A New Fault Diagnosis Method Based on Attributes Weighted Neutrosophic Set

Gou, Linfeng; Zhong, Yu

doi:10.1109/access.2019.2936494

Cited by 5 publications

(3 citation statements)

References 46 publications

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“…It is, therefore, fuzzy information. Since the controller requires a precise control signal at its input [13,14], it is necessary to transform this fuzzy information into specific information, which is called defuzzification [15]. There are several methods for calculating the representative value of an output set, and the main ones of which are:…”

Section: D-defuzzificationmentioning

confidence: 99%

A New Fuzzy Controlled Antenna Network Proposal for Small Satellite Applications

Hamrouni¹

2022

Computers, Materials &Amp; Continua

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This research contributes to small satellite system development based on electromagnetic modeling and an integrated meta-materials antenna networks design for multimedia transmission contents. It includes an adaptive nonsingular mode tracking control design for small satellites systems using fuzzy waveless antenna networks. By analyzing and modeling based on electromagnetic methods, propagation properties of guided waves from metallic structures with simple or complex forms charge partially or entirely by anisotropic materials such as metamaterials. We propose a system control rule to omit uncertainties, including the inevitable approximation errors resulting from the finite number of fuzzy signal power value basis functions in antenna networks. Moreover, both the stability and the tracking performance of the closed-loop robotic system are experimentally validated. The research lies within the scope of the improvement of speed, effectiveness, and precision of numerical methods applied to electro-magnetic modeling with complex structures, essentially rectangular metallic waveguides filled with isotropic or anisotropic metamaterials. Three axes of our research are presented: waveguides, filters, and antennas. The proposed controller does not require prior knowledge about the dynamics of the fuzzy system controller for antenna networks or the offline learning phase. In addition, this work contributes to solving the problem of non-visibility stations to ensure data transmission in wireless networks. The proposed solution maximizes inter-connection by using a fuzzy controlled antenna network, and the novelty guarantees nonlimited interconnection in wireless networks compared to traditional methods.

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Section: D-defuzzificationmentioning

confidence: 99%

A New Fuzzy Controlled Antenna Network Proposal for Small Satellite Applications

Hamrouni¹

2022

Computers, Materials &Amp; Continua

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“…The literature [39] introduced the theory of interval neutrosophic set and single-valued neutrosophic set; The literature [40] proposed the theory of simplified neutrosophic set; Literature [41] proposed a single-valued neutrosophic set SVNS method with a weighted correlation coefficient to realize fault diagnosis. However, the correlation coefficient does not comprehensively consider the single-valued neutrosophic set and ideal neutrosophic set data under various faults [42][43][44][45][46], only the maximum value between them is considered [47][48][49]. This does not completely deal with the uncertain and inaccurate information in the fault information, and may lead to an incorrect diagnosis.…”

Section: Research Statusmentioning

confidence: 99%

Single-Valued Neutrosophic Set Correlation Coefficient and Its Application in Fault Diagnosis

et al. 2020

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With the increasing automation of mechanical equipment, fault diagnosis becomes more and more important. However, the factors that cause mechanical failures are becoming more and more complex, and the uncertainty and coupling between the factors are getting higher and higher. In order to solve the given problem, this paper proposes a single-valued neutrosophic set ISVNS algorithm for processing of uncertain and inaccurate information in fault diagnosis, which generates neutrosophic set by triangular fuzzy number and introduces the formula of the improved weighted correlation coefficient. Since both the single-valued neutrosophic set data and the ideal neutrosophic set data are considered, the proposed method solves the fault diagnosis problem more effectively. Finally, experiments show that the algorithm can significantly improve the accuracy degree of fault diagnosis, and can better satisfy the diagnostic requirements in practice.

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“…As a new kind of fuzzy set, neutrosophic set [43,44] have been used in many fields, such as decision-making [45][46][47][48], data analysis [49,50], fault diagnosis [51], the shortest path problem [52]. There is also a lot of progress in the related theoretical research of neutrosophic set.…”

Section: Introductionmentioning

confidence: 99%

A New Multi-Sensor Fusion Target Recognition Method Based on Complementarity Analysis and Neutrosophic Set

Gong

Wang

et al. 2020

Symmetry

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To improve the efficiency, accuracy, and intelligence of target detection and recognition, multi-sensor information fusion technology has broad application prospects in many aspects. Compared with single sensor, multi-sensor data contains more target information and effective fusion of multi-source information can improve the accuracy of target recognition. However, the recognition capabilities of different sensors are different during target recognition, and the complementarity between sensors needs to be analyzed during information fusion. This paper proposes a multi-sensor fusion recognition method based on complementarity analysis and neutrosophic set. The proposed method mainly has two parts: complementarity analysis and data fusion. Complementarity analysis applies the trained multi-sensor to extract the features of the verification set into the sensor, and obtain the recognition result of the verification set. Based on recognition result, the multi-sensor complementarity vector is obtained. Then the sensor output the recognition probability and the complementarity vector are used to generate multiple neutrosophic sets. Next, the generated neutrosophic sets are merged within the group through the simplified neutrosophic weighted average (SNWA) operator. Finally, the neutrosophic set is converted into crisp number, and the maximum value is the recognition result. The practicality and effectiveness of the proposed method in this paper are demonstrated through examples.

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A New Fault Diagnosis Method Based on Attributes Weighted Neutrosophic Set

Cited by 5 publications

References 46 publications

A New Fuzzy Controlled Antenna Network Proposal for Small Satellite Applications

A New Fuzzy Controlled Antenna Network Proposal for Small Satellite Applications

Single-Valued Neutrosophic Set Correlation Coefficient and Its Application in Fault Diagnosis

A New Multi-Sensor Fusion Target Recognition Method Based on Complementarity Analysis and Neutrosophic Set

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