Due　to　the　similarity　in　appearance　and　dense　deployment　of　devices　in　industrial　environments,　relying　solely　on　machine　vision　makes　it　challenging　for　inspection　robots　to　accurately　identify　similar　devices.　Although　wireless　signals　from　industrial　internet　of　things　(IoT)　can　serve　as　identification　features,　signal　fluctuations　impact　the　accuracy　and　efficiency　of　recognition.　To　address　this　issue,　this　paper　proposes　a　proximity　estimation　algorithm　with　position　adjustment　for　autonomous　industrial　inspection.　The　algorithm　considers　the　spatial　relationships　between　nodes　and　the　topological　relationship　between　the　signal　strength　and　variations　among　the　nodes.　By　analyzing　the　topological　relationship　between　the　signal　strength　and　variations　among　the　nodes,　the　robot　autonomously　adjusts　its　position　and　selects　the　proximal　node　based　on　the　spatial　topology　relationship　between　them.　We　have　built　an　inspection　platform　using　quadruped　robots　to　evaluate　the　effectiveness　of　the　experiments.　The　experimental　results　demonstrate　that　the　algorithm　further　improves　the　efficiency　of　identifying　proximal　devices　while　ensuring　the　estimation　accuracy　of　the　algorithm.　©　2024　IEEE.