In order to solve the problems caused by the inherent complex nonlinearity and the limitation of traditional linear modeling technology in engine fault diagnosis, the Equilibrium manifold model is introduced in this paper, The equilibrium manifold model can describe the actual operating state of the engine more accurately, and capture the higher-order nonlinear characteristics that are ignored by the traditional linear model.Furthermore, a dual-channel sensor fault diagnosis and isolation approach is proposed, which integrates the nonlinear engine model with the Cubature Kalman filter. Simulations conducted that, compared to traditional Kalman filter-based methods, this approach not only reduces the demands on data storage and computational resources but also achieves accurate sensor fault diagnosis. Crucially, it effectively separates engine gas path faults from sensor faults, thus eliminating the potential interference of gas path faults on sensor fault diagnosis and isolation outcomes.