Both　calibration　method　and　static　decoupling　algorithm　were　employed　to　analyze　wheel　force　transducer　(WFT).　Firstly,　the　calibration　procedure　and　extraction　of　sample　data　were　presented　in　detail　based　on　the　self-developed　hydraulic　bench.　Then,　three　decoupling　methods　were　utilized　respectively　to　quantify　the　coupling　effects.　The　main　findings　are　as　the　follows:　the　linearity　of　each　main　calibration　channel　is　notable;　the　calculated　rate　of　static　coupling　of　the　self-developed　WFT　is　equal　to　the　same-type　foreign　product;　the　least　square　support　vector　regression　(LS-SVR)　algorithm　owns　the　characteristics　of　high　regression　precision,　outstanding　generalization　and　excellent　algorithm　stability;　the　method　to　modify　the　algorithm　of　the　standard　OLS-RBF　NN　(orthogonal　least　square　radial-basis-function　neural　network)　improves　the　regression　performance　significantly.