| 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...

A complete fault diagnosis system requires not only the identification of the various types of abrupt and incipient faults, but also robustness against signal blackout due to communication channel failure and sensor malfunctioning. The problem of identification of abrupt and incipient faults has been attempted in the previous work of the corresponding author. Hence, the design of decision makin...

Safe, reliable, and efficient operation of complex dynamical systems requires the ability to detect, isolate, and identify degradation in system components. Degradations are typically modeled as incipient faults, which are slow drifts in system parameters over time. This paper presents an efficient approach for the detection, isolation, and identification of incipient faults under uncertainty u...

This paper emphasizes on the use of fuzzy approach in dealing with the incipient fault conditions of power transformer. DGA (Dissolved Gas in Oil Analysis) cannot provide better fault diagnosis results when multiple faults are involved. The boundary values specified by the ratio methods are of limited concern .Considering the limitations of convergence of the conventional neural networks in the...

The gases generated in oil filled transformers can be used for qualitative determination of incipient faults. The Dissolved Gas Analysis has been widely used by utilities throughout the world as the primarily diagnostic tool for transformer maintenance. In this paper, various Artificial Intelligence Techniques that have been used by the researchers in the past have been reviewed, some conclusio...

This paper presents a novel method for performing automatic power quality diagnosis to identify the causes of short duration voltage disturbances such as voltage sags and swells. Such voltage disturbances can be caused by permanent or non permanent faults. A permanent fault causes permanent damage and power interruption to the customers whereas a non permanent fault can be categorized as either...

A new observer based fault detection and diagnosis scheme for predicting induction motors’ faults is proposed in this paper. Prediction of incipient faults, using different variants of Kalman filter and their relative performance are evaluated. Only soft faults are considered for this work. The data generation, filter convergence issues, hypothesis testing and residue estimates are addressed. S...

Model-based fault detection and isolation (FDI) is an approach with increasing attention in the academic and industrial fields, due to economical and safety related matters. In FDI, the discrepancies between system outputs and model outputs are called residuals, and are used to detect and isolate faults. This paper proposes a model-based architecture for fault detection and isolation based on f...

Detection and removal of incipient faults in power transformer winding is essential because minor faults may develop and lead to major faults and finally irretrievable damages occur. This research article presenta a new, simple and incipient fault detection technique, which is based on symmetrical component approach. Using this protection technique, it is possible to detect minor turn-to-turn f...

Fault tree analysis is widely used in industry in fault diagnosis. The diagnosis of incipient or ‘soft’ faults is considerably more difficult than of ‘hard’ faults, which is the situation considered normally. A detailed fault tree model reflecting signal variations over wide range is required for diagnosing such soft faults. This paper describes the investigation of a machine learning method fo...