Structural　safety　monitoring　system　uses　an　array　of　sensors　to　continuously　monitor　a　structure　to　provide　an　early　indication　of　problems　such　as　damage　to　the　structure　from　fatigue,　corrosion　or　impact.　The　system　is　a　large　sensor　network　containing　about　two　hundred　nodes,　each　of　which　contains　multiple　sensors.　So　the　sensor　fault　diagnosis　is　getting　more　and　more　important.　A　fuzzy-neural　method　is　suggested　in　this　paper.　Based　on　the　function　equivalence　between　T-S　fuzzy　inference　and　RBF　network,　a　kind　of　fuzzy　neural　controller　based　on　RBF　network　with　full-net　structure　is　put　forward.　This　paper　proposes　a　real　code　GA　to　optimize　all　factors　including　scaling　factors,　membership　functions　and　fuzzy　rules.　The　RBF　network　with　two　inputs-one　output　model　is　used　as　fuzzy　controller,　the　result　of　the　simulation　illustrates　that　the　controller　has　good　dynamic　performance　and　strong　robust.