Analysis Method and Device for Relevant Factors of Abnormal Vibration of Engineering Structures

Abstract

The present invention provides a method and device for analyzing relevant factors of abnormal vibration of an engineering structure. According to a preset data acquisition unit, monitoring data of a target engineering structure under a variety of preset working conditions is collected; based on the monitoring data under each preset working condition, modal parameters of the target engineering structure under each preset working condition are determined; the modal parameters correspond to preset parameters corresponding to multiple time periods; for each preset working condition, the relative change relationship between the monitoring data within a preset time period under the current working condition and the modal parameters corresponding to the monitoring data is determined; according to the relative change relationship corresponding to each preset working condition, relevant factors of abnormal vibration of the target engineering structure are determined. The present invention combines the degree of correlation between the changes in the monitoring data and the modal parameters. The modal parameters are composed of preset parameters corresponding to multiple time periods, making the modal parameter data more comprehensive. Therefore, this method can accurately and quickly identify the modal parameters to determine the possible causes of abnormal vibration of high-rise structures.

Description

Technical Field

[0001] The present invention relates to the technical field of modal parameter identification and applications, and in particular, to a method and device for analyzing related factors of abnormal vibration of engineering structures. Background Art

[0002] With the progress of human society and the development of science and technology, the time-varying problems of engineering structures have become increasingly prominent in the fields of civil engineering, aerospace, mechanical design, etc. Under the influence of some working conditions, some parameters of the structure, such as mass, stiffness, damping ratio, etc., will change rather than remain constant. Therefore, it is urgent to develop a time-varying structural parameter identification theory and technical means through structural health monitoring to combine the modal parameters of the engineering structure to explain the possible reasons for the abnormal vibration of the engineering structure, so as to provide reference for the reasonable design and standardized construction of high-rise building structures.

[0003] At present, the developed time-varying structural parameter identification is based on the short-time time-invariant assumption, online or recursive technology, and signal processing technology methods. Among them, the method based on the short-time time-invariant assumption has low time resolution. If the modal parameters change too fast, the time period of the data needs to be further subdivided to adapt to the system. The method based on signal processing technology is mainly the time-frequency analysis method. The time-frequency analysis method needs to convert the time-domain signal into a frequency-domain signal and analyze it in the two-dimensional time-frequency space, which has problems such as modal aliasing and leakage. Therefore, the above methods cannot accurately and quickly perform structural analysis based on the data of engineering structures and rapidly changing modal parameters, and thus cannot accurately and quickly explain the possible reasons for the abnormal vibration of engineering structures. For this reason, the present application proposes a method for identifying time-varying structural parameters based on recursive technology, which can accurately and quickly perform structural analysis based on the data of engineering structures and rapidly changing modal parameters, and thus accurately and quickly explain the possible reasons for the abnormal vibration of high-rise structures in engineering structures. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and device for analyzing related factors of abnormal vibration of engineering structures to solve the technical problem of how to accurately and quickly explain the possible reasons for the abnormal vibration of high-rise structures.

[0005] In a first aspect, the present invention provides a method for analyzing relevant factors of abnormal vibration of an engineering structure, the method comprising: collecting monitoring data of a target engineering structure under a variety of preset working conditions according to a preset data acquisition unit; determining modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition; there are preset parameters corresponding to multiple time periods for the above modal parameters; for each preset working condition, determining the relative change relationship between the monitoring data under the current working condition and the modal parameters corresponding to the monitoring data; determining relevant factors of abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition.

[0006] In an alternative embodiment, the step of determining modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition includes: for each of the variety of preset working conditions, performing the following operations: selecting monitoring data of the free decay section from the monitoring data under the preset working condition; there are monitoring data corresponding to multiple time periods in the monitoring data of the free decay section; determining a Hankel matrix corresponding to the first time period based on the monitoring data corresponding to the first time period among the multiple time periods; obtaining a Toeplitz matrix corresponding to the first time period according to the Hankel matrix corresponding to the first time period; determining the second time period among the multiple time periods as the new first time period, and continuing to perform the step of determining a Hankel matrix corresponding to the first time period based on the monitoring data corresponding to the first time period among the multiple time periods until the last time period among the multiple time periods is determined as the new first time period, obtaining a Toeplitz matrix corresponding to the last time period; determining modal parameters under the preset working condition based on the Toeplitz matrix corresponding to each time period among the multiple time periods.

[0007] In an alternative embodiment, the step of determining modal parameters under the preset working condition based on the Toeplitz matrix corresponding to each time period among the multiple time periods includes: for each time period among the multiple time periods, performing the following operations: introducing a variable forgetting factor into the Toeplitz matrix corresponding to the current time period to obtain a Toeplitz matrix with a variable forgetting factor corresponding to the current time period; performing singular value decomposition on the Toeplitz matrix with a variable forgetting factor corresponding to the current time period to obtain an observable matrix corresponding to the current time period; obtaining a preset parameter corresponding to the current time period according to the observable matrix corresponding to the current time period; determining a combination of preset parameters corresponding to each time period among the multiple time periods as modal parameters under the preset working condition.

[0008] In an alternative embodiment, the step of obtaining the preset parameter corresponding to the current time period based on the observable matrix corresponding to the current time period includes: determining the state matrix corresponding to the current time period based on the observable matrix corresponding to the current time period; performing eigenvalue decomposition on the state matrix to obtain the eigenvalues corresponding to the state matrix; and obtaining the preset parameter corresponding to the current time period according to the eigenvalues corresponding to the state matrix.

[0009] In an alternative embodiment, the above-mentioned modal parameter is the preset parameter corresponding to multiple time periods; the step of determining the relative change relationship between the monitoring data and the modal parameter corresponding to the monitoring data under the current working condition includes: determining the change result corresponding to the monitoring data under the current working condition according to the monitoring data under the current working condition; determining the corresponding modal parameter under the current working condition according to the monitoring data under the current working condition; and obtaining the relative change relationship based on the modal parameter and the change result.

[0010] In an alternative embodiment, the above-mentioned modal parameter is the preset parameter corresponding to multiple time periods; the relative change relationship includes the change result corresponding to the monitoring data under each preset working condition and the modal parameter corresponding to the monitoring data under each preset working condition; the step of determining the relevant factors of the abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition includes: obtaining the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition among multiple preset working conditions; determining the correlation degree between the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition; and determining the relevant factors of the abnormal vibration of the target engineering structure based on the correlation degree.

[0011] In an alternative embodiment, each of the above-mentioned time periods includes multiple moments; the step of determining the second time period among multiple time periods as the new first time period includes: determining the second moment in the first time period as the first moment in the second time period; obtaining the initial moment corresponding to the new first time period based on the first moment in the second time period; and determining the new first time period according to the initial moment corresponding to the new first time period.

[0012] In an alternative embodiment, after the step of determining the modal parameter of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition, the method further includes: determining the accuracy of the modal parameter under each preset working condition based on the preset threshold parameter.

[0013] In a second aspect, the present invention provides an apparatus for determining relevant factors of abnormal vibration of a high-rise structure. The apparatus includes: a data acquisition module for acquiring monitoring data of a target engineering structure under a variety of preset working conditions according to a preset data acquisition unit; a modal parameter determination module for determining modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition; the above modal parameters correspond to preset parameters corresponding to multiple time periods; a relative relationship determination module for determining, for each preset working condition, the relative change relationship between the monitoring data under the current working condition and the modal parameters corresponding to the monitoring data; a factor determination module for determining relevant factors of abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition.

[0014] In a third aspect, the present invention provides an electronic device, which includes a processor and a memory. The above memory stores machine-executable instructions that can be executed by the processor, and the above processor executes the machine-executable instructions to implement the above method for analyzing relevant factors of abnormal vibration of an engineering structure.

[0015] The present invention brings the following beneficial effects:

[0016] The present invention first acquires the monitoring data of the target engineering structure under a variety of preset working conditions, and determines the modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition. Then, for each preset working condition, it determines the relative change relationship between the monitoring data within a preset time period under the current working condition and the modal parameters corresponding to the monitoring data, and determines the relevant factors of abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition. The present invention combines the degree of correlation between the changes in the monitoring data and the modal parameters. In addition, the above modal parameters are preset parameters corresponding to multiple time periods, and experiments are carried out based on these modal parameters to make the modal parameter data more comprehensive and accurate when determining the possible causes of abnormal vibration of the high-rise structure. Description of the Drawings

[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a flowchart of a method for analyzing relevant factors of abnormal vibration of an engineering structure provided by an embodiment of the present invention;

[0019] Figure 2 It is a flowchart of another method for analyzing relevant factors of abnormal vibration of an engineering structure provided by an embodiment of the present invention;

[0020] Figure 3 It is a flowchart of another method for analyzing relevant factors of abnormal vibration of an engineering structure provided by an embodiment of the present invention;

[0021] Figure 4 It is a schematic structural diagram of a device for analyzing relevant factors of abnormal vibration of an engineering structure provided by an embodiment of the present invention;

[0022] Figure 5 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Specific embodiments

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] Based on the problems mentioned in the background art, the embodiments of the present invention provide a method and a device for analyzing relevant factors of abnormal vibration of an engineering structure. This technology can be applied to the scenario of structural analysis of building engineering structures, which include building engineering structures corresponding to housing, bridges, railways, highways, hydraulic engineering, marine engineering, ports, underground, etc., especially high-rise structures among the above building engineering structures.

[0026] To facilitate the understanding of this embodiment, first, a method for analyzing relevant factors of abnormal vibration of an engineering structure disclosed in the embodiments of the present invention will be introduced in detail. Through this method, modal parameter data can be made more comprehensive to explain the possible reasons for abnormal vibration of high-rise structures; as Figure 1 shown, the method includes the following specific steps:

[0027] Step S102, collect monitoring data of the target engineering structure under a variety of preset working conditions according to a preset data acquisition unit.

[0028] The engineering structure is usually a building engineering structure corresponding to housing, bridges, railways, highways, hydraulic engineering, marine engineering, ports, underground, etc., such as buildings, structures, and facilities. The target engineering structure is the engineering structure currently monitored by the user.

[0029] When monitoring the above-mentioned target engineering structure, it is usually necessary to use a corresponding data acquisition unit to collect the vibration response signal of the above-mentioned target engineering structure for the analysis of the target engineering structure.

[0030] The above-mentioned preset working condition refers to the vibration state under the condition that there is a direct relationship between the above-mentioned target engineering structure and its vibration action. The monitoring data collected under this vibration state is the monitoring data under the above-mentioned preset working condition. Specifically, the conditions directly related to the vibration action can be the load of the target engineering structure and the external environmental conditions during the vibration of the target engineering structure. In specific implementation, there can be various monitoring data under the above-mentioned preset working conditions, that is, it can be the monitoring data of the load or the monitoring data of the target engineering structure. Further, the conditions directly related to the vibration action in the above-mentioned multiple preset working conditions can be determined according to the user's needs.

[0031] Step S104: Based on the monitoring data under each preset working condition, determine the modal parameters of the target engineering structure under each preset working condition.

[0032] The modal parameters of a structure are very important characteristics of the structure, such as modal mass, modal stiffness, natural frequency, modal damping ratio, and modal vibration mode, etc. These modal parameters can be obtained through calculation or experimental analysis based on the monitoring data, and such a calculation or experimental analysis process is called modal analysis. Through the modal analysis method of the engineering structure, the vibration characteristics of each order of the modal in a frequency range vulnerable to influence of the engineering structure can be obtained, as well as the vibration response results of the engineering structure under the excitation of various internal or external vibration sources in this frequency band. Then, the modal parameters are obtained by the modal analysis method, and these specific parameters help to provide a reference for the reasonable design of other structures.

[0033] Further, some of the above-mentioned modal parameters change relatively fast, and it is impossible to accurately determine the influencing factors of the abnormal vibration of the above-mentioned target engineering structure only based on the modal parameters in one time period. Therefore, in this embodiment, the above-mentioned modal parameters correspond to preset parameters corresponding to multiple time periods, that is, preset parameters corresponding to multiple time periods are determined to conduct relevant experiments. The nature of the preset parameters is the same as that of the above-mentioned modal parameters of the structure, including modal mass, modal stiffness, natural frequency, modal damping ratio, and modal vibration mode, etc.

[0034] Step S106: For each preset working condition, determine the relative change relationship between the monitoring data under the current working condition and the modal parameters corresponding to the monitoring data.

[0035] In specific implementation, the actual preset working conditions can be set according to the needs of users. After obtaining the monitoring data under each preset working condition, the modal parameters corresponding to the monitoring data can be determined according to the above-mentioned monitoring data. Different monitoring data can obtain different modal parameters. Further, the change result corresponding to the monitoring data within a preset time period can be obtained based on the monitoring data within the preset time period, and then the change result of the above-mentioned modal parameters can also be obtained. By comparing the change result corresponding to the above-mentioned monitoring data with the change result corresponding to the above-mentioned modal parameters, the relative change relationship between the monitoring data and its modal parameters can be obtained.

[0036] Step S108, determine the relevant factors of abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition.

[0037] When the relative change relationship between the monitoring data and its modal parameters corresponding to the above-mentioned preset working condition is relevant, the corresponding relevant conditions in the current preset working condition can be determined as the relevant factors of the abnormal vibration of the above-mentioned target engineering structure.

[0038] In specific implementation, loads will be set on the building corresponding to the above-mentioned target engineering structure. During the vibration process of the above-mentioned target engineering structure, the above-mentioned loads may directly or indirectly affect the above-mentioned target engineering structure, and even cause the above-mentioned target engineering structure to have abnormal vibration. Therefore, the load of the target engineering structure itself is a relevant factor corresponding to the target engineering structure. In addition, the above-mentioned load can also be the relevant conditions corresponding to the above-mentioned multiple preset working conditions, that is, these loads are monitored and the monitoring data is collected.

[0039] An analysis method for relevant factors of abnormal vibration of an engineering structure provided by an embodiment of the present invention combines the degree of change correlation between monitoring data and modal parameters. In addition, the above-mentioned modal parameters are composed of preset parameters corresponding to multiple time periods. Experiments are carried out based on the preset parameters corresponding to multiple time periods, making the modal parameter data more comprehensive to determine the possible reasons for the abnormal vibration of the engineering structure.

[0040] For the above-mentioned embodiment, the present invention provides an analysis method for relevant factors of abnormal vibration of an engineering structure, which is implemented on the basis of the above-mentioned method. This method focuses on describing the specific process of determining the modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition (implemented through the following step S204), as Figure 2 shown, this method includes the following specific steps:

[0041] Step S202, collect the monitoring data of the target engineering structure under multiple preset working conditions according to the preset data acquisition unit.

[0042] Step S204: Based on the monitoring data under each preset working condition, determine the modal parameters of the target engineering structure under each preset working condition.

[0043] Specifically, for each of the multiple preset working conditions, perform the following steps 10 - 14 to obtain the modal parameters of the target engineering structure under each preset working condition:

[0044] Step 10: Select the monitoring data of the free decay segment from the monitoring data under the preset working condition.

[0045] Collect the monitoring data of the above - mentioned target engineering structure under multiple preset working conditions, and extract the monitoring data corresponding to the free decay segment from this monitoring data for operation; specifically, the monitoring data collected in the above - mentioned manner contains forced vibration segment signals and free decay response signals. When applying it to the modal parameter identification of the above - mentioned target engineering structure, the free decay response signals need to be extracted to obtain the monitoring data of the free decay segment. The monitoring data corresponding to the free decay segment corresponds to the monitoring data of multiple time periods. Each time period of the above - mentioned multiple time periods contains the monitoring data corresponding to multiple moments.

[0046] Furthermore, in order to determine the relevant factors of the abnormal vibration of the above - mentioned target engineering structure, in this embodiment, the modal damping ratio in the above - mentioned modal parameters is mainly analyzed. Since the damping ratio changes too fast, it is necessary to determine the numerical value of the modal parameter that can be updated.

[0047] Step 11: Based on the monitoring data corresponding to the first time period among multiple time periods, determine the Hankel matrix corresponding to the first time period.

[0048] After determining the monitoring data corresponding to the above - mentioned free decay segment, select the monitoring data corresponding to the first time period from the monitoring data of multiple time periods corresponding to the free decay segment, and determine the Hankel matrix corresponding to the first time period. Specifically, each time period of the above - mentioned multiple time periods contains the monitoring data corresponding to multiple moments. In specific implementation, the above - mentioned determination of the Hankel matrix corresponding to the first time period is determined through the following steps 20 - 21:

[0049] Step 20: Define the monitoring data starting from the k - th moment as the monitoring data of the first time period, and perform calculations on the monitoring data at the k - th moment to obtain the observed output vector y k , specifically, the above - mentioned observed output vector is calculated through the following formula:

[0050] g k+1 =Ag k +w k

[0051] y k = Cg k + v k

[0052] where g k is the state vector at time k, g k ∈ R m×1 ; y k is the observed output vector at time k, y k ∈ R l×1 ; A is the state vector of the discrete-time state, A ∈ R m×m ; C is the observation matrix of the discrete-time state, C ∈ R l×m ; w k is the noise caused by the processing of the above monitoring data and the modeling error, w k ∈ R m×1 ; v k is the noise caused by the device error of the above preset data acquisition unit, v k ∈ R l×1 . Specifically, m = 2n, where n is the degree of freedom of the structure; l is the number of layout points of the above preset data acquisition unit corresponding to the measuring points.

[0053] Step 21, determine the observed output vector corresponding to the above first time period, and construct the Hankel matrix corresponding to the first time period according to the observed output vector.

[0054] In specific implementation, the above Hankel matrix is represented by the following matrix:

[0055]

[0056] where the Hankel matrix Y 0|2M-1 is a matrix including "2M row blocks" and "j column blocks", and each row block consists of l rows, where l is the number of output channels. Theoretically, it is assumed that j → ∞, but in fact j cannot be infinite. The Hankel matrix is divided into two parts: "past" and "future". The subscripts 0|2M - 1 represent the subscripts of the first block row and the last block row of the first column of the Hankel matrix, and the subscripts p and f represent "past" and "future" respectively. The matrix is divided into Y p and Y f Divide Y 0|2M-1 into two equal parts, and each part has M block rows.

[0057] Take the covariance of the above observed output vector to obtain R Mcov ∈ R l×l as: R Mcov = E[y k+M y k T = CAG i-1 Gcov ;

[0058] Covariance is taken between the above state vector and the above observation output vector to obtain G cov ∈R n×l as: G cov ∈E[g k+1 y k T = E[(Ag k + w k )·(Cg k + v k ) T .

[0059] If the stochastic process of the above monitoring data is stable and satisfies the ergodicity condition, then the above Hankel matrix can be approximately written as: Obtain the final Hankel matrix.

[0060] Step 12: Obtain the Toeplitz matrix corresponding to the first time period according to the Hankel matrix corresponding to the first time period.

[0061] After obtaining the Hankel matrix corresponding to the above first time period, the Toeplitz matrix can be obtained according to the above Hankel matrix, that is, the Toeplitz matrix corresponding to the first time period is obtained. Specifically, the Toeplitz matrix corresponding to the above first time period is represented by the following matrix:

[0062]

[0063] Furthermore, according to the above covariance form, the above Toeplitz matrix can be written in the following form:

[0064]

[0065] where Γ M is the observable matrix, Γ M ∈R lM×n ; O M is the controllable matrix, O M ∈R n×lM .

[0066] Step 13: Determine the second time period among multiple time periods as the new first time period, and continue to execute the step of determining the Hankel matrix corresponding to the first time period based on the monitoring data corresponding to the first time period among multiple time periods until the last time period among multiple time periods is determined as the new first time period, and obtain the Toeplitz matrix corresponding to the last time period.

[0067] During the free decay of the vibration of the above-mentioned target engineering structure, the modal parameters will also change accordingly. They are not a continuously stable parameter. Therefore, it is necessary to obtain updatable modal parameters. When specifically implemented, after obtaining the Toeplitz matrix corresponding to the first time period, the Toeplitz matrices corresponding to each of the above-mentioned multiple time periods are further determined.

[0068] Specifically, the k-th moment in the second time period is the (k + 1)-th moment in the first time period, and the k-th moment in the third time period is the (k + 2)-th moment in the first time period; that is, the value of k in the k-th moment of the new first time period is the value corresponding to the (k + 1)-th moment in its previous time period. When specifically implemented, when the starting moment of the free decay response signal in the first time period is 10 s, the starting moment of the free decay response signal in the second time period is 11 s, and the starting moment of the free decay response signal in the third time period is 12 s. Then, according to the starting moment corresponding to each time period, the Toeplitz matrices corresponding to each of the above-mentioned multiple time periods are determined.

[0069] Step 14: Determine the modal parameters under the preset working condition based on the Toeplitz matrices corresponding to each of the multiple time periods.

[0070] When specifically implemented, the modal parameters under the above-mentioned preset working condition are realized through the following steps 30-33:

[0071] Step 30: For each of the multiple time periods, introduce a variable forgetting factor to the Toeplitz matrix corresponding to the current time period to obtain the Toeplitz matrix with the variable forgetting factor introduced corresponding to the current time period.

[0072] Specifically, the Toeplitz matrix without the variable forgetting factor corresponding to the current time period can be expressed by the following formula:

[0073]

[0074]

[0075]

[0076] where p 1 is the normalization parameter.

[0077] Further, a variable forgetting factor is introduced into the Toeplitz matrix corresponding to the above current time period to obtain a Toeplitz matrix with a forgetting factor. Specifically, first, the output matrix with a forgetting factor at time k is represented by the following matrix:

[0078]

[0079] Among them, is the output matrix at time k, and β is the forgetting factor.

[0080] The above output matrix with a forgetting factor corresponding to time k can also be represented by the following formula as:

[0081]

[0082] β Y = diag(β M-1 I l , β M-2 I l , … βI l , I l )

[0083] β L = diag(β L-1 , β L-2 , … β, 1)

[0084] Specifically, β Y is the output forgetting matrix; β L is the right forgetting matrix.

[0085] Define the variable θ β based on the above forgetting factor. Specifically, the variable of the above forgetting factor can be represented by the following formula:

[0086] θ β = βθθ p β L

[0087]

[0088] β θ = diag(β M-1 I l , β M-2 I l , … βI l , I l )

[0089] Among them, β θ is the variable forgetting matrix.

[0090] Determine the output matrix corresponding to the past k moments. Specifically, the output matrix corresponding to the past k moments can be represented by the following matrix:

[0091]

[0092] In specific implementation, based on the output matrix corresponding to the past k moments, the variable θ of the forgetting factor β is represented by a matrix. Specifically, the variable θ of the forgetting factor β is represented by the following matrix:

[0093]

[0094] Furthermore, according to the output matrix with the forgetting factor corresponding to the past k moments and the output matrix with the forgetting factor corresponding to the kth moment, determine the set corresponding to the output matrix with the forgetting factor, that is, the Toeplitz matrix with the forgetting factor corresponding to the current time period. Specifically, the Toeplitz matrix with the variable forgetting factor introduced in the current time period can be represented by the following formula K:

[0095]

[0096]

[0097] Step 31: Perform singular value decomposition on the Toeplitz matrix with the variable forgetting factor introduced in the current time period to obtain the observable matrix corresponding to the current time period.

[0098] After obtaining the Toeplitz matrix with the variable forgetting factor introduced in the current time period, perform singular value decomposition (Singular Value Decomposition, abbreviated as SVD) on it to obtain the observable matrix corresponding to the current time period. Specifically, the observable matrix corresponding to the current time period can be represented by the following formula:

[0099]

[0100] In the above formula, S ∈ R lM×lM and D ∈ R lM×lM are orthogonal matrices, V is a diagonal matrix with non-zero singular values arranged in descending order. Therefore, the rank of the original estimation matrix can be determined by the V matrix, and the zero singular values and their corresponding singular value vectors can be omitted. Therefore, the observable matrix Γ M in the Toeplitz matrix corresponding to the current time period and the controllable matrix O M can be simplified to S 1 、V 1 、D1 The product, where S 1 ∈R lM×n 、V 1 ∈R n×n 、D 1 ∈R n×lM , where l is the number of measurement points and n is the dimension of the V 1 matrix dimension.

[0101] Specifically, the observable matrix Γ in the Toeplitz matrix corresponding to the current time period above M can be represented by the following formula:

[0102]

[0103] Step 32, obtain the preset parameters corresponding to the current time period according to the observable matrix corresponding to the current time period.

[0104] Specifically, the above step 32 can be implemented by the following steps 40 - 42:

[0105] Step 40, based on the observable matrix corresponding to the current time period, determine the state matrix corresponding to the current time period.

[0106] When the above observable matrix Γ in the Toeplitz matrix corresponding to the current time period is obtained M After that, according to the above observable matrix Γ M the state matrix A corresponding to the current time period (such as the first time period) can be obtained. Specifically, the above state matrix A can be represented by the following formula:

[0107]

[0108] In the above formula, is the pseudo-inverse of the above observable matrix.

[0109] Step 41, perform eigenvalue decomposition on the state matrix to obtain the eigenvalues corresponding to the state matrix.

[0110] Specifically, the eigenvalues corresponding to the above state matrix can be determined by the following formula:

[0111] A = ΦRΦ -1

[0112] where Φ is the eigenvector of the above state matrix A; R is the eigenvalue of the above state matrix A.

[0113] Step 42, obtain the preset parameters corresponding to the current time period according to the eigenvalues corresponding to the state matrix.

[0114] After obtaining the eigenvalues corresponding to the above state matrix, the modal frequency matrix f and the damping ratio matrix ε can be obtained. Specifically, the above modal frequency matrix f and the above damping ratio matrix ε can be determined by the following formula:

[0115]

[0116]

[0117] Among them, the above damping ratio matrix ε is a preset parameter corresponding to the current time period; |…| is the modulus of the above real number.

[0118] Step 33: Determine the combination of preset parameters corresponding to each time period in multiple time periods as the modal parameters under the preset working condition.

[0119] Specifically, after obtaining the preset parameters corresponding to the above current time period, it is also necessary to determine the combination of preset parameters corresponding to each time period to determine the modal parameters under the preset working condition. In specific implementation, the above step 33 is implemented through the following steps 50-53:

[0120] Step 50: Determine the observed output vector of the changing time period.

[0121] In specific implementation, let j = 1, 2, …, then the observed output vector of the changing time period can be obtained, that is, the recursive observed output vector. Among them, the recursive observed output vector can be represented by the following formula as:

[0122]

[0123] Step 51: Based on the above output matrix at time k and the above recursive observed output vector determine the updated Toeplitz matrix.

[0124] Specifically, in the process of determining the second time period in multiple time periods as the new first time period until the last time period in multiple time periods is determined as the new first time period, an updated above output matrix will be continuously formed (that is, the output matrix corresponding to the above current time period will be continuously updated). Specifically, the above updated output matrix can be represented by the following formula:

[0125]

[0126]

[0127] Among them, is Moment output matrix; θ β (j) is the past Moment output matrix.

[0128] Step 52, according to the updated moment output matrix, and the set corresponding to the output matrix at the above-mentioned k moment, determine the set corresponding to the above output matrix.

[0129] Specifically, the set corresponding to the above output matrix can be represented by the following formula K:

[0130]

[0131] Step 53, according to the updated output matrix and the set corresponding to the above output matrix, obtain an updatable observable matrix, and determine the modal parameters under the preset working conditions.

[0132] Specifically, when the above updated output matrix is obtained, an updatable observable matrix can be obtained. Specifically, the above updatable observable matrix is represented by the following formula:

[0133]

[0134] When the above updatable observable matrix is obtained, the above updatable state matrix A can be represented by the following formula:

[0135]

[0136] In the above formula, is the pseudo-inverse of the above updatable observable matrix.

[0137] According to the updatable state matrix A, an updatable preset parameter can be obtained. The step of obtaining the updatable preset parameter according to the updatable state matrix A is the same as the step of obtaining the preset parameter corresponding to the current time period in the above step 32, and will not be repeated here. Then, the combination of the preset parameters corresponding to each time period in multiple time periods is determined as the modal parameters under the preset working conditions. At this time, time-varying modal parameters can be obtained, rather than a stable modal parameter value.

[0138] Step S206, based on the preset threshold parameter, determine the accuracy of the modal parameter identification under each preset working condition.

[0139] Furthermore, after the step of determining the modal parameters of the target engineering structure under each preset working condition, the accuracy of the modal parameter identification under each preset working condition can also be determined based on the preset threshold parameter to verify the accuracy of the above method for determining the modal parameters. Among them, the above preset threshold parameter is the theoretical value of the above modal parameter.

[0140] In specific implementation, the above-mentioned target engineering structure may be a numerical model implemented through finite element numerical simulation. Specifically, the above-mentioned target engineering structure may be a four-story frame structure established based on the laboratory frame structure and using finite element software. Among them, the monitoring data under each of the above-mentioned preset working conditions may be the time-varying free decay response signal, the time-invariant free decay response signal, and the sudden free decay response signal obtained through transient dynamic time history analysis. The time-varying, time-invariant, and sudden are for each of the above-mentioned preset working conditions.

[0141] Specifically, the above-mentioned theoretical value is the theoretical modal parameter corresponding to the monitoring data under each preset working condition.

[0142] In specific implementation, based on the preset threshold parameter, the accuracy of the modal parameter under each preset working condition can be determined through the following steps 60-63:

[0143] Step 60: Based on the monitoring data under each preset working condition, determine the theoretical value of the modal parameter under each preset working condition. Specifically, the above-mentioned theoretical value is determined through the following formula:

[0144]

[0145] Among them, ξ m is generally the first-order damping ratio of the structure; ξ n is generally the second-order damping ratio of the structure; ω m generally takes the first-order frequency of the structure; ω n generally takes the second-order frequency of the structure; a 1 and a 2 are proportional constants, and the units are s -1 and s respectively.

[0146] By changing the values of a 1 and a 2 to determine the first-order damping ratio of the high-rise structure.

[0147] Step 61: According to the above-mentioned theoretical value, define the maximum absolute error. Specifically, the above-mentioned maximum absolute error is determined through the following formula: e 1 =|ξ t -ξ c |. Among them, e 1 is the maximum absolute error, ξ t is the theoretical damping ratio under the current preset working condition (i.e., the above-mentioned theoretical value of the modal parameter), and ξ c is the identified damping ratio under the current preset working condition (i.e., the modal parameter under each preset working condition determined based on the monitoring data under each preset working condition).

[0148] Step 62: Determine the standard error e of the modal parameters under each preset condition according to the above theoretical damping ratio and the above identified damping ratio. 2 Specifically, the standard error of the above modal parameters is determined by the following formula:

[0149]

[0150] wherein, in the above formula, T is the symbol identifier of matrix transpose, and (ξ t - ξ c ) T is the transposed matrix, and N is the number of rows or columns of the matrix.

[0151] Step 63: Determine the accuracy of the modal parameter identification under each preset condition according to the above maximum absolute error and the above standard error.

[0152] Specifically, the value of the identified damping ratio under the current preset condition can be determined through the above step S204, and then based on the value of the identified damping ratio and the value of the above theoretical damping ratio, the above maximum absolute error and the above standard error are determined. After that, according to the magnitudes of the value of the above maximum absolute error and the value of the above standard error, the accuracy of the modal parameters under each preset condition is determined.

[0153] Furthermore, the value of the identified damping ratio under the current preset condition can also be determined by a method based on the short-time time-invariant assumption, and by comparing the maximum absolute error and the standard error between the identified damping ratio and the theoretical damping ratio, it is determined which one of the method based on the short-time time-invariant assumption and the method described in the above step S204 is optimal. Optionally, the above modal parameters can be determined according to the monitoring data corresponding to a higher time resolution (i.e., the interval time between every two time periods is longer), and then which method is optimal is determined according to the magnitudes of the maximum absolute error and the standard error. When the magnitudes of the value of the above maximum absolute error and the value of the above standard error are smaller, it indicates that the accuracy of the modal parameters under each preset condition determined by the method for determining the modal parameters is higher.

[0154] Step S208: For each preset condition, determine the relative change relationship between the monitoring data under the current condition and the modal parameters corresponding to the monitoring data.

[0155] Specifically, when the monitoring data under each preset working condition is obtained, the change result corresponding to the monitoring data under each preset working condition can be obtained. The above change result will gradually tend to be stable. Therefore, in this embodiment, the time period corresponding to before the above change result tends to be stable is the preset time period. When the modal parameters of the above target engineering structure under each preset working condition are obtained, the parameter change trend indicated by the preset parameter corresponding to each time period in the modal parameter can be obtained. Further, the parameter change trend in the preset time period corresponding to the above change result can be determined.

[0156] When the parameter change trend corresponding to each preset working condition and the change result corresponding to the current preset working condition are obtained, by comparing the above parameter change trend with the above change result, the relative change relationship between the above parameter change trend and the above change result can be obtained.

[0157] Step S210, determine the relevant factors of the abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition.

[0158] When the parameter change trend corresponding to the above preset parameter and the change result corresponding to the above monitoring data are obtained, by comparing the above parameter change trend with the above change result, the relative change relationship between the above parameter change trend and the above change result can be obtained, which can be used to infer the cause of the abnormal vibration of the target engineering structure.

[0159] The method for analyzing the relevant factors of the abnormal vibration of an engineering structure provided by the embodiment of the present invention can also obtain accurate results based on the modal parameters with too rapid changes, and there is no need to further subdivide the time period. Furthermore, it can accurately and quickly analyze based on the data of the high-rise structure and the modal parameters with too rapid changes to explain the possible reasons for the abnormal vibration of the high-rise structure.

[0160] For the above embodiment, the present invention provides a method for analyzing the relevant factors of the abnormal vibration of an engineering structure, which is implemented on the basis of the above method. This method focuses on describing the specific process of determining the relative change relationship between the monitoring data under the current working condition and the modal parameters corresponding to the monitoring data (implemented through the following steps S306 - S312), and determining whether there is a correlation between the monitoring data of the target engineering structure and the modal parameters corresponding to the monitoring data. As Figure 3 shown, this method includes the following steps:

[0161] Step S302, collect the monitoring data of the target engineering structure under multiple preset working conditions according to the preset data acquisition unit.

[0162] Specifically, the above-mentioned target engineering structure can be an actual four-story frame. When the above-mentioned target engineering structure is an actual four-story frame, the above-mentioned preset data acquisition unit is an acceleration acquisition system, which includes an acceleration sensor and acquisition equipment. Among them, the above-mentioned acceleration sensor selects the 941B ultra-low frequency vibration pickup of the Institute of Engineering Mechanics, China Earthquake Administration, and the above-mentioned acquisition equipment can select products of National Instruments (abbreviated as NI). Further, the above-mentioned acceleration acquisition system also includes an acquisition board and an acquisition slot. The acquisition board selects NI-9234, and the above-mentioned acquisition slot can select c-DAQ 9185. When the above-mentioned acquisition equipment acquires data, the corresponding acquisition program can be a self-compiled LabVIEW program, which includes a channel setting module, a real-time monitoring module of the acquisition status, a data storage module, and a data processing module.

[0163] In specific implementation, the above-mentioned target engineering structure can be vibrated by the way of pulling rope excitation. Specifically, a rope is pulled on the side of the structure and quickly released. The pulling rope excitation method is to fix the side steel rope of the actual four-story frame to make the above-mentioned target engineering structure do free decay vibration.

[0164] In specific implementation, there are 4 acceleration sensors corresponding to the above-mentioned preset data acquisition unit, and they are respectively arranged on each layer frame corresponding to the above-mentioned target engineering structure. Then, the above-mentioned target engineering structure is made to do free decay vibration by the way of pulling rope excitation. Then, the voltage signals output by different sensors are simultaneously acquired by the acquisition equipment corresponding to the preset data acquisition unit, and the monitoring data measured by the above-mentioned 4 acceleration sensors are recorded and saved. At this time, the free decay signal of the above-mentioned target engineering structure is acquired.

[0165] Further, after the monitoring data of the above-mentioned target engineering structure is acquired, the monitoring data needs to be preprocessed to obtain the preprocessed monitoring data. Specifically, the way to preprocess the monitoring data under each above-mentioned preset working condition is to remove the trend item of the above-mentioned monitoring data. During the free decay vibration of the above-mentioned target engineering structure, the acquired monitoring data will hide some environmental interference signals, such as the unstable low-frequency performance outside the working frequency of the above-mentioned preset data acquisition unit and the interference of the surrounding environment on the above-mentioned preset data acquisition unit. Under the action of the above various influencing factors, the data often deviates from the baseline, and it is also possible that the deviated baseline will change with time. This deviation is called the trend item of the monitoring data. Since the correctness of the data analysis result is directly affected by the trend item, it is necessary to eliminate the trend item to realize the preprocessing of the data.

[0166] Specifically, in this embodiment, the above-mentioned target engineering structure can also be a real high-rise building. When the above-mentioned target engineering structure is a real high-rise building, the above-mentioned preset data acquisition unit is a distributed synchronous acquisition system, which is generally composed of a data acquisition subsystem, a data transmission subsystem and an automatic data processing subsystem module. In this embodiment, measuring points are arranged on individual floors of the above-mentioned real high-rise building. Among them, the specific number of floors with measuring points can be set according to user needs. Further, the high-rise structure of the above-mentioned high-rise building may include loads, such as masts. Therefore, measuring points are also arranged at the load positions of the above-mentioned high-rise building, and then the monitoring data of the measuring points arranged on the above-mentioned individual floors and the monitoring data of the measuring points arranged at the above-mentioned load positions are collected.

[0167] Further, the above-mentioned target engineering structure can be made to vibrate by the excitation method of an active mass damper (AMD for short). Specifically, the above-mentioned active mass damper feeds back the structural response or feeds forward the external excitation at key positions in the structure, or both the feedback of the structural response and the feed forward of the external excitation at key positions in the structure. After computer analysis and processing, appropriate information is sent to the actuator (connecting the mass block and the structure), so that the actuator counteracts the mass block and applies inertial control force to the structure to achieve vibration control.

[0168] When the above-mentioned target engineering structure vibrates by the AMD excitation method, the excitation is mainly applied to the peripheral structure of the above-mentioned individual floors of the above-mentioned high-rise building. For example, the AMD excitation device is placed on the periphery of the 70th or 71st floor of the high-rise building for excitation.

[0169] Further, the above-mentioned target engineering structure can also be made to vibrate by the cable excitation method. The cable excitation method is to fix one end of the steel cable at a certain position of the mast, tie the other end to the excitation device, and place the excitation device on the top of the high-rise structure. Then, a periodic tensile force is applied to the cable connection point of the mast through the steel cable.

[0170] Step S304: Based on the monitoring data under each preset working condition, determine the modal parameters of the target engineering structure under each preset working condition.

[0171] After obtaining the monitoring data under each preset working condition through the above excitation method, according to the above monitoring data under each preset working condition, determine the modal parameters under the current preset working condition. The determination method of the modal parameters of the above-mentioned target engineering structure under each preset working condition is the same as that in step S204, and will not be elaborated here.

[0172] Step S306: For each preset working condition, determine the change result corresponding to the monitoring data under the current working condition according to the monitoring data under the current working condition.

[0173] Step S308: Determine the corresponding modal parameters under the current working condition according to the monitoring data under the current working condition.

[0174] Step S310: Based on the modal parameters and the change result, obtain the relative change relationship.

[0175] In specific implementation, after obtaining the preprocessed monitoring data corresponding to each of the above preset working conditions, the change result corresponding to the monitoring data under each preset working condition can be obtained, that is, the change curve of the monitoring data. Further, the above change result will gradually tend to be stable. Among them, the time period corresponding before the above change result tends to be stable is the change threshold time period.

[0176] In addition, the embodiments of the present invention can determine the modal parameters based on the method of step S204 above. After obtaining the modal parameters of the above target engineering structure under each preset working condition, further, the parameter change trend in the change threshold time period corresponding to the above change result can be determined. The above parameter change trend is also the change curve of the preset parameter.

[0177] When the parameter change trend corresponding to each preset working condition and the change result corresponding to the current preset working condition are obtained, compare the above parameter change trend with the above change result to determine whether the change result corresponding to the above monitoring data is related to the above modal parameters. The relationship between the change result and the above modal parameters is the relative change relationship. That is, at this time, the relative change relationship between the above parameter change trend and the above change result can be obtained.

[0178] Step S312: Obtain the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition among multiple preset working conditions.

[0179] Step S314: Determine the correlation degree between the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition.

[0180] Specifically, select two of the above multiple preset working conditions for operation. In this embodiment, the above two preset working conditions can be the vibration states of the engineering structure vibration of the above target engineering structure under different excitation methods or the same excitation method; determining the above two preset working conditions is to guess whether the relevant factors of the abnormal vibration of the above target engineering structure are the existing loads (such as the mast of a high-rise structure). For example, when the above load is not removed from the high-rise structure building, the vibration state corresponding to the tower of the high-rise structure building, and when the above load is not removed from the high-rise structure building, the vibration state corresponding to the mast of the high-rise structure building.

[0181] The above two preset working conditions may also be the vibration states of the target engineering structure with engineering structure vibration under different excitation modes or the same excitation mode when the target engineering structure lacks load (such as the mast of a high-rise structure) and the part of the structure that is not lacking (such as the mast of a high-rise structure); determining the above two preset working conditions lies in further determining whether the relevant factors of the target engineering structure are the existing loads (such as the mast of a high-rise structure). For example, when the above load of a high-rise building is removed, the corresponding vibration state of the tower of the high-rise building, and when the above load of the high-rise building is not removed, the corresponding vibration state of the tower of the high-rise building.

[0182] In specific implementation, the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition are obtained.

[0183] In this embodiment, the change result corresponding to the first preset working condition and the change result corresponding to the second preset working condition can be determined, and the correlation between the change results corresponding to the two preset working conditions can be determined to determine whether the target engineering structure is related to the existing load (such as the mast of a high-rise structure), where the above correlation is the degree of correlation.

[0184] Step S316, based on the degree of correlation, determine the relevant factors for the abnormal vibration of the target engineering structure.

[0185] In specific implementation, the loads of the high-rise building corresponding to the first preset working condition and the second preset working condition in the above two preset working conditions are both in the non-removed state, the monitoring data corresponding to the first preset working condition is the monitoring data of the tower of the high-rise building, and the monitoring data corresponding to the second preset working condition is the monitoring data of the load of the high-rise building.

[0186] Furthermore, both the first preset working condition and the second preset working condition correspond to a relative change relationship, as well as the change result and the parameter change trend in the relative change relationship.

[0187] In specific implementation, determine whether there is a correlation between the parameter change trend corresponding to the first preset working condition and the parameter change trend corresponding to the second preset working condition, and determine whether there is a correlation between the change result corresponding to the first preset working condition and the change result corresponding to the second preset working condition.

[0188] When there is a high correlation between the parameter change trends and the change results of the first preset working condition and the second preset working condition respectively, it is preliminarily determined that the position corresponding to the data collected in the second preset working condition is related to the abnormal vibration of the target engineering structure, that is, the load (such as the mast) of the high-rise building may be related to the abnormal vibration of the target engineering structure.

[0189] Furthermore, remove the load (such as the mast) of the above-mentioned high-rise building structure to further determine whether the removed load is related to the abnormal vibration of the above-mentioned target engineering structure.

[0190] In specific implementation, remove the load of the above-mentioned high-rise building structure, and determine the preset working condition as the new second preset working condition, that is, the vibration state of the above-mentioned high-rise building tower corresponding to the new second preset working condition. At this time, the first preset working condition is the vibration state of the above-mentioned high-rise building tower when the load of the above-mentioned high-rise building structure is in the non-removed state.

[0191] Specifically, determine the correlation degree between the change result corresponding to the above-mentioned first preset working condition and the change result corresponding to the above-mentioned new second preset working condition. When the change result corresponding to the above-mentioned first preset working condition is not related to the change result corresponding to the above-mentioned new second preset working condition, it can be determined that the removed load is related to the abnormal vibration of the above-mentioned target engineering structure, and at this time, determine the relevant factors of the abnormal vibration of the above-mentioned target engineering structure.

[0192] A method for analyzing relevant factors of abnormal vibration of an engineering structure provided by the present invention first guesses whether a load (such as a mast) is a relevant factor for abnormal vibration of a target engineering structure based on the correlation degree of the relative change relationship corresponding to two preset working conditions, and then determines whether a collection position is a relevant factor for abnormal vibration of a target engineering structure according to the correlation degree corresponding to two preset working conditions at the same collection position. When the correlation degree of the preset working conditions corresponding to different collection positions is high, it is initially guessed that one of the collection positions is the relevant factor, and then the structure at the collection position is removed to verify whether the collection position is a relevant factor for abnormal vibration of the target engineering structure. When the above-mentioned correlation degree decreases after removal, it indicates that the removed structure is a relevant factor for abnormal vibration of the target engineering structure, and explains the possible reasons for the abnormal vibration of the engineering structure.

[0193] Based on the above system embodiment, an embodiment of the present invention further provides an apparatus for analyzing relevant factors of abnormal vibration of an engineering structure; as Figure 4 shown, the apparatus includes:

[0194] A data acquisition module 401, configured to acquire monitoring data of a target engineering structure under multiple preset working conditions according to a preset data acquisition unit.

[0195] A modal parameter determination module 402, configured to determine modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition; the modal parameters correspond to preset parameters corresponding to multiple time periods.

[0196] A relative relationship determination module 403 is configured to determine, for each preset working condition, the relative change relationship between the monitoring data and the modal parameters corresponding to the monitoring data under the current working condition.

[0197] A factor determination module 404 is configured to determine the relevant factors for the abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition.

[0198] The above-mentioned device for determining the relevant factors for the abnormal vibration of the high-rise structure first collects the monitoring data of the target engineering structure under multiple preset working conditions, and determines the modal parameters corresponding to each preset working condition of the target engineering structure based on the monitoring data under each preset working condition. Then, for each preset working condition, it determines the relative change relationship between the monitoring data within a preset time period under the current working condition and the modal parameters corresponding to the monitoring data, and determines the relevant factors for the abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each preset working condition. This method combines the degree of correlation between the changes in the monitoring data and the modal parameters. In addition, the above-mentioned modal parameters are composed of preset parameters corresponding to multiple time periods, and experiments are carried out based on the preset parameters corresponding to multiple time periods, making the modal parameter data more comprehensive to determine the possible reasons for the abnormal vibration of the engineering structure.

[0199] An embodiment of the present invention further provides an electronic device, as Figure 5 shown. The electronic device includes a processor 101 and a memory 100. The memory 100 stores machine-executable instructions that can be executed by the processor 101, and the processor 101 executes the machine-executable instructions to implement the above-mentioned method for analyzing the relevant factors of the abnormal vibration of the engineering structure.

[0200] Furthermore, Figure 5 the terminal device shown further includes a bus 102 and a communication interface 103. The processor 101, the communication interface 103, and the memory 100 are connected through the bus 102.

[0201] Among them, the memory 100 may include a high-speed random access memory (RAM, Random Access Memory), and may also include a non-volatile memory, such as at least one disk memory. Through at least one communication interface 103 (which can be wired or wireless), a communication connection is realized between this system network element and at least one other network element, and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 102 can be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity of representation, Figure 5 only a bidirectional arrow is shown in

[0202] The processor 101 may be an integrated circuit chip with the ability to process signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor 101 or the instructions in the form of software. The above-mentioned processor 101 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by the combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 100, and the processor 101 reads the information in the memory 100 and combines its hardware to complete the steps of the method in the foregoing embodiments.

[0203] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing relevant factors of abnormal vibration of an engineering structure, characterized in that, the method includes: Collecting monitoring data of the target engineering structure under a variety of preset working conditions according to a preset data acquisition unit; Based on the monitoring data under each of the preset working conditions, determining the modal parameters of the target engineering structure under each of the preset working conditions; the modal parameters are preset parameters corresponding to multiple time periods; For each of the preset working conditions, determining the relative change relationship between the monitoring data under the current working condition and the modal parameters corresponding to the monitoring data; Determining the relevant factors of abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each of the preset working conditions; Wherein, the relative change relationship includes the change result corresponding to the monitoring data under each of the preset working conditions, and the modal parameters corresponding to the monitoring data under each of the preset working conditions; the step of determining the relevant factors of abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each of the preset working conditions includes: Obtaining the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition among the multiple preset working conditions; Determining the degree of correlation between the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition; Based on the degree of correlation, determining the relevant factors of abnormal vibration of the target engineering structure; Wherein, the step of determining the relative change relationship between the monitoring data under the current working condition and the modal parameters corresponding to the monitoring data includes: Determining the change result corresponding to the monitoring data under the current working condition according to the monitoring data under the current working condition; Determining the corresponding modal parameters under the current working condition according to the monitoring data under the current working condition; Based on the modal parameters and the change result, obtaining the relative change relationship.

2. The method according to claim 1, characterized in that, the step of determining the modal parameters of the target engineering structure under each of the preset working conditions based on the monitoring data under each of the preset working conditions includes: For each of the preset working conditions among the multiple preset working conditions, perform the following operations: Selecting the monitoring data of the free decay section from the monitoring data under the preset working condition; there are monitoring data corresponding to multiple time periods in the monitoring data of the free decay section; Based on the monitoring data corresponding to the first time period among the multiple time periods, determining the Hankel matrix corresponding to the first time period; According to the Hankel matrix corresponding to the first time period, obtaining the Toeplitz matrix corresponding to the first time period; Determining the second time period among the multiple time periods as the new first time period, and continuing to execute the step of determining the Hankel matrix corresponding to the first time period based on the monitoring data corresponding to the first time period among the multiple time periods until the last time period among the multiple time periods is determined as the new first time period, and obtaining the Toeplitz matrix corresponding to the last time period; Determine the modal parameters under the preset working conditions based on the Toeplitz matrix corresponding to each of the multiple time periods.

3. The method according to claim 2, wherein, the step of determining the modal parameters under the preset working conditions based on the Toeplitz matrix corresponding to each of the multiple time periods includes: For each of the multiple time periods, perform the following operations: Introduce a variable forgetting factor into the Toeplitz matrix corresponding to the current time period to obtain a Toeplitz matrix with a variable forgetting factor corresponding to the current time period; Perform singular value decomposition on the Toeplitz matrix with a variable forgetting factor corresponding to the current time period to obtain an observable matrix corresponding to the current time period; Obtain the preset parameters corresponding to the current time period according to the observable matrix corresponding to the current time period; Determine the combination of the preset parameters corresponding to each of the multiple time periods as the modal parameters under the preset working conditions.

4. The method according to claim 3, wherein, the step of obtaining the preset parameters corresponding to the current time period according to the observable matrix corresponding to the current time period includes: Determine the state matrix corresponding to the current time period based on the observable matrix corresponding to the current time period; Perform eigenvalue decomposition on the state matrix to obtain the eigenvalues corresponding to the state matrix; Obtain the preset parameters corresponding to the current time period according to the eigenvalues corresponding to the state matrix.

5. The method according to claim 2, wherein, each time period includes multiple moments; the step of determining the second time period among the multiple time periods as the new first time period includes: Determine the second moment in the first time period as the first moment in the second time period; Based on the first moment in the second time period, obtain the initial moment corresponding to the new first time period; Determine the new first time period according to the initial moment corresponding to the new first time period.

6. The method according to claim 1, wherein, after the step of determining the modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition, the method further includes: Determine the accuracy of the modal parameters under each preset working condition based on preset threshold parameters.

7. An analysis device for related factors of abnormal vibration of an engineering structure, wherein, the device includes: A data acquisition module for acquiring monitoring data of a target engineering structure under multiple preset working conditions according to a preset data acquisition unit; A modal parameter determination module for determining the modal parameters of the target engineering structure under each preset working condition based on the monitoring data under each preset working condition; the modal parameters are preset parameters corresponding to multiple time periods. A relative relationship determination module, configured to determine, for each of the preset working conditions, the relative change relationship between the monitoring data and the modal parameters corresponding to the monitoring data under the current working condition; A factor determination module, configured to determine the relevant factors for the abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each of the preset working conditions; Wherein, the relative change relationship includes the change result corresponding to the monitoring data under each of the preset working conditions, and the modal parameters corresponding to the monitoring data under each of the preset working conditions; the step of determining the relevant factors for the abnormal vibration of the target engineering structure according to the relative change relationship corresponding to each of the preset working conditions includes: obtaining the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition among the multiple preset working conditions; determining the correlation degree between the relative change relationship corresponding to the first preset working condition and the relative change relationship corresponding to the second preset working condition; based on the correlation degree, determining the relevant factors for the abnormal vibration of the target engineering structure; Wherein, the step of determining the relative change relationship between the monitoring data and the modal parameters corresponding to the monitoring data under the current working condition includes: determining the change result corresponding to the monitoring data under the current working condition according to the monitoring data under the current working condition; determining the corresponding modal parameters under the current working condition according to the monitoring data under the current working condition; based on the modal parameters and the change result, obtaining the relative change relationship.

8. An electronic device Characterized in that The electronic device includes a processor and a memory, the memory stores machine-executable instructions that can be executed by the processor, and the processor executes the machine-executable instructions to implement the method for analyzing relevant factors of abnormal vibration of an engineering structure according to any one of claims 1 to 6.

Images