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Verification of Near Field SAR Image Formation Based on RMA in Blast Furnace Stock Lines

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Verification of Near Field SAR Image Formation Based on RMA ...

第37届中国控制会议

作者： Qing Yu Xianzhong Chen qingwen hou School of Automation Engineering University of Science Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing

In this paper, the imaging of blast furnace（BF） stock line has been studied. The three-dimensional synthetic aperture radar（SAR） imaging of BF stock line is realized in anechoic chamber, which lays the foundation for the research and development of blast furnace imaging system. By improving the classical RMA algorithm, adding the original data down-sampling, targeting feature extraction, zero-filling to the frequency domain and other operations the speed of imaging and the quality of imaging are constantly improved. The three-dimensional imaging experiments of K band and X band are implemented based on the comparative method. It has been used on the typical stock line scaling model, and the stock line scaling model consists of steel ball. The imaging error of the steel balls in the K band is analyzed.

关键词： blast furnace stock line SAR imaging RMA imaging algorithm

Image Feature Extraction of FMCW Signal For Unsteady Rough Flow Interface

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Image Feature Extraction of FMCW Signal For Unsteady Rough F...

第37届中国控制会议

作者： Yongliang Ma qingwen hou Xianzhong Chen School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education

On the basis of Fast Fourier transform, the FMCW signals of unsteady rough flow interface are extended on a multi-time scale. This method avoids the shortcomings of poor anti-interference ability of the conventional peak-searching distance-calculating method. After the Fast Fourier transform is performed on sampling data in a fixed time period, a two-dimensional matrix containing distance information is generated. Based on the variance theory, an FMCW image feature extraction algorithm is proposed, which can achieve the accuracy of 97.5% for low SNR signal extraction even in harsh environments. At the same time, the iterative algorithm in image threshold segmentation is also applied to the distance information extraction of rough flow interface, and the useful distance information is extracted from fuzzy wideband.

关键词： Rough Interface FMCW Feature Extraction Variance Iteration

3D Object Detection Algorithm in Adverse Weather Conditions Based on LiDAR-Radar Fusion

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3D Object Detection Algorithm in Adverse Weather Conditions ...

第43届中国控制会议

作者： Zeyu Wu qingwen hou Xianzhong Chen Jie zhang Kexing Gao School of Automation and Electrical Engineering University of Science and Technology Beijing Shunde Innovation School University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education University of Science and Technology Beijing

In adverse weather conditions such as rainy or foggy weather, the point cloud data from lidar may not reliably describe the environment. In such situations, the robust information from millimeter-wave radar, which is less susceptible to environmental interference, can compensate for the limitations of lidar. Effectively integrating the information from both radars to enhance the robustness of target detection under adverse weather conditions poses a challenge. To address this issue, a road scene multi-object detection algorithm based on the fusion of lidar and millimeter-wave radar in adverse weather conditions is proposed, leveraging improvements based on the CenterPoint framework. The algorithm incorporates a transformer-enhanced network and fuses information from both radars at the feature level. Experimental evaluations conducted on the Fog-nuscenes dataset, which underwent simulated foggy weather conditions, demonstrate that the proposed network achieves a mAP of 49.52%.Compared to the original CenterPoint network, this represents a significant improvement of 10.75%.

关键词： 3D object detection Sensor fusion Transformer Adverse weather Self-driving

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高炉浓尘环境料面散射特性建模与成像

系统工程与电子技术 2023年第5期45卷 1277-1285页

作者：于晴侯庆文陈先中北京科技大学自动化学院北京100083 北京科技大学工业过程知识自动化教育部重点实验室北京100083

工业恶劣成像环境下的雷达图像常存在对比度低和清晰度差等问题,质量退化的图像直接影响计算机视觉任务的处理效果以及目标参数反演结果。因此,对高炉料面后向散射进行建模,并针对弥散浓尘环境下的随机粗糙料面成像,提出一种基于衰减补... 详细信息

工业恶劣成像环境下的雷达图像常存在对比度低和清晰度差等问题,质量退化的图像直接影响计算机视觉任务的处理效果以及目标参数反演结果。因此,对高炉料面后向散射进行建模,并针对弥散浓尘环境下的随机粗糙料面成像,提出一种基于衰减补偿和散射修正的成像方法。考虑微波沿空间路径的传播损耗,在回波模型中加入环境因子,采用瑞利散射和积分方程法分别求解衰减系数和粗糙面的后向散射系数,从传输损耗和散射机理出发,对图像进行损耗补偿以及目标像素亮度的提升,减小图像因成像环境、目标距离以及表面起伏形状不同造成的信号强度差异。通过南钢3号高炉雷达数据验证算法,目标像素亮度差异平均减小4.33 dB,有效改善雷达成像中高炉径向距离起伏料面的成像性能。

关键词：散射特性随机粗糙面损耗补偿高炉料面成像

RPCNet:Vehicle Completion in Traffic Scenes Based on mmWave Radar Point Cloud Data

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RPCNet:Vehicle Completion in Traffic Scenes Based on mmWave ...

第43届中国控制会议

作者： Kexin Gao Xianzhong Chen qingwen hou Jie Zhang Zeyu Wu School of Automation University of Science and Technology Beijing Shunde Innovation School University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Process of Ministry of Education University of Science and Technology Beijing

Millimeter-wave radar has the advantages of low hardware cost, all-weather operation, and long detection range that other sensors do not have. However, due to the flaws in its working principle and the large influence of resolution by hardware(e.g., antenna array size), the point clouds of millimeter-wave radar are relatively sparse. Therefore, the direct utilization of millimeter-wave radar raw point clouds for target detection is greatly restricted. In this paper, we propose an end-to-end radar point cloud completion network(RPCNet). A generative adversarial network(GAN) framework is used to learn the rich spatial features of vehicle radar point cloud and their differences from ground truth. First, to better integrate feature information at different scales, intra-layer dense connections(ILDC) are used to extract features. Dense connections are used within dense blocks and between blocks to realize the feeding of point features, improving feature extraction's accuracy and ***, an up-down-up sampling(UDUS) unit is designed to achieve feature expansion. Feed correction of features is achieved by introducing the difference between point features before up-sampling and after down-sampling into the feature expansion module. It is conducive to generating fine-grained features. Finally, experimental verification is performed on the nu Sence dataset. The fidelity error(FD) reaches 0.0213m and the F-Score reaches 70.68%. Compared with the current best-performing ASFM-Net model, the FD is reduced by 0.0037m, and the F-Score is also increased by 1.96%. The chamfer distance(CD) is 0.2678m, which is also close to the optimal performance.

关键词： point cloud completion multi-radar intra-layer dense connection up-down-up sampling expansion self-attention

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77GHz宽带低副瓣毫米波微带天线设计

西安电子科技大学学报 2022年第5期49卷 109-116页

作者：范文颖侯庆文陈先中北京科技大学自动化学院北京100083 北京科技大学工业过程知识自动化教育部重点实验室北京100083 北京科技大学顺德研究生院广东528300

针对微带天线带宽较窄的问题,提出一种适用于地下煤矿机器人环境感知的宽带低副瓣毫米波微带阵列天线。该毫米波天线阵列由主辐射单元层、寄生贴片层以及空气层构成。主辐射单元采取道尔夫-切比雪夫阵列综合方法以实现低副瓣特点,空气... 详细信息

针对微带天线带宽较窄的问题,提出一种适用于地下煤矿机器人环境感知的宽带低副瓣毫米波微带阵列天线。该毫米波天线阵列由主辐射单元层、寄生贴片层以及空气层构成。主辐射单元采取道尔夫-切比雪夫阵列综合方法以实现低副瓣特点,空气层和寄生单元通过降低等效介电常数及增加新的谐振点有效展宽天线带宽,T形功分器馈电网络设计实现良好的阻抗匹配。HFSS仿真结果表明,天线的-10 dB阻抗带宽为7 GHz,工作频率为76.6~83.6 GHz,E面最大副瓣电平为-15 dB,H面最大副瓣电平为-24 dB,最大增益为17 dBi,满足了毫米波雷达远近距离切换和复杂散射介质回波灵敏度的应用需求。与目前的77 GHz毫米波天线相比,此天线有效降低了副瓣电平,进一步拓展了工作带宽,提高了雷达的抗干扰能力以及分辨率。针对地下煤矿复杂的地磁环境特点,该天线所具有的强抗干扰能力和高分辨率等性能在地下巷道环境感知方面有很大的优势。

关键词：微带天线宽带低副瓣毫米波煤矿机器人

Image Enhancement and Feature Understanding of Blast Furnace Swing Radar

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Image Enhancement and Feature Understanding of Blast Furnace...

第32届中国控制与决策会议

作者： Yang Liu Xin Lv Lingkun Chen qingwen hou Xianzhong Chen Rongjie Liu School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Ironmaking Institute Central Research Institute of Baosteel Co.Ltd.

Radar technology is performed to obtain the position and morphology of burden surface in blast furnace,which is conducive to the optimal process of decision-making over burden *** the imaging of the of echo spectrum,includes the characteristics of local highlighting and low signal-to-noise ratio,the adaptive gray-scale compensation algorithm combined with multi-scale Retinex image enhancement is adopted for high-quality brightness adjustment and color ***,in order to make the target burden surface prominent and distinguishable,the improved hot metal coding method is applied to conduct pseudo-color processing of the enhanced image as obtained *** the meantime,the guided image filtering algorithm is introduced to maintain the target boundary of the burden surface while ensuring the effective removal of ***,the fractal interpolation algorithm is employed in line with the principle of SAR imaging to reconstruct the radar image of burden surface in blast ***,a qualitative analysis is conducted during production of the major characteristics of burden surface.

关键词： Blast Furnace Radar Image Enhancement Denoising Characteristics Analysis

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面向高炉料面监测的宽带微带阵列天线设计

西安电子科技大学学报 2021年第4期48卷 83-90页

作者：王宇于静娜陈先中侯庆文北京科技大学自动化学院北京100083 北京科技大学工业过程知识自动化教育部重点实验室北京100083

针对高炉雷达高分辨率成像和高集成度的设计需求,设计了一种宽带微带阵列天线。通过寄生贴片和空气层的设计展宽天线带宽,将多输入多输出雷达与合成孔径雷达成像原理相结合,设计了线性多输入多输出阵列。通过波数域成像算法,对模拟料线... 详细信息

针对高炉雷达高分辨率成像和高集成度的设计需求,设计了一种宽带微带阵列天线。通过寄生贴片和空气层的设计展宽天线带宽,将多输入多输出雷达与合成孔径雷达成像原理相结合,设计了线性多输入多输出阵列。通过波数域成像算法,对模拟料线进行了近场仿真成像实验。实验结果表明,天线主瓣方向增益可达14.05 dBi,反射系数小于-10 dB,绝对带宽为5.25 GHz,工作频率为20.67~25.92 GHz。距离向分辨率较现有高炉雷达提高至3 cm,模拟料线成像的方位向平均误差为0.008 m,距离向平均误差约为0.0011 m。与传统微带阵列天线相比,此天线有效地拓宽了带宽,距离向分辨率比传统高炉雷达高,可以准确地获得模拟料线形状信息,对高炉料面监测有工程应用价值。

关键词：微带天线宽带寄生贴片高炉近场成像

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三坐标机在齿轮误差测量中的应用

四川联合大学学报（工程科学版） 1997年第4期1卷 73-77页

作者：樊庆文侯力四川联合大学机械系

本文讨论了三坐标测量机测量误差的原理，提供了一种测量齿轮误差的新方法。并用实验证明了该测量方法的正确性。

关键词：三坐标机齿轮误差测量加工精度