MR Damper Modeling using Gaussian and Generalized Bell of ANFIS Algorithm

This paper proposes a bifilar coil numerical analysis for asphalt induction heating. The software utilized in this research was ANSYS Electronics Desktop and ANSYS Transient Analysis. The asphalt has been modified by adding a certain amount of iron flakes. The asphalt containing magnetic substances is modeled and subjected to an electromagnetic field, thus a comparative temperature distribution between bifilar and monofilar coils is achieved. The bifilar coil has a slight increase in output than the monofilar coil under conditions of equal current and frequency. However, bifilar coil provides less power consumption and self-capacitance compared to the counterpart.

Section: Introductionmentioning

confidence: 99%

Numerical Analysis of Bifilar Coil Geometry on Induction Heating Performance for Self-healing Asphalt

Budi¹,

Ubaidillah²,

Prabowo³

et al. 2023

“…According to the results, SIFLC is superior to Proportional, Integral, and Derivative (PID) controllers. Choirunisa et al 18) modeled an M.R. Damper utilizing an Adaptive Neuro-Fuzzy Inference System with Gaussian and generalized bell membership functions.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of SPV Power Plant Based On Real-Time Data

Laxmi Kant Sagar,

D Bhagwan Das

2023

To guarantee maximum performance and reliability of solar plants, the probability of occurrence of improper operations should be very low. For that, a fault diagnosis expert system can be one of the solutions that can figure out the improper operations very precisely and suggest corrective actions. In this study, we will use a hybrid approach for fault detection, i.e., a knowledgebased and data-driven approach, i.e., fuzzy logic and machine learning. A fuzzy model will sense the real-time data and classify it into good or faulty. The fuzzy simulation model, thus, developed, will be used to generate a large amount of training data required for machine learning methods. Further clustering techniques are applied to the available database to determine which improper operation (fault) has the highest probability of occurrence.

“…The results show that SIFLC is the best technique, in comparison with Proportional, Integral, and Derivative (PID), Fuzzy Logic Controller (FLC). Choirunisa et al 16) modeled an MR Damper with an Adaptive Neuro-Fuzzy Inference System using Gaussian and generalized bell membership functions. The results show Gaussian function is more accurate than the generalized bell membership function.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Expert System for Determining State of Solar Photo Voltaic Power Plant Based on Real-Time Data

Sagar¹,

Das²

2022

This paper presents an implementation of fuzzy expert system for determining state of a solar plant in real-time, based on reliability, economy, and possible improper operations of the system components, using streaming real-time data of the solar plant. The reliability depends on the state of battery charge and the available backup time. The economy depends on the purchase of power from the utility supply. Improper operation of the system could be due to faulty or maloperation of a component that could degrade the performance of plant. The proposed fuzzy expert system was developed for a 40 kWp Hybrid Solar power plant installed at Dayalbagh Educational Institute. The system determines the state of the plant in terms of reliability, economy, and possibility of improper operations under real-time conditions. In addition to reliability and economy being the key parameters, much focus has been placed on improper operations and corrective measures have been suggested.