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Work modal parameter identification method and device based on self-iteration principal component extraction

A technology of parameter identification and working mode, which is applied in the direction of measuring devices, electrical digital data processing, special data processing applications, etc., can solve the problems of high time and space complexity, and is not suitable for embedding into portable devices

Active Publication Date: 2017-10-20
HUAQIAO UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, based on the traditional batch PCA algorithm, the linear transformation matrix and pivot are obtained through singular value decomposition (SVD) or eigenvalue decomposition (EVD), which has the disadvantages of high time and space complexity and is not suitable for embedding into portable devices.

Method used

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  • Work modal parameter identification method and device based on self-iteration principal component extraction
  • Work modal parameter identification method and device based on self-iteration principal component extraction
  • Work modal parameter identification method and device based on self-iteration principal component extraction

Examples

Experimental program
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Effect test

Embodiment 1

[0121] Apply multi-frequency sinusoidal excitation to the undamped simply supported beam; divide the undamped simply supported beam with a length of 1 meter into 1000 equal parts at equal intervals to generate 1001 response measuring points, m = 1001; apply multiple intensively at 0.2 meters Frequency sine excitation and get response data; sampling frequency is 4096Hz, sampling time is 1s, T=4096, setting accuracy threshold α=0.000001, current order contribution threshold η=0.001, maximum iteration number T max =100;

[0122] Such as Figure 7 As shown, the modal coordinate response is obtained by the working modal parameter identification algorithm based on self-iterative principal component extraction, and the FFT calculation is performed on it to obtain the common frequency of each order;

[0123] Such as Figure 8 As shown, the comparison between the recognized mode shape and the real mode shape shows that the working mode parameter identification method based on self-iterative ...

Embodiment 2

[0139] A cylindrical shell with simply supported boundary conditions at both ends, applying uniform reverberation Gaussian white noise excitation. The parameters of the cylindrical shell are: thickness 0.005m, length 0.37m, radius 0.1825m, elastic modulus 205GPa, material Poisson's ratio 0.3, material density 7850kg / m*m*m; the modal damping ratio is 0.03, 0.05, 0.10, respectively. 4370 sensors are evenly arranged on the surface, the sampling frequency is set to 5120Hz, and the sampling time is set to 1s. Use the finite element method in the LMS Virtual.lab software to calculate, obtain 3 different damping ratios from each observation point of the structure displacement response data in 3 directions, X, Y, and Z, to form a response data set in 3 directions

[0140] Such as Picture 10 As shown, the response signal matrix in three directions of the three-dimensional structure is observed, and the response signals in the three directions are directly assembled to obtain A self-iter...

Embodiment 3

[0155] Combining the short-time invariance theory and the self-iterative principal component extraction algorithm, using the statistical characteristics of the linear time-varying structural working modal parameter identification method based on sliding window self-iterative principal component extraction in each window, the working modal at each moment is estimated Parameters (including the natural frequency and mode shape of each mode), and then the working modal parameters obtained at each time are connected to realize the identification of the working modal parameters of the time-varying linear structure.

[0156] In this embodiment, the method for identifying working modal parameters of a linear time-varying structure based on sliding window self-iterative principal component extraction adopts a one-dimensional cantilever beam structure to simulate a time-varying structure. For a one-dimensional cantilever beam structure, the shearing is not considered In the case of deformat...

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Abstract

The invention relates to a one-dimensional and three dimensional linear time invariant structure work modal parameter identification method based on self-iteration principal component extraction, a linear time-varying structure work modal parameter identification method based on slide window self-iteration principal component extraction, a fault diagnosis and health state detection method based on self-iteration principal component extraction work modal parameter identification, a work modal parameter identification testing device, and a work modal parameter identification device; the work modal parameter identification device can combine the one-dimensional and three dimensional work modal parameter identification method based on self-iteration principal component extraction, the linear time-varying structure work modal parameter identification method based on slide window self-iteration principal component extraction, and the equipment fault diagnosis and health state detection method, thus developing an embedded portable device. The method and device can effectively detecting the linear engineering structure work modal parameters online, can greatly reduce the time and memory expenditure, and can be easily applied on equipment fault diagnose, health monitoring, and system structure online real time analysis and optimization.

Description

Technical field [0001] The invention relates to the field of modal parameter identification, and in particular to a method and device for identifying working modal parameters based on self-iterative principal component extraction. Background technique [0002] Modal parameters are important parameters that determine the dynamic characteristics of structures, such as modal natural frequencies, modal damping ratios, and main vibration shapes. They are an important inverse problem in the study of structural dynamic characteristics. In addition, when the system vibration is at the natural frequency, the modal shape provides a mathematical description of the vibration state. Therefore, modal parameter identification plays a vital role in the fields of structural modeling and model modification, sensitivity analysis, active and passive vibration control, damage identification, and structural health monitoring. Different from traditional experimental modal analysis (EMA), operating mod...

Claims

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Application Information

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IPC IPC(8): G01M7/02G06F17/50
CPCG01M7/025G06F30/23
Inventor 王成张天舒
Owner HUAQIAO UNIVERSITY
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