许可项目：第一类增值电信业务；互联网信息服务；建筑智能化工程施工；各类工程建设活动；建设工程设计；检验检测服务；测绘服务；出版物批发；出版物零售(依法须经批准的项目，经相关部门批准后方可开展经营活动，具体经营项目以审批结果为准)。一般项目：软件开发；技术服务、技术开发、技术咨询、技术交流、技术转让、技术推广；人工智能应用软件开发；物联网技术研发；在线能源监测技术研发；在线能源计量技术研发；海上风电相关系统研发；风电场相关系统研发；智能机器人的研发；物联网应用服务；工程和技术研究和试验发展；资源再生利用技术研发；新材料技术研发；信息技术咨询服务；企业管理咨询；信息系统运行维护服务；人工智能行业应用系统集成服务；信息系统集成服务；工程管理服务；互联网安全服务；互联网数据服务；网络技术服务；新材料技术推广服务；区块链技术相关软件和服务；人工智能双创服务平台；接受金融机构委托从事信息技术和流程外包服务（不含金融信息服务）；云计算设备制造；机械电气设备制造；电池制造；电池销售；通讯设备销售；物联网设备销售；电子产品销售；人工智能硬件销售；照明器具销售；机械电气设备销售；建筑材料销售；电线、电缆经营；互联网销售（除销售需要许可的商品）；汽车新车销售；新能源汽车整车销售；计算机软硬件及辅助设备批发；计算机及通讯设备租赁；仓储设备租赁服务；汽车租赁；国内贸易代理；科技中介服务；会议及展览服务；平面设计；广告设计、代理；广告制作；广告发布（非广播电台、电视台、报刊出版单位）(除依法须经批准的项目外，凭营业执照依法自主开展经营活动)。
In power systems,the stability and reliability of transmission lines are crucial.Bolts,as key components for connecting and fixing the main body of the lines,play a decisive role in maintaining the stability of a power system.However,during the inspection of transmission lines,detecting defects in these bolts using vision-based methods becomes particularly difficult because of the small proportion,uneven distribution,and indistinct features of bolts in the inspection images.To address these issues,an adaptive block detection method consisting of two stages is designed.In the first stage,an improved target density distribution map generation network is employed to predict a target density distribution map containing the approximate size and distribution information of the targets.This network is composed of RepODconv convolution blocks based on parameter reconstruction and multidimensional dynamic convolution technology,which effectively controls the model's parameter quantity while enhancing the network's attention to small-sized targets.Subsequently,a clustering block algorithm is designed to obtain fixed-size and unsealed block-area images based on this target density distribution map.In the second stage,the YOLOX model combined with self-attention modules is employed to detect these images,enhancing the network's discrimination ability for defects of different categories.Experimental results on a dataset of transmission line bolt inspections by unmanned aerial vehicles show that the recall rate and precision of majority-class defects reach 70％.Compared to the experimental results of current advanced detection networks,the Average Precision at Intersection over Union(IoU)of 0.5(mAP@0.5)is improved by approximately 30％,mean AveragePrecision(mAP)is improved by approximately 70％,and the mAP of small targets is improved by approximately 2 times.
