主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

消防科学与技术 ›› 2020, Vol. 39 ›› Issue (12): 1770-1772.

• • 上一篇    下一篇

神经网络方法在变电站消防管理的应用研究

李富强,瞿航,徐宁一,朱文超   

  1. 国网浙江省电力有限公司宁波供电公司,浙江宁波315000
  • 出版日期:2020-12-15 发布日期:2020-12-15
  • 作者简介:李富强(1983-),男,国网浙江省电力有限公司宁波供电公司高级工程师,主要从事变电站消防管理工作,浙江省宁波市海曙区丽园北路1408 号,315000。

Study on the application of neural network on transformer substation fire management

LI Fu-qiang, QU Hang, XU Ning-yi, ZHU Wen-chao   

  1. Ningbo power supply company of State Grid Zhejiang Electric Power Co., Ltd., Zhejiang Ningbo 315000, China  

  • Online:2020-12-15 Published:2020-12-15

摘要:

为了提升变电站消防管理科学化水平,实现视频图片火焰特征提取及识别定位。接入视频监控码流数据,构建基于卷积神经网络的火焰识别模型,进行实时识别火焰特征并预警预报。实验表明,该方法能够自动提取火焰特征,有效提高复杂背景下的火焰识别的准确率,具有良好的鲁棒性和泛化能力,在变电站消防管理中有较大应用前景。

关键词: 卷积神经网络, 火焰识别, 变电站, 消防管理

Abstract:

In order to improve the fire management of transformer substation, the video and image flame feature extraction and identification are achieved. The stream data of video surveillance is accessed. The flame identification model based on convolution neural network is built. The flame features are real time identified, and early warning and forecast are performed. Experiments showed that, the method can extract the flame feature automatically, and efficiently improve the accuracy of flame identification with complex background, with good robustness and generalization ability, and have great application prospect in the fire management of transformer substation.  

Key words:

convolution neural network, flame identification, transformer substation, fire management