A structural health monitoring method for a self-hydraulic cambered trestle

Abstract

The present application relates to the technical field of monitoring methods, in particular to a structural health monitoring method for a self-hydraulic inverted arch trestle, which determines the response extreme position in the trestle main bridge model through simulation simulation, sets sensors on the self-hydraulic inverted arch trestle according to the response extreme position, obtains response data through the sensors, processes the response data to obtain the response parameters of the self-hydraulic inverted arch trestle, predicts the response parameter changes of the self-hydraulic inverted arch trestle in the future 60 minutes based on the response parameters, establishes an early warning mechanism based on the response parameter changes, and realizes the structural change early warning of the trestle.

Description

Technical Field

[0001] This invention relates to the field of monitoring methods, specifically to a method for monitoring the structural health of a self-propelled hydraulic inverted arch bridge. Background Technology

[0002] Currently, the structural safety monitoring of self-propelled inverted arch trestle bridges during tunnel construction generally adopts a static data acquisition method based on discrete sensors. The typical approach is to place an inclinometer at the mid-span of the main bridge to obtain local deformation information, and then transmit the data to a monitoring platform for viewing and analysis via wired or wireless networks. However, this method can only be used for post-construction data review and cannot reflect the structural changes of the trestle bridge in a timely manner during its use, nor can it provide early warnings before the bridge is in use. Therefore, a structural health monitoring method for self-propelled hydraulic inverted arch trestle bridges is proposed. Summary of the Invention

[0003] To address the technical problems existing in the prior art, the present invention provides a method for structural health monitoring of self-hydraulic inverted arch trestle bridges.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for structural health monitoring of a self-propelled hydraulic inverted arch trestle bridge, comprising the following steps:

[0005] Step S1: Establish a model of the main bridge of the trestle bridge, determine the extreme value location of the response in the model of the main bridge of the trestle bridge through simulation, and set up sensors on the self-hydraulic inverted arch trestle bridge according to the extreme value location of the response, and obtain response data through the sensors.

[0006] Step S2: Filter and reduce noise in the response data to obtain the response parameters, which are deflection parameters. ;

[0007] Select the mid-span deflection value of the trestle bridge within a continuous 30-minute period from the response parameters. By using sliding window linear regression to fit the deformation trend of the deflection data, the deformation trend at time t is obtained. Mid-span deflection value of the trestle bridge ;

[0008] Based on time Mid-span deflection value of the trestle bridge Predicting the deflection of the self-hydraulic inverted arch bridge over the next 60 minutes. change;

[0009] Step S3: Define the fuzzy threshold and perform membership calculations based on the fuzzy threshold. Calculation;

[0010] Based on membership degree The calculation results are used to make a safety assessment.

[0011] Preferably, step S1 includes:

[0012] Step S11: Establish the main bridge model of the trestle bridge;

[0013] Step S12: Determine the typical load conditions encountered by the main bridge of the trestle during operation;

[0014] Step S13: Run the static simulation function and the moving load dynamic simulation function of the simulation software to perform static simulation and moving load dynamic simulation on the main bridge model under each typical load condition. Determine the response extreme value position in the main bridge model based on the simulation results and map the response extreme value position on the trestle model to the trestle.

[0015] Step S14: Arrange sensors on the trestle and acquire response data at the extreme value locations of the trestle response through the sensors.

[0016] Preferably, in step S12, the typical load conditions of the self-propelled hydraulic trestle include:

[0017] Condition A: A 60t tanker truck passes through the main bridge of the self-propelled hydraulic inverted arch trestle bridge in the center.

[0018] Condition B: A 60t tanker truck with a lateral offset of ±30cm passes through the main bridge of a self-propelled hydraulic arch bridge.

[0019] Preferably, in step S13, the extreme value of the response is located at the mid-span of the main bridge model, and the extreme value of the response on the trestle is located at the mid-span of the trestle.

[0020] Preferably, in step S14, the sensor used is a tilt sensor. The tilt sensor is set at four measurement points: one-quarter length position on both sides of the trestle and three-quarter length position of the main beam of the trestle. The tilt sensor collects the instantaneous tilt angle data of the trestle at the measurement points, and calculates the response data at the extreme position of the trestle response based on the instantaneous tilt angle data.

[0021] Preferably, in step S14, the tilt sensors at one-quarter of the length of the left side of the trestle and at three-quarters of the length of the main beam of the trestle respectively acquire the left tilt angle time sequence data. and left third tilt angle timing data Inclination sensors located at one-quarter of the length of the right side of the trestle and at three-quarters of the length of the main beam of the trestle respectively acquired the right inclination angle time-series data. and right three-pitch timing data ;

[0022] Based on left tilt angle time series data and left third tilt angle time series data Right tilt angle time series data and right three-pitch timing data The mid-span deflection of the left side of the trestle bridge was inverted using the same-side double-inclination difference method. Mid-span deflection on the right side of the trestle :

[0023] ;

[0024] ;

[0025] In the formula, The spacing between the two sets of biaxial inclinometers on the same side;

[0026] Mid-span deflection on the left side of the trestle Mid-span deflection on the right side of the trestle This is the final response data.

[0027] Preferably, in step S2, time Mid-span deflection value of the trestle bridge The formula for calculation is:

[0028] ;

[0029] In the formula, It is a time variable, counting from the start of the window. The slope is used to reflect the deformation rate at mid-span of the main bridge of the self-hydraulic inverted arch trestle bridge. This represents the mid-span deflection value of the main bridge at the start of the window.

[0030] Deflection value at mid-span of main bridge at minute The expression is:

[0031] ;

[0032] In the formula, This is the current mid-span deflection value of the main bridge. The deformation rate is obtained by sliding window linear regression when t=60min.

[0033] Preferably, in step S3, a fuzzy threshold is defined. ;

[0034] In the formula, This is the lower limit of the threshold. The threshold center value, The upper limit of the threshold;

[0035] Membership degree The formula for calculation is:

[0036] ;

[0037] Based on membership degree The rules for making security judgments based on the calculation results are as follows:

[0038] like If so, it is considered safe;

[0039] like And the trend slope If so, a yellow alert will be issued;

[0040] like or A red alert will be issued.

[0041] Preferably, in step S3:

[0042] Define the fuzzy threshold values ​​for self-propelled hydraulic inverted arch trestle bridges under various typical load conditions:

[0043] Operating Condition A, Centered: ;

[0044] Condition B, off-center load: .

[0045] Preferably, in step S3: and These correspond to 20% early abnormalities and 70% critical mutation states, respectively.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] 1. This invention provides a method for structural health monitoring of a self-propelled hydraulic inverted arch trestle. The method determines the extreme response locations in the main bridge model of the trestle through simulation, sets sensors on the self-propelled hydraulic inverted arch trestle according to the extreme response locations, acquires response data through the sensors, processes the response data to obtain the response parameters of the self-propelled hydraulic inverted arch trestle, and predicts the changes in the response parameters of the self-propelled hydraulic inverted arch trestle in the next 60 minutes based on the response parameters. Based on the changes in the response parameters, an early warning mechanism can be established to achieve early warning of structural changes of the trestle. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0049] The present invention will be further described below with reference to the accompanying drawings and embodiments, which illustrate the above and other technical features and advantages of the present invention. However, the following embodiments are merely preferred embodiments of the present invention and are not exhaustive.

[0050] Example:

[0051] like Figure 1As shown, the present invention provides a method for structural health monitoring of a self-propelled hydraulic inverted arch bridge, comprising the following steps:

[0052] Step S1: Establish a model of the main bridge of the trestle bridge, determine the extreme value location of the response in the model of the main bridge of the trestle bridge through simulation, and set up sensors on the self-hydraulic inverted arch trestle bridge according to the extreme value location of the response, and obtain response data through the sensors.

[0053] Establish a model of the main bridge of the trestle bridge;

[0054] Determine the typical load conditions encountered by the main bridge of the trestle during operation;

[0055] Typical load conditions for self-propelled hydraulic trestles include:

[0056] Condition A: A 60t tanker truck passes through the main bridge of the self-propelled hydraulic inverted arch trestle bridge in the center.

[0057] Condition B: A 60t tanker truck with a lateral offset of ±30cm passes through the main bridge of a self-propelled hydraulic arch bridge.

[0058] The static simulation function and the moving load dynamic simulation function of the simulation software are used to perform static simulation and moving load dynamic simulation on the main bridge model under each typical load condition. Based on the simulation results, the extreme value position of the response in the main bridge model is determined. The extreme value position of the response is located at the mid-span of the main bridge model. The extreme value of the response on the trestle is located at the mid-span of the trestle. The extreme value position of the response on the trestle model is mapped to the trestle.

[0059] Sensors are deployed on the trestle to acquire response data at extreme response locations. Inclination sensors are selected and are set at four measurement points: one-quarter of the length on both sides of the trestle and three-quarters of the length of the main beam. The inclination sensors collect instantaneous inclination data of the trestle at the measurement points, and the response data at extreme response locations is calculated based on the instantaneous inclination data.

[0060] Inclination sensors located at one-quarter of the length of the left side of the trestle and at three-quarters of the length of the main beam of the trestle respectively acquired time-series data of the left inclination angle. and left third tilt angle time series data Inclination sensors located at one-quarter of the length of the right side of the trestle and at three-quarters of the length of the main beam of the trestle respectively acquired the right inclination angle time-series data. and right three-pitch timing data ;

[0061] Based on left tilt angle time series data and left third tilt angle time series data Right tilt angle time series data and right three-pitch timing data The mid-span deflection of the left side of the trestle bridge was inverted using the same-side double-inclination difference method. Mid-span deflection on the right side of the trestle :

[0062] ;

[0063] ;

[0064] In the formula, The spacing between the two sets of biaxial inclinometers on the same side;

[0065] The mid-span deflection on the left side of the trestle bridge was inverted using the same-side double-inclination difference method. Mid-span deflection on the right side of the trestle This is the final response data;

[0066] Step S2: Process the response data to obtain the response parameters of the self-propelled hydraulic inverted arch trestle, and predict the change of the response parameters of the self-propelled hydraulic inverted arch trestle in the next 60 minutes based on the response parameters.

[0067] The response data is filtered and denoised to obtain the response parameters, which are deflection parameters. :

[0068] Select the mid-span deflection value of the trestle bridge within a continuous 30-minute period from the response parameters. By using sliding window linear regression to fit the deformation trend of the deflection data, the deformation trend at time t is obtained. Mid-span deflection value of the trestle bridge :

[0069] ;

[0070] In the formula, It is a time variable, counting from the start of the window. The slope is used to reflect the deformation rate at mid-span of the main bridge of the self-hydraulic inverted arch trestle bridge. This represents the mid-span deflection value of the main bridge at the start of the window.

[0071] Based on the response parameters, predict the deflection value at mid-span of the main bridge at 60 minutes:

[0072] ;

[0073] In the formula, This is the current mid-span deflection value of the main bridge. The deformation rate is obtained by linear regression of the sliding window at t=60min;

[0074] Step S3: Establish an early warning mechanism based on changes in response parameters;

[0075] Define fuzzy threshold ;

[0076] In the formula, This is the lower limit of the threshold. The threshold center value, The upper limit of the threshold;

[0077] Define the fuzzy threshold values ​​for self-propelled hydraulic inverted arch trestle bridges under various typical load conditions:

[0078] Operating Condition A, Centered: ;

[0079] Condition B, off-center load: ;

[0080] Based on fuzzy threshold Perform membership Calculation:

[0081] ;

[0082] Security assessment based on membership degree:

[0083] like If so, it is considered safe;

[0084] like And the trend slope If so, a yellow alert will be issued;

[0085] like or A red alert will then be issued;

[0086] and These correspond to 20% early abnormalities and 70% critical mutation states, respectively.

[0087] The above description is merely a preferred embodiment of the present invention and is illustrative rather than restrictive. Those skilled in the art will understand that many changes, modifications, and even equivalents can be made within the spirit and scope defined by the claims of the present invention, all of which will fall within the protection scope of the present invention.

Claims

1. A method for structural health monitoring of a self- hydraulic inverted arch trestle characterized by, Includes the following steps: Step S1: Establish a model of the main bridge of the trestle bridge, determine the extreme value location of the response in the model of the main bridge of the trestle bridge through simulation, and set up sensors on the self-hydraulic inverted arch trestle bridge according to the extreme value location of the response, and obtain response data through the sensors. Step S1 includes: Step S11: Establish the main bridge model of the trestle bridge; Step S12: Determine the typical load conditions encountered by the main bridge of the trestle during operation; Step S13: Run the static simulation function and the moving load dynamic simulation function of the simulation software to perform static simulation and moving load dynamic simulation on the main bridge model under each typical load condition. Determine the response extreme value position in the main bridge model based on the simulation results and map the response extreme value position on the trestle model to the trestle. Step S14: Deploy sensors on the trestle and acquire response data at the extreme value locations of the trestle response through the sensors; Step S2, filtering and denoising the response data to obtain a response parameter, the response parameter being the deflection ; Select the deflection value of the stack bridge span in the continuous 30 minutes from the response parameters , the deflection data deformation trend is fitted by using sliding window linear regression to obtain the stack bridge main span deflection value at time ; Based on time Mid-span deflection value of the trestle bridge Predicting the deflection of the self-hydraulic inverted arch bridge over the next 60 minutes. change; Step S3, defining a blur threshold and performing membership based on the blur threshold of the calculation; Based on membership degree The calculation results are used to make a safety assessment.

2. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 1, wherein: In step S12, the typical load conditions for the self-propelled hydraulic trestle include: Condition A: A 60t tanker truck passes through the main bridge of the self-propelled hydraulic inverted arch trestle bridge in the center. Condition B: A 60t tanker truck with a lateral offset of ±30cm passes through the main bridge of a self-propelled hydraulic arch bridge.

3. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 1, wherein: In step S13, the extreme value of the response is located at the mid-span of the main bridge model, and the extreme value of the response on the trestle is located at the mid-span of the trestle.

4. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 1, wherein: In step S14, an inclination sensor is selected. The inclination sensor is set at four measurement points: one-quarter of the length on both sides of the trestle and three-quarters of the length of the main beam of the trestle. The inclination sensor collects the instantaneous inclination data of the trestle at the measurement points, and calculates the response data at the extreme value position of the trestle response based on the instantaneous inclination data.

5. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 1, wherein: In step S14, tilt sensors located at one-quarter of the length of the left side of the trestle and at three-quarters of the length of the main beam of the trestle respectively acquire left tilt angle time-series data. and left third tilt angle time series data Inclination sensors located at one-quarter of the length of the right side of the trestle and at three-quarters of the length of the main beam of the trestle respectively acquired the right inclination angle time-series data. and right three-pitch timing data ; Based on left tilt angle time series data and left third tilt angle timing data Right tilt angle time series data and right three-pitch time series data The mid-span deflection of the left side of the trestle bridge was inverted using the same-side double-inclination difference method. Mid-span deflection on the right side of the trestle : ； ； In the formula, is the arrangement interval of the two groups of the same side biaxial inclinometer. midspan deflection of the left side of the deck midspan deflection of the right side of the deck is the final response data.

6. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 1, wherein: In step S2, time... Mid-span deflection value of the trestle bridge The formula for calculation is: ； In the formula, It is a time variable, counting from the start of the window. The slope is used to reflect the deformation rate at mid-span of the main bridge of the self-hydraulic inverted arch trestle bridge. This represents the mid-span deflection value of the main bridge at the start of the window. Deflection value at mid-span of main bridge at minute The expression is: ； In the formula, This is the current mid-span deflection value of the main bridge. The deformation rate is obtained by sliding window linear regression when t=60min.

7. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 1, wherein: In the step S3, the blur threshold is defined ; wherein is a lower threshold value, is a center threshold value, is an upper threshold value; Degree of membership The calculation formula is: ； Based on membership degree The rules for making security judgments based on the calculation results are as follows: If then it is judged to be safe; If and the trend slope then a yellow warning is issued; If or a red warning is issued.

8. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 7, wherein: In step S3: Define the fuzzy threshold values ​​for self-propelled hydraulic inverted arch trestle bridges under various typical load conditions: Operating condition A, centered: ; Case B, partial load: .

9. A method for structural health monitoring of a self- hydraulic inverted arch trestle as claimed in claim 7, wherein: The step S3: With Corresponding to 20% early abnormalities and 70% borderline mutation status, respectively.

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