Analysis of training techniques of ANN for classification of insulators in electrical power systems

Stefenon, Stéfano Frizzo; Branco, Nathielle Waldrigues; Nied, Ademir; Bertol, Douglas Wildgrube; Finardi, Erlon Cristian; Sartori, Andreza; Meyer, Luiz Henrique; Grebogi, Rafael Bartnik

doi:10.1049/iet-gtd.2019.1579

Cited by 36 publications

(11 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, the algorithm maintains a moving average of the element-wise squares of the parameter gradients. The ADAM optimization method calculates adaptive learning rates for each parameter [46]. The structure of the ANFIS is a combination of a fuzzy inference system and a neural network, some methods of cluster organization can be used for this model.…”

Section: Benchmarkingmentioning

confidence: 99%

Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Benchmarkingmentioning

confidence: 99%

Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…For the activation function, the interval sigmoid function (σ) [0, 1] was chosen (Equation ( 6)) and, for training, the backpropagation technique [58]. The neural network configuration parameters, such as the number of layers and activation function, were defined based on the study presented in [17]. In which several parameters are evaluated for an equivalent signal, and the best configuration for the specific application is presented.…”

Section: Model Activation and Training Functionmentioning

confidence: 99%

“…From the audible information, the operator then evaluates the condition of the component [17]. If the dependence and complications of demanding an operator with experience operating equipment are considered, it is justified to search for techniques that analyze the signal emitted through mathematical tools [18].…”

Section: Introductionmentioning

confidence: 99%

“…The problem of fault identification can be seen in two ways, through the classification of the fault or the failure's prediction. Considering a classification problem in [17], the ultrasound signal is evaluated from the comparison of the Fourier transform in relation to different insulators' conditions. Bruns [30] using the same database of this paper, obtained 98.8% accuracy in differentiating a dry and non-perforated insulator from a perforated and wet one.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Study of Multilayer Perceptron Networks Applied to Classification of Ceramic Insulators Using Ultrasound

et al. 2021

Self Cite

View full text Add to dashboard Cite

Interruptions in the supply of electricity cause numerous losses to consumers, whether residential or industrial and may result in fines being imposed on the regulatory agency’s concessionaire. In Brazil, the electrical transmission and distribution systems cover a large territorial area, and because they are usually outdoors, they are exposed to environmental variations. In this context, periodic inspections are carried out on the electrical networks, and ultrasound equipment is widely used, due to non-destructive analysis characteristics. Ultrasonic inspection allows the identification of defective insulators based on the signal interpreted by an operator. This task fundamentally depends on the operator’s experience in this interpretation. In this way, it is intended to test machine learning applications to interpret ultrasound signals obtained from electrical grid insulators, distribution, class 25 kV. Currently, research in the area uses several models of artificial intelligence for various types of evaluation. This paper studies Multilayer Perceptron networks’ application to the classification of the different conditions of ceramic insulators based on a restricted database of ultrasonic signals recorded in the laboratory.

show abstract

“…Technical sustainability is achieved if energy planning can meet the current and future energy needs of society [80]. This is possible if the power supply is reliable, efficient, and based on renewable energy [81] with locally available support services for the maintenance and execution of energy systems [82][83][84].…”

Section: Energy and The Dimensions Of Sustainabilitymentioning

confidence: 99%

Tools for Measuring Energy Sustainability: A Comparative Review

et al. 2020

Self Cite

View full text Add to dashboard Cite

This paper is intended to perform a comparative and qualitative review among eight tools to measure energy sustainability. Therefore, it was necessary to create a theoretical and conceptual framework based on four criterias of selection and six categories of comparison. In this work, the conceptual bases that supported the research and the methodology created to carry out the comparative review will be presented. This analysis was based on the intrinsic concepts of energy sustainability of each of the reviewed tools with a critical qualitative analysis. Some conclusions shown through the conceptual framework developed that it was possible to apply an innovative methodology to qualitatively compare different tools to measure sustainability. The importance of this reflects the difficulty of conceptualizing the subjectivity of sustainable development, as shown throughout the paper, where it is often not possible to obtain a measurable result since the measured phenomenon is too complex to reduce it to a numerical value.

show abstract

Analysis of training techniques of ANN for classification of insulators in electrical power systems

Cited by 36 publications

References 33 publications

Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting

Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting

A Study of Multilayer Perceptron Networks Applied to Classification of Ceramic Insulators Using Ultrasound

Tools for Measuring Energy Sustainability: A Comparative Review

Contact Info

Product

Resources

About