With　the　goal　to　realize　the　real-time　measurement　of　key　water　quality　parameters　in　wastewater　treatment　process,　this　paper　constructs　a　novel　soft-measurement　model　based　on　the　brain-like　modular　neural　network　(BLMNN).　First,　based　on　the　mutation　information　and　expert　knowledge,　the　easy-to-measure　variables　which　have　strong　correlations　to　the　effluent　water　quality　parameters　are　chosen　as　the　model　inputs.　Then,　simulating　the　modular　structure　of　brain　cortex,　the　effluent　water　parameters　are　measured　by　different　sub-models,　improving　both　the　modeling　accuracy　and　modeling　speed.　The　simulation　results　based　on　real　data　verify　the　accuracy　and　effectiveness　of　the　proposed　method.　Copyright　©　2019　Acta　Automatica　Sinica.　All　rights　reserved.