Failures of the aircraft control system sensors can cause both deterioration of stability and controllability characteristics and the inability of safe automatic control. It is necessary to detect and isolate such failures to determine the time and place of their occurrence in order to disable failed sensors or to diagnose them subsequently for reconfiguration during the flight. The direct use of traditional parametric approaches for sensors health monitoring by using their mathematical models is impossible due to the lack of data about the true information input signals received by their sensitive elements. This leads to the necessity of solving the problem of modeling the aircraft flight dynamics with a high level of uncertainties, which makes it difficult to utilize the functional control methods and necessitate the use of excessive sensor hardware redundancy. Well-known nonparametric methods either require a priori knowledge base, preliminary training or long-term tuning on a large volume of real flight data or have low selective sensitivity for reliable detection of failed sensors. In this work, the original nonparametric criterion for detecting and isolating sensors failures is derived. Its sensitivity is analyzed by using a complete nonlinear mathematical model of aircraft flight dynamics with a regular flight control system. The theoretical value and the criterion sensitivity coefficients are determined. The formula for the automatic evaluation of the float criterion threshold value is given. A high convergence of the results with theoretical ones is shown. This makes it possible to use the obtained criterion not only for the instant detection and isolation of sensors failures, but also for preliminary diagnostics of their quantitative characteristics.


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