Monitoring electrical systems data-network equipment by means of Fuzzy and Paraconsistent Annotated Logic

Côrtes, Hyghor Miranda; Santos, Paulo E.; Filho, João Inácio da Silva

doi:10.1016/j.eswa.2021.115865

Cited by 5 publications

(6 citation statements)

References 18 publications

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“…However, there are other non-classical logics that were created to be used in conditions in which classical logic, with its binary principles, proves to be inoperative. Currently, paraconsistent logic (PL), which is based on opposing the principle of non-contradiction (which is one of the basic principles of classical logic), has stood out in applications of its algorithms in various areas of knowledge [6,7].…”

Section: Of 28mentioning

confidence: 99%

“…The lPANCell is considered completely trained when µ E(k+1) = 1 and µ ctr(k+1) = 0. If the pattern applied to the cell input is unitary (µ 1 = 1), then the output will converge to µ E(k+1) = 1 with a monotonic variation, whose number of iterations (n) for the output to reach this maximum value will depend on the l F value [4,7,13].…”

Section: Paraconsistent Artificial Neural Cell Of Learning (Lpancell)mentioning

confidence: 99%

“…Therefore, the simplified algorithm with a learning factor set in l F = 1, for the learning of any value between 0 and 1, is shown in the Algorithm 1 below [6,7,13]. µ E(k+1) = {µ1−(λ2)lF}+1 2 6.…”

Section: Paraconsistent Artificial Neural Cell Of Learning (Lpancell)mentioning

confidence: 99%

“…Figure 4 shows the values obtained in the form of graphs [4,7,13]. When the lF value is other than 1, the output will not converge to the input pattern value if the u1 pattern is different from 1.…”

Section: Paraconsistent Artificial Neural Cell Of Learning (Lpancell)mentioning

confidence: 99%

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Process of Learning from Demonstration with Paraconsistent Artificial Neural Cells for Application in Linear Cartesian Robots

et al. 2023

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Paraconsistent Annotated Logic (PAL) is a type of non-classical logic based on concepts that allow, under certain conditions, for one to accept contradictions without invalidating conclusions. The Paraconsistent Artificial Neural Cell of Learning (lPANCell) algorithm was created from PAL-based equations. With its procedures for learning discrete patterns being represented by values contained in the closed interval between 0 and 1, the lPANCell algorithm presents responses similar to those of nonlinear dynamical systems. In this work, several tests were carried out to validate the operation of the lPANCell algorithm in a learning from demonstration (LfD) framework applied to a linear Cartesian robot (gantry robot), which was moving rectangular metallic workpieces. For the LfD process used in the teaching of trajectories in the x and y axes of the linear Cartesian robot, a Paraconsistent Artificial Neural Network (lPANnet) was built, which was composed of eight lPANCells. The results showed that lPANnet has dynamic properties with a robustness to disturbances, both in the learning process by demonstration, as well as in the imitation process. Based on this work, paraconsistent artificial neural networks of a greater complexity, which are composed of lPANCells, can be formed. This study will provide a strong contribution to research regarding learning from demonstration frameworks being applied in robotics.

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Section: Of 28mentioning

confidence: 99%

Section: Paraconsistent Artificial Neural Cell Of Learning (Lpancell)mentioning

confidence: 99%

Section: Paraconsistent Artificial Neural Cell Of Learning (Lpancell)mentioning

confidence: 99%

Section: Paraconsistent Artificial Neural Cell Of Learning (Lpancell)mentioning

confidence: 99%

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Process of Learning from Demonstration with Paraconsistent Artificial Neural Cells for Application in Linear Cartesian Robots

et al. 2023

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“…This can analyze bearings vibration in real time and using patterns learned by the algorithm itself to compare and provide diagnostics in real time. Therefore, the objective of this work is to show an algorithmic structure based on Paraconsistent Logic (PL) working as an expert system (ESvbrPAL2v) capable of continuously monitoring the vibration of bearings to warn about risks of breaking an industrial machine (Da Costa & Abe, 2000) (Côrtes, et al,2022.…”

Section: Introductionmentioning

confidence: 99%

Paraconsistent annotated logic applied to industry assets condition monitoring and failure prevention based on vibration signatures

Correa

Machado

Filho

et al. 2022

RSD

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In this study, we introduced an expert system (ESvbrPAL2v), responsible for monitoring assets based on vibration signature analysis through a set of algorithms based on the Paraconsistent Annotated Logic – PAL. Being a non-classical logic, the main feature of the PAL is to support contradictory inputs in its foundation. It is therefore suitable for building algorithmic models capable of performing out appropriate treatment for complex signals, such as those coming from vibration. The ESvbrPAL2v was built on an ATMega2560 microcontroller, where vibration signals were captured from the mechanical structures of the machines by sensors and, after receiving special treatment through the Discrete Fourier Transform (DFT), then properly modeled to paraconsistent logic signals and vibration patterns. Using the PAL fundamentals, vibration signature patterns were built for possible and known vibration issues stored in ESvbrPAL2v and continuously compared through configurations composed by a network of paraconsistent algorithms that detects anomalies and generate signals that will report on the current risk status of the machine in real time. The tests to confirm the efficiency of ESvbrPAL2v were performed in analyses initially carried out on small prototypes and, after the initial adjustments, tests were carried out on bearings of a group of medium-power motor generators built specifically for this study. The results are shown at the end of this study and have a high index of signature identification and risk of failure detection. These results justifies the method used and future applications considering that ESvbrPAL2v is still in its first version.

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A comprehensive review on paraconsistent annotated evidential logic: Algorithms, Applications, and Perspectives

de Carvalho Junior,

Justo,

de Oliveira

et al. 2024

Engineering Applications of Artificial Intelligence

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Monitoring electrical systems data-network equipment by means of Fuzzy and Paraconsistent Annotated Logic

Cited by 5 publications

References 18 publications

Process of Learning from Demonstration with Paraconsistent Artificial Neural Cells for Application in Linear Cartesian Robots

Process of Learning from Demonstration with Paraconsistent Artificial Neural Cells for Application in Linear Cartesian Robots

Paraconsistent annotated logic applied to industry assets condition monitoring and failure prevention based on vibration signatures

A comprehensive review on paraconsistent annotated evidential logic: Algorithms, Applications, and Perspectives

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