Aiming at solving the problems of machine-learning in fault diagnosis,a diagnosis ap- proach is proposed based on hidden Markov model(HMM)and support vector machine(SVM). HMM usually describes intra-class measure well and is good at dealing with continuous dynamic signals.SVM expresses inter-class difference effectively and has perfect classify ability.This ap- proach is built on the merit of HMM and SVM.Then,the experiment is made in the transmission system of a helicopter.With the features extracted from vibration signals in gearbox,this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox’s faults.The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples. Aiming at solving the problems of machine-learning in fault diagnosis, a diagnosis ap-proach is proposed based on hidden Markov model (HMM) and support vector machine (SVM). HMM are described intra-class measure well and is good at dealing with continuous dynamic signals.SVM expresses inter-class difference effectively and has perfect classify ability.This ap-proach is built on the merit of HMM and SVM.Then, the experiment is made in the transmission system of a helicopter .With the features extracted from vibration signals in gearbox, this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox’s faults.The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples .