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公开(公告)号：US20210350040A1
公开(公告)日：2021-11-11
申请号：US17052748
申请日：2020-03-06
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Tinghua YI , Mingsheng XUE , Chunxu QU , Hongnan LI
Abstract: The present invention belongs to the technical field of data analysis for structural testing, and relates to a method of the physical mode exaction for flexibility identification of engineering structures. In the present invention combined deterministic-stochastic subspace identification algorithm is first adopted to calculate basic modal parameters and modal scaling factors from state-space models of different orders. Subsequently, the relative scaling factor difference is added as a new modal indicator to the classic stabilization diagram to better clean out the stabilization diagram. And check the correctness of the selection of the stable axis using single-modal frequency-domain similarity index (SFSI) between single-order FRF and measured FRF. Then, further determine the physical modes from the modes in the stable axis using multi-modal frequency-domain similarity index (MFSI) between lower-order superposition FRF and measured FRF. Finally, calculate flexibility matrix using identified modal parameters and predict the displacement of the structure under static load.
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公开(公告)号：US20200033226A1
公开(公告)日：2020-01-30
申请号：US16342954
申请日：2018-03-12
Applicant: Dalian University of Technology
Inventor： Tinghua YI , Xiaomei YANG , Chunxu QU , Hongnan LI
IPC: G01M5/00
Abstract: Structural health monitoring relating to an automatic method for tracking structural modal parameters. First, Natural Excitation Technique is used to transform the random responses into correlation functions and Eigensystem Realization Algorithm combined with the stabilization diagram is used to estimate modal parameters from various response segments. Then, modes from the latter response segment are classified as traceable modes or untraceable modes according to correlations between their observability vectors and subspaces of the existing reference modes. Final, traceable modes will be grouped into specified clusters with the same structural characteristics on the basis of maximum modal observability vector correlation and minimum frequency difference. Meanwhile, union of the untraceable modes and existing reference modes are updated as the new reference modes which can be applied into the next tracking process. This can track the modal parameters automatically without artificial thresholds and the specified reference modes.
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公开(公告)号：US20200074221A1
公开(公告)日：2020-03-05
申请号：US16342948
申请日：2018-03-28
Applicant: Dalian University of Technology
Inventor： Tinghua YI , Xiaomei YANG , Chunxu QU , Hongnan LI
Abstract: Structural health monitoring relating to an automatic method for estimating structural modal parameters by clustering. The structural modal parameters from state-space models are calculated in different orders by Natural Excitation Technique in combination with Eigensystem Realization Algorithm According to the characteristics that physical modes are those with high similarity and stably appearing at different orders while spurious modes are those with little similarity and unstably appearing at different orders, the modal dissimilarity between two nearest modes in consecutive order are considered as feature of the mode in the lower order. Then, features of modes are used in fuzzy C-means clustering to adaptively acquire the stable cluster where modes are with high similarity. Finally, Hierarchical clustering is used to group the stable modes with identical modal parameters together and thus each physical mode can be obtained.
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公开(公告)号：US20190171691A1
公开(公告)日：2019-06-06
申请号：US16321183
申请日：2018-03-06
Applicant: Dalian University of Technology
Inventor： Chunxu QU , Tinghua YI , Hongnan LI
Abstract: The presented invention belongs to the technical field of data analysis for structural health monitoring, and relates to a method of the mode order determination for the modal identification of engineering structures. The presented invention first calculates the structural natural frequencies for every order by eigensystem realization algorithm. Then the modal responses for every natural frequency are extracted. After obtaining the square mean root of modal responses, the modal response contribution index (MRCI) is calculated by summation of square mean root for every degree-of-freedom. The relation map between mode order and MRCI is drawn. The mode order is determined by the obvious gap between two adjacent MRCI according to the relation map. This order is also the truncated order of singular matrix in the eigensystem realization algorithm, which is useful to identify other modal parameters accurately.
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5.发明申请公开(公告)号：US20190121838A1
公开(公告)日：2019-04-25
申请号：US16090911
申请日：2018-02-12
Applicant: Dalian University of Technology
Inventor： Tinghua YI , Haibin HUANG , Hongnan LI
IPC: G06F17/18
Abstract: The present invention belongs to the technical field of health monitoring for civil structures, and a dynamically non-Gaussian anomaly identification method is proposed for structural monitoring data. First, define past and current observation vectors for the monitoring data and pre-whiten them; second, establish a statistical correlation model for the whitened past and current observation vectors to obtain dynamically whitened data; then, divide the dynamically whitened data into two parts, i.e., the system-related and system-unrelated parts, which are further modelled by the independent component analysis; finally, define two statistics and determine their corresponding control limits, respectively, it can be decided that there is anomaly in the monitoring data when each of the statistics exceeds its corresponding control limit. The non-Gaussian and dynamic characteristics of structural monitoring data are simultaneously taken into account, based on that the defined statistics can effectively identify anomalies in the data.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20200073908A1
公开(公告)日：2020-03-05
申请号：US16342952
申请日：2018-03-06
Applicant: Dalian University of Technology
Inventor： Tinghua YI , Xiaojun YAO , Hongnan LI
Abstract: Structural health monitoring providing sparse component analysis method for structural modal identification with incomplete number of sensors. Transforming structural acceleration response data into time frequency domain by short time Fourier transform, detecting time frequency points contributed by only one-order mode where real and imaginary parts have the same direction, and taking the detection result as the initial result of single-source-points; refining the initial result of detection of single-source-point located near the peak of power spectral density, and clustering single-source-points to obtain a mode shape matrix; constructing generalized spectral matrixes using short time Fourier transform coefficients, conducting singular value decomposition on generalized spectral matrix at a single-source-point, taking the first singular value as an auto-spectrum of single-order mode, obtaining the frequency of each order by picking the peak of auto-spectrum, and extracting damping ratio of each order by transforming the auto-spectrum into a time domain through inverse Fourier transform
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公开(公告)号：US20200065438A1
公开(公告)日：2020-02-27
申请号：US16342929
申请日：2018-03-27
Applicant: Dalian University of Technology
Inventor： Tinghua YI , Xiaomei YANG , Chunxu QU , Hongnan LI
Abstract: Structural health monitoring relating to a real-time tracking method for structural modal parameters. The Natural Excitation Technique transforms structural random responses into free decaying responses used to calculate structural modal parameters by the Eigensystem Realization Algorithm combined with the stabilization diagram. Considering influence of environmental excitation level on the number of identified modes, the reference mode list is formed by union of modes obtained from response sets in a day. Then the modes can be tracked automatically according to rules of minimum frequency difference and maximum Modal Assurance Criterion (MAC). To avoid mode mismatch problem caused by absence of threshold, frequency differences and MACs between all modes from the latter response set and all reference modes are calculated and the mode will be tracked into the cluster corresponding to the specified reference mode only in the case that their frequency difference is smallest and the MAC is largest.
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8.发明申请公开(公告)号：US20190122131A1
公开(公告)日：2019-04-25
申请号：US16090744
申请日：2018-02-12
Applicant: Dalian University of Technology
Inventor： Tinghua YI , Haibin HUANG , Hongnan LI , Shuwei MA
Abstract: The present invention belongs to the technical field of health monitoring for civil structures, and an anomaly identification method considering spatial-temporal correlation is proposed for structural monitoring data. First, define current and past observation vectors for the monitoring data and pre-whiten them; second, establish a statistical correlation model for the pre-whitened current and past observation vectors to simultaneously consider the spatial-temporal correlation in the monitoring data; then, divide the model into two parts, i.e., the system-related and system-unrelated parts, and define two corresponding statistics; finally, determine the corresponding control limits of the statistics, and it can be decided that there is anomaly in the monitoring data when each of the statistics exceeds its corresponding control limit.
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公开(公告)号：US20210223214A1
公开(公告)日：2021-07-22
申请号：US17046713
申请日：2019-11-06
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Chunxu QU , Tinghua YI , Hongnan LI
IPC: G01N29/46
Abstract: The presented invention belongs to the technical field of data analysis for engineering structural monitoring, and relates to a method of complex modal identification for the structure with proportional damping. Firstly, the set of single source points containing the real modal shapes are obtained by short time Fourier transform and single source point detection, and then the real modal shapes are calculated by hierarchical distance method. Then, the impulse response and its Hilbert transform are obtained by natural excitation technology and Hilbert transform, respectively. The relationship between modal response and impulse response with its Hilbert transform is established. Finally, the complex modal parameters are solved. In this invention, the procedures of hidden complex modes of structures with proportional damping are given by explicit expression, which reveal the structural dynamic characteristics essentially.
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10.发明申请公开(公告)号：US20200034500A1
公开(公告)日：2020-01-30
申请号：US16342907
申请日：2018-03-19
Applicant: Dalian University of Technology
Inventor： Tinghua YI , Xueyang PEI , Hongnan LI
IPC: G06F17/50
Abstract: Sensor placement for structural health monitoring relating to modal estimation of bridge structures using structural data from strain gauges and accelerometers. Arrange strain gauges at large deformation positions of the structure for monitoring local deformation information. Adjust positions of strain gauges to include as much important displacement modal information as possible. Use strain mode shapes of strain gauge positions to estimate the displacement mode shapes of the structure and increase accelerometer to improve distinguishability of estimated displacement mode shapes, while reducing redundancy information among obtained displacement mode shapes. Different structural information contained in the strain gauges and the accelerometers are used, and placement of strain gauges can give local deformation information of key positions of the structure and obtain accurate structural displacement modal information. Placement of accelerometers improves displacement modal information obtained by estimation of strain mode shapes, and high-quality structural overall displacement modal information is obtained.
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