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Proceedings ArticleDOI

Fuzzy logic based impulse test analysis

28 Jun 2005-pp 38-43
TL;DR: A fusion of hard and soft computing is proposed for the impulse analysis problem, where the number of simulations can become unbounded to cater to all types of faults and lead to automation of impulse analysis function.
Abstract: A fusion of hard and soft computing is proposed for the impulse analysis problem. An optimal hardware platform for the data acquisition and a minimal set of simulations form the hard computing element. As the number of simulations can become unbounded to cater to all types of faults, a soft computing approach based on fuzzy logic is proposed. This can lead to automation of impulse analysis function.
Citations
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Proceedings ArticleDOI
01 Dec 2010
TL;DR: In this article, the location of partial discharge in transformer windings is identified using least deviation methods, and the simulation studies are carried out on lumped layer winding to prove the feasibility of the methods.
Abstract: Partial discharge location is important for transformer maintenance and repair. In this paper, the location of PD is identified using least deviation methods. The simulation studies are carried out on lumped layer winding to prove the feasibility of the methods and also validated with 22kV transformer windings. The efficacy of the methods is also checked with standard PD calibrator and multiple discharges.

Cites methods from "Fuzzy logic based impulse test anal..."

  • ...In this section, the principle of nearest neighbourhood rule [ 7 ] is utilized for PD location....

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References
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Journal ArticleDOI
TL;DR: An additive fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy.
Abstract: An additive fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. An additive fuzzy system approximates the function by covering its graph with fuzzy patches in the input-output state space and averaging patches that overlap. The fuzzy system computes a conditional expectation E|Y|X| if we view the fuzzy sets as random sets. Each fuzzy rule defines a fuzzy patch and connects commonsense knowledge with state-space geometry. Neural or statistical clustering systems can approximate the unknown fuzzy patches from training data. These adaptive fuzzy systems approximate a function at two levels. At the local level the neural system approximates and tunes the fuzzy rules. At the global level the rules or patches approximate the function. >

1,282 citations

Journal ArticleDOI
TL;DR: In this article, the transfer function of a transformer winding is deconvoluted in the frequency domain from the digitally recorded neutral current and high voltage applied during impulse tests, and the integrity of the winding insulation is determined by comparing the transferred function obtained at full and reduced test voltage.
Abstract: The transfer function of a transformer winding is deconvoluted in the frequency domain from the digitally recorded neutral current and high voltage applied during impulse tests. The integrity of the winding insulation is determined by comparing the transfer function obtained at full and reduced test voltage. Differences between the transfer function plots reveal local breakdowns in the winding that can be dissociated from partial discharges. Thus the method permits unambiguous acceptance or rejection if the transformer and, since the transfer function is theoretically immune to changes in the applied impulse, also allows evaluation of the chopped-impulse test. Some 100 windings of large HV power transformers have been tested using the transfer function method, which on several occasions has revealed transformer faults as well a test setup problems that would have been missed or misinterpreted by conventional techniques. >

162 citations

Journal ArticleDOI
01 May 2002
TL;DR: An overview of applications in which the fusion of soft computing and hard computing has provided innovative solutions for challenging real-world problems is presented.
Abstract: Soft computing (SC) is an emerging collection of methodologies which aims to exploit tolerance for imprecision, uncertainty, and partial truth to achieve robustness, tractability, and low total cost. It differs from conventional hard computing (HC) in the sense that, unlike hard computing, it is strongly based on intuition or subjectivity. Therefore, soft computing provides an attractive opportunity to represent the ambiguity in human thinking with real life uncertainty. Fuzzy logic (FL), neural networks (NN), and genetic algorithms (GA) are the core methodologies of soft computing. However, FL, NN, and GA should not be viewed as competing with each other, but synergistic and complementary instead. Considering the number of available journal and conference papers on various combinations of these three methods, it is easy to conclude that the fusion of individual soft computing methodologies has already been advantageous in numerous applications. On the other hand, hard computing solutions are usually more straightforward to analyze; their behavior and stability are more predictable; and, the computational burden of algorithms is typically either low or moderate. These characteristics. are particularly important in real-time applications. Thus, it is natural to see SC and HC as potentially complementary methodologies. Novel combinations of different methods are needed when developing high-performance, cost-effective, and safe products for the demanding global market. We present an overview of applications in which the fusion of soft computing and hard computing has provided innovative solutions for challenging real-world problems. A carefully selected list of references is considered with evaluative discussions and conclusions.

60 citations

Proceedings ArticleDOI
19 Oct 2003
TL;DR: In this article, it is shown that the nearest neighbourhood rule based on a clustering approach provides a good framework for fault location. But it is not shown how to estimate the location of the fault based on the resonant frequencies of the winding current.
Abstract: It is possible to estimate the location of the fault based on a study of the resonant frequencies of the winding current. It is shown that the nearest neighbourhood rule based on a clustering approach provides a good framework for fault location. Additional signal acquisition in the form of the tank current can considerably simplify the identification of a fault to ground. Experimental investigations are performed in order to identify and locate breakdown in windings.

7 citations

Proceedings ArticleDOI
20 Dec 2004
TL;DR: In this paper, an objective formulation of the impulse testing procedure is proposed based on models for winding response as well as fault models, and experimental validation of the fault models for breakdown and partial discharge is provided.
Abstract: An objective formulation of the impulse testing procedure is proposed based on models for winding response as well as fault models. Experimental validation of the fault models for breakdown and partial discharge (PD) is provided. A new adaptive filtering approach is proposed for analysis during impulse tests. The procedure is validated with experimental investigation on a 10 section lumped parameter network.

4 citations