Data Science - MotorDocAI

How to Evaluate an Electric Motor with Voltage Variance and Unbalance

By MotorDoc October 1, 2022Data Science, Electric Machine, Power, Power Quality, Time to Failure Estimation, Uncategorized

Voltage variation and unbalance are defined separately within NEMA MG-1. However, in real-life applications these conditions exist at the same time. In this paper we will discuss combined voltage variations…

Review of Power Quality Data in a Traditional Grid Environment Part 2

By MotorDoc August 30, 2022Alternative Energy, Artificial Intelligence, Data Science, Internet of Things, Power Quality

Figure 1: First service at a manufacturing facility. Secondary of Utility Transformer (PCC) in an area with heavy wind/solar/nuclear Figure 2: Second service at same facility as Figure 1. Secondary…

Review of Power Quality Data in a Traditional Grid Environment Part 1

By MotorDoc August 28, 2022Alternative Energy, Data Science, Electric Machine, Internet of Things, Power Quality, Time to Failure Estimation, Uncategorized

Figure 1: Part of Data Analytics Project The condition of incoming power has a direct impact on the electrical reliability of a plant. As the conditions surround electrical equipment they…

Interactive Low and High Frequency FFT ESA/MCSA Datasets

By MotorDoc May 23, 2022Artificial Intelligence, Data Science, Electric Machine, Internet of Things, Machine Learning, Remaining Useful Life, Time to Failure Estimation, Uncategorized

Interactive ESA/MCSA spectra at the end of this post. These interactive charts go along with the following https://theramreview.com articles: https://theramreview.com/part-1-whats-behind-mcsa-and-esa-anyways/ https://theramreview.com/part-2-whats-behind-mcsa-and-esa-anyways/ https://theramreview.com/part-3-whats-behind-mcsa-and-esa-anyways/ More can be found in the associated code…

A Quick Demo of MCSA Raw Data in Python Part 3

By MotorDoc May 18, 2022Artificial Intelligence, Data Science, Electric Machine, Internet of Things, Machine Learning, Remaining Useful Life, Time to Failure Estimation, Uncategorized1 Comment

In Parts 1 and 2 we used 10kHz sampling data in current to take a look at an electric motor. In this part we will look at high and low…

A Quick Demo of MCSA Using Raw Data in Python – Part 2

By MotorDoc May 11, 2022Artificial Intelligence, Data Science, Electric Machine, Internet of Things, Machine Learning, Remaining Useful Life, Time to Failure Estimation

The data behind the second part of the series on https://theramreview.com. Note: this is for demonstrating the concepts behind MCSA/ESA, vibration and other similar spectral data analysis and should not…

A Quick Demo of MCSA Using Raw Data in Python – Part 1

By MotorDoc May 4, 2022Artificial Intelligence, Data Science, Electric Machine, Internet of Things, Machine Learning

Done in Jupyter Notebook to demonstrate some of the concepts behind MCSA/ESA/Vibration and any other data of this type. This will be very basic - DO NOT USE for product…

Challenge Data: What did the motor studies really say?

By MotorDoc April 29, 2022Data Science, Electric Machine, Remaining Useful Life, Time to Failure Estimation

Taking data at face value can result in bad decisions for your physical asset management programs. In this white paper (circa 2017) MotorDoc LLC evaluated the electric motor studies on…

Machine Learning for Electric Machine Prognostics IEEE Paper

By MotorDoc April 26, 2022Data Science, Internet of Things, Machine Learning, Remaining Useful Life, Time to Failure Estimation, Uncategorized