Multi-dimensional dynamic fingerprint damage identification method based on MCD abnormal point test algorithm

A technology for damage identification and abnormal points, applied in vibration testing, complex mathematical operations, testing of machines/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: 2019-11-15
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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  • Multi-dimensional dynamic fingerprint damage identification method based on MCD abnormal point test algorithm
  • Multi-dimensional dynamic fingerprint damage identification method based on MCD abnormal point test algorithm
  • Multi-dimensional dynamic fingerprint damage identification method based on MCD abnormal point test algorithm

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[0037] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and cannot be used 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 practical engineering, the damage area is local and small-scale to the overall structure, so the observation data characteristics in the non-damage area are dominant and dominant in the overall observation data, while the observation data characteristics in the damage area are different from those in the non-damage area. The damage observation area observes the data characteristics, so finding outliers that are not in harmony with the overall data is the mathematical essence of structural damage identification. Therefore, the prese...

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Abstract

The invention discloses a multi-dimensional dynamic fingerprint damage identification method based on an MCD abnormal point test algorithm. The method comprises following steps of: S01, selecting multiple dynamic fingerprints, and constructing dynamic fingerprint change characteristic vectors based on changes of the dynamic fingerprint before and after damage; S02, standardizing each characteristic vector, and obtaining a standardized characteristic vector; S03, using all unit characteristic vectors as a multi-dimensional random whole, iteratively searching all subsamples with sample capacityof h, obtaining subsamples with a minimum covariance determinant and sample capacity of h, and evaluating an overall mean value and a covariance matrix by using the subsamples; S04, calculating Mahalanobis distance of each characteristic vector under a MCD method; and S05, comparing the obtained Mahalanobis distance with a threshold so as to find an abnormal point, that is, a damaged unit. The multi-dimensional dynamic fingerprint damage identification method based on the MCD abnormal point test algorithm has a proper parameter extraction process, and solves a technical problem that a damagedposition cannot be determined clearly due to noise and measurement errors in 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, and 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-scale civil engineering such as bridges and high-rise buildings. Dynamic fingerprints include mode shape, curvature mode, compliance 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 flattening method, sensitivity However, when combined with the measured data, it is easy to cause misjudgment and misjudgment due to the influence of noise and errors. SUMMARY OF THE INVENTION [0003] The technical problem to be solved by the present invention...

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Application Information

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Patent Type & Authority Applications(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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