Seismic test response spectrum identification method, seismic capacity analysis method and equipment for electromechanical equipment

Abstract

The present invention relates to a method for identifying a response spectrum of a seismic test, and a method and device for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant. In order to solve the problems that the prior art cannot be customized, still requires a large amount of manual spectrum reading, has poor spectrum reading accuracy, and cannot be directly applied to subsequent vulnerability calculations; the method identifies the characteristics of the response spectrum curve of the seismic test, separates the response spectrum curve from the background grid, associates the identified response spectrum image with an adaptive coordinate axis network, automatically identifies multiple peak acceleration values ​​and corresponding frequencies that meet the conditions in the original response spectrum, automatically identifies key frequencies and acceleration values, and provides data input for subsequent response spectrum peak clipping processing. The present invention can effectively improve the processing efficiency and accuracy of the original response spectrum in the vulnerability analysis of electromechanical equipment, and can be widely used in the vulnerability analysis of electromechanical equipment related to earthquake PSA in nuclear power plants.

Description

Technical Field

[0001] The present invention belongs to the technology of analyzing the seismic capacity of electromechanical equipment, and specifically relates to a method for identifying a seismic test response spectrum, a method for analyzing the seismic capacity of electromechanical equipment and a device. Background Art

[0002] The seismic capacity analysis of electromechanical equipment is the process of evaluating the seismic vulnerability of electromechanical equipment in nuclear power plants. It is a key link in the evaluation of weak links in seismic design and an important part of the probabilistic safety analysis of the entire plant. Due to its own characteristics, the seismic performance of electromechanical equipment is often verified through seismic tests. When conducting seismic capacity analysis of electromechanical equipment, it is necessary to combine the test spectrum (TRS) used during the seismic test of the equipment, read the seismic acceleration value of each frequency point during the seismic test, and compare it with the corresponding acceleration value in the seismic requirement spectrum (RRS). By identifying the key frequencies and performing multiple calculations and iterations, the key frequency points of the equipment and its seismic capacity values ​​can be finally determined to complete the evaluation of the seismic performance of the equipment.

[0003] The seismic test spectra of equipment are mostly recorded in paper or electronic files in the form of pictures. When performing such calculations, a large amount of manual spectrum reading is usually required to manually record the acceleration values ​​of different frequency points and use them for subsequent calculations. During the iteration process, since the frequency points of concern may change, it is often necessary to read the spectrum repeatedly for the frequency bands of focus. The workload of spectrum reading is large, and the reading accuracy is poor. Manually recording the results is not conducive to storage and reuse, and is not conducive to automatic calculation with the help of software. Traditional image recognition software is mostly based on conventional charts. The recognition rate of seismic test spectra that usually use logarithmic coordinates and have more interference information is not high, and the read values ​​cannot correspond to the frequency points of the seismic requirement spectrum, and it is impossible to compare TRS and RRS, and it is impossible to directly perform subsequent vulnerability calculations.

[0004] In traditional software recognition, it is impossible to add image recognition function for a specific frequency; secondly, when using existing mathematical graphics analysis software, in the process of extracting curve features and separating background grids and curves, the curve and the coordinate axis grid need to be clearly distinguished, and the axis grid of the seismic test spectrum is dense, highly superimposed with the response spectrum curve, the axis grid color is the same as the curve color, and there are many interference items, making it difficult to achieve a good recognition effect. In addition, due to the variety of types of seismic equipment in nuclear power plants, the time of seismic tests, and the actual laboratories conducting seismic tests are different, the response spectra provided by laboratories at different times, in different countries and regions are often quite different, and the formats of the test response spectra are quite different. Existing image recognition software cannot solve this problem.

[0005] In addition, the existing mathematical graphics analysis software can only generate a coordinate system according to the type of coordinate axis during the image recognition process. During the image recognition process, it can only recognize the image according to the established image recognition density. It cannot adaptively modify or adjust the image recognition points according to actual calculation needs. It cannot meet the reading requirements for specific frequency points in the process of calculating the vulnerability of electromechanical equipment in nuclear power plants. It can only obtain the acceleration value of the frequency point of concern through the initial reading and multi-frequency point interpolation calculation.

[0006] Moreover, existing technical means cannot provide a full-process solution and cannot realize the identification, storage, seismic analysis and result reuse of test response spectra. Since the same set of equipment may be used in different nuclear power plants or different rooms in the same nuclear power plant, the reuse of test spectrum reading results is required to be high, and existing technical means cannot provide the reuse function, resulting in duplication of work when analyzing the same type of equipment in multiple nuclear power plants or plants. Summary of the invention

[0007] The purpose of the present invention is to provide a method for automatically identifying and storing seismic test response spectra and a method and device for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant in order to address the problems existing in the current process of analyzing the seismic capacity of electromechanical equipment. The method and device can adaptively generate a frequency coordinate system and automatically read the seismic test acceleration values ​​in a sensitive frequency band at a high density according to demand, store the read results in a structured form, and realize digital conversion and processing of test response spectra reused in multiple nuclear power projects.

[0008] The technical solution of the present invention is as follows: A method for identifying a seismic test response spectrum comprises the following steps:

[0009] Step 1: for the response spectrum image to be identified, identify the characteristics of the seismic test response spectrum curve, and separate the response spectrum curve from the background grid through the obtained curve characteristics;

[0010] Step 2: Generate an adaptive coordinate axis grid for key frequency points, associate the identified response spectrum image with the coordinate axis grid, and realize automatic reading of key readings;

[0011] Step three, storing the automatically read data.

[0012] Further, in the above-mentioned seismic test response spectrum identification method, identifying the characteristics of the seismic test response spectrum curve in step 1 includes identifying the response spectrum curve, the coordinate system and the interference curve.

[0013] Furthermore, in step one, for the response spectrum image to be identified, the characteristics of the seismic test response spectrum curve are identified by coloring, the lines depicted with different colors are identified as the response spectrum curve, and the lines of the original colors are identified as the axis of the axis grid; the response spectrum curve and the axis of the axis grid are distinguished to achieve the separation of the response spectrum curve and the background grid.

[0014] Furthermore, in the seismic test response spectrum identification method described above, in step 2, the coordinate division of the coordinate axis network is set according to the peaks on the seismic requirement spectrum or the troughs on the test acceleration spectrum to determine the key frequency points; or the key frequency points are set according to the characteristics of the equipment itself.

[0015] Furthermore, in the above-mentioned seismic test response spectrum identification method, the key frequency points described in step 2 are determined based on the key frequency points in the seismic test requirement spectrum.

[0016] Furthermore, in the above-mentioned seismic test response spectrum identification method, in step 2, according to the key coordinate division input by the user, the axis corresponding to the division value is drawn into the coordinate axis grid to form encrypted coordinates.

[0017] Furthermore, in the above-mentioned seismic test response spectrum identification method, in step 2, a continuous line is drawn in the coordinate system according to the response spectrum image, and each response spectrum curve corresponds to a complete continuous segment line; and the coordinate values ​​of the points on the continuous segment line are extracted in sequence.

[0018] Furthermore, in the above-mentioned seismic test response spectrum identification method, in step three, the read seismic test response spectrum data are stored separately according to the equipment type, manufacturer, and model, and corresponding indexes are established.

[0019] A method for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant uses the seismic test response spectrum identification method as described above to obtain seismic test response spectrum data, and combines the seismic test requirement spectrum data to evaluate the seismic vulnerability of the electromechanical equipment, and determines the seismic capacity of the electromechanical equipment through the vulnerability evaluation results.

[0020] Furthermore, in the above-mentioned method for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant, the method for evaluating the seismic vulnerability of electromechanical equipment is to read the seismic acceleration value of each frequency point during the seismic test in combination with the identified equipment seismic test response spectrum, and compare it with the corresponding acceleration value in the seismic test requirement spectrum, and determine the key frequency points of the equipment and its seismic capacity values ​​by identifying the key frequencies, performing calculations and iterations, thereby completing the evaluation of the seismic performance of the equipment.

[0021] A seismic test response spectrum identification device, comprising:

[0022] A response spectrum curve feature recognition module is used to identify the characteristics of the seismic test response spectrum curve for the response spectrum image to be identified, and separate the response spectrum curve from the background grid through the obtained curve characteristics;

[0023] A coordinate axis network generation and key reading reading module is used to generate an adaptive coordinate axis network for key frequency points, associate the identified response spectrum image with the coordinate axis network, and realize automatic reading of key readings;

[0024] The data storage module is used to store the automatically read data.

[0025] A device for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant, comprising:

[0026] A response spectrum curve feature recognition module is used to identify the characteristics of the seismic test response spectrum curve for the response spectrum image to be identified, and separate the response spectrum curve from the background grid through the obtained curve characteristics;

[0027] A coordinate axis network generation and key reading reading module is used to generate an adaptive coordinate axis network for key frequency points, associate the identified response spectrum image with the coordinate axis network, and realize automatic reading of key readings;

[0028] A data storage module, used for storing the automatically read data;

[0029] The seismic vulnerability assessment module for electromechanical equipment is used to combine the seismic test response spectrum data with the seismic test requirement spectrum data to assess the seismic vulnerability of electromechanical equipment and determine the seismic resistance of the electromechanical equipment based on the vulnerability assessment results.

[0030] The beneficial effects of the present invention are as follows:

[0031] 1. In the traditional manual image recognition, the equipment seismic test response spectrum stored in the form of pictures has become a key link restricting digital and automated design. The present invention stores the test response spectrum provided by the equipment manufacturer in a structured format for easy reading and further application without manual reading.

[0032] 2. In the process of mining the maximum margin between the seismic test spectrum and the seismic requirement spectrum, multiple iterations are required, which is achieved by repeated readings, and the efficiency is low. The present invention uses automatic calculation tools and computer software to perform seismic analysis; and the present invention improves the manual reading and software-assisted curve recognition methods of the equipment test response spectrum, which is accurate in recognition and has strong versatility. After one-time recognition, the stored response spectrum data can be used as basic data for subsequent analysis, which improves the efficiency of seismic capacity analysis of electromechanical equipment as a whole.

[0033] 3. The present invention solves the problem that in the existing manual view, in the process of extracting curve features and separating background grids and curves based on existing mathematical graphics analysis software, the curve and the coordinate axis grid need to be clearly distinguished, while the axis grid of the seismic test spectrum is dense, highly overlapped with the response spectrum curve, the axis grid color is the same as the curve color, and there are many interference items, making it difficult to achieve a good recognition effect; and the present invention can simultaneously process multiple types of nuclear power plant seismic equipment, unify the format of response spectra provided by different laboratories at different times and in different countries and regions, and solve the problem that the spectrum distinction cannot be unified.

[0034] 4. The present invention can generate a complete coordinate system according to the type of coordinate axis. During the image recognition process, it can not only recognize the image according to the established image recognition density, but also adaptively modify or adjust the image recognition points to meet the reading requirements for specific frequency points in the process of calculating the vulnerability of electromechanical equipment in nuclear power plants, and obtain the acceleration value of the frequency point of concern.

[0035] 5. The present invention can directly formulate the required spectrum through user-defined coordinate division or specific frequency points, so as to carry out the subsequent automatic recognition process of the response spectrum, solving the cumbersome process of the previous image recognition process in which the acceleration of the key frequency points of concern could not be directly read and the problem of the need for secondary calculation was solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flow chart of a method for identifying response spectra of seismic tests;

[0037] Figure 2 Draw a flow chart for coordinate identification of equipment test response spectrum;

[0038] Figure 3 is the seismic test spectrum to be identified;

[0039] Figure 4 This is a schematic diagram of the coordinate system identification result;

[0040] Figure 5 This is an example diagram of the response spectrum of the seismic test;

[0041] Figure 6 This is an example of the spectrum required for seismic testing;

[0042] Figure 7 Schematic diagram of the storage method of experimental spectrum recognition results (image storage). DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] The horizontal axis of the seismic test spectrum of electromechanical equipment in nuclear power plants is the frequency, and the vertical axis is the seismic acceleration value (for example Figure 3 ). According to the calculation requirements of the seismic vulnerability of electromechanical equipment, in the calculation process, all peaks in the test response spectrum should be accurately identified first. For example, the curve can be traversed from low to high along the horizontal axis, all the vertical coordinate peaks can be identified and marked, and the corresponding acceleration values ​​sa-peak and frequency values ​​fc can be recorded. For the frequency points that can be clipped, the response spectrum clipping calculation should also be performed. During the clipping process, it is also necessary to identify the difference (△f) between the frequency coordinates (horizontal coordinates) of the two points corresponding to 0.8 times the peak acceleration (0.8sa-peak), and further calculate the ratio of △f / fc on this basis. The peak clipping factor Cc is calculated based on the result of this ratio. The reading error of the frequency value and acceleration value of the key frequency point directly affects the correctness of the vulnerability calculation result.

[0045] Based on this calculation process, it is often necessary to read the diagram repeatedly and identify multiple times during the vulnerability calculation process. As mentioned above, the vulnerability calculation results of the electromechanical equipment in nuclear power plants are highly correlated with the acceleration values ​​at the key frequency points, so the acceleration reading work at the key frequency points is very important.

[0046] like Figure 1 As shown in the figure, the key factors in the response spectrum recognition task include three key technical elements: response spectrum curve feature extraction and background grid separation, adaptive coordinate axis grid generation and automatic reading of key frequency points, and structured storage.

[0047] 1. Response spectrum curve feature extraction and background grid separation

[0048] like Figure 5 The seismic test response spectrum to be identified shown in the drawings to be identified includes both the coordinate system and the seismic test response spectrum curve, as well as interference curves that are irrelevant to the identification task. In the identification process, the equipment response spectrum identification task is first established. In view of the characteristics of the seismic test response spectrum, such as high density of the axis network, high superposition of the response spectrum curve, the same axis network color as the curve color, and many interference items, the curve features are formed by tracing the red lines through the designed human-machine interface or manual method. By identifying the red lines in the picture as the seismic test response spectrum curve and the black lines as the axis line, the interference caused by the superposition of the curve and the axis network is reduced, the recognition of the curve features and the separation of the curve from the background grid are realized, and the digital storage of the curve features is further completed. The tracing process can be tracing the red lines with the help of the mouse, tracing the red lines with the mouse, or tracing the red lines with the help of an electronic pen (such as a computer stylus pen, etc.), or the picture can be printed out, manually traced, scanned, and then imported. Of course, it should be clear to those skilled in the art that the response spectrum curve can also be depicted in other colors with prominent colors and large contrast.

[0049] 2. Generation of adaptive coordinate axis grid and automatic reading of key frequency points

[0050] The present invention associates the determination of key frequencies in the vulnerability calculation of electromechanical equipment in nuclear power plants with the generation of a coordinate system axis network. According to the calculation requirements, a specific coordinate axis network required for the vulnerability calculation of electromechanical equipment is automatically generated, and this axis network is preset as a coordinate system preset by the program. After inserting the equipment response spectrum image, a curve is drawn by superimposing the response spectrum image with a standard coordinate template to achieve the extraction of the response spectrum. By associating the preset coordinate system with the image to be identified, the seismic test curve under the coordinate axis network of interest is automatically identified, and the direct reading of key frequency points is achieved. The specific steps are as follows:

[0051] 2.1 Automatic drawing of standardized coordinate system (process as follows Figure 2 (shown)

[0052] 1) Based on the coordinate (0, 0) as the reference origin;

[0053] 2) Determine the X-axis interval (X0-X max ), X-axis is frequency, Xmax is the maximum frequency;

[0054] 3) According to the response spectrum coordinate system rules, generate a set of X-axis values ​​(X0, X1, X2, X3...X max );

[0055] 4) Determine the Y-axis range (Y0-Y max ), the Y axis is acceleration, and Ymax is the maximum value of acceleration;

[0056] 5) According to the response spectrum coordinate system rules, generate a set of Y-axis values ​​(Y0, Y1, Y2, Y3...Y max );

[0057] 6) Take the value Y according to the Y axis n , draw horizontal line segments by line, the rule is starting point (X0,Y n ) to the end point (X max ,Y n );

[0058] 7) Take the value X according to the X axis n , draw vertical line segments by column, the rule is starting point (X n ,Y0) to the end point (X n ,Y max );

[0059] 8) Draw scales based on the values ​​of the X-axis and Y-axis, close to the starting point of the line segment.

[0060] Based on the key frequency points, the coordinate system is refined. Currently, there are two main methods (such as Figure 4 shown):

[0061] The system firstly calculates the seismic test response spectrum (such as Figure 5 ) Extract key coordinates or according to the seismic test requirements spectrum (such as Figure 6 ) to extract the key coordinate divisions, automatically generate a coordinate system based on the key divisions, and on this basis, further divide the key coordinates input by the user. For example, taking the horizontal coordinate as an example, the user can customize f1, f2..., fn, etc. as new coordinate divisions or key frequency points. The division value will be automatically drawn into the recognized and generated coordinate system in the form of a vertical axis to form an encrypted coordinate. When reading the response spectrum curve in the next step, the system will automatically include all the curve points corresponding to the horizontal and vertical coordinates involved in the encrypted coordinate system in the image recognition process during the image recognition process. Based on this coordinate system, identify the acceleration at the location of the key frequency point input by the user. Users can set the coordinate divisions or key coordinate frequency points according to their needs, such as setting according to the peaks on the seismic requirement spectrum, or setting the coordinate divisions or key frequency points according to the troughs on the test acceleration spectrum, or setting the key frequency points according to the characteristics of the equipment itself.

[0062] 2.2 Drawing the response spectrum curve

[0063] A continuous line is drawn according to the response spectrum image within the range of the coordinate system, and each response spectrum curve corresponds to a complete continuous segment line.

[0064] 2.3 Extracting curve data

[0065] Extract the coordinate values ​​of points on the continuous line in order (X n ,Y n ) as a reference value. And the frequency of the plant floor response spectrum is used as the basis to find points in the curve so that they can be used directly in the analysis.

[0066] 3. Structured Storage

[0067] According to the characteristics of vulnerability analysis of electromechanical equipment in nuclear power plants and specific functional requirements, the read seismic test spectra are stored separately according to equipment type, manufacturer, and model, and corresponding indexes are established. In subsequent analysis, data can be quickly and repeatedly called up.

[0068] The identified data can be presented in two forms: numerical and graphical, and the two can be correlated. The numerical storage (as shown in the following table) can be used for data call in the vulnerability calculation process, and the graphical form (as shown in the following table) can be used for data call in the vulnerability calculation process. Figure 7 ) provides users with a display of image recognition results, which facilitates users to compare and confirm the image recognition results. On the other hand, it also provides an operation interface for the peak clipping of the response spectrum of the fragility calculation software. The interactive storage and call of images and values ​​ensures the peak clipping of the fragility calculation.

[0069] Example table of response spectrum curve feature extraction rules

[0070]

[0071]

[0072] The identified data is stored in the form of equipment type, manufacturer and model, and the identification result is corresponding to the specific model. Compared with the traditional storage method indexed by engineering projects, this solution makes it easy to call data between different engineering projects. In the process of analyzing the seismic capacity of electromechanical equipment, if the same type of instruments are used in different projects, there is no need to identify the drawings for each project separately, which greatly reduces the workload and reduces the calculation problems caused by human errors.

[0073] Compared with the traditional manual image recognition, or the recognition based on the frequency range and interval step, and the connection or quadratic interpolation method on this basis, the acceleration after the above two methods can more accurately describe the acceleration value of the seismic test at the key frequency point, and the calculation result is more accurate; by pre-setting specific key frequency points as the premise of image recognition, by superimposing the built-in response spectrum grid, the original image is superimposed on the grid, the two curves are overlapped as much as possible, the response spectrum of the image is used as the base map, and the curve is drawn on the basis of the response spectrum axis. Finally, the standardized grid and the drawn curve are used as the recognition object to realize the recognition and digital storage of the equipment test response spectrum curve. With the help of this technology, the reading accuracy is refined to the response spectrum frequency point of concern.

[0074] The present invention improves the manual reading and software-assisted curve recognition of equipment test response spectrum, and has accurate recognition and strong versatility. It can meet the recognition requirements of seismic test response spectra provided by various types of equipment and seismic laboratories. Through the centralized database storage of the recognition curve, the recognized response spectrum data can be directly used for seismic analysis. The structured storage formed realizes the reuse of the vulnerability calculation data of electromechanical equipment in nuclear power plants, solves the problem of repeated reading in the previous calculation process, greatly reduces the workload, increases functions and improves performance, reduces costs in the process of applying equipment in nuclear power plants, and can complete accurate recognition based on computer programs. It is easy to use and greatly improves safety.

[0075] The special response spectrum curve feature extraction and background grid separation technology solves the problems of high axis grid density in the seismic test spectrum images of electromechanical equipment in nuclear power plants, high overlap with the response spectrum curve, the same axis grid color as the curve color, and many interference items. It improves the recognition ability of response spectrum curve features and is more versatile.

[0076] The recognition sampling of equipment test response spectrum can be based on adaptive and self-set coordinate axis grids, and preset basic frequency points, and automatically read and store the acceleration of the seismic test spectrum according to the requirements of specific axis grids and specific frequency points. The accuracy of response spectrum recognition is improved, and there is no need for secondary calculation after the drawing is recognized, which reduces the workload.

[0077] After one-time identification, the stored response spectrum data can be used as basic data for subsequent analysis. By storing data according to equipment type, manufacturer, and model, and establishing corresponding indexes, data can be quickly called and reused, which greatly improves the efficiency of seismic capacity analysis of electromechanical equipment.

[0078] By integrating the various previously independent links in seismic analysis, a complete process solution integrating response spectrum identification, storage, and seismic analysis methods is formed, which improves the efficiency of seismic analysis. The analysis results use a set of data to ensure the consistency of data analysis.

[0079] During the recognition process, we tried to adjust the direction of the curve, extract the curve features, and separate the background grid and curve by using color, reducing interference items, and other methods. However, it is difficult to achieve a good recognition effect in the test response spectrum, which has a high density of axis grids, is highly overlapped with the response spectrum curve, has the same axis grid color as the curve color, and has many interference items. The selection of sampling frequency points for response spectrum curve recognition is based on axis acquisition. In the process of digital fitting, the actual difference with the original image is large. Starting from the analysis plan, because the test method ultimately uses the TRS / RRS value in a certain frequency range, the sampled frequency points and the floor response spectrum are used as references, and the frequencies in all floor response spectra are taken as the union. The curve is stored after recognition based on this reference. In addition, when reusing data between nuclear power plants, the natural logarithm interpolation of the damping ratio and the double logarithm interpolation between frequencies are used to automatically establish the complete response spectrum analysis data.

[0080] After one-time identification, the stored response spectrum data can be used as basic data for subsequent analysis. By storing data according to equipment type, manufacturer, and model, and establishing corresponding indexes, data can be quickly called and reused, which greatly improves the efficiency of seismic capacity analysis of electromechanical equipment.

[0081] Notes on earthquake vulnerability calculation:

[0082] The seismic vulnerability of equipment is the conditional failure probability of the equipment under a certain earthquake motion acceleration value (such as peak ground acceleration (PGA) or spectral acceleration values ​​at different frequencies). The purpose is to estimate the ability of the equipment to withstand seismic acceleration parameters (such as PGA or other spectral acceleration). The ability of equipment to withstand seismic acceleration is a random variable and can be fully described by a probability distribution. There is uncertainty in the estimation of the parameters and exact shape of the probability distribution, and there is also uncertainty in the failure simulation of the equipment. The vulnerability assessment method uses the lognormal probability density function as the basis for modeling.

[0083] The response spectrum is a curve showing the maximum displacement response, velocity response and acceleration response of a single-particle system as the particle's natural vibration period changes during a given earthquake acceleration period. It is used to calculate the internal force and deformation of a structure under earthquake action.

[0084] The test method is one of the main methods to obtain the seismic capacity of electromechanical equipment. It can usually be calculated by using the median seismic capacity (Am) and the random logarithmic standard deviation (β R ), uncertainty logarithmic standard deviation (β U ) is used to characterize the equipment vulnerability, and its vulnerability model is as follows:

[0085]

[0086] TRS C =TRS·C T ·C I ·F ms

[0087] RRS C =RRS·C C ·D R ·AF C

[0088]

[0089]

[0090] In the above formula:

[0091] Am: median seismic resistance of the equipment;

[0092] TRSc: The test spectrum obtained after the seismic test response spectrum (TRS) is pre-processed by peak clipping / broadening;

[0093] RRSc: seismic requirement spectrum (RRS) obtained after preprocessing such as peak clipping / broadening;

[0094] F D : Broadband input spectrum device capability factor;

[0095] FRS : Structural response factor of the structure where the equipment is located;

[0096] PGA REF : peak acceleration (PGA) of the reference earthquake;

[0097] C T : Peak clipping coefficient;

[0098] C I : Capacity increase coefficient;

[0099] F ms :Multi-axis-single-axis conversion factor;

[0100] C C : Peak clipping coefficient;

[0101] D R : Demand reduction coefficient;

[0102] AF C : Cabinet magnification factor;

[0103] β R : random logarithmic standard deviation;

[0104] β U : logarithmic standard deviation of uncertainty;

[0105] Its TRSc / RRSc is the ratio of the equipment test response spectrum within its frequency range (such as 3.5Hz~100Hz) to the required response spectrum at the corresponding frequency point.

[0106] This embodiment divides the functional modules according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or software functional modules, and the final program is encapsulated and called in combination with database software. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0107] Specifically, a seismic test response spectrum identification device includes:

[0108] A response spectrum curve feature recognition module is used to identify the characteristics of the seismic test response spectrum curve for the response spectrum image to be identified, and separate the response spectrum curve from the background grid through the obtained curve characteristics;

[0109] A coordinate axis network generation and key reading reading module is used to generate an adaptive coordinate axis network for key frequency points, associate the identified response spectrum image with the coordinate axis network, and realize automatic reading of key readings;

[0110] The data storage module is used to store the automatically read data.

[0111] A device for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant, comprising:

[0112] A response spectrum curve feature recognition module is used to identify the characteristics of the seismic test response spectrum curve for the response spectrum image to be identified, and separate the response spectrum curve from the background grid through the obtained curve characteristics;

[0113] A coordinate axis network generation and key reading reading module is used to generate an adaptive coordinate axis network for key frequency points, associate the identified response spectrum image with the coordinate axis network, and realize automatic reading of key readings;

[0114] A data storage module, used for storing the automatically read data;

[0115] The seismic vulnerability assessment module for electromechanical equipment is used to combine the seismic test response spectrum data with the seismic test requirement spectrum data to assess the seismic vulnerability of electromechanical equipment and determine the seismic resistance of the electromechanical equipment based on the vulnerability assessment results.

[0116] The hardware system of the device may include a processor and memory;

[0117] The memory is used to store computer-executable instructions, the processor is connected to the memory via the bus, the processor executes the computer-executable instructions stored in the memory, and the communication device is responsible for connecting to the external network to perform data transmission and reception; the processor is connected to the memory, and the memory includes database software.

[0118] The database software is a database of SQL Server 2005 or above, and is stored in a computer-readable storage medium; the processor and the memory contain a number of instructions for enabling a personal computer, a server, or a network device to execute all or part of the steps of the method; the processor type used includes a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof; the storage medium includes a USB flash drive, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk, or an optical disk.

[0119] Specifically, the software system is carried by a central processing unit (CPU), a general processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic boxes, modules and circuits described in conjunction with the disclosure of the present invention. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of DSP and microprocessor, and the like. The communication equipment for communication between relevant personnel and users can utilize a transceiver, a transceiver circuit or a communication interface, and the like.

[0120] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the present invention may be implemented in hardware, software, firmware, or any combination thereof. When implemented using software, the functions may be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of a computer program from one place to another. The storage medium may be any available medium that a general or special-purpose computer can access.

[0121] It will be apparent to those skilled in the art that the structure of the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-restrictive in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0122] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for identifying a seismic test response spectrum comprises the following steps: Step 1: for the response spectrum image to be identified, identify the characteristics of the seismic test response spectrum curve, and separate the response spectrum curve from the background grid through the obtained curve characteristics; for the response spectrum image to be identified, identify the characteristics of the seismic test response spectrum curve by coloring, identify the lines depicting different colors as the response spectrum curve, identify the lines of the original color as the axis of the axis grid, distinguish the response spectrum curve from the axis of the axis grid, and realize the separation of the response spectrum curve from the background grid; Step 2: Generate an adaptive coordinate axis grid for the key frequency point, associate the identified response spectrum image with the coordinate axis grid, and realize automatic reading of key data; set the coordinate division of the coordinate axis grid according to the peak on the seismic requirement spectrum or the trough on the test acceleration spectrum to determine the key frequency point; or set the key frequency point according to the characteristics of the equipment itself; or the key frequency point is determined based on the key frequency point in the seismic test requirement spectrum; Step three, storing the automatically read seismic test response spectrum data.

2. The seismic test response spectrum identification method according to claim 1, characterized in that: Identifying the characteristics of the seismic test response spectrum curve in step 1 includes identifying the response spectrum curve, the coordinate system and the interference curve.

3. The method for identifying seismic test response spectrum according to claim 1, characterized in that: In step 2, according to the key coordinate division input by the user, the axis corresponding to the division value is drawn into the coordinate axis grid to form encrypted coordinates.

4. The method for identifying seismic test response spectrum according to any one of claims 1 to 3, characterized in that: In step 2, a continuous line is drawn in the coordinate system according to the response spectrum image, and each response spectrum curve corresponds to a complete continuous segment line; the coordinate values ​​of the points on the continuous segment line are extracted in sequence.

5. The method for identifying seismic test response spectrum according to claim 1, characterized in that: In step three, the read seismic test response spectrum data are stored according to equipment type, manufacturer, and model, and corresponding indexes are established.

6. A method for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant, characterized in that: The seismic test response spectrum identification method described in any one of claims 1 to 5 is used to obtain seismic test response spectrum data, and the seismic vulnerability of electromechanical equipment is evaluated in combination with the seismic test requirement spectrum data, and the seismic resistance of the electromechanical equipment is determined by the vulnerability evaluation result.

7. The method for analyzing the seismic capability of electromechanical equipment in a nuclear power plant according to claim 6, characterized in that: The method for evaluating the seismic vulnerability of electromechanical equipment is to read the seismic acceleration value of each frequency point during the seismic test in combination with the identified equipment seismic test response spectrum, and compare it with the corresponding acceleration value in the seismic test requirement spectrum. By identifying the key frequencies, performing calculations and iterations, the key frequency points of the equipment and its seismic resistance values ​​are determined to complete the evaluation of the seismic performance of the equipment.

8. A seismic test response spectrum identification device, comprising: The response spectrum curve feature recognition module is used to identify the characteristics of the seismic test response spectrum curve for the response spectrum image to be identified, and separate the response spectrum curve from the background grid through the obtained curve characteristics; for the response spectrum image to be identified, the characteristics of the seismic test response spectrum curve are identified by coloring, the lines depicting different colors are identified as the response spectrum curve, the lines of the original color are identified as the axis of the axis network, the response spectrum curve is distinguished from the axis of the axis network, and the response spectrum curve is separated from the background grid; A coordinate axis network generation and key reading reading module is used to generate an adaptive coordinate axis network for key frequency points, associate the identified response spectrum image with the coordinate axis network, and realize automatic reading of key data; set the coordinate division of the coordinate axis network according to the peak on the seismic requirement spectrum or the trough on the test acceleration spectrum to determine the key frequency point; or set the key frequency point according to the characteristics of the equipment itself; or the key frequency point is determined based on the key frequency point in the seismic test requirement spectrum; The data storage module is used to store the automatically read seismic test response spectrum data.

9. A device for analyzing the seismic capacity of electromechanical equipment in a nuclear power plant, comprising: The response spectrum curve feature recognition module is used to identify the characteristics of the seismic test response spectrum curve for the response spectrum image to be identified, and separate the response spectrum curve from the background grid through the obtained curve characteristics; for the response spectrum image to be identified, the characteristics of the seismic test response spectrum curve are identified by coloring, the lines depicting different colors are identified as the response spectrum curve, the lines of the original color are identified as the axis of the axis network, the response spectrum curve is distinguished from the axis of the axis network, and the response spectrum curve is separated from the background grid; A coordinate axis network generation and key reading reading module is used to generate an adaptive coordinate axis network for key frequency points, associate the identified response spectrum image with the coordinate axis network, and realize automatic reading of key data; set the coordinate division of the coordinate axis network according to the peak on the seismic requirement spectrum or the trough on the test acceleration spectrum to determine the key frequency point; or set the key frequency point according to the characteristics of the equipment itself; or the key frequency point is determined based on the key frequency point in the seismic test requirement spectrum; A data storage module, used for storing the automatically read seismic test response spectrum data; The electromechanical equipment seismic vulnerability assessment module is used to combine the seismic test response spectrum data with the seismic test requirement spectrum data to assess the seismic vulnerability of the electromechanical equipment and determine the seismic resistance of the electromechanical equipment based on the vulnerability assessment results.

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