators related to the public carried significant weight, indicating that the public also played an important role in UUP informatization. The degree of UUP informatization in the eight studied cities is ranked as follows: Guangzhou > Beijing > Qingdao > Kunming > Shanghai > Chengdu > Wuhan > Sian. This paper further discusses the unique roles and contributions of the tripartite social groups in UUP informatization, aiming to provide decision support for the future construction, management, and safe operation and maintenance of urban underground pipelines in China.

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Section: Literature Reviewmentioning

confidence: 99%

Tripartite Social Roles of Urban Underground Pipeline Informatization in China

Xie,

Liu,

Feng

et al. 2024

Sustainability

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“…Since both traditional optimization algorithms and sequence methods can only get suboptimal solutions, intelligent optimization algorithms are more widely used for such a problem. Commonly used intelligent optimization algorithms are usually swarm-based intelligence, including the particle swarm optimization (PSO) algorithm [11][12][13][14] and the ant colony optimization (ACO) algorithm [15]. These algorithms have been used to determine the tunnel fire sources and to optimize the sensor layout.…”

Section: Introductionmentioning

confidence: 99%

Risk and Energy Based Optimization for Fire Monitoring System in Utility Tunnel Using Cellular Automata

Zhang,

Bai,

Diao

et al. 2024

Sustainability

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Fire is one of the biggest threats to the safety of utility tunnels, and establishing camera-based monitoring systems is conducive to early fire finding and better understanding of the evolution of tunnel fires. However, conventional monitoring systems are being faced with the challenge of high energy consumption. In this paper, the camera operation in a utility tunnel was optimized considering both fire risk and energy consumption. Three design variables were investigated, namely the camera sight, the number of cameras in simultaneous operation, and the duration of camera operation. Cellular automata were used as a simple but effective method to simulate the spread of fire in a utility tunnel. Results show that as the number of cameras in simultaneous operation increases, the probability of fire capture also increases, but the energy consumption decreases. A shorter duration of camera operation can lead to a higher probability of fire capture, and meanwhile, lower energy consumption. For the duration of camera operation shorter than or equal to the allowable time, the probability of fire capture is significantly higher than that for the duration longer than the allowable time. Increasing the camera sight will significantly increase the probability of fire capture and lower the total energy consumption when a blind monitoring area exists. The total energy consumption of a camera-based monitoring system roughly satisfies hyperbolic correlation with the duration of camera operation, while the probability of fire capture can be predicted based on the number of cameras in simultaneous operation through a power model. The optimal design for the modeled tunnel section is two cameras in simultaneous operation with a tangent monitoring area. The duration of camera operation should be as short as possible, at least shorter than the allowable time. The study is expected to provide a reference for the sustainable design of energy-saving utility tunnels with lower fire risk.

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“…The results show that the trained intelligences improve the accuracy and reliability of building fire warnings. Sun et al [ 10 ] verified a bio-inspired artificial intelligence algorithm driven by temperature data to detect fire in 3D spaces. Yusuf et al [ 3 ] presented a linearly regressive artificial-neural-network-based technique to predict temperature increases caused by building fire environments.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Feature Fusion-Based High-Sensitivity Fire Detection and Early Warning for Intelligent Building Systems

Xiao

Wang

et al. 2023

Sensors

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High-sensitivity early fire detection is an essential prerequisite to intelligent building safety. However, due to the small changes and erratic fluctuations in environmental parameters in the initial combustion phase, it is always a challenging task. To address this challenge, this paper proposes a hybrid feature fusion-based high-sensitivity early fire detection and warning method for in-building environments. More specifically, the temperature, smoke concentration, and carbon monoxide concentration were first selected as the main distinguishing attributes to indicate an in-building fire. Secondly, the propagation neural network (BPNN) and the least squares support vector machine (LSSVM) were employed to achieve the hybrid feature fusion. In addition, the genetic algorithm (GA) and particle swarm optimization (PSO) were also introduced to optimize the BPNN and the LSSVM, respectively. After that, the outputs of the GA-BPNN and the PSO-LSSVM were fused to make a final decision by means of the D-S evidence theory, achieving a highly sensitive and reliable early fire detection and warning system. Finally, an early fire warning system was developed, and the experimental results show that the proposed method can effectively detect an early fire with an accuracy of more than 96% for different types and regions of fire, including polyurethane foam fire, alcohol fire, beech wood smolder, and cotton woven fabric smolder.

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Temperature data-driven fire source estimation algorithm of the underground pipe gallery

Cited by 37 publications

References 34 publications

Tripartite Social Roles of Urban Underground Pipeline Informatization in China

Tripartite Social Roles of Urban Underground Pipeline Informatization in China

Risk and Energy Based Optimization for Fire Monitoring System in Utility Tunnel Using Cellular Automata

Hybrid Feature Fusion-Based High-Sensitivity Fire Detection and Early Warning for Intelligent Building Systems

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