A large structure deformation measurement method based on fiber grating sensor network

Abstract

This invention discloses a method for measuring the deformation of large structures based on fiber Bragg grating sensor networks, relating to the field of deformation monitoring. The method includes: uploading structural parameters; constructing a three-dimensional model of the structure based on these parameters; traversing the three-dimensional model; identifying fiber Bragg grating sensor deployment paths within the model; and deploying fiber Bragg grating sensors based on these paths. This invention accurately identifies fiber Bragg grating sensor deployment paths by constructing a three-dimensional model of the structure, and optimizes deployment by combining n-pyramidal segmentation and point number correction, thereby improving the rationality and comprehensiveness of sensor layout while controlling sensor deployment costs and limiting the difficulty of subsequent sensor maintenance.

Description

Technical Field

[0001] This invention relates to the field of deformation monitoring technology, specifically to a method for measuring the deformation of large structures based on fiber optic grating sensor networks. Background Technology

[0002] Large-scale structural deformation monitoring is a technology that uses sensors, total stations, and other means to continuously monitor the displacement, settlement, and other deformations of large-scale projects such as bridges and dams, analyze the changing trends, assess the structural safety, and provide data support for maintenance and early warning.

[0003] Patent application No. 201410353892.3 discloses a method for measuring the deformation of large structures based on a fiber optic grating sensor network. The method involves averaging the wavelength data measured by the fiber optic grating sensor network to obtain the average wavelength data for the measurement period. Then, by substituting the pre-calibrated temperature sensitivity coefficients of the temperature sensor and the temperature and strain sensitivity coefficients of the strain sensor, and performing temperature compensation calculations, the discrete strain values ​​of all strain sensors are obtained. Interpolation of the discrete strain values ​​yields the strain polynomial. The strain polynomial is then integrated twice to obtain the polynomial of the structural deformation. Finally, based on the state of the structure, the initial integration conditions (i.e., the slope and offset of the curve) are substituted to obtain the final deflection curve of the structural deformation. This application aims to provide a technical solution for effectively monitoring the deformation of a structure caused by external or internal forces.

[0004] However, in the existing technology for monitoring the deformation of large structures such as bridges and buildings using fiber optic grating sensor networks, in order to ensure monitoring accuracy, a large number of sensor arrays are often deployed on the surface of the structure. Although this method can effectively monitor structural deformation, the subsequent maintenance costs and troubleshooting time costs are relatively high.

[0005] To address this, a new method for measuring the deformation of large structures based on fiber grating sensor networks is proposed. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a method for measuring the deformation of large structures based on fiber optic grating sensor networks, which can effectively solve the problems of the existing technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions;

[0008] This invention discloses a method for measuring the deformation of large structures based on fiber Bragg grating sensor networks, comprising:

[0009] Upload the structural construction parameters, construct a 3D model of the structure based on the parameters, traverse the 3D model, identify the fiber optic grating sensor deployment path within the model, and deploy the fiber optic grating sensors based on the path. Number each fiber optic grating sensor deployed on the structure, control the sensor to sense its own axial strain information, mark the strain information with the sensor number from which it originated, and differentiate and store all marked strain information based on sensing time. Select a deformation monitoring area on the 3D model of the structure, select strain information from the stored strain information based on the deformation monitoring area, and apply the selected strain information to assess the degree of deformation at the corresponding location on the structure surface monitoring area. Set a deformation risk threshold, obtain the deformation assessment result, and compare the assessment result with the deformation risk threshold to determine whether the structure has a deformation risk.

[0010] Furthermore, the structural construction parameters are derived from the structural design drawings. After the three-dimensional model of the structure is completed, all combinations of adjacent n faces with the same vertices are used as the target for the fiber optic grating sensor deployment path.

[0011] The n-sided edges of the target are used as edges to construct an n-sided pyramid. The base of each n-sided pyramid is an n-sided polygon. In other words, each n-sided pyramid is used as the fiber optic grating sensor deployment path to identify the target.

[0012] The n-sided pyramid is divided such that the vertices of the n-sided pyramid are on the dividing surface, the base of the dividing surface falls on the base of the n-sided pyramid, and the resulting sectional surface is the largest sectional surface of the n-sided pyramid. The contour part of the sectional surface that does not originate from the base of the n-sided pyramid is used as the deployment reference path of the fiber optic grating sensor, and the deployment path is identified based on the deployment reference path.

[0013] Furthermore, the operation of identifying the deployment path based on the deployment reference path, that is, the operation of picking up the deployment points of the fiber Bragg grating sensor on the deployment reference path:

[0014] If a basic deployment ratio is set, in meters per unit, then the initial number of fiber Bragg grating sensor deployment points along the deployment reference path is: , Indicates the total length of the deployment reference path. Indicates the proportion of basic deployment;

[0015] The initial number of fiber Bragg grating sensor deployment points is adjusted to determine the final number of fiber Bragg grating sensor deployment points on the deployment reference path. , denoted as N;

[0016] In the formula: The angle of the apex of the cross section; The maximum vertex angle of the tangent face of all n-sided pyramids; For the height of the cut surface; The maximum value of the tangent height of all n-sided pyramids; It is a constant;

[0017] Where, constant ∈ (0, 1], the user-defined deformation monitoring criticality of the corresponding part of the n-pyramid structure. The greater the deformation monitoring criticality, the more constants are used. The larger the value of N, the more the deployment reference path is divided into N-1 segments after N is determined. The endpoints of each segment are recorded as the deployment points of the fiber Bragg grating sensor, and the fiber Bragg grating sensor is deployed at the deployment points.

[0018] Furthermore, the operating cycle of the fiber Bragg grating sensor follows the following:

[0019] ;

[0020] In the formula: Material coefficients for the deployment location of fiber Bragg grating sensors; The grating stability coefficient of the fiber Bragg grating sensor; Redundancy for fiber Bragg grating sensors; The density coefficient of the fiber Bragg grating sensor; Temperature sensitivity coefficient for the deployment location of fiber Bragg grating sensors; The ambient temperature difference range at the deployment location of the fiber Bragg grating sensor; The stress influence coefficient for the deployment location of the fiber Bragg grating sensor; The maximum stress value at the deployment location of the fiber Bragg grating sensor; This refers to the data sampling frequency of the fiber Bragg grating sensor. This is the wavelength drift threshold for the fiber Bragg grating sensor; The spatial attenuation factor for fiber Bragg grating sensors;

[0021] In this process, based on the above formula, the set of fiber Bragg grating sensors deployed on each deployment path is used as the calculation target, and an independent operating cycle is configured for the set of fiber Bragg grating sensors deployed on each deployment path.

[0022] Furthermore, the material coefficient of the fiber Bragg grating sensor deployment location The values ​​are as follows: 1.0-1.3 for metallic materials; 0.7-0.9 for concrete materials; and 0.8-1.1 for composite materials. Furthermore, the higher the material strength of the fiber Bragg grating sensor deployment location, the higher its stability. The larger the value;

[0023] grating stability coefficient of fiber Bragg grating sensor The value ranges from [0.5, 1.1], and follows the principle that higher manufacturing precision results in better quality and performance. The larger the value;

[0024] ;

[0025] Temperature sensitivity coefficient of fiber Bragg grating sensor deployment location The range of values ​​is Furthermore, the larger the diurnal temperature difference at the fiber Bragg grating sensor deployment location, the larger the value.

[0026] Stress influence coefficient of fiber Bragg grating sensor deployment location The range of values ​​is Furthermore, the greater the rigidity of the fiber Bragg grating sensor deployment location, the smaller the value;

[0027] Wavelength drift threshold of fiber Bragg grating sensor The value follows the rule that the greater the criticality of deformation monitoring of the part of the structure corresponding to the deployment location of the fiber Bragg grating sensor, the smaller its value should be.

[0028] Spatial attenuation factor of fiber Bragg grating sensor The value follows the rule that the greater the average distance between each sensor in the fiber Bragg grating sensor set and the maintenance point, the larger the value.

[0029] Among them, maintenance points are fixed locations or temporary work points that are pre-set for each fiber Bragg grating sensor set for daily inspection, data reading, fault repair, and equipment calibration.

[0030] Furthermore, when selecting the deformation monitoring area on the three-dimensional model of the structure, each fiber Bragg grating sensor set is used as the selection target, and the selected deformation monitoring area corresponds to no less than two fiber Bragg grating sensor sets, and each fiber Bragg grating sensor set is adjacent to the surface of the structure.

[0031] After the deformation monitoring area is selected, the set of fiber optic grating sensors corresponding to the deformation monitoring area is used as the query target. In the stored strain information, the strain information pointed to by each query target is identified, and a set of the latest stored strain information is obtained for each query target's strain information, so as to evaluate the degree of deformation at the corresponding position of the monitoring area on the structure surface.

[0032] Furthermore, when evaluating the degree of deformation at the location corresponding to the monitoring area on the surface of the structure, the earliest stored strain information of each fiber grating sensor set corresponding to the deformation monitoring area is simultaneously acquired, and the degree of deformation at the location corresponding to the monitoring area on the surface of the structure is evaluated based on the earliest stored strain information combined with the latest stored strain information.

[0033] When the selected deformation monitoring area corresponds to more than 2 fiber grating sensor sets, each pair of adjacent fiber grating sensor sets is still grouped together, and the deformation degree of the structure is evaluated separately. The maximum deformation degree in the evaluation result is recorded as the deformation degree of the corresponding position of the monitoring area on the surface of the structure.

[0034] Furthermore, the degree of deformation at the corresponding location on the surface monitoring area of ​​the structure is evaluated according to the following:

[0035] ;

[0036] In the formula: The degree of deformation; This is a correction factor for the structure type; This represents the number of fiber Bragg grating sensors in the fiber Bragg grating sensor set. Let be the axial strain change of the i-th sensor in fiber Bragg grating sensor set A′ and fiber Bragg grating sensor set B′; The effective monitoring length of a single fiber Bragg grating sensor; This represents the change in the lateral tilt angle between the positions of the i-th fiber Bragg grating sensor and the (i+1)-th fiber Bragg grating sensor. This represents the maximum spatial distance between fiber Bragg grating sensor set A′ and fiber Bragg grating sensor set B′. The time difference between the perception of the two sets of strain information; These are material property coefficients; The material aging coefficient; Spatial weighting coefficient;

[0037] Among them, the structure type correction coefficient The values ​​are user-defined on the system side. The default value for structures derived from bridges is 1.2, and the default value for structures derived from high-rise buildings is 0.8.

[0038] Furthermore, the axial strain change of the i-th sensor in the fiber Bragg grating sensor set A′ It is the difference between the most recent strain value and the earliest strain value. Similarly;

[0039] , ;

[0040] In the formula: The elastic modulus is the value at the corresponding location on the monitoring area of ​​the structure surface. The Poisson's ratio is the ratio of the location corresponding to the monitoring area on the surface of the structure. This is the initial aging factor; The activation energy of the material; It is the ideal gas constant; The absolute temperature of the environment at the corresponding location on the surface monitoring area of ​​the structure during the deformation assessment stage.

[0041] Compared with the known prior art, the technical solution provided by this invention has the following beneficial effects:

[0042] This invention provides a method for measuring the deformation of large structures based on fiber optic grating sensor networks. During execution, the method accurately identifies the deployment path of fiber optic grating sensors by constructing a three-dimensional model of the structure. It optimizes deployment by combining n-pyramidal segmentation and point number correction, improving the rationality and comprehensiveness of sensor layout while controlling deployment costs and limiting subsequent sensor maintenance difficulty. Strain information is stored using numbering and time differentiation, and deformation is assessed by combining the earliest and latest data. Multiple parameters, such as structure type and material properties, are incorporated to improve the accuracy of deformation assessment. Furthermore, deformation risks are promptly determined through risk threshold comparison. This method is effectively adapted to large structures such as bridges and high-rise buildings, enabling precise monitoring and risk warning of deformation in key areas. It provides reliable data support for structural safety maintenance and ensures stable operation. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating a method for measuring the deformation of large structures based on fiber optic grating sensor networks. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0046] The present invention will be further described below with reference to embodiments.

[0047] Example:

[0048] This embodiment presents a method for measuring the deformation of large structures based on fiber optic grating sensor networks, such as... Figure 1 As shown, it includes:

[0049] Upload the structure construction parameters, build a 3D model of the structure based on the structure construction parameters, traverse the 3D model of the structure, identify the fiber optic grating sensor deployment path in the 3D model of the structure, and deploy the fiber optic grating sensor based on the fiber optic grating sensor deployment path.

[0050] The structural construction parameters are derived from the structural design drawings. After the three-dimensional model of the structure is completed, all combinations of n adjacent faces with the same vertices are used as the deployment paths for fiber optic grating sensors to identify targets on the three-dimensional model of the structure.

[0051] The n-sided edges of the target are used as edges to construct an n-sided pyramid. The base of each n-sided pyramid is an n-sided polygon. In other words, each n-sided pyramid is used as the fiber optic grating sensor deployment path to identify the target.

[0052] The n-shaped pyramid is divided such that the vertices of the n-shaped pyramid are on the dividing surface, the base of the dividing surface falls on the base of the n-shaped pyramid, and the resulting sectional surface is the largest sectional surface of the n-shaped pyramid. The contour part of the sectional surface that does not originate from the base of the n-shaped pyramid is used as the deployment reference path of the fiber optic grating sensor, and the deployment path is identified based on the deployment reference path.

[0053] The operation of identifying the deployment path based on the deployment reference path, that is, the operation of picking up the deployment points of the fiber Bragg grating sensor on the deployment reference path:

[0054] If a basic deployment ratio is set, in meters per unit, then the initial number of fiber Bragg grating sensor deployment points along the deployment reference path is: , Indicates the total length of the deployment reference path. Indicates the proportion of basic deployment;

[0055] The initial number of fiber Bragg grating sensor deployment points is adjusted to determine the final number of fiber Bragg grating sensor deployment points on the deployment reference path. , denoted as N;

[0056] In the formula: The angle of the apex of the cross section; The maximum vertex angle of the tangent face of all n-sided pyramids; For the height of the cut surface; The maximum value of the tangent height of all n-sided pyramids; It is a constant;

[0057] Where, constant ∈ (0, 1], the user-defined deformation monitoring criticality of the corresponding part of the n-pyramid structure. The greater the deformation monitoring criticality, the more constants are used. The larger the value of N, the more the deployment reference path is divided into N-1 segments after N is determined. The endpoints of each segment are recorded as the deployment points of the fiber Bragg grating sensor, and the fiber Bragg grating sensor is deployed at the deployment points.

[0058] The above formula combines the physical characteristics of the fiber Bragg grating sensor deployment reference path with the criticality of structural deformation monitoring, and dynamically adjusts the initial number of points determined by the basic deployment ratio to achieve rational sensor deployment. Compared with the traditional uniform deployment mode, by introducing structural geometric parameters and monitoring criticality coefficients, it ensures that the number of deployment points can cover the entire path length while avoiding large-area deployment, thus controlling deployment costs without reducing monitoring accuracy.

[0059] The operating cycle of the fiber Bragg grating sensor follows the following rules:

[0060] ;

[0061] In the formula: Material coefficients for the deployment location of fiber Bragg grating sensors; The grating stability coefficient of the fiber Bragg grating sensor; Redundancy for fiber Bragg grating sensors; The density coefficient of the fiber Bragg grating sensor; Temperature sensitivity coefficient for the deployment location of fiber Bragg grating sensors; The ambient temperature difference range at the deployment location of the fiber Bragg grating sensor; The stress influence coefficient for the deployment location of the fiber Bragg grating sensor; The maximum stress value at the deployment location of the fiber Bragg grating sensor; This refers to the data sampling frequency of the fiber Bragg grating sensor. This is the wavelength drift threshold for the fiber Bragg grating sensor; The spatial attenuation factor for fiber Bragg grating sensors;

[0062] In this process, based on the above formula, the set of fiber Bragg grating sensors deployed on each deployment path is used as the calculation target, and an independent operating cycle is configured for the set of fiber Bragg grating sensors deployed on each deployment path.

[0063] The above formula integrates the sensor's own performance, deployment environment characteristics, and operating parameters to construct a multi-dimensional coupled operating cycle calculation model. This ensures that the cycle is adapted to the actual working conditions, enabling each sensor set to operate in real time based on an independent operating cycle. By integrating multiple parameters such as material properties, environmental interference, and equipment performance, the operating cycle can guarantee the timeliness and accuracy of data acquisition while reducing ineffective energy consumption and data redundancy, thus adapting to the complex and ever-changing service environment of large structures.

[0064] Material coefficient of fiber Bragg grating sensor deployment location The values ​​are as follows: 1.0-1.3 for metallic materials; 0.7-0.9 for concrete materials; and 0.8-1.1 for composite materials. Furthermore, the higher the material strength of the fiber Bragg grating sensor deployment location, the higher its stability. The larger the value;

[0065] grating stability coefficient of fiber Bragg grating sensor The value ranges from [0.5, 1.1], and follows the principle that higher manufacturing precision results in better quality and performance. The larger the value;

[0066] ;

[0067] Temperature sensitivity coefficient of fiber Bragg grating sensor deployment location The range of values ​​is Furthermore, the larger the diurnal temperature difference at the fiber Bragg grating sensor deployment location, the larger the value.

[0068] Stress influence coefficient of fiber Bragg grating sensor deployment location The range of values ​​is Furthermore, the greater the rigidity of the fiber Bragg grating sensor deployment location, the smaller the value;

[0069] Wavelength drift threshold of fiber Bragg grating sensor The value follows the rule that the greater the criticality of deformation monitoring of the part of the structure corresponding to the deployment location of the fiber Bragg grating sensor, the smaller its value should be.

[0070] Spatial attenuation factor of fiber Bragg grating sensor The value follows the rule that the greater the average distance between each sensor in the fiber Bragg grating sensor set and the maintenance point, the larger the value.

[0071] Among them, maintenance points are fixed locations or temporary work points that are pre-set for each fiber Bragg grating sensor set for daily inspection, data reading, fault repair, and equipment calibration.

[0072] Each fiber Bragg grating sensor deployed on the structure is numbered, the fiber Bragg grating sensor is controlled to sense its own axial strain information, the strain information is marked with the number of the fiber Bragg grating sensor from which it originates, and all marked strain information is distinguished and stored based on the sensing time.

[0073] On the three-dimensional model of the structure, a deformation monitoring area is selected. Based on the deformation monitoring area, strain information is selected from the stored strain information. The selected strain information is then used to evaluate the degree of deformation at the corresponding location of the monitoring area on the surface of the structure.

[0074] When selecting deformation monitoring areas on the three-dimensional model of the structure, each fiber Bragg grating sensor set is used as the selection target. The selected deformation monitoring area corresponds to no less than two fiber Bragg grating sensor sets, and each fiber Bragg grating sensor set is adjacent to the surface of the structure.

[0075] After the deformation monitoring area is selected, the set of fiber optic grating sensors corresponding to the deformation monitoring area is used as the query target. In the stored strain information, the strain information pointed to by each query target is identified, and a set of the latest stored strain information is obtained for each query target's strain information, which is used to evaluate the degree of deformation at the corresponding position of the monitoring area on the structure surface.

[0076] When evaluating the degree of deformation at the corresponding location of the monitoring area on the surface of the structure, the earliest strain information stored in each fiber grating sensor set corresponding to the deformation monitoring area is acquired simultaneously. The degree of deformation at the corresponding location of the monitoring area on the surface of the structure is evaluated based on the earliest stored strain information combined with the latest stored strain information.

[0077] When the selected deformation monitoring area corresponds to more than 2 fiber grating sensor sets, each pair of adjacent fiber grating sensor sets is still grouped together, and the deformation degree of the structure is evaluated separately. The maximum deformation degree in the evaluation result is recorded as the deformation degree of the corresponding position of the monitoring area on the surface of the structure.

[0078] The degree of deformation at the corresponding location on the monitored area of ​​the structure surface shall be subject to the following during the evaluation:

[0079] ;

[0080] In the formula: The degree of deformation; This is a correction factor for the structure type; This represents the number of fiber Bragg grating sensors in the fiber Bragg grating sensor set. Let be the axial strain change of the i-th sensor in fiber Bragg grating sensor set A′ and fiber Bragg grating sensor set B′; The effective monitoring length of a single fiber Bragg grating sensor; This represents the change in the lateral tilt angle between the positions of the i-th fiber Bragg grating sensor and the (i+1)-th fiber Bragg grating sensor. This represents the maximum spatial distance between fiber Bragg grating sensor set A′ and fiber Bragg grating sensor set B′. The time difference between the perception of the two sets of strain information; These are material property coefficients; The material aging coefficient; Spatial weighting coefficient;

[0081] Among them, the structure type correction coefficient The value is defined by the system user. The default value for a structure derived from a bridge is 1.2, and the default value for a structure derived from a high-rise building is 0.8.

[0082] The above formula integrates strain changes, spatial geometric features, time dimension (sensing time difference), and material properties of the monitoring area on the surface of the structure, and introduces structural type correction coefficient and spatial weight coefficient to achieve a comprehensive assessment of the degree of deformation. Through the collaborative calculation of multi-dimensional parameters, it accurately reflects the cumulative effect and spatial distribution characteristics of complex deformation of large structures, and is especially suitable for the differentiated monitoring needs of different types of structures such as bridges and high-rise buildings.

[0083] The axial strain change of the i-th sensor in the fiber Bragg grating sensor set A′ It is the difference between the most recent strain value and the earliest strain value. Similarly;

[0084] , ;

[0085] In the formula: The elastic modulus is the value at the corresponding location on the monitoring area of ​​the structure surface. The Poisson's ratio is the ratio of the location corresponding to the monitoring area on the surface of the structure. This is the initial aging factor; The activation energy of the material; It is the ideal gas constant; The absolute temperature of the environment at the corresponding location of the monitoring area on the surface of the structure during the deformation assessment stage;

[0086] Set a deformation risk threshold, obtain deformation assessment results, and determine whether the structure has deformation risk based on the comparison between the assessment results and the deformation risk threshold.

[0087] In this embodiment, the deployment path of fiber optic grating sensors is precisely planned based on a 3D model, and sensors are rationally deployed using optimization algorithms to improve the scientific nature of monitoring coverage. Strain information is stored by numbering and time differentiation to ensure data traceability and effectiveness. Deformation is jointly assessed based on a multi-sensor set, and the accuracy of deformation assessment is improved by comparing new and old data. Deformation risk is promptly determined by comparing risk thresholds, which can efficiently warn of potential safety hazards in large structures, provide a reliable basis for maintenance decisions, and effectively ensure structural safety.

[0088] It should be noted that, compared with the existing technology, its fiber Bragg grating sensor is divided into several fiber Bragg grating sensor sets, and each set is configured with a different operating cycle. Based on this setting, when finally evaluating the degree of deformation, the evaluation data should come from different time periods. The evaluation results obtained by applying the sensing data from all sensors running synchronously can better highlight the deformation characteristics of the deformation monitoring area on the structure.

[0089] The following is an application example of the method described in the above embodiments:

[0090] I. Sensor Deployment Preparation and Implementation

[0091] A cable-stayed bridge spanning a river is a large steel and concrete hybrid structure. To monitor its deformation during operation, a deformation measurement method based on a fiber optic grating sensor network was adopted. First, structural parameters were extracted from the bridge's design drawings, including the main bridge length, pier height, bridge deck width, and the connection methods and dimensions of the steel and concrete components. Based on these parameters, a three-dimensional model of the bridge was constructed.

[0092] In the 3D model, the deployment path of the fiber optic grating sensor was identified: For the connection between the bridge pier and the bridge deck (this area is a stress concentration zone and requires close monitoring), four adjacent faces with the same vertex (n=4) were identified. The connecting edges of these four faces were used as edges to construct a quadrangular pyramid (with a quadrilateral base). This pyramid was then divided such that the dividing face passed through the vertex and the base edge fell on the base. The resulting cross-section was the largest cross-section of the pyramid. The portion of the cross-section that did not belong to the base was used as the deployment reference path (measured to be 12 meters long).

[0093] The initial deployment ratio was set at 0.6 meters per point, and the initial number of deployment points was the total length of the reference path divided by the initial deployment ratio, i.e., 12 ÷ 0.6 = 20 points. The initial number was then adjusted: the apex angle of the cross-section was 60°, and the largest apex angle among all the pyramids was 80°; the cross-section height was 3 meters, and the largest cross-section height was 5 meters; because this area is a critical monitoring location with high deformation monitoring importance, the constant Ɛ was set to 0.9. After the adjustments and calculations, the final number of deployment points was determined to be 23. The reference path was divided into 22 equal segments, and fiber Bragg grating sensors were deployed at the endpoints of each segment, divided into two groups, A and B (adjacent relationship). Group A was numbered A1 to A23, and group B was numbered B1 to B23.

[0094] II. Strain Information Collection

[0095] The operating cycle configuration was performed for 46 fiber Bragg grating sensors in two groups, A and B: the material coefficient of the concrete components in this area was set to 0.8, and that of the steel structure connection parts to 1.1; the sensor manufacturing process has high precision, so the grating stability coefficient was set to 1.0; the redundancy was set to 1.3; the density coefficient was set to 0.85; due to the large diurnal temperature difference along the river, the temperature sensitivity coefficient was set to 0.75; the connection between the bridge pier and the bridge deck has high rigidity, so the stress influence coefficient was set to 0.3; the wavelength drift threshold of the critical area was set to 0.4; and the average distance between the maintenance points and the sensors was relatively short, so the spatial attenuation factor was set to 0.5. After substituting into the operating cycle calculation formula, it was determined that the sensors would collect axial strain information every 6 minutes, and the sensor number and collection time were simultaneously marked (e.g., "A1 - Day 1, 8:00", "B1 - Day 1, 8:00"). All data were stored in chronological order.

[0096] III. Selection of Deformation Monitoring Area and Assessment of Deformation Degree

[0097] On the 3D model of the bridge, the corner area where the pier connects to the bridge deck was selected as the deformation monitoring area, which corresponds to two adjacent fiber optic grating sensor sets, A and B. The earliest stored strain information (8:00 AM on day 1) and the latest stored strain information (6:00 PM on day 30) of the two sets of sensors were selected for evaluation.

[0098] During the evaluation, the structural type correction factor Because the bridge defaults to 1.2; the number of sensors per group =23; Calculate the axial strain change: The average difference between the latest and earliest strain values ​​of each sensor in group A′ is 62 microstrains, and the average difference in group B′ is 58 microstrains; Effective monitoring length of a single sensor =0.4 meters; the average change in the lateral tilt angle between the i-th and (i+1)-th sensors is 0.015 radians; the maximum spatial distance between sensor sets A′ and B′. =4 meters; the time difference between the two sets of strain information =30 days (i.e., 43,200 minutes); property coefficient of concrete-steel composite materials Take 0.85; Material aging coefficient The calculated value (considering parameters such as elastic modulus, Poisson's ratio, initial aging coefficient, material activation energy, and ambient absolute temperature) is 1.05; spatial weighting coefficient. The average is 0.9.

[0099] Substituting the above parameters into the deformation degree calculation formula, the final deformation degree assessment result of the monitored area is 0.006.

[0100] IV. Deformation Risk Assessment

[0101] According to the design standards of this cable-stayed bridge, the risk threshold for deformation was set at 0.01 (i.e., 10 mm of deformation per meter of length). Since the assessment result of 0.006 is less than the risk threshold, it is determined that there is currently no significant deformation risk in the area where the bridge piers and deck connect, and the bridge can continue to operate normally. It is recommended to maintain the current monitoring frequency.

[0102] In summary, the method described in the above embodiments accurately identifies the deployment path of fiber optic grating sensors by constructing a three-dimensional model of the structure, optimizes deployment by combining n-pyramid segmentation and point quantity correction, improves the rationality and comprehensiveness of sensor layout, controls sensor deployment costs, and limits the difficulty of subsequent sensor maintenance. It uses numbering markers and time distinctions to store strain information, evaluates deformation by combining the earliest and latest data, and incorporates multiple parameters such as structure type and material properties to improve the accuracy of deformation degree assessment. At the same time, it timely determines deformation risk by comparing risk thresholds. It can effectively adapt to large structures such as bridges and high-rise buildings, realize accurate monitoring and risk warning of deformation in key areas, provide reliable data support for the safe maintenance of structures, and ensure their stable operation.

[0103] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A large structure deformation measurement method based on fiber grating sensor network, characterized by, The method comprises the following steps: uploading structure construction parameters, constructing a structure three-dimensional model based on the structure construction parameters, traversing the structure three-dimensional model, identifying a fiber grating sensor deployment path on the structure three-dimensional model, and deploying a fiber grating sensor based on the fiber grating sensor deployment path; the structure construction parameters are derived from design drawings of the structure, and after the structure three-dimensional model is completed, all combinations of adjacent n faces with the same vertex on the structure three-dimensional model are taken as identification targets of the fiber grating sensor deployment path; the n face connecting edges of the identification target are taken as edge lines to construct an n pyramid, and the bottom surface of each n pyramid is an n polygon, that is, each n pyramid is taken as an identification target of the fiber grating sensor deployment path; the n pyramid is segmented so that the vertex of the n pyramid is on the segmentation surface, the bottom edge of the segmentation surface falls on the bottom surface of the n pyramid, and the segmentation surface is the largest cross section of the n pyramid, the contour part of the cross section contour that is not derived from the bottom surface of the n pyramid is taken as a deployment reference path of the fiber grating sensor, and the deployment reference path is identified based on the deployment reference path; each fiber grating sensor deployed on the structure is numbered, the fiber grating sensor is controlled to perceive strain information in the axial direction of the fiber grating sensor, the strain information is marked with the number of the fiber grating sensor from which the strain information is derived, and based on the perception time, all the strain information with the mark is distinguished and stored; a deformation monitoring area is selected on the structure three-dimensional model, strain information is selected from the stored strain information based on the deformation monitoring area, and the selected strain information is used to evaluate the deformation degree of the corresponding position of the structure surface monitoring area; when the deformation monitoring area is selected on the structure three-dimensional model, each fiber grating sensor set is taken as a selection target, the selected deformation monitoring area corresponds to no less than two fiber grating sensor sets, and each fiber grating sensor set has an adjacent relationship with respect to the structure surface; when the deformation degree of the corresponding position of the structure surface monitoring area is evaluated, the deformation degree is subject to: ； In the formula: is a degree of deformation; is a structure type correction coefficient; is a number of fiber grating sensors in the fiber grating sensor set; is an axial strain change of the i-th sensor in the fiber grating sensor set A' and the fiber grating sensor set B'; is an effective monitoring length of a single fiber grating sensor; is a lateral tilt angle change of the i-th fiber grating sensor and the i+1-th fiber grating sensor; is a maximum spatial distance between the fiber grating sensor set A' and the fiber grating sensor set B'; is a sensing time difference of the two groups of strain information; is a material characteristic coefficient; is a material aging coefficient; is a spatial weight coefficient; Wherein, the structure type correction coefficient The value is defined by the system user, and the structure source is derived from the bridge default value of 1.2, and the structure source is derived from the high-rise building default value of 0.8; a deformation degree risk threshold is set, a deformation degree evaluation result is obtained, and based on the comparison between the evaluation result and the deformation degree risk threshold, it is determined whether the structure has a deformation risk.

2. The method according to claim 1, wherein, The operation of identifying the deployment path based on the deployment reference path is the operation of picking up the deployment point of the fiber grating sensor on the deployment reference path: The initial pickup number of fiber grating sensor deployment points on the deployment reference path is , The total length of the deployment reference path is represented by L The basic deployment ratio is represented by R The number of fiber grating sensor deployment points initially picked up is corrected to determine the number of fiber grating sensor deployment points finally picked up on the deployment reference path , denoted as N; wherein: is the angle of the top corner of the tangent plane; is the maximum angle of the top corner of the tangent plane of all n-pyramids; is the height of the tangent plane; is the maximum value of the height of the tangent plane of all n-pyramids; is a constant; Wherein, constant ∈ (0, 1], user-defined n-pyramid corresponding to the upper part of the structure of the deformation monitoring key degree, the greater the deformation monitoring key degree, the greater the constant The value, after N is determined, the reference path is divided into N-1 segments, and each segment endpoint is marked as a deployment point of the fiber grating sensor.

3. The method according to claim 1, wherein, the running cycle of the fiber grating sensor is subject to: ； In the formula: is the material coefficient of the fiber grating sensor deployment location; is the grating stability coefficient of the fiber grating sensor; is the redundancy of the fiber grating sensor; is the density coefficient of the fiber grating sensor; is the temperature sensitivity coefficient of the fiber grating sensor deployment location; is the environmental temperature difference amplitude of the fiber grating sensor deployment location; is the stress influence coefficient of the fiber grating sensor deployment location; is the maximum stress value of the fiber grating sensor deployment location; is the data sampling frequency of the fiber grating sensor; is the wavelength drift threshold of the fiber grating sensor; is the spatial attenuation factor of the fiber grating sensor; wherein, based on the above formula, each fiber grating sensor set deployed on each deployment path is taken as a calculation target, and an independent running cycle is configured for each fiber grating sensor set deployed on each deployment path.

4. The method according to claim 3, wherein, Material coefficient of the fiber grating sensor deployment position The value is subject to: metal material takes 1.0-1.3; concrete material takes 0.7-0.9; composite material takes 0.8-1.1, and is subject to the greater the material strength of the fiber grating sensor deployment position, the higher the stability, The greater the value is; Fiber grating sensor grating stability coefficient The value is [0.5, 1.1], and the higher the manufacturing process precision is, the better the quality performance is, The greater the value is; ； Temperature sensitivity coefficient of fiber grating sensor deployment location The value range is , and the greater the diurnal temperature difference of the fiber grating sensor deployment location, the greater the value. Stress influence coefficient of fiber grating sensor deployment position The value range is , and the greater the rigidity of the fiber grating sensor deployment position, the smaller the value. Wavelength shift threshold for fiber grating sensors The value is smaller when the deformation monitoring criticality of the fiber grating sensor deployment position corresponding to the upper part of the structure is greater. Spatial attenuation factor of fiber grating sensors The value of the sensor is subject to the average distance between each sensor in the fiber grating sensor set and the maintenance point, the greater the value. The maintenance point is a fixed place or a temporary work point preset for daily inspection, data reading, fault maintenance, and equipment calibration of each fiber grating sensor set.

5. The method according to claim 1, wherein After the deformation monitoring area is selected, the fiber grating sensor set corresponding to the deformation monitoring area is taken as a query target, the query target points to the strain information in the stored strain information, and a set of the latest stored strain information is obtained for each query target pointed strain information, which is used for evaluating the deformation degree of the corresponding position of the structure surface monitoring area.

6. The method according to claim 1, wherein In the evaluation of the deformation degree of the structure surface monitoring area corresponding position, the earliest stored strain information of each fiber grating sensor set corresponding to the deformation monitoring area is synchronously acquired, and the deformation degree of the structure surface monitoring area corresponding position is evaluated based on the earliest stored strain information and the latest stored strain information. In the evaluation of the deformation degree of the structure surface monitoring area corresponding position, the earliest stored strain information of each fiber grating sensor set corresponding to the deformation monitoring area is synchronously acquired, and the deformation degree of the structure surface monitoring area corresponding position is evaluated based on the earliest stored strain information and the latest stored strain information. In the evaluation of the deformation degree of the structure surface monitoring area corresponding position, the earliest stored strain information of each fiber grating sensor set corresponding to the deformation monitoring area is synchronously acquired, and the deformation degree of the structure surface monitoring area corresponding position is evaluated based on the earliest stored strain information and the latest stored strain information.

7. The method according to claim 6, wherein The axial strain variation of the i-th sensor in the fiber grating sensor set A' is the difference between the latest strain value and the earliest strain value, Similarly; ， ； In the formula: is the elastic modulus of the corresponding position of the surface monitoring area of the structure; is the Poisson's ratio of the corresponding position of the surface monitoring area of the structure; is the initial aging coefficient; is the material activation energy; is the ideal gas constant; is the absolute temperature of the environment in which the corresponding position of the surface monitoring area of the structure is located in the deformation degree evaluation stage.

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