Extreme condition strain signal reliability assessment using empirical mode decomposition

被引：0

作者：

Nasir, N. N. M. ^{[1
]}

Abdullah, S. ^{[1
]}

Singh, S. S. K. ^{[1
]}

Haris, S. M. ^{[1
]}

机构：

[1] Univ Kebangsaan Malaysia, Fac Engn & Built Environm, Ctr Integrated Design Adv Mech Syst PRISMA, Ukm Bangi 43600, Selangor, Malaysia

来源：

PROCEEDINGS OF MECHANICAL ENGINEERING RESEARCH DAY 2018 (MERD) | 2018年

关键词：

Empirical mode decomposition; Gumbel distribution; strain data; HILBERT-HUANG TRANSFORM;

D O I：

暂无

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper studies the reliability of the decomposition strain signal data using the Gumbel distribution model. The fatigue signal is decomposed using the Hilbert-Huang transform method, Empirical Mode Decomposition, which extracted a set number of intrinsic mode functions that emphasized a different oscillation with different amplitudes and frequencies. Each decomposition signal is calculated with Gumbel distribution to identify the decomposition signal data characteristics. The decomposition process produced 9 IMFs and a residue showing the pattern of PDF and CDF for each IMF signal.

引用

页码：23 / 24

页数：2

共 3 条

[1] Kumar Raj, 2012, International Journal of Advanced Research in Artificial Intelligence, V1, P39
[2] Performance evaluation of the Hilbert-Huang transform for respiratory sound analysis and its application to continuous adventitious sound characterization
Lozano, Manuel
Fiz, Jose Antonio
Jane, Raimon
[J]. SIGNAL PROCESSING, 2016, 120 : 99 - 116
[3] An improved Hilbert-Huang transform and its application in vibration signal analysis
Peng, ZK
Tse, PW
Chu, FL
[J]. JOURNAL OF SOUND AND VIBRATION, 2005, 286 (1-2) : 187 - 205

← 1 →