Assessment of power transformer conditions has become increasingly important in recent years. As an asset that represents one of the largest investments in a utility’s system, detection of incipient faults in power transformers is crucial. Dissolved gas-in-oil analysis (DGA) is a successful technique to detect these potential faults and it provides wealth of diagnostic information. This project...

Early detection and diagnosis of incipient faults is desirable for online condition assessment, product quality assurance, and improved operational efficiency of induction motors. In this paper, a speed-sensorless fault diagnosis system is developed for induction motors, using recurrent dynamic neural networks and multiresolution or Fourier-based signal processing for transient or quasi-steady-...

This paper presents DE/IFT, a new fault diagnosis engine which is based on the authors’ IFT algorithm for induction of fault trees. It learns from an examples database comprising sensor recordings, all of which have been classified as corresponding to either the normal behaviour of the system or to one or more fault states. The fault trees generated by IFT are translated into functions in the C...

Fault diagnosis is crucial for guaranteeing safe, reliable and efficient operation of modern engineering systems. These systems are typically hybrid. They combine continuous plant dynamics described by continuous-state variables and discrete switching behavior between several operating modes. This paper presents an integrated approach for online tracking and diagnosis of hybrid linear systems. ...

For the safety and continuity of service in industrial electrical systems, availability transformers is essential. this reason, it necessary to develop intelligent fault diagnosis techniques reduce repair maintenance costs. Recently, several methods have been developed that use artificial intelligence such as neural networks, support vector machines, hybrid techniques, etc., for faults power us...

This paper describes a case study of model-based diagnostics system development for an aircraft Auxiliary Power Unit (APU) turbine system. The off-line diagnostics algorithms described in the paper work with historical data of a flight cycle. The diagnostics algorithms use detailed turbine engine systems models and fault model knowledge available to an engine manufacturer. The developed algorit...

Bond graph models of an electrical transformer including the nonlinear saturation are presented. These models determine the relation between self and mutual inductances, and the leakage and magnetizing inductances of power transformers with two and three windings using the properties of a bond graph. The modelling and analysis using this methodology to three phase power transformers or transfor...

This brief paper presents a symbolic dynamicsbased method for detection of incipient faults in gas turbine engines. The underlying algorithms for fault detection and classification are built upon the recently reported work on symbolic dynamic filtering. In particular, Markov model-based analysis of quasi-stationary steady-state time series is extended to analysis of transient time series during...