Fourier, Wavelet, and Hilbert-Huang Transforms for Studying Electrical Users in the Time and Frequency Domain

被引:18
|
作者
Puliafito, Vito [1 ]
Vergura, Silvano [2 ]
Carpentieri, Mario [2 ]
机构
[1] Univ Messina, Dept Engn, I-98166 Messina, Italy
[2] Polytech Univ Bari, Dept Elect & Informat Engn, Via E Orabona 4, I-70125 Bari, Italy
关键词
non-stationary signal; time-frequency analysis; power quality; wavelet; Hilbert-Huang transform; EMPIRICAL MODE DECOMPOSITION; POWER; COMPRESSION; FORMS;
D O I
10.3390/en10020188
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The analysis of electrical signals is a pressing requirement for the optimal design of power distribution. In this context, this paper illustrates how to use a variety of numerical tools, such as the Fourier, wavelet, and Hilbert-Huang transforms, to obtain information relating to the active and reactive power absorbed by different types of users. In particular, the Fourier spectrum gives the most important frequency components of the electrical signals, and the wavelet analysis highlights the non-stationarity of those frequency contributions, whereas the Hilbert-Huang transform, by means of the Empirical Mode Decomposition, provides a more complete spectrum of frequencies.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] The fast Fourier and Hilbert-Huang transforms: A comparison
    Donnelly, Denis
    [J]. 2006 IMACS: MULTICONFERENCE ON COMPUTATIONAL ENGINEERING IN SYSTEMS APPLICATIONS, VOLS 1 AND 2, 2006, : 84 - 88
  • [2] A Time-Frequency Analysis of Electrical Users by means of Fourier and Wavelet Transforms
    Vergura, Silvano
    Carpentieri, Mario
    Puliafito, Vito
    [J]. 2016 IEEE 16TH INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING (EEEIC), 2016,
  • [3] Trend detection and data mining via wavelet and Hilbert-Huang transforms
    Yasar, Murat
    Ray, Asok
    [J]. 2008 AMERICAN CONTROL CONFERENCE, VOLS 1-12, 2008, : 4292 - +
  • [4] Time, wavelet and Hilbert-Huang domain analysis of signals from ultrasonic based NDT
    Barmada, S.
    Raugi, M.
    Musolino, A.
    Tucci, M.
    Turcu, F.
    [J]. COMPUTATIONAL METHODS AND APPLIED COMPUTING, 2008, : 300 - +
  • [5] Hilbert-Huang Transforms for fault detection and degradation assessment in electrical motors
    Rigamonti, M.
    Rantala, S.
    [J]. SAFETY AND RELIABILITY: METHODOLOGY AND APPLICATIONS, 2015, : 939 - 944
  • [6] A comparative study of modal parameter identification based on wavelet and Hilbert-Huang transforms
    Yan, BF
    Miyamoto, A
    [J]. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2006, 21 (01) : 9 - 23
  • [7] Cutting force response in milling of Inconel: Analysis by wavelet and Hilbert-Huang Transforms
    Litak, Grzegorz
    Kecik, Krzysztof
    Rusinek, Rafal
    [J]. LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES, 2013, 10 (01) : 133 - 140
  • [8] The application of Hilbert-Huang transforms to meteorological datasets
    Duffy, Dean G.
    [J]. HILBERT-HUANG TRANSFORM AND ITS APPLICATIONS, 2005, 5 : 129 - 147
  • [9] The application of Hilbert-Huang transforms to meteorological datasets
    Duffy, DG
    [J]. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2004, 21 (04) : 599 - 611
  • [10] Hilbert-Huang transform and wavelet analysis of time history signal
    石春香
    罗奇峰
    [J]. Earthquake Science, 2003, (04) : 422 - 429