False mode removing method based on density clustering

A density clustering and modal technology, which is applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the difficulty in determining the order of the model in the time domain method, the identification results are mixed with false modes, and the time-frequency domain method Noise interference and other problems, to achieve the effect of eliminating false mode problems, simplifying the calculation process, and high processing efficiency

Inactive Publication Date: 2018-01-19
HARBIN INST OF TECH
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Problems solved by technology

[0005] The present invention aims to solve the problem that the model order of the time-domain method in the existing time-varying modal parameter identification method is not easy to determine, there are false modes, and the time-frequency domain method has noise interference, which leads to the identification results being mixed To deal with the problem of false modals, a false modal elimination method based on density clustering is proposed

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  • False mode removing method based on density clustering
  • False mode removing method based on density clustering
  • False mode removing method based on density clustering

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specific Embodiment approach 1

[0027] Specific implementation mode one: combine figure 1 To illustrate this embodiment, a false mode elimination method based on density clustering in the present invention is specifically implemented according to the following steps:

[0028] Step 1. Use the time-varying modal parameter identification method to identify engineering structures (solar panels, antennas, and missile wings), and obtain preliminary identification results. The preliminary identification results include modal frequencies, modal damping ratios, and corresponding time vectors ;

[0029] When the subspace tracking algorithm in the time-varying modal parameter identification method is used, the modal frequency matrix obtained by identification is every two columns (the first column and the second column, the third column and the fourth column, the fifth column and the Six columns, and so on) as an order, extract the odd or even columns in the modal frequency matrix and the corresponding time vectors to...

specific Embodiment approach 2

[0037] Specific embodiment two: the difference between this embodiment and specific embodiment one is: given the parameters MinPts and eps required by the density clustering algorithm in the step three, the specific formula is:

[0038] MinPts and eps can be determined according to literature [1], or can be given directly according to experience: 0t ; N t is the length of the time vector in step 1, and the value range of eps is 0.0001≤eps≤0.1.

[0039] Literature [1] is: Li Zonglin, Luo Ke. Adaptive determination of parameters in DBSCAN algorithm [J]. Computer Engineering and Applications, 2016,52(3):70-73.

[0040] Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0041] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is that: given the parameters MinPts and eps required by the density clustering algorithm in the step 3, the density clustering algorithm is used for each subset D i Perform cluster analysis to obtain M clusters, each of which represents the first-order modal parameters; the specific process is:

[0042] If the number of data points in a data point eps radius circle is greater than or equal to MinPts, the data point is marked as a core point;

[0043] Judge the remaining data points after marking them as core points:

[0044] If the number of data points in the eps radius circle of a data point is less than MinPts, and there is a core point in the eps radius circle of the data point, the data point is marked as a boundary point;

[0045] If the number of data points in the eps radius circle of a data point is less than MinPts, and there is no core point in the eps radiu...

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Abstract

The invention provides a false mode removing method based on density clustering and relates to a false mode parameter removing method. The problems are solved that order determination of a time domainmethod model is not easy and a false mode exists in an existing time varying mode parameter identification method and noise interference exists in a time-frequency domain method so that the false mode can be mingled in an indemnification result. The method comprises the steps that 1, the time varying mode parameter identification method is adopted for identifying an engineering structure, and a primary identification result is obtained and comprises mode frequency, mode damping ratio and corresponding time vectors; 2, a matrix is averagely divided into N subsets according to data length; 3, adensity clustering algorithm is adopted for conducting clustering analysis on each subset Di to obtain M clusters; 4, the obtained M clusters are filtered, and the identification result of which thefalse mode is removed is obtained. The false mode removing method based on density clustering is applied to the technical field of structural dynamics.

Description

technical field [0001] The invention relates to a false modal parameter elimination method and belongs to the technical field of structural dynamics. Background technique [0002] Various forms of engineering structures are widely used in aerospace, architecture, civil engineering, machinery, automobiles, ships and other fields. In addition to static loads, engineering structures are often subjected to dynamic loads, so their dynamic characteristics have attracted more attention from researchers. Modal parameters are a common way to describe the dynamic characteristics of engineering structures. Generally speaking, modal parameters include modal frequency, modal damping ratio, etc. Determining the modal parameters of a structure by means of tests is called structural modal parameter identification, which has important application value in the engineering field. [0003] With the development of engineering structures in aerospace, machinery, construction and other fields to...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
Inventor 于开平周昊天赵锐赵婕白云鹤
Owner HARBIN INST OF TECH
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