Dissolved Gas Analysis (DGA) is one of the most common techniques to detect the incipient faults in the oil-filled power transformers. In this paper, a new approach of DGA technique is proposed to overcome the conflict that takes place in the traditional interpretation techniques for transformer fault diagnosis. The new approach is based on the analysis of 386 dissolved gas samples data set tha...

This paper presents a nonlinear observer and prediction based analytical redundancy for a SteerBy-Wire (SBW) system. A Sliding Mode Observer was designed to estimate the vehicle steering angle by using the combined linear vehicle model, SBW system, and the yaw rate feedback. The estimated steering angle along with the current input was used to predict the steering angle at various prediction ho...

This paper presents an intelligent methodology for diagnosing incipient faults in mine hoist. As Probabilistic Causal-effect Model-Based diagnosis is an active branch of Artificial Intelligent, in this paper, the feasibility of using probabilistic causal-effect model is studied and it is applied in artificial fish-swarm algorithm (AFSA) to classify the faults of mine hoist. In probabilistic cau...

The performance of nonlinear fault detection schemes is hard to decide objectively, so Monte Carlo simulations are often used to get a subjective measure and relative performance for comparing different algorithms. There is a strong need for a constructive way of computing an analytical performance bound, similar to the Cramér-Rao lower bound for estimation. This paper provides such a result fo...

Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or even serious safety breaches, are often difficult to avoid. Fault detection in such systems is imperative to improve their reliability, productivity, safety and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current ...

This paper proposes a pattern recognition based differential spectral energy protection scheme for ac microgrids using a Fourier kernel based fast sparse time-frequency representation (SST or simply the sparse S-Transform). The average and differential current components are passed through a change detection filter, which senses the instant of fault inception and registers a change detection po...

Using the parity-space approach, a residual is formed by applying a projection to a batch of observed data and this is a well established approach to fault detection. Based on a stochastic state space model, the parity-space residual can be put into a stochastic framework where conventional hypothesis tests apply. In an on-line application, the batch of data corresponds to a sliding window and ...

Transformer is the main important equipment in electrical power system. Early stage detection of the transformer faults has great economic significance because it considered expensive equipment and it helps to maintain the continuous operation of the electrical power system. Transformer oil is used for two main purposes, one for insulating liquid and the other for cooling. Some physicalchemical...

In this note, fault detection techniques based on finite dimensional results are extended and applied to a class of infinite dimensional dynamical systems. This special class of systems assumes linear plant dynamics having an abrupt additive perturbation as the fault. This fault is assumed to be linear in the (unknown) constant (and possibly functional) parameters. An observer-based model estim...