A　damage　detection　method　using　BP　neural　network　based　on　a　novel　damage　index,　the　correlation　characteristic　of　the　acceleration　response,　is　proposed,　and　is　evaluated　through　the　FEM　simulation　and　experiment　verification.　On　the　basis　of　achievements　in　existence,　the　feasibility　of　using　the　correlation　characteristic　as　damage　index　is　validated　theoretically.　The　damage　detection　for　a　simple-supported　beam　using　the　proposed　method　was　FEM　simulated.　The　results　showed　that　the　trained　BP　neural　network　can　correctly　detect　the　location　and　extent　of　damages　in　both　single　damage　case　and　multi-damage　case.　A　model　test　of　a　reinforced　concrete　simple-supported　beam　was　performed　to　verify　the　validity　and　efficiency　of　the　damage　detection　method.　From　the　results　of　the　model　test,　it　is　shown　that　the　trained　BP　neural　network　can　correctly　locate　the　damage　mostly　detect　the　extent　of　damage.　A　conclusion　is　given　that　the　novel　damage　detection　method　using　the　correlation　characteristic　of　the　acceleration　response　as　damage　index　is　feasible　and　efficient.　Copyright　©　2013　Trans　Tech　Publications　Ltd,　Switzerland.