IEEE Paper The Application of Electrical and Current Signature Analysis for DFIG Turbine and Powertrain Defects

Electrical and Current Signature Analysis, Electrical Reliability, EMPATH, EMPOWER, Energy, Environment, IIoT, Insulation Systems, Motor Diagnostics, Motor Theory, Reliability, Time To Failure Estimation TTFE, Uncategorized, Wind Power, , , , , , , ,

Abstract—Electrical and current signature analysis (ESA/MCSA) techniques provide a valuable method for detecting defects in wind turbine generators, particularly in doubly-fed induction generator (DFIG) systems.  This paper explores the application of ESA/MCSA in identifying defects such as wye-ring fractures, bearing wear, and gearbox faults.  We discuss the data acquisition process, spectral analysis methodologies, and case…

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Understanding the Energy Impact of Lubrication in Electric Machines

Electrical and Current Signature Analysis, Electrical Reliability, EMPATH, EMPOWER, Energy, Environment, Motor Diagnostics, Motor Management, Reliability, Time To Failure Estimation TTFE, Vibration, , , , , , ,

It is generally understood that lubrication must, by default, have an impact on equipment efficiency in terms of friction.  These losses, which are lumped into friction and windage in efficiency standards, such as IEEE Standard 112 Method B[1], which is one of the five types of electric machine losses: core losses (15-25%) and friction and…

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TheRamReview.com Machine Learning Article Part III Addendum – the code

2 CommentsArchive, Electrical Reliability, IIoT, Motor Diagnostics, Motor Management, Physical Asset Management, Reliability, Time To Failure Estimation TTFE, Uncategorized,

For trying out the method described Mathworks (https://mathworks.com) provides 30 day trials of their personal and business versions of the Matlab and Simulink systems.  The *.csv files created for this article series were developed within Matlab (Figure 2) using the code which follows. *Note: The code in this article is for demonstration purposes only and…

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