The large aircraft engine fault diagnosis in the problem of accurate. General components with different, large aircraft engine structure and its complex, the work in higher frequency failure, failure appear in a relatively short time, and it is difficult to retrieval, leading to establish the connection between the fault occurs when the connection breaks. The traditional fault detection method ...

This paper propose a diagnosis architecture that integrates consistency based diagnosis with induced time series classifiers, trying to combine the advantages of both methods. Consistency based diagnosis allows fault detection and localization without prior knowledge of the device fault modes. Machine learning techniques are able to induce time series classifiers that may be used to identify fa...

The improvement of the detection and diagnosis capability for the unanticipated fault is a tendency in the research and application of fault diagnosis. In this paper, some notions and the basic principles for the unanticipated fault detection and diagnosis are given. A general process model applied to the diagnosis for the unanticipated fault is designed, by adopting a three-layer progressive s...

A conceptual design of a model-based fault detection and diagnosis system is developed for the Space Shuttle main engine. The design approach consists of process modeling, residual generation, and fault detection and diagnosis. The engine is modeled using a discrete time, quasilinear state-space representation. Model parameters are determined by identification. Residuals generated from the mode...

Fault diagnosis is a central aspect of network fault management. Since faults are unavoidable in communication systems, their quick detection and isolation is essential for the robustness, reliability, and accessibility of a system. In large and complex communication networks, automating fault diagnosis is critical. Traditionally, fault localization has been performed manually by experts but, a...

This paper presents a quantitative review of early detection and estimation of fault for wind turbine system. The model-based technique is proposed to provide an assessment of all possible faults for renewable energy sources. The augmented observer is applied to estimate the real physical data of the system sensor faults and states simultaneously. The fault detection and diagnosis is designed t...

Different test sequence selection methods, namely, the Dmethod, C-method, W-method, T-method, U-method, Uvmethod and the Wp-method, are reviewed and analysed for their fault detection capabilities. We show that the C-method and the Uv-method do not provide complete fault coverage. These seven methods are formally analysed for their fault diagnosis capabilities under single fault assumption. Amo...

Quality control of textile products is an important stage in textile industries. To this end, the conventional method in fault detection is human inspection. In the present work, Wavelet transform was applied on images of simple circular knitted fabrics to diagnose five regular defects. The results showed that the method applied was accurate and fast in addition to being capable of determining ...

The objective of ESPRIT-project 6731 FTMPS [1] is to develop techniques and system software to integrate Fault Tolerance in Massively Parallel Systems [2] . This covers the whole range from error detection, over fault-diagnosis and fault isolation to system and application recovery. Important is the research for applicability in massively parallel systems as well as the development of system so...