分布式电力应急救援指挥监控仿真研究
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摘要
当前电力应急救援指挥监控延时现象严重,且监控过程抗干扰性能较差,提出基于广义似然比的分布式电力应急救援指挥监控方法。利用小波变换对监控图像进行处理,将一维变换扩展至二维函数,并设置一个二维尺度函数与三个二维小波。构建监控图像处理的增益函数,分析该函数,将较小的系数认为是噪声分量。将增强函数进行归一化,引入噪声抑制适应度函数,结合尺度函数与二维小波实现分布式电力应急救援指挥监控图像处理。将经处理过的电力应急救援指挥监控图像划分成不重叠且大小相同的区域,得到各个区域灰度均值。利用全部区域灰度均值广义似然比的统计量之和获取控制图,以此完成电力应急救援指挥监控研究。实验结果表明,所提方法平均抗干扰系数为0.96,监控延时短。
At present, the phenomenon about the monitoring delay of power emergency rescue command is serious, and the anti-interference performance is poor. Therefore, this article presented a method to monitor distributed electric power emergency rescue command based on generalized likelihood ratio. Firstly, we used the wavelet transform to process monitoring image and the extended one-dimensional transform to two-dimensional function. Secondly, we set a two-dimensional scaling function and three two-dimensional wavelets. Thirdly, we constructed the gain function for monitoring image, and then analyzed this function, so as to consider the smaller coefficient as noise component. Moreover, we normalized the enhancement function and introduced the noise suppression fitness function. Combined the scale function with the two-dimensional wavelet, we achieved monitoring image processing of distributed power emergency rescue command. After that, we divided the processed monitoring image of electric emergency rescue command into some regions without overlapping each other, so as to get the gray mean value of these regions. Finally, we used the statistical sum of generalized likelihood ratios of gray mean values of all regions to get the control map. Thus, we completed the research on monitoring the electric power emergency rescue command. Simulation results prove that the average anti-interference coefficient of proposed method is 0.96. Meanwhile, this method has short monitoring delay.
At present, the phenomenon about the monitoring delay of power emergency rescue command is serious, and the anti-interference performance is poor. Therefore, this article presented a method to monitor distributed electric power emergency rescue command based on generalized likelihood ratio. Firstly, we used the wavelet transform to process monitoring image and the extended one-dimensional transform to two-dimensional function. Secondly, we set a two-dimensional scaling function and three two-dimensional wavelets. Thirdly, we constructed the gain function for monitoring image, and then analyzed this function, so as to consider the smaller coefficient as noise component. Moreover, we normalized the enhancement function and introduced the noise suppression fitness function. Combined the scale function with the two-dimensional wavelet, we achieved monitoring image processing of distributed power emergency rescue command. After that, we divided the processed monitoring image of electric emergency rescue command into some regions without overlapping each other, so as to get the gray mean value of these regions. Finally, we used the statistical sum of generalized likelihood ratios of gray mean values of all regions to get the control map. Thus, we completed the research on monitoring the electric power emergency rescue command. Simulation results prove that the average anti-interference coefficient of proposed method is 0.96. Meanwhile, this method has short monitoring delay.
引文
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[2] 张学华,王捷,范春波,等. 基于北斗与移动互联网的应急救援系统设计[J]. 消防科学与技术, 2017,36(6):813-816.
[3] 李寰纹,魏梦,陈雨晴,等. 基于云模型的电力应急群体决策评价方法[J]. 中国电力, 2016,49(4):42-48.
[4] 郑万波. 矿山应急救援一体化指挥决策信息平台研究[J]. 工矿自动化, 2017,43(12): 70-75.
[5] 杨锡运,刘玉奇,张璜,等. 电力应急指挥中心屏显系统综合改造分析[J]. 高电压技术, 2016,42(13):2689-2696.
[6] 都成刚,黄静.柔性交流输电系统设备对电力系统暂态失稳风险的影响[J].电子设计工程,2018,26(06):189-193.
[7] 张鹏,许金龙,赵世伟. 民航飞机飞行管理系统可靠性监控仿真研究[J]. 计算机仿真, 2017,34(8):105-109.
[8] 董存祥. 铁路隧道防灾救援移动监控系统研究[J]. 铁道标准设计, 2017,61(1): 119-122.
[9] 晋良海,吴菊华,余迪,等. 水电厂电力设备事故应急响应FPN-MC模型及效能分析[J]. 中国安全生产科学技术, 2017,13(4): 123-128.
[10] 魏振生,陈守文,马姝婧,等. 基于流程的应急预案结构化与图形化应急指挥[J]. 化工进展, 2017,36(s1):121-126.