摘要
设计了一种基于CMOS图像传感器与FPGA结合HMI(Human Machine Interface)的低能辐射探测系统。该系统通过HMI将数据传输至手机APP,使用手机APP对探测结果进行显示并同步HMI进行远程控制。优化前端算法,提出了BP神经网络与边缘检测求和算法相结合的算法。利用60Co对系统的精确度与灵敏度进行测试,实验结果表明,通过BP神经网络与边缘检测求和算法的结合,采用HMI进行无线远程控制,可实现低能辐射在线探测技术的高精确度和高灵敏度特性。
A low energy radiation detection system based on CMOS image sensor and FPGA com-bined with HMI is designed.The system transmits the data to the mobile APP through HMI,and the mobile APP displays the detection results and synchronizes the HMI for remote control.The front end algorithm is optimized,and an algorithm combining BP neural network and edge detec-tion summation algorithm is proposed.The accuracy and sensitivity of system were tested with"0 Co.The experimental results showed that the combination of BP neural network and edge detection sum mation algorithm and wireless remote control with HMI could realize the high accu-racy and high sensitivity of low-energy radiation online detection technology.
作者
王芳
郑丽雯
袁延忠
马春旺
金婵
WANG Fang;ZHENG Li-wen;YUAN Yan-zhong;MA Chun-wang;JIN Chan(College of Electronics and Electrical Engineering,Henan Normal University,Xinxiang Henan 453007,China;College of Physics,Henan Normal University,Xinxiang Henan 453007,China;Key Laboratory of Optoelectronic Sensing Integrated Application of Henan Province,Xinxiang Henan 453007,China;Shanghai Institute of Applied Physics,Chinese Academy of Sciences,Shanghai 201800,China)
出处
《核电子学与探测技术》
CAS
北大核心
2020年第4期544-549,共6页
Nuclear Electronics & Detection Technology
基金
国家自然科学基金(61627818)
河南师范大学国家级项目培育基金(2017PL04)
河南省重点科技攻关计划项目(182102210366)资助。
