Abstract:  In order to effectively identify and prevent fire accidents in the comprehensive gallery of pipes caused by uncertain factors, this paper uses a variety of sensor data fusion methods to monitor various risk factors that can cause fire in the integrated pipe gallery, and proposes a comprehensive gallery fire hazard identification and early warning system with PLC as lower computer and LabVIEW developed by NI Corporation as the upper computer. The system uses the improved Apriori algorithm regulation to analyze many gallery fire risk factors, and quantifies the results of the analysis. The results show that the system can quickly identify the environmental factors that cause fire accidents in the comprehensive gallery of pipes, and provide early warning, providing a reference for the application of urban underground comprehensive gallery fire warning engineering.

Key words: comprehensive gallery of pipes, fire warning, LabVIEW, PLC, Apriori algorithm