Hydropower station full-space positioning monitoring method and system and storage medium

Abstract

The invention discloses a hydropower station full-space positioning monitoring method and system based on a digital twin model, and a storage medium. Hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data corresponding to a hydraulic system, a mechanical system, an electric energy system and a connection system are obtained and mapped to a digital twinborn model corresponding to the hydropower station for analysis; and obtaining a hydraulic monitoring result, a mechanical monitoring result, an electric energy monitoring result and a connection monitoring result to carry out whole-space positioning monitoring on the hydropower station. According to the method, a hydraulic system, a mechanical system, an electric energy system and a connection system of a hydropower station are subjected to full-space division, monitoring data are obtained for each divided system every preset monitoring period and mapped to a digital twin model for analysis, and related monitoring results are obtained and reflected on related positions of the digital twin model; therefore, the hydropower station can be accurately positioned and monitored in the whole space in advance.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to a method, system and storage medium for full-space positioning monitoring of a hydropower station based on a digital twin model. Background Art

[0002] A hydropower station is a key water conservancy project that realizes the conversion of water energy into electrical energy. It realizes the conversion of water energy into mechanical energy through the cooperation of the pressure water pipe and the turbine, and realizes the production of electricity using water energy by utilizing the linkage relationship between the turbine and the generator. The normal operation of a hydropower station is inseparable from the close cooperation of its various components. Failure of various components may affect the power generation efficiency of the hydropower station at the least, and may even cause the hydropower station to stop operating at a serious level. Therefore, in order to ensure the operation of the hydropower station, it is usually necessary to monitor its various components.

[0003] At present, the monitoring of components in hydropower stations is mainly achieved by setting sensors for the main components in the hydropower station, and collecting data through sensors and manual inspection. When the data collected by the sensor detects that the main component may have a fault, a prompt message is sent to the relevant personnel, who then check and verify to determine whether there is a fault. On the one hand, this monitoring method is not comprehensive, and on the other hand, it is a post-event monitoring, and in the case of many components, it is difficult to accurately determine the location of the faulty component. Therefore, how to conduct accurate and comprehensive positioning monitoring of each component in the hydropower station in advance is one of the technical problems that hydropower stations currently need to solve. Summary of the invention

[0004] The main purpose of the present invention is to provide a method, system and medium for full-space positioning monitoring of a hydropower station based on a digital twin model, aiming to solve the technical problem in the prior art of how to accurately and comprehensively position and monitor various components in a hydropower station in advance.

[0005] To achieve the above object, the present invention provides a full-space positioning monitoring method for a hydropower station based on a digital twin model, wherein the hydropower station includes a hydraulic system, a mechanical system, an electric energy system, and a connection system, and the full-space positioning monitoring method for the hydropower station includes:

[0006] At each preset monitoring period, hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data corresponding to the hydraulic system, mechanical system, electric energy system and connection system are obtained respectively;

[0007] The hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are mapped to the digital twin model corresponding to the hydropower station, and the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are analyzed based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results;

[0008] Based on the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results, the hydropower station is subjected to full-space positioning monitoring.

[0009] Preferably, the steps of analyzing the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data respectively based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results include:

[0010] Based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model, the hydraulic monitoring data is analyzed to obtain a hydraulic monitoring result;

[0011] Analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain a mechanical monitoring result;

[0012] Based on the electric energy reference data corresponding to the electric energy system in the digital twin model, analyzing the electric energy monitoring data to obtain an electric energy monitoring result;

[0013] Based on the connection reference data corresponding to the connection system in the digital twin model, the connection monitoring data is analyzed to obtain a connection monitoring result.

[0014] Preferably, the hydraulic monitoring data includes water flow data and water surface images within a preset monitoring period;

[0015] The step of analyzing the hydraulic monitoring data based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model to obtain the hydraulic monitoring results includes:

[0016] The water flow data is formed into a water flow curve within a preset monitoring period, and the water flow curve is analyzed based on the water flow reference curve in the hydraulic reference data to determine whether the water flow data is turbulent data, and generate a water flow analysis result;

[0017] Determine a similarity value between a water surface reference image in the hydraulic reference data and the water surface image, and determine whether there is impurity imaging in the water surface image according to the similarity value, and generate a water surface analysis result;

[0018] The water flow analysis result and the water surface analysis result are jointly formed into the hydraulic monitoring result.

[0019] Preferably, the mechanical monitoring data includes an impeller image of the water turbine, shutdown data within a preset monitoring period, and bearing vibration data;

[0020] The step of analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain the mechanical monitoring result includes:

[0021] Determine whether there is downtime duration data in the downtime data; if there is downtime duration data, compare the downtime duration data with the reference downtime duration in the mechanical reference data, analyze whether the downtime data belongs to the target downtime data causing the water hammer phenomenon, and generate a water hammer analysis result;

[0022] Based on the comparison and analysis between the reference impeller image in the mechanical reference data and the impeller image, determining whether the impeller of the turbine has wear and corrosion, and generating an impeller analysis result;

[0023] Based on the comparison and analysis of the reference bearing data in the mechanical reference data and the bearing vibration data, determining whether the bearing of the turbine has cracks, and generating a bearing analysis result;

[0024] The water hammer analysis result, the impeller analysis result and the bearing analysis result are jointly generated as the mechanical monitoring result.

[0025] Preferably, the electric energy monitoring data includes power generation data, temperature data and noise data of the generator in the electric energy system within a preset monitoring period;

[0026] The step of analyzing the electric energy monitoring data based on the electric energy reference data corresponding to the electric energy system in the digital twin model to obtain the electric energy monitoring result comprises:

[0027] Determining theoretical power generation data corresponding to the electric energy system based on water flow data in the hydraulic monitoring data;

[0028] Based on the operating age parameter and operating environment parameter of the generator included in the electric energy reference data, the theoretical power generation data is updated, and the theoretical temperature data and theoretical noise data of the generator are determined;

[0029] The power generation data is analyzed based on the updated theoretical power generation data, and the temperature data and noise data are analyzed based on the theoretical temperature data and the theoretical noise data, respectively, to generate a generator analysis result.

[0030] Preferably, the connection monitoring data includes connection cable images, communication data and hydraulic line pressure;

[0031] The step of analyzing the connection monitoring data based on the connection reference data corresponding to the connection system in the digital twin model to obtain the connection monitoring result includes:

[0032] Analyze the connection cable image based on the reference cable image in the connection reference data, determine whether the connection cable in the connection system has a damaged cable insulation layer, and generate a cable analysis result;

[0033] Analyze whether the communication data has abnormal delay based on the reference communication data in the connection reference data, and generate a communication analysis result;

[0034] analyzing whether the hydraulic line pressure is abnormal based on the reference hydraulic pressure in the connection reference data, and generating a pressure analysis result;

[0035] The cable analysis result, the communication analysis result and the pressure analysis result are jointly generated as a connection monitoring result.

[0036] Preferably, the step of performing full-space positioning monitoring of the hydropower station according to the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results comprises:

[0037] Determine whether there are abnormal monitoring results in the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results;

[0038] If there is an abnormal monitoring result, determine the abnormal type and abnormal location area of ​​the abnormal monitoring result, find the abnormal analysis information corresponding to the abnormal type, and add the abnormal type, abnormal location area and abnormal analysis information to the digital twin model to complete the full-space positioning monitoring of the hydropower station in the preset monitoring period;

[0039] If there is no abnormal monitoring result, a prompt message is output based on the digital twin model that the full-space positioning monitoring of the hydropower station is normal during the preset monitoring period.

[0040] Preferably, before the step of obtaining hydraulic monitoring data, mechanical monitoring data and electric energy monitoring data corresponding to the hydraulic system, mechanical system and electric energy system respectively, and connection monitoring data of the connection system at each preset monitoring period, the step includes:

[0041] Acquire the center positioning information and the boundary positioning information of the hydropower station in a first preset coordinate system corresponding to the hydropower station, and construct the center positioning information and the boundary positioning information into a digital contour twin model of the hydropower station according to a transformation relationship between the first preset coordinate system and the second preset coordinate system;

[0042] Acquire spatial positioning information of each device in the hydropower station in the first preset coordinate system, and transform the spatial positioning information into spatial transformation information in the second preset coordinate system according to the transformation relationship;

[0043] The digital profile twin model is updated based on the spatial transformation information to obtain a full-space digital twin model of the hydropower station.

[0044] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a hydropower station full-space positioning monitoring system based on a digital twin model, wherein the hydropower station full-space positioning monitoring system based on a digital twin model comprises a storage device, a processor, a communication bus, and a control program stored on the storage device:

[0045] The communication bus is used to realize the connection and communication between the processor and the storage;

[0046] The processor is used to execute the control program to implement the steps of the full-space positioning monitoring method of a hydropower station based on a digital twin model as described above.

[0047] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a storage medium, on which a control program is stored, and when the control program is executed by a processor, the steps of the full-space positioning monitoring method of a hydropower station based on a digital twin model as described above are implemented.

[0048] The present invention provides a method, system and storage medium for full-space positioning monitoring of a hydropower station based on a digital twin model, divides the hydropower station into a hydraulic system, a mechanical system, an electric energy system and a connection system, and pre-sets a monitoring cycle. Whenever the preset monitoring cycle is spaced, the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data corresponding to the hydraulic system, the mechanical system, the electric energy system and the connection system are acquired, and the acquired hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are mapped to a digital twin model pre-built for the hydropower station, so as to analyze the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data respectively based on the digital twin model, and obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results; and then, based on the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results, the full-space positioning monitoring of the hydropower station is performed. In this way, by dividing the hydropower station into hydraulic system, mechanical system, electric energy system and connection system, and monitoring each divided system at each preset monitoring period, the relevant monitoring data is mapped to the digital twin model for analysis, and the monitoring results obtained reflect whether each component has initially experienced a fault phenomenon, whether a fault may occur, etc. Moreover, regardless of whether the components in each system fail, the monitoring results obtained are directly reflected in the relevant positions of the numerical twin model, so as to quickly determine the location of the components that may fail in the hydropower station, and realize the accurate positioning monitoring of the hydropower station in the whole space in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a flow chart of the first embodiment of the method for full-space positioning and monitoring of a hydropower station based on a digital twin model of the present invention;

[0050] Figure 2 It is a flow chart of a second embodiment of a method for full-space positioning and monitoring of a hydropower station based on a digital twin model according to the present invention;

[0051] Figure 3 It is a flow chart of a third embodiment of a method for full-space positioning and monitoring of a hydropower station based on a digital twin model according to the present invention;

[0052] Figure 4 It is a structural schematic diagram of the hardware operating environment involved in an embodiment of a hydropower station full-space positioning monitoring system based on a digital twin model of the present invention.

[0053] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0054] 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.

[0055] The present invention provides a method for full-space positioning and monitoring of a hydropower station based on a digital twin model. The hydropower station includes a hydraulic system, a mechanical system, an electrical energy system, and a connection system. Figure 1 , Figure 1 It is a flow chart of the first embodiment of the method for full-space positioning and monitoring of a hydropower station based on a digital twin model of the present invention.

[0056] The embodiment of the present invention provides an embodiment of a method for full-space positioning and monitoring of a hydropower station based on a digital twin model. It should be noted that although a logical sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that here. Specifically, the method for full-space positioning and monitoring of a hydropower station based on a digital twin model in this embodiment includes:

[0057] Step S10, obtaining hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data corresponding to the hydraulic system, mechanical system, electric energy system and connection system respectively at every preset monitoring period.

[0058] The full-space positioning monitoring method of a hydropower station based on a digital twin model in this embodiment is applied to the control platform of the hydropower station. The full space of the hydropower station can be divided into a hydraulic system, a mechanical system, an electrical energy system, and a connection system. The hydraulic system is mainly the upstream head part, the mechanical system is mainly the turbine part that realizes the conversion of water energy into mechanical energy, and the electrical energy system is mainly the generator part that is linked with the turbine to generate electrical energy. The connection system is mainly the part that realizes the physical connection and communication connection of each system, such as cable connection, hydraulic pipeline connection, communication connection, etc. Each system can be directly connected to the control platform separately to transmit the monitoring data for the components contained therein to the control platform, and the control platform will analyze and process it according to the digital twin model pre-set for the hydropower station to realize the full-space positioning monitoring of the hydropower station.

[0059] Specifically, sensors for monitoring the operation of each system component are provided, including but not limited to water flow sensors, pressure sensors, temperature sensors, binocular vision, cameras, infrared detection equipment, ultrasonic detection equipment, etc. In addition, a monitoring cycle is pre-set according to the wear cycle, fatigue failure cycle or experience cycle of each system component, and system data collected by sensors in each system are acquired at intervals of the preset monitoring cycle, that is, hydraulic monitoring data collected by sensors in the hydraulic system in the preset monitoring cycle, mechanical monitoring data collected by sensors in the mechanical system in the preset monitoring cycle, electric energy monitoring data collected by sensors in the electric energy system in the preset monitoring cycle, and connection monitoring data collected by sensors in the connection system in the preset monitoring cycle are acquired. Then, the operating status of each component in the hydraulic system, mechanical system, electric energy system and connection system is reflected through analysis and processing of hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data.

[0060] Step S20, mapping the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data to the digital twin model corresponding to the hydropower station, and analyzing the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results.

[0061] Furthermore, an array twin model is pre-built for the hydropower station. The digital twin model is a holographic mapping of the complex physical entity of the substation from the real space to the virtual digital space. Through the virtual-real connection, it depicts and simulates the real-time status and dynamic characteristics of the substation. In this embodiment, the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are mapped to the component parameters of the system components in the digital twin model according to the system components from which they are derived. Data representing the normal operation of each system component is pre-added to the digital twin model. The digital twin model analyzes and processes the mapped hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data based on such normal operation data, and obtains the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results of the hydraulic system, mechanical system, electric energy system and connection system respectively in the preset monitoring period.

[0062] Step S30, performing full-space positioning monitoring of the hydropower station based on the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results.

[0063] Furthermore, the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results, and connection monitoring results respectively reflect whether each component in the hydraulic system, each component in the mechanical system, each component in the electric energy system, and each component in the connection system may fail within a preset monitoring period. Therefore, based on the components that may fail reflected in the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results, and connection monitoring results, as well as the positions of the components in the digital twin model, full-space positioning monitoring of the hydropower station can be performed. Specifically, the steps of performing full-space positioning monitoring of the hydropower station based on the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results, and connection monitoring results include:

[0064] Step S31, determining whether there are any abnormal monitoring results among the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results;

[0065] Step S32: if there is an abnormal monitoring result, determine the abnormal type and abnormal location area of ​​the abnormal monitoring result, find abnormal analysis information corresponding to the abnormal type, and add the abnormal type, abnormal location area and abnormal analysis information to the digital twin model to complete the full-space positioning monitoring of the hydropower station in the preset monitoring period;

[0066] Step S33: If there is no abnormal monitoring result, outputting prompt information that the full-space positioning monitoring of the hydropower station in the preset monitoring period is normal based on the digital twin model.

[0067] Furthermore, in the process of analyzing each monitoring data through the digital twin model, for the monitoring data that may have abnormalities, relevant abnormal identification will be added to the monitoring results of the production. Therefore, when the full-space positioning monitoring of the hydropower station is carried out, it is judged whether there are abnormal monitoring results in the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results, that is, monitoring results with abnormal identification. Among them, because the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data all contain sub-monitoring data from multiple components of each system, the generated hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results correspondingly contain sub-monitoring results of multiple components of each system. As long as there is any sub-monitoring result carrying an abnormal identification, the monitoring result to which the sub-monitoring result belongs is determined to be an abnormal monitoring result. On the contrary, only when all the sub-monitoring results contained in the monitoring result do not carry an abnormal identification, can the monitoring result be determined to be a non-abnormal monitoring result.

[0068] Further, if it is determined that there are abnormal monitoring results in the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results, that is, there is a monitoring result in the four monitoring results that contains a sub-monitoring result with an abnormal identification. At this time, the abnormal component of the abnormal monitoring result is determined according to the system component from which the sub-monitoring result comes, and the location area where the abnormal component is located is determined as the abnormal positioning area corresponding to the abnormal monitoring result. At the same time, the abnormal type of the abnormal monitoring result can be determined according to the abnormal type of the sub-monitoring result. In addition, in order to facilitate the rapid investigation of abnormalities, abnormal analysis information corresponding to various types of abnormalities is also pre-set. After determining the abnormal type, the abnormal analysis information corresponding to the abnormal type is found from the preset abnormal analysis information, and it is added to the corresponding component of the digital twin model together with the abnormal type and abnormal positioning area, and the full-space positioning monitoring of the hydropower station within the preset monitoring period is completed. Among them, in order to investigate the abnormality more quickly, the corresponding abnormal prompt information can be output after mapping to the digital twin model to prompt the hydropower station that there is an abnormality that needs to be processed.

[0069] Furthermore, if it is determined that there are no abnormal monitoring results in the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results, and connection monitoring results, it means that the components of each system in the hydropower station are operating normally and there are no components that may cause risks. At this time, the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results, and connection monitoring results are added to the corresponding components of the digital twin model. At the same time, the prompt information that the full-space positioning monitoring of the hydropower station in the preset monitoring period is normal is output, and the full-space positioning monitoring of the hydropower station in the preset monitoring period is completed.

[0070] The method for full-space positioning and monitoring of a hydropower station based on a digital twin model implemented in this embodiment divides the hydropower station into a hydraulic system, a mechanical system, an electric energy system and a connection system, and pre-sets a monitoring cycle. Whenever the preset monitoring cycle is spaced, the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data corresponding to the hydraulic system, the mechanical system, the electric energy system and the connection system are obtained, and the obtained hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are mapped to a digital twin model pre-built for the hydropower station, so as to analyze the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data based on the digital twin model, and obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results; and then, based on the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results, the full-space positioning monitoring of the hydropower station is performed. In this way, by dividing the hydropower station into hydraulic system, mechanical system, electric energy system and connection system, and monitoring each divided system at each preset monitoring period, the relevant monitoring data is mapped to the digital twin model for analysis, and the monitoring results obtained reflect whether each component has initially experienced a fault phenomenon, whether a fault may occur, etc. Moreover, regardless of whether the components in each system fail, the monitoring results obtained are directly reflected in the relevant positions of the numerical twin model, so as to quickly determine the location of the components that may fail in the hydropower station, and realize the accurate positioning monitoring of the hydropower station in the whole space in advance.

[0071] For further information, please refer to Figure 2 Based on the first embodiment of the full-space positioning monitoring method of a hydropower station based on a digital twin model of the present invention, a second embodiment of the full-space positioning monitoring method of a hydropower station based on a digital twin model of the present invention is proposed.

[0072] The difference between the second embodiment of the method for full-space positioning and monitoring of a hydropower station based on a digital twin model and the first embodiment of the method for full-space positioning and monitoring of a hydropower station based on a digital twin model is that the steps of analyzing the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results include:

[0073] Step S21, analyzing the hydraulic monitoring data based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model to obtain a hydraulic monitoring result;

[0074] Furthermore, the data of normal operation of each component of the hydraulic system is added to the digital twin model as hydraulic reference data corresponding to the hydraulic system, and the control platform analyzes the collected hydraulic monitoring data based on the hydraulic reference data in the digital twin model to obtain hydraulic monitoring results. Among them, the hydraulic monitoring data at least includes water flow data and water surface images within a preset monitoring period; the water flow data represents the size of the water flow entering the turbine at each moment within the preset monitoring period at the upstream head, and the water surface image can reflect whether the water surface of the reservoir corresponding to the upstream head accumulates impurities that may block the water inlet of the turbine within the preset monitoring period. For the hydraulic monitoring data containing water flow data and water surface images, the steps of analyzing the hydraulic monitoring data based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model to obtain hydraulic monitoring results include:

[0075] Step S211, forming the water flow data into a water flow curve within a preset monitoring period, and analyzing the water flow curve based on the water flow reference curve in the hydraulic reference data, determining whether the water flow data is turbulent data, and generating a water flow analysis result;

[0076] Step S212, determining a similarity value between a water surface reference image in the hydraulic reference data and the water surface image, and determining whether there is impurity imaging in the water surface image according to the similarity value, and generating a water surface analysis result;

[0077] Step S213, combining the water flow analysis result and the water surface analysis result into the hydraulic monitoring result.

[0078] Further, the water flow data is formed into a water flow curve according to the formation time sequence in the preset monitoring cycle, and the water flow curve represents the water flow size at each moment in the preset monitoring cycle. At the same time, there is a water flow reference curve in the hydraulic reference data, and the water flow reference curve is relatively gentle, indicating that the water flow entering the turbine is relatively stable. A comparison analysis is performed between the water flow reference curve and the water flow curve to determine the fit between the water flow curve and the water flow reference curve. The higher the fit between the two, the higher the degree of proximity between the two, the water flow curve belongs to a gentle curve, and the water flow entering the turbine is relatively stable. On the contrary, if the fit between the two is low, the lower the degree of proximity between the two, the water flow curve is not a gentle curve, the water flow entering the turbine is unstable, and the water flow changes at multiple moments, which is a turbulent water flow that affects the performance of the turbine. Therefore, by comparing and analyzing the water flow reference curve with the water flow curve, it is determined whether the water flow data belongs to turbulent data. That is, if the water flow reference curve data fits the water flow data well, it means that the water flow entering the turbine is not turbulent water flow, and the water flow data does not belong to turbulent data. If the water flow reference curve data fits the water flow data poorly, it means that the water flow entering the turbine is turbulent water flow, and the water flow data belongs to turbulent data. Then, a water flow analysis result that belongs to or does not belong to turbulent data is generated.

[0079] Furthermore, for the water surface image, a corresponding water surface reference image is pre-set in the hydraulic reference data, and the water surface reference image is an image without impurities on the water surface. The similarity value between the water surface reference image and the water surface image is calculated, and the similarity between the water surface image and the water surface reference image is determined by the similarity value between the two. Among them, the similarity value can be obtained by dividing the two images into multiple blocks. Specifically, the water surface reference image and the water surface image are collected at the same position and at the same angle, and then the two are divided into water surface reference sub-images and water surface sub-images according to the same division rule, for example, divided into 9 equal parts of 3*3 or 16 equal parts of 4*4. The pixel values ​​of the two sub-images at the same position are calculated, and the similarity of the two sub-images is determined by the difference in pixel values. A preset threshold representing the similarity is pre-set, and after calculating each sub-similarity value, each sub-similarity value is averaged to obtain the overall similarity, that is, the similarity value between the water surface reference image and the water surface image. Then, the similarity value is compared with the preset threshold. If the similarity value is less than the preset threshold, it means that the similarity between the two images is low, and other objects may be imaged in the water surface image. On the contrary, if the similarity value is greater than or equal to the preset threshold, it means that the similarity between the two images is high, and no other objects are imaged in the water surface image. Therefore, whether there are other objects imaged as impurities in the water surface image is determined based on the similarity value, and the corresponding water surface analysis results are generated.

[0080] Furthermore, the water flow analysis results and the water surface analysis results are jointly formed into a hydraulic monitoring result to reflect whether turbulent water flow that affects the performance of the turbine occurs within a preset monitoring period, and whether there are impurities on the water surface that may block the water inlet of the turbine.

[0081] Step S22, analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain a mechanical monitoring result;

[0082] Furthermore, the data of normal operation of each component of the mechanical system is added to the digital twin model as the mechanical reference data corresponding to the mechanical system, and the control platform analyzes the collected mechanical monitoring data according to the mechanical reference data in the digital twin model to obtain the mechanical monitoring results. Among them, the mechanical monitoring data at least includes the impeller image of the turbine, as well as the shutdown data and bearing vibration data within the preset monitoring period; the impeller image is used to reflect whether the impeller has corrosion, wear, etc., the shutdown data is used to reflect whether the turbine is affected by water hammer, and the bearing vibration data is used to reflect whether the bearing has cracks, etc. For the mechanical monitoring data containing the impeller image, shutdown data and bearing vibration data, the step of analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain the mechanical monitoring results includes:

[0083] Step S221, determining whether there is downtime duration data in the downtime data, and if there is downtime duration data, comparing the downtime duration data with the reference downtime duration in the mechanical reference data, analyzing whether the downtime data belongs to the target downtime data causing the water hammer phenomenon, and generating a water hammer analysis result;

[0084] Step S222, based on the comparison and analysis between the reference impeller image in the mechanical reference data and the impeller image, determining whether the impeller of the turbine is worn and corroded, and generating an impeller analysis result;

[0085] Step S223, based on the comparison and analysis between the reference bearing data in the mechanical reference data and the bearing vibration data, determining whether the bearing of the turbine has cracks, and generating a bearing analysis result;

[0086] Step S224: The water hammer analysis result, the impeller analysis result and the bearing analysis result are jointly generated as the mechanical monitoring result.

[0087] Furthermore, the shutdown data within the preset monitoring period at least includes status data of whether the turbine has been shut down within the preset monitoring period. And for the status data of shutdown, the number of shutdowns and the shutdown time spent for each shutdown are jointly formed into shutdown data. In addition, for the analysis of the shutdown data, it is first determined whether there is shutdown time data. If there is, it means that the turbine has been shut down within the preset monitoring period, and the shutdown may cause the turbine to be affected by water hammer. Among them, the water hammer effect is that when the turbine is suddenly shut down, due to the inertia of the pressure water flow, a water flow shock wave is generated, and the force generated by the water flow shock wave back and forth affects the turbine. A reference shutdown time is pre-set in the mechanical reference data, and the reference shutdown time indicates that the turbine is shut down for a time not less than this time and will not be affected by the water hammer effect. The downtime data in the downtime data is compared with the reference downtime data, and through the size relationship between the two, it is analyzed whether the downtime data belongs to the target downtime data that causes the water hammer phenomenon, and the corresponding water hammer analysis results are generated. If the downtime data is greater than the reference downtime, it means that the turbine will not be affected by the water hammer effect, otherwise it will be affected by the water hammer effect, thereby generating a water hammer analysis result that the downtime data belongs to the target downtime data or does not belong to the target downtime data.

[0088] Furthermore, for the impeller image, a corresponding reference impeller image is pre-set in the mechanical reference data, and the reference impeller image is an outer surface image of a normal impeller without corrosion and wear. The digital twin model can be pre-connected with a preset recognition model for image feature extraction and recognition, and the reference impeller image and the impeller image are compared and recognized through the preset recognition model to analyze whether the impeller of the turbine is worn and corroded, and generate corresponding impeller analysis results. For the bearing vibration data, the mechanical reference data is pre-set with reference bearing data, and the reference bearing data is a data interval formed by collecting vibration data of a normal bearing without cracks running under various conditions. The bearing vibration data is compared and analyzed based on the reference bearing data to determine whether the bearing vibration data is within the data interval corresponding to the reference bearing data. If it is within the corresponding data interval, it means that there is no crack in the bearing of the turbine, and a bearing analysis result without cracks is generated. On the contrary, if it is determined that the bearing vibration data is not within the corresponding data interval, it means that there is a crack in the bearing of the turbine, and a bearing analysis result with cracks is generated.

[0089] Furthermore, the water hammer analysis results, impeller analysis results and bearing analysis results are jointly formed into mechanical monitoring results to reflect whether water hammer effects affecting turbine performance occur within a preset monitoring period, whether the turbine impeller is subject to wear and corrosion, and whether the turbine bearings are subject to cracks.

[0090] Step S23, analyzing the power monitoring data based on the power reference data corresponding to the power system in the digital twin model to obtain a power monitoring result;

[0091] Furthermore, the data of normal operation of each component of the electric energy system is added to the digital twin model as the electric energy reference data corresponding to the electric energy system, and the control platform analyzes the collected electric energy monitoring data according to the electric energy reference data in the digital twin model to obtain the electric energy monitoring result. Among them, the electric energy monitoring data at least includes the power generation data, temperature data and noise data of the generator in the electric energy system within a preset monitoring period. The power generation data is used to reflect the amount of power generated by the generator within the preset monitoring period, the temperature data is used to reflect the heat generation of the generator during the power generation process of the preset monitoring period, and the noise data is used to reflect the noise generated by the generator during the power generation process of the preset monitoring period. For the electric energy monitoring data containing the power generation data, temperature data and noise data, the step of analyzing the electric energy monitoring data based on the electric energy reference data corresponding to the electric energy system in the digital twin model to obtain the electric energy monitoring result includes:

[0092] Step S231, determining theoretical power generation data corresponding to the electric energy system based on the water flow data in the hydraulic monitoring data;

[0093] Step S232, based on the operating age parameter and operating environment parameter of the generator included in the electric energy reference data, the theoretical power generation data is updated, and the theoretical temperature data and theoretical noise data of the generator are determined;

[0094] Step S233, analyzing the power generation data based on the updated theoretical power generation data, and analyzing the temperature data and noise data based on the theoretical temperature data and theoretical noise data, respectively, to generate a generator analysis result.

[0095] Understandably, the amount of power generated by a hydropower station is related to the amount of water flowing through the turbine. The more water flows through, the higher the power generation. The monitored amount of water flowing through the turbine is used as the water flow data in the hydraulic monitoring data, and the theoretical power generation is calculated based on the water flow data, and the calculated power generation is used as the theoretical power generation data corresponding to the electric energy system. In addition, as the generator in the electric energy system increases in service life, the power generation will be affected, so that the power generation will be different under the same amount of water. In addition, there are differences in the power generation of the generator in different environments. Based on this, the operating life parameters and operating environment parameters of the generator are obtained, and the two are added to the electric energy reference data to update the theoretical power generation data based on the two. Specifically, the power generation change parameters of the generator under various operating years and operating environments can be tracked in advance, and a corresponding relationship between the operating years, operating environment and power generation change parameters can be formed. Then, the operating year parameters and operating environment parameters contained in the electric energy reference data can be compared with the corresponding relationship to determine the matching corresponding relationship. The theoretical power generation data can be updated by the power generation change parameters in the matching corresponding relationship to obtain the accurate theoretical power generation under the water volume of the turbine.

[0096] Furthermore, the heat generation and noise generated by generators with different operating years and different operating environments during the power generation process are also different. The heating change parameters and noise change parameters of the generator under various operating years and operating environments are tracked in advance, and the heating correspondence between the operating years, operating environment and heating change parameters, and the noise correspondence between the operating years, operating environment and noise change parameters are formed. Then, the operating years parameters and operating environment parameters contained in the electric energy reference data are compared with the heating correspondence and noise correspondence, respectively, to determine the matching heating correspondence and noise correspondence, and the theoretical temperature data and theoretical noise data of the generator are determined from the matching heating correspondence and noise correspondence.

[0097] Furthermore, the power generation data is analyzed according to the updated theoretical power generation data to determine whether the monitored power generation data is close to the theoretical power generation data, and the temperature data and noise data are analyzed according to the theoretical temperature data and the theoretical noise data to determine whether the monitored temperature data is close to the theoretical temperature data, and whether the monitored noise data is close to the theoretical noise data. Among them, the judgment method of closeness or not can be to set a variation range based on the theoretical power generation data, the theoretical temperature data and the theoretical noise data, for example, plus or minus 10%. If the power generation data, temperature data and noise data are within their respective corresponding variation ranges, they are determined to be close and a normal analysis result is generated; otherwise, they are determined to be not close and an abnormal analysis result is generated. For the power monitoring result, if the analysis results of the power generation data, temperature data and noise data are all normal, the power monitoring result is normal. If any one of them is abnormal, the generated power monitoring result is abnormal, so as to reflect that the generator has abnormal power generation, abnormal heating or abnormal noise during the power generation process.

[0098] Step S24: analyzing the connection monitoring data based on the connection reference data corresponding to the connection system in the digital twin model to obtain a connection monitoring result.

[0099] Furthermore, the data of normal operation of each component of the connection system is added to the digital twin model as the connection reference data corresponding to the connection system, and the control platform analyzes the collected connection monitoring data according to the connection reference data in the digital twin model to obtain the connection monitoring result. Among them, the connection monitoring data at least includes the connection cable image, communication data and hydraulic line pressure in the connection system. The connection cable image reflects whether the insulation layer of the connection cable between the systems is damaged, the communication data reflects whether there is a serious delay in the communication between the systems, and the hydraulic line pressure reflects whether there is leakage in the hydraulic line between the systems. For the connection monitoring data containing the connection cable image, communication data and hydraulic line pressure, the step of analyzing the connection monitoring data based on the connection reference data corresponding to the connection system in the digital twin model to obtain the connection monitoring result includes:

[0100] Step S241, analyzing the connection cable image based on the reference cable image in the connection reference data, determining whether the connection cable in the connection system has a damaged cable insulation layer, and generating a cable analysis result;

[0101] Step S242, analyzing whether the communication data has abnormal delay based on the reference communication data in the connection reference data, and generating a communication analysis result;

[0102] Step S243, analyzing whether the hydraulic line pressure is abnormal pressure based on the reference hydraulic pressure in the connection reference data, and generating a pressure analysis result;

[0103] Step S244, the cable analysis result, the communication analysis result and the pressure analysis result are jointly generated as a connection monitoring result.

[0104] Furthermore, for the connection cable image, a reference cable image is pre-set in the connection reference data, and the reference cable image is an outer surface image of a normal connection cable that is not damaged. The reference cable image and the connection circuit image are compared and identified through a preset recognition model pre-connected in the digital twin model to analyze whether there is a damaged cable insulation layer in the connection cable in the connection system, and generate corresponding cable analysis results.

[0105] Furthermore, for communication data, reference communication data is pre-set in the connection reference data, and the reference communication data represents the transmission time interval in which data transmission between each system is not delayed. The communication data is analyzed based on the reference communication data, and by comparing the size relationship between the communication data and the reference communication data, it is determined whether the communication data has an abnormal delay. If the communication data exceeds the upper limit of the interval corresponding to the reference communication data, it means that the time for data transmission between the systems is too long, and there is an abnormal delay in the communication, and a communication analysis result of abnormal communication is generated. Otherwise, it means that there is no abnormal delay in the communication, and a communication analysis result of normal communication is generated.

[0106] Furthermore, for the hydraulic line pressure, a reference hydraulic pressure is pre-set in the connection reference data, and the reference hydraulic pressure represents the normal pressure value when the hydraulic line is not damaged. The hydraulic line pressure is compared and analyzed based on the reference hydraulic pressure to determine whether the hydraulic line pressure is abnormal pressure, and a corresponding pressure analysis result is generated. If the hydraulic line pressure is determined to be less than the pressure boundary value formed by the reference hydraulic pressure through comparison, the hydraulic line pressure is determined to be abnormal pressure, indicating that the hydraulic line may be damaged, and a pressure analysis result of abnormal pressure is generated. Otherwise, the hydraulic line pressure is determined to be normal pressure, and a pressure analysis result of normal pressure is generated.

[0107] Furthermore, the cable analysis results, communication analysis results and pressure analysis results are jointly formed into a connection monitoring result to reflect whether there is damage to the cable insulation layer, abnormal communication delay, or hydraulic oil leakage within a preset monitoring period.

[0108] This embodiment sets corresponding hydraulic reference data, mechanical reference data, electric energy reference data and connection reference data for the hydraulic system, mechanical system, electric energy system and connection system, respectively, and analyzes the monitored hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data, so that the analysis is more comprehensive and accurate.

[0109] For further information, please refer to Figure 3 Based on the first and second embodiments of the full-space positioning monitoring method of a hydropower station based on a digital twin model of the present invention, a third embodiment of the full-space positioning monitoring method of a hydropower station based on a digital twin model of the present invention is proposed.

[0110] The third embodiment of the method for full-space positioning and monitoring of a hydropower station based on a digital twin model is different from the first and second embodiments of the method for full-space positioning and monitoring of a hydropower station based on a digital twin model in that, before the step of obtaining hydraulic monitoring data, mechanical monitoring data and electric energy monitoring data corresponding to the hydraulic system, mechanical system and electric energy system, respectively, and connection monitoring data of the connection system at each preset monitoring period, the step includes:

[0111] Step S40, obtaining the center positioning information and the boundary positioning information of the hydropower station in the first preset coordinate system corresponding to the hydropower station, and constructing the center positioning information and the boundary positioning information into a digital contour twin model of the hydropower station according to the transformation relationship between the first preset coordinate system and the second preset coordinate system;

[0112] Step S50, obtaining spatial positioning information of each device in the hydropower station in the first preset coordinate system, and transforming the spatial positioning information into spatial transformation information in the second preset coordinate system according to the transformation relationship;

[0113] Step S60: updating the digital profile twin model based on the spatial transformation information to obtain a full-space digital twin model of the hydropower station.

[0114] Furthermore, in order to construct an accurate digital twin model for the hydropower station, the geodetic coordinate system where the hydropower station is located is set to the first preset coordinate system, and the center positioning information and boundary positioning information of the hydropower station in the first preset coordinate system are obtained. In addition, the coordinate system set for constructing the digital twin model is set to the second preset coordinate system. There is a displacement difference in the position of the coordinate origin between the first preset coordinate system and the second preset coordinate system, and there is an angle difference in the direction between the coordinate axes. According to the size of the displacement difference and the size of the angle difference, the conversion between the two coordinate systems can be realized. The transformation of the displacement difference and the angle difference is pre-set as the transformation relationship between the first preset coordinate system and the second preset coordinate system. According to the transformation relationship, the obtained center positioning information and boundary positioning information are constructed as a digital contour twin model of the hydropower station. The digital contour twin model reflects the center position of the hydropower station and its boundary positions.

[0115] Furthermore, the spatial positioning information of each device in the hydropower station in the first preset coordinate system is obtained, and according to the transformation relationship between the first preset coordinate system and the second preset coordinate system, the spatial positioning information is transformed into the second preset coordinate system to become the spatial transformation information in the second preset coordinate system. Then, the spatial transformation information is added to the digital profile twin model, and the digital profile twin model is updated to form a digital twin model of the entire space of the hydropower station.

[0116] This embodiment first constructs a digital profile twin model of the hydropower station through the transformation relationship between the first preset coordinate system and the second preset coordinate system, and then transforms the acquired spatial positioning information of each device in the hydropower station into spatial transformation information, updates the digital profile twin model, and obtains the digital twin model. Each device in the hydropower station can be reflected in the array twin model, and the digital twin model more accurately reflects the information of each device in the hydropower station, which is conducive to the fault monitoring of each device.

[0117] In addition, the embodiment of the present invention also provides a full-space positioning monitoring system for a hydropower station based on a digital twin model. Figure 4 , Figure 4 It is a structural schematic diagram of the equipment hardware operating environment involved in the implementation scheme of the hydropower station full-space positioning monitoring system based on the digital twin model of the present invention.

[0118] like Figure 4 As shown, the full-space positioning monitoring system of the hydropower station based on the digital twin model may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a storage 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The storage 1005 may be a high-speed RAM storage, or a stable storage (non-volatile memory), such as a disk storage. The storage 1005 may also be a storage device independent of the aforementioned processor 1001.

[0119] Those skilled in the art will understand that Figure 4 The hardware structure of the hydropower station full-space positioning monitoring system based on the digital twin model shown in the figure does not constitute a limitation of the hydropower station full-space positioning monitoring system based on the digital twin model, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0120] like Figure 4 As shown, the storage 1005 as a storage medium may include an operating system, a network communication module, a user interface module and a control program. Among them, the operating system is a program for managing and controlling the full-space positioning monitoring system and software resources of the hydropower station based on the digital twin model, supporting the operation of the network communication module, the user interface module, the control program and other programs or software; the network communication module is used to manage and control the network interface 1004; the user interface module is used to manage and control the user interface 1003.

[0121] exist Figure 4 In the hardware structure of the hydropower station full-space positioning monitoring system based on the digital twin model shown, the network interface 1004 is mainly used to connect to other system servers and communicate data with other system servers; the user interface 1003 is mainly used to connect to the client (user end) and communicate data with the client; the processor 1001 can call the control program stored in the storage 1005 and perform the following operations:

[0122] At each preset monitoring period, hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data corresponding to the hydraulic system, mechanical system, electric energy system and connection system are obtained respectively;

[0123] The hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are mapped to the digital twin model corresponding to the hydropower station, and the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are analyzed based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results;

[0124] Based on the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results, the hydropower station is subjected to full-space positioning monitoring.

[0125] Furthermore, the steps of analyzing the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results include:

[0126] Based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model, the hydraulic monitoring data is analyzed to obtain a hydraulic monitoring result;

[0127] Analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain a mechanical monitoring result;

[0128] Based on the electric energy reference data corresponding to the electric energy system in the digital twin model, analyzing the electric energy monitoring data to obtain an electric energy monitoring result;

[0129] Based on the connection reference data corresponding to the connection system in the digital twin model, the connection monitoring data is analyzed to obtain a connection monitoring result.

[0130] Further, the hydraulic monitoring data includes water flow data and water surface images within a preset monitoring period;

[0131] The step of analyzing the hydraulic monitoring data based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model to obtain the hydraulic monitoring results includes:

[0132] The water flow data is formed into a water flow curve within a preset monitoring period, and the water flow curve is analyzed based on the water flow reference curve in the hydraulic reference data to determine whether the water flow data is turbulent data, and generate a water flow analysis result;

[0133] Determine a similarity value between a water surface reference image in the hydraulic reference data and the water surface image, and determine whether there is impurity imaging in the water surface image according to the similarity value, and generate a water surface analysis result;

[0134] The water flow analysis result and the water surface analysis result are jointly formed into the hydraulic monitoring result.

[0135] Further, the mechanical monitoring data includes an impeller image of the turbine, shutdown data within a preset monitoring period, and bearing vibration data;

[0136] The step of analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain the mechanical monitoring result includes:

[0137] Determine whether there is downtime duration data in the downtime data; if there is downtime duration data, compare the downtime duration data with the reference downtime duration in the mechanical reference data, analyze whether the downtime data belongs to the target downtime data causing the water hammer phenomenon, and generate a water hammer analysis result;

[0138] Based on the comparison and analysis between the reference impeller image in the mechanical reference data and the impeller image, determining whether the impeller of the turbine has wear and corrosion, and generating an impeller analysis result;

[0139] Based on the comparison and analysis of the reference bearing data in the mechanical reference data and the bearing vibration data, determining whether the bearing of the turbine has cracks, and generating a bearing analysis result;

[0140] The water hammer analysis result, the impeller analysis result and the bearing analysis result are jointly generated as the mechanical monitoring result.

[0141] Further, the electric energy monitoring data includes power generation data, temperature data and noise data of the generator in the electric energy system within a preset monitoring period;

[0142] The step of analyzing the electric energy monitoring data based on the electric energy reference data corresponding to the electric energy system in the digital twin model to obtain the electric energy monitoring result comprises:

[0143] Determining theoretical power generation data corresponding to the electric energy system based on water flow data in the hydraulic monitoring data;

[0144] Based on the operating age parameter and operating environment parameter of the generator included in the electric energy reference data, the theoretical power generation data is updated, and the theoretical temperature data and theoretical noise data of the generator are determined;

[0145] The power generation data is analyzed based on the updated theoretical power generation data, and the temperature data and noise data are analyzed based on the theoretical temperature data and the theoretical noise data, respectively, to generate a generator analysis result.

[0146] Further, the connection monitoring data includes connection cable images, communication data and hydraulic line pressure;

[0147] The step of analyzing the connection monitoring data based on the connection reference data corresponding to the connection system in the digital twin model to obtain the connection monitoring result includes:

[0148] Analyze the connection cable image based on the reference cable image in the connection reference data, determine whether the connection cable in the connection system has a damaged cable insulation layer, and generate a cable analysis result;

[0149] Analyze whether the communication data has abnormal delay based on the reference communication data in the connection reference data, and generate a communication analysis result;

[0150] analyzing whether the hydraulic line pressure is abnormal based on the reference hydraulic pressure in the connection reference data, and generating a pressure analysis result;

[0151] The cable analysis result, the communication analysis result and the pressure analysis result are jointly generated as a connection monitoring result.

[0152] Furthermore, the step of performing full-space positioning monitoring of the hydropower station according to the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results includes:

[0153] Determine whether there are abnormal monitoring results in the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results;

[0154] If there is an abnormal monitoring result, determine the abnormal type and abnormal location area of ​​the abnormal monitoring result, find the abnormal analysis information corresponding to the abnormal type, and add the abnormal type, abnormal location area and abnormal analysis information to the digital twin model to complete the full-space positioning monitoring of the hydropower station in the preset monitoring period;

[0155] If there is no abnormal monitoring result, a prompt message is output based on the digital twin model that the full-space positioning monitoring of the hydropower station is normal during the preset monitoring period.

[0156] Furthermore, before the step of obtaining the hydraulic monitoring data, mechanical monitoring data and electric energy monitoring data corresponding to the hydraulic system, mechanical system and electric energy system respectively, and the connection monitoring data of the connection system at each preset monitoring period, the processor 1001 may call the control program stored in the storage 1005 and perform the following operations:

[0157] Acquire the center positioning information and the boundary positioning information of the hydropower station in a first preset coordinate system corresponding to the hydropower station, and construct the center positioning information and the boundary positioning information into a digital contour twin model of the hydropower station according to a transformation relationship between the first preset coordinate system and the second preset coordinate system;

[0158] Acquire spatial positioning information of each device in the hydropower station in the first preset coordinate system, and transform the spatial positioning information into spatial transformation information in the second preset coordinate system according to the transformation relationship;

[0159] The digital profile twin model is updated based on the spatial transformation information to obtain a full-space digital twin model of the hydropower station.

[0160] The specific implementation methods of the full-space positioning monitoring system of a hydropower station based on a digital twin model of the present invention are basically the same as the various embodiments of the full-space positioning monitoring method of a hydropower station based on a digital twin model mentioned above, and will not be repeated here.

[0161] The embodiment of the present invention further provides a storage medium having a control program stored thereon, and when the control program is executed by a processor, the steps of the method for full-space positioning and monitoring of a hydropower station based on a digital twin model are implemented as described above.

[0162] The storage medium of the present invention may be a computer-readable storage medium, and its implementation method is basically the same as the above-mentioned embodiments of the full-space positioning monitoring method of a hydropower station based on a digital twin model, and will not be repeated here.

[0163] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims. All equivalent structures or equivalent process changes made using the contents of the specification and drawings of the present invention, or directly or indirectly used in other related technical fields, are protected by the present invention.

Claims

1. A method for full-space positioning and monitoring of a hydropower station based on a digital twin model, characterized in that: The hydropower station includes a hydraulic system, a mechanical system, an electric energy system and a connection system. The full-space positioning monitoring method of the hydropower station includes: At each preset monitoring period, hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data corresponding to the hydraulic system, mechanical system, electric energy system and connection system are obtained respectively; The hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are mapped to the digital twin model corresponding to the hydropower station, and the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data are analyzed based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results; Based on the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results, the hydropower station is subjected to full-space positioning monitoring.

2. The method for full-space positioning and monitoring of a hydropower station according to claim 1, characterized in that: The steps of analyzing the hydraulic monitoring data, mechanical monitoring data, electric energy monitoring data and connection monitoring data based on the digital twin model to obtain hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results include: Based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model, the hydraulic monitoring data is analyzed to obtain a hydraulic monitoring result; Analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain a mechanical monitoring result; Based on the electric energy reference data corresponding to the electric energy system in the digital twin model, analyzing the electric energy monitoring data to obtain an electric energy monitoring result; Based on the connection reference data corresponding to the connection system in the digital twin model, the connection monitoring data is analyzed to obtain a connection monitoring result.

3. The full-space positioning monitoring method for a hydropower station according to claim 2, characterized in that: The hydraulic monitoring data includes water flow data and water surface images within a preset monitoring period; The step of analyzing the hydraulic monitoring data based on the hydraulic reference data corresponding to the hydraulic system in the digital twin model to obtain the hydraulic monitoring results includes: The water flow data is formed into a water flow curve within a preset monitoring period, and the water flow curve is analyzed based on the water flow reference curve in the hydraulic reference data to determine whether the water flow data is turbulent data, and generate a water flow analysis result; Determine a similarity value between a water surface reference image in the hydraulic reference data and the water surface image, and determine whether there is impurity imaging in the water surface image according to the similarity value, and generate a water surface analysis result; The water flow analysis result and the water surface analysis result are jointly formed into the hydraulic monitoring result.

4. The method for full-space positioning and monitoring of a hydropower station according to claim 2, characterized in that: The mechanical monitoring data includes an image of a turbine impeller, shutdown data within a preset monitoring period, and bearing vibration data; The step of analyzing the mechanical monitoring data based on the mechanical reference data corresponding to the mechanical system in the digital twin model to obtain the mechanical monitoring result includes: Determine whether there is downtime duration data in the downtime data; if there is downtime duration data, compare the downtime duration data with the reference downtime duration in the mechanical reference data, analyze whether the downtime data belongs to the target downtime data causing the water hammer phenomenon, and generate a water hammer analysis result; Based on the comparison and analysis between the reference impeller image in the mechanical reference data and the impeller image, determining whether the impeller of the turbine has wear and corrosion, and generating an impeller analysis result; Based on the comparison and analysis of the reference bearing data in the mechanical reference data and the bearing vibration data, determining whether the bearing of the turbine has cracks, and generating a bearing analysis result; The water hammer analysis result, the impeller analysis result and the bearing analysis result are jointly generated as the mechanical monitoring result.

5. The full-space positioning monitoring method for a hydropower station according to claim 2, characterized in that: The electric energy monitoring data includes power generation data, temperature data and noise data of the generator in the electric energy system within a preset monitoring period; The step of analyzing the electric energy monitoring data based on the electric energy reference data corresponding to the electric energy system in the digital twin model to obtain the electric energy monitoring result comprises: Determining theoretical power generation data corresponding to the electric energy system based on water flow data in the hydraulic monitoring data; Based on the operating age parameter and operating environment parameter of the generator included in the electric energy reference data, the theoretical power generation data is updated, and the theoretical temperature data and theoretical noise data of the generator are determined; The power generation data is analyzed based on the updated theoretical power generation data, and the temperature data and noise data are analyzed based on the theoretical temperature data and the theoretical noise data, respectively, to generate a generator analysis result.

6. The method for full-space positioning and monitoring of a hydropower station according to claim 2, characterized in that: The connection monitoring data includes connection cable images, communication data and hydraulic line pressure; The step of analyzing the connection monitoring data based on the connection reference data corresponding to the connection system in the digital twin model to obtain the connection monitoring result includes: Analyze the connection cable image based on the reference cable image in the connection reference data, determine whether the connection cable in the connection system has a damaged cable insulation layer, and generate a cable analysis result; Analyze whether the communication data has abnormal delay based on the reference communication data in the connection reference data, and generate a communication analysis result; analyzing whether the hydraulic line pressure is abnormal based on the reference hydraulic pressure in the connection reference data, and generating a pressure analysis result; The cable analysis result, the communication analysis result and the pressure analysis result are jointly generated as a connection monitoring result.

7. The method for full-space positioning and monitoring of a hydropower station according to any one of claims 1 to 6, characterized in that: The step of performing full-space positioning monitoring of the hydropower station according to the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results comprises: Determine whether there are abnormal monitoring results in the hydraulic monitoring results, mechanical monitoring results, electric energy monitoring results and connection monitoring results; If there is an abnormal monitoring result, determine the abnormal type and abnormal location area of ​​the abnormal monitoring result, find the abnormal analysis information corresponding to the abnormal type, and add the abnormal type, abnormal location area and abnormal analysis information to the digital twin model to complete the full-space positioning monitoring of the hydropower station in the preset monitoring period; If there is no abnormal monitoring result, a prompt message is output based on the digital twin model that the full-space positioning monitoring of the hydropower station is normal during the preset monitoring period.

8. The method for full-space positioning and monitoring of a hydropower station according to any one of claims 1 to 6, characterized in that: The step of obtaining hydraulic monitoring data, mechanical monitoring data and electric energy monitoring data corresponding to the hydraulic system, mechanical system and electric energy system respectively, and connection monitoring data of the connection system at each preset monitoring period includes: Acquire the center positioning information and the boundary positioning information of the hydropower station in a first preset coordinate system corresponding to the hydropower station, and construct the center positioning information and the boundary positioning information into a digital contour twin model of the hydropower station according to a transformation relationship between the first preset coordinate system and the second preset coordinate system; Acquire spatial positioning information of each device in the hydropower station in the first preset coordinate system, and transform the spatial positioning information into spatial transformation information in the second preset coordinate system according to the transformation relationship; The digital profile twin model is updated based on the spatial transformation information to obtain a full-space digital twin model of the hydropower station.

9. A full-space positioning monitoring system for a hydropower station based on a digital twin model, characterized in that: The hydropower station full-space positioning monitoring system based on the digital twin model includes a storage device, a processor, a communication bus, and a control program stored in the storage device: The communication bus is used to realize the connection and communication between the processor and the storage; The processor is used to execute the control program to implement the steps of the full-space positioning monitoring method of a hydropower station based on a digital twin model as described in any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium stores a control program, which, when executed by the processor, implements the steps of the full-space positioning monitoring method of a hydropower station based on a digital twin model as described in any one of claims 1 to 8.

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