Strain-vertical deflection conversion method for high-density measuring points on the main beam of π-type composite beam bridge

Abstract

The present invention discloses a method for converting the strain of high-density measuring points of the main beam of a π-type composite beam bridge into vertical deflection. The method uses BOTDA technology to collect strain monitoring data at different measuring points of the main beam, constructs a high-density measuring point strain monitoring data set, adopts discrete wavelet transform to realize low-frequency and high-frequency signal division, uses a soft-hard threshold function-FastICA joint algorithm to remove high-frequency signal noise, reconstructs the strain monitoring data set, relies on the energy variation principle, corrects the normal stress calculation method in the Euler-Bernoulli Beam theory, constructs a π-type composite beam bridge main beam deflection correction coefficient considering the shear lag effect, uses the virtual conjugate beam theory to calculate the vertical deflection of the main beam of the π-type composite beam bridge, and realizes the effective acquisition of the deflection data of the π-type composite beam bridge structure. The method solves the problems of uneven distribution of deflection data of existing π-type composite beam bridges, complex data interpretation, and inaccuracy due to environmental factors.

Description

Technical Field

[0001] The invention belongs to the field of bridge structure disease monitoring and relates to a method for realizing conversion between strain data and deflection data of a π-type composite beam bridge structure. Background Art

[0002] The application of deflection data in bridge engineering covers many aspects, from structural health monitoring to damage detection, providing engineers with valuable information. First, deflection data plays a vital role in the daily monitoring and maintenance of bridge structures. By monitoring the deflection of the bridge in real time, engineers can detect structural deformation, cracks or fatigue in a timely manner, and achieve a comprehensive assessment of the structural health. This helps to take timely maintenance measures to prevent potential structural damage and increase the service life of the bridge. Second, deflection data plays a key role in structural damage detection. By comparing the measured deflection with the designed deflection, engineers can identify whether the structure is damaged and then determine whether its performance meets the design requirements. This method is highly sensitive and can detect small structural changes, providing a reliable basis for accurate damage assessment. However, compared with other bridge types, π-type composite beam bridges face some unique problems in deflection data acquisition. First, the structure of π-type composite beam bridges is usually complex, with multiple supports and intersections, resulting in uneven deflection distribution, which increases the complexity of data interpretation. Second, environmental factors also pose challenges to deflection data acquisition, especially wind loads and temperature changes. Under the action of wind, the π-type composite beam bridge is susceptible to lateral vibration, resulting in instability of deflection deformation. Structural expansion and contraction caused by temperature changes may lead to errors in deflection data, which need to be corrected in data analysis. In summary, considering the importance of deflection data in bridge structure disease monitoring, in order to ensure the safety of the π-type composite beam bridge structure during operation, it is urgent to obtain effective deflection data of the π-type composite beam bridge structure, overcome environmental interference and complex structural characteristics, and ensure reliable structural health information.

[0003] With the emergence of advanced bridge structure monitoring technology and equipment, the technology for acquiring deflection data of π-type composite beam bridge structures has also been developed. However, due to many problems in acquiring deflection data of π-type composite beam bridge structures, it is difficult to ensure the damage diagnosis effect of π-type composite beam bridge structures based on deflection data. Considering that the strain data of π-type composite beam bridge structures can detect minor damage, it is more sensitive to structural health monitoring and damage diagnosis, and the measurement is relatively simple and not affected by the environment, from this perspective, the conversion between strain data and deflection data of π-type composite beam bridge structures can be realized through some technical means, which can undoubtedly realize the effective acquisition of deflection data of π-type composite beam bridge structures. Summary of the invention

[0004] In view of the shortcomings of the above-mentioned existing π-type composite beam bridge structure deflection data acquisition method, the present invention provides a π-type composite beam bridge main beam high-density measurement point strain-vertical deflection conversion method. The method solves the problems of uneven distribution of existing π-type composite beam bridge deflection data, complex data interpretation, and inaccuracy due to environmental factors, and can achieve effective acquisition of π-type composite beam bridge structure deflection.

[0005] The objective of the present invention is achieved through the following technical solutions:

[0006] A method for converting strain-vertical deflection of a main beam of a π-type composite beam bridge with high-density measuring points, comprising the following steps:

[0007] Step 1: According to the design and construction drawings of the π-type composite beam bridge, the distributed strain sensing optical fiber of the main beam is laid out, and the strain monitoring data at different measuring points of the main beam are collected by using the BOTDA technology to construct a high-density measuring point strain monitoring data set;

[0008] Step 2: Based on the high-density measurement point strain monitoring data set constructed in step 1, discrete wavelet transform is used to realize the division of low-frequency and high-frequency signals, and the soft and hard threshold function-FastICA joint algorithm is used to remove high-frequency signal noise and reconstruct the strain monitoring data set;

[0009] Step 3: Based on the energy variation principle, the normal stress calculation method in the Euler-Bernoulli Beam theory is modified to construct the deflection correction coefficient of the main beam of the π-type composite beam bridge considering the shear lag effect;

[0010] Step 4: Based on the strain monitoring data set reconstructed in step 2 and the main beam deflection correction coefficient constructed in step 3, the vertical deflection of the main beam of the π-type composite beam bridge is calculated using the virtual conjugate beam theory.

[0011] Compared with the prior art, the present invention has the following advantages:

[0012] The present invention can effectively collect strain data of π-type composite beam bridge structures, complete the conversion of bridge structure strain data into deflection data, and realize the effective acquisition of deflection data of π-type composite beam bridge structures, and is suitable for structural status diagnosis and disease monitoring of π-type composite beam bridges. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a flow chart of the strain-vertical deflection conversion method for high-density measuring points on the main beam of a π-type composite beam bridge.

[0014] Figure 2 Schematic diagram of a π-type composite beam bridge.

[0015] Figure 3 This is a schematic diagram of the cross section of the main beam of a π-type composite beam bridge.

[0016] Figure 4 Schematic diagram of the distributed sensing optical fiber layout of the main beam of a π-type composite beam bridge.

[0017] Figure 5 This is the finite element model diagram of the main beam of the π-type composite beam bridge.

[0018] Figure 6 The calculation results of the high-density measuring point strain-vertical deflection conversion method for the main beam of a π-type composite beam bridge are shown in Figure 2.

[0019] Figure 7 It is a schematic diagram of the relative error between the calculation results of the method of the present invention and the finite element model. DETAILED DESCRIPTION

[0020] The technical solution of the present invention is further described below in conjunction with the accompanying drawings, but is not limited thereto. Any modification or equivalent replacement of the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention should be included in the protection scope of the present invention.

[0021] The present invention provides a method for converting the strain of high-density measuring points of the main beam of a π-type composite beam bridge to vertical deflection. The method uses the BOTDA technology to collect strain monitoring data at different measuring points of the main beam, constructs a high-density measuring point strain monitoring data set, uses discrete wavelet transform to achieve low-frequency and high-frequency signal division, uses a soft-hard threshold function-FastICA joint algorithm to remove high-frequency signal noise, reconstructs the strain monitoring data set, relies on the energy variation principle, corrects the normal stress calculation method in the Euler-Bernoulli Beam theory, constructs a π-type composite beam bridge main beam deflection correction coefficient considering the shear lag effect, uses the virtual conjugate beam theory to calculate the vertical deflection of the main beam of the π-type composite beam bridge, and realizes the effective acquisition of the deflection data of the π-type composite beam bridge structure. Figure 1 As shown, the method comprises the following steps:

[0022] Step 1: According to the design and construction drawings of the π-type composite beam bridge, the distributed strain sensing optical fiber of the main beam is laid out, and the strain monitoring data at different measuring points of the main beam are collected using the BOTDA technology to construct a high-density measuring point strain monitoring data set. The specific steps are as follows:

[0023] Step 1: According to the design and construction drawings of the π-type composite beam bridge, select the top and bottom of the middle beam and the side beam, and lay the distributed strain sensing optical fiber. The number of loops and the length of the optical fiber should meet the following requirements:

[0024] N ≥ 3 (1)

[0025] L=2a·N·(l+h) (2)

[0026] Where N is the number of loops; L is the length of the laid optical fiber; a is the length correction coefficient; l is the total length of each section of the π-type composite beam bridge, in meters; h is the height of the main beam of the π-type composite beam bridge.

[0027] Step 1 and 2: According to the layout plan of the distributed strain sensing optical fiber designed in step 1, the BOTDA technology is used to collect strain monitoring data at different measuring points of the main beam to construct a high-density measuring point strain monitoring data set:

[0028] n=5l (3)

[0029] Y=[ε T1 ,ε T2 ,…ε Ti ,…ε Tn ,ε B1 ,ε B2 ,…ε Bi ,…ε Bn ] (4)

[0030] Where n is the number of measuring points; ε Ti is the vector composed of the monitoring data of the i-th measuring point on the top of the main beam, i∈(1,2,…,n); ε Bi is the vector formed by the monitoring data of the i-th measuring point at the bottom of the main beam; ε Ti and ε Bi Explained as:

[0031]

[0032]

[0033] Where m is the number of monitoring time of strain measuring points; is the strain data value of the i-th measuring point on the top of the main beam at the k-th monitoring time, k∈(1,2,…,m); is the strain data value of the i-th measuring point on the top of the main beam at the k-th monitoring moment, k∈(1,2,…,m).

[0034] Step 2: Based on the high-density measurement point strain monitoring data set constructed in step 1, discrete wavelet transform is used to realize the division of low-frequency and high-frequency signals, and the soft and hard threshold function-FastICA joint algorithm is used to remove high-frequency signal noise and reconstruct the strain monitoring data set. The specific steps are as follows:

[0035] Step 21: According to the high-density measurement point strain monitoring data set constructed in steps 1 and 2, sym4 is selected as the wavelet basis function, and the data set is subjected to discrete wavelet transform to obtain:

[0036]

[0037] In the formula, εi is the strain monitoring signal of the i-th measuring point; is the low-frequency strain signal of the i-th measuring point; is the high-frequency strain signal of the i-th measuring point. The discrete wavelet coefficients are expressed as:

[0038]

[0039] In the formula, is the discrete wavelet coefficient of the high-frequency strain monitoring signal at the i-th measuring point; is the discrete wavelet coefficient of the high-frequency strain spectrum signal at the i-th measuring point; is the discrete wavelet coefficient of the high-frequency strain noise signal at the i-th measuring point; g is the number of wavelet decomposition layers; p is the signal length.

[0040] Step 22: According to the discrete wavelet coefficients of the high-frequency strain monitoring signal at the i-th measuring point obtained in step 21, construct the soft and hard threshold functions and calculate the denoising wavelet coefficients of the high-frequency strain signal at the i-th measuring point:

[0041]

[0042] In the formula, is the wavelet coefficient for denoising the high-frequency strain signal at the i-th measuring point; sign(·) is the sign function sign; λ is the threshold.

[0043] Step 23: Based on the discrete wavelet coefficients of the high-frequency strain monitoring signal at the i-th measuring point obtained in step 21 and the denoised wavelet coefficients of the high-frequency strain signal at the i-th measuring point obtained in step 22, construct the FastICA analysis input matrix:

[0044]

[0045] Step 24: Perform FastICA analysis based on the FastICA analysis input matrix obtained in step 23 to obtain the secondary denoising wavelet coefficients of the high-frequency strain signal at the i-th measuring point Combined with the low-frequency strain signal of the i-th measuring point obtained in step 2.1 Using inverse wavelet transform, the strain monitoring data set is reconstructed:

[0046]

[0047] In the formula, is the reconstructed strain monitoring dataset; is the vector formed by the monitoring data of the i-th measuring point on the top of the main beam after noise removal; It is the vector composed of the monitoring data of the i-th measuring point at the bottom of the main beam after denoising.

[0048] Step 3: Based on the energy variation principle, the normal stress calculation method in the Euler-Bernoulli Beam theory is modified to construct the deflection correction coefficient of the main beam of the π-type composite beam bridge considering the shear lag effect. The specific steps are as follows:

[0049] Step 31: According to the geometric parameters of the cross section of the π-type composite beam, the total bending potential energy expression of the π-type composite beam is established:

[0050] Π=Ω+Ψ (12)

[0051] In the formula, Ω is the total strain energy of the π-type composite beam; Ψ is the external force potential energy of the π-type composite beam under the vertical load. Ω and Ψ are expressed as follows:

[0052]

[0053]

[0054] Where E is the elastic modulus; G is the shear modulus; ε x is the longitudinal linear strain at any point on the cross section of the π-type composite beam, ε x =-zw″+ωU′, z is the distance from the position to the neutral axis of the cross section, ω is the shear lag displacement distribution coefficient; γ xy is the shear strain at any point on the cross section of the π-type composite beam; p is the vertical load acting on the π-type composite beam; w is the deflection deformation of the π-type composite beam under the vertical load; w″ is the second-order derivative of w; U′ is the first-order derivative of the maximum shear rotation difference U of shear lag.

[0055] Step 32: According to the principle of minimum potential energy stationary value, calculate the first-order variation of the total potential energy, and set δΠ=0 to obtain the shear lag control differential equation:

[0056] EI y w″-EI zw U′+M=0 (15)

[0057] After sorting, we get:

[0058]

[0059] In the formula, I y is the moment of inertia of the π-type composite beam section; I zw is the shear hysteresis warping inertia product of the π-type composite beam section; M is the bending moment of the π-type composite beam section.

[0060] Step 33: Based on the shear lag control differential equation obtained in step 32, establish the calculation formula for the normal stress of the cross section of the π-type composite beam considering the shear lag effect:

[0061] σ x =Eε x(17)

[0062]

[0063] Step 34: Based on the cross-sectional normal stress calculation formula established in step 33 and combined with the cross-sectional normal stress calculation formula in Euler-Bernoulli Beam theory, the deflection correction coefficient of the main beam of the π-type composite beam bridge considering the shear lag effect is constructed:

[0064]

[0065] In the formula, is the correction coefficient of the main beam deflection of the π-type composite beam bridge considering the shear lag effect, σ o is the result of the cross-sectional normal stress calculation in the Euler-Bernoulli Beam theory. x and σ o Substitute the expression into equation (18) and take z = z u , z u is the distance from the top plate of the π-type composite beam to the centroidal axis, which can be obtained after sorting:

[0066]

[0067] Substituting equation (19) into equation (16), we get the second-order derivative expression of the deflection of the π-type composite beam considering the shear lag effect:

[0068]

[0069] Step 35: Based on the second-order derivative expression of the π-type composite beam deflection considering the shear lag effect obtained in step 34, establish the analytical solution of the π-type composite beam deflection based on the main beam deflection correction coefficient:

[0070]

[0071] In the formula, w 0 is the main beam deflection calculated based on Euler-Bernoulli Beam theory; w f is the initial deflection, which is usually 0.

[0072] Step 4: Based on the strain monitoring data set reconstructed in step 2 and the main beam deflection correction coefficient constructed in step 3, the vertical deflection of the main beam of the π-type composite beam bridge is calculated using the virtual conjugate beam theory. The specific steps are as follows:

[0073] Step 41: Based on the strain monitoring data set reconstructed in step 25, calculate the curvature of the cross section where each strain measurement point is located:

[0074]

[0075] Where: is the curvature value of the cross section where the i-th strain measuring point is located at the k-th monitoring moment.

[0076] Step 42: According to the actual π-type composite beam structure, an equivalent virtual conjugate beam is established. The curvature value calculated in step 41 is used as a distributed load on the virtual conjugate beam structure to calculate the internal force of the virtual conjugate beam:

[0077]

[0078]

[0079] Where: Q 0 ' k is the shear force at the left end point of the virtual conjugate beam at the kth monitoring moment; Δl is the distance between the measuring points, M a ' k is the bending moment of the section where the ath measuring point is located at the corresponding position of the virtual conjugate beam at the kth monitoring moment; M 0 ' k is the bending moment of the left end point of the virtual conjugate beam at the kth monitoring moment; M n ' k is the bending moment at the right end point of the virtual conjugate beam at the kth monitoring moment.

[0080] Step 43: Based on the strain monitoring data set reconstructed in step 25, the deflection correction coefficient of the π-type composite beam bridge main beam constructed in step 34, and the virtual conjugate beam internal force calculated in step 42, calculate the deflection of the π-type composite beam bridge main beam considering the shear lag effect:

[0081]

[0082] In the formula, w ak is the deflection of the a-th measuring point of the main beam of the π-type composite beam bridge at the k-th monitoring moment; w 0k is the deflection of the left end point of the main beam of the π-type composite beam bridge at the kth monitoring moment; w nk is the deflection of the right end point of the main beam of the π-type composite beam bridge at the kth monitoring moment.

[0083] The above-mentioned π-type composite beam bridge main beam high-density measurement point strain-vertical deflection conversion method reconstructs the collected strain monitoring data of the π-type composite beam bridge main beam, constructs the deflection correction coefficient of the π-type composite beam bridge main beam considering the shear lag effect, and uses the virtual conjugate beam theory to realize the conversion of the bridge structure strain data to deflection data. The existing strain-deflection conversion algorithm often follows this idea: considering the geometric shape, material properties, boundary conditions and other factors of the bridge structure, a numerical model of the bridge structure is established, and the deflection field of the bridge structure under force and boundary conditions is obtained by using the established numerical model to solve the corresponding boundary value problem, and the obtained deflection field is established with the strain field. The relationship is established, and the collected strain data is converted into corresponding deflection data using the established strain-deflection relationship. However, the boundary conditions of the bridge structure are often difficult to determine under actual operating conditions, resulting in a large error in the converted deflection data. Therefore, the present invention, from the perspective of information conversion, reconstructs the collected strain monitoring data of the bridge structure, constructs the main beam deflection correction coefficient, and then realizes the effective calculation of the deflection of the main beam of the π-type composite beam bridge, ensuring the safe operation and maintenance of the bridge structure during the operation period.

[0084] The following test is used to verify the effect of the present invention:

[0085] In this experiment, the finite element analysis method was used to establish a finite element model of the main beam of a π-type composite beam bridge to verify the effectiveness of the method. The strain monitoring data was extracted from the finite element model strain data and 5% Gaussian noise was added for simulation.

[0086] The details of this test are as follows:

[0087] (1) Establish a finite element model of the main beam of a π-type composite beam bridge, apply random traffic loads to the model, and obtain strain simulation data under the load as a strain monitoring data set. Figure 2 As shown in the figure, the cross section of the main beam of the π-type composite beam bridge is as follows: Figure 3 As shown in the figure, the distributed sensing optical fiber arrangement of the main beam of the π-type composite beam bridge is as follows: Figure 4 As shown in the figure, the finite element model of the main beam of the π-type composite beam bridge is as follows: Figure 5 shown.

[0088] (2) Based on the strain monitoring data obtained above, discrete wavelet transform is used to realize the division of low-frequency and high-frequency signals, and the soft and hard threshold function-FastICA joint algorithm is used to remove high-frequency signal noise to realize the reconstruction of the strain monitoring data set.

[0089] (3) Based on the energy variation principle, the normal stress calculation method in the Euler-Bernoulli Beam theory is modified, and the deflection correction coefficient of the main beam of the π-type composite beam bridge considering the shear lag effect is constructed.

[0090] (4) Based on the reconstructed strain monitoring data set and the established correction coefficient of the main beam deflection of the π-type composite beam bridge, the vertical deflection of the main beam of the π-type composite beam bridge is calculated using the virtual conjugate beam theory.

[0091] Comparing the deflection calculation results of the finite element model of the main beam of the π-type composite beam bridge, such as Figure 6 As shown in the figure, the two broken lines represent the calculation results of the numerical simulation and the calculation results of the present invention respectively. It can be seen that the calculation results of the present invention are very close to the calculation results of the numerical simulation. The relative error between the calculation results of the present invention and the calculation results of the numerical simulation is calculated, as shown in FIG. Figure 7 As shown, the relative error is within 2%, which is very small, verifying the effectiveness of the method of the present invention.

[0092] From the perspective of information conversion, the present invention reconstructs the collected strain monitoring data of the bridge structure and constructs the main beam deflection correction coefficient, thereby realizing the effective calculation of the main beam deflection of the π-type composite beam bridge and ensuring the safe operation and maintenance of the bridge structure during the operation period.

Claims

1. A method for converting strain-vertical deflection of a π-type composite beam bridge main beam with high-density measurement points, characterized in that The method comprises the following steps: Step 1: According to the design and construction drawings of the π-type composite beam bridge, the distributed strain sensing optical fiber of the main beam is laid out, and the strain monitoring data at different measuring points of the main beam are collected by using the BOTDA technology to construct a high-density measuring point strain monitoring data set; Step 2: Based on the high-density measurement point strain monitoring data set constructed in step 1, discrete wavelet transform is used to realize the division of low-frequency and high-frequency signals, and the soft and hard threshold function-FastICA joint algorithm is used to remove high-frequency signal noise and reconstruct the strain monitoring data set; Step 3: Based on the energy variation principle, the normal stress calculation method in the Euler-Bernoulli Beam theory is modified to construct the deflection correction coefficient of the main beam of the π-type composite beam bridge considering the shear lag effect. The specific steps are as follows: Step 31: According to the geometric parameters of the cross section of the π-type composite beam, the total bending potential energy expression of the π-type composite beam is established: Π=Ω+Ψ(12) Where, Ω is the total strain energy of the π-type composite beam; Ψ is the external force potential energy of the π-type composite beam under vertical load; The Ω and Ψ are expressed as follows: Where E is the elastic modulus; G is the shear modulus; ε x is the longitudinal linear strain at any point on the cross section of the π-type composite beam, ε x =-zw″+ωU′, z is the distance from any point on the cross section of the π-type composite beam to the neutral axis of the cross section, ω is the shear lag displacement distribution coefficient; γ xy is the shear strain at any point on the cross section of the π-type composite beam; p is the vertical load acting on the π-type composite beam; w is the deflection deformation of the π-type composite beam under the vertical load; w″ is the second-order derivative of w; U′ is the first-order derivative of the maximum shear rotation difference U of shear lag; Step 32: According to the principle of minimum potential energy stationary value, calculate the first-order variation of the total potential energy, and set δΠ=0 to obtain the shear lag control differential equation: NO y w″-NO zw U′+M=0 (15) After sorting, we get: In the formula, I y is the moment of inertia of the π-type composite beam section; I zw is the shear hysteresis warping inertia product of the π-type composite beam section; M is the bending moment of the π-type composite beam section; Step 33: Based on the shear lag control differential equation obtained in step 32, establish the calculation formula for the normal stress of the cross section of the π-type composite beam considering the shear lag effect: s x =Ee x (17) Step 34: Based on the cross-sectional normal stress calculation formula established in step 33 and combined with the cross-sectional normal stress calculation formula in Euler-Bernoulli Beam theory, the deflection correction coefficient of the main beam of the π-type composite beam bridge considering the shear lag effect is constructed: In the formula, is the correction coefficient of the main beam deflection of the π-type composite beam bridge considering the shear lag effect, σ o is the calculation result of the cross-section normal stress in the Euler-Bernoulli Beam theory; x and σ o Substitute the expression into equation (18) and take z = z u , z u is the distance from the top plate to the centroidal axis of the π-type composite beam, which can be obtained after sorting: Substituting equation (19) into equation (16), we get the second-order derivative expression of the deflection of the π-type composite beam considering the shear lag effect: Step 35: Based on the second-order derivative expression of the π-type composite beam deflection considering the shear lag effect obtained in step 34, establish the analytical solution of the π-type composite beam deflection based on the main beam deflection correction coefficient: Where w0 is the main beam deflection calculated based on Euler-Bernoulli Beam theory; w f is the initial deflection; Step 4: Based on the strain monitoring data set reconstructed in step 2 and the main beam deflection correction coefficient constructed in step 3, the vertical deflection of the main beam of the π-type composite beam bridge is calculated using the virtual conjugate beam theory.

2. The method for converting high-density measuring point strain to vertical deflection of a π-type composite beam bridge main beam according to claim 1 is characterized in that The specific steps of step one are as follows: Step 1: According to the design and construction drawings of the π-type composite beam bridge, select the top and bottom of the middle beam and the side beam, lay out the distributed strain sensing optical fiber, and lay out the number of loops and the length of the optical fiber to meet the following requirements: N≥3(1) L = 2a·N·(l+h)(2) Where, N is the number of loops; L is the length of the laid optical fiber; a is the length correction coefficient; l is the total length of each section of the π-type composite beam bridge, in meters; h is the height of the main beam of the π-type composite beam bridge; Step 1 and 2: According to the layout plan of the distributed strain sensing optical fiber designed in step 1, the BOTDA technology is used to collect strain monitoring data at different measuring points of the main beam to construct a high-density measuring point strain monitoring data set: n＝5l(3) Y=[e T1 ,he T2 ,…eh Ti ,…eh Tn ,he B1 ,he B2 ,…eh Bi ,…eh Bn ](4) Where n is the number of measuring points; ε Ti is the vector composed of the monitoring data of the i-th measuring point on the top of the main beam, i∈(1,2,…,n); ε Bi It is the vector composed of the monitoring data of the i-th measuring point at the bottom of the main beam.

3. The method for converting high-density measuring point strain to vertical deflection of a π-type composite beam bridge main beam according to claim 2 is characterized in that The ε Ti and ε Bi Explained as: Where m is the number of monitoring time of strain measuring points; is the strain data value of the i-th measuring point on the top of the main beam at the k-th monitoring moment, k∈(1,2,…,m); It is the strain data value of the i-th measuring point on the top of the main beam at the k-th monitoring moment.

4. The method for converting high-density measuring point strain to vertical deflection of a π-type composite beam bridge main beam according to claim 1 is characterized in that The specific steps of step 2 are as follows: Step 21: According to the high-density measurement point strain monitoring data set constructed in step 1, select sym4 as the wavelet basis function, perform discrete wavelet transform on the data set, and obtain: In the formula, ε i is the strain monitoring signal of the i-th measuring point; is the low-frequency strain signal of the i-th measuring point; is the high-frequency strain signal of the i-th measuring point; Step 22: According to the discrete wavelet coefficients of the high-frequency strain monitoring signal at the i-th measuring point obtained in step 21, construct the soft and hard threshold functions and calculate the denoising wavelet coefficients of the high-frequency strain signal at the i-th measuring point: In the formula, is the denoising wavelet coefficient of the high-frequency strain signal at the i-th measuring point; sign(·) is the sign function sign; λ is the threshold; Step 23: Based on the discrete wavelet coefficients of the high-frequency strain monitoring signal at the i-th measuring point obtained in step 21 and the denoised wavelet coefficients of the high-frequency strain signal at the i-th measuring point obtained in step 22, construct the FastICA analysis input matrix: Step 24: Perform FastICA analysis based on the FastICA analysis input matrix obtained in step 23 to obtain the secondary denoising wavelet coefficients of the high-frequency strain signal at the i-th measuring point Combined with the low-frequency strain signal of the i-th measuring point obtained in step 2.1 Using inverse wavelet transform, the strain monitoring data set is reconstructed: In the formula, is the reconstructed strain monitoring dataset; is the vector formed by the monitoring data of the i-th measuring point on the top of the main beam after noise removal; It is the vector composed of the monitoring data of the i-th measuring point at the bottom of the main beam after denoising.

5. The method for converting high-density measuring point strain to vertical deflection of a π-type composite beam bridge main beam according to claim 4 is characterized in that The high-frequency strain monitoring signal of the i-th measuring point The discrete wavelet coefficients are expressed as: In the formula, is the discrete wavelet coefficient of the high-frequency strain monitoring signal at the i-th measuring point; is the discrete wavelet coefficient of the high-frequency strain spectrum signal at the i-th measuring point; is the discrete wavelet coefficient of the high-frequency strain noise signal at the i-th measuring point; g is the number of wavelet decomposition layers; p is the signal length.

6. The method for converting high-density measuring point strain to vertical deflection of a π-type composite beam bridge main beam according to claim 1 is characterized in that The specific steps of step 4 are as follows: Step 41: Based on the strain monitoring data set reconstructed in step 2, calculate the curvature of the cross section where each strain measurement point is located: Where: is the curvature value of the cross section where the i-th strain measuring point is located at the k-th monitoring moment; Step 42: According to the actual π-type composite beam structure, an equivalent virtual conjugate beam is established. The curvature value calculated in step 41 is used as a distributed load on the virtual conjugate beam structure to calculate the internal force of the virtual conjugate beam: Where: Q0′ k is the shear force at the left end point of the virtual conjugate beam at the kth monitoring moment; Δl is the distance between the measuring points, M a ' k is the bending moment of the section where the ath measuring point is located at the corresponding position of the virtual conjugate beam at the kth monitoring moment; M0′ k is the bending moment of the left end point of the virtual conjugate beam at the kth monitoring moment; M n ' k is the bending moment of the right end point of the virtual conjugate beam at the kth monitoring moment; Step 43: Based on the strain monitoring data set reconstructed in step 2, the deflection correction coefficient of the main beam of the π-type composite beam bridge constructed in step 3, and the internal force of the virtual conjugate beam calculated in step 42, calculate the deflection of the main beam of the π-type composite beam bridge considering the shear lag effect: In the formula, w ak is the deflection of the a-th measuring point of the main beam of the π-type composite beam bridge at the k-th monitoring moment; w 0k is the deflection of the left end point of the main beam of the π-type composite beam bridge at the kth monitoring moment; w nk is the deflection of the right end point of the main beam of the π-type composite beam bridge at the kth monitoring moment.

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