NDLI: Insulation condition assessment of high-voltage rotating machines using hybrid techniques

Content Provider	IET Digital Library
Author	Gopinath, Singaram Sathiyasekar, Kumarasamy Padmanaban, Sanjeevikumar Chokkalingam, Bharatiraja
Abstract	The enduring life span of the machine insulation will be decided based on degradation level in motor and generator stator windings. The non-destructive diagnostic tools like dielectric loss and capacitance test and partial discharge (PD) analysis, recognized to access the deterioration in the insulation system of rotating machines. The experiments reveal various characteristic parameters such as leakage current, dielectric dissipation factor, the capacitance value, and PD magnitude. The integrity of the rotating machine can be find out by analyzing these parameters. This research study shows the hybrid method for prediction of insulation condition in the stator winding by utilizing the artificial neural network (ANN) with gravitational search algorithm in comparison with ANN and ANN–genetic algorithm. The advent of expert systems ensures the quality assurance and service life assessment of the high-voltage assets. It offers a predictive maintenance solution to personnel dealt with power utilities thereby increasing the uptime, reliability, and productivity, which in turn reducing the operating costs, downtime and unplanned outages. For testing and predicting the insulation status, several 11 kV machines are considered. The predicted results using hybrid techniques extend a close agreement with reference to the data obtained from the experiments performed. The proposed method indicate the competent and trustworthy, by the presented test results.
Starting Page	171
Ending Page	180
Page Count	10
ISSN	17518687
Volume Number	13
e-ISSN	17518695
Issue Number	Issue 2, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/13/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.6500
Journal	IET Generation, Transmission & Distribution
Publisher Date	2018-09-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	A.C. Machine ANN Artificial Neural Network Capacitance Test Capacitance Value Characteristic Parameter Condition Monitoring D.C. Machines Degradation Level Dielectric Breakdown And Discharges Dielectric Dissipation Factor Dielectric Loss Electric Machine Analysis Computing Electric Machines Expert System Generator Stator Windings Genetic Algorithm Gravitational Search Algorithm High-voltage Assets High-voltage Rotating Machine Hybrid Technique Insulation Condition Assessment Insulation Status Insulation Testing Leakage Current Life Span Machine Insulation Machine Testing Maintenance Engineering Motor Windings Neural Computing Technique Neural Nets Nondestructive Diagnostic Tool Optimisation Technique Partial Discharge Analysis Partial Discharges PD Magnitude Power Engineering Computing Power Transformer Insulation Predictive Maintenance Solution Quality Assurance Reliability Rotating Machine Service Life Assessment Stators Transformer And Reactors Voltage 11.0 KV
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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