In　the　real　civil　structures,　material　deterioration,　overloading　and　environmental　corrosion　inevitably　lead　to　sensor　performance　degradation　or　sensor　fault.　Sensor　performance　degradation　or　sensor　fault　usually　introduce　observable　changes　in　the　measured　structural　responses,　which　may　be　incorrectly　interpreted　as　structural　damage.　This　paper　proposes　a　novel　approach　to　quickly　distinguish　sensor　fault　from　structural　damage　and　locate　the　faulty　or　degraded　sensors.　Two　steps　are　involved　in　this　approach.　In　the　first　step,　the　root　mean　square　of　the　generalized　likelihood　ratio　test　(GLRT)　is　used　to　detect　and　localize　the　structural　damage　or　degraded　sensors.　In　the　second　step,　a　new　index　is　proposed　used　along　with　the　statistical　process　control　chart　to　distinguish　sensor　performance　degradation　from　structural　damage.　The　proposed　index　is　the　percentage　of　the　extreme　value　of　the　largest　principal　component　scores　of　the　generalized　likelihood　ratio,　which　not　only　has　excellent　noise　tolerance　but　also　can　distinguish　sensor　performance　degradation　from　structural　damage.　The　applicability　and　efficiency　of　the　proposed　approach　are　validated　by　numerical　studies　on　a　planar　11-element　truss　structure　and　experimental　studies　on　a　simply-supported　steel　beam　in　the　laboratory.　The　results　demonstrate　that　the　proposed　approach　can　locate　the　damage　accurately　when　taking　into　account　of　sensor　performance　degradation　and　environmental　noise　in　the　measurements.　The　proposed　index　is　able　to　accurately　and　quickly　determine　the　source　of　the　novelty　in　the　responses.　©　2018