Real-time monitoring method and device for rotating stall of pump turbine under turbine operating condition

Abstract

The present invention relates to the field of fluid machinery and control technology, and discloses a real-time monitoring method and device for rotating stall of a pump turbine under turbine working conditions, the method comprising: obtaining a pump turbine model; calculating the pump turbine model through CFD fluid mechanics calculation and FEM finite element calculation to obtain a proxy model; the proxy model is used to characterize the relationship between the operating parameters of the rotating stall working condition and the stress and strain of the runner; obtaining the operating parameters and rotating stall characteristic signals of the target pump turbine; inputting the operating parameters and the rotating stall characteristic signals into the proxy model, and calculating the blade stress and strain conditions, the blade stress and strain conditions including the blade stress and strain time series and the unevenness of the blade stress and strain distribution. The technical solution provided by one or more embodiments of the present invention can solve the problem that traditional monitoring means cannot identify and warn the rotating stall phenomenon in real time.

Description

Technical Field

[0001] The invention relates to the field of fluid machinery and control technology, and in particular to a method and a device for real-time monitoring of rotational stall of a pump turbine under turbine working conditions. Background Art

[0002] The core equipment of a pumped-storage power station is a pump-turbine. Unlike a general turbine that is only used for power generation, a pump-turbine needs to have the bidirectional operation capability of a pump and a turbine. According to the changes in the grid load, it is necessary to perform more frequent operating mode conversions between power generation and pumping conditions. This complex operating condition and transition process results in unstable internal flow characteristics. Under turbine conditions and pump conditions, it will face extremely unstable flow areas in the S zone and the hump zone, respectively. Taking the S zone of the turbine condition as an example, when the pump-turbine is started and shut down under the turbine condition, the same speed can correspond to more than one (3 or four) operating points on the characteristic curve, which enables the unit to operate in any condition between these points, making it difficult to stabilize. A very unstable operating characteristic in the S zone is rotating stall. Once rotating stall occurs, the flow field near the runner and guide vanes will show obvious asymmetry in the entire circumference, with large flow rates in some flow channels and small flow rates in other flow channels. Such flow field distribution will induce strong low-frequency pressure pulsations, causing components such as the runner to be subjected to periodic alternating stress, and there is a risk of fatigue damage to important parts such as the blades, which has a great impact on the safe and stable operation of the unit.

[0003] With the development of new energy, hydropower, including pumped storage power stations, are required to play a greater role in regulating power supplies. The units will face more start and stop times, faster load changes and more frequent operating condition conversions, which makes the internal flow of the units more complex, the non-steady-state characteristics significantly enhanced, the conditions for rotating stall to occur greater, and the impact on the units greater.

[0004] For the analysis and research of rotating stall, the relevant technology mainly uses unsteady numerical calculation methods or model test methods to analyze and study the designed flow channel to determine the operating range in which the rotating stall phenomenon occurs. At present, hydropower and pumped storage power stations do not have a special monitoring system for rotating stall, and the research on rotating stall still mainly exists at the academic research and model test level.

[0005] Currently, analyzing the characteristics of the starting point of rotating stall requires a large amount of computing resources or test conditions and time cost. The following three methods are analyzed:

[0006] Unsteady numerical calculation. Existing numerical calculations are mainly aimed at the full flow channel model. It is difficult to divide the mesh in the flow channel such as the volute, runner and guide vane, and the mesh units of the entire flow channel are generally in the millions to tens of millions, which places high requirements on computer performance. In addition, rotating stall is an unsteady phenomenon with obvious dynamic characteristics. Unsteady calculations must be used to obtain its starting point, frequency and other characteristics. Even using a powerful computer takes a long time. In addition, numerical calculations can determine the flow field characteristics where rotating stall exists, but it is difficult to determine the starting point of rotating stall;

[0007] Model test. Model test can obtain more accurate information, but it requires the processing and manufacturing of proportionally reduced models, and the model manufacturing cost of pump-turbine units is relatively high. During the design stage, it is impossible to test every runner designed in the design process for a certain unit. In addition, model tests also make it difficult to identify the operating point where rotating stall occurs;

[0008] Real machine experiment. Rotating stall will have a great impact on the unit. In order to protect the safety of the unit and ensure the life of the unit, research on rotating stall will not be conducted on a real machine.

[0009] In view of this, a method for identifying the starting point of rotating stall of a pump-turbine based on numerical calculation method and theoretical analysis method is needed. Summary of the invention

[0010] In view of this, the present invention provides a real-time monitoring method and device for rotational stall of a pump turbine under turbine operating conditions, so as to solve the problem that traditional monitoring means cannot identify and warn the rotational stall phenomenon in real time.

[0011] In a first aspect, the present invention provides a method for real-time monitoring of rotating stall of a pump-turbine under turbine operating conditions, the method comprising: obtaining a pump-turbine model; calculating the pump-turbine model through CFD fluid mechanics calculation and FEM finite element calculation to obtain a proxy model; the proxy model is used to characterize the relationship between operating parameters and runner stress and strain under rotating stall conditions; obtaining operating parameters and rotating stall characteristic signals of a target pump-turbine; inputting the operating parameters and rotating stall characteristic signals into the proxy model to calculate the blade stress and strain conditions, wherein the blade stress and strain conditions include the blade stress and strain time series and the unevenness of the blade stress and strain distribution.

[0012] In an optional embodiment, the method also includes: based on the agent model, calculating the stress and strain conditions of the blades during the transition process of different operating conditions, and constructing an operation strategy library; when the stress, strain or non-uniformity exceeds a preset threshold, issuing a warning and adjusting the operation mode according to the operation strategy library.

[0013] In an optional embodiment, the proxy model is used to: generate boundary conditions for CFD calculations based on multiple operating parameters of operating conditions with a risk of rotating stall; determine the internal flow field of the runner through CFD calculations; and extract fluid-structure coupling boundary conditions corresponding to FEM calculations from the internal flow field of the runner;

[0014] The boundary conditions are used to calculate and obtain the runner stress and strain.

[0015] In some optional embodiments, the rotational stall characteristic signal includes: setting a sampling frequency, sampling the sensor signal, and identifying whether it is a rotational stall characteristic signal; when the target pump-turbine operates in a specific area, the rotational stall characteristic signal is not collected; when the target pump-turbine operates outside the specific area, the rotational stall characteristic signal is collected.

[0016] In some optional embodiments, identifying whether it is a rotating stall characteristic signal includes: performing low-frequency filtering on the rotating stall signal to obtain a low-frequency signal; performing Fourier transform on the low-frequency signal to obtain frequency domain information; based on the frequency domain information, identifying the rotating stall phenomenon; if the rotating stall phenomenon exists, the sensor signal is a rotating stall characteristic signal.

[0017] In some optional implementations, adjusting the operation mode according to the operation strategy library includes: analyzing different operation paths using the operation strategy library; determining whether there is a path for optimizing the operation mode; and adjusting the operation mode if an influencing path is found.

[0018] In a second aspect, the present invention provides a real-time monitoring device for rotating stall of a pump-turbine under turbine operating conditions, the device comprising: a model acquisition module, used to acquire a pump-turbine model; a model calculation module, used to calculate the pump-turbine model through CFD fluid mechanics calculation and FEM finite element calculation to obtain a proxy model; the proxy model is used to characterize the relationship between the operating parameters of the rotating stall condition and the stress and strain of the runner; a signal acquisition module, used to acquire the operating parameters and rotating stall characteristic signals of the target pump-turbine; a stress calculation module, used to input the operating parameters and the rotating stall characteristic signals into the proxy model to calculate the stress and strain conditions of the blades, wherein the stress and strain conditions of the blades include the stress and strain time series of the blades and the unevenness of the stress and strain distribution of the blades.

[0019] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for real-time monitoring of rotational stall of a pump turbine under turbine operating conditions of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0020] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for real-time monitoring of rotational stall of a pump turbine under turbine operating conditions according to the first aspect or any corresponding embodiment thereof.

[0021] In a fifth aspect, the present invention provides a computer program product comprising computer instructions for causing a computer to execute the method for real-time monitoring of rotational stall of a pump turbine under turbine operating conditions according to the first aspect or any corresponding embodiment thereof.

[0022] The present invention provides a real-time monitoring method and device for rotating stall of a pump-turbine under turbine working conditions. By obtaining a pump-turbine model and using CFD and FEM technology for calculation, a proxy model is generated to map the relationship between the operating parameters under rotating stall conditions and the stress and strain of the runner. By collecting the real-time operating parameters and rotating stall characteristic signals of the pump-turbine, the proxy model is input to infer the stress and strain state of the blades, and then the stress and strain time series changes and distribution uniformity of the blades are evaluated, providing a method for focusing on monitoring the potential damage part of the runner blades when the unit is in a strong non-steady state and unstable flow such as rotating stall. The use of this system can provide timely information on the stress and strain of the runner blades during the transition process, and provide effective information for operation and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 is a flow chart of a method for real-time monitoring of rotating stall of a pump turbine under turbine working conditions according to an embodiment of the present invention;

[0025] Figure 2 is a schematic diagram of sensor monitoring point locations according to an embodiment of the present invention;

[0026] Figure 3 is a structural block diagram of a device for real-time monitoring of rotating stall of a pump turbine under turbine working conditions according to an embodiment of the present invention;

[0027] Figure 4 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0029] An embodiment of the present invention provides a real-time monitoring method for rotational stall of a pump-turbine under turbine operating conditions. By comprehensively applying CFD and FEM calculations, a proxy model is established to map the relationship between operating parameters and stress and strain of runner blades, so as to achieve real-time monitoring of the rotational stall state of the pump-turbine, so as to achieve early warning and optimize operating strategies, reduce the risk of blade damage, and improve the safety and stability of unit operation.

[0030] According to an embodiment of the present invention, an embodiment of a method for real-time monitoring of rotational stall of a pump turbine under turbine operating conditions is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] In this embodiment, a method for real-time monitoring of rotational stall of a pump turbine under turbine operating conditions is provided. Figure 1 4 is a flow chart of a method for real-time monitoring of rotating stall of a pump turbine under turbine operating conditions according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0032] Step S101, obtaining a pump-turbine model.

[0033] Create a 3D model of a pump-turbine, including the geometry of all its key components, material properties, boundary conditions and initial conditions, and perform necessary model verification, so that it can truly reflect the actual pump-turbine and provide a basis for subsequent numerical calculations and analysis.

[0034] Step S102, the pump-turbine model is calculated by CFD fluid mechanics calculation and FEM finite element calculation to obtain a proxy model; the proxy model is used to characterize the relationship between the operating parameters of the rotating stall condition and the runner stress and strain.

[0035] CFD fluid dynamics calculations are used to numerically simulate the fluid flow inside the pump-turbine. Multiple operating parameters with rotating stall conditions are used as boundary conditions for CFD calculations to calculate the flow field inside the runner. The fluid-solid coupling boundary conditions calculated by FEM are extracted from the runner flow field to calculate the stress and strain of the runner. A proxy model is developed based on the calculation results of CFD and FEM. This model is a simplified mathematical representation that can quickly predict the stress and strain state of the runner under specific operating parameters.

[0036] The input variables of the proxy model are the rotating stall condition parameters, and the output variables are the runner stress and strain. The operating parameters of the rotating stall condition refer to the various parameters used to describe and control the operating state of the pump-turbine during its operation, especially under specific conditions where rotating stall may occur, including the runner inlet flow, water head, rotating stall speed, etc.

[0037] Step S103, obtaining the operating parameters and rotating stall characteristic signal of the target pump-turbine.

[0038] Sensors are used to collect key parameters of the pump-turbine during operation, such as flow, head, speed, guide vane opening, etc. The rotating stall characteristic signal refers to the signal that can characterize the phenomenon detected by a specific sensor when the rotating stall phenomenon occurs during the operation of the pump-turbine. These signals can be obtained by sensors arranged at key parts of the pump-turbine, such as the volute, movable guide vanes or the wall of the tailwater pipe, such as pressure pulsation sensors and acceleration vibration sensors.

[0039] In the embodiments of the present application, Figure 2 As shown, taking the acceleration vibration sensor signal as an example: the sensor is arranged at the best position on the movable guide vane shaft, and sensors are arranged on the movable guide vane shaft in the +X, +Y and -XY directions within the entire circumference to monitor the vibration in the z direction, and the phase difference of the monitoring points in the three directions is obtained.

[0040] Step S104, inputting the operating parameters and the rotating stall characteristic signal into the proxy model, calculating the blade stress and strain conditions, wherein the blade stress and strain conditions include the blade stress and strain time series and the unevenness of the blade stress and strain distribution.

[0041] After determining that there is rotating stall in the flow field, the pump-turbine operating parameters (such as flow, head, speed, etc.) and rotating stall characteristic signals (rotating stall speed and phase difference of monitoring points in three directions) obtained from the sensor are input into the proxy model. Through the calculation of the proxy model, the stress and strain of the runner blades are predicted under the current operating parameters and rotating stall characteristic signals. Among them, since the circumferential non-uniformity of the flow inside the runner is very strong after the rotating stall occurs, the characteristics of the flow difference parameters between each flow channel must be present. Therefore, the input parameters include the signal phase difference of the three measuring points. According to the phase difference, the stress and strain characteristics of different blades of the runner can be determined. Analyze the change trend of blade stress and strain over time, that is, the stress and strain time series. Evaluate the uniformity of the distribution of blade stress and strain on the entire runner. Non-uniformity may indicate stress concentration or excessive strain in certain areas.

[0042] The present embodiment provides a real-time monitoring method for rotating stall of a pump turbine under turbine operating conditions, which monitors operating parameters and characteristic signals in real time, uses a proxy model to predict blade stress and strain, promptly detects and warns of rotating stall, optimizes operating strategies, and improves equipment safety.

[0043] In some optional embodiments, the method for real-time monitoring of rotating stall of a pump turbine under turbine operating conditions further includes:

[0044] Step S201, based on the agent model, calculate the stress and strain of the blade during the transition process of different working conditions, and build an operation strategy library.

[0045] The transition process of different working conditions refers to the process of converting a pump-turbine from one working condition to another during operation. Using the proxy model previously calculated by CFD and FEM, the model can quickly predict the stress and strain of the runner blades under different paths during the transition process. Collect these calculation results, including the stress and strain distribution and time series changes of the blades under different working conditions. Organize the collected calculation results into a library to form an operation strategy library. This library contains the optimal operating parameters and operating steps under various working conditions to guide actual operations.

[0046] Step S202: When the stress strain or non-uniformity exceeds a preset threshold, a warning is issued and the operation mode is adjusted according to the operation strategy library.

[0047] Based on engineering experience and historical data, safety thresholds are set for the stress and strain distribution of pump-turbine blades. Sensors installed on the pump-turbine are used to monitor the stress and strain state of the blades and their uniformity of distribution in real time. The monitored data is compared with the preset threshold to evaluate whether the stress and strain level of the blades is within the safe range. Once the monitored stress and strain or the unevenness of its distribution exceeds the preset threshold, the system will automatically issue a warning to prompt the operator. While issuing a warning, the system will find and recommend appropriate operation adjustment measures based on the information in the operation strategy library. According to the recommendations provided by the system, the operator adjusts the operation mode of the pump-turbine, such as changing the flow rate, adjusting the guide vane opening, changing the speed, etc., to reduce the stress and strain level of the blades and reduce the unevenness.

[0048] The method provided in this embodiment monitors the stress-strain state of the blades in real time and compares it with the optimal operating parameters and operating steps stored in the operating strategy library. This method can guide the operating personnel to select a more optimized operating path, which helps to reduce the stress and strain on the blades during the operating condition transition process, thereby effectively reducing the accumulation of blade damage, extending the service life of the equipment, and ensuring the stable and safe operation of the pump turbine.

[0049] In some optional implementations, the proxy model in step S104 is used to:

[0050] Step a11, generating boundary conditions for CFD calculation according to operating parameters of multiple operating conditions with rotating stall risk.

[0051] In this step, the operating parameters (such as flow rate, head, speed, etc.) of multiple operating conditions that may cause rotating stall are first identified and collected to generate the boundary conditions required for CFD (computational fluid dynamics) calculations. The boundary conditions define the fluid state of the computational domain and provide the necessary input data for simulating the fluid flow inside the runner.

[0052] Step a12, determining the internal flow field of the runner through CFD calculation.

[0053] Using the boundary conditions generated in step a11, the flow field characteristics inside the runner are simulated and determined through CFD calculation.

[0054] Step a13, extracting the fluid-solid coupling boundary conditions corresponding to the FEM calculation from the internal flow field of the runner.

[0055] After the CFD calculation is completed, key information is extracted from the flow field inside the runner to form fluid-solid coupling boundary conditions corresponding to the FEM (finite element method) calculation. These boundary conditions usually include fluid dynamics acting on the runner blades, such as pressure distribution and shear force. Step a14, calculate using the boundary conditions to obtain the runner stress and strain.

[0056] Finally, the stress and strain state of the runner under these conditions is analyzed by FEM calculation using the fluid-structure interaction boundary conditions extracted from the CFD calculation. FEM calculation can predict the stress and strain of the runner blades under the action of fluid dynamics.

[0057] The method provided in this embodiment, this series of steps integrates CFD and FEM calculations, and provides a basis for monitoring and preventing rotating stall by simulating and analyzing the fluid flow and structural response of the pump-turbine under rotating stall risk conditions.

[0058] In some optional implementations, the rotating stall characteristic signal in step S103 includes:

[0059] Step b11, setting the sampling frequency, sampling the sensor signal, and identifying whether it is a rotating stall characteristic signal.

[0060] Since rotating stall is a low frequency rotating flow characteristic, it can be sampled from the sensor signal at a lower sampling frequency, 40 to 50 times the rotor rotation frequency fr.

[0061] Step b12: when the target pump-turbine operates in a specific area, the rotating stall characteristic signal is not collected.

[0062] Based on the full characteristic curve of the pump-turbine, in the unit operating area and the area of ​​extremely small guide vane opening, rotational stall will not occur inside the pump-turbine. When the unit operates in these two areas, there is no need to collect signals.

[0063] Step b13, when the target pump turbine operates outside the specific area, a rotating stall characteristic signal is collected.

[0064] Conversely, when the operating parameters of the pump turbine indicate that it is outside certain areas, which are areas with a higher risk of rotating stall, the system will start collecting rotating stall characteristic signals. These signals will be used for further analysis to monitor the occurrence of rotating stall.

[0065] The method provided in this embodiment can intelligently select when to collect the rotating stall characteristic signal, thereby ensuring the effectiveness of monitoring and improving the efficiency of data processing.

[0066] In some optional implementations, the step b11 of identifying whether it is a rotating stall characteristic signal includes:

[0067] Step c11, performing low-frequency filtering on the rotating stall signal to obtain a low-frequency signal.

[0068] Low-pass filter the sensor signals that may contain rotating stall characteristics. Since the rotating stall phenomenon is usually related to low-frequency flow characteristics, the purpose of low-pass filtering is to remove high-frequency noise and unnecessary high-frequency components in the signals, thereby highlighting the low-frequency information related to rotating stall.

[0069] Step c12: Perform Fourier transform on the low-frequency signals to obtain frequency-domain information.

[0070] Performing Fourier transform on the signals after low-pass filtering can convert the time-domain signals to the frequency domain, thereby analyzing the frequency components of the signals.

[0071] Step c13: Identify the rotating stall phenomenon based on the frequency-domain information.

[0072] After obtaining the frequency-domain information, identify the rotating stall phenomenon based on this data. This usually involves analyzing specific frequency peaks or measuring point phases in the frequency domain, which correspond to the flow characteristics of rotating stall. For example, if a low-frequency peak related to the runner rotation frequency is observed in the frequency domain, this may be a sign of rotating stall.

[0073] Step c14: If there is a rotating stall phenomenon, the sensor signal is a rotating stall characteristic signal.

[0074] Finally, if the existence of the rotating stall phenomenon is confirmed through frequency-domain analysis, then the sensor signal is considered to contain the characteristic signal of rotating stall.

[0075] For example, filter out high-frequency components above 20 times the runner rotation frequency and retain low-frequency information. Perform Fourier transform on the signals of three measuring points after filtering, calculate the frequency-domain information, and obtain the main low-frequency peak f. If f < fr, then compare the time-domain signal phases of the three measuring point positions of +X, +Y, and -X - Y, which are P0, P0 - π / (2f), and P0 - 5π / (4f) respectively, then the existence of rotating stall phenomenon in the pump-turbine can be identified.

[0076] The method provided in this embodiment can systematically process and analyze rotating stall signals, which helps to identify the rotating stall phenomenon in a timely manner.

[0077] In some alternative embodiments, the above step S202 of adjusting the operation mode according to the operation strategy library includes:

[0078] Step c11: Analyze different operation paths using the operation strategy library.

[0079] The operation strategy library contains the operation data and historical experience of the pump-turbine under different working conditions. Using this database, analyze various possible operation paths.

[0080] Step c12: Determine whether there is a path to optimize the operation mode.

[0081] After analyzing all possible operation paths, the system needs to determine whether there is a path that can optimize the current operation mode.

[0082] Step c13: if an impact path is found, the operation mode is adjusted.

[0083] If the system finds that a certain operating path may lead to performance degradation or increase the risk of rotating stall, it needs to adjust the current operating mode. This adjustment may involve changing the flow rate, adjusting the guide vane opening, optimizing the speed change rate or other control parameters to ensure that the pump turbine can operate safely and stably when transitioning to the new operating conditions.

[0084] The method provided in this embodiment can improve the intelligent level of operation and achieve more accurate and efficient management by analyzing and optimizing the operation path.

[0085] In this embodiment, a real-time monitoring device for rotating stall of a pump turbine under turbine working conditions is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0086] This embodiment provides a real-time monitoring device for rotating stall of a pump turbine under turbine operating conditions, such as Figure 3 As shown, including:

[0087] The model acquisition module 301 is used to acquire a pump-turbine model.

[0088] The model calculation module 302 is used to calculate the pump-turbine model through CFD fluid mechanics calculation and FEM finite element calculation to obtain a proxy model; the proxy model is used to characterize the relationship between the operating parameters of the rotating stall condition and the runner stress and strain.

[0089] The signal acquisition module 303 is used to acquire the operating parameters and rotating stall characteristic signal of the target pump-turbine.

[0090] The stress calculation module 304 is used to input the operating parameters and the rotating stall characteristic signal into the proxy model to calculate the blade stress and strain conditions, which include the blade stress and strain time series and the unevenness of the blade stress and strain distribution.

[0091] In some optional embodiments, the device for real-time monitoring of rotational stall of a pump turbine under turbine operating conditions further comprises:

[0092] The operation strategy library construction unit is used to calculate the stress and strain of the blades during the transition process of different working conditions based on the agent model and to construct the operation strategy library.

[0093] The operation mode adjustment unit is used to issue a warning when the stress, strain or non-uniformity exceeds a preset threshold, and adjust the operation mode according to the operation strategy library.

[0094] In some optional implementations, the stress calculation module 304 includes:

[0095] A first stress calculation unit, for generating boundary conditions for CFD calculations based on a plurality of operating parameters of operating conditions with a risk of rotating stall;

[0096] The second stress calculation unit is used to determine the internal flow field of the runner through CFD calculation;

[0097] The third stress calculation unit is used to extract the fluid-solid coupling boundary conditions corresponding to the FEM calculation from the internal flow field of the runner;

[0098] The fourth stress calculation unit is used to calculate using boundary conditions to obtain the runner stress and strain.

[0099] In some optional implementations, the signal acquisition module 303 includes:

[0100] A signal identification unit, used to set the sampling frequency, sample the sensor signal, and identify whether it is a rotating stall characteristic signal;

[0101] A first signal acquisition unit, configured to not acquire a rotating stall characteristic signal when the target pump-turbine operates in a specific area;

[0102] The second signal acquisition unit is used to collect the rotating stall characteristic signal when the target pump-turbine operates outside the specific area.

[0103] In some optional implementations, the signal recognition unit includes:

[0104] A first signal identification subunit is used to perform low-frequency filtering on the rotation stall signal to obtain a low-frequency signal;

[0105] The second signal recognition subunit is used to perform Fourier transform on the low-frequency signal to obtain frequency domain information;

[0106] A third signal identification subunit is used to identify the rotational stall phenomenon based on frequency domain information;

[0107] The fourth signal identification subunit is used to determine that if a rotational stall phenomenon exists, the sensor signal is a rotational stall characteristic signal.

[0108] In some optional implementations, the operation mode adjustment unit includes:

[0109] A first operation mode adjustment subunit is used to analyze different operation paths using an operation strategy library;

[0110] The second operation mode adjustment subunit is used to determine whether there is a path to optimize the operation mode;

[0111] The third operation mode adjustment subunit is used to adjust the operation mode if an influencing path is found.

[0112] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0113] In this embodiment, the real-time monitoring device for rotational stall of a pump-turbine under turbine operating conditions is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0114] The embodiment of the present invention also provides a computer device having the above Figure 3 The device shown is a real-time monitoring device for rotational stall of a pump turbine under turbine operating conditions.

[0115] See also Figure 4 , Figure 4 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 4 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 4 A processor 10 is taken as an example.

[0116] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0117] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0118] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0119] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0120] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 4 The example of connecting through bus is taken in the following.

[0121] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device may be a touch screen.

[0122] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0123] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0124] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for real-time monitoring of rotating stall of a pump turbine under turbine operating conditions, characterized in that: The method comprises: Get the pump-turbine model; The pump-turbine model is calculated by CFD fluid mechanics calculation and FEM finite element calculation to obtain a proxy model; the proxy model is used to characterize the relationship between the operating parameters of the rotating stall condition and the runner stress and strain; Obtaining the operating parameters and rotating stall characteristic signals of the target pump-turbine; Inputting the operating parameters and the rotating stall characteristic signal into the proxy model, calculating the blade stress and strain conditions, wherein the blade stress and strain conditions include the blade stress and strain time series and the unevenness of the blade stress and strain distribution; The inputting the operating parameter and the rotating stall characteristic signal into the agent model comprises: After determining that there is rotating stall in the flow field, the pump-turbine operating parameters and rotating stall characteristic signals obtained from the sensor are input into the proxy model; the rotating stall characteristic signal includes the rotating stall speed and the phase difference of the monitoring points in three directions; the phase difference of the monitoring points in the three directions is obtained by arranging sensors on the movable guide vane shaft in the three directions of +X, +Y and -XY within the entire circumference to monitor the vibration in the z direction.

2. The method according to claim 1, characterized in that The method further comprises: Based on the agent model, the stress and strain of the blades during the transition of different working conditions are calculated to build an operation strategy library; When the stress, strain or non-uniformity exceeds a preset threshold, a warning is issued and the operation mode is adjusted according to the operation strategy library.

3. The method according to claim 1, characterized in that The proxy model is used to: Generate boundary conditions for CFD calculations based on operating parameters for multiple operating conditions with risk of rotating stall; Determine the flow field inside the runner through the CFD calculation; Extracting fluid-solid coupling boundary conditions corresponding to FEM calculation from the internal flow field of the runner; The boundary conditions are used to perform calculations to obtain the runner stress and strain.

4. The method according to any one of claims 1 to 3, characterized in that: The rotating stall characteristic signal includes: Set the sampling frequency, sample the sensor signal, and identify whether it is a rotating stall characteristic signal; When the target pump-turbine operates in a specific area, the rotating stall characteristic signal is not collected; When the target pump-turbine operates outside a specific area, the rotating stall characteristic signal is collected.

5. The method according to claim 4, characterized in that The identifying whether it is a rotating stall characteristic signal comprises: Performing low-frequency filtering on the rotating stall characteristic signal to obtain a low-frequency signal; Performing Fourier transform on the low-frequency signal to obtain frequency domain information; Based on the frequency domain information, identifying a rotating stall phenomenon; If the rotating stall phenomenon exists, the sensor signal is a rotating stall characteristic signal.

6. The method according to claim 2, characterized in that The adjusting the operation mode according to the operation strategy library comprises: Analyzing different operation paths using the operation strategy library; Determine whether there is a path to optimize the operation mode; If an impact path is found, the operation mode will be adjusted.

7. A real-time monitoring device for rotational stall of a pump turbine under turbine operating conditions, characterized in that: The device comprises: A model acquisition module, used to acquire a pump-turbine model; A model calculation module is used to calculate the pump-turbine model through CFD fluid mechanics calculation and FEM finite element calculation to obtain a proxy model; the proxy model is used to characterize the relationship between the operating parameters of the rotating stall condition and the runner stress and strain; A signal acquisition module, used to acquire the operating parameters and rotating stall characteristic signals of the target pump-turbine; A stress calculation module, used for inputting the operating parameters and the rotating stall characteristic signal into the proxy model to calculate the blade stress and strain conditions, wherein the blade stress and strain conditions include the blade stress and strain time series and the unevenness of the blade stress and strain distribution; The stress calculation module is also used for: After determining that there is rotating stall in the flow field, the pump-turbine operating parameters and rotating stall characteristic signals obtained from the sensor are input into the proxy model; the rotating stall characteristic signal includes the rotating stall speed and the phase difference of the monitoring points in three directions; the phase difference of the monitoring points in the three directions is obtained by arranging sensors on the movable guide vane shaft in the three directions of +X, +Y and -XY within the entire circumference to monitor the vibration in the z direction.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method according to any one of claims 1 to 6.

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