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

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…

Evaluating Wind Turbines With Electrical Signature Analysis

Electrical Signature Analysis (ESA) is the method of using the electric machine magnetic field as the transducer as measured through voltage and current.  The method was originally developed by Oak Ridge National Labs in the late 1980s for the expressed purpose of fault detection of gear and bearing wear in driven equipment in addition to…

Evaluation of the Impact of Harmonics on Electric Machine Reliability

Power, magnetic and ground harmonics have a negative impact on the reliability of your electric motors both electrically and mechanically.  We often focus just on the power harmonics when reviewing information on power quality, but rarely view the self-generated electric machine harmonics and the harmonic content present in grounds and neutrals.  Over the past several…

Update Energy Savings through the Application of Neutral Harmonic Filter: A Case Study

It is established that neutral and ground harmonic content will load transformers and systems. Prior work has been limited as to the direct relationship of this additional loading on power consumption for a facility. Over the past 24 months applied research has been performed on the measured impact of neutral and ground harmonics and energy…

Reliability Engineering, Data Science, Machine Learning and Bias

When dealing with statistical analysis and probabilities its often the missing information that can be an issue.  This can result in bias when working in areas such as reliability, data science and machine learning that result in incorrect solutions.  We’ve seen that in such things as the percentage of type of motor failures, faulty IoT…

EMPATH Continuous Monitoring Special Applications for Energy Analysis

The EMPATH™ family of Electrical Signature and Motor Current Signature Analysis (ESA/MCSA) systems go well beyond analyzing electric motors, generators and wind turbines.  It provides prognostic and time to failure estimation (TTFE) capabilities for AC/DC electric motors, synchronous machines, servo motors, machine tools, generators – including utility scale, and transformers.  Not only will it identify…

Concepts in Reliability Keeping it Simple and Random Thoughts

As I just mentioned to a friend – I seem to be waxing philosophical this past weekend as I complete reading “Wizard: The Life and Times of Nikola Tesla, Biography of a Genius,” by Marc J Seifer. I would not have tripped over this and several other excellent texts had I not started returning to…

Code for TheRamReview.com Part VII Electric Motor Raw Data Machine Learning

Following is the code used to develop the script bringing the details developed in Parts I-VI together for classification and RUL/TTFE outputs in the Part VII article: (article to be posted by September 19, 2021. *Note: The code in this article is for demonstration purposes only and is not meant for real-world applications of this…