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This paper presents some techniques for fault diagnosis in aerospace and automotive systems. A diagnosis technique is an algorithm to detect and isolate fault components in a dynamic process, such as sensor biases, actuator malfunctions, leaks and equipment deterioration. Fault diagnosis is the first step to achieve fault tolerance, but the redundancy has to be included in the system. This redundancy can be either by hardware or software. In situations in which it is not possible to use hardware redundancy only the analytical redundancy approach can be used to design fault diagnosis systems. Methods based on analytical redundancy need no extra hardware, since they are based on mathematical models of the system.

Eigenstructure techniques allow to detect and isolate faulty components in a dynamic process, such as sensor biases, actuator malfunctions, changes in dynamic parameters due to leaks and deterioration. Fault detection is the first step to achieve fault tolerance, but for this the redundancy has to be included in the system. This redundancy can be either by hardware or by software. In situations in which it is not possible to use hardware redundancy only the software redundancy can be used. Therefore using eigenstructure techniques, for the fault detection and isolation, the tests can be done through the angle between the residue vector direction and the fault direction vector. By this way, we can reduce false alarm and the alarm loss rates due to the noise and changes in system parameters.