Three-dimensional mechanical models are used to evaluate the performance of different fault growth criteria in predicting successive growth of three échelon thrust faults similar to the segments of the Puente Hills thrust system of the Los Angeles basin, California. Four sequential Boundary Element Method models explore the growth of successive échelon faults within the system by simulating sna...

Dissolved gas analysis (DGA) is one of the most useful techniques to detect the incipient faults of power transformer. However, the identification of the faulted location by the traditional method is not always an easy task due to the variability of gas data and operational natures. In this paper, a novel cerebellar model articulation controller (CMAC) neural network (NN) method is presented fo...

Considering the problem to diagnose incipient faults in nonlinear analog circuits, a novel approach based on fractional correlation is proposed and the application of the subband Volterra series is used in this paper. Firstly, the subband Volterra series is calculated from the input and output sequences of the circuit under test (CUT). Then the fractional correlation functions between the fault...

The gases generated in oil filled transformer can be used for determination of incipient faults. Dissolved gas analysis (DGA) of transformer oil has been one of the most power full methods to detect the faults. The various methods such as liquid chromatography, acoustic analysis, and transformer function techniques are require some experience to interpret observations. The researchers have used...

This paper presents a diagnosis scheme based on a linear matrix inequality LMI algorithm for incipient faults in a nonlinear system class with unknown input disturbances. First, the nonlinear system is transformed into two subsystems, one of which is unrelated to the disturbances. Second, for the subsystem that is free from disturbances, a Luenberger observer is constructed; a sliding mode obse...

Diagnostics of incipient faults for analog circuits is very important, yet very difficult. Traditionally, the soft faults can only be diagnosed under the occurrence of large variation of component parameters. In this paper, a novel approach for diagnosing incipient faults in analog circuits is proposed. First, a statistical property feature vector composed of range, mean, standard deviation, sk...

This paper proposes the application of Adaptive Neuro-Fuzzy Inference System to improve the diagnosis accuracy of dissolved gas analysis for classification of different types of incipient faults in oil immersed power transformers. The proposed method integrated the capabilities of neural network to the robustness of fuzzy logic system for the effectiveness to be embedded in the network structur...

The switched reluctance motor (SRM) has inherently high level of fault tolerance. However despite of its high robustness and reliability it can face windings and bearings faults. The faults can cause costly downtimes in industrial environment, or they can bring about more severe consequences in safety critical applications. Therefore the detection of the faults in their incipient phase and the ...

This paper presents a new approach to the design of a robust observer-based fault detection scheme for diagnosing incipient faults, called H∞ robust fault detection observer (RFDO). It takes into account the robustness of the fault detection observer against disturbances and sensitivity to faults simultaneously. The approach has originated from the robust H∞ estimator which minimizes the effect...