Classification of Low Frequency Signals Emitted by Power Transformers Using Sensors and Machine Learning Methods
This paper proposes a method of automatically detecting and classifying low frequency noise generated by power transformers using sensors and dedicated machine learning algorithms. The method applies the frequency spectra of sound pressure levels generated during operation by transformers in a real...
Main Authors: | Daniel Jancarczyk, Marcin Bernaś, Tomasz Boczar |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-11-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/19/22/4909 |
Similar Items
-
Distribution Transformer Parameters Detection Based on Low-Frequency Noise, Machine Learning Methods, and Evolutionary Algorithm
by: Daniel Jancarczyk, et al.
Published: (2020-08-01) -
Low-Frequency Noise Evaluation on a Commercial Magnetoimpedance Sensor at Submillihertz Frequencies for Space Magnetic Field Detection
by: Tao Wang, et al.
Published: (2019-11-01) -
Design of Low-frequency Impact Frequency Measuring Circuit with Resistance Strain Force Sensor
by: LIU Jian-zhao, et al.
Published: (2012-10-01) -
Development and Validation of a Masking System for Mitigation of Low-Frequency Audible Noise from Electrical Substations
by: Rogerio Regazzi, et al.
Published: (2021-08-01) -
On the Control of Low-Frequency Audible Noise from Electrical Substations: A Case Study
by: Edoardo Alessio Piana, et al.
Published: (2020-01-01)