Cloud computing-based water conservancy project seismic reliability prediction method and system

Abstract

The application discloses a cloud-computing-based water conservancy project anti-seismic reliability prediction method and system, relates to the technical field of water conservancy projects, and comprises the following steps: collecting state parameters of a water conservancy project structure in real time by using a data collection module; integrating and storing data by using a data integration and storage module; calculating and outputting initial response coefficients Ca and dynamic prediction coefficients Cb by using a calculation optimization module; comparing the sizes of the dynamic prediction coefficients Cb and dynamic prediction comparison coefficients Cb0; and simultaneously performing early warning by using an early warning module and calculating and outputting new seismic forces L by using the calculation optimization module new The initial response coefficients Ca and the dynamic prediction coefficients Cb are calculated and optimized, the parameters of the initial response coefficients Ca and the dynamic prediction coefficients Cb are optimized, the problems in the prior art are solved, and the accuracy, real-time performance and comprehensiveness of water conservancy project anti-seismic reliability prediction are improved by means of data integration, advanced calculation algorithms and consideration of uncertain factors.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy projects, and in particular to a method and system for predicting the seismic reliability of water conservancy projects based on cloud computing. Background Art

[0002] In the field of water conservancy projects, earthquakes are one of the natural disasters that pose a major threat to the structural safety of water conservancy projects. Accurately predicting the seismic reliability of water conservancy projects under earthquakes is crucial to ensuring the safe operation of projects and reducing disaster losses. With the development of science and technology, cloud computing technology has gradually been applied to various fields. Its powerful computing power and data storage capabilities provide new solutions for the prediction of seismic reliability of water conservancy projects.

[0003] However, the existing methods for predicting the seismic reliability of water conservancy projects are mainly based on limited monitoring data and simplified mechanical models. It is difficult to fully and accurately consider the complexity of earthquake effects and the actual status of water conservancy project structures. At the same time, the efficiency of data processing and analysis is low and cannot meet the requirements of real-time and dynamic performance. Therefore, there is a need for a cloud computing-based water conservancy project seismic reliability prediction method and system that can integrate multi-source data, use advanced algorithms for processing and prediction, and improve the accuracy and timeliness of predictions. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for predicting the seismic reliability of water conservancy projects based on cloud computing, which solves the problems raised in the above background technology.

[0005] To achieve the above objectives, the present invention provides the following cloud computing-based method for predicting the seismic reliability of water conservancy projects, which is specifically implemented in the following steps:

[0006] Step 1: Using the data collection module, the state parameters of the water conservancy project structure, including displacement and acoustic emission data, are collected in real time and transmitted to the data integration and storage module;

[0007] Step 2: Use the data integration and storage module to integrate and store data;

[0008] Step 3: Based on the integration and storage of the data integration and storage module, and using the calculation optimization module, calculate and output the initial response coefficient Ca and the dynamic prediction coefficient Cb;

[0009] Step 4: Based on the comparison between the dynamic prediction coefficient Cb and the dynamic prediction comparison coefficient Cb0, while using the early warning module to issue an early warning, the calculation optimization module is used to calculate and output the new earthquake force L. new , to optimize the prediction and calculation of the parameters of the initial response coefficient Ca and the dynamic prediction coefficient Cb;

[0010] The calculation optimization module includes a basic response prediction unit, a seismic reliability reflection unit, and an optimization adjustment unit.

[0011] Optionally, the calculation formula of the basic response prediction unit is as follows:

[0012] ;

[0013] in:

[0014] Ca is the initial response coefficient, which reflects the initial response degree of the water conservancy project structure under the action of earthquake force;

[0015] L is the earthquake force, which reflects the external force exerted by the earthquake on the structure of the water conservancy project;

[0016] G is the structural stiffness, which reflects the ability of the water conservancy project structure to resist deformation;

[0017] Z is the structural mass, which reflects the mass of the water conservancy project structure itself;

[0018] V is the acceleration due to gravity, which reflects the standard physical constant under the action of the earth's gravity and has a value of 9.8 m / s 2 ;

[0019] The structural stiffness G and structural mass Z will be measured and stored before the water conservancy project structure is put into use.

[0020] Optionally, in the initial prediction stage, the seismic force L is first calculated using the earthquake response spectrum theory in combination with the dynamic characteristics of the natural vibration period of the water conservancy project structure to calculate the equivalent horizontal seismic force on the structure under the design earthquake. The base shear method is used. For structures with a height of no more than 40m, which are mainly shear deformed and have a relatively uniform distribution of mass and stiffness along the height, the calculation formula of the seismic force L is α1Geq;

[0021] Among them, α1 is the horizontal seismic influence coefficient corresponding to the basic natural vibration period of the structure, and is obtained from the seismic response spectrum curve;

[0022] Geq is the equivalent total gravity load of the structure. The representative value of the total gravity load is taken for a single mass point, and 85% of the representative value of the total gravity load is taken for multiple mass points.

[0023] Optionally, the calculation formula reflecting the seismic reliability unit is as follows:

[0024] ;

[0025] in:

[0026] Cb is the dynamic prediction coefficient;

[0027] S is the material cumulative damage amount, S reflects the damage accumulation degree of the water conservancy structure material, and the acoustic emission monitoring technology is used to monitor the damage of the structure material in real time;

[0028] J is the material ultimate energy, J represents the energy corresponding to the ultimate strength of the water conservancy structure material, and J is the same as the structure stiffness G and the structure mass Z, which is measured and stored before the water conservancy structure is put into use;

[0029] WB is the displacement change amount, WB reflects the displacement change amount generated in the water conservancy structure in the month;

[0030] W0 is the historical average displacement change amount, W0 is calculated according to the historical monitoring data, that is, W0=(Wa-Wb) / Y;

[0031] Wa is the initial position, Wa reflects the position when the water conservancy project is just built;

[0032] Wb is the current position, Wb reflects the current real-time monitoring position of the water conservancy project;

[0033] Y is the use month, Y reflects the month that the water conservancy project has been used so far.

[0034] Optionally, the calculation formula of the provided optimization adjustment unit is as follows:

[0035] ;

[0036] Wherein:

[0037] L new is the new seismic force;

[0038] K is the adjustment coefficient, and the value range is {0-1};

[0039] Cb0 is the dynamic prediction comparison coefficient;

[0040] When Cb≥Cb0, 0<K≤1, and the prediction of the seismic reliability of the current water conservancy structure is reduced;

[0041] When Cb<Cb0, K=0, and the prediction of the seismic reliability of the current water conservancy structure is improved.

[0042] Optionally, the initial prediction stage of the water conservancy structure, that is, the new seismic force L new needs to be predicted by using ;

[0043] During the second prediction, the dynamic prediction coefficient Cb needs to be compared with the dynamic prediction coefficient Cb calculated in the first prediction. That is, the previous dynamic prediction coefficient Cb is the input value of the dynamic prediction comparison coefficient Cb0. In this way, within half a year, the dynamic prediction coefficient Cb calculated in real time needs to be compared with the previous dynamic prediction coefficient Cb.

[0044] After half a year, the maximum and minimum values ​​of the dynamic prediction coefficient Cb within half a year are removed and averaged to obtain the current dynamic prediction comparison coefficient Cb0. Each subsequent prediction and calculation of the dynamic prediction coefficient Cb will remove the maximum and minimum values ​​and average them to update the dynamic prediction comparison coefficient Cb0 in real time.

[0045] At the same time, the purpose of the present invention is to provide a cloud computing-based water conservancy project seismic reliability prediction system based on the cloud computing-based water conservancy project seismic reliability prediction method, which solves the problems raised in the above background technology.

[0046] To achieve the above objectives, the present invention provides the following cloud computing-based water conservancy project seismic reliability prediction system, including a data collection module, a data integration and storage module, a calculation optimization module, and an early warning module;

[0047] The data collection module is responsible for collecting the status parameters of the water conservancy project structure in real time;

[0048] The data integration and storage module is responsible for integrating and storing state parameters, structural stiffness G, structural mass Z, gravitational acceleration V, and material ultimate energy J;

[0049] The calculation optimization module is responsible for calculating the initial response coefficient Ca and the dynamic prediction coefficient Cb, and calculating the new earthquake force L according to the comparison between the dynamic prediction coefficient Cb and the dynamic prediction comparison coefficient Cb0. new ;

[0050] The early warning module is responsible for making predictions and early warnings based on the comparison between the dynamic prediction coefficient Cb and the dynamic prediction comparison coefficient Cb0.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. The method and system of the present invention integrate multi-source heterogeneous data such as water conservancy project design information, earthquake monitoring data, structural material damage monitoring data, and real-time structural status monitoring data, thereby providing more comprehensive and accurate input parameters, thereby improving the accuracy of predictions, and utilizing the powerful data processing capabilities of cloud computing to achieve real-time dynamic integration of data.

[0053] Second, the basic response prediction unit of the present invention comprehensively considers the effects of the earthquake force L, structural stiffness G, structural mass Z and gravity acceleration V on the initial response of the structure. The seismic reliability reflection unit further considers the effects of the material cumulative damage S and the changes in real-time monitoring data on the seismic reliability of the structure. Through nonlinear square root operations, it more accurately describes the complex relationship between various factors. Finally, by providing an optimization adjustment unit, the new earthquake force L is adjusted in real time according to the calculated dynamic prediction coefficient Cb. new , which realizes the dynamic update of the prediction results and ensures the timeliness of the prediction. In addition, the input and update of the comparison values ​​of the dynamic prediction coefficient Cb at different stages can better ensure the accuracy of the prediction.

[0054] 3. In the calculation formula, the present invention takes into account the uncertainty of structural material properties and seismic effects by introducing the parameters of material cumulative damage S, displacement change WB and historical average displacement change W0. The real-time update and dynamic change of these parameters make the prediction results more reflective of the actual situation and reduce the prediction deviation caused by ignoring uncertainty factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a flow chart of the seismic reliability prediction method for water conservancy projects;

[0056] Figure 2 This is the overall structural diagram of the seismic reliability prediction system for this water conservancy project. DETAILED DESCRIPTION

[0057] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0058] Regarding this water conservancy project seismic reliability prediction method and system, it is different from the existing water conservancy project seismic reliability prediction method and system. The existing water conservancy project seismic reliability prediction method and system have the problems of a single data source, lack of dynamic update, and ignore the uncertainty of earthquake activity and material performance factors. This algorithm unit achieves multi-source data fusion, real-time dynamic integration, dynamic prediction and update, and takes uncertainty into consideration.

[0059] For example 1, please refer to Figure 1-Figure 2 This implementation provides a cloud computing-based seismic reliability prediction method for water conservancy projects. The specific implementation steps are as follows:

[0060] Step 1: Using the data collection module, the state parameters of the water conservancy project structure, including displacement and acoustic emission data, are collected in real time and transmitted to the data integration and storage module;

[0061] Step 2: Use the data integration and storage module to integrate and store data;

[0062] Step 3: Based on the integration and storage of the data integration and storage module, and using the calculation optimization module, calculate and output the initial response coefficient Ca and the dynamic prediction coefficient Cb;

[0063] Step 4: Based on the comparison of the dynamic prediction coefficient Cb and the dynamic prediction comparison coefficient Cb0, while using the early warning module to issue an early warning, the calculation optimization module is used to calculate and output the new earthquake force L. new , in order to optimize the parameters of the prediction calculation of the initial response coefficient Ca and the dynamic prediction coefficient Cb;

[0064] Among them, the calculation optimization module includes a basic response prediction unit, a seismic reliability reflection unit, and an optimization adjustment unit.

[0065] In this embodiment, the data collection module collects data from multiple sources in real time, the preprocessing module cleans and converts data to ensure data accuracy and uniformity, the data integration and storage module integrates related data and stores it in the cloud to facilitate query and retrieval, the calculation optimization module calculates parameters and coefficients according to formulas, analyzes and predicts, and evaluates status, and cooperates with the early warning module to achieve prediction and early warning. Among them, the calculation optimization module updates data in real time and optimizes in a cycle to ensure the timeliness and accuracy of the results.

[0066] See also Figure 1-Figure 2 , the calculation formula of the basic response prediction unit is as follows:

[0067] ;

[0068] in:

[0069] Ca is the initial response coefficient, which reflects the initial response degree of the water conservancy project structure under the action of earthquake force;

[0070] L is the earthquake force, which reflects the external force exerted by the earthquake on the structure of the water conservancy project;

[0071] In the initial prediction stage of the earthquake force L, the earthquake response spectrum theory is first used, combined with the dynamic characteristics of the natural vibration period of the hydraulic engineering structure, to calculate the equivalent horizontal earthquake force on the structure under the design earthquake. The base shear method is used. For structures with a height of no more than 40m, mainly shear deformation, and relatively uniform mass and stiffness distribution along the height, the calculation formula of the earthquake force L is α1Geq;

[0072] Among them, α1 is the horizontal seismic influence coefficient corresponding to the basic natural vibration period of the structure, and is obtained from the seismic response spectrum curve;

[0073] Geq is the equivalent total gravity load of the structure, which is the representative value of the total gravity load for a single mass point and 85% of the representative value for multiple mass points;

[0074] G is the structural stiffness, which reflects the ability of the water conservancy project structure to resist deformation;

[0075] Z is the structural mass, which reflects the mass of the water conservancy project structure itself;

[0076] V is the acceleration due to gravity, which reflects the standard physical constant under the action of the earth's gravity and has a value of 9.8 m / s 2 ;

[0077] The structural stiffness G and structural mass Z will be measured and stored before the water conservancy project structure is put into use.

[0078] In this embodiment: First The calculation part obtains a measure of the initial displacement response of the hydraulic engineering structure under the action of earthquake force based on stiffness, which deforms according to Hooke's law and combines In the calculation part, L is the earthquake force and G is the structural stiffness. The division between the two can reflect the theoretical initial displacement of the structure under the action of the earthquake force. It is a basic part of calculating the initial response coefficient Ca of the structure, reflecting the influence of the earthquake force L and the structural stiffness G on the structural response.

[0079] The calculation part considers the influence of structural mass Z and gravitational acceleration V on the structural response, and introduces a correction factor related to the structural inertia. In dynamics, the structural mass Z is a measure of the inertia of an object, and the gravitational acceleration V is related to the gravity exerted on the object. Under the action of an earthquake, the inertia of the structure will affect its response. By taking the square root of the ratio of the structural mass Z to the gravitational acceleration V, a dimensionless factor related to the structural inertia can be obtained for correction. The calculation part is based on the displacement response obtained from the stiffness, and finally the initial response coefficient Ca is obtained, which reflects the initial dynamic characteristics of the structure under earthquake action;

[0080] The foundation response prediction unit comprehensively considers the effects of seismic force L, structural stiffness G, structural mass Z, and gravitational acceleration V on the initial response of water conservancy project structures, comprehensively covering multiple key factors and more accurately describing the initial dynamic characteristics of the structure under earthquake action. Moreover, each parameter in the foundation response prediction unit has a clear physical meaning and is actually measurable. This calculation method based on actual physical quantities ensures the reliability and practicality of the calculation results and avoids calculation errors caused by the use of abstract or difficult-to-measure parameters.

[0081] See also Figure 1-Figure 2 , the calculation formula reflecting the seismic reliability unit is as follows:

[0082] ;

[0083] in:

[0084] Cb is the dynamic prediction coefficient;

[0085] S is the cumulative damage of the material, which reflects the degree of damage accumulation of the structural materials of the water conservancy project. The damage of the structural materials is monitored in real time using acoustic emission monitoring technology.

[0086] J is the material limit energy, which represents the energy corresponding to the ultimate strength of the hydraulic engineering structure material. Similar to the structural stiffness G and structural mass Z, J is measured and stored before the hydraulic engineering structure is put into use.

[0087] WB is the displacement change, which reflects the displacement change of the water conservancy project structure within the month;

[0088] W0 is the historical average displacement change, which is calculated based on the historical monitoring data, that is, W0=(Wa-Wb) / Y;

[0089] Wa is the initial position, which reflects the position of the water conservancy project when it is just built;

[0090] Wb is the current location, which reflects the current real-time monitoring location of the water conservancy project;

[0091] Y is the month of use, which reflects the number of months that the water conservancy project has been used so far.

[0092] In this embodiment, first In the calculation part, the material cumulative damage S is the cumulative damage of the structural material, and the material limit energy J is the energy corresponding to the ultimate strength of the structural material. The ratio of the two is It reflects the ratio of the material damage degree to the ultimate strength. Subtracting this ratio from 1 gives the ratio of the material's residual bearing capacity, which is multiplied by the initial response coefficient Ca to correct the initial response coefficient Ca of the structure, making the prediction result more consistent with the actual situation.

[0093] In the calculation part, The ratio reflects the change ratio of the current structural state relative to the historical average state. Adding 1 to this ratio gives the structural state adjustment factor after considering real-time changes. The correction results of the calculation part are multiplied to further consider the impact of changes in real-time monitoring data on the seismic reliability of the structure, making the prediction more dynamic and accurate;

[0094] The overall calculation part can transform the comprehensive evaluation into a dynamic prediction coefficient Cb that is more in line with the actual physical meaning and prediction needs through square root extraction;

[0095] In actual water conservancy projects, as time goes by and earthquake effects accumulate, structural materials will be damaged and real-time monitoring data will continue to change. The seismic reliability unit can reflect these changes in a timely manner, improving the accuracy and timeliness of the prediction. In addition, the calculation results after comprehensive consideration of multiple factors are optimized through the nonlinear transformation of square root. This transformation can reasonably scale and adjust the influence of each factor, so that the dynamic prediction coefficient Cb is more in line with the actual physical meaning and engineering needs. Specifically, the dynamic prediction coefficient Cb obtained by square root avoids the problem of too large or too small results caused by simple multiplication of various factors, so that the dynamic prediction coefficient Cb can more intuitively reflect the seismic reliability of the structure.

[0096] See also Figure 1-Figure 2 , the calculation formula for the optimization adjustment unit is as follows:

[0097] ;

[0098] in:

[0099] L new is the new earthquake force;

[0100] K is the adjustment coefficient, and its value range is {0-1};

[0101] Cb0 is the dynamic prediction contrast coefficient;

[0102] When Cb≥Cb0, 0 <K≤1,且预测当前水利工程结构的抗震可靠性降低;

[0103] Cb <Cb0时,K=0,且预测当前水利工程结构的抗震可靠性提升。

[0104] In this embodiment, K in the optimization adjustment unit is provided as an adjustment coefficient with a value range of {0-1}, which is used to control the degree of adjustment of the dynamic prediction coefficient Cb to the seismic force. The dynamic prediction coefficient Cb reflects the current seismic reliability state of the structure. The two are multiplied to obtain an adjustment coefficient related to the seismic reliability of the structure.

[0105] In the optimization adjustment unit provided in this embodiment, when Cb≥Cb0, it indicates that the seismic reliability of the structure is reduced. Increase to get the new earthquake force L new , making subsequent calculations more conservative, which is equivalent to appropriately increasing the impact of earthquake forces while taking into account the poor current state of the structure, so as to more strictly evaluate the seismic performance of the structure. <Cb0时,保持 地震作用力L不变,避免了不必要的过度调整,这种动态调整机制使得预测过程能够根据结构的实时状态进行自适应调整,提高了预测的准确性和可靠性;

[0106] The dynamic prediction coefficient Cb of the result of the seismic reliability unit reflects the new seismic force L in the foundation response prediction unit. new This produces a cyclical effect, forming a closed-loop feedback system. As the calculation continues, the system can adjust the input parameters in a timely manner according to the latest calculation results, so that the prediction results are continuously optimized.

[0107] For example 2, please refer to Figure 1-Figure 2 , the initial prediction stage of the hydraulic engineering structure, that is, the new earthquake force L obtained by the first prediction and calculation new All must be adopted , make predictions;

[0108] During the second prediction, the dynamic prediction coefficient Cb needs to be compared with the dynamic prediction coefficient Cb calculated in the first prediction. That is, the previous dynamic prediction coefficient Cb is the input value of the dynamic prediction comparison coefficient Cb0. In this way, within half a year, the dynamic prediction coefficient Cb calculated in real time needs to be compared with the previous dynamic prediction coefficient Cb.

[0109] After half a year, the maximum and minimum values ​​of the dynamic prediction coefficient Cb within half a year are removed and averaged to obtain the current dynamic prediction comparison coefficient Cb0. Each subsequent prediction and calculation of the dynamic prediction coefficient Cb will remove the maximum and minimum values ​​and average them to update the dynamic prediction comparison coefficient Cb0 in real time.

[0110] In this embodiment, by comparing the dynamic prediction coefficient Cb at different stages, the changing trend of the seismic performance of the water conservancy project structure can be clearly captured. If the dynamic prediction coefficient Cb continues to increase, it indicates that the seismic reliability of the structure is decreasing. If the dynamic prediction coefficient Cb continues to decrease, it indicates that the structural state is improving. This understanding of the changing trend makes the prediction more in line with the actual situation.

[0111] It is worth noting that after a cyclic comparison within half a year, removing the maximum and minimum dynamic prediction coefficients Cb and taking the average value can reduce the interference of accidental factors on the prediction, making the result more representative of the true seismic performance of the structure. In addition, real-time comparison of the dynamic prediction coefficient Cb allows the system to respond promptly to changes in the structural state of the water conservancy project. Once the dynamic prediction coefficient Cb changes significantly, the seismic force L can be quickly changed based on the optimization adjustment unit to obtain the new seismic force L. new , and recalculate relevant parameters so that the prediction results can reflect the current seismic capacity of the structure in a timely manner, providing real-time and effective information for engineering decision-making. Since the environment faced by water conservancy projects is dynamically changing, seismic activities and material properties will change over time. Therefore, continuous comparison and adjustment of the dynamic prediction coefficient Cb can make the prediction model adapt to this dynamic change and accurately predict the seismic reliability of the structure under different environmental conditions;

[0112] The comparative adjustment of the dynamic prediction coefficient Cb also provides an intuitive basis for evaluating the seismic safety of water conservancy projects. When multiple comparisons show that the dynamic prediction coefficient Cb is close to and exceeds the dynamic prediction comparison coefficient Cb0, it indicates that the seismic reliability of the project is reduced and reinforcement and enhanced monitoring measures are needed. Otherwise, the existing operating status can be maintained, providing scientific guidance for project safety management.

[0113] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. The cloud computing-based seismic reliability prediction method for water conservancy projects is characterized by: The specific implementation steps are as follows: Step 1: Use the data collection module to collect the state parameters of the water conservancy project structure in real time, including displacement and acoustic emission data, and transmit them to the data integration and storage module; Step 2: Use the data integration and storage module to integrate and store the data; Step 3: Based on the integration and storage of the data integration and storage module, and use the calculation and optimization module to calculate and output the initial response coefficient Ca and the dynamic prediction coefficient Cb; Step 4: Based on the comparison of the dynamic prediction coefficient Cb and the dynamic prediction comparison coefficient Cb0, while using the early warning module to issue an early warning, the calculation optimization module is used to calculate and output the new earthquake force L. new , to optimize the calculation parameters of the initial response coefficient Ca and the dynamic prediction coefficient Cb; Among them, the calculation and optimization module includes a basic response prediction unit, a seismic reliability reflection unit, and an optimization adjustment unit; The calculation formula of the basic response prediction unit is as follows: Where: Ca is the initial response coefficient, and Ca reflects the initial response degree of the water conservancy project structure under the action of seismic force; L is the seismic action force, and L reflects the external force exerted by the earthquake on the water conservancy project structure; G is the structural stiffness, and G reflects the ability of the water conservancy project structure to resist deformation; Z is the structural mass, and Z reflects the mass size of the water conservancy project structure itself; V is the acceleration due to gravity, which reflects the standard physical constant under the action of the earth's gravity and has a value of 9.8m / s 2 ; Both the structural stiffness G and the structural mass Z will be measured and stored before the water conservancy project structure is put into use; In the initial prediction stage of the seismic action force L, first use the seismic response spectrum theory, combine the dynamic characteristics of the natural vibration period of the water conservancy project structure, calculate the equivalent horizontal seismic force received by the structure under the design earthquake action, and use the bottom shear method. For structures with a height not exceeding 40m, mainly shear deformation and relatively uniform mass and stiffness distribution along the height, the calculation formula of the seismic action force L is α1Geq; Among them, α1 is the horizontal seismic influence coefficient corresponding to the basic natural vibration period of the structure, and is obtained from the seismic response spectrum curve; Geq is the equivalent total gravity load of the structure. For a single particle, it takes the representative value of the total gravity load, and for multiple particles, it takes 85% of the representative value of the total gravity load; The calculation formula of the seismic reliability reflection unit is as follows: Where: Cb is the dynamic prediction coefficient; S is the cumulative damage amount of the material, and S reflects the cumulative damage degree of the materials of the water conservancy project structure, and the acoustic emission monitoring technology is used to monitor the damage of the structural materials in real time; J is the material limit energy, and J represents the energy corresponding to the ultimate strength of the materials of the water conservancy project structure. Similar to the structural stiffness G and the structural mass Z, it is measured and stored before the water conservancy project structure is put into use; WB is the displacement change amount, and WB reflects the displacement change amount generated by the water conservancy project structure within the current month; W0 is the historical average displacement change amount, and W0 is calculated based on historical monitoring data, that is, W0=(Wa - Wb) / Y; Wa is the initial position, and Wa reflects the position when the water conservancy project was just built; Wb is the current position, and Wb reflects the current real-time monitored position of the water conservancy project; Y is the usage month, and Y reflects the number of months that the water conservancy project has been used so far.

2. The method for predicting earthquake-resistant reliability of water conservancy projects based on cloud computing according to claim 1 is characterized in that: The calculation formula of the optimization adjustment unit is as follows: Where: L new is the new earthquake force; K is the adjustment coefficient, and the value range is {0 - 1}; Cb0 is the dynamic prediction comparison coefficient; When Cb≥Cb0, 0<K≤1, and it is predicted that the seismic reliability of the current water conservancy project structure is reduced; When Cb<Cb0, K = 0, and it is predicted that the seismic reliability of the current water conservancy project structure is improved.

3. The method for predicting earthquake-resistant reliability of water conservancy projects based on cloud computing according to claim 2 is characterized in that: The initial prediction stage of the water conservancy project structure, that is, the new earthquake force L obtained by the first prediction and calculation new All predictions need to be made using L×(1+K×Cb), Cb≥Cb0; During the second prediction, the dynamic prediction coefficient Cb needs to be compared with the dynamic prediction coefficient Cb calculated in the first prediction. That is, the previous dynamic prediction coefficient Cb is the input value of the dynamic prediction comparison coefficient Cb0. In this way, within half a year, the dynamic prediction coefficient Cb calculated in real time needs to be compared with the previous dynamic prediction coefficient Cb. After half a year, the maximum and minimum values ​​of the dynamic prediction coefficient Cb within half a year are removed and averaged to obtain the current dynamic prediction comparison coefficient Cb0. Each subsequent prediction and calculation of the dynamic prediction coefficient Cb will remove the maximum and minimum values ​​and average them to update the dynamic prediction comparison coefficient Cb0 in real time.

4. A cloud computing-based water conservancy project seismic reliability prediction system, which adopts the cloud computing-based water conservancy project seismic reliability prediction method according to any one of claims 1 to 3, characterized in that: Including data collection module, data integration and storage module, calculation optimization module, and early warning module; The data collection module is responsible for collecting the status parameters of the water conservancy project structure in real time; The data integration and storage module is responsible for integrating and storing state parameters, structural stiffness G, structural mass Z, gravitational acceleration V, and material ultimate energy J; The calculation optimization module is responsible for calculating the initial response coefficient Ca and the dynamic prediction coefficient Cb, and calculating the new earthquake force L according to the comparison between the dynamic prediction coefficient Cb and the dynamic prediction comparison coefficient Cb0. new ; The early warning module is responsible for making predictions and early warnings based on the comparison between the dynamic prediction coefficient Cb and the dynamic prediction comparison coefficient Cb0.

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