Method and device for evaluating service performance of metal roof connection node, terminal and medium

Abstract

The invention provides a service performance evaluation method and device for a metal roof connection node, a terminal and a medium. The method comprises the following steps: acquiring a load parameter of a target metal roof or a morphology parameter of each connection node of the target metal roof; wherein the morphology parameters comprise difference values between one or more of the height, the width, the opening spacing and the curve area of the profile curve of the plate rib corresponding to the connection node and an initial value; based on the load parameter or the morphology parameter, calculating an accumulated damage factor of each connection node of the target metal roof; and for each connection node, predicting the damage degree parameter of the connection node by using the accumulated damage factor of the connection node and the relation curve of the damage degree parameter and the accumulated damage factor, so as to perform service performance evaluation on each connection node of the metal roof based on the damage degree parameter. The damage degree of the metal roof connection node can be directly predicted, and the service performance degradation degree of the metal roof can be scientifically quantified.

Description

Technical Field

[0001] The present invention relates to the field of structural safety technology, and in particular to a service performance evaluation method, device, terminal and medium for metal roof connection nodes. Background Art

[0002] Currently, metal roof systems are widely used in large buildings such as high-speed rail stations, airports, and convention centers. The metal roof is mechanically connected to the purlins, allowing it to expand and contract freely to adapt to changes in the external temperature. This solves the stress concentration problem caused by thermal expansion and contraction of the roof panels, allowing the metal roof panels to be arranged in extended lengths according to the roof's shape. Furthermore, the entire roof panel has no nail holes, eliminating the hidden danger of rainwater leaking through the nail holes. However, after years of service, the connection nodes of metal roofs can become loose and their bearing capacity can decrease. In severe cases, large areas can become loose, leading to wind-induced damage. Therefore, conducting service performance testing and evaluation of metal roof connection nodes has important scientific research significance and engineering application value in guiding the design and operation management of metal roofs.

[0003] Currently, static and dynamic pressure methods are primarily used to test the wind-uplift resistance of metal roofs. These methods involve fixing large metal roof panels, supports, and purlins to a box, which is then inflated or deflated according to a specific loading sequence to simulate wind loads. The differences lie in the size of the roof panel test specimens and the airflow loading sequence. However, these methods have the following shortcomings:

[0004] 1. The test samples are large in size (for example, the minimum sample size in GB / T39794.1-2021 is 7.3m×3.7m, and the minimum sample size in ANSI / UL 580 is 3.05m×3.05m), and are placed on the upper part of a closed box. The changes in the service performance of the nodes during the test are not easy to observe and quantify. The failure of the test samples under a certain test load level reflects the macro-wind-resistant ability of the metal roof, and cannot represent the service performance of local nodes.

[0005] 2. The above-mentioned detection method clearly stipulates the test loading sequence, which is convenient for the test. However, due to differences in region and roof shape, the actual wind environment in which the metal roof is in service is quite different from the loading sequence specified in the above-mentioned method. As a result, the test results cannot meet the actual needs of the metal roof. The existing method lacks specificity and adaptability in simulating roof wind loads.

[0006] 3. Existing technologies consider static wind pressure and dynamic wind pressure separately, and only focus on whether metal roofs suffer wind-induced damage under certain load levels. However, the service performance of metal roofs is a dynamic process. Wind-induced damage is related to both the high wind pressure values and the reduction in bearing capacity caused by long-term service. Existing test methods lack the ability to characterize and track the degree of degradation of roof bearing capacity and service performance. Summary of the Invention

[0007] The embodiments of the present invention provide a method, device, terminal and medium for evaluating the service performance of metal roof connection nodes, so as to solve the problem of evaluating the service performance of metal roof connection nodes.

[0008] In a first aspect, an embodiment of the present invention provides a method for evaluating the service performance of a metal roof connection node, comprising:

[0009] Obtaining load parameters of the target metal roof or shape parameters of each connection node of the target metal roof; wherein the shape parameters include the difference between one or more of the height, width, opening spacing, and curve area of the profile curve of the plate rib corresponding to the connection node and the initial value;

[0010] Calculate the cumulative damage factor of each connection node of the target metal roof based on load parameters or shape parameters;

[0011] For each connection node, the damage degree parameter of the connection node is predicted using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor, so as to evaluate the service performance of each connection node of the metal roof based on the damage degree parameter; among which, the relationship curve between the damage degree parameter and the cumulative damage factor is determined through experiments.

[0012] In a second aspect, an embodiment of the present invention provides a service performance evaluation device for a metal roof connection node, comprising:

[0013] An acquisition module is used to acquire the load parameters of the target metal roof or the morphological parameters of each connection node of the target metal roof; wherein the morphological parameters include the difference between one or more of the height, width, opening spacing and curve area of the profile curve of the plate rib corresponding to the connection node and the initial value;

[0014] A calculation module, used for calculating the cumulative damage factor of each connection node of the target metal roof based on load parameters or shape parameters;

[0015] The prediction module is used to predict the damage degree parameter of each connection node using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor, so as to evaluate the service performance of each connection node of the metal roof based on the damage degree parameter; wherein the relationship curve between the damage degree parameter and the cumulative damage factor is determined through experiments.

[0016] In a third aspect, an embodiment of the present invention provides a terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method described in the first aspect or any possible implementation of the first aspect are implemented.

[0017] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0018] The embodiment of the present invention provides a service performance evaluation method, device, terminal and medium for metal roof connection nodes. By converting the load parameters of the target metal roof into cumulative damage factors, the destructive effects of dynamic and static wind pressures on the metal roof connection nodes are comprehensively considered, thereby describing the load history of the connection nodes under various constant amplitude load conditions. At the same time, the relationship between the morphological parameters and the cumulative damage factors is established. When the load parameters cannot be obtained, the cumulative damage factors are indirectly identified by using the morphological changes of the plate rib profile curve. Finally, the relationship between the damage degree parameters and the cumulative damage factors is used to directly predict the damage degree of the metal roof connection nodes and scientifically quantify the degree of degradation of the service performance of the metal roof. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is a flowchart of a method for evaluating the service performance of a metal roof connection node according to an embodiment of the present invention;

[0021] Figure 2A is a schematic diagram of time-history data of internal force response of a connection node provided by an embodiment of the present invention;

[0022] Figure 2B is a schematic diagram of a rain flow counting method provided by one embodiment of the present invention;

[0023] Figure 2C is a schematic diagram of a node internal force periodic matrix provided by an embodiment of the present invention;

[0024] Figure 3A This is a schematic diagram of the distribution of metal roof supports provided by one embodiment of the present invention;

[0025] Figure 3B This is a structural diagram of a metal roof provided by one embodiment of the present invention;

[0026] Figure 3C is a schematic structural diagram of a test sample provided by an embodiment of the present invention;

[0027] Figure 4A This is a schematic structural diagram of a test frame with an actuator arranged at the bottom provided by one embodiment of the present invention;

[0028] Figure 4B This is a schematic structural diagram of a test frame with an actuator arranged at the top provided by one embodiment of the present invention;

[0029] Figure 4C 1 is a schematic structural diagram of a roof panel fixing fixture provided by one embodiment of the present invention;

[0030] Figure 5 1 is a schematic diagram of an embodiment of the present invention provided by the upper arch displacement measurement;

[0031] Figure 6A This is an image of the contact position between the metal roof panel and the support provided by one embodiment of the present invention;

[0032] Figure 6B This is a microscope scanning image of the contact position between the metal roof panel and the support provided by one embodiment of the present invention;

[0033] Figure 6C Schematic diagram of extracting the wear scar depth and width at the contact position between the metal roof panel and the support provided by one embodiment of the present invention;

[0034] Figure 7A This is a schematic diagram of the scanning point cloud position of a metal roof panel provided by one embodiment of the present invention;

[0035] Figure 7B 1 is a schematic diagram of a projection range provided by an embodiment of the present invention;

[0036] Figure 7C This is a schematic diagram of a scanning point cloud fitting curve of a metal roof panel provided by an embodiment of the present invention.

[0037] Figure 7D Schematic diagram of the collection position of the topography parameters on the fitting curve provided by one embodiment of the present invention;

[0038] Figure 7E is a schematic diagram of a contour area provided by an embodiment of the present invention;

[0039] Figure 8A is a schematic diagram of a relationship curve between morphology parameters and cumulative damage factors provided by an embodiment of the present invention;

[0040] Figure 8B is a schematic diagram of a relationship curve between a bearing capacity loss coefficient and a cumulative damage factor provided by an embodiment of the present invention;

[0041] Figure 9 1 is a schematic structural diagram of a service performance evaluation device for a metal roof connection node provided by one embodiment of the present invention;

[0042] Figure 10 FIG. 4 is a schematic diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below with reference to the accompanying drawings.

[0045] See also Figure 1 , which shows a flow chart for implementing a service performance evaluation method for a metal roof connection node provided by an embodiment of the present invention, and is described in detail as follows:

[0046] Step 101: Obtain the load parameters of the target metal roof or the shape parameters of each connection node of the target metal roof; wherein the shape parameters include the difference between one or more of the height, width, opening spacing and curve area of the profile curve of the plate rib corresponding to the connection node and the initial value.

[0047] In this embodiment, the metal roof load can be measured using sensors for wind speed, wind direction, and wind pressure. If load parameters cannot be directly obtained from sensors, regular inspections can be performed using a 3D scanner to obtain a point cloud of the roof's topography, thereby extracting the geometric parameters of the cross-section near the connection nodes. The collected parameters, such as the height, width, opening spacing, and curve area of the profile curve, are compared with the initial values to obtain the difference between the parameters. These topographic parameters can describe the changes in the metal roof's geometry and reflect the service status of the connection nodes.

[0048] Step 102: Calculate the cumulative damage factor of each connection node of the target metal roof based on the load parameter or the shape parameter.

[0049] In this embodiment, the cumulative damage factor is the ratio of the actual number of cycles of the connection node of the metal roof under a certain load condition to the total number of fatigue failures, which can indicate the degree to which the connection node is close to fatigue failure.

[0050] When the load parameters are available, the finite element model can be used to convert the overall load parameters of the metal roof into the load parameters of each connection node, and the dynamically changing load conditions can be converted into multiple conditions with different loads and different numbers of cycles, so as to calculate the cumulative damage factor in sections for more accurate quantification of service performance.

[0051] Since both the morphological parameters and the cumulative damage factor are used to reflect the service status of the connection node, the relationship curve between the two can be determined through experiments. When the load parameters cannot be obtained, this relationship curve can be used to determine the cumulative damage factor.

[0052] Step 103: For each connection node, the damage degree parameter of the connection node is predicted using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor, so as to evaluate the service performance of each connection node of the metal roof based on the damage degree parameter; wherein the relationship curve between the damage degree parameter and the cumulative damage factor is determined through experiments.

[0053] In this embodiment, damage severity parameters may include the residual bearing capacity of the connection node and the depth and width of the wear scar at the contact point between the metal roof and the support. In metal roof systems, connection nodes are critical structures that ensure a reliable connection between the ribs, supports, and the main structure. Their composition and design directly impact the structural safety, waterproofing, and durability of the roof. The contact point between the metal roof and the support is the most critical physical interface in the connection node. These damage severity parameters can be used to quantitatively evaluate the service performance of each connection node.

[0054] This embodiment of the present invention converts the load parameters of the target metal roof into a cumulative damage factor, comprehensively considering the destructive effects of dynamic and static wind pressure on the metal roof connection nodes, thereby describing the load history of the connection nodes under various constant-amplitude load conditions. Simultaneously, a relationship between morphological parameters and cumulative damage factors is established. When load parameters are unavailable, the cumulative damage factor is identified using the morphological changes in the plate rib profile curve. Finally, the relationship between the damage degree parameter and the cumulative damage factor is used to directly predict the damage degree of the metal roof connection nodes and scientifically quantify the degree of degradation of the metal roof's service performance.

[0055] In one possible implementation, the cumulative damage factor of each connection node of the target metal roof is calculated based on the load parameters, including:

[0056] Apply the load parameters to the finite element model of the target metal roof to obtain the internal force response time history data of each connection node of the target metal roof;

[0057] For each connection node, the internal force response time history data of the connection node is decomposed into multiple constant amplitude cyclic load cases and the number of cycles of each constant amplitude cyclic load case based on the rain flow counting method;

[0058] For each constant amplitude cyclic load condition of the first connection node, calculate the ratio of the number of cycles of the first connection node under the constant amplitude cyclic load condition to the total number of fatigue failures under the constant amplitude cyclic load condition, and use this ratio as the cumulative damage factor of the first connection node under the constant amplitude cyclic load condition, thereby obtaining multiple cumulative damage factors of the first connection node; wherein the first connection node is any connection node;

[0059] Accordingly, for each connection node, the cumulative damage factor of the connection node and the relationship curve between the damage severity parameter and the cumulative damage factor are used to predict the damage severity parameter of the connection node, including:

[0060] In the relationship curve between the damage degree parameter and the cumulative damage factor, find the damage degree parameter corresponding to each cumulative damage factor of the first connection node;

[0061] Each damage degree parameter is added together to obtain the damage degree parameter of the first connection node.

[0062] In this embodiment, the load is applied to the finite element model of the large-span roof structure to obtain the internal force response time history data of all connection nodes of the metal roof. The internal force response time history data of the connection nodes are as follows: Figure 2A shown.

[0063] Then, the internal force cycle of the node is obtained by the rain flow counting method, and the maximum load in each cycle is recorded as p max The minimum load is denoted as p min , the internal force amplitude is recorded as p d =p max -p min , the mean internal force is denoted as p m =(p max +p min ) / 2, such as Figure 2B shown.

[0064] According to the internal force amplitude and mean value in all internal force cycles, the internal force amplitude interval and mean interval are set, and the number of internal force cycles in each interval is counted to form the node internal force period matrix, such as Figure 2C shown.

[0065] Get the actual number of cycles m of the kth constant amplitude cyclic load conditionk , and according to the total number of load cycles M of this working condition k , calculate the cumulative damage factor D k =m k / M k According to the cumulative damage factor curve obtained in the preliminary test, D k The corresponding damage degree parameter R k , d k , s k By summing up the various indicators under all working conditions, the damage degree of each node of the roof under the measured wind load can be estimated without damaging the roof. k ,∑d k ,∑s k .

[0066] In one possible implementation, the damage degree parameter includes one or more of a bearing capacity loss coefficient, a wear scar depth at a contact position between the metal roof and the support, and a wear scar width at a contact position with the support. Before predicting the damage degree parameter of each connection node using the cumulative damage factor of the connection node and a relationship curve between the damage degree parameter and the cumulative damage factor, the method further includes:

[0067] Obtain multiple test samples; wherein each test sample includes a roof panel and a support, the roof panel is rectangular, the length of the rectangle is the node spacing in the long direction of the target metal roof, and the width of the rectangle is the node spacing in the short direction of the target metal roof;

[0068] For the jth test sample, perform j×M / n constant amplitude cyclic loading on the jth test sample based on the first load, and measure the wear scar depth and wear scar width at the contact position between the roof panel and the support of the jth test sample; where j∈[1,n], n is the total number of test samples, and M is the total number of fatigue failures corresponding to the first load;

[0069] Perform static graded loading test on the jth test sample until the jth test sample fails;

[0070] The maximum load in the static graded loading test As the residual bearing capacity of the jth test sample after the first load cycle j×M / n times, and calculate the loss rate of the residual bearing capacity compared to the maximum load of the test sample, to obtain the bearing capacity loss coefficient of the jth test sample after the first load cycle j×M / n times;

[0071] Based on the wear scar depth, wear scar width, bearing capacity loss coefficient, and the corresponding cumulative damage factor, curve fitting was performed to obtain the relationship curve between the wear scar depth and the cumulative damage factor under the first load, the relationship curve between the wear scar width and the cumulative damage factor, and the relationship curve between the bearing capacity loss coefficient and the cumulative damage factor.

[0072] In this example, before conducting the test, a finite element model of a long-span roof structure including a metal roof was established. Wind load conditions were determined based on the structure's location and environment. Wind loads were applied to the finite element model, and the overall response of the roof structure was calculated. Time-history data of the internal force responses of all metal roof connection nodes were extracted. Using the rainflow counting method, the internal force amplitudes and mean internal forces of each node's fluctuation cycle were calculated to form a node internal force period matrix. The results of the internal force period matrix calculations for all nodes were then statistically analyzed to determine the test load conditions, including one static load condition and multiple constant-amplitude cyclic load conditions. The load maximum and minimum values for each constant-amplitude cyclic load condition varied. Tests were then conducted separately, generating curves showing the cumulative damage factor under each test load condition, thus providing a basis for evaluating the performance of actual metal roof connection nodes.

[0073] According to the actual spacing of the roof nodes, a test sample is made, which includes a roof panel and a support. The roof panel is rectangular. The length and width of the rectangle are determined according to the node spacing in the long and short sides, and the clamping boundary width is appropriately considered. The distribution of metal roof supports and node spacing are as follows: Figure 3A 、 Figure 3B The structure of the test sample is shown in Figure 3C shown.

[0074] The test equipment includes a test frame, a roof panel fixture, a support force sensor, a support displacement sensor, a cyclic load actuator and control system, and a metal roof panel profile measurement system. The test frame is used to fix the roof panel fixture and the cyclic load actuator and provide a self-balancing reaction force. Depending on the space conditions, the load can be applied to the upper part of the roof panel or the lower part of the roof panel, respectively. Figure 4A 、 Figure 4B As shown in the figure, for the load applied on the upper part of the roof panel, the load actuator is installed on the upper part of the roof panel fixing fixture; for the load applied on the upper part of the roof panel, the load actuator is installed on the lower part of the roof panel fixing fixture.

[0075] The roof panel fixing fixture consists of three parts: the bottom frame, the top frame, and the fixing bolts. The bottom frame and the top frame each have four supporting edges. The two edges parallel to the plate ribs are affixed with 5mm×5mm hard rubber strips to clamp the roof panel and limit the translational constraint of the metal roof panel, but not its rotational constraint. The two edges perpendicular to the plate ribs are affixed with 20mm thick soft material plates to form limited constraints on the roof panel. The structure is as follows: Figure 4C shown.

[0076] The elastic modulus of the soft material plate is determined based on the following finite element simulation test. A uniformly distributed wind pressure is applied to the finite element model established in 1, causing the roof panel to arch upward. The maximum arch displacement of the center of the roof panel between the two supports is measured, as shown in the figure below. Figure 5 shown.

[0077] Based on the metal roof connection node test device, a finite element model of the connection node is established. Based on the roof panel area covered by the support spacing and the uniformly distributed wind pressure load, the concentrated support reaction force is converted to calculate the relative displacement of the roof panel. Based on the relative displacement, the elastic modulus of the soft material board is adjusted and selected. The soft material board can be made of soft rubber or high-density polyethylene foam board.

[0078] The support force sensor and support displacement sensor are used to obtain the support reaction force and the displacement of the support under external load in real time, and feed the information back to the load actuator control system to control the next action of the actuator.

[0079] The cyclic load actuator and control system are used to provide static load and cyclic load to the support and are installed on the upper or lower part of the roof panel as required.

[0080] The metal roof panel topography measurement system consists of a fill light, an industrial camera, a 3D structured light scanner, and a computer. These are all mounted on the roof panel. The 3D structured light scanner is used to obtain point cloud data of the panel's shape, while the industrial camera is used to capture damage to the metal panel. The industrial camera and 3D structured light scanner are connected to the computer.

[0081] Each constant-amplitude cyclic load condition corresponds to a load value, such as the first load. For each constant-amplitude cyclic load condition, the number of test specimens, n, is determined based on the total number of cycles required for fatigue failure. Generally, n is greater than 5. The total number of cycles refers to the number of load cycles required to achieve failure after constant-amplitude cyclic loading is applied to the test specimen. This number is denoted as M.

[0082] By subjecting the jth test sample to j×M / n constant amplitude cyclic loading, the cumulative damage factor corresponding to each test sample can be increased in equal amplitude, thereby facilitating the subsequent fitting of the relationship curve between the damage degree parameter and the cumulative damage factor.

[0083] The steps of the static graded loading test are as follows:

[0084] (1) According to the actual construction conditions of the metal roof, the test sample is locked manually or mechanically, and the locked test sample is fixed on the loading device.

[0085] (2) Apply graded loads to the support of the test specimen until the specimen fails. After each load level is completed, measure the internal force N and the displacement f of the support.

[0086] (3) For different test samples, parallel tests are carried out, the average values of various parameters are calculated, and the curve function of the change of the support internal force N with the support displacement f is obtained through curve fitting.

[0087] The internal force of the support represents the load applied to the test specimen. A static graded loading test is performed on a specimen that has not undergone constant-amplitude cyclic loading to determine the maximum load. A static graded loading test is performed on a specimen that has undergone j × M / n cycles of constant-amplitude cyclic loading to determine the residual bearing capacity of the specimen.

[0088] After the jth test sample was subjected to j×M / n times of constant amplitude cyclic loading, the wear condition was measured using a laser scanning confocal microscope, and the wear scar depth and width at the contact position between the metal roof panel and the support were calculated, which were recorded as d j and s j , the image of the contact position between the metal roof panel and the support is as follows Figure 6A As shown, the microscope scanning image is as follows Figure 6B As shown, the position of the wear scar depth and wear scar width is as follows Figure 6C shown.

[0089] The jth test sample is subjected to constant amplitude cyclic loading, and the number of load cycles is j×M / n. Similarly, each morphological parameter is recorded after every 10,000 cycles of loading, and is recorded as The subscript i in the parameter indicates the test result after the i-th load cycle, and the superscript j indicates the test result of the j-th sample. After the number of load cycles reaches j×M / n, the test sample is subjected to a static load test until failure, and the load-displacement curve is recorded. The maximum load in the curve is is the residual bearing capacity of the jth test sample after j×M / n load cycles, The maximum load N in the static load test max Compare, ratio Recorded as the bearing capacity loss coefficient.

[0090] In this way, the wear scar depth, wear scar width and bearing capacity loss coefficient of n test samples under different cumulative damage factors under the constant amplitude cyclic load condition of the first load can be obtained, thereby fitting the relationship curve between the wear scar depth and the cumulative damage factor, the relationship curve between the wear scar width and the cumulative damage factor, and the relationship curve between the bearing capacity loss coefficient and the cumulative damage factor under the first load.

[0091] In one possible implementation, the cumulative damage factor of each connection node of the target metal roof is calculated based on the morphological parameters, including:

[0092] Based on a relationship curve between each morphological parameter and the cumulative damage factor, determining the cumulative damage factor corresponding to each morphological parameter of the second connection node, and obtaining at least one cumulative damage factor of the second connection node; wherein the relationship curve between the morphological parameter and the cumulative damage factor is determined by experiment, and the second connection node is any connection node;

[0093] Accordingly, for each connection node, the damage degree parameter of the connection node is predicted using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor. Predicting the damage degree parameter of the connection node includes:

[0094] determining a cumulative damage factor range of the second connection node based on a maximum value and a minimum value among the respective cumulative damage factors of the second connection node;

[0095] The damage degree parameter range of the second connection node is determined by using the cumulative damage factor range of the second connection node and the relationship curve between the damage degree parameter and the cumulative damage factor.

[0096] In this embodiment, for each connection node of the target metal roof, the geometric shape parameters h of the cross section at different positions near it are obtained. k 、w k 、o k 、a k and compared with the initial morphology parameters h0, w0, o0, a0 to obtain the difference Δh of each parameter k =h k -h0、Δw k =w k -w0、Δo k =w k -w0、Δa k =w k -w0, where k represents the kth cross section.

[0097] Perform weighted averaging to obtain the actual parameter change value of each node: Δh=∑q k ·Δh k , Δw=∑q k ·Δw k , Δo=∑q k ·Δo k , Δa=∑qk·Δa k . Where q k represents the weight of the kth cross section.

[0098] Using the obtained cumulative damage factor curve, we can obtain several cumulative damage factors D corresponding to the actual parameter change value. According to D, we can further obtain the corresponding damage degree parameters R, d, s, and select the maximum value D.max and minimum value D min The actual damage range D of the node can be estimated min ≤D≤D max , and the node damage parameter R can also be quantified min ≤R≤R max d min ≤d≤d max 、s min ≤s≤s max , or estimate the residual bearing capacity of the node (1-R max )N max ≤N≤(1-R min )N max .

[0099] In one possible implementation, before determining the cumulative damage factor corresponding to each morphological parameter of the second connection node based on the relationship curve between each morphological parameter and the cumulative damage factor and obtaining at least one cumulative damage factor of the second connection node, the method further includes:

[0100] Obtain multiple test samples; wherein each test sample includes a roof panel and a support, the roof panel is rectangular, the length of the rectangle is the node spacing in the long direction of the target metal roof, and the width of the rectangle is the node spacing in the short direction of the target metal roof;

[0101] For each test sample, constant amplitude cyclic loading is performed on the test sample based on the second load. After each preset number of loadings, multiple sets of morphological parameters are collected until the test sample fails. The number of constant amplitude cyclic loadings at the time of failure of the test sample is used as the total number of fatigue failures corresponding to the second load. Each set of morphological parameters is collected from the profile curve of the plate rib of the test sample at different cross sections.

[0102] For each set of morphological parameters, the ratio of the number of constant amplitude cyclic loadings corresponding to the set of morphological parameters to the total number of fatigue failures corresponding to the second load is calculated as the cumulative damage factor corresponding to the set of morphological parameters;

[0103] For each cumulative damage factor of each test sample, based on the distance from the cross section of each set of morphological parameters to the center of the support, multiple sets of morphological parameters corresponding to the cumulative damage factor are weighted and averaged to obtain multiple sets of one-to-one corresponding morphological parameters and cumulative damage factors;

[0104] Based on the one-to-one correspondence between the morphological parameters and the cumulative damage factors of each group, curve fitting was performed to obtain the relationship curve between the morphological parameters and the cumulative damage factors under the second load.

[0105] In this embodiment, the overall process of conducting tests for different constant amplitude load conditions and fitting the relationship curve between the morphology parameters and the cumulative damage factor includes:

[0106] After the edge-locked test sample is fixed on the loading device, a 3D scanner is used to scan the overall morphology of the test sample, and point cloud data is output, which is defined as the initial point cloud.

[0107] During the test, after each load step (for example, after every 10,000 load steps), the following parameters are recorded: the load is set to zero, and the test sample is scanned with a 3D scanner to form a point cloud, such as Figure 7A As shown. A cross section is uniformly selected along the length direction of the plate rib, and the point cloud within the range of r / 2 from the cross section (r is the average distance between the point clouds) is projected onto the cross section, as shown in Figure 7B As shown. Curve fitting of the projection points yields Figure 7C The curve shown in the figure is used to calculate the height h, width w, opening spacing o and curve contour area a of the fitting curve at the plate rib, as shown in the figure. Figure 7D 、 Figure 7E shown.

[0108] Compare the parameters formed in each load step with the parameters formed in the initial load step to obtain the difference between the parameters In the above parameters, the subscript i represents the test result after the i-th cyclic loading, the subscript k represents the k-th cross section, and the superscript n represents the test result of the n-th sample.

[0109] Thus, the morphological parameters of n test samples under different cumulative damage factors under the constant amplitude cyclic load condition of the second load can be obtained, thereby fitting the relationship curve between the morphological parameters and the cumulative damage factor. By adjusting the load and repeating the test, the relationship curve between the morphological parameters and the cumulative damage factor under various constant amplitude cyclic load conditions can be obtained. For example, the relationship curve Δh-D between the morphological parameters and the cumulative damage factor is as follows: Figure 8A As shown, the relationship curve RD between the bearing capacity loss coefficient and the cumulative damage factor is as follows Figure 8B shown.

[0110] In a possible implementation, obtaining the topographic parameters of each connection node of the target metal roof includes:

[0111] Acquire multiple sets of morphological parameters of the second connection node of the target metal roof; wherein each set of morphological parameters is collected from the contour curves of the plate rib corresponding to the second connection node at different cross sections;

[0112] Based on the distance from the cross section where each set of morphological parameters of the second connection node is located to the center of the support, weighted average of each set of morphological parameters is performed to obtain the morphological parameters of the second connection node.

[0113] In this embodiment, considering that multiple cross sections are selected during the test, a weighted average of the cross-sectional data is calculated to facilitate the use of the test data: Comprehensively reflects the changes in the node's morphology. k is the weight function, and the distance l from the kth cross section to the support center k The smaller the distance, the greater the weight, and the larger the distance, the smaller the weight.

[0114] In one possible implementation, based on the distance from the cross section of each set of topography parameters to the center of the support, the weighted average calculation formula for each topography parameter is:

[0115] Δh=∑q k ·Δh k

[0116] Δw=∑q k ·Δw k

[0117] Δo=∑q k ·Δo k

[0118] Δa=∑q k ·Δa k

[0119] Where Δh is the difference between the height of the contour curve connecting the nodes and the initial value, q k is the weight of the kth cross section, Δh k is the difference between the height of the profile curve of the kth cross section and the initial value, Δw is the difference between the width of the profile curve connecting the nodes and the initial value, Δw k is the difference between the width of the profile curve of the kth cross section and the initial value, Δo is the difference between the opening spacing of the profile curve connecting the nodes and the initial value, Δo k is the difference between the opening spacing of the profile curve of the kth cross section and the initial value, Δa is the difference between the curve area of the profile curve connecting the nodes and the initial value, Δa k is the difference between the curve area of the profile curve of the kth cross section and the initial value;

[0120] The cross-sectional weights are calculated using any of the following formulas:

[0121]

[0122] q k =exp[-λl k ]

[0123]

[0124] Among them, l k is the distance from the kth cross section to the center of the support, σ is the bandwidth parameter, λ is the attenuation rate parameter, and L is half of the longitudinal spacing of the supports.

[0125] In this embodiment, Gaussian weighting can be selected according to the influence degree of the morphological parameters of each cross section in actual conditions. Exponentially decaying weighted q k =exp[-λl k ], cubic function The weight of each cross section is calculated using an equal weight function. In the above formula, σ is the bandwidth parameter that controls the weight decay rate, λ>0 represents the decay rate parameter, and L is half of the longitudinal spacing of the supports.

[0126] As can be seen from the above, the present invention has the following beneficial effects:

[0127] 1. This method determines load conditions based on the metal roof system's environment and actual structural form, combined with the actual internal force response of the nodes. This combination of load conditions reflects the node's true service state. As a result, the node's test load history is similar to its actual environmental load history, and through this combination, it is applicable to all roof nodes. This method is both targeted and universal in simulating roof wind loads.

[0128] 2. The present invention is aimed at the service performance of metal roof nodes. The test results are directional, the test equipment and samples are small in size, the test cost is low, and the test results have good reproducibility. The test results quantify the service performance and remaining life of metal roof nodes, which is convenient for scientific research and is also suitable for engineering detection.

[0129] 3. The present invention comprehensively considers the destructive effects of dynamic and static wind pressure on metal roof nodes, and conducts static load destructive tests after the test samples have undergone a certain number of cyclic loads. The test results directly reflect the residual bearing capacity of the nodes and scientifically quantify the degree of degradation of the service performance of the metal roof.

[0130] 4. The present invention uses an industrial camera and a three-dimensional structured light scanner to track the geometric changes and damage of metal roof panels in real time. The functional relationships of Δh-D, Δw-D, Δo-D, and Δa-D obtained from the test results represent the service status of the metal roof connection nodes. RD, dD, and sD represent the degree of damage to the metal roof connection nodes. This intuitive and operational approach can be easily extended to in-situ inspection projects for existing metal roofs to quantify the service status of existing roofs.

[0131] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0132] The following are device embodiments of the present invention. For details not fully described therein, reference may be made to the corresponding method embodiments described above.

[0133] Figure 9 The following is a schematic diagram showing the structure of a service performance evaluation device for a metal roof connection node provided by an embodiment of the present invention. For ease of explanation, only the parts related to the embodiment of the present invention are shown, which are described in detail as follows:

[0134] like Figure 9 As shown, the service performance evaluation device 2 for the metal roof connection node includes:

[0135] An acquisition module 21 is configured to acquire load parameters of a target metal roof or morphological parameters of each connection node of the target metal roof; wherein the morphological parameters include a difference between an initial value and one or more of the height, width, opening spacing, and curve area of a rib profile curve corresponding to the connection node;

[0136] A calculation module 22 is used to calculate the cumulative damage factor of each connection node of the target metal roof based on the load parameter or the shape parameter;

[0137] The prediction module 23 is used to predict the damage degree parameter of each connection node using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor, so as to evaluate the service performance of each connection node of the metal roof based on the damage degree parameter; wherein the relationship curve between the damage degree parameter and the cumulative damage factor is determined through experiments.

[0138] In a possible implementation, the calculation module 22 is specifically configured to:

[0139] Apply the load parameters to the finite element model of the target metal roof to obtain the internal force response time history data of each connection node of the target metal roof;

[0140] For each connection node, the internal force response time history data of the connection node is decomposed into multiple constant amplitude cyclic load cases and the number of cycles of each constant amplitude cyclic load case based on the rain flow counting method;

[0141] For each constant amplitude cyclic load condition of the first connection node, calculate the ratio of the number of cycles of the first connection node under the constant amplitude cyclic load condition to the total number of fatigue failures under the constant amplitude cyclic load condition, and use this ratio as the cumulative damage factor of the first connection node under the constant amplitude cyclic load condition, thereby obtaining multiple cumulative damage factors of the first connection node; wherein the first connection node is any connection node;

[0142] Accordingly, the prediction module 23 is specifically used for:

[0143] In the relationship curve between the damage degree parameter and the cumulative damage factor, find the damage degree parameter corresponding to each cumulative damage factor of the first connection node;

[0144] Each damage degree parameter is added together to obtain the damage degree parameter of the first connection node.

[0145] In a possible implementation, the damage degree parameter includes one or more of a bearing capacity loss coefficient, a wear scar depth at a contact position between the metal roof and the support, and a wear scar width at a contact position between the metal roof and the support; and the prediction module 23 is further configured to:

[0146] Before predicting the damage degree parameter of each connection node using the cumulative damage factor of the connection node and a relationship curve between the damage degree parameter and the cumulative damage factor, a plurality of test samples are obtained; wherein each test sample includes a roof panel and a support, the roof panel is rectangular, the length of the rectangle is the node spacing in the long direction of the target metal roof, and the width is the node spacing in the short direction of the target metal roof;

[0147] For the jth test sample, perform j×M / n constant amplitude cyclic loading on the jth test sample based on the first load, and measure the wear scar depth and wear scar width at the contact position between the roof panel and the support of the jth test sample; where j∈[1,n], n is the total number of test samples, and M is the total number of fatigue failures corresponding to the first load;

[0148] Perform static graded loading test on the jth test sample until the jth test sample fails;

[0149] The maximum load in the static graded loading test As the residual bearing capacity of the jth test sample after the first load cycle j×M / n times, and calculate the loss rate of the residual bearing capacity compared to the maximum load of the test sample, to obtain the bearing capacity loss coefficient of the jth test sample after the first load cycle j×M / n times;

[0150] Based on the wear scar depth, wear scar width, bearing capacity loss coefficient, and the corresponding cumulative damage factor, curve fitting was performed to obtain the relationship curve between the wear scar depth and the cumulative damage factor under the first load, the relationship curve between the wear scar width and the cumulative damage factor, and the relationship curve between the bearing capacity loss coefficient and the cumulative damage factor.

[0151] In a possible implementation, the calculation module 22 is specifically configured to:

[0152] Based on a relationship curve between each morphological parameter and the cumulative damage factor, determining the cumulative damage factor corresponding to each morphological parameter of the second connection node, and obtaining at least one cumulative damage factor of the second connection node; wherein the relationship curve between the morphological parameter and the cumulative damage factor is determined by experiment, and the second connection node is any connection node;

[0153] Accordingly, the prediction module 23 is specifically used for:

[0154] determining a cumulative damage factor range of the second connection node based on a maximum value and a minimum value among the respective cumulative damage factors of the second connection node;

[0155] The damage degree parameter range of the second connection node is determined by using the cumulative damage factor range of the second connection node and the relationship curve between the damage degree parameter and the cumulative damage factor.

[0156] In a possible implementation, the calculation module 22 is further configured to:

[0157] Before determining the cumulative damage factor corresponding to each morphological parameter of the second connection node based on a relationship curve between each morphological parameter and the cumulative damage factor, and obtaining at least one cumulative damage factor of the second connection node, a plurality of test samples are obtained; wherein each test sample includes a roof panel and a support, the roof panel is rectangular, the length of the rectangle is the node spacing in the long side direction of the target metal roof, and the width is the node spacing in the short side direction of the target metal roof;

[0158] For each test sample, constant amplitude cyclic loading is performed on the test sample based on the second load. After each preset number of loadings, multiple sets of morphological parameters are collected until the test sample fails. The number of constant amplitude cyclic loadings at the time of failure of the test sample is used as the total number of fatigue failures corresponding to the second load. Each set of morphological parameters is collected from the profile curve of the plate rib of the test sample at different cross sections.

[0159] For each set of morphological parameters, the ratio of the number of constant amplitude cyclic loadings corresponding to the set of morphological parameters to the total number of fatigue failures corresponding to the second load is calculated as the cumulative damage factor corresponding to the set of morphological parameters;

[0160] For each cumulative damage factor of each test sample, based on the distance from the cross section of each set of morphological parameters to the center of the support, multiple sets of morphological parameters corresponding to the cumulative damage factor are weighted and averaged to obtain multiple sets of one-to-one corresponding morphological parameters and cumulative damage factors;

[0161] Based on the one-to-one correspondence between the morphological parameters and the cumulative damage factors of each group, curve fitting was performed to obtain the relationship curve between the morphological parameters and the cumulative damage factors under the second load.

[0162] In a possible implementation, the acquisition module 21 is specifically configured to:

[0163] Acquire multiple sets of morphological parameters of the second connection node of the target metal roof; wherein each set of morphological parameters is collected from the contour curves of the plate rib corresponding to the second connection node at different cross sections;

[0164] Based on the distance from the cross section where each set of morphological parameters of the second connection node is located to the center of the support, weighted average of each set of morphological parameters is performed to obtain the morphological parameters of the second connection node.

[0165] In one possible implementation, based on the distance from the cross section of each set of topography parameters to the center of the support, the weighted average calculation formula for each set of topography parameters is:

[0166] Δh=∑q k ·Δh k

[0167] Δw=∑q k ·Δw k

[0168] Δo=∑q k ·Δo k

[0169] Δa=∑q k ·Δa k

[0170] Where Δh is the difference between the height of the contour curve connecting the nodes and the initial value, q k is the weight of the kth cross section, Δh k is the difference between the height of the profile curve of the kth cross section and the initial value, Δw is the difference between the width of the profile curve connecting the nodes and the initial value, Δw k is the difference between the width of the profile curve of the kth cross section and the initial value, Δo is the difference between the opening spacing of the profile curve connecting the nodes and the initial value, Δo k is the difference between the opening spacing of the profile curve of the kth cross section and the initial value, Δa is the difference between the curve area of the profile curve connecting the nodes and the initial value, Δa k is the difference between the curve area of the profile curve of the kth cross section and the initial value;

[0171] The cross-sectional weights are calculated using any of the following formulas:

[0172]

[0173] q k =exp[-λl k ]

[0174]

[0175] Among them, l k is the distance from the kth cross section to the center of the support, σ is the bandwidth parameter, λ is the attenuation rate parameter, and L is half of the longitudinal spacing of the supports.

[0176] This embodiment of the present invention converts the load parameters of the target metal roof into a cumulative damage factor, comprehensively considering the destructive effects of dynamic and static wind pressure on the metal roof connection nodes, thereby describing the load history of the connection nodes under various constant-amplitude load conditions. Simultaneously, a relationship between morphological parameters and cumulative damage factors is established. When load parameters are unavailable, the cumulative damage factor is indirectly identified using the morphological changes in the plate rib profile curve. Finally, the relationship between the damage degree parameter and the cumulative damage factor is used to directly predict the damage degree of the metal roof connection nodes and scientifically quantify the degree of degradation of the metal roof's service performance.

[0177] Figure 10 Schematic diagram of a terminal provided by an embodiment of the present invention. Figure 10 As shown, the terminal 3 of this embodiment includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30. When the processor 30 executes the computer program 32, the steps of the above-mentioned service performance evaluation method for each metal roof connection node are implemented, such as Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, Figure 9 Functions of the modules / units 21 to 23 are shown.

[0178] Exemplarily, the computer program 32 may be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 30 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program 32 in the terminal 3. For example, the computer program 32 may be divided into Figure 9 Modules / units 21 to 23 are shown.

[0179] The terminal 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal 3 may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will understand that Figure 10 It is only an example of terminal 3 and does not constitute a limitation on terminal 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0180] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0181] The memory 31 may be an internal storage unit of the terminal 3, such as a hard disk or memory of the terminal 3. The memory 31 may also be an external storage device of the terminal 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. equipped on the terminal 3. Furthermore, the memory 31 may include both an internal storage unit of the terminal 3 and an external storage device. The memory 31 is used to store the computer program and other programs and data required by the terminal. The memory 31 may also be used to temporarily store data that has been output or is about to be output.

[0182] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0183] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0184] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0185] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, and can be electrical, mechanical, or other forms.

[0186] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0187] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0188] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned service performance evaluation method embodiments of each metal roof connection node. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0189] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for evaluating the service performance of metal roof connection nodes, characterized in that: include: Obtaining load parameters of a target metal roof or morphological parameters of each connection node of the target metal roof; wherein the morphological parameters include a difference between one or more of the height, width, opening spacing, and curve area of a profile curve of a rib corresponding to the connection node and an initial value; Calculating the cumulative damage factor of each connection node of the target metal roof based on the load parameter or the shape parameter; For each connection node, the damage degree parameter of the connection node is predicted using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor, so as to evaluate the service performance of each connection node of the metal roof based on the damage degree parameter; wherein the relationship curve between the damage degree parameter and the cumulative damage factor is determined through experiments.

2. The service performance evaluation method of the metal roof connection node according to claim 1, characterized in that: Calculating the cumulative damage factor of each connection node of the target metal roof based on the load parameters, including: Applying the load parameters to the finite element model of the target metal roof to obtain internal force response time history data of each connection node of the target metal roof; For each connection node, the internal force response time history data of the connection node is decomposed into multiple constant amplitude cyclic load cases and the number of cycles of each constant amplitude cyclic load case based on the rain flow counting method; For each constant amplitude cyclic load condition of a first connection node, calculating a ratio of the number of cycles of the first connection node under the constant amplitude cyclic load condition to the total number of fatigue failures under the constant amplitude cyclic load condition, and using this ratio as the cumulative damage factor of the first connection node under the constant amplitude cyclic load condition, thereby obtaining a plurality of cumulative damage factors of the first connection node; wherein the first connection node is any connection node; Accordingly, for each connection node, using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor, predicting the damage degree parameter of the connection node includes: In a relationship curve between damage degree parameters and cumulative damage factors, searching for a damage degree parameter corresponding to each cumulative damage factor of the first connection node; Each damage degree parameter is added together to obtain the damage degree parameter of the first connection node.

3. The service performance evaluation method of the metal roof connection node according to claim 2, characterized in that: The damage degree parameter includes one or more of the following: a bearing capacity loss coefficient, a wear scar depth at the contact position between the metal roof and the support, and a wear scar width at the contact position between the metal roof and the support; and before predicting the damage degree parameter of each connection node using the cumulative damage factor of the connection node and a relationship curve between the damage degree parameter and the cumulative damage factor, the method further includes: Obtain multiple test samples; wherein each test sample includes a roof panel and a support, the roof panel is rectangular, the length of the rectangle is the node spacing in the long side direction of the target metal roof, and the width of the rectangle is the node spacing in the short side direction of the target metal roof; For the jth test sample, perform j×M / n constant amplitude cyclic loading on the jth test sample based on the first load, and measure the wear scar depth and wear scar width at the contact position between the roof panel and the support of the jth test sample; where j∈[1,n], n is the total number of test samples, and M is the total number of fatigue failures corresponding to the first load; Performing a static graded loading test on the j-th test sample until the j-th test sample fails; The maximum load in the static graded loading test as the residual bearing capacity of the j-th test sample after j×M / n times of the first load cycle, and calculating the loss rate of the residual bearing capacity compared to the maximum load of the test sample to obtain the bearing capacity loss coefficient of the j-th test sample after j×M / n times of the first load cycle; Based on the wear scar depth, wear scar width, bearing capacity loss coefficient, and the corresponding cumulative damage factor, curve fitting is performed to obtain the relationship curve between the wear scar depth and the cumulative damage factor under the first load, the relationship curve between the wear scar width and the cumulative damage factor, and the relationship curve between the bearing capacity loss coefficient and the cumulative damage factor.

4. The service performance evaluation method of the metal roof connection node according to claim 1, characterized in that: Calculating the cumulative damage factor of each connection node of the target metal roof based on the morphological parameters, including: Determine, based on a relationship curve between each morphological parameter and the cumulative damage factor, a cumulative damage factor corresponding to each morphological parameter of the second connection node, and obtain at least one cumulative damage factor of the second connection node; wherein the relationship curve between the morphological parameter and the cumulative damage factor is determined by experiment, and the second connection node is any connection node; Accordingly, for each connection node, the damage degree parameter of the connection node is predicted using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor. Predicting the damage degree parameter of the connection node includes: determining a cumulative damage factor range of the second connection node based on a maximum value and a minimum value among the respective cumulative damage factors of the second connection node; The damage degree parameter range of the second connection node is determined by using the cumulative damage factor range of the second connection node and a relationship curve between the damage degree parameter and the cumulative damage factor.

5. The service performance evaluation method of the metal roof connection node according to claim 4, characterized in that: Before determining the cumulative damage factor corresponding to each morphology parameter of the second connection node based on the relationship curve between each morphology parameter and the cumulative damage factor, and obtaining at least one cumulative damage factor of the second connection node, the method further includes: Obtain multiple test samples; wherein each test sample includes a roof panel and a support, the roof panel is rectangular, the length of the rectangle is the node spacing in the long side direction of the target metal roof, and the width of the rectangle is the node spacing in the short side direction of the target metal roof; For each test sample, constant amplitude cyclic loading is performed on the test sample based on the second load. After each preset number of loadings, multiple sets of morphological parameters are collected until the test sample fails. The number of constant amplitude cyclic loadings at the time of failure of the test sample is used as the total number of fatigue failures corresponding to the second load. Each set of morphological parameters is collected from a profile curve of the plate rib of the test sample at different cross sections. For each set of morphological parameters, calculating the ratio of the number of constant amplitude cyclic loadings corresponding to the set of morphological parameters to the total number of fatigue failures corresponding to the second load as the cumulative damage factor corresponding to the set of morphological parameters; For each cumulative damage factor of each test sample, based on the distance from the cross section of each set of morphological parameters to the center of the support, multiple sets of morphological parameters corresponding to the cumulative damage factor are weighted and averaged to obtain multiple sets of one-to-one corresponding morphological parameters and cumulative damage factors; Based on the one-to-one correspondence between the morphological parameters and the cumulative damage factors of each group, curve fitting is performed to obtain a relationship curve between the morphological parameters and the cumulative damage factors under the second load.

6. The service performance evaluation method of the metal roof connection node according to claim 4, characterized in that: Obtaining the morphological parameters of each connection node of the target metal roof, including: Acquire multiple sets of morphological parameters of the second connection node of the target metal roof; wherein each set of morphological parameters is collected from the contour curves of the plate rib corresponding to the second connection node at different cross sections; Based on the distance from the cross section where each set of morphological parameters of the second connection node is located to the center of the support, weighted averaging of each set of morphological parameters is performed to obtain the morphological parameters of the second connection node.

7. The service performance evaluation method of the metal roof connection node according to claim 6, characterized in that: Based on the distance from the cross section of each set of morphological parameters to the center of the support, the calculation formula for the weighted average of each set of morphological parameters is: Δh=∑q k ·Δh k Δw=∑q k ·Δw k Δo=∑q k ·Δo k Δα=∑q k ·Da k Where Δh is the difference between the height of the contour curve connecting the nodes and the initial value, q k is the weight of the kth cross section, Δh k is the difference between the height of the profile curve of the kth cross section and the initial value, Δw is the difference between the width of the profile curve connecting the nodes and the initial value, Δw k is the difference between the width of the profile curve of the kth cross section and the initial value, Δo is the difference between the opening spacing of the profile curve connecting the nodes and the initial value, Δo k is the difference between the opening spacing of the profile curve of the kth cross section and the initial value, Δa is the difference between the curve area of the profile curve connecting the nodes and the initial value, Δa k is the difference between the curve area of the profile curve of the kth cross section and the initial value; The cross-sectional weights are calculated using any of the following formulas: q k =exp[-λl k ] Among them, l k is the distance from the kth cross section to the center of the support, σ is the bandwidth parameter, λ is the attenuation rate parameter, and L is half of the longitudinal spacing of the supports.

8. A service performance evaluation device for metal roof connection nodes, characterized in that: include: An acquisition module, configured to acquire load parameters of a target metal roof or morphological parameters of each connection node of the target metal roof; wherein the morphological parameters include a difference between an initial value and one or more of the height, width, opening spacing, and curve area of a profile curve of a rib corresponding to the connection node; a calculation module, configured to calculate a cumulative damage factor of each connection node of the target metal roof based on the load parameter or the shape parameter; A prediction module is used to predict the damage degree parameter of each connection node using the cumulative damage factor of the connection node and the relationship curve between the damage degree parameter and the cumulative damage factor, so as to evaluate the service performance of each connection node of the metal roof based on the damage degree parameter; wherein the relationship curve between the damage degree parameter and the cumulative damage factor is determined through experiments.

9. A terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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