Comparative analysis of Direct and Indirect Model Reference Adaptive Control by Extended Kalman Filter
Volume-3 | Issue-3
Smart Wires and Modular FACTS Controllers for Smart Grid Applications: A Review
Volume-3 | Issue-4
Integrated Renewable Energy Management System for Reduced Hydrogen Consumption using Fuel Cell
Volume-3 | Issue-1
Wireless Power Transfer Device Based on RF Energy Circuit and Transformer Coupling Procedure
Volume-3 | Issue-3
Artificial Intelligence based Business Process Automation for Enhanced Knowledge Management
Volume-3 | Issue-2
Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard
Volume-3 | Issue-2
Design of Effective Smart Communication System for Impaired People
Volume-2 | Issue-4
Automated Multimodal Fusion Technique for the Classification of Human Brain on Alzheimer’s Disorder
Volume-3 | Issue-3
Prediction of Energy Consumption by Ships at the port using Deep Learning
Volume-3 | Issue-2
A Novel Adaptive Fuzzy MPPT Algorithm under Changing Atmospheric Conditions
Volume-3 | Issue-4
Power Transfer Capability Recognition in Deregulated System under Line Outage Condition Using Power World Simulator
Volume-3 | Issue-4
Transformer Oil Diagnostic Tests Analysis using Statistical Correlation Technique
Volume-4 | Issue-3
Design of Inverter Voltage Mode Controller by Backstepping Technique for Nonlinear Power System Model
Volume-3 | Issue-4
Automated Multimodal Fusion Technique for the Classification of Human Brain on Alzheimer’s Disorder
Volume-3 | Issue-3
Performance Analysis of Multiple Pico Hydro Power Generation
Volume-2 | Issue-2
Energy Efficient Data Mining Approach for Estimating the Diabetes
Volume-3 | Issue-2
Wireless Power Transfer Device Based on RF Energy Circuit and Transformer Coupling Procedure
Volume-3 | Issue-3
Prediction of Energy Consumption by Ships at the port using Deep Learning
Volume-3 | Issue-2
A Novel Adaptive Fuzzy MPPT Algorithm under Changing Atmospheric Conditions
Volume-3 | Issue-4
Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard
Volume-3 | Issue-2
Volume - 5 | Issue - 4 | december 2023
Published
02 January, 2024
Testing and experimental processes in industries and research institutes play important roles in understanding systems and developing accurate models. Experimental uncertainties in variables introduce deviations (errors) in measured data, which can stem from various factors, one of which is the presence of outliers. Outliers impact the accuracy of measurements significantly during analysis and lead to inaccurate conclusions. Outliers can be due to environmental changes, drift in measurements, etc., during assessment. Identifying outliers and eliminating them is a crucial step during data analysis. This research aims to investigate real-time outlier detection and removal using LabVIEW. Peirce Criteria are assessed for detecting and eliminating outliers from displacement data obtained through LVDT sensors. The research demonstrates that Peirce’s criteria are particularly well suited for small datasets. By employing LabVIEW and Peirce criteria, this study presents a practical approach to accurately detect and remove outliers in real time to enhance the reliability of data analysis.
KeywordsData collection Outliers CNC LabVIEW LVDT
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