The　membrane　bioreactor　(MBR)　has　been　widely　used　to　purify　wastewater　in　wastewater　treatment　plants.　However,　a　critical　difficulty　of　the　MBR　is　membrane　fouling.　To　reduce　membrane　fouling,　in　this　work,　an　intelligent　detecting　system　is　developed　to　evaluate　the　performance　of　MBR　by　predicting　the　membrane　permeability.　This　intelligent　detecting　system　consists　of　two　main　parts.　First,　a　soft　computing　method,　based　on　the　partial　least　squares　method　and　the　recurrent　fuzzy　neural　network,　is　designed　to　find　the　nonlinear　relations　between　the　membrane　permeability　and　the　other　variables.　Second,　a　complete　new　platform　connecting　the　sensors　and　the　software　is　built,　in　order　to　enable　the　intelligent　detecting　system　to　handle　complex　algorithms.　Finally,　the　simulation　and　experimental　results　demonstrate　the　reliability　and　effectiveness　of　the　proposed　intelligent　detecting　system,　underlying　the　potential　of　this　system　for　the　online　membrane　permeability　for　detecting　membrane　fouling　of　MBR.