Data Flow Distribution Method Based on Superior-subordinate Server for Process Safety Monitoring

Wei ZHANG , Ye-cheng ZHANG , Chong ZHANG , Ting-sheng ZHAO

Science Technology and Engineering ›› 2025, Vol. 25 ›› Issue (5) : 2175 -2183.

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Science Technology and Engineering ›› 2025, Vol. 25 ›› Issue (5) : 2175-2183 DOI: 10.12404/j.issn.1671-1815.2403658
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Data Flow Distribution Method Based on Superior-subordinate Server for Process Safety Monitoring
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Abstract

Process production safety monitoring is the main technical method for safety risk control and accident prevention, and data is a significant basis for safety control and decision-making. In the existing security monitoring network, there are many sensor nodes and large amounts of data, which cause heavy channel load in the wireless sensor network. This often leads to issues such as data latency and loss, which affects the timeliness and accuracy of safety control decisions. Therefore, the security risk factors of typical process production scenarios were focused on. Based on this, the sensor deployment plan and wireless sensor network data transmission architecture were clarified, a security monitoring data flow scheduling method based on superior-subordinate server was proposed, and the data stream congestion index and abnormal data packet frequency index were used as the main indicators of data flow performance evaluation. Subsequently, the chemical polymerization reactor were taken as an engineering scenario, the performance improvement was examined after the subordinate server was initiated to share the data flow for the superior server. Through the comprehensive study of channel load balancing, the method of superior-subordinate server is benefit to ensure the effectiveness of orderly transmission of safety monitoring data and risk control.

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process industry / wireless sensor network / safety monitoring / channel load / data flow distribution

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Wei ZHANG, Ye-cheng ZHANG, Chong ZHANG, Ting-sheng ZHAO. Data Flow Distribution Method Based on Superior-subordinate Server for Process Safety Monitoring. Science Technology and Engineering, 2025, 25(5): 2175-2183 DOI:10.12404/j.issn.1671-1815.2403658

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