Research on False Alarm Rate Reducing Strategies for Subway Train Fire Alarm System

[Objective] Given the high false alarm rate in subway train fire alarm systems, it is necessary to study strategies of effectively reducing the false alarm rate, so as to minimize operational disruptions and resource waste caused by false alarms, enhancing subway operation safety and passengers′ travel experience. [Method] Through the introduction of fire alarm system and the investigation of subway train fire alarm system historical data, main types and potential causes of false fire alarms are analyzed. [Result & Conclusion] Environmental factors, detector type selection, detector detection principle, and software algorithm are identified as main causes for false fire alarms. The false alarm rate can be reduced by hardware optimization methods such as adding dust filter devices, adopting dual light source detectors, multi-parameter gas detectors and pyrolysis particle detectors; the rate can also be reduced by optimizing software algorithms (optimization modeling method, automatic adjustment of alarm thresholds, machine self-learning algorithm, etc.). Combining multi-parameters acquisition unit detection with intelligent analysis algorithms, distinguishing interference factors such as dust, water vapor, and smoke particles can also reduce the false alarm rate and improve the anti-interference ability and reliability of the fire detection system.