A large cavity structure deformation monitoring system and method

Abstract

This invention provides a deformation monitoring system and method for large cavitation water tunnel structures, including a distributed monitoring device and a central processing unit connected to the distributed monitoring device. The distributed monitoring device includes a sensor assembly, a data acquisition unit connected to the sensor assembly, and a controller connected to the data acquisition unit. The sensor assembly includes several strain gauges vertically arranged on the intermediate bearing base of the cavitation water tunnel structure and a temperature sensor arranged in the working space of the cavitation water tunnel structure. The data acquisition unit includes a strain acquisition unit connected to the strain gauges and a temperature acquisition unit connected to the temperature sensors. This invention has the following advantages: by deploying a small number of sensors to measure strain and temperature data, and combining this with a deformation inversion algorithm to calculate the overall temperature deformation and shaft deformation of the structure, this invention solves the problem of directly measuring and continuously monitoring the overall deformation and internal shaft deformation of large structures.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology, and in particular to a system and method for monitoring the deformation of a large cavitation water tunnel structure. Background Technology

[0002] Cavitation tunnels are crucial hydrodynamic experimental facilities for studying cavitation phenomena and turbulence effects, playing an irreplaceable role in ship model flow field measurement, hull pulsating pressure testing, cavitation erosion experiments, and fine flow analysis. During operation, the tunnel may experience overall expansion or contraction deformation due to periodic changes in ambient temperature, leading to axis misalignment in various sections and affecting experimental accuracy. Simultaneously, factors such as uneven foundation settlement and excitation motor vibration can cause vertical deformation of the drive shaft, causing it to deviate from its design axis. Severe attitude changes and structural deformations can lead to abnormal equipment operation and distorted test data, affecting the reliable operation of the tunnel facility. Therefore, continuous and reliable monitoring of the overall structural deformation and shaft deformation of the tunnel is necessary to provide data support for evaluating the validity of experimental results and analyzing the structural health status of the facility.

[0003] Existing structural deformation monitoring methods mainly include optical imaging methods and strain-based monitoring methods. Optical imaging methods utilize equipment such as laser scanners to perform non-contact scanning of the structure, acquiring high-precision geometric information, but they are complex to operate, have long measurement cycles, and are costly. Strain-based deformation monitoring methods deploy strain sensors on the structural surface to acquire discrete measurement values ​​in real time, and combine signal processing and deformation inversion algorithms to achieve online deformation monitoring of the entire structure. This method has advantages such as flexible deployment, fast response speed, and low cost, and has been applied to structures such as bridges, railways, and spacecraft. However, a systematic solution is lacking for closed, large-scale, complex structures such as large cavitation water tunnels. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a deformation monitoring system and method for large cavitation water tunnel structures, which solves the problems of complex operation, long measurement cycle and high cost of the prior art, as well as the lack of a systematic solution for such closed, large-scale complex structures as large cavitation water tunnels.

[0005] To achieve the above and other related objectives, the present invention provides the following technical solution:

[0006] A deformation monitoring system for a large cavitation water tunnel structure includes a distributed monitoring device and a central processing unit connected to the distributed monitoring device. The distributed monitoring device includes a sensor assembly, a data acquisition unit connected to the sensor assembly, and a controller connected to the data acquisition unit. The sensor assembly includes several strain gauges vertically mounted on an intermediate bearing base of the cavitation water tunnel structure and a temperature sensor mounted in the working space of the cavitation water tunnel structure. The data acquisition unit includes a strain acquisition unit connected to the strain gauges and a temperature acquisition unit connected to the temperature sensor.

[0007] In one embodiment of the present invention, the central processing unit includes a monitoring data input module, a deformation inversion module, a data processing and analysis module, a visualization display module, and a data management module; the monitoring data input module is used to receive measured data sent by the strain gauge and temperature sensor; the deformation inversion module performs deformation inversion processing on the measured data sent by the strain gauge and temperature sensor, and obtains the deformation information of the cavitation water tunnel structure based on the processing result; the data processing and analysis module is used to process and analyze the original acquired data and the inverted deformation data; the visualization display module is used to intuitively display the original monitoring data and the output results of the deformation inversion module; and the database management module is used to store, manage, and distribute the deformation data.

[0008] In one embodiment of the present invention, the deformation inversion module includes an axis deformation submodule and a temperature deformation submodule; the axis deformation submodule is used to obtain the deformation information of the cavitation water tunnel structure according to the axis deflection curve equation, and the temperature deformation submodule is used to obtain the deformation information of the cavitation water tunnel structure according to the temperature deformation inversion function.

[0009] A method for monitoring the structural deformation of a large cavitation water tunnel, based on the aforementioned large cavitation water tunnel structural deformation monitoring system, includes the following steps: determining the layout locations and acquisition frequencies of strain gauges and temperature gauges according to the structural form, operating conditions, and on-site installation conditions of the large cavitation water tunnel, combined with finite element analysis; installing strain gauges and temperature sensors at the strain gauge locations and temperature gauge locations respectively; installing the data acquisition device in a location convenient for wiring and maintenance; and then connecting the sensor signal lines to the data acquisition device and protecting it.

[0010] Based on the finite element simulation results, the temperature deformation inversion function of the large cavitation water tunnel structure is determined, and the temperature deformation inversion function is set in the temperature deformation submodule of the central processing unit located in the host computer. The controller is placed in the cabinet, and the signal and power connection between the data acquisition unit and the controller is completed. The controller is connected to the host computer through a crossover network cable, and then the power is turned on and the system is debugged. Data is collected at a preset frequency, and the collected data is input into the temperature deformation inversion function in the shaft deformation submodule and the temperature deformation submodule respectively, so as to obtain the deformation information of the cavitation water tunnel structure.

[0011] In one embodiment of the present invention, the step of determining the temperature deformation inversion function of a large cavitation water tunnel structure based on finite element simulation results includes: determining the deformation data of each segment of the cavitation water tunnel structure under multiple temperature conditions based on finite element simulation technology, and plotting the axial deformation curves of each segment of the cavitation water tunnel structure based on the deformation data of each segment; fitting the axial deformation curves of each segment of the cavitation water tunnel structure using the least squares method, and obtaining the fourth-order polynomial curves of the axial deformation of each segment based on the fitting results;

[0012] The polynomial coefficients in the fourth-order polynomial curves of the axial deformation of each segment are obtained, and the polynomial coefficients are fitted using a linear regression method to obtain the temperature deformation inversion function of each segment of the large cavitation water tunnel structure; the temperature deformation inversion functions of each segment are integrated to obtain the temperature deformation inversion function of the large cavitation water tunnel structure.

[0013] In one embodiment of the present invention, the step of determining the deformation data of each segment of the cavitation water tunnel structure under multiple temperature conditions based on finite element simulation technology, and drawing the axial deformation curve of each segment of the cavitation water tunnel structure based on the deformation data of each segment, includes: establishing a corresponding three-dimensional finite element model based on the actual size of the large cavitation water tunnel structure; performing temperature deformation simulation calculations on the three-dimensional finite element model, obtaining the real deformation response of the cavitation water tunnel structure under different temperature loads based on the simulation calculation results; selecting several positions on each segment of the cavitation water tunnel structure as axial deformation curve measuring points, obtaining the deformation data corresponding to the axial deformation curve measuring points, and drawing the axial deformation curve of each segment of the cavitation water tunnel structure based on the deformation data of the axial deformation curve measuring points on each segment.

[0014] In one embodiment of the present invention, the step of fitting the axial deformation curves of each segment of the cavitation water tunnel structure using the least squares method, and obtaining the fourth-order polynomial curves of the axial deformation of each segment based on the fitting results, includes: obtaining the fourth-order polynomial curves of the axial deformation of each segment according to the following formula: ;in, It is represented as a fourth-order polynomial curve of the segmental axial deformation under different ambient temperatures; , , , and Represented as the coefficients of a polynomial function; It represents the independent variable.

[0015] In one embodiment of the present invention, the step of obtaining the polynomial coefficients in the fourth-order polynomial curve of the axial deformation of each segment and fitting the polynomial coefficients using a linear regression method to obtain the temperature deformation inversion function of each segment of the large cavitation water tunnel structure includes: obtaining the polynomial coefficients in the fourth-order polynomial curve of the axial deformation of each segment and fitting the polynomial coefficients using a linear regression method to obtain a first-order function of the polynomial coefficients with respect to temperature change; and obtaining the temperature deformation inversion function of each segment of the large cavitation water tunnel structure based on the first-order function of the polynomial coefficients with respect to temperature change.

[0016] In one embodiment of the present invention, the step of integrating the temperature deformation inversion functions of each segment to obtain the temperature deformation inversion function of the large cavitation water tunnel structure includes: determining the temperature deformation inversion function of the large cavitation water tunnel structure according to the following formula:

[0017] ;

[0018] in, This is the temperature deformation inversion function for a large cavitation water tunnel structure. The coefficient matrix, to All are linear functions with polynomial coefficients related to temperature difference; is the independent variable.

[0019] As described above, the large-scale cavitation water tunnel structure deformation monitoring system and method of the present invention has the following beneficial effects:

[0020] This invention solves the problem of directly measuring and continuously monitoring the overall deformation and internal shaft deformation of large structures by deploying a small number of sensors to measure strain and temperature data and combining this with a deformation inversion algorithm to calculate the overall temperature deformation and shaft deformation. Furthermore, by combining finite element analysis with the deployment of measuring points and performing unified modeling processing on the measured discrete data, this invention improves the accuracy and stability of the shaft deformation calculation results, avoiding errors caused by single measuring points or empirical judgments. Simultaneously, it enables continuous acquisition and real-time calculation and display of structural deformation data, reducing manual intervention and post-processing workload, and improving the engineering applicability and work efficiency of deformation monitoring for large cavitation water tunnel structures. Attached Figure Description

[0021] Figure 1This is a schematic diagram of the overall structure of the large cavitation water tunnel structure deformation monitoring system in the first embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram of the layout of strain measuring points on the intermediate bearing base in the deformation monitoring system for a large cavitation water tunnel structure according to the first embodiment of the present invention.

[0023] Figure 3 This is a schematic diagram of the signal acquisition and transmission process of the large cavitation water tunnel structure deformation monitoring system in the first embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of the functional modules of the central processing unit in the large cavitation water tunnel structure deformation monitoring system according to the first embodiment of the present invention.

[0025] Figure 5 This is a schematic diagram of the monitoring interface of the large cavitation water tunnel structure deformation monitoring system in the first embodiment of the present invention;

[0026] Figure 6 This is an overall flowchart of the method for monitoring the deformation of a large cavitation water tunnel structure according to the second embodiment of the present invention;

[0027] Figure 7 This is a flowchart of determining the temperature deformation inversion function of a large cavitation water tunnel structure in the deformation monitoring method of a large cavitation water tunnel structure in the second embodiment of the present invention.

[0028] Figure 8 This is a schematic diagram of two-dimensional plane temperature deformation in the deformation monitoring method for large cavitation water tunnel structures according to the second embodiment of the present invention.

[0029] Figure 9 This is a schematic diagram of the overall structure of the cavitation water tunnel in the deformation monitoring method for large cavitation water tunnel structures in the second embodiment of the present invention;

[0030] Figure 10 This is a schematic diagram of the column legs and guide vane structure in the deformation monitoring method for large cavitation water tunnel structures according to the second embodiment of the present invention;

[0031] Figure 11 This is a schematic diagram of the finite element model of the cavitation water tunnel in the deformation monitoring method of the large cavitation water tunnel structure in the second embodiment of the present invention;

[0032] Figure 12 This is a schematic diagram of the mesh refinement region in the large cavitation water tunnel structure deformation monitoring method in the second embodiment of the present invention;

[0033] Figure 13 This is a schematic diagram of the middle support frame model in the deformation monitoring method for large cavitation water tunnel structures according to the second embodiment of the present invention;

[0034] Figure 14 This is a schematic diagram of the actual tooling of the cavitation water tunnel structure in the deformation monitoring method of the large cavitation water tunnel structure in the second embodiment of the present invention.

[0035] Figure 15 This is a schematic diagram of the pile leg boundary conditions in the deformation monitoring method for a large cavitation water tunnel structure according to the second embodiment of the present invention.

[0036] Figure 16 This is a schematic diagram of the selected water tunnel structure node in the large cavitation water tunnel structure deformation monitoring method in the second embodiment of the present invention.

[0037] Figure 17 This is a schematic diagram of the deformation of the upper axis of the water tunnel structure in the deformation monitoring method for large cavitation water tunnel structure according to the second embodiment of the present invention.

[0038] Figure 18 This is a schematic diagram of the deformation of the second column leg axis in the deformation monitoring method for large cavitation water tunnel structures according to the second embodiment of the present invention;

[0039] Figure 19 This is a schematic diagram of the deformation of the first column leg axis in the deformation monitoring method for a large cavitation water tunnel structure according to the second embodiment of the present invention.

[0040] Figure 20 This is a schematic diagram of the deformation of the bottom axis of the water tunnel in the deformation monitoring method of the large cavitation water tunnel structure in the second embodiment of the present invention;

[0041] Figure 21 This is a schematic diagram of the deformation fitting of the upper axis of the water tunnel structure in the deformation monitoring method of the large cavitation water tunnel structure in the second embodiment of the present invention.

[0042] Figure 22 This is a schematic diagram of linear regression fitting of the working segment in the deformation monitoring method for large cavitation water tunnel structures according to the second embodiment of the present invention.

[0043] Figure 23 This is a schematic diagram of the linear regression fitting of the second column leg in the deformation monitoring method for large cavitation water tunnel structures in the second embodiment of the present invention.

[0044] Figure 24 This is a schematic diagram of the temperature deformation inversion of the water tunnel structure in the deformation monitoring method for large cavitation water tunnel structures according to the second embodiment of the present invention. Detailed Implementation

[0045] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. It should be noted that, unless otherwise specified, the following embodiments and features described herein can be combined with each other.

[0046] The first embodiment of the present invention relates to a deformation monitoring system for a large cavitation water tunnel structure, such as... Figure 1 As shown, the system includes a distributed monitoring device and a central processing unit connected to the distributed monitoring device, wherein the central processing unit is located in a host computer; the distributed monitoring device includes sensor components, a data acquisition unit connected to the sensor components, and a controller connected to the data acquisition unit; the sensors include several welded strain gauges and temperature sensors, wherein the strain gauges are vertically arranged on the intermediate bearing base of the cavitation water tunnel structure, and their measured values ​​are used to invert the shaft system deformation. For details, please refer to [link to relevant documentation]. Figure 2 Six strain gauges are arranged along the Z direction on the intermediate bearing base, and temperature sensors are arranged in the working space of the water tunnel structure to measure the ambient temperature in order to invert the overall structural deformation caused by temperature changes.

[0047] The data acquisition units include strain data acquisition units and temperature data acquisition units; please refer to [link / reference]. Figure 3 The data acquisition unit includes two strain data acquisition units and one temperature data acquisition unit. The data acquisition units are connected to the corresponding sensors via four-core signal lines, and the data acquisition units communicate with each other via an RS485 bus. In actual installation, the distance between the data acquisition units and the sensors does not exceed 30m. The controller is connected to the data acquisition units via an RS485 bus and is controlled by a host computer to transmit the time domain signals of each sensor in real time.

[0048] Please see Figure 4 and Figure 5 The central processing unit includes a monitoring data input module, a deformation inversion module, a data processing and analysis module, a visualization display module, and a data management module. The monitoring data input module receives measured data from strain gauges and temperature sensors and transmits the received measured data to the deformation inversion module in real time for processing. The deformation inversion module performs deformation inversion processing on the measured data from strain gauges and temperature sensors, and obtains the deformation information of the cavitation water tunnel structure based on the processing results. The deformation inversion module includes a shaft system deformation submodule and a temperature deformation submodule. The shaft system deformation submodule is used to obtain the deformation information of the cavitation water tunnel structure based on the shaft system deflection curve equation, and the temperature deformation submodule is used to obtain the deformation information of the cavitation water tunnel structure based on the temperature deformation inversion function.

[0049] The data processing and analysis module is used to process and analyze the raw collected data and the inverted deformation data. This module includes time-domain signal analysis, statistical value analysis, deformation extraction of structural feature points, and extraction of the maximum deformation and its location. The visualization module is used to intuitively display the raw monitoring data and the output results of the deformation inversion module, and to achieve multi-dimensional visualization through deformation cloud maps, waveform diagrams, trend charts, digital tables, dashboards, etc. The database management module is used to store, manage, and distribute deformation data.

[0050] The second embodiment of the present invention relates to a method for monitoring the deformation of a large cavitation water tunnel structure, the process of which is as follows: Figure 6 As shown, the details are as follows:

[0051] Step 101: Based on the structural form, operating conditions, and on-site installation conditions of the large cavitation water tunnel, and in conjunction with finite element analysis, determine the layout locations and acquisition frequencies of strain measuring points and temperature measuring points.

[0052] Step 102: Install strain gauges and temperature sensors at the strain measurement point and temperature measurement point, respectively. Then, install the data acquisition device in a location that is easy to wire and maintain. Finally, connect the sensor signal line to the data acquisition device and protect it.

[0053] Specifically, at the strain measurement point, the structural surface is ground, cleaned, and marked for positioning. Then, the strain gauge is spot-welded and installed. Sealant is applied to the surface of the strain gauge and a protective shell is installed. At the temperature measurement point, a temperature sensor is installed and fixed. Then, the data acquisition unit is installed in a location that is easy to wire and maintain. The sensor signal line is connected to the data acquisition unit and protected.

[0054] Step 103: Determine the temperature deformation inversion function of the large cavitation water tunnel structure based on the finite element simulation calculation results, and set the temperature deformation inversion function in the temperature deformation submodule of the central processing unit located in the host computer.

[0055] Specifically, based on finite element calculation results and least squares fitting, an explicit equation is established between structural deformation and measured discrete data, which is the temperature deformation inversion function of a large cavitation water tunnel structure; then, monitoring software is developed to realize functions such as data access, deformation inversion, data analysis, visualization display, and data management.

[0056] More specifically, the method for determining the temperature deformation inversion function of a large cavitation water tunnel structure based on finite element simulation results includes the following steps: First, based on finite element simulation technology, the deformation data of each segment of the cavitation water tunnel structure under multiple temperature conditions is determined, and the axial deformation curves of each segment of the cavitation water tunnel structure are plotted according to the deformation data of each segment; then, the least squares method is used to fit the axial deformation curves of each segment of the cavitation water tunnel structure, and the fourth-order polynomial curves of the axial deformation of each segment are obtained according to the fitting results; next, the polynomial coefficients in the fourth-order polynomial curves of the axial deformation of each segment are obtained, and the polynomial coefficients are fitted using the linear regression method, thereby obtaining the temperature deformation inversion function of each segment of the large cavitation water tunnel structure; finally, the temperature deformation inversion functions of each segment are integrated to obtain the temperature deformation inversion function of the large cavitation water tunnel structure.

[0057] It should be noted that this invention focuses on the generation process of the temperature deformation inversion function of the large cavitation water tunnel structure. The shaft deflection curve equation has been disclosed in patent (CN121185245A), so the generation process of the shaft deflection curve equation will not be described in detail in this invention.

[0058] Step 104: Place the controller in the cabinet, complete the signal and power connection between the data acquisition unit and the controller, connect the controller to the host computer via a crossover network cable, and then turn on the power and perform system debugging.

[0059] Step 105: Collect data at a preset frequency, and input the collected data into the temperature deformation inversion function in the shaft deformation submodule and the temperature deformation submodule respectively, so as to obtain the deformation information of the cavitation water tunnel structure.

[0060] Furthermore, the detailed steps for determining the temperature deformation inversion function of the large cavitation water tunnel structure based on the finite element simulation calculation results in step 103 above are as follows:

[0061] Please refer to section 7 for details. Step 1: Based on finite element simulation calculations, extract the simulation deformation results of key structural feature nodes. Step 2: Use the least squares method to fit the fourth-order polynomial curves of the deformation of each segment's axis. That is, based on the simulation calculation results, select data from the key feature locations of the water tunnel structure as virtual measuring points, and use the least squares method to fit a fourth-order polynomial to express the deformation curves of each segment's axis, as shown below: In the formula, It is represented as a fourth-order polynomial curve of the segmental axial deformation under different ambient temperatures; , , , and Represented as the coefficients of a polynomial function; Indicates the independent variable. It can be a variable in the X-axis direction or a variable in the Y-axis direction;

[0062] Step 3: Further obtain the fitting coefficients and temperature change through linear regression analysis. The expression between them; where, according to theoretical analysis and numerical simulation results, for the same structural segment, the polynomial coefficients of its deformation curve under different environmental temperatures are known. , Equal to the change in ambient temperature The relationship is linear, therefore a linear regression method is used to fit the polynomial coefficients, as shown in the following formula: In the formula: to All are linear functions of polynomial coefficients with respect to temperature changes, and each function contains... , and Let the variables be different constants; rewrite all coefficients as independent variables. After obtaining a linear function, we get... The fourth step involves integrating the segmented deformation curves of each axis as input parameters to establish an algorithm for the overall temperature deformation inversion of the water tunnel structure, with ∆T as the input parameter. The above equation is the temperature deformation inversion function for a large cavitation water tunnel structure; where, Let be the coefficient matrix of the equation. to All of them are linear functions with polynomial coefficients that are related to the temperature difference. When the temperature difference ∆T is determined, they are constant coefficient matrices. The independent variable is ; by inputting different changes in ambient temperature, the axial deformation curves for each segment can be obtained.

[0063] To go further, corresponding Figure 7 For each step, the following detailed explanation is provided:

[0064] 1. Inversion Principle: In thermoelasticity, temperature loads are introduced into the mechanical equilibrium equations through the constitutive relations of materials to establish the relationship between structural temperature and deformation. For details, please refer to [link to relevant documentation]. Figure 8 When dealing with thermal problems, the total strain of a structure can be divided into two parts: structural strain and thermal strain, namely: The thermal strain of a material is directly caused by temperature change, and its expression is: In the formula: The coefficient of thermal expansion of the material. For temperature change; within the elastic range, stress and strain satisfy: In the formula: D is the elastic matrix of the material; at the same time, the stress inside the structure should also satisfy the equilibrium equation: Substituting the material constitutive equations into the equilibrium equations and combining them with the geometric equations: The thermoelastic equilibrium equation can then be obtained: The above equation shows that, in a single direction, the structural deformation caused by temperature is related to the amount of temperature change. The relationship between them is linear; based on this, the present invention develops a high-efficiency overall temperature deformation inversion algorithm that takes the working environment temperature of the water tunnel as input and has a certain accuracy, which can quickly and accurately monitor the overall deformation of the cavitation water tunnel structure according to the change of ambient temperature.

[0065] 2. Cavitation water tunnel structure: The research object of this invention is described in [reference needed]. Figure 9 The water tunnel is approximately 61m long, 21m high, and 6m wide, with a total weight of about 1980t. Its structure is complex, consisting of 14 sections including a working section, a contraction section, and a diffusion section. The overall structure comprises the inner wall of the cylinder, reinforcing ribs, 45° inclined cladding, a support frame structure, and pile legs. At the corners of the water tunnel, guide vanes are installed to direct the water flow; these vanes consist of crescent-shaped guide plates and reinforcing ribs. Figure 10 .

[0066] 3. Finite element analysis of temperature deformation of water tunnel structure:

[0067] 3.1 Temperature Load: The normal operating ambient temperature range of the large cavitation water tunnel test facility is 20℃-35℃; in this invention, the temperature load adopts the ambient temperature loading mode, and three sets of characteristic ambient temperatures are selected near this operating temperature range for simulation calculation. The parameters of each working condition are shown in Table 1; the deformation of the large cavitation water tunnel structure during the operation stage is affected by multiple coupled factors. In order to highlight the structural deformation caused by ambient temperature, gravity load and water pressure load caused by water level changes are not considered in the analysis process. Only by changing the operating ambient temperature of the structure, the structural deformation characteristics under temperature action are obtained.

[0068] Table 1 Temperature Load Input

[0069]

[0070] 3.2 Finite Element Model: A three-dimensional finite element model was established based on the actual dimensions of the large cavitation water tunnel structure, see... Figure 11 The water tunnel model is built using shell elements, divided into 4-5 mesh elements according to the spacing of the reinforcing ribs, with a size of 200mm. 200mm; the stiffener web is divided into 3 grids, each 150mm in size. 150mm; the grid is refined at the corners and four bends, with a refined grid size of approximately 50mm × 50mm; the unit size gradually changes in the transition area to coordinate the different grid sizes, see... Figure 12The model primarily uses quadrilateral elements, with triangular elements used in areas with complex curvature variations. The support frame structure is also built using shell elements, with a mesh size of 50mm × 50mm. Mesh transitions are implemented in the area connecting to the water tunnel base to ensure mesh consistency. (See...) Figure 13 The finite element model contains a total of 1,075,975 nodes and 1,092,323 elements. In thermal analysis and structural analysis, the element types are set to DS4, DS3 and S4R, S3, respectively.

[0071] 3.3 Boundary Conditions: To obtain the true deformation response of the cavitation water tunnel structure under temperature load, the constraints of the finite element model of the water tunnel structure are not simplified in the temperature deformation simulation analysis. The boundary conditions are determined according to the tooling conditions under the actual working state of the water tunnel to ensure that the simulation boundaries are consistent with the actual engineering conditions. The actual working constraint conditions of the large cavitation water tunnel structure are shown in [reference needed]. Figure 14 ;Depend on Figure 14 As can be seen, the bottom fixture of the water tunnel test facility has seven boundary constraint areas, and the constraint forms are divided into two types: sliding rail constraint and bolt connection. Among them, the friction coefficient of the sliding rail constraint is set to 0.1 in the X direction and a displacement of 0.05mm is reserved in the Z direction to allow slight sliding during the operation of the structure. The bottom of the impeller chamber and the front section of the second corner are fastened to the ground base by bolts, and it is considered that this place is rigidly fixed. The boundary conditions of each layout location are detailed in Table 2.

[0072] Table 2 Boundary Conditions

[0073]

[0074] In finite element method software, sliding friction and allowable displacement constraints are typically applied using surface-to-surface contact. This invention achieves these boundary conditions by establishing rigid surfaces, selecting a hard contact mode, meaning the outer surface (water tunnel structure) cannot pass through the main surface (rigid surface). Based on this, a horizontal ground surface and a vertical baffle are established to restrict displacement in the Y and Z directions, respectively. The surface friction coefficient of the horizontal ground surface is set to 0.1 in the X direction and to be completely smooth in the Z direction, i.e., the friction coefficient is 0. The vertical baffle is used to constrain displacement in the Z direction, see... Figure 15 The distance between the baffle at the pile leg and the water tunnel structure is 0.05mm, and the height is 100mm; the final constraints are as follows: ; ;

[0075] 3.4 Calculation Results: The calculation results of the maximum relative deformation of the large cavitation water tunnel structure in the X and Y directions under three different ambient temperature conditions are shown in Table 3. As the ambient temperature increases, the maximum relative deformation of the structure shows a linear increasing trend, which is consistent with the thermal expansion effect of materials, indicating the rationality of the simulation calculation.

[0076] Table 3 Maximum relative deformation

[0077]

[0078] To achieve a fourth-order polynomial fit for the axial deformation curve of the cavitation water tunnel, at least five locations need to be selected as measurement points for the axial deformation curve on each structural segment. Based on the actual segmentation of the water tunnel structure, nodes are selected in the finite element model, as shown below. Figure 16 Deformation data of the outer wall of each segment was extracted; different numbers of nodes were selected based on the deformation characteristics of each region of the water tunnel; in addition, in the bottom circular cylinder, the average value of the results of the corresponding upper and lower points on the inner wall of the structure was used as virtual node data; the deformation results of these measuring points under different working conditions were plotted as curves, which can more intuitively show the temperature deformation characteristics of the water tunnel structure in two directions. Figures 17 to 20 In the entire coordinate system, the first node on the upper part of the inner wall of the fourth corner is taken as the origin.

[0079] 4. Inversion Algorithm:

[0080] 4.1 Fitting the Deformation of the Water Tunnel Axis: Based on the selected nodes, the least squares method was used to fit the deformation curve of the axis. Considering the complex deformation of the upper structure of the water tunnel, piecewise fitting was adopted. At the junctions of the contraction section, working section 1, working section 2, and the upper diffusion section, the function values ​​were ensured to be equal and the first and second derivatives to be continuous. However, the bottom of the water tunnel structure and the two column legs were not piecewise processed and were directly fitted.

[0081] Taking the upper part of the water cave structure as an example, Figure 21 The X and Y axis deformation curves obtained by fitting according to the above method are shown. As can be seen from the figure, the fitting curves are basically consistent with the deformation curves drawn in the previous section in terms of overall trend. In the Y-direction deformation fitting, some nodes do not pass through the curve. This is due to prioritizing the smoothness of the connection between each segment. For other structures of the water tunnel, since no segmentation is performed, this situation does not exist in the fitting lines.

[0082] 4.2 Linear Regression Analysis: Under three operating conditions, the five coefficients of the fourth-degree polynomial obtained through fitting are correlated with the temperature change. They all showed a high degree of linear correlation; Figure 22 and Figure 23 The coefficients of the fourth-order polynomials corresponding to the working section of the water tunnel and the second column leg structure are shown respectively, along with the temperature change. Based on the above linear relationship, a linear regression method is used to fit the equations, yielding the coefficients of the five fourth-order polynomials with respect to the temperature change. A linear function;

[0083] 4.3 Inversion Algorithm: This algorithm converts the polynomial coefficients with respect to temperature changes. Relationship according to formula Formal representation, substitution The specific forms of the temperature deformation inversion functions for each segment of the large cavitation water tunnel structure can then be obtained as follows:

[0084] 1. Upper part of the water tunnel structure:

[0085] 1) Deformation in the U1 direction:

[0086] contraction segment: ;

[0087] ;

[0088] Work Section 1: ;

[0089] ;

[0090] Work Section 2: ;

[0091] ;

[0092] Upper diffusion section: ;

[0093] ;

[0094] 2) Deformation in the U2 direction:

[0095] contraction segment: ;

[0096] ;

[0097] Work Section 1: ;

[0098] ;

[0099] Work Section 2: ;

[0100] ;

[0101] Upper diffusion section: ;

[0102] ;

[0103] 2. Second column leg

[0104] 1) Deformation in the U1 direction: ;

[0105] ;

[0106] 2) Deformation in the U2 direction: ;

[0107] ;

[0108] 3. Bottom of the water tunnel structure

[0109] 1) Deformation in the U1 direction: ;

[0110] ;

[0111] 2) Deformation in the U2 direction: ;

[0112] ;

[0113] 4. First column leg

[0114] 1) Deformation in the U1 direction: ;

[0115] ;

[0116] 2) Deformation in the U2 direction: ;

[0117] ;

[0118] Integrating the temperature deformation inversion algorithm into a large-scale cavitation water tunnel health monitoring system enables real-time monitoring of the overall structural temperature deformation. (See...) Figure 24 ;

[0119] 4.4 Verification of Temperature Deformation Inversion Algorithm: To evaluate the accuracy and reliability of the inversion algorithm developed in this invention, this section verifies the inversion results based on measured temperature data. The selected measured temperature data are as follows: 13:00 on September 28, 30.8℃; 9:00 on September 29, 29.1℃; 7:00 on September 30, 27.8℃; 12:00 on November 18, 19.6℃. The working section of the water tunnel is selected as the verification object, and the comparison results are shown in Tables 4 and 5.

[0120] Table 4 Comparison of working section axis in the x-direction

[0121]

[0122] Table 5 Comparison of the working section axis in the y-direction

[0123]

[0124] The verification results show that the error range between the inverted value and the calculated value of the measured temperature is 0.3%-3.1%, which meets the engineering accuracy requirements and can realize the accurate inversion of the temperature deformation of the axial direction of the cavitation water tunnel structure.

[0125] 5. Summary: For large cavitation water tunnel structures, the finite element method is used to analyze their temperature deformation characteristics. By fitting the axial deformation curve through linear regression, a temperature deformation inversion function adapted to its segmented characteristics is proposed, achieving rapid inversion of the overall temperature deformation. The protection points of this invention are: 1.1, the finite element model of the large cavitation water tunnel structure; 1.2, the temperature deformation inversion algorithm of the large cavitation water tunnel structure; furthermore, this invention has stronger adaptability to segmented cavitation water tunnel structures, requiring only temperature data collection to complete the inversion, resulting in lower costs; this invention, through linear regression fitting function, achieves inversion efficiency exceeding theoretical calculations and inverse finite element solutions. The inversion algorithm is based on the calculation results of a refined finite element model, eliminating modeling simplification errors and exhibiting good accuracy.

[0126] In summary, this invention solves the problem of directly measuring and continuously monitoring the overall deformation and internal shaft deformation of large structures by deploying a small number of sensors to measure strain and temperature data and combining this with a deformation inversion algorithm to calculate the overall temperature deformation and shaft deformation. Furthermore, by combining finite element analysis with the deployment of measuring points and performing unified modeling processing on the measured discrete data, this invention improves the accuracy and stability of the shaft deformation calculation results, avoiding errors caused by single measuring points or empirical judgments. Simultaneously, it enables continuous acquisition and real-time calculation and display of structural deformation data, reducing manual intervention and post-processing workload, and improving the engineering applicability and work efficiency of deformation monitoring for large cavitation water tunnel structures.

[0127] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. All equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this invention should still be covered by the claims of this invention.

Claims

1. A deformation monitoring system for a large cavitation water tunnel structure, characterized in that: It includes a distributed monitoring device and a central processing unit connected to the distributed monitoring device; The distributed monitoring device includes a sensor assembly, a data acquisition unit connected to the sensor assembly, and a controller connected to the data acquisition unit. The sensor assembly includes several strain gauges vertically arranged on the intermediate bearing base of the cavitation water tunnel structure and a temperature sensor arranged in the working space of the cavitation water tunnel structure. The data acquisition unit includes a strain acquisition unit connected to the strain gauges and a temperature acquisition unit connected to the temperature sensor.

2. The deformation monitoring system for a large cavitation water tunnel structure according to claim 1, characterized in that: The central processing unit includes a monitoring data input module, a deformation inversion module, a data processing and analysis module, a visualization display module, and a data management module; The monitoring data input module is used to receive the measured data sent by the strain gauge and temperature sensor; The deformation inversion module performs deformation inversion processing on the measured data sent by the strain gauge and temperature sensor, and obtains the deformation information of the cavitation water tunnel structure based on the processing results. The data processing and analysis module is used to process and analyze the original collected data and the inverted deformed data; The visualization module is used to intuitively display the original monitoring data and the output results of the deformation inversion module; the database management module is used to store, manage and distribute deformation data.

3. The deformation monitoring system for a large cavitation water tunnel structure according to claim 2, characterized in that: The deformation inversion module includes a shaft system deformation submodule and a temperature deformation submodule; The shaft system deformation submodule is used to obtain the deformation information of the cavitation water tunnel structure according to the shaft system deflection curve equation, and the temperature deformation submodule is used to obtain the deformation information of the cavitation water tunnel structure according to the temperature deformation inversion function.

4. A method for monitoring the deformation of a large cavitation water tunnel structure, characterized in that: The large cavitation water tunnel structure deformation monitoring system based on any one of claims 1-3 includes the following steps: Based on the structural form, operating conditions and on-site installation conditions of the large cavitation water tunnel, and combined with finite element analysis, the layout locations and acquisition frequencies of strain measuring points and temperature measuring points were determined. Strain gauges and temperature sensors are installed at the strain measurement point and temperature measurement point, respectively. The data acquisition unit is then installed in a location that facilitates wiring and maintenance. The sensor signal lines are then connected to the data acquisition unit and protected. The temperature deformation inversion function of the large cavitation water tunnel structure is determined based on the finite element simulation calculation results, and the temperature deformation inversion function is set in the temperature deformation submodule of the central processing unit located in the host computer. Place the controller in the cabinet, complete the signal and power connection between the data acquisition unit and the controller, connect the controller to the host computer through a crossover network cable, and then turn on the power and perform system debugging. Data is collected at a preset frequency, and the collected data is input into the temperature deformation inversion function in the shaft deformation submodule and the temperature deformation submodule respectively, so as to obtain the deformation information of the cavitation water tunnel structure.

5. The method for monitoring the deformation of a large cavitation water tunnel structure according to claim 4, characterized in that: The method for determining the temperature deformation inversion function of a large cavitation water tunnel structure based on finite element simulation results includes: Based on finite element simulation technology, the deformation data of each segment of the cavitation water tunnel structure under multiple temperature conditions is determined, and the axial deformation curves of each segment of the cavitation water tunnel structure are plotted based on the deformation data of each segment. The least squares method was used to fit the axial deformation curves of each segment of the cavitation water tunnel structure, and the fourth-order polynomial curves of the axial deformation of each segment were obtained based on the fitting results. The polynomial coefficients in the fourth-order polynomial curves of the axial deformation of each segment are obtained, and the polynomial coefficients are fitted by the linear regression method to obtain the temperature deformation inversion function of each segment of the large cavitation water tunnel structure. By integrating the temperature deformation inversion functions of each segment, the temperature deformation inversion function of the large cavitation water tunnel structure is obtained.

6. The method for monitoring the deformation of a large cavitation water tunnel structure according to claim 5, characterized in that: The deformation data of each segment of the cavitation water tunnel structure under multiple temperature conditions is determined based on finite element simulation technology, and the axial deformation curves of each segment of the cavitation water tunnel structure are plotted based on the deformation data of each segment, including: A three-dimensional finite element model was established based on the actual dimensions of the large cavitation water tunnel structure. Temperature deformation simulation calculations were performed on the three-dimensional finite element model, and the actual deformation response of the cavitation water tunnel structure under different temperature loads was obtained based on the simulation results. Several locations are selected as axis deformation curve measuring points on each segment of the cavitation water tunnel structure. Deformation data corresponding to the axis deformation curve measuring points are obtained, and the axis deformation curves of each segment of the cavitation water tunnel structure are plotted based on the deformation data of the axis deformation curve measuring points on each segment.

7. The method for monitoring the deformation of a large cavitation water tunnel structure according to claim 5, characterized in that: The least squares method is used to fit the axial deformation curves of each segment of the cavitation water tunnel structure. Based on the fitting results, a fourth-order polynomial curve of the axial deformation of each segment is obtained, including: The fourth-order polynomial curves of the segmental axis deformation are obtained using the following formula: ； in, It is represented as a fourth-order polynomial curve of the segmental axial deformation under different ambient temperatures; , , , and Represented as the coefficients of a polynomial function; It represents the independent variable.

8. The method for monitoring the deformation of a large cavitation water tunnel structure according to claim 5, characterized in that: The process involves obtaining the polynomial coefficients from the fourth-order polynomial curves of the axial deformation of each segment, and fitting these polynomial coefficients using a linear regression method to obtain the temperature deformation inversion function for each segment of the large cavitation water tunnel structure. This includes: Obtain the polynomial coefficients from the fourth-order polynomial curves of the deformation of each segment of the axis, and use the linear regression method to fit the polynomial coefficients, thereby obtaining a first-order function of the polynomial coefficients with respect to temperature change. The temperature deformation inversion function of each segment of the large cavitation water tunnel structure is obtained by using the first-order function of the polynomial coefficients with respect to temperature change.

9. A method for monitoring the deformation of a large cavitation water tunnel structure according to claim 5, characterized in that: The temperature deformation inversion functions of each segment are integrated to obtain the temperature deformation inversion function of the large cavitation water tunnel structure, including: The temperature deformation inversion function for a large cavitation water tunnel structure is determined using the following formula: ； in, This is the temperature deformation inversion function for a large cavitation water tunnel structure. The coefficient matrix, to All are linear functions with polynomial coefficients related to temperature difference; is the independent variable.

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