基于多源数据融合的天然气站场设备运行监控方法设计

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中图分类号：TQ517.1;TP277 文献标志码：A 文章编号：1001-5922（2025）07-0129-04

Abstract：Due to the ignorance of the equipment operation and maintenance distribution deviation characteristics in the operation and monitoring of natural gas station equipment，it is dificult to accuratelyobtain the distribution matrixof operation and maintenance form of equipment operation，resulting in high monitoring leakage inductance rate and low monitoring accuracy.A method for monitoring the operation of natural gas station equipment was proposed based on multi-source data fusion.By determining the safety level of theequipment，collecting and converting the operation data of the equipment，and full considering the operation and maintenance distribution deviation characteristics ofthe equipment，the deviation function was used to obtain the operation and maintenance form distribution matrixof the equipment operation，so as to detect the state characteristic quantity.The multi-sourcedata fusion method was introduced to fuse the upper bound state information and the lower bound state information of the equipment to obtain the equipment failure probability，and then the equipment operation state evolution model was constructed.The operating state of the equipment was determined bycalculating thequantization value of the operating stateof theequipment and comparing it to a preset threshold.The experimental results showed that the monitoring leakage inductance rate of the proposed method was lower and the monitoring accuracy was higher.

Key words：multi source data fusion；natural gas station yard；natural gas equipment；operating status；character istic quantity；condition monitoring

通过传感器和其他设备收集电力设备的实时运行数据，根据电力设备的特点和要求，选择递归神经网络建立设备运行状态监测模型，并利用大量的电力设备运行数据和故障样本对模型进行训练，使其能够自动识别和预测电力设备的运行状态[1]。（剩余6080字）