Rockfill dam concrete face plate strain soft sensing method and system

Abstract

The application discloses a kind of rock-fill dam concrete faceplate strain soft sensing method and system of structural safety monitoring technical field, the method includes: obtaining the monitoring data of rock-fill body deformation sensor, input to the mapping model constructed in advance, the monitoring data of concrete faceplate strain virtual sensor is calculated;The construction of mapping model includes: according to actual rock-fill dam engineering, finite element simulation model is established;Using finite element simulation model, the situation of rock-fill body deformation and concrete faceplate strain under environmental load is simulated, and simulation result data is obtained;The mapping relationship between rock-fill body deformation and concrete faceplate strain is established by actually collected rock-fill body deformation monitoring data, concrete faceplate strain monitoring data and simulation result data;Based on mapping relationship, the final mapping model is constructed.The rock-fill dam concrete faceplate strain soft sensing method of the application can provide more comprehensive faceplate strain virtual monitoring data under the condition of low monitoring cost.

Description

TECHNICAL FIELD

[0001] The present application relates to a kind of rock-fill dam concrete faceplate strain soft sensing method and system, belong to structural safety monitoring technical field. BACKGROUND

[0002] Generally, strain gauge is arranged at the key position of concrete faceplate rock-fill dam panel to monitor the stress state of panel structure, and the position of strain gauge is generally selected according to engineering experience and finite element simulation calculation results in the design stage.

[0003] For super high dam or concrete faceplate rock-fill dam with poor dam material (foundation) conditions, the panel usually bears large and complex stress, and the accurate arrangement and stable operation of strain gauge are more important, but due to inaccurate estimation of engineering parameters, the strain gauge arranged sparsely according to engineering experience and finite element simulation calculation results in the design stage is difficult to accurately capture the maximum value of panel strain, and the survival rate is also low due to the harsh working conditions. SUMMARY

[0004] The present application aims to overcome the deficiencies in the prior art, and provides a kind of rock-fill dam concrete faceplate strain soft sensing method and system, which can provide more comprehensive panel strain virtual monitoring data under the condition of low monitoring cost.

[0005] To achieve the above-mentioned purpose, the present application is realized by using the following technical scheme:

[0006] In the first aspect, the present application provides a kind of rock-fill dam concrete faceplate strain soft sensing method, comprising:

[0007] The monitoring data of rockfill deformation sensor is obtained, and input to the mapping model constructed in advance, to calculate the monitoring data of concrete faceplate strain virtual sensor;

[0008] The construction of the mapping model comprises:

[0009] According to the actual rock-fill dam project, a finite element simulation model is established;

[0010] The material parameters in the finite element simulation model are inverted and calibrated using the actually collected rockfill deformation monitoring data and concrete faceplate strain monitoring data, to obtain the finite element simulation model after parameter calibration;

[0011] The parameter calibrated finite element simulation model is used to simulate the deformation of rockfill and the strain of concrete faceplate under real environmental load, to obtain simulation result data;

[0012] The mapping relationship between rockfill deformation and concrete faceplate strain is established by the actually collected rockfill deformation monitoring data, concrete faceplate strain monitoring data and simulation result data;

[0013] Based on the mapping relationship, a final mapping model is constructed.

[0014] Further, the actually collected rockfill deformation monitoring data includes monitoring data of rockfill deformation sensors ; the actually collected concrete panel strain monitoring data includes monitoring data of concrete panel strain sensors ;

[0015] Y Fig. 1 = [ y 1 Fig. 2 y 2 Fig. 3 ⋮ y p Fig. 4 ] ; S Fig. 1 = [ s 1 Fig. 2 s 2 Fig. 2 ⋮ s q Fig. 3 ] ;

[0016] In the formula: represents monitoring data of a rockfill deformation sensor numbered , , represents the total number of rockfill deformation sensors; represents monitoring data of a concrete panel strain sensor numbered , , represents the total number of concrete panel strain sensors; and are time series vectors.

[0017] Further, the parameter-calibrated finite element simulation model is used to simulate the deformation of the rockfill and the strain of the concrete panel under real environmental loads to obtain simulation result data, including:

[0018] The parameter-calibrated finite element simulation model includes a plurality of rockfill calculation nodes and concrete panel calculation nodes, and the deformation simulation result data of the rockfill calculation nodes and the strain simulation result data of the concrete panel calculation nodes are calculated and extracted.

[0019] Y ¯ = [ y 1 ¯ y 2 ¯ ⋮ y i ¯ ] ; S ¯ = [ s 1 ¯ s 2 ¯ ⋮ s J ¯ ] ;

[0020] In the formula: represents deformation simulation results at a rockfill calculation node numbered , , represents the total number of rockfill calculation nodes; represents strain simulation results at a concrete panel calculation node numbered , , represents the total number of concrete panel calculation nodes; and are time series vectors.

[0021] Further, the calculation nodes are divided into monitoring nodes and virtual nodes, the monitoring nodes include rockfill monitoring nodes and concrete panel monitoring nodes, the positions of which respectively correspond to the actual positions of rockfill deformation sensors and concrete panel strain sensors one by one; the virtual nodes include rockfill virtual nodes and concrete panel virtual nodes;

[0022] The deformation simulation result data and the strain simulation result data of the rockfill monitoring nodes and the concrete panel monitoring nodes are respectively denoted as and The deformation simulation result data and the strain simulation result data of the rockfill virtual nodes and the concrete panel virtual nodes are respectively denoted as and and are constrained by the following relations:

[0023] ; ; .

[0024] Further, a mapping relationship between the rockfill deformation and the concrete panel strain is established by the actually collected rockfill deformation monitoring data, concrete panel strain monitoring data and simulation result data, including:

[0025] According to the deformation simulation result data of the rockfill monitoring nodes and the strain simulation result data of the concrete panel monitoring nodes , a mapping relationship between the rockfill monitoring nodes and the concrete panel monitoring nodes is established , as shown in the following formula, the mapping relationship is represented by a transfer function tensor :

[0026] ;

[0027] According to the deformation simulation result data of the rockfill monitoring nodes and the strain simulation result data of the concrete panel virtual nodes , a mapping relationship between the rockfill monitoring nodes and the concrete panel virtual nodes is established , as shown in the following formula, the mapping relationship is represented by a transfer function tensor :

[0028] ;

[0029] According to the monitoring data of the rockfill deformation sensors and the monitoring data of the concrete panel strain sensors , the mapping relationship between the actual monitoring data of the rockfill body monitoring node and the concrete panel monitoring node is established , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows

[0030] , the mapping relationship is shown as follows ; ; ;

[0031] , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows

[0032] Further, based on the mapping relationship, a final mapping model is constructed, including:

[0033] , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows

[0034] , the mapping relationship is shown as follows ; ; ;

[0035] , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows

[0036] , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows

[0037] , the mapping relationship is shown as follows ; ;

[0038] , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows , the mapping relationship is shown as follows

[0039] ; ;

[0040] In the formula: This represents the monitoring data provided by the virtual sensor for concrete panel strain at the virtual node of the concrete panel.

[0041] Secondly, the present invention provides a soft-sensing system for strain of concrete panels in rockfill dams, comprising:

[0042] The simulation and parameter calibration module is used to establish a finite element simulation model based on the actual rockfill dam project, and to perform inversion calibration of the material parameters in the finite element simulation model using the actual collected deformation monitoring data of the rockfill body and strain monitoring data of the concrete panel.

[0043] The environmental load simulation module is used to simulate the deformation of the rockfill and the strain of the concrete panel under real environmental loads using a finite element simulation model after parameter calibration, and obtain simulation result data.

[0044] The mapping model establishment module is used to establish a mapping relationship between the deformation of the rockfill and the strain of the concrete panel by using the actual collected deformation monitoring data of the rockfill, the strain monitoring data of the concrete panel and the simulation result data, and to construct the final mapping model based on the mapping relationship.

[0045] The virtual monitoring data calculation module is used to calculate the monitoring data of the virtual sensor for concrete panel strain using the final mapping model.

[0046] Furthermore, the actual collected rockfill deformation monitoring data includes monitoring data from rockfill deformation sensors. The actual collected concrete panel strain monitoring data includes monitoring data from concrete panel strain sensors. ;

[0047] Y Fig. 4 = [ y 1 Fig. 1 y 2 Fig. 2 ⋮ y p Fig. 3 ] ; S Fig. 4 = [ s 1 Fig. 1 s 2 Fig. 2 ⋮ s q Fig. 2 ] ;

[0048] In the formula: Indicates the number is The monitoring data from the deformation sensors of the rockfill mass, , This indicates the total number of deformation sensors on the rockfill. Indicates the number is Monitoring data from strain sensors on concrete panels, , This indicates the total number of strain sensors on the concrete panel; and All are time-series vectors.

[0049] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0050] The present invention provides a soft-sensing method for the strain of concrete panels in rockfill dams. By establishing a finite element simulation model and combining it with actual monitoring data, this method achieves soft sensing of concrete panel strain, significantly improving monitoring efficiency and coverage. The method uses actual monitoring data to inversely calibrate the model parameters, ensuring the accuracy of the simulation results. Furthermore, by establishing a mapping relationship between rockfill deformation and concrete panel strain, high-precision virtual monitoring data is calculated. This not only reduces reliance on physical sensors and lowers monitoring costs, but also provides real-time and continuous strain information for the concrete panels, offering reliable data support for the safety assessment and early warning of rockfill dams, and possesses significant engineering application value. Attached Figure Description

[0051] Fig. 3 This is a flowchart of the mapping model construction provided in Embodiment 1 of the present invention;

[0052] Fig. 4 This is a schematic diagram of a concrete-faced rockfill dam provided in Embodiment 1 of the present invention;

[0053] ​ This is a schematic cross-section diagram of a finite element simulation model of a concrete-faced rockfill dam provided in Embodiment 1 of the present invention;

[0054] ​ This is a schematic diagram of the mapping relationship between a concrete-faced rockfill dam and a finite element simulation model provided in Embodiment 1 of the present invention;

[0055] The meanings of the labels in the figures are as follows:

[0056] 101. Concrete-faced rockfill dam; 102. Rockfill body; 103. Concrete face; 104. Rockfill body deformation sensor; 105. Concrete face strain sensor; 106. Virtual strain sensor for concrete face; 201. Finite element simulation model; 202. Finite element simulation model of rockfill body; 203. Finite element simulation model of concrete face; 204. Rockfill body monitoring node; 205. Virtual node of rockfill body; 206. Concrete face monitoring node; 207. Virtual node of concrete face. Detailed Implementation

[0057] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0058] Example 1:

[0059] The soft strain sensing method for concrete panels of rockfill dams provided in this embodiment specifically includes the following steps:

[0060] The monitoring data from the deformation sensors of the rockfill body is acquired and input into a pre-built mapping model to calculate the monitoring data from the virtual sensors of the concrete panel strain.

[0061] The construction of the mapping model, such as ​ As shown, it includes:

[0062] Based on the actual rockfill dam project, a finite element simulation model 201 was established;

[0063] Using the actual collected deformation monitoring data of the rockfill and the strain monitoring data of the concrete panel, the material parameters in the finite element simulation model 201 were inverted and calibrated to obtain the finite element simulation model after parameter calibration.

[0064] Using the finite element simulation model after parameter calibration, the deformation of the rockfill and the strain of the concrete panel under real environmental loads were simulated to obtain simulation results data.

[0065] By collecting actual data on rockfill deformation monitoring, concrete panel strain monitoring, and simulation results, a mapping relationship between rockfill deformation and concrete panel strain is established.

[0066] Based on the mapping relationship, the final mapping model is constructed.

[0067] Traditionally, engineers install strain gauges (sensors) on concrete panels to monitor panel deformation. However, the number of these strain gauges is limited, and their placement is not always ideal, especially in cases of ultra-high dams or complex geological conditions, where the strain gauges may fail to accurately capture the point of maximum panel deformation. Moreover, strain gauges are prone to damage in harsh environments, leading to incomplete data.

[0068] Therefore, this embodiment uses the deformation data of the riprap to infer the strain of the concrete panel. By utilizing the deformation data of the riprap and combining it with a computer-implemented finite element simulation model 201, the strain of the concrete panel is "virtually" calculated, thereby compensating for the shortcomings of traditional strain gauges and providing more comprehensive and accurate strain data.

[0069] The present invention relates to a soft-sensing method for the strain of concrete panels in rockfill dams. This method aims to establish a mapping relationship between the deformation of the rockfill body and the strain of the concrete panels using a finite element simulation model 201 and actual monitoring data, thereby achieving soft sensing of the concrete panel strain. The core of this method lies in utilizing finite element simulation technology, combined with actual monitoring data, to construct a mathematical model that accurately reflects the deformation and strain behavior of the rockfill dam under real environmental loads. This model is then used to calculate virtual strain data for the concrete panels, thus supplementing the information on the strain of the concrete panels.

[0070] First, based on actual rockfill dam projects, a finite element simulation model 201 was established, including information on the geometry, material properties, and boundary conditions of the rockfill body and concrete face. The main structure of a rockfill dam consists primarily of the rockfill body and the concrete face. The rockfill body, as the core supporting component of the dam, is constructed of rock and bears the weight of the dam itself, upstream and downstream water pressure, and other loads. The concrete face, located on the upstream face of the dam, is an important seepage prevention structure and is mostly made of reinforced concrete. For example... ​ As shown, the finite element simulation model 201 established in this embodiment includes a finite element simulation model 202 for the rockfill dam and a finite element simulation model 203 for the concrete panel. The establishment of the finite element simulation model 201 is the foundation of the entire process, and its accuracy directly affects the subsequent simulation results and the establishment of mapping relationships. Using finite element analysis software (such as ANSYS, ABAQUS, etc.), the structural characteristics of the rockfill dam are accurately simulated, providing a basis for subsequent material parameter inversion calibration.

[0071] Next, the material parameters in the finite element simulation model 201 are calibrated by inversion using actual monitoring data. For example... ​ As shown, the main structure of the concrete-faced rockfill dam 101 includes the core supporting part of the dam, the rockfill body 102, and the concrete face 103 located on the upstream face of the dam. The actual collected deformation monitoring data of the rockfill body and the strain monitoring data of the concrete face include monitoring data extracted from the concrete face strain sensor 105. and monitoring data extracted from rockfill deformation sensor 104 As shown in the following formula:

[0072] ; ;

[0073] In the formula: Indicates the number is The monitoring data from the deformation sensors of the rockfill mass, , This indicates the total number of deformation sensors on the rockfill. Indicates the number is Monitoring data from strain sensors on concrete panels, , This indicates the total number of strain sensors on the concrete panel; and All are time-series vectors.

[0074] By optimizing algorithms (such as genetic algorithms and particle swarm optimization), the material parameters in the finite element simulation model 201 are adjusted to minimize the error between the simulation results and the actual monitoring data. The purpose of this step is to ensure that the finite element simulation model 201 can accurately reflect the mechanical behavior of the rockfill dam under actual working conditions, thereby improving the reliability of the simulation results.

[0075] After completing the material parameter inversion calibration, the deformation of the rockfill dam and the strain of the concrete panel were simulated under real environmental loads using the calibrated finite element simulation model 201. Real environmental loads include external factors such as water pressure and temperature changes, which significantly affect the deformation and strain of the rockfill dam. Finite element simulation model 201 contains several calculation nodes for the rockfill dam and the concrete panel. Deformation simulation results from the rockfill calculation nodes were extracted using finite element simulation model 201. Strain simulation results data of concrete panel calculation nodes As shown in the following formula:

[0076] ; ;

[0077] In the formula: Indicates the number is The simulation results of deformation at the calculation nodes of the riprap body. , This represents the total number of calculation nodes for the rockfill structure; Indicates the number is The simulation results of strain at the joint of the concrete panel are calculated. , This indicates the total number of calculated nodes for the concrete panel; and All are time-series vectors.

[0078] These simulation results provide important data support for the subsequent establishment of mapping relationships.

[0079] The computing nodes are divided into monitoring nodes and virtual nodes, such as... ​ As shown, the monitoring nodes include a rockfill monitoring node 204 and a concrete panel monitoring node 206, whose positions correspond one-to-one with the actual positions of the rockfill deformation sensor 104 and the concrete panel strain sensor 105, respectively; the virtual nodes include a rockfill virtual node 205 and a concrete panel virtual node 207.

[0080] The deformation simulation results and strain simulation results of monitoring node 204 of the riprap and monitoring node 206 of the concrete panel are respectively denoted as: and The deformation simulation results and strain simulation results of virtual node 205 of the riprap and virtual node 206 of the concrete panel are respectively denoted as... and And it is subject to the following relation:

[0081] ; ; .

[0082] Finally, using the established mapping relationship, virtual monitoring data of the concrete panel is calculated to achieve soft sensing of the concrete panel strain. Specifically, the monitoring data of the rockfill deformation sensor 104 is input, and the virtual strain monitoring data of the virtual node 207 of the concrete panel is calculated through the mapping model. This virtual monitoring data can be used as the output of the concrete panel strain virtual sensor 106 to achieve real-time monitoring of the concrete panel strain. In this way, comprehensive monitoring of concrete panel strain can be achieved without adding physical sensors, thereby reducing monitoring costs and improving monitoring efficiency.

[0083] Data obtained from actual monitoring data and simulation results calculated using the finite element simulation model 201, such as... ​ As shown, a mapping relationship is established between the deformation of the riprap and the strain of the concrete panel. The key to this step is matching the actual monitoring data provided by the sensors with the simulation data provided by the finite element simulation model 201, and using the transfer function tensor to establish a mathematical model between the two. The transfer function tensor can be solved using the least squares method or other optimization methods. Its purpose is to map the deformation data of the riprap onto the strain data of the concrete panel, thereby achieving soft sensing of the concrete panel strain.

[0084] Specifically, the process of establishing each mapping relationship is as follows:

[0085] (1) Establish the mapping relationship between monitoring node 204 of the rockfill body and monitoring node 206 of the concrete panel.

[0086] Based on the deformation simulation results of monitoring node 204 of the riprap body Strain simulation results data of monitoring node 206 of concrete panel Establish a mapping relationship between monitoring node 204 of the riprap body and monitoring node 206 of the concrete panel. As shown in the following formula, the mapping relationship is... From the transfer function tensor express:

[0087] ;

[0088] Mapping relationship Its purpose is to reveal the intrinsic connection between the simulation data of the rockfill deformation monitoring node and the concrete panel strain monitoring node, providing a foundation for the construction of more complex relationships in the future, and building a bridge between the two from the perspective of simulation data.

[0089] (2) Establish the mapping relationship between monitoring node 204 of the rockfill body and virtual node 207 of the concrete panel.

[0090] Based on the deformation simulation results of monitoring node 204 of the riprap body Strain simulation results data of virtual node 207 of concrete panel Establish a mapping relationship between monitoring node 204 of the rockfill and virtual node 207 of the concrete panel. As shown in the following formula, the mapping relationship is... From the transfer function tensor express:

[0091] ;

[0092] Mapping relationship It is mainly used to establish the relationship between the deformation monitoring nodes of the rockfill and the strain virtual nodes of the concrete panel (corresponding to the strain virtual sensor 106 of the concrete panel), and to use the monitoring information of the rockfill to estimate the strain of the strain virtual sensor 106 of the concrete panel, thereby expanding the coverage of strain monitoring.

[0093] (3) Establish a mapping relationship between the actual monitoring data of the rockfill monitoring node 204 and the concrete panel monitoring node 206.

[0094] Based on monitoring data extracted from rockfill deformation sensor 104 and monitoring data extracted from concrete panel strain sensor 105 Establish a mapping relationship between the actual monitoring data of monitoring node 204 of the rockfill and monitoring node 206 of the concrete panel. As shown in the following formula, the mapping relationship is... From the transfer function tensor express:

[0095] ; ; ;

[0096] In the formula: This represents the monitoring data provided by the concrete panel strain sensor at the concrete panel monitoring node; This represents the monitoring data provided by the rockfill deformation sensor at the rockfill monitoring node; and All are time-series vectors.

[0097] Mapping relationship This reflects the actual correlation between the monitoring data of the rockfill deformation monitoring node 204 and the concrete panel strain monitoring node 206, organically combining the actual monitoring data to make the relationship more consistent with the actual monitoring situation.

[0098] Next, integrate the mapping relationships. and Establish a mapping model The mapping model This is used to combine simulation results data with actual monitoring data, as shown in the following formula, mapping model. From the transfer function tensor express:

[0099] ; ; ;

[0100] In the formula: for The generalized inverse matrix;

[0101] By integrating the relationship between simulation results data and actual monitoring data, virtual strain monitoring results can better reflect reality and effectively improve monitoring accuracy.

[0102] Based on mapping relationship and mapping model Establish a mapping model The mapping model The virtual monitoring data used to calculate the virtual node 207 of the concrete panel is shown in the following formula, mapping model. From the transfer function tensor express:

[0103] ; ;

[0104] The monitoring data of the rockfill deformation sensor 104 Input to the final mapping model Calculate the monitoring data of the virtual sensor 106 for concrete panel strain. As shown in the following formula:

[0105] ; ;

[0106] In the formula: This represents the monitoring data provided by the virtual sensor for concrete panel strain at virtual node 207 of the concrete panel.

[0107] In summary, this invention provides an efficient and low-cost method for monitoring the strain of concrete panels in rockfill dams by combining finite element simulation technology with actual monitoring data. This method not only enables real-time monitoring of concrete panel strain but also provides crucial data support for the safety assessment and maintenance of rockfill dams, demonstrating broad application prospects.

[0108] The following specific embodiment further illustrates the implementation of the present invention.

[0109] A concrete-faced rockfill dam project is underway, with a dam height of 120 meters and a crest length of 250 meters. The thickness of the concrete face varies from 0.3 meters to 0.72 meters, and the rockfill material is limestone crushed stone. Deformation sensors 104 for the rockfill and strain sensors 105 for the concrete face are installed to monitor the deformation and strain of the dam.

[0110] Based on the geometry, material properties, and boundary conditions of the rockfill dam, a finite element simulation model 201 was established using ANSYS software. The finite element simulation model 201 contains 20,000 calculation nodes for the rockfill body and 500 calculation nodes for the concrete panel. The monitoring nodes include rockfill body monitoring node 204 and concrete panel monitoring node 206, whose positions correspond one-to-one with the actual positions of the rockfill body deformation sensor 104 and the concrete panel strain sensor 105, respectively. The virtual nodes include rockfill body virtual node 205 and concrete panel virtual node 207.

[0111] Monitoring data were extracted from the rockfill deformation sensor 104 and the concrete panel strain sensor 105 and denoted as a time-series vector. A genetic algorithm was used to adjust the material parameters in the finite element simulation model to minimize the error between the simulation results and the actual monitoring data. After multiple iterations, the parameter-calibrated finite element simulation model 201 was finally obtained.

[0112] In the finite element simulation model 201 after parameter calibration, environmental loads from actual engineering (such as water pressure, temperature changes, etc.) are applied, and finite element simulation calculations are performed. Deformation simulation results data of the calculation nodes of the rockfill and strain simulation results data of the calculation nodes of the concrete panel are extracted.

[0113] By matching actual monitoring data with simulation data, a mapping model between the deformation sensor monitoring data of the riprap and the virtual node 207 of the concrete panel is established using the transfer function tensor. The mapping model is obtained by solving the transfer function tensor using the least squares method.

[0114] Input the monitoring data from the rockfill deformation sensor 104, and use the mapping model to calculate the virtual strain monitoring data of the concrete panel virtual node 207. Output the virtual strain monitoring data of the concrete panel as the monitoring data of the concrete panel strain virtual sensor 106.

[0115] This invention establishes a finite element simulation model 201 and combines it with actual monitoring data to achieve soft sensing of the strain of the concrete panel of a rockfill dam. This method can effectively reduce monitoring costs and improve monitoring efficiency, providing a new technical means for the safety monitoring of rockfill dams.

[0116] Example 2:

[0117] This invention also provides a soft-sensing system for strain of concrete panels in rockfill dams, comprising:

[0118] The simulation and parameter calibration module is used to establish a finite element simulation model 201 based on the actual rockfill dam project, and to perform inversion calibration of the material parameters in the finite element simulation model 201 using the actual collected deformation monitoring data of the rockfill body and the strain monitoring data of the concrete panel.

[0119] The environmental load simulation module is used to simulate the deformation of the rockfill and the strain of the concrete panel under real environmental loads using the finite element simulation model 201 after parameter calibration, and obtain simulation result data.

[0120] The mapping model establishment module is used to establish a mapping relationship between the deformation of the rockfill and the strain of the concrete panel by using the actual collected deformation monitoring data of the rockfill, the strain monitoring data of the concrete panel and the simulation result data, and to construct the final mapping model based on the mapping relationship.

[0121] The virtual monitoring data calculation module is used to calculate the monitoring data of the virtual sensors for concrete panel strain using the final mapping model. The actual collected rockfill deformation monitoring data includes the monitoring data from the rockfill deformation sensors. The actual collected concrete panel strain monitoring data includes monitoring data from concrete panel strain sensors. ;

[0122] Y ​ = [ y 1 ​ y 2 ​ ⋮ y p ​ ] ; S ​ = [ s 1 ​ s 2 ​ ⋮ s q ​ ] ;

[0123] In the formula: Indicates the number is The monitoring data from the deformation sensors of the rockfill mass, , This indicates the total number of deformation sensors on the rockfill. Indicates the number is Monitoring data from strain sensors on concrete panels, , This indicates the total number of strain sensors on the concrete panel; and All are time-series vectors.

[0124] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A soft-sensing method for strain of concrete panels in rockfill dams, characterized in that, include: The monitoring data from the deformation sensors of the rockfill body is acquired and input into a pre-built mapping model to calculate the monitoring data from the virtual sensors of the concrete panel strain. The construction of the mapping model includes: A finite element simulation model was established based on the actual rockfill dam project. Using the actual collected deformation monitoring data of the rockfill and the strain monitoring data of the concrete panel, the material parameters in the finite element simulation model were inverted and calibrated to obtain the parameter-calibrated finite element simulation model. Using the finite element simulation model after parameter calibration, the deformation of the rockfill and the strain of the concrete panel under real environmental loads were simulated to obtain simulation results data. By collecting actual data on rockfill deformation monitoring, concrete panel strain monitoring, and simulation results, a mapping relationship between rockfill deformation and concrete panel strain is established. Based on the mapping relationship, the final mapping model is constructed; Using the finite element simulation model with the parameters calibrated, the deformation of the riprap and the strain of the concrete panel were simulated under real environmental loads, and the simulation results data were obtained, including: The parameter-calibrated finite element simulation model includes several rockfill calculation nodes and concrete panel calculation nodes. The deformation simulation results data of the rockfill calculation nodes are calculated and extracted. Strain simulation results data of concrete panel calculation nodes ; ； ； In the formula: Indicates the number is The simulation results of deformation at the calculation nodes of the riprap body. , This represents the total number of calculation nodes for the rockfill structure; Indicates the number is The simulation results of strain at the joint of the concrete panel are calculated. , This indicates the total number of calculated nodes for the concrete panel; and All are time-series vectors; The computing nodes are divided into monitoring nodes and virtual nodes. The monitoring nodes include rockfill monitoring nodes and concrete panel monitoring nodes, whose positions correspond one-to-one with the actual positions of rockfill deformation sensors and concrete panel strain sensors, respectively. The virtual nodes include rockfill virtual nodes and concrete panel virtual nodes. The deformation simulation results and strain simulation results of the rockfill monitoring node and the concrete panel monitoring node are respectively denoted as... and The deformation simulation results and strain simulation results of the virtual nodes of the riprap and the virtual nodes of the concrete panel are respectively denoted as... and And it is subject to the following relation: ； ； ； By using actual collected data on rockfill deformation monitoring, concrete panel strain monitoring, and simulation results, a mapping relationship between rockfill deformation and concrete panel strain is established, including: Based on the deformation simulation results of the monitoring nodes of the riprap body Strain simulation results data of concrete panel monitoring nodes Establish a mapping relationship between monitoring nodes of the riprap body and monitoring nodes of the concrete panel. As shown in the following formula, the mapping relationship is... From the transfer function tensor express: ； Based on the deformation simulation results of the monitoring nodes of the riprap body Strain simulation results data of virtual nodes of concrete panels Establish a mapping relationship between monitoring nodes of the riprap body and virtual nodes of the concrete panel. As shown in the following formula, the mapping relationship is... From the transfer function tensor express: ； Based on the monitoring data of the rockfill deformation sensor Monitoring data from concrete panel strain sensors Establish a mapping relationship between the actual monitoring data of the rockfill monitoring nodes and the concrete panel monitoring nodes. As shown in the following formula, the mapping relationship is... From the transfer function tensor express: ； ； ； In the formula: This represents the monitoring data provided by the concrete panel strain sensor at the concrete panel monitoring node; This represents the monitoring data provided by the rockfill deformation sensor at the rockfill monitoring node; and All are time-series vectors; Based on the mapping relationship, the final mapping model is constructed, including: Based on mapping relationship and Establish a mapping model The mapping model This is used to combine simulation results data with actual monitoring data, as shown in the following formula, mapping model. From the transfer function tensor express: ； ； ； In the formula: for The generalized inverse matrix; Based on mapping relationship and mapping model And establish the final mapping model As shown in the following equation, the final mapping model From the transfer function tensor express: ； ； Monitoring data from deformation sensors of the rockfill mass Input to the final mapping model Calculate the monitoring data of virtual sensors for concrete panel strain. As shown in the following formula: ； ； In the formula: This represents the monitoring data provided by the virtual sensor for concrete panel strain at the virtual node of the concrete panel.

2. The soft-sensing method for strain of concrete panels in rockfill dams according to claim 1, characterized in that, The actual collected rockfill deformation monitoring data includes monitoring data from rockfill deformation sensors. The actual collected concrete panel strain monitoring data includes monitoring data from concrete panel strain sensors. ; ； ； In the formula: Indicates the number is The monitoring data from the deformation sensors of the rockfill mass, , This indicates the total number of deformation sensors on the rockfill. Indicates the number is Monitoring data from strain sensors on concrete panels, , This indicates the total number of strain sensors on the concrete panel; and All are time-series vectors.

3. A soft-sensing system for strain of concrete panels in rockfill dams, characterized in that, include: The simulation and parameter calibration module is used to establish a finite element simulation model based on the actual rockfill dam project, and to perform inversion calibration of the material parameters in the finite element simulation model using the actual collected deformation monitoring data of the rockfill body and strain monitoring data of the concrete panel. The environmental load simulation module is used to simulate the deformation of the rockfill and the strain of the concrete panel under real environmental loads using a finite element simulation model after parameter calibration, and obtain simulation result data. The mapping model establishment module is used to establish a mapping relationship between the deformation of the rockfill and the strain of the concrete panel by using the actual collected deformation monitoring data of the rockfill, the strain monitoring data of the concrete panel and the simulation result data, and to construct the final mapping model based on the mapping relationship. The virtual monitoring data calculation module is used to calculate the monitoring data of the virtual sensor for the strain of the concrete panel using the final mapping model. Using the finite element simulation model with the parameters calibrated, the deformation of the riprap and the strain of the concrete panel were simulated under real environmental loads, and the simulation results data were obtained, including: The parameter-calibrated finite element simulation model includes several rockfill calculation nodes and concrete panel calculation nodes. The deformation simulation results data of the rockfill calculation nodes are calculated and extracted. Strain simulation results data of concrete panel calculation nodes ; ； ； In the formula: Indicates the number is The simulation results of deformation at the calculation nodes of the riprap body. , This represents the total number of calculation nodes for the rockfill structure; Indicates the number is The simulation results of strain at the joint of the concrete panel are calculated. , This indicates the total number of calculated nodes for the concrete panel; and All are time-series vectors; The computing nodes are divided into monitoring nodes and virtual nodes. The monitoring nodes include rockfill monitoring nodes and concrete panel monitoring nodes, whose positions correspond one-to-one with the actual positions of rockfill deformation sensors and concrete panel strain sensors, respectively. The virtual nodes include rockfill virtual nodes and concrete panel virtual nodes. The deformation simulation results and strain simulation results of the rockfill monitoring node and the concrete panel monitoring node are respectively denoted as... and The deformation simulation results and strain simulation results of the virtual nodes of the riprap and the virtual nodes of the concrete panel are respectively denoted as... and And it is subject to the following relation: ； ； ； By using actual collected data on rockfill deformation monitoring, concrete panel strain monitoring, and simulation results, a mapping relationship between rockfill deformation and concrete panel strain is established, including: Based on the deformation simulation results of the monitoring nodes of the riprap body Strain simulation results data of concrete panel monitoring nodes Establish a mapping relationship between monitoring nodes of the riprap body and monitoring nodes of the concrete panel. As shown in the following formula, the mapping relationship is... From the transfer function tensor express: ； Based on the deformation simulation results of the monitoring nodes of the riprap body Strain simulation results data of virtual nodes of concrete panels Establish a mapping relationship between monitoring nodes of the riprap body and virtual nodes of the concrete panel. As shown in the following formula, the mapping relationship is... From the transfer function tensor express: ； Based on the monitoring data of the rockfill deformation sensor Monitoring data from concrete panel strain sensors Establish a mapping relationship between the actual monitoring data of the rockfill monitoring nodes and the concrete panel monitoring nodes. As shown in the following formula, the mapping relationship is... From the transfer function tensor express: ； ； ； In the formula: This represents the monitoring data provided by the concrete panel strain sensor at the concrete panel monitoring node; This represents the monitoring data provided by the rockfill deformation sensor at the rockfill monitoring node; and All are time-series vectors; Based on the mapping relationship, the final mapping model is constructed, including: Based on mapping relationship and Establish a mapping model The mapping model This is used to combine simulation results data with actual monitoring data, as shown in the following formula, mapping model. From the transfer function tensor express: ； ； ； In the formula: for The generalized inverse matrix; Based on mapping relationship and mapping model And establish the final mapping model As shown in the following equation, the final mapping model From the transfer function tensor express: ； ； Monitoring data from deformation sensors of the rockfill mass Input to the final mapping model Calculate the monitoring data of virtual sensors for concrete panel strain. As shown in the following formula: ； ； In the formula: This represents the monitoring data provided by the virtual sensor for concrete panel strain at the virtual node of the concrete panel.

4. The soft-sensing system for strain of concrete panels in rockfill dams according to claim 3, characterized in that, The actual collected rockfill deformation monitoring data includes monitoring data from rockfill deformation sensors. The actual collected concrete panel strain monitoring data includes monitoring data from concrete panel strain sensors. ; ； ； In the formula: Indicates the number is The monitoring data from the deformation sensors of the rockfill mass, , This indicates the total number of deformation sensors on the rockfill. Indicates the number is Monitoring data from strain sensors on concrete panels, , This indicates the total number of strain sensors on the concrete panel; and All are time-series vectors.

Images