Dual ant colony operational modal analysis parameter estimation method

被引:4
|
作者
Sitarz, Piotr [1 ]
Powalka, Bartosz [1 ]
机构
[1] West Pomeranian Univ Technol, Fac Mech Engn, Piastow 19, PL-70310 Szczecin, Poland
关键词
Operational modal analysis; Modal parameters estimation; Ant colony optimisation; Modal analysis identification; Artificial intelligence; STOCHASTIC SUBSPACE IDENTIFICATION; SHAPE NORMALIZATION; ALGORITHM; BRIDGE;
D O I
10.1016/j.ymssp.2017.04.046
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:231 / 267
页数:37
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