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On-line identification method of time-varying working mode based on eigenvector recursion with forgetting factor

A technology of eigenvector and forgetting factor, which is applied in the field of modal parameter identification of linear time-varying structure by principal component analysis, and can solve the problem of inability to identify modal parameters online.

Active Publication Date: 2019-04-26
HUAQIAO UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The working mode recognition methods based on PCA, ICA, SOBI and manifold learning are all statistical mode recognition methods, which are only suitable for linear time-invariant structures, and cannot identify the modal parameters of linear time-varying structures online.

Method used

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  • On-line identification method of time-varying working mode based on eigenvector recursion with forgetting factor
  • On-line identification method of time-varying working mode based on eigenvector recursion with forgetting factor
  • On-line identification method of time-varying working mode based on eigenvector recursion with forgetting factor

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Embodiment 1

[0141] Such as image 3 As shown, it is a three-degree-of-freedom spring oscillator system that simulates environmental excitation. The system is a slow time-varying system with weak damping. The mass m of block 1 1 is time-varying, m 2 、m 3 The mass remains constant to simulate a time-varying mass system; the external excitation uses Gaussian white noise with a mean value of 0 and a variance of 1 (in many practical problems, external environments that are difficult to measure are often simulated with white noise to solve problems) .

[0142] In this embodiment, the method for identifying working modal parameters of a linear time-varying structure based on eigenvalue eigenvector recursion with forgetting factor recursive principal component analysis uses a three-degree-of-freedom spring oscillator to simulate a time-varying structure, wherein, m 2 =1kg, m 3 = 1 kg; k 1 =1000N / m,k 2 =1000N / m,k 3 =1000N / m; c 1 =0.01N.s / m,c 2 =0.01N.s / m,c 3 =0.01 N.s / m. The initial d...

Embodiment 2

[0188] Such as Figure 32 As shown, it is the finite element model diagram of discretizing the cantilever beam into 40 elements;

[0189] In this embodiment, the method of principal component analysis linear time-varying structure working modal parameter identification method using eigenvalue eigenvector recursion with forgetting factor uses density-time-varying cantilever beams to simulate time-varying structures, wherein the beam parameter setting As follows: the size is 1×0.02×0.02m 3 (length × width × height), the cross-sectional area is A=W×H=4×10 -4 m 2 , the moment of inertia is I=WH 3 / 12, Young's modulus E=2.1×10 11 N / m 2 , Poisson's ratio u=0.3, the density is

[0190] Figure 33 For the proposed method to identify the frequency, sliding window recursive principal component analysis algorithm to identify the first-order natural frequency and the comparison chart of the theoretical first-order natural frequency;

[0191] Figure 34 A comparison chart for th...

Embodiment 3

[0236] Figure 55 is the block diagram of the working mode parameter device design system;

[0237] Figure 56 is the design block diagram of the upper computer;

[0238] Such as Figure 55 Shown, the time-varying structure operating mode parameter identification device based on the recursive principal component analysis algorithm of band forgetting factor of the present invention, comprises by OMAP processor (possess dual-core structure, ARM core+DSP core, has low power consumption , strong data processing capability) composed of control and data processing modules, give full play to the ability of DSP signal processing and ARM control; vibration data acquisition module (including signal input, signal conditioning, A / D data acquisition and conversion, etc. ); storage module (store a large amount of vibration data); liquid crystal display module (use LCD liquid crystal screen as output to display diagnostic results and waveform information); power supply module (responsible...

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Abstract

The invention discloses an online identification method for working mode parameters of a linear time-varying structure of principal component analysis of eigenvalue eigenvector recursion with a forgetting factor. According to the method, thoughts of ''the forgetting factor'', ''online recursion'', ''eigenvalue eigenvector recursion'' and ''matrix rank-1 correction'' are introduced based on identification of working mode parameters of a linear time-invariant structure of classic principal component analysis, so that a time-varying transient modal vibration shape and an inherent frequency of the linear time-varying structure can be identified only from a non-stationary vibration response signal. An eigenvalue eigenvector is directly subjected to online recursion updating, so that the shortcoming that a principal component model needs to be repeatedly updated in a conventional method for identifying time-varying working mode parameters of recursive principal component analysis is overcome, the algorithm time and the space complexity are shortened and lowered, online real-time time-varying working mode parameter identification is realized, and dynamic change characteristics of the working mode parameters of the structure can be effectively monitored; and the method can be used for equipment fault diagnosis, health monitoring and system structure analysis and optimization.

Description

technical field [0001] The invention relates to the field of modal parameter identification, in particular to a principal component analysis linear time-varying structural working modal parameter identification method with eigenvalue eigenvector recursion with forgetting factor. Background technique [0002] With the development and progress of science and technology, engineering structures in the fields of aerospace, architecture, bridges, oceans, machinery, etc. are gradually developing in the direction of large-scale, complex, and intelligent. The loads on the structures are difficult to measure. To establish their dynamics Model, the traditional method of obtaining system modal parameters based on measurement input and output is difficult to apply, and only the working modal parameter identification method that only needs to measure the output response can be used. Moreover, in the actual operation of many engineering structures, due to various internal and external exci...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50
CPCG16Z99/00
Inventor 王成官威陈锻生张天舒陈叶旺王建英王田张惠臻
Owner HUAQIAO UNIVERSITY
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