1. 国网重庆市电力公司电力科学研究院
2. 重庆大学自动化学院
3. 哈尔滨工业大学深圳研究生院
纸质出版:2015
移动端阅览
[1]宋伟,王玉平,张文杰,张家齐,郑彦宁,吴高林.基于颜色与运动特征的变电站实时烟雾检测[J].传感器与微系统,2015,34(12):127-130.
SONG Wei, WANG Yu-ping, ZHANG Wen-jie, et al. Real-time smoke detection in substation based on color and motion features[J]. 2015, 34(12): 127-130.
[1]宋伟,王玉平,张文杰,张家齐,郑彦宁,吴高林.基于颜色与运动特征的变电站实时烟雾检测[J].传感器与微系统,2015,34(12):127-130. DOI: 10.13873/J.1000-9787(2015)12-0127-04.
SONG Wei, WANG Yu-ping, ZHANG Wen-jie, et al. Real-time smoke detection in substation based on color and motion features[J]. 2015, 34(12): 127-130. DOI: 10.13873/J.1000-9787(2015)12-0127-04.
变电站的环境特殊性要求站内火灾检测准确、快速
烟雾检测是早期火灾检测中的常用方法。针对变电站特殊环境
提出一种快速烟雾检测算法。首先
利用改进的Vi Be算法检测变电站实时监控视频中的运动区域
再通过颜色特征确定疑似烟雾区域
然后结合烟雾面积增长特性和移动特性识别烟雾区域。实验结果表明:这种算法能够检测到不同场景中的烟雾
对远距离、稀薄烟雾也能有效检测
满足变电站火灾检测实时性、准确性要求
能够应用于变电站场景烟雾检测。
The fire detection in substation is required to be fast and exact
due to its special surroundings
smoke detection is a commonly used method in early fire detection
therefore
a fast smoke detection algorithm is proposed for such unique environment. The specific steps are as follows: Firstly
moving area are determined in real-time by using the improved Vi Be algorithm. Then
the suspected smoke area will be identified by judging color features of the detected regions. Finally
the smoke diffuse and moving characteristics are considered to ascertain the real smoke region. Experimental result shows that this algorithm can be used to detect smoke in different situations
it is not only suitable for nearby smoke detection
but also quite useful for detecting thin smoke in distance. Therefore
this algorithm
which meets the requirements of real-time and accuracy of fire detection in the substation
can be applied in smoke detection in the substation.
基于YCbCr颜色空间的火焰图像分割方法 [J]. 陈天炎,曾思通,吴海彬. 传感器与微系统 . 2011(10)
无人值守变电站中智能视频监控的技术研究 [D]. 景美丽. 华北电力大学 2012
基于视频特征的火灾火焰识别算法 [D]. 刘昕雨. 西安电子科技大学 2009
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