Fuzzy Fault Tree Analysis for Fault Diagnosis of Cannula Fault in Power Transformer

Tyagi, Saurabh; Pandey, D.; Kumar, Vinesh

doi:10.4236/am.2011.211188

Cited by 22 publications

(15 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ferdous, Khan, Veitch, & Amyotte (2009) have proposed a computer-aided fuzzy fault tree analysis method. Tyagi, Pandey, & Kumar (2011) have applied FFTA in reliability analysis of an electric power transformer. Recently, FFTA has been used to evaluate the probability of the fire and explosion in crude oil tanks (Wang, Zhang, & Chen, 2013) and Rajakarunakaran, Kumar, & Prabhu (2015) have applied FFTA for risk evaluation of an LPG refuelling station.…”

Section: Fuzzy Fault Treesmentioning

confidence: 99%

An overview of fault tree analysis and its application in model based dependability analysis

Kabir

2017

Expert Systems with Applications

320

134

View full text Add to dashboard Cite

Fault Tree Analysis (FTA) is a well-established and well-understood technique, widely used for dependability evaluation of a wide range of systems. Although many extensions of fault trees have been proposed, they suffer from a variety of shortcomings. In particular, even where software tool support exists, these analyses require a lot of manual effort. Over the past two decades, research has focused on simplifying dependability analysis by looking at how we can synthesise dependability information from system models automatically. This has led to the field of modelbased dependability analysis (MBDA). Different tools and techniques have been developed as part of MBDA to automate the generation of dependability analysis artefacts such as fault trees. Firstly, this paper reviews the standard fault tree with its limitations. Secondly, different extensions of standard fault trees are reviewed. Thirdly, this paper reviews a number of prominent MBDA techniques where fault trees are used as a means for system dependability analysis and provides an insight into their working mechanism, applicability, strengths and challenges. Finally, the future outlook for MBDA is outlined, which includes the prospect of developing expert and intelligent systems for dependability analysis of complex open systems under the conditions of uncertainty.

show abstract

Section: Fuzzy Fault Treesmentioning

confidence: 99%

An overview of fault tree analysis and its application in model based dependability analysis

Kabir

2017

Expert Systems with Applications

320

134

View full text Add to dashboard Cite

show abstract

“…This can be done in two steps. In the first step, the fuzzy possibility will be converted to failure probability (FP) using equation (22). In the second step, the failure rate can be obtained using the following equation.…”

Section: Fuzzy Operator For the And Gatementioning

confidence: 99%

“…So we have to define new importance measures that are suitable for the fuzzy set theory based methodology. Different methodologies (e.g., [13,50,22]) have already been proposed to quantify fuzzy importance measures.…”

Section: Importance Measuresmentioning

confidence: 99%

“…Ferdous et al [21] have proposed a computer-aided fuzzy fault tree analysis method. Tyagi et al [22] have applied FFTA in reliability analysis of an electric power transformer. Recently, FFTA has been used to evaluate the probability of the fire and explosion in crude oil tanks [23] and Rajakarunakaran et al [24] have applied FFTA for risk evaluation of an LPG refuelling station.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy temporal fault tree analysis of dynamic systems

Kabir

Walker

Papadopoulos

et al. 2016

International Journal of Approximate Reasoning

View full text Add to dashboard Cite

Fault tree analysis (FTA) is a powerful technique that is widely used for evaluating system safety and reliability. It can be used to assess the effects of combinations of failures on system behaviour but is unable to capture sequence dependent dynamic behaviour. A number of extensions to fault trees have been proposed to overcome this limitation. Pandora, one such extension, introduces temporal gates and temporal laws to allow dynamic analysis of temporal fault trees (TFTs). It can be easily integrated in model-based design and analysis techniques. The quantitative evaluation of failure probability in Pandora TFTs is performed using exact probabilistic data about component failures. However, exact data can often be difficult to obtain. In this paper, we propose a method that combines expert elicitation and fuzzy set theory with Pandora TFTs to enable dynamic analysis of complex systems with limited or absent exact quantitative data. This gives Pandora the ability to perform quantitative analysis under uncertainty, which increases further its potential utility in the emerging field of model-based design and dependability analysis. The method has been demonstrated by applying it to a fault tolerant fuel distribution system of a ship, and the results are compared with the results obtained by other existing techniques.

show abstract

“…Other metrics such as the failure probability of different paths in the tree can be determined based on failure probability distributions or failure rates taken from the literature. Main reliability analysis methods in FTA include direct calculation of structure importance coefficients [2,3] and fuzzy number fault trees [4][5][6]. A structure importance coefficient is the degree of importance of an event and relates to the component's location and importance in the physical system, not to the component's failure probability.…”

Section: Introductionmentioning

confidence: 99%

Fault tree reliability analysis of a micro-grid using Monte Carlo simulations

Shi

Bazzi

2015

2015 IEEE Power and Energy Conference at Illinois (PECI)

View full text Add to dashboard Cite

In this paper, the traditional Fault Tree Analysis (FTA) method combined with Monte Carlo simulations (MCSs) is introduced to a real micro-gird with significant clean energy penetration. Importance of different components in the microgrid is first found using the traditional FTA but cannot show a clear illustration of the system's reliability with respect to time. Using the proposed fault-tree-MCS (FT-MCS) method, a simulation program can be established with random sampling time. In this process, the contribution of each part to the whole system reliability can be clearly shown with varying time. A more accurate Mean Time to Failure (MTTF) can thus be achieved using the FT-MCS. FT-MCS is shown to combine the benefits of fault tree component hierarchy for fault propagation, as well as fault occurrence over time.

show abstract

Fuzzy Fault Tree Analysis for Fault Diagnosis of Cannula Fault in Power Transformer

Cited by 22 publications

References 14 publications

An overview of fault tree analysis and its application in model based dependability analysis

An overview of fault tree analysis and its application in model based dependability analysis

Fuzzy temporal fault tree analysis of dynamic systems

Fault tree reliability analysis of a micro-grid using Monte Carlo simulations

Contact Info

Product

Resources

About