A comprehensive pipe gallery fire early warning method and system

Abstract

The invention discloses a comprehensive pipe gallery fire early warning method and system. The method comprises the steps that acquring environment monitoring data in the comprehensive pipe gallery; performing data compression on the environment monitoring data to obtain environment monitoring compressed data; classifying and dividing the environmental monitoring compressed data to obtain a plurality of sub-databases; scanning each sub-database by adopting an Apriori algorithm to obtain a frequent item set; wherein each sub-database corresponds to one or more frequent item sets; sherein each frequent item set corresponds to one group of association rules; calculating the confidence of each frequent item set; determining an association rule corresponding to the frequent item set with the confidence greater than a preset confidence as a strong association rule; judging whether early warning information is generated or not according to the strong association rule; if yes, early warning information is generated, and an early warning signal is sent out according to the early warning information. According to the invention, the accuracy of early warning can be improved, and the occurrence of pipe gallery fire accidents is greatly reduced.

Description

technical field [0001] The invention relates to the technical field of fire early warning, in particular to a fire early warning method and system for a comprehensive utility gallery. Background technique [0002] At present, most of the research in China is on the fire risk control technology of the comprehensive utility corridor in the event of a fire, and there are few researches on the fire hazard identification and early warning of the comprehensive utility corridor. In the existing fire hazard identification technology, the STM32 embedded processor is usually used for monitoring and early warning. First, the environmental parameters of the comprehensive utility gallery are monitored, and then the Kalman filter method is used for prediction. In theory, the Kalman filter As the filtering progresses, the accuracy of the Kalman filter estimation should become higher and higher, and the variance matrix of the filtering error should tend to a stable value or a bounded value....

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Problems solved by technology

[0002] At present, most of the research in China is on the fire risk control technology of the comprehensive utility gallery in the event of a fire, and there are few studies on the fire hazard identification and early warning of the comprehensive utility gallery.

In the existing fire hazard identification technology, the STM32 embedded processor is usually used for monitoring and early warning. First, the environmental parameters of the comprehensive utility gallery are monitored, and then the Kalman filter method is used for prediction. In theory, the Kalman filter As the filtering progresses, the accuracy of the Kalman filter estimation should become higher and higher, and the variance matrix of the filtering error should tend to a stable value or a bounded value. However, in practical applications, as the number of measured values ​​increases, there is an estimation The mean value of the error and the estimated error covariance are getting larger and larger, which causes the filtering to gradually lose the role of accurate estimation.

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