基于改进Deformable DETR模型的多源局部放电识别方法及其应用
Pattern Recognition Methods of Multi-source Partial Discharge Based on the Improved Deformable DETR Model and its Application
雷志鹏 1彭川 1许子涵 1姜宛廷 1李传扬 2吝伶艳 1彭邦发1
作者信息
- 1. 煤矿电气设备与智能控制山西省重点实验室(太原理工大学电气与动力工程学院),山西省 太原市 030024
- 2. 电力系统及大型发电设备安全控制和仿真国家重点实验室(清华大学电机系),北京市 海淀区 100084
- 折叠
摘要
基于图像的局部放电识别方法大部分仅对单源局部放电谱图有效,无法识别多源局部放电谱图.为实现对多源局部放电谱图的识别,该文提出一种基于Transformer架构的局部放电Deformable DETR目标检测模型,收集典型单源局部放电和多源局部放电数据,生成局部放电相位角解析和极坐标相位分布解析谱图数据集.在Deformable DETR模型中引入去噪训练任务和贝叶斯优化算法,优化了局部放电目标检测模型;编写局部放电谱图采集和识别程序,并使用优化后的局部放电Deformable DETR模型对单源和多源局部放电谱图进行识别.结果表明:局部放电 Deformable DETR模型不仅可有效识别出单源和多源局部放电的类型,而且大幅提升了局部放电类型识别的收敛速度和精度等性能.在对真实绝缘缺陷电动机的局部放电谱图识别中,局部放电Deformable DETR模型的识别准确率达到 91%,证明该模型在实际应用中的有效性.
Abstract
Pattern recognition methods of partial discharge(PD)utilizing images are efficient for the single PD source,yet they face challenges in recognizing the multi-source PD.An object detection model is proposed for the recognition of multi-source PD according to Deformable detection with transformers(Deformable DETR).Typical single-source PD and multi-source PD signals are collected by experiment.Two types of PD spectra,namely phase-resolved partial discharge spectrum and polar coordinate phase-resolved spectrum,are used to generate the data set.The denoising training task and Bayesian optimization algorithm are introduced to optimize the performance of the Deformable DETR model.Single-source and multi-source PD spectra are identified by the optimized PD Deformable DETR model.Results show that the proposed model can effectively recognize the source of single-and multi-PD patterns.In addition,compared with common types of object detection models,the performance of the PD Deformable DETR model can be evidently improved at the cost of losing a few efficiencies.Finally,the PD spectra of real motors with insulation defects are identified by the PD Deformable DETR model.The recognition accuracy reaches 91%,which shows the validity of this proposed method.Additionally,the acquisition and recognition program of PD spectrum is developed.The paper provides novel perspectives for identifying multi-source PD.
关键词
局部放电/模式识别/Deformable/DETR/目标检测/多源局部放电Key words
partial discharge/pattern recognition/Deformable DETR/object detection/multi-source partial discharge引用本文复制引用
基金项目
山西省留学回国人员科技活动择优资助项目(20240005)
国家自然科学基金项目(51977137)
出版年
2024
国家科技期刊平台
NSTL
万方数据