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1.湖北省铁路集团汉十城际铁路有限责任公司,武汉 430062
2.华东交通大学电气与自动化工程学院,南昌 330013
余世文(1971—),男,高级工程师,主要从事铁路四电工程管理工作。
石钟锋(1999—),男,硕士研究生,研究方向为电力设备无损检测。E-mail:1925506621@qq.com。
程宏波(1979—),男,教授,研究方向为电力设备故障诊断。
收稿日期:2025-05-08,
纸质出版日期:2025-06-25
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余世文, 石钟锋, 程宏波. 基于多能量X射线图像融合的电缆接头状态判断方法[J]. 电力电容器与无功补偿, 2025,46(3):13-19.
YU Shiwen, SHI Zhongfeng, CHENG Hongbo. Condition Judgement Method of Cable Joints Based on Multi Energy X-ray Image Fusion[J]. Power capacitor & reactive power compensation, 2025, 46(3): 13-19.
余世文, 石钟锋, 程宏波. 基于多能量X射线图像融合的电缆接头状态判断方法[J]. 电力电容器与无功补偿, 2025,46(3):13-19. DOI: 10.14044/j.1674-1757.pcrpc.2025.03.002.
YU Shiwen, SHI Zhongfeng, CHENG Hongbo. Condition Judgement Method of Cable Joints Based on Multi Energy X-ray Image Fusion[J]. Power capacitor & reactive power compensation, 2025, 46(3): 13-19. DOI: 10.14044/j.1674-1757.pcrpc.2025.03.002.
电缆接头内部结构复杂、组成材质性质各异,为利用X射线实现电缆接头内部全部结构的清晰呈现,提出了一种基于多能量X射线图像融合的电缆接头状态判断方法。采用引导滤波将电缆接头X检测图像进行多尺度分解,将多能量X射线图像分为细节层和基础层,利用多尺度梯度函数生成细节层的显著性映射,归一化后得到细节层的融合权重图,基于曝光度的偏离程度分配不同基础层的融合权重,对基础层和细节层分别进行加权融合得到重构后的融合图像,将融合后的待检图像与标准图像进行差分计算来判断缺陷的位置。试验结果表明,采用分解后再融合的方法,所得融合图像在方差、信息熵、平均梯度与空间频率几个指标方面有明显的优势;与单一检测图像相比,多能量X射线融合图像能将电缆接头内部不同结构在一张图像上呈现的更清晰更完整,有利于电缆接头缺陷的精确识别和定位。
The cable joints is complex in internal structure and the composition of the material properties are different. In order to use X-ray to realize a clear presentation of all the internal structure of cable joints
a condition judgement method of cable joints based on multi-energy X-ray image fusion is proposed. The guided filtering is used to decompose the X-ray inspection image of cable joints into multi-scale and the multi-energy X-ray image is divided into both detail layer and base layer. The multi-scale gradient function is used to generate the significant mapping of the detail layer
and the fusion weight map of the detail layer is obtained after normalization
the fusion weights of different base layers are assigned based on the degree of deviation from the exposure degree
and the weighted fusion is performed on the base and detail layers to get the reconstructed fusion image. Moreover
the fused image to be examined is differentiated from the standard image to judge the location of defects. The test results show that the fusion image obtained by the method of decomposition and then fusion has better advantages in variance
information entropy
average gradient and spatial frequency. The multi-energy X-ray fusion image
compared with the single detection image
can present the different internal structures of the cable joints in a clearer and more complete image
which is conducive to the accurate identification and localization of the defects in the cable joints.
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