With　the　development　of　microgrid,　the　issue　of　short　circuit　fault　detection　and　location　has　become　key　challenges　for　the　reliable　operation　of　microgrids.　Traditional　microgrid　fault　protection　schemes　often　overlook　the　changes　in　system　topology,　but　the　switching　of　distributed　energy　sources　(DES)　and　loads　can　result　in　topology　change,　which　impairs　the　performance　of　fault　detection　and　location.　In　this　paper,　addressing　the　limitations　of　existing　microgrid　fault　protection　schemes,　a　microgrid　simulation　model　including　a　variety　of　DES　is　built　in　MATLAB,　and　the　wavelet　energy　spectrum　transformation　is　applied　for　the　analysis　of　short　circuit　fault　with　changing　microgrid　topology.　Then,　a　multi-agent　collaborative　protection　strategy　based　on　edge　computing　is　proposed　to　achieve　short　circuit　fault　detection　and　location　with　automatic　topology　adaption.　The　concept　of　edge　computing,　which　is　a　branch　of　artificial　intelligence　(AI)　is　incorporated　for　automatic　collaboration　of　agents.　Results　of　simulation　experiments　with　changing　topology　and　multiple　types　of　short　circuit　fault　validate　the　feasibility　of　the　proposed　method.　©　2025　IEEE.