Twin support vector machine(TWSVM)is a new development of support vector machine(SVM)algo-rithm.It has the smaller computation scale and the stronger ability to cope with unbalanced problems.In this pa-per,TWSVM is introduced into aircraft engine gas path fault diagnosis.The generalization capacity of Gauss ker-nel function usually used in TWSVM is relatively weak.So a mixed kel function is used to improve performance to ensure that the TWSVM algorithm can better balance a strong generalization ability and a good leing ability. Experimental results prove that the cross validation training accuracy of TWSVM using the mixed kel function averagely increases 2%.Grid search is usually applied in parameter optimization of TWSVM,but it heavily de-pends on experience.Therefore,the hybrid particle swarm algorithm is introduced.It can intelligently and rapidly find the global optimum.Experiments prove that its training accuracy is better than that of the classical particle swarm algorithm by 5%.