In　order　to　make　full　use　of　the　information　collected　by　multi-source　sensors　and　to　increase　the　damage　identification　accuracy　of　a　structural　health　monitoring　system,　a　damage　identification　method　with　data-fusion　based　on　fuzzy　neural　network　is　proposed　in　this　paper.　In　this　method,　original　structural　response　data　is　preprocessed　and　feature　parameters　are　extracted.　The　parameters　are　used　as　the　input　of　the　fuzzy　neural　network　model,　and　decision　is　obtained　using　this　model.　Finally,　fusion　decision　results　are　analyzed　by　data　fusion　algorithms.　A　7-degree-of-freedom　building　model　is　utilized　to　validate　the　proposed　method,　and　a　comparison　is　made　between　this　method　and　a　single　fuzzy　neural　network　model.　The　results　show　that　the　proposed　damage　identification　method　is　more　exact　and　reliable　than　that　of　a　single　fuzzy　neural　network　model.