中国电机工程学报2024，Vol.44Issue(15)：6248-6260,封3,14.DOI:10.13334/j.0258-8013.pcsee.240009
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
摘要
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分类
信息技术与安全科学引用本文复制引用
雷志鹏,彭川,许子涵,姜宛廷,李传扬,吝伶艳,彭邦发..基于改进Deformable DETR模型的多源局部放电识别方法及其应用[J].中国电机工程学报,2024,44(15):6248-6260,封3,14.基金项目
山西省留学回国人员科技活动择优资助项目(20240005) （20240005）
国家自然科学基金项目(51977137). Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province(20240005) （51977137）
Project Supported by National Natural Science Foundation of China(51977137). （51977137）
