Scalable fault diagnosis is necessary for constructing fault tolerance mechanisms in large massively parallel multiprocessor systems. The diagnosis algorithm must operate efficiently even if the system consists of several thousand processors. In this paper we introduce an event-driven, distributed system-level diagnosis algorithm. It uses a small number of messages and is based on a general dia...

This paper presents an applicable procedure for Fault Detection and Diagnosis (FDD) in a realistic nonlinear six degree-of-freedom unmanned aerial vehicle (UAV) model. The work has been developed based on the Matlab/Simulink environment of the NASA Generic Transport Model (GTM) UAV under the NASA Aviation Safety Program (AvSP). By introducing the partial loss fault in aircraft actuators into th...

In this paper, an approach for fault detection and isolation filter design based on the reconstruction of the fault modes is presented. Input reconstruction and a very closely related concept, the system inversion is addressed to the fault detection and isolation problem. Moreover, the basic concept of that field, the fault detectability, output separability, and the fault detection and isolati...

The paper focuses on the application of neural network techniques in fault detection and diagnosis. The objective of this paper is to detect and diagnose the faults to a continuous stirred tank reactor (CSTR). Fault detection is performed by using the error signals, where when error signal is zero or nearly zero, the system is in normal condition, and when the fault occurs, error signals should...

Telecommunication companies have received a great deal of research attention, which have many advantages such as low cost, higher qualification, simple installation and maintenance, and high reliability. However, the using of technical maintenance approaches in Telecommunication companies could improve system reliability and users' satisfaction from Asymmetric digital subscriber line (ADSL) ser...

Because of the product variety and structure complexity of the engineering machinery, it was difficult to meet the requirements of fault detection and maintenance for the traditional diagnosis technologies. In order to improve the diagnostic level, the intelligent control technology of neural network and its application in engineering machinery fault diagnosis were studied. The basic concepts o...

Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work. Every fourth cycle of the instantaneous current signal, the mean is computed and carried into the next cycle to discover nonlinearities in the signal. A fault detection task is complete...

We here analyze the parity space approach to fault detection and isolation in a stochastic setting. Using a state space model with both deterministic and stochastic unmeasurable inputs we show a formal relationship between the Kalman filter and the parity space. Based on a statistical fault detection and diagnosis algorithm, the probability for incorrect diagnosis is computed explicitly, given ...

| Detection of incipient (slowly developing) faults is crucial in automated maintenance problems where early detection of worn equipment is required. In this note, a general framework for model-based fault detection and diagnosis of a class of incipient faults is developed. The changes in the system dynamics due to the fault are modeled as nonlinear functions of the state and input variables, w...