A spherical square root unscented Kalman filter algorithm was investigated to effectively track the health parameters of the gas path components of turbofan engine with the gradual and rapid faults. In this algorithm

a spherical simplex sampling was exploited to decrease the computational complexity. And the square root of measurement residuals covariance matrix was used instead of variance matrix during recursive arithmetic to improve the calculation efficiency and numerical stability of algorithm. Then

the simulation of a turbofan engine was conducted by extended Kalman filter

unscented Kalman filter and spherical square root unscented Kalman filter algorithms. The results show that filter time consumption by spherical square root unscented Kalman filter algorithm is cut by about 50%

with accurate estimation of health parameters in gradual and rapid faults

thus adapting to the parameters estimation and fault diagnosis of gas path components of turbofan engine.