Abstract - Use of efficient signal processing tools (SPTs) to extract proper indices for fault detection in induction motors (IMs) is the essential part of any fault recognition procedure. The Part1 of the two parts paper focuses on Fourier-based techniques including fast Fourier transform and short time Fourier transform. In this paper, all utilized SPTs which have been employed for fault fete...

This paper presents a novel approach for fault type estimation in power systems. The Fault type estimation is the first step to estimate instantaneous voltage, voltage sag magnitude and duration in a three-phase system at fault duration. The approach is based on time-domain state estimation where redundant measurements are available. The current based model allows a linear mapping between the m...

A model based fault detection and diagnosis technique for DC motor is proposed in this paper. Fault detection using Kalman filter and its different variants are compared. Only incipient faults are considered for the study. The Kalman Filter iterations and all the related computations required for fault detection and fault confirmation are presented. A second order linear state space model of DC...

Arc fault is one of the primary reasons that cause electrical fire. When arc fault occurs in power supply line, the current can not make protective equipments act and the arc fault can not be found and cut off easily, so electrical fire comes into being. In the comparisons, the current signal is used for the detection physical parameter and the wavelet transform is used to study the arc fault d...

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...

This research study focuses on the discussion regarding the development of fault detection in gas metering station using an Artificial Neural Network (ANN). The proposed model of fault detection applies ANN approach in order to provide a good detection method for billing purpose. However, one of the main problems faced by gas metering system is the undiagnosed faulty condition of measurement. M...

induction motor bearing is one of the key parts of the machine and its analysis and interpretation are important for fault detection. in the present work vibration signal has been taken for the classification i.e. bearing is healthy (h) or defective (d). for this purpose, clustering based classification of bearing vibration data has been carried out using principal component analysis (pca) and ...

In this paper, fault detection problems for linear uncertain systems are studied. Instead of designing fault detection systems from the viewpoint of increasing the system robustness against unknown inputs and the sensitivity to the faults, an approach is proposed, which allows us to design fault detection systems in such a way that the missed detection rate is minimized for a given false alarm ...

The paper presents a mathematical base modeling combined to Modified-Winding -Function-Approach (MWFA) for eccentricity fault detection of a round-rotor synchronous machine. For this aim, a 6-pole machine is considered, and the machine inductances are computed by MWFA in healthy and also under eccentricity fault. A numerical discrete-time method has been proposed to machine modeling in voltage-...

This paper presents the fault detection algorithm using regression method for plural indoor units faults of multi-heat pump system under heating mode. To develop the fault detection algorithm, experiment was performed under no fault mode. Total 65 experimental data were obtained from the experiment. Regression models for five heat exchangers which including one outdoor unit and four indoor unit...