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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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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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