Flywheel operation risk monitoring system and method

Abstract

The present invention provides a flywheel operation risk monitoring system and method, including: a sensor component for detecting the initial operation data of the flywheel entity at startup and the real-time operation data during operation; a flywheel digital twin for simulating the operation status of the flywheel entity throughout its life cycle according to the initial operation data, and sending the simulated operation data obtained by simulation to an intelligent decision-making module; the intelligent decision-making module is used to predict the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity based on the operation risk. The flywheel digital twin simulates the entire life cycle of the flywheel entity, and compares the real-time operation data of the flywheel entity with the simulation data obtained by simulation to determine the operation risk of the flywheel entity, thereby achieving real-time monitoring of the operation risk of the flywheel entity, thereby improving the safety of the operation of the flywheel entity and ensuring the service life of the flywheel entity.

Description

Technical Field

[0001] The present invention relates to the field of flywheel risk monitoring, and in particular to a flywheel operation risk monitoring system and method. Background Art

[0002] A magnetic levitation flywheel is an energy storage device that stores mechanical energy in a vacuum environment by rotating the rotor at high speed. If the rotor overspeeds when rotating at high speed, the internal stress of the rotor will exceed the material strength limit, causing crack damage inside the rotor components. In extreme cases, the rotor will explode, resulting in casualties.

[0003] Due to the complexity of the flywheel structure, it is difficult for the existing flywheel control system to restore the actual operating scenario of the flywheel. Therefore, the existing flywheel system mainly prevents the occurrence of safety accidents through remote monitoring and control of the flywheel, and the safety of flywheel operation is relatively low. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a flywheel operation risk monitoring system and method, which simulates the entire life cycle of the flywheel entity through a flywheel digital twin, compares the real-time operation data of the flywheel entity with the simulation data obtained by simulation, so as to determine the operation risk of the flywheel entity, thereby realizing the prediction of the operation risk of the flywheel entity, and controlling the operation of the flywheel entity based on the operation risk, thereby improving the safety of the flywheel entity operation and ensuring the service life of the flywheel entity.

[0005] In the first aspect, an embodiment of the present invention provides a flywheel operation risk monitoring system, the system comprising: a flywheel entity, an intelligent decision-making module and a flywheel digital twin that are communicatively connected to each other; a sensor assembly is arranged on the flywheel entity; the sensor assembly is used to detect the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and send the initial operation data to the flywheel digital twin, and send the real-time operation data to the intelligent decision-making module; the flywheel digital twin is used to simulate the operation status of the flywheel entity throughout its life cycle according to the initial operation data, and send the simulated operation data obtained by the simulation to the intelligent decision-making module; the intelligent decision-making module is used to predict the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity based on the operation risk.

[0006] Furthermore, the intelligent decision-making module is also used to: determine the target emergency measures corresponding to the operating risks based on the operating risks of the flywheel entity; and control the operation of the flywheel entity according to the target emergency measures so that the real-time operating data of the flywheel entity is consistent with the simulated operating data of its corresponding life cycle.

[0007] Furthermore, the flywheel digital twin is obtained in the following manner: constructing an initial three-dimensional model of the flywheel entity; taking the initial operating data of the flywheel entity as input and the real-time operating data of the flywheel entity during operation as output, training the initial three-dimensional model until the preset training conditions are met to obtain a trained flywheel digital twin; wherein the initial operating data includes initial vacuum data, initial temperature data, initial speed data, initial vibration data, initial electromagnetic field data and initial rotor position data of the flywheel entity; the real-time operating data includes operating vacuum data, operating temperature data, operating speed data, operating vibration data, operating electromagnetic field data and operating rotor position data of the flywheel entity.

[0008] Furthermore, the step of constructing an initial three-dimensional model of the flywheel entity includes: constructing the initial three-dimensional model of the flywheel based on the mechanical properties, electrical properties, hydraulic properties, control properties and electromagnetic properties of the flywheel entity.

[0009] Furthermore, the sensor assembly is also used to detect the ambient temperature information and ambient air pressure information of the flywheel entity when the flywheel entity is in a stationary state; the flywheel digital twin is also used to simulate the material weathering state and oxidation state of the flywheel entity based on the ambient temperature information, ambient air pressure information, and the material properties of the flywheel entity.

[0010] Furthermore, the system also includes a display module, which is communicatively connected to the flywheel digital twin; the display module is used to display the flywheel digital twin when the flywheel entity is stationary; the display module is also used to display the simulation process of the flywheel digital twin in real time when the flywheel entity is running.

[0011] In the second aspect, an embodiment of the present invention provides a flywheel operation risk monitoring method, which is applied to any of the above-mentioned flywheel operation risk monitoring systems; the system includes a flywheel entity, an intelligent decision-making module and a flywheel digital twin that are communicatively connected to each other; a sensor component is arranged on the flywheel entity; the method includes: the sensor component detects the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and sends the initial operation data to the flywheel digital twin, and sends the real-time operation data to the intelligent decision-making module; the flywheel digital twin simulates the operation status of the flywheel entity throughout its life cycle according to the initial operation data, and sends the simulated operation data obtained by the simulation to the intelligent decision-making module; the intelligent decision-making module predicts the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjusts the operation control of the flywheel entity based on the operation risk.

[0012] Furthermore, the intelligent decision-making module predicts the operating risk of the flywheel entity based on the real-time operating data of the flywheel entity and the simulated operating data of its corresponding life cycle, and adjusts the operating control of the flywheel entity based on the operating risk. The steps also include: the intelligent decision-making module determines the target emergency measures corresponding to the operating risks based on the operating risks of the flywheel entity; and performs operation control of the flywheel entity according to the target emergency measures to ensure that the real-time operating data of the flywheel entity is consistent with the simulated operating data of its corresponding life cycle.

[0013] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method described above when executing the computer program.

[0014] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and the program code enables the processor to execute the method as described above.

[0015] An embodiment of the present invention provides a flywheel operation risk monitoring system and method, the system comprising: a flywheel entity, an intelligent decision-making module and a flywheel digital twin that are communicatively connected to each other; a sensor assembly is arranged on the flywheel entity; the sensor assembly is used to detect the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and send the initial operation data to the flywheel digital twin, and send the real-time operation data to the intelligent decision-making module; the flywheel digital twin is used to simulate the operation status of the flywheel entity throughout its life cycle according to the initial operation data, and send the simulated operation data obtained by the simulation to the intelligent decision-making module; the intelligent decision-making module is used to predict the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity based on the operation risk. In this method, the entire life cycle of the flywheel entity is simulated by constructing a flywheel digital twin, and the real-time operation data of the flywheel entity is compared with the simulation data obtained by simulation to determine the operation risk of the flywheel entity, and the operation of the flywheel entity is controlled based on the operation risk, thereby realizing the monitoring of the operation risk of the flywheel entity, thereby improving the safety of the flywheel entity operation and ensuring the service life of the flywheel entity.

[0016] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] 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.

[0019] Figure 1 A schematic diagram of a flywheel operation risk monitoring system provided in Embodiment 1 of the present invention;

[0020] Figure 2 A schematic diagram of another flywheel operation risk monitoring system provided in Embodiment 1 of the present invention;

[0021] Figure 3 A schematic diagram of the overall architecture of a flywheel digital twin provided in the second embodiment of the present invention;

[0022] Figure 4 This is a flow chart of a flywheel operation risk monitoring method provided in Embodiment 3 of the present invention.

[0023] Icons: 1-flywheel entity; 2-intelligent decision-making module; 3-flywheel digital twin; 4-sensor component. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] To facilitate understanding of this embodiment, the embodiment of the present invention is described in detail below.

[0026] Embodiment 1:

[0027] Figure 1 Schematic diagram of a flywheel operation risk monitoring system provided in Embodiment 1 of the present invention.

[0028] Figure 2 A schematic diagram of another flywheel operation risk monitoring system provided in Embodiment 1 of the present invention.

[0029] Reference Figure 1 and Figure 2The flywheel operation risk monitoring system includes a flywheel entity 1, an intelligent decision-making module 2 and a flywheel digital twin 3 which are communicatively connected to each other; a sensor component 4 is arranged on the flywheel entity 1.

[0030] The sensor component 4 is used to detect the initial operating data of the flywheel entity 1 at startup and the real-time operating data during operation, and send the initial operating data to the flywheel digital twin 3 and send the real-time operating data to the intelligent decision-making module 2.

[0031] Here, the sensor assembly includes a temperature sensor for collecting temperature data at various locations on the flywheel; a Hall sensor or a resolver sensor for collecting flywheel speed data; an electromagnetic bearing displacement sensor for collecting axial and radial displacements of the electromagnetic bearing in the flywheel, thereby determining the vibration data of the flywheel; an electromagnetic field measuring instrument for collecting electromagnetic field data of the flywheel; and a rotor displacement sensor for collecting rotor position data in the flywheel.

[0032] The initial operation data includes initial vacuum degree data, initial temperature data, initial rotation speed data, initial vibration data, initial electromagnetic field data and initial rotor position data of the flywheel entity.

[0033] The real-time operation data includes the operation vacuum data, operation temperature data, operation speed data, operation vibration data, operation electromagnetic field data and operation rotor position data of the flywheel entity.

[0034] The flywheel digital twin 3 is used to simulate the operating status of the flywheel entity 1 throughout its life cycle based on the initial operating data, and send the simulated operating data obtained by the simulation to the intelligent decision-making module 2.

[0035] Here, the intelligent decision-making module includes a simulation operation result database for storing simulation operation data sent after the flywheel digital twin performs a full life cycle simulation. In one embodiment, the flywheel digital twin is obtained by:

[0036] First, an initial 3D model of the flywheel entity is constructed.

[0037] Then, the initial operating data of the flywheel entity is used as input, and the real-time operating data of the flywheel entity during operation is used as output. The initial three-dimensional model is trained until the preset training conditions are met to obtain a trained flywheel digital twin.

[0038] Here, the steps to construct the initial 3D model of the flywheel entity include:

[0039] An initial 3D model of the flywheel is constructed based on the mechanical, electrical, hydraulic, control, and electromagnetic properties of the flywheel entity.

[0040] The intelligent decision-making module 2 is used to predict the operation risk of the flywheel entity 1 according to the real-time operation data of the flywheel entity 1 and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity 1 based on the operation risk.

[0041] Here, after receiving the real-time operation data sent by the flywheel entity, the intelligent decision-making module extracts the simulation operation data in the simulation operation result database, and compares the real-time operation data with the simulation operation data to predict the operation risk of the flywheel entity.

[0042] Furthermore, the intelligent decision-making module is also used to:

[0043] Based on the operational risk of the flywheel entity, the target emergency measures corresponding to the operational risk are determined.

[0044] The flywheel entity is operated and controlled according to the target emergency measures so that the real-time operation data of the flywheel entity is consistent with the simulation operation data of its corresponding life cycle.

[0045] Specifically, when the operating vacuum data is inconsistent with the simulated vacuum data, the intelligent decision module controls the vacuum pump of the flywheel entity to turn on or off, so that the operating vacuum data is consistent with the simulated vacuum data. When the operating temperature data is inconsistent with the simulated temperature data, the intelligent decision module controls the water cooling device of the flywheel entity to increase or decrease the water flow or the air cooling device to increase or decrease the wind speed, so that the operating temperature data is consistent with the simulated temperature data. When the operating speed data is inconsistent with the simulated speed data, the intelligent decision module controls the flywheel entity motor to increase or decrease the speed of the flywheel entity, so that the operating speed data is consistent with the simulated speed data. When the operating vibration data is inconsistent with the simulated vibration data, the intelligent decision module controls the electromagnetic bearing of the flywheel entity to make the operating vibration data consistent with the simulated vibration data. When the operating rotor position data is inconsistent with the simulated rotor position data, the intelligent decision control module generates an electromagnetic force equivalent to the rotor weight by adjusting the current of the control electromagnet winding, so that the rotor position data is consistent with the simulated rotor position data.

[0046] In one embodiment, the sensor assembly is further used to detect the ambient temperature information and ambient air pressure information of the flywheel entity when the flywheel entity is in a stationary state.

[0047] Here, the sensor assembly also includes an ambient temperature sensor and an ambient air pressure gauge. The ambient temperature sensor is used to measure the temperature data of the environment where the flywheel entity is located; the ambient air pressure gauge is used to measure the air pressure data of the environment where the flywheel entity is located.

[0048] The flywheel digital twin is also used to simulate the material weathering state and oxidation state of the flywheel entity based on ambient temperature information, ambient air pressure information, and material properties of the flywheel entity.

[0049] Here, the flywheel digital twin can simulate the material weathering state and oxidation state of the flywheel entity based on the pre-set material properties of the flywheel entity and the temperature data and air pressure data of the environment in which the flywheel entity is located.

[0050] In one embodiment, the system further comprises a display module, the display module being communicatively connected to the flywheel digital twin;

[0051] The display module is used to display the digital twin of the flywheel when the flywheel entity is stationary.

[0052] Here, when the flywheel entity is stationary, the display module will display the flywheel digital twin to simulate the weathering state and oxidation state of the flywheel entity material, so as to facilitate the staff to maintain and service the flywheel entity according to the simulated weathering and oxidation states.

[0053] The display module is also used to display the simulation process of the flywheel digital twin in real time when the flywheel entity is running.

[0054] Here, when the flywheel entity is running, the display module will display the full-cycle simulation process of the flywheel digital twin in real time, showing the operating status of the flywheel entity to the staff more intuitively.

[0055] The embodiment of the present invention provides a flywheel operation risk monitoring system, the system includes: a flywheel entity, an intelligent decision module and a flywheel digital twin that are connected to each other in communication; a sensor component is arranged on the flywheel entity; the sensor component is used to detect the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and send the initial operation data to the flywheel digital twin, and send the real-time operation data to the intelligent decision module; the flywheel digital twin is used to simulate the operation state of the flywheel entity throughout the life cycle according to the initial operation data, and send the simulated operation data obtained by the simulation to the intelligent decision module; the intelligent decision module is used to predict the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity based on the operation risk. In this method, the flywheel digital twin is constructed to simulate the entire life cycle of the flywheel entity, and the real-time operation data of the flywheel entity is compared with the simulation data obtained by the simulation to determine the operation risk of the flywheel entity, and the flywheel entity is operated and controlled based on the operation risk, so as to realize the monitoring of the operation risk of the flywheel entity, thereby improving the safety of the operation of the flywheel entity and ensuring the service life of the flywheel entity.

[0056] Embodiment 2:

[0057] Figure 3 Schematic diagram of the overall architecture of the flywheel digital twin provided in Example 2 of the present invention.

[0058] Reference Figure 3 ,The overall architecture is divided into four levels: flywheel data acquisition and entity control, flywheel digital twin core entity, user entity, and cross-domain entity.

[0059] Flywheel data collection and entity control, including flywheel data collection and flywheel control. Using perception, control, identification and other technologies, it undertakes the uplink perception data collection and downlink control command execution of the flywheel digital twin and the flywheel entity.

[0060] The core entities of the flywheel digital twin include flywheel modeling, simulation, data access and interaction, cloud computing, machine learning, and big data.

[0061] Here, the core entity of the flywheel digital twin is supported by general technology to realize functions such as model construction and fusion, data integration, simulation analysis, and system expansion. Since the flywheel digital twin needs to accurately express the state of the flywheel entity, it is critical to establish a suitable model. The Modelica modeling language can be used to establish the initial three-dimensional model of the flywheel entity according to the mechanical, electrical, hydraulic, control, and electromagnetic performance of the flywheel entity. Because the main function of the flywheel digital twin is to predict the operating status of the equipment during its life cycle, and the design is only for the flywheel entity, which belongs to the unit-level simulation, the ANSYS software can be used to simulate and calculate the mechanical structure and electromagnetic field distribution of the flywheel. Since the simulation of the operating status of the life cycle requires real-time processing of information, the timeliness of the simulation calculation is required to be high at one time, and cloud computing can also be used to provide sufficient computing power for simulation calculation. With ANSYS system software as the core, building a suitable model can more realistically reflect the actual operating status of the flywheel entity. Combined with cloud computing, the flywheel operating status can be simulated and predicted in real time. The initial three-dimensional model is trained through machine learning and continuously corrected until the preset training conditions are met, and a trained flywheel digital twin is obtained, and feedback control is performed.

[0062] User entities, including web visualization (HMI / WEB, human-machine interface / World Wide Web) and virtual visualization (AR / VR / XR, augmented reality / virtual reality / extended reality). Based on visualization and virtual display technology, the flywheel digital twin is displayed to achieve human-computer interaction.

[0063] Cross-domain entities, including data transmission and security protection. Responsible for data interoperability and security between entities.

[0064] The embodiment of the present invention provides a flywheel operation risk monitoring system, the system includes: a flywheel entity, an intelligent decision module and a flywheel digital twin that are connected to each other in communication; a sensor component is arranged on the flywheel entity; the sensor component is used to detect the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and send the initial operation data to the flywheel digital twin, and send the real-time operation data to the intelligent decision module; the flywheel digital twin is used to simulate the operation state of the flywheel entity throughout the life cycle according to the initial operation data, and send the simulated operation data obtained by the simulation to the intelligent decision module; the intelligent decision module is used to predict the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity based on the operation risk. In this method, the overall idea of ​​the flywheel digital twin is to use three-dimensional visualization technology to map the flywheel entity to the virtual world, and realize the monitoring of the flywheel entity through virtual-real interaction, so as to determine the operation risk of the flywheel entity, and adjust the operation control of the flywheel entity based on the operation risk, thereby improving the safety of the flywheel entity operation and ensuring the service life of the flywheel entity.

[0065] Embodiment three:

[0066] Figure 4 This is a flow chart of a flywheel operation risk monitoring method provided in Embodiment 3 of the present invention.

[0067] Reference Figure 4 The flywheel operation risk monitoring method is applied to any of the above flywheel operation risk monitoring systems, the system comprising a flywheel entity, an intelligent decision module and a flywheel digital twin that are communicatively connected to each other; a sensor component is arranged on the flywheel entity; the method comprises:

[0068] Step S101, the sensor component detects the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and sends the initial operation data to the flywheel digital twin, and sends the real-time operation data to the intelligent decision-making module.

[0069] In step S102, the flywheel digital twin performs a full life cycle simulation of the operating state of the flywheel entity according to the initial operating data, and sends the simulated operating data obtained by the simulation to the intelligent decision-making module.

[0070] Step S103, the intelligent decision-making module predicts the operating risk of the flywheel entity according to the real-time operating data of the flywheel entity and the simulated operating data of its corresponding life cycle, and adjusts the operating control of the flywheel entity based on the operating risk.

[0071] The embodiment of the present invention provides a flywheel operation risk monitoring method, the system includes: a flywheel entity, an intelligent decision module and a flywheel digital twin that are connected to each other in communication; a sensor component is arranged on the flywheel entity; the sensor component is used to detect the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and send the initial operation data to the flywheel digital twin, and send the real-time operation data to the intelligent decision module; the flywheel digital twin is used to simulate the operation state of the flywheel entity throughout the life cycle according to the initial operation data, and send the simulated operation data obtained by the simulation to the intelligent decision module; the intelligent decision module is used to predict the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity based on the operation risk. In this method, the flywheel digital twin is constructed to simulate the entire life cycle of the flywheel entity, and the real-time operation data of the flywheel entity is compared with the simulation data obtained by the simulation to determine the operation risk of the flywheel entity, and the operation control of the flywheel entity is performed based on the operation risk, so as to realize the monitoring of the operation risk of the flywheel entity, thereby improving the safety of the operation of the flywheel entity and ensuring the service life of the flywheel entity.

[0072] An embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the flywheel operation risk monitoring method provided in the above embodiment are implemented.

[0073] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the flywheel operation risk monitoring method of the above embodiment are executed.

[0074] The computer program product provided in the embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be found in the method embodiment and will not be repeated here.

[0075] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0076] In addition, in the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0077] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0078] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0079] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A flywheel operation risk monitoring system, characterized in that: The system comprises: a flywheel entity, an intelligent decision-making module and a flywheel digital twin that are communicatively connected to each other; a sensor component is arranged on the flywheel entity; The sensor component is used to detect the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and send the initial operation data to the flywheel digital twin, and send the real-time operation data to the intelligent decision-making module; The flywheel digital twin is used to simulate the operating state of the flywheel entity throughout its life cycle according to the initial operating data, and send the simulated operating data obtained by the simulation to the intelligent decision-making module; The intelligent decision-making module is used to predict the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjust the operation control of the flywheel entity based on the operation risk; wherein the real-time operation data includes operation vacuum data, operation temperature data, operation speed data, operation vibration data and operation rotor position data; the simulated operation data includes simulated vacuum data, simulated temperature data, simulated speed data, simulated vibration data and simulated rotor position data; the flywheel entity is provided with a vacuum pump, a water cooling device, an air cooling device, a flywheel entity motor, an electromagnetic bearing and an electromagnet winding; The intelligent decision-making module is also used to: determine the target emergency measures corresponding to the operation risk based on the operation risk of the flywheel entity; and control the operation of the flywheel entity according to the target emergency measures so that the real-time operation data of the flywheel entity is consistent with the simulation operation data of its corresponding life cycle; When the operating vacuum data is inconsistent with the simulated vacuum data, the vacuum pump is controlled to be turned on or off; when the operating temperature data is inconsistent with the simulated temperature data, the flow rate of the water cooling device or the wind speed of the air cooling device is controlled; when the operating speed data is inconsistent with the simulated speed data, the speed of the flywheel physical motor is controlled; when the operating vibration data is inconsistent with the simulated vibration data, the electromagnetic bearing is controlled; when the operating rotor position data is inconsistent with the simulated rotor position data, the electromagnetic force is controlled by adjusting the current of the electromagnet winding.

2. The flywheel operation risk monitoring system according to claim 1, characterized in that: The flywheel digital twin is obtained in the following way: Constructing an initial three-dimensional model of the flywheel entity; Taking the initial operation data of the flywheel entity as input and the real-time operation data of the flywheel entity during operation as output, the initial three-dimensional model is trained until the preset training conditions are met, thereby obtaining the trained flywheel digital twin; The initial operation data includes initial vacuum degree data, initial temperature data, initial rotation speed data, initial vibration data, initial electromagnetic field data and initial rotor position data of the flywheel entity; The real-time operation data includes operation vacuum degree data, operation temperature data, operation speed data, operation vibration data, operation electromagnetic field data and operation rotor position data of the flywheel entity.

3. The flywheel operation risk monitoring system according to claim 2, characterized in that: The step of constructing an initial three-dimensional model of the flywheel entity comprises: An initial three-dimensional model of the flywheel is constructed based on the mechanical properties, electrical properties, hydraulic properties, control properties and electromagnetic properties of the flywheel entity.

4. The flywheel operation risk monitoring system according to claim 1, characterized in that: The sensor assembly is also used to detect the ambient temperature information and ambient air pressure information of the flywheel entity when the flywheel entity is in a stationary state; The flywheel digital twin is also used to simulate the material weathering state and oxidation state of the flywheel entity according to the ambient temperature information, the ambient air pressure information, and the material properties of the flywheel entity.

5. The flywheel operation risk monitoring system according to claim 4, characterized in that: The system further comprises a display module, wherein the display module is communicatively connected to the flywheel digital twin; The display module is used to display the flywheel digital twin when the flywheel entity is stationary; The display module is also used to display the simulation process of the flywheel digital twin in real time when the flywheel entity is running.

6. A flywheel operation risk monitoring method, characterized in that: A flywheel operation risk monitoring system as described in any one of claims 1 to 5, wherein the system comprises a flywheel entity, an intelligent decision-making module and a flywheel digital twin that are communicatively connected to each other; A sensor assembly is arranged on the flywheel entity; the method comprises: The sensor component detects the initial operation data of the flywheel entity at startup and the real-time operation data during operation, and sends the initial operation data to the flywheel digital twin, and sends the real-time operation data to the intelligent decision-making module; The flywheel digital twin performs a full life cycle simulation on the operating state of the flywheel entity according to the initial operating data, and sends the simulated operating data obtained by the simulation to the intelligent decision-making module; The intelligent decision-making module predicts the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjusts the operation control of the flywheel entity based on the operation risk; wherein the real-time operation data includes operation vacuum data, operation temperature data, operation speed data, operation vibration data and operation rotor position data; the simulated operation data includes simulated vacuum data, simulated temperature data, simulated speed data, simulated vibration data and simulated rotor position data; the flywheel entity is provided with a vacuum pump, a water cooling device, an air cooling device, a flywheel entity motor, an electromagnetic bearing and an electromagnet winding; The intelligent decision module predicts the operation risk of the flywheel entity according to the real-time operation data of the flywheel entity and the simulated operation data of its corresponding life cycle, and adjusts the operation control of the flywheel entity based on the operation risk, and further includes: The intelligent decision-making module determines the target emergency measures corresponding to the operation risk based on the operation risk of the flywheel entity; and controlling the operation of the flywheel entity according to the target emergency measures so that the real-time operation data of the flywheel entity is consistent with the simulation operation data of its corresponding life cycle; When the operating vacuum data is inconsistent with the simulated vacuum data, the vacuum pump is controlled to be turned on or off; when the operating temperature data is inconsistent with the simulated temperature data, the flow rate of the water cooling device or the wind speed of the air cooling device is controlled; when the operating speed data is inconsistent with the simulated speed data, the speed of the flywheel physical motor is controlled; when the operating vibration data is inconsistent with the simulated vibration data, the electromagnetic bearing is controlled; when the operating rotor position data is inconsistent with the simulated rotor position data, the electromagnetic force is controlled by adjusting the current of the electromagnet winding.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the method according to claim 6 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program executes the steps of the method according to claim 6 when executed by a processing device.

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