The　technical　foundation　of　intelligent　inspection　of　power　lines　is　the　detection　of　components　in　aerial　images.　With　the　rapid　development　of　deep　learning,　new　object　detection　technologies　are　constantly　emerging.　However,　accurate　annotation　of　data　sets　is　equally　crucial　for　improving　detection　performance.　This　study　proposes　a　truth　inference　algorithm　for　transmission　line　components　to　improve　the　accuracy　and　reliability　of　annotated　data.　Propose　Multi　component　label　removal　algorithm　and　Large　box　label　removal　algorithm　for　both　normal　sized　and　small-sized　components,　respectively.　The　experimental　results　show　that　our　method　has　achieved　significant　results　in　improving　the　quality　and　accuracy　of　annotated　data.　This　study　is　of　great　significance　for　improving　the　accuracy　of　annotation　on　power　line　datasets.