Search results for "ANFIS"

showing 2 items of 2 documents

Data-based modeling of vehicle crash using adaptive neural-fuzzy inference system

2014

Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research. For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different…

Adaptive neuro fuzzy inference systemEngineeringVehicle crash reconstructionAdaptive neural-fuzzy inference system (ANFIS)-based prediction; Time-series analysis; Vehicle crash reconstruction; Vehicle dynamics modeling; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineeringbusiness.industryControl engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionKinematicsCollisionDisplacement (vector)Computer Science ApplicationsVehicle dynamicsAccelerationAdaptive neural-fuzzy inference system (ANFIS)-based predictionControl and Systems EngineeringTime-series analysisTime seriesElectrical and Electronic EngineeringbusinessReliability (statistics)Vehicle dynamics modeling
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Broken rotor bars detection via Park's vector approach based on ANFIS

2014

Many attempts have been made on fault diagnosis of induction motors based on frequency and time domain analysis of stator current. In this paper, first the Park's vector transformation and frequency analysis for fault detection of induction motors are introduced. Then a smart approach using Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed. This approach uses the time domain features derived from the Park's vector transformation of stator current. By the proposed method, a partial break including 5 mm crack on a bar, one broken bar and two broken bars using experimental data are investigated. It will be shown that features derived from Park's vector compared to features obtained fro…

EngineeringAdaptive neuro fuzzy inference systemRotor (electric)business.industryStatorANFIS; broken rotor bars; fault diagnosis; Park's transformation; Electrical and Electronic Engineering; Control and Systems EngineeringCoordinate vectorfault diagnosisFault (power engineering)Fault detection and isolationlaw.inventionlawControl theoryControl and Systems EngineeringTime domainElectrical and Electronic EngineeringbusinessANFISbroken rotor barsPark's transformationInduction motor
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