A sensor fault diagnosis system with support vector regression(SVR) for a given turbofan engine was designed.It can detect sensor fault and recover fault-sensor signal.On the basis of training the SVR model with the trial run data of one turbofan engine

the system was simulated in the MATLAB through three different kinds of sensor fault

i.e.offset fault

impact fault and drift fault.The results show that the system has many advantages including high level of precision and good real-time performance.So SVR is an effective method for sensor fault diagnosis.