A fault diagnosis method suitable for an electrical system of an unmanned aerial vehicle comprises the following steps of: establishing a fault diagnosis knowledge library and a fault symptom set of the electrical system of the unmanned aerial vehicle at first and then taking out a fault diagnosis rule completely containing all symptoms and all fault diagnosis decision tables; and outputting a fault reason with the highest diagnosis success frequency as a fault diagnosis prediction result, verifying the fault reason, and if the verification is passed, taking the fault reason as a final diagnosis result for positioning a fault mode to finish autonomous and quick dynamic reconfiguration, otherwise, reselecting the fault reason. The method greatly improves the reliability and fault-tolerant capability of the electrical system, thereby having relatively high engineering application values.