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学者姓名：陈丹
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Abstract ：
The meter reading with machine vision greatly improves the efficiency of industrial monitoring. However, the pointer and scales of the meter can be occluded by rain or dirt, which greatly reduces the accuracy of the meter reading recognition. To solve this problem, we propose a generative adversarial network (PMS-GAN) with pointer generation and main scale detection for occluded meter reading. Specifically, dilated convolution block is designed to correlate separated pointer features. Then multi-scale feature fusion mechanism is proposed to guarantee the precision of pointer generation and main scale detection with guidance of semantic information. Moreover, feature enhancement mechanism is proposed to construct the long -range relationship for generating pointer under high occlusion. Finally, the reading is accomplished by calculating local angle with generated pointer and detected main scales. Experiments show that PMS-GAN can generate more intact pointer and detect main scales to guarantee the success and accuracy of occluded meter reading.
Keyword ：
Generative adversarial network Generative adversarial network Local angle calculation Local angle calculation Main scale detection Main scale detection Occluded meter reading Occluded meter reading Pointer generation Pointer generation
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| GB/T 7714 | Lin, Ye , Xu, Zhezhuang , Yuan, Meng et al. Pointer generation and main scale detection for occluded meter reading based on generative adversarial network [J]. | MEASUREMENT , 2024 , 234 . |
| MLA | Lin, Ye et al. "Pointer generation and main scale detection for occluded meter reading based on generative adversarial network" . | MEASUREMENT 234 (2024) . |
| APA | Lin, Ye , Xu, Zhezhuang , Yuan, Meng , Chen, Dan , Zhu, Jinyang , Yuan, Yazhou . Pointer generation and main scale detection for occluded meter reading based on generative adversarial network . | MEASUREMENT , 2024 , 234 . |
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Occlusion recognition plays a vital role in smart manufacturing and industrial automation. This paper proposes an enhanced YOLOv8-based model designed to accurately recognize and locate occluded objects in industrial environments, assisting robots in precise grasping tasks. The model integrates the AKConv module and the Effciou loss function, which improve feature extraction and bounding box regression, especially in complex and highly occluded scenarios. Experimental results confirm that the modified YOLOv8s_Effciou model achieves a balanced performance across different levels of occlusion, showing notable robustness in challenging environments with high occlusion. © 2024 IEEE.
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| GB/T 7714 | Liu, R. , Zhang, H. , Liu, Z. et al. CAE-YOLOV8: Occlusion Object Detection Based on Improved YOLOv8 [未知]. |
| MLA | Liu, R. et al. "CAE-YOLOV8: Occlusion Object Detection Based on Improved YOLOv8" [未知]. |
| APA | Liu, R. , Zhang, H. , Liu, Z. , Chen, D. . CAE-YOLOV8: Occlusion Object Detection Based on Improved YOLOv8 [未知]. |
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针对ACCT-Ⅲ实验箱开展"自动控制原理"实验教学缺乏具体的被控对象的问题,设计以电机为被控对象的实验教学,内容包括建立电机电流和速度数学模型,设计电流、速度闭环PID控制系统,控制系统Matlab仿真,实际伺服电机平台实验等.该实验教学从实物建模、模型仿真、控制器设计到控制系统仿真与实物验证,以项目设计理念为指导,让学生更好地理论与实际相结合,达到知识的内化,提高了教学质量.
Keyword ：
仿真与实物验证 仿真与实物验证 电机实验教学 电机实验教学 自动控制原理 自动控制原理
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| GB/T 7714 | 黄宴委 , 程国扬 , 陈丹 et al. 基于电机的"自动控制原理"实验教学 [J]. | 电气电子教学学报 , 2024 , 46 (4) : 186-191 . |
| MLA | 黄宴委 et al. "基于电机的"自动控制原理"实验教学" . | 电气电子教学学报 46 . 4 (2024) : 186-191 . |
| APA | 黄宴委 , 程国扬 , 陈丹 , 陈少斌 . 基于电机的"自动控制原理"实验教学 . | 电气电子教学学报 , 2024 , 46 (4) , 186-191 . |
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Surface defect detection of sawn timber is a critical task to ensure the quality of wooden products. Current methods have challenges in considering detection accuracy and speed simultaneously, due to the complexity of defects and the massive length of sawn timbers. Specifically, there are scale variation, large intraclass difference and high interclass similarity in the defects, which reduce the detection accuracy. To overcome these challenges, we propose an efficient multilevel-feature integration network (EMINet) based on YOLOv5s. To obtain discriminative features of defects, the cross fusion module (CFM) is proposed to fully integrate the multilevel features of backbone. In the CFM, the local information aggregation is designed to enrich the detailed information of high-level features, and the global information aggregation is designed to enhance the semantic information of low-level features. Experimental results demonstrate that the proposed EMINet achieves better accuracy with fast speed compared with the state-of-the-art methods.
Keyword ：
information aggregation information aggregation machine vision machine vision multilevel feature integration multilevel feature integration sawn timber sawn timber surface defect detection surface defect detection
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| GB/T 7714 | Zhu, Yuhang , Xu, Zhezhuang , Lin, Ye et al. Surface defect detection of sawn timbers based on efficient multilevel feature integration [J]. | MEASUREMENT SCIENCE AND TECHNOLOGY , 2024 , 35 (4) . |
| MLA | Zhu, Yuhang et al. "Surface defect detection of sawn timbers based on efficient multilevel feature integration" . | MEASUREMENT SCIENCE AND TECHNOLOGY 35 . 4 (2024) . |
| APA | Zhu, Yuhang , Xu, Zhezhuang , Lin, Ye , Chen, Dan , Zheng, Kunxin , Yuan, Yazhou . Surface defect detection of sawn timbers based on efficient multilevel feature integration . | MEASUREMENT SCIENCE AND TECHNOLOGY , 2024 , 35 (4) . |
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针对基于随机采样的RRT机械臂路径规划算法在全局工作空间下采样效率低、随机性强等问题,提出一种基于采样点优化RRT算法的机械臂路径规划算法.相对于全局工作空间采样,优化算法首先基于非障碍物空间生成随机采样点,以降低算法碰撞检测概率与冗余节点的生成,再结合一定概率的人工势场法产生启发式采样点,使得机械臂臂体于路径规划采样过程中既能保证随机采样的概率完备,又能使采样点更具目标导向性.其次,为使得路径更加简洁平滑,使用冗余节点删除策略剔除路径中的冗余节点来优化最终路径.最后在二维、三维的仿真环境中对优化算法进行对比实验分析,以验证算法在随机采样路径规划算法中的良好性能,并在IRB 1200-7/0.7机械臂上进行避障规划算法实验.仿真和实验结果都表明,所提出的算法在机械臂路径规划中可以获得更高的规划效率和更优的路径.
Keyword ：
人工势场法 人工势场法 启发式采样 启发式采样 快速随机搜索树 快速随机搜索树 机械臂运动规划 机械臂运动规划 采样点优化 采样点优化 非障碍物空间采样 非障碍物空间采样
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| GB/T 7714 | 陈丹 , 谭钦 , 徐哲壮 . 基于采样点优化RRT算法的机械臂路径规划 [J]. | 控制与决策 , 2024 , 39 (08) : 2597-2604 . |
| MLA | 陈丹 et al. "基于采样点优化RRT算法的机械臂路径规划" . | 控制与决策 39 . 08 (2024) : 2597-2604 . |
| APA | 陈丹 , 谭钦 , 徐哲壮 . 基于采样点优化RRT算法的机械臂路径规划 . | 控制与决策 , 2024 , 39 (08) , 2597-2604 . |
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Wood surface broken defects seriously damage the structure of wooden products, these defects have to be detected and eliminated. However, current defect detection methods based on machine vision have difficulty distinguishing the interference, similar to the broken defects, such as stains and mineral lines, and can result in frequent false detections. To address this issue, a multi-source data fusion network based on U-Net is proposed for wood broken defect detection, combining image and depth data, to suppress the interference and achieve complete segmentation of the defects. To efficiently extract various semantic information of defects, an improved ResNet34 is designed to, respectively, generate multi-level features of the image and depth data, in which the depthwise separable convolution (DSC) and dilated convolution (DC) are introduced to decrease the computational expense and feature redundancy. To take full advantages of two types of data, an adaptive interacting fusion module (AIF) is designed to adaptively integrate them, thereby generating accurate feature representation of the broken defects. The experiments demonstrate that the multi-source data fusion network can effectively improve the detection accuracy of wood broken defects and reduce the false detections of interference, such as stains and mineral lines.
Keyword ：
deep learning deep learning multi-source data fusion multi-source data fusion semantic segmentation semantic segmentation U-Net U-Net wood defect detection wood defect detection
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| GB/T 7714 | Zhu, Yuhang , Xu, Zhezhuang , Lin, Ye et al. A Multi-Source Data Fusion Network for Wood Surface Broken Defect Segmentation [J]. | SENSORS , 2024 , 24 (5) . |
| MLA | Zhu, Yuhang et al. "A Multi-Source Data Fusion Network for Wood Surface Broken Defect Segmentation" . | SENSORS 24 . 5 (2024) . |
| APA | Zhu, Yuhang , Xu, Zhezhuang , Lin, Ye , Chen, Dan , Ai, Zhijie , Zhang, Hongchuan . A Multi-Source Data Fusion Network for Wood Surface Broken Defect Segmentation . | SENSORS , 2024 , 24 (5) . |
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针对遮挡目标的机器人抓取存在的遮挡干扰问题,提出了改进的YOLO-CA-SD和语义分割的遮挡目标检测模型及抓取方法,完成多目标及非目标物互相遮挡干扰情况下的抓取.首先,该模型在YOLOv5l中添加坐标注意力,在损失函数基础上考虑检测框匹配方向的问题,增加框之间的角度信息,并对原模型检测部分进行解耦,减少耦合造成的信息丢失.其次,提出了改进的DeeplabV3+目标分割模型,用MobileNetV2 替换DeeplabV3+原主干网络,减小模型复杂度,在空洞空间金字塔池化结构中添加CA模块融合像素坐标信息提高分割精度,解决了遮挡干扰问题.最后,利用点云配准得到目标姿态相对于模板姿态的末端旋转角及最优抓取点.在 2 750 张自主构建的常用工具遮挡数据集上进行性能测试,结果表明:改进后的模型在mAP@0.5,mAP@0.5:0.95、60%目标物体遮挡率数据集及 60%非目标物体遮挡率数据集上的检测精度分别提高了 0.052%、0.968%、6.000%、7.400%.此基础上改进的语义分割模型分割速度和MIOU分别提升了 33.45%和 0.625%,并且通过ABB IRB1200 机械臂实现遮挡目标的抓取实验,验证了该方法的可行性与实用性.
Keyword ：
DeeplabV3+模型 DeeplabV3+模型 YOLO YOLO 点云配准 点云配准 目标抓取 目标抓取 遮挡目标检测 遮挡目标检测
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| GB/T 7714 | 林哲 , 潘慧琳 , 陈丹 . 融合改进YOLO和语义分割的遮挡目标抓取方法 [J]. | 电子测量与仪器学报 , 2024 , 38 (12) : 190-201 . |
| MLA | 林哲 et al. "融合改进YOLO和语义分割的遮挡目标抓取方法" . | 电子测量与仪器学报 38 . 12 (2024) : 190-201 . |
| APA | 林哲 , 潘慧琳 , 陈丹 . 融合改进YOLO和语义分割的遮挡目标抓取方法 . | 电子测量与仪器学报 , 2024 , 38 (12) , 190-201 . |
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在输电线张力放线过程中，走板过转角塔时易因其受力复杂导致其倾斜角与滑车倾斜角不一致而发生跳槽甚至翻转故障。针对此问题，本文建立张力机出口张力与走板倾斜角的数学模型，以便准确控制走板过转角塔时的倾斜角。首先，根据导线的牵展计算得到张力机出口张力控制值；然后考虑到走板在放线过程中的受力情况，建立走板力矩平衡方程；最后，获得张力机出口张力对走板倾斜角的控制模型，并提出张力机出口张力调整策略。在某实际输电线路工程中应用本文提出的力学模型进行仿真验证。结果表明，模型计算的张力机出口张力控制值与实际值误差在5%以内；并且，根据模型分析了走板尺寸、重量及转角塔的位置对走板倾斜角的影响，并结合走板期望倾斜角确定张力机出口张力的最佳调整策略，提高了放线施工的效率和安全。
Keyword ：
姿态调节 姿态调节 张力放线 张力放线 调整策略 调整策略 走板力学模型 走板力学模型 转角塔 转角塔 输电线 输电线
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| GB/T 7714 | 张建勋 , 卞宏志 , 杨大淼 et al. 架空输电线走板与张力机之间的力学模型研究 [J]. | 科技通报 , 2023 , 39 (01) : 53-58,90 . |
| MLA | 张建勋 et al. "架空输电线走板与张力机之间的力学模型研究" . | 科技通报 39 . 01 (2023) : 53-58,90 . |
| APA | 张建勋 , 卞宏志 , 杨大淼 , 徐康 , 陈丹 . 架空输电线走板与张力机之间的力学模型研究 . | 科技通报 , 2023 , 39 (01) , 53-58,90 . |
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| GB/T 7714 | Lin, Ye , Xu, Zhezhuang , Chen, Dan et al. Wood Crack Detection Based on Data-Driven Semantic Segmentation Network [J]. | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2023 , 10 (6) : 1510-1512 . |
| MLA | Lin, Ye et al. "Wood Crack Detection Based on Data-Driven Semantic Segmentation Network" . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA 10 . 6 (2023) : 1510-1512 . |
| APA | Lin, Ye , Xu, Zhezhuang , Chen, Dan , Ai, Zhijie , Qiu, Yang , Yuan, Yazhou . Wood Crack Detection Based on Data-Driven Semantic Segmentation Network . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2023 , 10 (6) , 1510-1512 . |
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Due to the characteristics of similar appearance and dense deployment of devices in industrial field, it is difficult for the inspection robot to recognize similar devices in industrial field only by machine vision, which affects the accuracy and efficiency of autonomous inspection. To solve the above problems, this article proposes a similar industrial devices recognition strategy by using machine vision and proximity estimation based on the wireless signal characteristics of industrial internet of things. Firstly, the initial pose of the inspection robot is estimated by machine vision and the efficient perspective-N-point algorithm. Then, the proximity estimation algorithm is used to realize the recognition of proximal industrial devices targets by inspection robot. On the other hand, the strategy also includes robot angle correction and position adjustment algorithm to ensure the accuracy of proximity estimation. Compared with the traditional recognition method based on machine vision, experimental results show that the designed strategy can improve the recognition accuracy of similar industrial devices by 2% ~49% in different devices density scenarios, which effectively solves the problem of similar devices recognition of inspection robots in industrial field. © 2023 Science Press. All rights reserved.
Keyword ：
industrial Internet of things industrial Internet of things inspection robot inspection robot machine vision machine vision pose estimation pose estimation proximity estimation proximity estimation similar industrial devices recognition similar industrial devices recognition
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| GB/T 7714 | Xu, Z. , Huang, P. , Chen, D. et al. Research on similar industrial devices recognition strategy based on machine vision and proximity estimation; [融合机器视觉与邻近度估计的相似工业设备识别策略研究] [J]. | Chinese Journal of Scientific Instrument , 2023 , 44 (1) : 283-290 . |
| MLA | Xu, Z. et al. "Research on similar industrial devices recognition strategy based on machine vision and proximity estimation; [融合机器视觉与邻近度估计的相似工业设备识别策略研究]" . | Chinese Journal of Scientific Instrument 44 . 1 (2023) : 283-290 . |
| APA | Xu, Z. , Huang, P. , Chen, D. , Wu, K. , Li, J. . Research on similar industrial devices recognition strategy based on machine vision and proximity estimation; [融合机器视觉与邻近度估计的相似工业设备识别策略研究] . | Chinese Journal of Scientific Instrument , 2023 , 44 (1) , 283-290 . |
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