PurposeThe　combination　of　improved　PSO　(IPSO)　algorithm　and　artificial　neural　network　(ANN)　model　for　intelligent　monitoring　of　the　bearing　performance　of　the　hydrostatic　turntable.Design/methodology/approachThis　paper　proposes　an　artificial　neural　network　model　based　on　IPSO　algorithm　for　intelligent　monitoring　of　hydrostatic　turntables.FindingsThe　theoretical　model　proposed　in　this　paper　improves　the　accuracy　of　the　working　performance　of　the　static　pressure　turntable　and　provides　a　new　direction　for　intelligent　monitoring　of　the　static　pressure　turntable.　Therefore,　the　theoretical　research　in　this　paper　is　novel.Originality/valueTheoretical　novelties:　an　ANN　model　based　on　the　IPSO　algorithm　is　designed　to　monitor　the　load-bearing　performance　of　a　static　pressure　turntable　intelligently;　this　study　show　that　the　convergence　accuracy　and　convergence　speed　of　the　IPSO-NN　model　have　been　improved　by　52.55%　and　10%,　respectively,　compared　to　traditional　training　models;　and　the　proposed　model　could　be　used　to　solve　the　multidimensional　nonlinear　problem　in　the　intelligent　monitoring　of　hydrostatic　turntables.Peer　reviewThe　peer　review　history　for　this　article　is　available　at:　https://publons.com/publon/10.1108/ILT-03-2024-0081/