In　order　to　make　full　use　of　redundant,　complementary　and　uncertain　information　and　thus　assess　the　structural　health　states　with　a　structural　health　monitoring　system,　a　new　damage　identification　method　by　integrating　rough　set　with　revised　counter-propagation　network　(RCPN)　was　proposed.　In　the　method,　rough　set　was　used　to　deal　with　data　so　as　to　reduce　their　uncertainties　and　spatial　dimensions,　the　current　CPN　model　was　revised　to　improve　the　capabilities　of　processing　uncertainties　and　carring　on　classification,　and　then　the　RCPN　model　was　used　for　damage　identification.　To　validate　the　proposed　method,　single-　and　multi-damage　patterns　of　a　frame　were　identified　as　an　example,　and　some　important　factors,　such　as　measurement　noise,　neural　network　models　and　data　processing　technologies,　were　investigated　emphatically.　The　results　show　that　the　proposed　method　can　effectively　reduce　the　spatial　dimension　of　data　and　is　of　preferable　damage　identification　accuracy　and　robustness.