Lei Yang, Zou Yong, Jiang Bo, Tian Tian
China Academy of Railway Sciences, Beijing 100081, China.
Beijing ZhuoRuiXinDa Technology Co., Ltd, Beijing 101599, China.
Comput Intell Neurosci. 2022 Apr 25;2022:2459996. doi: 10.1155/2022/2459996. eCollection 2022.
With the rapid development of science and technology, testing equipment and testing methods are constantly updated. Radar detectors have the advantages of losslessness, high efficiency, high resolution, and high-speed radar image capture. They can accurately locate defects in railway tunnels, respond to hidden dangers in time, and provide strong technical support for transportation. This paper proposes to optimize the defect detection of railway tunnel radar through the combination of multisensor technology and active interference suppression algorithm and designs the corresponding sensor system according to the content. This article analyzes several factors that affect the radar detection effect and makes a detailed summary from the detection environment and other aspects. At the same time, it uses the multisensor system combined with active interference suppression algorithm to design a railway tunnel detection simulation experiment. Experimental results show that the use of multisensors combined with active interference suppression algorithm to optimize radar detection can effectively improve the accuracy of railway tunnel defect detection. Through the analysis of the results of tunnel defect detection, the detection accuracy of this paper has reached 98.8%, which can provide an effective reference for the detection of railway tunnels.
随着科学技术的飞速发展,检测设备和检测方法不断更新。雷达探测器具有无损、高效、高分辨率以及能高速捕捉雷达图像的优点。它们能够精确地定位铁路隧道中的缺陷,及时应对隐患,为交通运输提供有力的技术支持。本文提出通过多传感器技术与有源干扰抑制算法相结合来优化铁路隧道雷达的缺陷检测,并根据内容设计相应的传感器系统。本文分析了影响雷达检测效果的几个因素,并从检测环境等方面进行了详细总结。同时,利用多传感器系统结合有源干扰抑制算法设计了铁路隧道检测模拟实验。实验结果表明,采用多传感器结合有源干扰抑制算法优化雷达检测能够有效提高铁路隧道缺陷检测的准确性。通过对隧道缺陷检测结果的分析,本文的检测准确率达到了98.8%,可为铁路隧道检测提供有效的参考。