Given　the　problems　in　intelligent　diagnosis　methods　for　automotive　transmission,　it　is　difficult　to　obtain　the　fault　signal　features　and　a　large　enough　sample　size　to　study.　To　solve　these　problems,　a　method　integrating　order　tracking,　cepstrum,　support　vector　machine　(SVM)　and　extremal　curve　is　proposed　in　this　paper.　Order　tracking　and　cepstrum　are　combined　for　processing　the　non-stationary　vibration　signal　emitted　by　automotive　transmission.　As　conventional　intelligent　methods　cannot　produce　true　results　for　insufficient　samples,　a　method　that　combines　SVM　and　extremal　curve　is　presented.　Input　the　vector　acquired　from　the　feature　signals　into　the　SVM　model　for　the　first　detection,　and　then　do　the　second　detection　by　means　of　extremal　curve　which　in　turn　can　enrich　the　training　samples　in　SVM　model　thus　making　the　SVM　model　be　more　perfect.　Analytical　description　and　experimental　studies　are　presented　for　the　methods　of　signal　processing　and　quality　detection.　The　experimental　results　demonstrate　the　effectiveness　and　practicability　of　the　proposed　method.　©　2014　IFSA　Publishing,　S.　L.