Agent oriented intelligent fault diagnosis system using evidence theory

Luo, He; Yang, Shanlin; Hu, Xiaojian; Hu, Xiaoxuan

doi:10.1016/j.eswa.2011.08.104

Cited by 43 publications

(24 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Regarding Pedestrian and Vehicle Tracking, in this work, we use Optical flow algorithm [8] to detect coming traffics. Given the two consecutive frames, we find corner points with corner detector [15] and these features are matched by the Optical flow algorithm, which assumes that important features are detected in both frames.…”

Section: Introductionmentioning

confidence: 99%

Multi-agent System for Tracking and Classification of Moving Objects

Sánchez

Rodrı́guez

Prieta

et al. 2015

Distributed Computing and Artificial Intelligence, 12th International Conference

View full text Add to dashboard Cite

Abstract. In the past, computational barriers have limited the complexity of video and image processing applications but recently, faster computers have enabled researchers to consider more complex algorithms which can deal successfully with vehicle and pedestrian detection technologies. However, much of the work only pays attention to the accuracy of the final results provided by the systems, leaving aside the computational efficiency. Therefore, this paper describes a system using a paradigm of multi-agent system capable of regulating itself dynamically taking into account certain parameters pertaining to detection, tracking and classification, to reduce the computational burden as low as possible at all times without this in any way compromise the reliability of the result.

show abstract

Section: Introductionmentioning

confidence: 99%

Multi-agent System for Tracking and Classification of Moving Objects

Sánchez

Rodrı́guez

Prieta

et al. 2015

Distributed Computing and Artificial Intelligence, 12th International Conference

View full text Add to dashboard Cite

show abstract

“…The final step is to choose appropriate combination rules to fuse these BBAs and make a diagnosis decision according to the fused results. Besides Dempster's rule, some improved combination rules have also been given to handle conflicting diagnosis evidence 7,11 .…”

Section: Introductionmentioning

confidence: 99%

“…DST can robustly deal with incomplete data and allows the representation of both imprecision and uncertainty 2 . It provides such as rotating machinery [3][4] , power electronics [5][6] , control system [7][8] , sensor network 9 and so on.…”

Section: Introductionmentioning

confidence: 99%

Interval-valued Evidence Updating with Reliability and Sensitivity Analysis for Fault Diagnosis

Xu¹,

Zhang²,

Xu³

et al. 2016

IJCIS

View full text Add to dashboard Cite

Information fusion methods based on Dempster-Shafer evidence theory (DST) have been widely used in fault diagnosis. In DST-based methods, the monitoring information collected from sensors is modeled as multiple pieces of diagnosis evidence in the form of basic belief assignment (BBA), and Dempster's rule is then used to combine these BBAs to obtain the fused BBA for diagnosis decision making. However, the belief structure with crisp singlevalued belief degrees in BBA may be too coarse to truthfully represent detailed fault information. Moreover, Dempster's rule only uses a static combination process, which is unsuitable for dynamically fusing information collected at different time steps. In order to address these issues, the paper proposes a dynamic diagnosis method based on interval-valued evidential updating. First of all, the diagnosis evidence is constructed as an interval-valued belief structure (IBS), which provides a more informative scheme than BBA to model fault information. Secondly, the proposed evidential updating strategy can generate updated IBS as global diagnosis evidence by updating the previous evidence with the new incoming evidence recursively. Thirdly, the reliability and sensitivity indices are designed to evaluate and compare the performance of the proposed updating strategy with other commonly used strategies. Finally, the effectiveness of the proposed evidential updating strategy is demonstrated through some typical fault experiments of a machine rotor.

show abstract

“…To date, a large number of valuable approaches have been proposed for dealing with fault analysis issues, such as fuzzy theories [4,5], expert system [6], wavelet analysis [7,8], data fusion [9,10], and neural network [11,12]. Particularly, fuzzy approach is most successfully applied in fault diagnosis because it is in the simplest and most used form [13].…”

Section: Introductionmentioning

confidence: 99%

A New Similarity Measure of Generalized Trapezoidal Fuzzy Numbers and Its Application on Rotor Fault Diagnosis

Zuo

Wang

Yin

2013

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Fault diagnosis technology plays a vital role in the variety of critical engineering applications. Fuzzy approach is widely employed to cope with decision-making problems because it is in the simplest and most used form. This paper proposed a new similarity measure of generalized trapezoidal fuzzy numbers used for fault diagnosis. The presented similarity measure combines concepts of the geometric distance, the center of gravity point, the perimeter, and the area of the generalized trapezoidal fuzzy numbers for calculating the degree of similarity between generalized trapezoidal fuzzy numbers. This method is proposed to deal with both standardized and nonstandardized generalized trapezoidal fuzzy numbers. Some properties of the proposed similarity measure have been proved, and 12 sets of generalized fuzzy numbers have been used to compare the calculation results of the proposed similarity measures with the existing similarity measures. Comparison results indicate that the proposed similarity measure can overcome the drawbacks of existing similarity measures. Finally, a fault diagnosis experiment is carried out in laboratory based on multifunctional flexible rotor experiment bench. Experimental results demonstrate that the proposed similarity measure is more effective than other methods in terms of rotor fault diagnosis.

show abstract

Agent oriented intelligent fault diagnosis system using evidence theory

Cited by 43 publications

References 16 publications

Multi-agent System for Tracking and Classification of Moving Objects

Multi-agent System for Tracking and Classification of Moving Objects

Interval-valued Evidence Updating with Reliability and Sensitivity Analysis for Fault Diagnosis

A New Similarity Measure of Generalized Trapezoidal Fuzzy Numbers and Its Application on Rotor Fault Diagnosis

Contact Info

Product

Resources

About