Electric Power Research Institute, State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050017, China.
Sensors (Basel). 2022 Dec 13;22(24):9773. doi: 10.3390/s22249773.
The accurate detection of insulators is an important prerequisite for insulator fault diagnosis. To solve the problem of background interference and overlap caused by the axis-aligned bounding boxes in the tilting insulator detection tasks, we construct an improved detection architecture according to the scale and tilt features of the insulators from several perspectives, such as bounding box representation, loss function, and anchor box construction. A new orientation detection method for tilting insulators based on angle regression and priori constraints is put forward in this paper. Ablation tests and comparative validation tests were conducted on a self-built aerial insulator image dataset. The results show that the detection accuracy of our model was increased by 7.98% compared with that of the baseline, and the overall detection accuracy reached 82.33%. Moreover, the detection effect of our method was better than that of the YOLOv5 detection model and other orientation detection models. Our model provides a new idea for the accurate orientation detection of insulators.
准确检测绝缘子是绝缘子故障诊断的重要前提。为了解决倾斜绝缘子检测任务中由于轴对齐边界框引起的背景干扰和重叠问题，我们根据绝缘子的几个方面的尺度和倾斜特征，例如边界框表示、损失函数和锚框构建，构建了一个改进的检测架构。本文提出了一种基于角度回归和先验约束的倾斜绝缘子新的定向检测方法。在自建的架空绝缘子图像数据集上进行了消融测试和对比验证测试。结果表明，与基线相比，我们模型的检测精度提高了 7.98%，整体检测精度达到 82.33%。此外，我们的方法的检测效果优于 YOLOv5 检测模型和其他定向检测模型。我们的模型为绝缘子的准确定向检测提供了新的思路。
