1. bookVolume 25 (2017): Issue 3 (September 2017)
Journal Details
License
Format
Journal
eISSN
2450-5781
First Published
30 Mar 2017
Publication timeframe
4 times per year
Languages
English
Open Access

Aggregation of Electric Current Consumption Features to Extract Maintenance KPIs

Published Online: 01 Aug 2017
Volume & Issue: Volume 25 (2017) - Issue 3 (September 2017)
Page range: 183 - 190
Received: 01 Oct 2016
Accepted: 01 Apr 2017
Journal Details
License
Format
Journal
eISSN
2450-5781
First Published
30 Mar 2017
Publication timeframe
4 times per year
Languages
English
Abstract

All electric powered machines offer the possibility of extracting information and calculating Key Performance Indicators (KPIs) from the electric current signal. Depending on the time window, sampling frequency and type of analysis, different indicators from the micro to macro level can be calculated for such aspects as maintenance, production, energy consumption etc. On the micro-level, the indicators are generally used for condition monitoring and diagnostics and are normally based on a short time window and a high sampling frequency. The macro indicators are normally based on a longer time window with a slower sampling frequency and are used as indicators for overall performance, cost or consumption. The indicators can be calculated directly from the current signal but can also be based on a combination of information from the current signal and operational data like rpm, position etc. One or several of those indicators can be used for prediction and prognostics of a machine’s future behavior. This paper uses this technique to calculate indicators for maintenance and energy optimization in electric powered machines and fleets of machines, especially machine tools.

Keywords

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