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Method and device for identification of working mode parameters based on self-iterative principal component extraction

A technology for working mode and parameter identification, which is used in measurement devices, electrical digital data processing, special data processing applications, etc.

Active Publication Date: 2019-07-09
HUAQIAO UNIVERSITY
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  • Summary
  • 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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  • Method and device for identification of working mode parameters based on self-iterative principal component extraction
  • Method and device for identification of working mode parameters based on self-iterative principal component extraction
  • Method and device for identification of working mode parameters based on self-iterative principal component extraction

Examples

Experimental program
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Effect test

Embodiment 1

[0119] 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, and generate 1001 response measuring points, m=1001; frequency sine excitation and obtain response data; the sampling frequency is 4096Hz, the sampling time is 1s, T=4096, set the accuracy threshold α=0.000001, the current order contribution threshold η=0.001, and the maximum number of iterations T max = 100;

[0120] Such as Figure 7 As shown, the modal coordinate response is obtained through 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;

[0121] Such as Figure 8 As shown, the comparison between the identified mode shape and the real mode shape shows that the working mode parameter identification method based on self-iterative principal component...

Embodiment 2

[0137] A cylindrical shell with simply supported boundary conditions at both ends is excited by uniform reverberation Gaussian white noise. 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 ratios are 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. Using the finite element method in the LMS Virtual.lab software for calculation, the structural displacement response data in the X, Y, and Z directions of three different damping ratios are obtained from each observation point to form a response data set in the three directions

[0138] Such as Figure 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 ...

Embodiment 3

[0153] Combining the short-term time-invariant theory and the self-iterative principal component extraction algorithm, the operating mode at each time is estimated by using the statistical characteristics of the operating mode parameter identification method of the linear time-varying structure based on the sliding window self-iterative principal component extraction in each window parameters (including the natural frequency and mode shape of each mode), and then the working mode parameters obtained at each time are connected to realize the identification of time-varying linear structural working mode parameters.

[0154] In this embodiment, the method for identifying working modal parameters of linear time-varying structures based on sliding window self-iterative principal component extraction uses a one-dimensional cantilever beam structure to simulate a time-varying structure. For a one-dimensional cantilever beam structure, without considering shear In the case of deformati...

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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, 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 mode shapes. They are an important inverse problem in the study of structural dynamic characteristics. In addition, mode shapes provide a mathematical description of the state of vibration when the system is vibrating at a natural frequency. Therefore, modal parameter identification plays a vital role in the fields of structural modeling and model correction, sensitivity analysis, active and passive vibration control, damage identification, and structural health monitoring. Unlike traditional experimental modal analysis (EMA), operational modal analysis (OMA)...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M7/02G06F17/50
CPCG01M7/025G06F30/23
Inventor 王成张天舒
Owner HUAQIAO UNIVERSITY
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