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A multi-dimensional dynamic fingerprint damage identification method based on mcd outlier detection algorithm

A technology for damage identification and abnormal points, applied in vibration testing, complex mathematical operations, testing of machine/structural components, etc., can solve problems such as unclear damage location judgment, achieve automatic data processing, wide application range, and strong robustness sexual effect

Active Publication Date: 2021-08-27
HOHAI UNIV
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Problems solved by technology

[0003] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide an MCD-based MCD that is suitable for the parameter extraction process and can solve the technical problem of unclear damage location judgment due to noise and measurement errors in the existing dynamic damage identification. Multi-dimensional Dynamic Fingerprint Damage Recognition Method Based on Outlier Inspection Algorithm

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  • A multi-dimensional dynamic fingerprint damage identification method based on mcd outlier detection algorithm
  • A multi-dimensional dynamic fingerprint damage identification method based on mcd outlier detection algorithm
  • A multi-dimensional dynamic fingerprint damage identification method based on mcd outlier detection algorithm

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[0037] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0038] In a statistical sense, damage identification is essentially to find outliers whose structural unit behavior is different from the overall law. In actual engineering, the damage area is local and small-scale to the overall structure, so the characteristics of the observation data in the non-damage area are dominant and dominant in the overall observation data, while the characteristics of the observation data in the damage area are different from those in the non-damage area. The characteristics of the observation data in the damage observation area, so finding outliers that are inconsistent with the overall data is the mathematical essence of structural damage identification. Therefore, ...

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Abstract

The invention discloses a multi-dimensional dynamic fingerprint damage identification method based on an MCD abnormal point inspection algorithm, comprising the following steps: S01, selecting a plurality of dynamic fingerprints, and constructing a dynamic fingerprint change feature vector based on the changes before and after the dynamic fingerprint damage; S02, for each Standardize the eigenvectors to obtain standardized eigenvectors; S03, use all unit eigenvectors as a multidimensional random population, iteratively search for all sub-samples with a sample size of h, and obtain the sub-sample with the smallest covariance determinant and a sample size of h. This sample estimates the overall mean and covariance matrix; S04, calculates the Mahalanobis distance of each feature vector under the MCD method; S05, compares the obtained Mahalanobis distance with the threshold to find out the abnormal point, which is a damage unit based on MCD provided by the present invention The multi-dimensional dynamic fingerprint damage identification method of the outlier detection algorithm has a suitable parameter extraction process and can solve the technical problem of unclear damage location judgment due to noise and measurement errors in the existing dynamic damage identification.

Description

technical field [0001] The invention relates to a multi-dimensional dynamic fingerprint damage identification method based on an MCD abnormal point inspection algorithm, which belongs to the technical field of engineering detection. Background technique [0002] In recent years, the dynamic fingerprint damage identification method has been widely used in the safety monitoring of large civil engineering such as bridges and high-rise buildings. Dynamic fingerprints include vibration mode, curvature mode, flexibility matrix, stiffness matrix, strain mode, modal strain energy and other indicators. Based on these dynamic fingerprints, many identification methods are derived, such as modal guarantee rate method, frequency square method, sensitivity However, when combined with measured data, due to the influence of noise and errors, it is easy to cause misjudgment and misjudgment. Contents of the invention [0003] The technical problem to be solved by the present invention is t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M7/02G06F17/16
CPCG01M7/025G06F17/16
Inventor 朱瑞虎王启明郑金海罗孟岩车宇飞郭健王军磊曾海坤
Owner HOHAI UNIV
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