Reticulated shell structure damage identification method and device based on strain statistical moment

Abstract

The embodiment of the invention discloses a latticed shell structure damage identification method based on a strain statistical moment, and the method comprises the steps: obtaining the wind speed at a preset collection moment and first strain response data collected by a sensor at each measurement point under the wind direction, and carrying out the calculation of a first strain statistical moment value according to the first strain response data; acquiring second strain response data acquired by the sensors on the measuring points again under the same wind speed and the same wind direction, and calculating according to the second strain response data to obtain a second strain statistical moment value; calculating a strain statistical moment standardization difference value of each measuring point according to the first strain statistical moment value and the second strain statistical moment value; and performing L2 norm calculation according to the strain statistical moment standardized difference values of all the measuring points in any monitoring area to obtain an L2 norm of the monitoring area, and judging whether the monitoring area is damaged or not according to the L2 norm. Therefore, the damage area of the reticulated shell structure can be accurately identified, the detection sensitivity of local damage is improved, and the environmental noise interference resistance is enhanced.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of damage identification, in particular to a net shell structure damage identification method and device based on strain statistical moment. BACKGROUND

[0002] The net shell structure is a net-shaped shell structure, or a curved surface net rack structure. The rod mainly bears axial force, and the internal force distribution of the structure is relatively uniform, which can fully exert the strength of the material. It is widely used in large sports venues, transportation hubs, industrial facilities, etc.

[0003] In the whole process from construction to service of the large-span net shell structure, its stiffness will gradually decline under the influence of wind load, earthquake action, human impact, fatigue effect, chemical corrosion and other factors, and different degrees of structural damage will occur. With the continuous accumulation of damage, the mechanical properties of the structure as a whole may be weakened, and in severe cases, the structure may even fail, causing serious personnel casualties and property losses. In order to ensure the safe operation of the structure, it is necessary to establish an efficient early damage detection method and early warning mechanism to realize timely identification and treatment of initial structural defects, thereby preventing major accidents. Therefore, it is of great engineering significance to research and improve the damage identification technology of large-span net shell structures. SUMMARY

[0004] In view of the above problems, the present application is proposed to provide a net shell structure damage identification method, device, computing device, computer storage medium and computer program product based on strain statistical moment, which overcomes the above problems or at least partially solves the above problems, aiming to solve the technical problem that the existing net shell structure monitoring is not sensitive to local damage.

[0005] According to one aspect of the embodiment of the present application, a net shell structure damage identification method based on strain statistical moment is provided. The preset rod of the net shell structure to be identified is divided into a preset number of monitoring areas, and a plurality of sensors are arranged on each monitoring area as measuring points. The method comprises:

[0006] Obtaining first strain response data collected by the sensors on each measuring point under the preset collection time of wind speed and wind direction, and calculating first strain statistical moment values according to the first strain response data;

[0007] Obtaining second strain response data collected by the sensors on each measuring point again under the same wind speed and wind direction, and calculating second strain statistical moment values according to the second strain response data;

[0008] Calculating the strain statistical moment standardized difference value of each measuring point according to the first strain statistical moment value and the second strain statistical moment value;

[0009] According to the L2 norm, it is judged whether the monitoring area has damage.

[0010] Further, the calculating of the strain statistical moment normalized difference value of each measuring point according to the first strain statistical moment value and the second strain statistical moment value further comprises:

[0011] The strain statistical moment normalized difference value of any measuring point is calculated by using the following formula:

[0012]

[0013] Wherein, D is the strain statistical moment normalized difference value of a measuring point at different time under the condition that the wind speed and direction are unchanged, M1 is the first strain statistical moment value, M2 is the second strain statistical moment value,

[0014] Further, the calculating of the L2 norm of the monitoring area according to the normalized difference value of all measuring points in the monitoring area further comprises:

[0015] The L2 norm of any monitoring area is calculated by using the following formula:

[0016]

[0017] D is the strain statistical moment normalized difference value of a measuring point at different time under the condition that the wind speed and direction are unchanged, and L2 is the L2 norm of all measuring points in a monitoring area.

[0018] Further, the judging of whether the monitoring area has damage according to the L2 norm further comprises:

[0019] It is judged whether the L2 norm is greater than or equal to a preset L2 norm threshold value;

[0020] If yes, it is determined that the monitoring area has damage; if no, it is determined that the monitoring area has no damage.

[0021] Further, before the first strain statistical moment value is calculated according to the first strain response data, the method further comprises: filtering the first strain response data to obtain filtered first strain response data, wherein the filtered first strain response data is strain response data mainly in a first-order frequency signal;

[0022] The calculating of the first strain statistical moment value according to the first strain response data further comprises:

[0023] The first strain statistical moment value is calculated according to the filtered first strain response data;

[0024] Before the second strain statistical moment value is calculated according to the second strain response data, the method further comprises: filtering the second strain response data to obtain filtered second strain response data, wherein the filtered second strain response data is strain response data mainly in a first-order frequency signal;

[0025] The second strain statistical moment value is calculated according to the filtered second strain response data.

[0026] The second strain statistical moment value is calculated according to the filtered second strain response data.

[0027] Further, the preset rod member is a lower chord rod member, and the number of sensors is 4.

[0028] According to another aspect of the embodiments of the present application, a device for identifying damage of a latticed shell structure based on strain statistical moments is provided. The preset rod members of the latticed shell structure to be identified are divided into a preset number of monitoring areas, and a plurality of sensors are arranged on each monitoring area as measuring points. The device comprises:

[0029] The acquisition module is adapted to acquire first strain response data collected by the sensors on each measuring point under a preset acquisition time of wind speed and wind direction, and acquire second strain response data collected again by the sensors on each measuring point under the same wind speed and wind direction.

[0030] The first calculation module is adapted to calculate a first strain statistical moment value according to the first strain response data, and calculate a second strain statistical moment value according to the second strain response data.

[0031] The second calculation module is adapted to calculate a strain statistical moment normalized difference value of each measuring point according to the first strain statistical moment value and the second strain statistical moment value.

[0032] The third calculation module is adapted to calculate an L2 norm of a monitoring area according to the strain statistical moment normalized difference values of all measuring points in the monitoring area for any monitoring area.

[0033] The judgment module is adapted to judge whether the monitoring area has damage according to the L2 norm.

[0034] According to still another aspect of the embodiments of the present application, a computing device is provided, which comprises a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete communication with each other through the communication bus.

[0035] The memory is used to store at least one executable instruction, and the executable instruction causes the processor to perform operations corresponding to the above-mentioned method for identifying damage of a latticed shell structure based on strain statistical moments.

[0036] According to still another aspect of the embodiments of the present application, a computer storage medium is provided, and the computer storage medium stores at least one executable instruction, and the executable instruction causes a processor to perform operations corresponding to the strain statistical moment based damage identification method of a reticulated shell structure as described above.

[0037] According to still another aspect of the embodiments of the present application, a computer program product is provided, and the computer program product includes at least one executable instruction, and the executable instruction causes a processor to perform operations corresponding to the strain statistical moment based damage identification method of a reticulated shell structure as described above.

[0038] According to the strain statistical moment based damage identification method of a reticulated shell structure provided by the embodiments of the present application, the L2 norm of the standardized difference of the strain statistical moment is taken as a damage index, the regional damage of the reticulated shell structure can be identified, the workload of manual checking is reduced, and the method is suitable for preliminary damage identification of the reticulated shell structure. Meanwhile, based on the symmetry and stress analysis of the reticulated shell structure, the monitoring points are arranged on the lower chord members of the structure, the number of sensors is reduced, the monitoring cost is reduced, and the economic benefit is improved. Moreover, the present application has good noise resistance, thereby solving the technical problems that the existing damage identification method based on the modal index is not sensitive to local damage and is greatly affected by noise.

[0039] The above description is only a summary of the technical solutions of the embodiments of the present application, in order to enable the technical means of the embodiments of the present application to be more clearly understood, and to be implemented according to the content of the description, and in order to enable the above and other purposes, characteristics and advantages of the embodiments of the present application to be more apparent and easy to understand, the following specifically describes the specific implementation of the embodiments of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0040] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are intended to depict only preferred embodiments of the application and therefore should not be considered to limit the scope of the application. Furthermore, the drawings are provided for illustrative purposes only and represent only typical or exemplary embodiments of the application. Unless otherwise noted, like numerals refer to like elements throughout the drawings. Other embodiments of the large-span steel structure monitoring technology drawings can be derived from the large-span reticulated shell structure monitoring technology drawings without paying creative labor, which is apparent to those skilled in the art of monitoring. In the drawings:

[0041] Figure 1 Fig. 1 shows a flowchart of a strain statistical moment based damage identification method of a reticulated shell structure according to an embodiment of the present application;

[0042] Figure 2A Fig. 2 is a front view of a reticulated shell structure model;

[0043] Figure 2B Fig. 3 is a left view of a reticulated shell structure model;

[0044] Figure 2C Fig. 4 is a top view of a reticulated shell structure model;

[0045] Figure 3 A schematic diagram of monitoring areas and monitoring points of a latticed shell structure;

[0046] Figure 4 A flowchart of a method for latticed shell structure damage identification based on strain statistical moments according to another embodiment of the present application is shown;

[0047] Figures 5A-5D A damage identification result diagram of damage occurring in a monitoring area of a top chord member;

[0048] Figures 5E-5H A damage identification result diagram of damage occurring in a monitoring area of a bottom chord member;

[0049] Figures 5I-5L A damage identification result diagram of damage occurring in a monitoring area of a web member;

[0050] Figures 6A-6D A damage identification result diagram of damage occurring in a non-monitoring area of a top chord member;

[0051] Figures 6E-6H A damage identification result diagram of damage occurring in a non-monitoring area of a bottom chord member;

[0052] Figures 6I-6L A damage identification result diagram of damage occurring in a non-monitoring area of a web member;

[0053] Figure 7A A comparison diagram of damage identification results of a monitoring area and a non-monitoring area of a top chord member when the damage positions are the same;

[0054] Figure 7B A comparison diagram of damage identification results of a monitoring area and a non-monitoring area of a bottom chord member when the damage positions are the same;

[0055] Figure 7C A comparison diagram of damage identification results of a monitoring area and a non-monitoring area of a web member when the damage positions are the same;

[0056] Figure 8 A structural block diagram of a latticed shell structure damage identification device based on strain statistical moments according to an embodiment of the present application is shown;

[0057] Figure 9 A structural schematic diagram of a computing device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0058] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms without being limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be thoroughly and completely understood, and will fully convey the scope of the present disclosure to those skilled in the art.

[0059] In the description of the embodiments of the present application, it should be understood that the terms "length", "width", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited.

[0060] Figure 1 A flowchart of a strain statistical moment-based reticulated shell structure damage identification method according to an embodiment of the present application is shown. The preset members of the reticulated shell structure to be identified are divided into a preset number of monitoring areas, and a plurality of sensors are arranged on each monitoring area as measuring points. As shown in Figure 1 The method comprises the following steps:

[0061] In step S101, the first strain response data collected by the sensors on each measuring point at a preset collection time is obtained, and the first strain statistical moment value is calculated according to the first strain response data.

[0062] In the present embodiment, the reticulated shell structure to be identified is a large-span reticulated shell structure. According to the symmetry of the reticulated shell structure to be identified, the preset members are divided into a preset number of monitoring areas, for example, 12 monitoring areas. For example, the preset members are divided into 4 monitoring parts, and each monitoring part is divided into 3 monitoring areas.

[0063] Specifically, the position of the sensor arranged on the reticulated shell structure to be identified can be calculated and analyzed according to 3D3S or ANSYS. According to the engineering design drawings of the reticulated shell structure to be identified, a dynamic numerical model of the reticulated shell structure is established. The load simulation is performed on the dynamic numerical model of the reticulated shell structure, and the real internal force distribution of the structure is obtained. Under the influence of static load, the internal force of the lower chord member of the reticulated shell structure to be identified is greater than that of the upper chord member and the web member, so the measuring points are arranged on the lower chord member of the reticulated shell structure to be identified, i.e., the preset member is the lower chord member.

[0064] The number and position of the measuring points on the lower chord members of the to-be-identified latticed shell structure are determined according to the internal force fluctuation and the symmetry of the latticed shell structure, the lower chord members are divided into four monitoring parts, each monitoring part is divided into three monitoring regions, and there are totally 12 monitoring regions, four measuring points are arranged in one monitoring region, and the four measuring points are evenly arranged in the monitoring region, so as to collect the strain change information of the whole monitoring region as much as possible.

[0065] Firstly, the latticed shell structure is preliminarily divided into four monitoring parts based on the symmetry of the latticed shell structure. Since the number of members contained in each monitoring part is large, the monitoring range is further divided into a plurality of monitoring regions. Then, the measuring points are arranged in the monitoring region, and numerical simulation is performed by means of ANSYS software to analyze the damage identification effect.

[0066] If the number of region division is small, the number of members contained in each region is large, and a large number of measuring points need to be arranged to comprehensively monitor the health condition of the region. If the number of region division is too large, the total number of monitoring regions is large, which is not conducive to subsequent operation, maintenance and management. Therefore, after comparing the finite element simulation results of different division numbers and the corresponding sensor arrangement schemes, it is finally determined that the initial four monitoring parts are further divided into three monitoring regions respectively, and four measuring points are evenly arranged in each monitoring region, so as to realize effective monitoring of local damage.

[0067] The preset acquisition time can be an acquisition time defined according to actual needs. In the process of latticed shell structure damage identification, the anemometer and wind vane are used to measure and record the wind speed and direction at this time, so that the strain response data can be collected again under the same wind speed and direction for damage identification in the subsequent process.

[0068] The arranged sensors can be resistance strain gauges (having the advantages of low cost and being suitable for static / low-frequency dynamic strain) or optical fiber strain sensors (having the advantages of anti-electromagnetic interference and being suitable for long-term monitoring) according to the structure type (such as latticed shell lower chord members). The first strain response data of the sensors on each measuring point under the preset acquisition time of wind speed and direction are acquired, the first strain response data is a voltage signal, when the first strain statistical moment value is calculated according to the first strain response data, the first strain response data needs to be amplified, filtered and denoised, and then converted into physical quantity with micro-strain (με) as the unit according to the sensitivity coefficient of the strain gauge, bridge configuration and excitation voltage and other parameters. Then, the first strain statistical moment value is calculated according to the converted data, and the process of calculating the strain statistical moment value is not described in detail here.

[0069] In an optional embodiment of the present application, in order to accurately identify the damage and avoid irrelevant signals affecting the damage identification accuracy, the first strain response data needs to be filtered to obtain filtered first strain response data, wherein the filtered first strain response data is strain response data mainly in the form of first-order frequency signals; then, the first strain statistical moment value is calculated according to the filtered first strain response data, wherein the order of the first strain statistical moment value is four, i.e., the fourth-order strain statistical moment value.

[0070] Wherein, the strain statistical moment value can be calculated by using the following formula: In order to accurately identify the potential damage, the fourth-order strain statistical moment value needs to be calculated, and when n in the above formula is 4, it is the fourth-order strain statistical moment value, wherein M n is the n-order strain statistical moment value, x is the converted value of the filtered first strain response data, x is the mean value, p(x) is the strain probability density function, and when n is 4, M 4 is the fourth-order strain statistical moment value.

[0071] The first strain statistical moment value is used as an initial value for damage identification, which is the data of the net shell structure without damage obtained by finite element analysis.

[0072] In step S102, the second strain response data collected by the sensors at each measuring point under the same wind speed and the same wind direction is obtained, and the second strain statistical moment value is calculated according to the second strain response data.

[0073] At a time different from that in step S101, the wind speed is measured by using an anemometer and the wind direction is measured by using a wind vane, and when the wind speed and the wind direction are the same as those in step S101, the sensors at each measuring point are controlled to collect strain response data again, which is referred to as second strain response data. The specific implementation process of step S102 is similar to that of step S101, which will not be described here. The second strain statistical moment value is the data of the net shell structure after damage.

[0074] The second strain response data is the data obtained after the net shell structure to be identified is damaged, and the damage conditions are set according to three different types of members, i.e., upper chord members, lower chord members and web members. In one type of member, the members at different positions in the monitoring area are damaged (the simulation of member damage in the present application is simulated by removing the members), and part of the members in other monitoring areas are also damaged for comparative analysis.

[0075] In an optional embodiment of the present application, in order to accurately identify the damage and avoid irrelevant signals affecting the damage identification accuracy, the second strain response data needs to be filtered to obtain filtered second strain response data, wherein the filtered second strain response data is strain response data mainly in the form of a first-order frequency signal; then, the second strain statistical moment value is calculated according to the filtered second strain response data, and the second strain statistical moment value is a fourth-order strain statistical moment value, and the order is 4.

[0076] In step S103, the strain statistical moment normalized difference value of each measuring point is calculated according to the first strain statistical moment value and the second strain statistical moment value.

[0077] For any measuring point, the first strain statistical moment value is calculated by using step S101, and the second strain statistical moment value is calculated by using step S102; then, the strain statistical moment normalized difference value of the measuring point is calculated according to the first strain statistical moment value and the second strain statistical moment value. Here, the strain statistical moment normalized difference value is calculated in order to eliminate the dimensional and order differences, convert the difference between the first strain statistical moment value (in the undamaged state) and the second strain statistical moment value (in the damaged working condition) into a relatively comparable quantitative index, and avoid the problem that the absolute difference value cannot reflect the real relative change due to the different absolute values of the statistical moments of different measuring points.

[0078] In an optional embodiment of the present application, the strain statistical moment normalized difference value of any measuring point can be calculated by using the following method:

[0079] The strain statistical moment normalized difference value of any measuring point is calculated by using the following formula:

[0080]

[0081] Wherein, D is the strain statistical moment normalized difference value of a measuring point at different time under the condition that the wind speed and direction are unchanged, M1 is the first strain statistical moment value, M2 is the second strain statistical moment value,

[0082] In step S104, for any monitoring area, the L2 norm of the monitoring area is obtained by performing L2 norm calculation according to the strain statistical moment normalized difference values of all measuring points in the monitoring area, and whether the monitoring area has damage is judged according to the L2 norm.

[0083] The L2 norm (also known as the Euclidean norm) refers to converting the normalized difference values of n measuring points (forming an n-dimensional vector) into a single numerical value, quantifying the'modulus' of the vector. The greater the modulus, the more significant the overall difference of the measuring points in the monitoring area, and the higher the potential damage risk.

[0084] Specifically, the L2 norm of any monitoring area can be calculated by using the following formula:

[0085]

[0086] D is the strain statistical moment standardization difference of a monitoring point at different times under the condition that the wind speed and direction are constant, and L2 is the L2 norm of all monitoring points in a monitoring area.

[0087] Then, according to the L2 norm of each monitoring area, it is judged whether the monitoring area is damaged or not. For example, the L2 norm threshold is set in advance, which is the core basis for distinguishing between normal state and damage state. The L2 norm threshold can be determined based on the non-damage baseline method, the finite element simulation method and the engineering specification method. Then, the L2 norm corresponding to any monitoring area is compared with the preset L2 norm threshold to determine whether the L2 norm is greater than or equal to the preset L2 norm threshold. If yes, it is determined that the monitoring area is damaged. If not, it is determined that the monitoring area is not damaged.

[0088] Specifically, after the strain statistical moment standardization difference of each monitoring point is calculated according to step S103, and the L2 norm of any monitoring area is calculated according to step S104, a column chart can be drawn to determine whether the monitoring area is damaged or not by the size of the L2 norm.

[0089] 1 Theoretical analysis:

[0090] The existing related papers have deduced the relationship between the motion equation of a discrete multi-degree-of-freedom system under the excitation of fluctuating wind load, the structural strain response and the structural stiffness. Finally, the result is that if the structural stiffness decreases, i.e. the structure is damaged, the modal parameters of the structure change, thereby affecting the strain statistical moment value of the structure, so the change of the strain statistical moment value can be used to judge whether the regional damage of the reticulated shell structure occurs.

[0091] And existing studies have shown that different order statistical moments have an impact on damage identification efficiency and accuracy. The higher the order, the more sensitive the statistical moment index to damage, but the increase of the order will lead to the decrease of the stability of the index, i.e. it is easy to be affected by noise. Considering the sensitivity and stability, finally the fourth-order strain statistical moment data is selected for analysis, i.e. the fourth-order strain statistical moment value is calculated.

[0092] 2 Numerical simulation:

[0093] 2.1 Introduction of reticulated shell finite element model

[0094] Based on the actual dry coal shed structure drawing, a reticulated shell structure dynamic numerical model is established by using ANSYS. The model three views are shown in Figure 2. The model is 200m long, 100m wide and 35m high. The reticulated shell structure type is a three-center cylindrical double-layer positive four-corner pyramid cylindrical reticulated shell. The steel type of the reticulated shell structure is selected according to the structure drawing. The elastic modulus E=2.06×10 5MPa, density p = 7850 kg / m 3 The model is modeled by bar elements, and the external excitation is simulated by the harmonic superposition method to simulate the wind load. The basic wind pressure in this area is 0.65 KN / m 2 , and the ground roughness is B type. After obtaining the wind load, it is applied to the model node.

[0095] 2.2 Numerical checking

[0096] 2.2.1 Sensor layout

[0097] As shown in Figure 3 , the latticed shell structure model is biaxially symmetrical, and the internal force of the lower chord bar is large, so the lower chord bar is divided into four monitoring parts, and one part is taken for subsequent analysis. Further, one monitoring part is divided into three monitoring regions, and the measurement point arrangement of each monitoring region is as shown in Figure 3 , in order to collect as much information as possible about the strain changes of the entire region, four measurement points are evenly arranged in a region.

[0098] 2.2.2 Numerical example of damage identification

[0099] To verify the applicability of the present application, and considering the environmental noise interference that may occur in actual engineering, the response signal of the first order frequency of each monitoring point is analyzed based on the foregoing theory. First, calculate the strain statistical moment value of each monitoring point of the latticed shell structure under the condition of no damage, and set this value as the initial value. Under the condition that the wind load does not change, remove the bar on the latticed shell to simulate damage, and again obtain the strain statistical moment value of the monitoring point. Calculate the standardized difference value of each monitoring point with the initial value, and finally calculate the L2 norm of all monitoring points. Draw a column chart to determine whether there is damage in the monitoring region by the size of the L2 norm.

[0100] According to the operation steps, set the damage in the monitoring region, and the working conditions are shown in Table 1. Set the damage not in the monitoring region, and the working conditions are shown in Table 2. Set the damage in the same position of different regions for comparison, and the working conditions are shown in Table 3.

[0101] Table 1 Numerical simulation working condition detail table (damage in monitoring region)

[0102]

[0103] Table 2 Numerical simulation working condition detail table (damage not in monitoring region)

[0104]

[0105] Table 3 Numerical simulation working condition detail table (damage comparison group)

[0106]

[0107] (1) Monitoring area damage

[0108] ① Top chord member

[0109] As Figures 5A-5D shown in the monitoring area within the top chord member damage, each monitoring point D and L2 norm value, from 5A can be seen monitoring area unit 169 damage, 3 measuring point D value is larger, the remaining three measuring points D value is much smaller than the 3 measuring point, the L2 norm of four measuring points can be seen that the L2 norm value of the monitoring area is larger, in the case of no noise interference is 1.23. The theoretical part has explained that the structural damage will lead to the change of strain statistical moment value, that is, the change of D value and L2 norm, through the column chart, it can be obviously found that when the 169 unit is damaged, the L2 norm value of the monitoring area is larger, which shows that the damage index successfully identifies that the region exists damage. Further, under the influence of a certain noise, the D value of each measuring point and the L2 norm change is small, and the damage of the region can still be judged by the size of the L2 norm value. Figure 5B The column chart of unit 174 damage identification can be seen that when the 174 unit is damaged, the D value of 1 and 3 measuring points is larger, and the finally obtained L2 norm is larger, which still identifies that the monitoring area is damaged, wherein the four measuring points are greatly affected by the noise, but the final L2 norm index is less affected by the noise, which shows that the index has certain noise resistance. Figure 5C and Figure 5D The column chart also shows that the monitoring area unit is damaged, which can be reflected by the size of the L2 norm value, and is less affected by the noise.

[0110] ② Bottom chord member

[0111] As Figures 5E-5H shown in the monitoring area within the bottom chord member damage, the identification result diagram of the monitoring area bottom chord member damage. From Figures 5E-5H it can be found that when the bottom chord member unit is damaged, the L2 norm value can still be used to judge whether the monitoring area is damaged, and although part of the working condition measuring points are greatly affected by the noise, the L2 norm is less affected by the noise.

[0112] ③ Web member

[0113] As Figures 5I-5L shown in the monitoring area within the web member damage, the identification result diagram of the monitoring area web member damage. From the figure, it can be found that the web member damage is greatly affected by the noise as a whole, under the influence of 20dB noise, the change of the four measuring points including the L2 norm value is larger, but overall, the damage of the monitoring area structure can still be seen from the L2 norm, and under the influence of 30dB noise, the disturbance is smaller.

[0114] (2) Non-monitoring area damage

[0115] ①upper chord member

[0116] As Figures 6A-6D shown is the damage identification result diagram of the monitoring area when the upper chord member in the non-monitoring area is damaged. From Figure 6A it can be seen that when the unit 1880 in the monitoring area is damaged, the values of the four measuring points are very small, the L2 norm value is 0.0521, Figure 6B when the unit 1974 is damaged, the L2 norm value is 0.0519, and when the units 160 and 476 are damaged, the L2 norm values are 0.0440 and 0.0616 respectively. From the column chart, the L2 norm values of the four damage conditions are very small, and according to the foregoing theoretical analysis, it can be preliminarily judged that the damage does not occur in the monitoring area.

[0117] ②lower chord member

[0118] As Figures 6E-6H shown is the damage identification result diagram of the monitoring area when the lower chord member in the non-monitoring area is damaged. The result is consistent with the damage of the upper chord member, the L2 norm values of each damage condition are very small, and it is indicated that no damage occurs in the monitoring area.

[0119] ③web member

[0120] As Figures 6I-6L shown is the damage identification result diagram of the monitoring area when the web member in the non-monitoring area is damaged. The damage identification result is consistent with the damage of the upper chord member and the lower chord member, and since the L2 norm value is very small, it is indicated that no damage occurs in the region.

[0121] (3) Comparison diagram of damage identification results

[0122] In order to more clearly show the influence of the divided monitoring area on the damage identification result, two monitoring areas are selected, the members in the roughly same position are damaged, the monitoring area damage identification result column chart is drawn for comparison, and the result is shown in Figures 7A-7C From the figure, it can be seen that no matter which part of the reticulated shell structure the member is damaged, the damage in the monitoring area can be reflected by the L2 norm value of the four measuring points in the monitoring area, and when the member in the non-monitoring area is damaged, the L2 norm value of the four measuring points in the monitoring area is very small, and the damage cannot be identified. Therefore, the monitoring area divided by the application has a certain rationality. When the damage occurs in which area, the L2 norm value of the four measuring points in the area is larger, and the L2 norm value of the remaining monitoring area is smaller, which can preliminarily judge that the damage occurs in which area of the reticulated shell structure.

[0123] According to the method provided in the embodiments of the present application, the L2 norm value of the normalized difference of the strain statistical moments of multiple measuring points is used as a damage index, regional damage of a large-span net shell structure can be identified, the amount of manual checking is reduced, and the method is suitable for preliminary screening of structural damage. Based on the symmetry of the structure, the large-span structure is divided into multiple monitoring regions, the number of sensors is optimized, and the monitoring cost is reduced and the economic benefit is improved. The damage identification index provided in the present application has good noise resistance and is less affected by noise, and the damage identification accuracy is high. The present application improves the traditional modal index damage identification technology, significantly improves the detection sensitivity for local damage, enhances the anti-environmental noise interference ability, and has great engineering application value.

[0124] Figure 4 A flowchart of a net shell structure damage identification method based on strain statistical moments according to another embodiment of the present application is shown. As shown in Figure 4 , the sensors of each measuring point collect strain signals at a certain time under a certain wind speed and direction, the strain statistical moment values of each measuring point are calculated and recorded as initial values, the sensors of each measuring point collect strain signals again under the same wind speed and direction, the strain statistical moment values of each measuring point are calculated again, the strain statistical moment normalized difference D of each measuring point is calculated using the two strain statistical moment values, then the L2 norm of a monitoring region is calculated using the strain statistical moment normalized difference of all measuring points in the monitoring region, a column chart of D of each measuring point and the L2 norm of the monitoring region is drawn, and whether damage occurs is identified.

[0125] Figure 8 A structural block diagram of a net shell structure damage identification device based on strain statistical moments according to an embodiment of the present application is shown. The preset members of the net shell structure to be identified are divided into a preset number of monitoring regions, and multiple sensors are arranged on each monitoring region as measuring points; as shown in Figure 8 , the device comprises:

[0126] The acquisition module 801 is adapted to acquire first strain response data collected by the sensors on each measuring point under a preset acquisition time wind speed and direction; and acquire second strain response data collected again by the sensors on each measuring point under the same wind speed and direction;

[0127] The first calculation module 802 is adapted to calculate first strain statistical moment values according to the first strain response data; and calculate second strain statistical moment values according to the second strain response data;

[0128] The second calculation module 803 is adapted to calculate strain statistical moment normalized difference of each measuring point according to the first strain statistical moment values and the second strain statistical moment values;

[0129] The third calculation module 804 is adapted to calculate the L2 norm of any monitoring area according to the normalized difference of strain statistical moments of all measuring points in the monitoring area, to obtain the L2 norm of the monitoring area.

[0130] The judging module 805 is adapted to judge whether the monitoring area has damage according to the L2 norm.

[0131] Optionally, the second calculation module is further adapted to calculate the normalized difference of strain statistical moments of any measuring point by using the following formula:

[0132]

[0133] wherein D is the normalized difference of strain statistical moments of a measuring point at different time instants under the condition that the wind speed and direction are constant, M1 is the first strain statistical moment value, M2 is the second strain statistical moment value,

[0134] Optionally, the third calculation module is further adapted to calculate the L2 norm of any monitoring area by using the following formula:

[0135]

[0136] D is the normalized difference of strain statistical moments of a measuring point at different time instants under the condition that the wind speed and direction are constant, and L2 is the L2 norm of all measuring points in a monitoring area.

[0137] Optionally, the judging module is further adapted to judge whether the L2 norm is greater than or equal to a preset L2 norm threshold value.

[0138] If yes, it is determined that the monitoring area has damage; if no, it is determined that the monitoring area has no damage.

[0139] Optionally, the device further comprises a filtering module adapted to perform filtering processing on the first strain response data to obtain filtered first strain response data, wherein the filtered first strain response data is strain response data mainly in a first-order frequency signal; and perform filtering processing on the second strain response data to obtain filtered second strain response data, wherein the filtered second strain response data is strain response data mainly in a first-order frequency signal.

[0140] The first calculation module is further adapted to calculate the first strain statistical moment value according to the filtered first strain response data, and calculate the second strain statistical moment value according to the filtered second strain response data.

[0141] Optionally, the preset rod member is a lower chord rod member, and the number of sensors is 4.

[0142] The above description of each module refers to the corresponding description in the method embodiment, which will not be repeated here.

[0143] The device provided by the embodiment of the application uses the L2 norm value of the normalized difference of the strain statistical moments of multiple measuring points as a damage index, can identify regional damage of a large-span net shell structure, reduces the amount of manual checking, and is suitable for early screening of structural damage. Based on the symmetry of the structure, the large-span structure is divided into multiple monitoring regions, the number of sensors is optimized, and the monitoring cost is reduced and the economic benefit is improved. The damage identification index provided by the application has good noise resistance, is less affected by noise, and has high damage identification accuracy. The application improves the traditional modal index damage identification technology, significantly improves the detection sensitivity for local damage, enhances the anti-environmental noise interference capability, and has great engineering application value.

[0144] The embodiment of the application provides a nonvolatile computer storage medium, and the computer storage medium stores at least one executable instruction or computer program.

[0145] The embodiment of the application provides a computer program product, and the computer program product includes at least one executable instruction or computer program.

[0146] Figure 9 The structure schematic diagram of the computing device embodiment of the application is shown, and the specific implementation of the computing device is not limited in the specific embodiment of the application.

[0147] As shown in the figure, the computing device can include a processor 902, a communications interface 904, a memory 906, and a communications bus 908. Figure 9

[0148] The processor 902, the communications interface 904, and the memory 906 complete mutual communication through the communications bus 908. The communications interface 904 is used for communicating with network elements such as clients or other servers. The processor 902 is used for executing the program 910, and specifically can execute the related steps in the above-mentioned damage identification method for a net shell structure based on strain statistical moments of the computing device.

[0149] Specifically, the program 910 can include program code including computer operation instructions.

[0150] ​The processor 902 can be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to perform the operations of the embodiments of the application. The computing device can include one or more processors of the same type or different types of processors, such as one or more CPUs and one or more ASICs.

[0151] The memory 906 is configured to store the program 910. The memory 906 can include a high-speed RAM memory, and can also include a non-volatile memory, such as at least one disk memory.

[0152] The program 910 can be specifically configured to enable the processor 902 to perform the strain statistical moment-based reticulated shell structure damage identification method in any of the above method embodiments. The specific implementation of each step in the program 910 can refer to the corresponding description in the corresponding step and unit in the above strain statistical moment-based reticulated shell structure damage identification embodiments, which will not be described here. It can be clearly understood by those skilled in the art that, for the convenience and brevity of description, the specific working process of the above-described devices and modules can refer to the corresponding process description in the above method embodiments, which will not be described here.

[0153] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems can be used with these teachings, depending on the implementation. Those skilled in the art will recognize that structures required to construct such systems are apparent from the description above. In addition, the embodiments of the application are not directed to any particular programming language. It will be appreciated that a variety of programming languages can be used to implement the teachings of the application described herein, and that the above description of a specific language is provided merely for the best mode of the embodiments of the application.

[0154] In the specification provided herein, a large number of specific details are described. However, it can be understood that the embodiments of the application can be practiced without these specific details. In some examples, well-known methods, structures and techniques are not shown in detail in order not to obscure the understanding of the specification.

[0155] Similarly, it is to be understood that the embodiments of the application can sometimes alternately be termed as a system, a method, a device, a process or a procedure, depending on the particular context in which they are used. Accordingly, the terms "device", "method", "process", "procedure", "system", and the like, are not to be taken literally, but are employed in certain instances herein for the convenience of the reader. Hence, the terms "device", "method", "process", "procedure", "system", and the like, are to be interpreted in accordance with their broadest reasonable interpretation, as understood by those skilled in the art. Additionally, it is to be understood that the embodiments of the application can be one of several preferred aspects of the applications, and that each of the aspects can represent a single application or several applications that were developed in dependence

[0156] Those skilled in the art will appreciate that the modules in the apparatuses in the embodiments can be adapted and placed in one or more apparatuses other than the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and further can be divided into more sub-modules or sub-units or sub-components. Any combination of all the features disclosed in the specification (including the accompanying claims, abstract and drawings), and any method or of the apparatuses so disclosed, can be taken, except for the combinations of at least some features and / or processes are mutually exclusive, unless specifically stated otherwise. Each feature disclosed in the specification (including the accompanying claims, abstract and drawings) can be replaced by alternative features serving the same, equivalent or similar purpose, unless specifically stated otherwise.

[0157] Further, those skilled in the art will appreciate that a combination of features of different embodiments can mean that such combination is within the scope of the embodiments of the application and forms a different embodiment. For example, in the following claims, any of the claimed embodiments can be used in any combination. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0158] The various component embodiments of the present application can be implemented in hardware, or as software modules running in one or more processors, or in combinations thereof. Skilled persons should appreciate that a microprocessor or a digital signal processor (DSP) can be used to implement some or all of the functions of some or all of the components according to some or all of the embodiments of the present application in practice. The embodiments of the present application can also be implemented as a device or apparatus program (for example, a computer program and a computer program product) for performing part or all of the methods described herein. The program implementing the embodiments of the present application can be stored in a computer readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

[0159] It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of both hardware and software, and any combination thereof. In a unit claim, several devices can be listed with a conjunction like 'or', but it is to be understood that each of these devices can be implemented by its own hardware item. The use of the word 'at least' followed by a list of one or more members does not preclude the existence of additional such members. The word 'first' or'second' does not preclude the existence of additional such members.

Claims

1. A method for identifying damage to a reticulated shell structure based on strain statistical moments, wherein a preset member of the reticulated shell structure to be identified is divided into a preset number of monitoring areas, and multiple sensors are arranged as measuring points in each monitoring area; The method includes: The first strain response data collected by the sensors at each measuring point at the preset sampling time is obtained, and the first strain statistical moment value is calculated based on the first strain response data. The second strain response data collected again by the sensors at each measuring point under the same wind speed and wind direction is obtained, and the second strain statistical moment value is calculated based on the second strain response data. Calculate the standardized difference of strain statistical moments at each measuring point based on the first strain statistical moment value and the second strain statistical moment value; For any monitoring area, the L2 norm is calculated based on the standardized difference of the strain statistical moments of all measuring points within the monitoring area to obtain the L2 norm of the monitoring area. The presence of damage in the monitoring area is then determined based on the L2 norm.

2. The method according to claim 1, wherein, The step of calculating the standardized difference of strain statistical moments at each measuring point based on the first strain statistical moment value and the second strain statistical moment value further includes: The standardized deviation of the strain statistical moments at any measuring point is calculated using the following formula: Where D is the standardized difference of the strain statistical moments at different times under constant wind speed and direction at a measuring point, M1 is the first strain statistical moment value, and M2 is the second strain statistical moment value.

3. The method according to claim 1 or 2, wherein, The step of calculating the L2 norm of any monitoring area based on the standardized differences of all measuring points within the monitoring area further includes: The L2 norm of any monitored area can be calculated using the following formula: D represents the standardized difference of the strain statistical moments at different times for a measuring point under constant wind speed and direction, and L2 represents the L2 norm of all measuring points in a monitoring area.

4. The method according to claim 1 or 2, wherein, The step of determining whether damage exists in the monitored area based on the L2 norm further includes: Determine whether the L2 norm is greater than or equal to a preset L2 norm threshold; If yes, then it is determined that the monitored area is damaged; if no, then it is determined that the monitored area is not damaged.

5. The method according to claim 1 or 2, wherein, Before calculating the first strain statistical moment value based on the first strain response data, the method further includes: filtering the first strain response data to obtain filtered first strain response data, wherein the filtered first strain response data is strain response data dominated by first-order frequency signals. The step of calculating the first strain statistical moment value based on the first strain response data further includes: The first strain statistical moment value is calculated based on the filtered first strain response data; Before calculating the second strain statistical moment value based on the second strain response data, the method further includes: filtering the second strain response data to obtain filtered second strain response data, wherein the filtered second strain response data is strain response data dominated by first-order frequency signals; The step of calculating the second strain statistical moment value based on the second strain response data further includes: The second strain statistical moment value is calculated based on the filtered second strain response data.

6. The method according to claim 1 or 2, wherein, The preset member is the lower chord member, and the number of sensors is 4.

7. A damage identification device for reticulated shell structures based on strain statistical moments, wherein a preset member of the reticulated shell structure to be identified is divided into a preset number of monitoring areas, and multiple sensors are arranged as measuring points in each monitoring area; The device includes: The acquisition module is adapted to acquire the first strain response data collected by the sensors at each measuring point under the wind speed and wind direction at a preset acquisition time; and to acquire the second strain response data collected again by the sensors at each measuring point under the same wind speed and wind direction. The first calculation module is adapted to calculate a first strain statistical moment value based on the first strain response data; and to calculate a second strain statistical moment value based on the second strain response data. The second calculation module is adapted to calculate the standardized difference of strain statistical moments at each measuring point based on the first strain statistical moment value and the second strain statistical moment value. The third calculation module is adapted to calculate the L2 norm of any monitoring area based on the standardized difference of the strain statistical moments of all measuring points in the monitoring area; The judgment module is adapted to determine whether there is damage in the monitoring area based on the L2 norm.

8. A computing device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the method for identifying damage in reticulated shell structures based on strain statistical moments as described in any one of claims 1-6.

9. A computer storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the method for identifying damage to reticulated shell structures based on strain statistical moments as described in any one of claims 1-6.

10. A computer program product comprising at least one executable instruction that causes a processor to perform an operation corresponding to the method for identifying damage in reticulated shell structures based on strain statistical moments as described in any one of claims 1-6.

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