摘要
为了提高微弱光电信号检测效果,针对当前微弱光电信号检测过程存在的一些问题,提出基于嵌入式技术的微弱光电信号自动检测系统。分析了当前微弱光电信号的研究进展,采集微弱光电信号,并采用小波分析方法对微弱光电信号进行去噪处理,神经网络对微弱光电信号进行分析,建立微弱光电信号检测模型,通过仿真实验分析了微弱光电信号检测效果。结果表明,系统可以高精度实现微弱光电信号检测,减少了微弱光电信号误检率,同时缩短了微弱光电信号检测时间,提高了微弱光电信号检测效率。
In order to improve the detection effect of weak photoelectric signal,aiming at some problems existing in the detection process of weak photoelectric signal,an automatic detection system of weak photoelectric signal based on embedded technology was proposed.Firstly,the research progress of the weak photoelectric signal was analyzed,the weak photoelectric signal was collected,the wavelet analysis method was used to denoise the weak photoelectric signal,the neural network was used to analyze the weak photoelectric signal,and the weak photoelectric signal detection model was established.Finally,the detection effect of the weak photoelectric signal was analyzed by simulation experiment.The results showed that the system can realize the detection of weak photoelectric signal with high precision,reduce the false detection rate of weak photoelectric signal,reduce the detection time of weak photoelectric signal,and improve the detection efficiency of weak photoelectric signal.
作者
李斌
李莉
江恒
Li Bin;Li Li;Jiang Heng(Army Engineering University of PLA Ordnance Sergeant School of the Chinese People′s Liberation Army,Wuhan 430075,China)
出处
《能源与环保》
2021年第10期223-227,共5页
CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基金
陕西国防工业职业技术学院校级项目(Gfy18-09)。
关键词
微弱光电信号
检测模型
去噪处理
神经网络
仿真实验
weak photoelectric signal
detection model
denoising
neural network
simulation experiment