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Vertical take-off and landing (VTOL) vehicles are becoming increasingly popular for real-world transport; but, as with any vehicle, guaranteeing safety is both extremely critical and highly challenging due to issues like rotor faults. Existing fault detection and isolation (FDI) techniques usually focus on multirotor systems or fixed wing systems, rather than the hybrid VTOLs. Since VTOLs have both rotors and ailerons, a fault in a rotor may be masked by the (correctly working) ailerons, making it much more difficult to detect faults. However, this masking only works when ailersons are used (e.g., during cruising), leaving the takeoff and landing vulnerable to crashes. This paper presents an online rotor fault detection and isolation (FDI) method for VTOLs. The approach uses pose analysis and aileron command data to quickly and accurately identify the faulty rotor and to compute the severity of the fault. Our method works for hard-to-detect fault scenarios, such as small-severity faults that are masked during cruise flight but not during vertical motion. We evaluated our technique in a SITL PX4 simulation of a modified Deltaquad QuadPlane. The results show that our FDI technique can quickly detect and isolate faults in real time (within 1s-2.5s) and achieve high isolation success rate (91.67%) across six rotors, and that it can estimate the severity of faults to within 2%. When applying a simple recovery process post-isolation, the system consistently achieved safe landing.