Sensing data fusion and abnormal dynamic weight adjustment method for transformer fire
Through multi-sensor data fusion and dynamic weight adjustment algorithm, fire risk scores are calculated in real time, solving the problem of insufficient accuracy and real-time performance of traditional fire detection systems, and improving the sensitivity and accuracy of fire detection.
CN119649535APending Publication Date: 2025-03-18BEIJING NANRUI YIHE ENVIRONMENTAL PROTECTION TECH CO LTD
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Patent Information
- Application Number
- CN202411779437.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-05
- Publication Date
- 2025-03-18
AI Technical Summary
Technical Problem
Traditional transformer fire detection systems rely on a single sensor and cannot fully and accurately reflect the fire situation. Environmental changes and equipment aging lead to false alarms or missed reports.
Method used
The fusion of data of multiple sensors (such as temperature, smoke, gas concentration, sound, etc.) is adopted, and combined with dynamic weight adjustment algorithms, the comprehensive fire risk score is calculated in real time to determine whether a fire has occurred.
Benefits of technology
It significantly improves the sensitivity, accuracy and response speed of fire detection, reduces false alarms and missed alarms, and improves the fire protection level of ultra-high voltage substations and the safety of the power system.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention relates to a transformer fire sensing data fusion and abnormal dynamic weight adjustment method, and belongs to the field of hydrogen production. The method comprises a data fusion module and a data preprocessing and feature extraction module. Dynamically adjusting the weight of each sensor according to the real-time change condition of the signals after data preprocessing and feature extraction of different sensors; and calculating a comprehensive fire risk score in real time by fusing data from each sensor and the dynamically adjusted weight of each sensor, and judging whether a fire occurs or not. According to the invention, various sensor data are combined, the weight of the sensor data is dynamically adjusted, accurate detection of the transformer fire is realized, and the accuracy, reliability and real-time response capability of the system are optimized.
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