A multi-flywheel automatic test monitoring system

Abstract

The present invention discloses a multi-flywheel automatic test monitoring system, the system comprising: a data acquisition module, for collecting information of a flywheel device to be tested, and real-time collection of operating parameters of the flywheel device to be tested; a data processing module, for preprocessing the operating parameters of the flywheel device to be tested; an evaluation module, for inputting the information of the flywheel device to be tested and the preprocessed operating parameters into a pre-trained fault diagnosis model for fault evaluation, and outputting evaluation results; a control module, for matching preset operating instructions based on the evaluation results of the fault diagnosis model. Through the processing scheme disclosed in the present invention, faults and problems in the system can be discovered in a timely manner, ensuring that the flywheel energy storage device always maintains good performance and reliability, extending service life, improving safety, and optimizing energy management.

Description

Technical Field

[0001] The invention relates to the technical field of flywheel energy storage, and in particular to a multi-flywheel automatic testing and monitoring system. Background Art

[0002] Flywheel energy storage is a type of energy storage that can release a large amount of energy in a short period of time. It is suitable for high-power, short-time application scenarios and is very important for power system stability and frequency regulation that requires fast response.

[0003] And with the continuous advancement of technology, the cost of flywheel energy storage is gradually reduced, and the performance is continuously improved, and its application prospects in the field of energy storage are becoming more and more broad. In the future, flywheel energy storage is expected to be widely used in more fields and contribute to the realization of a sustainable energy system.

[0004] However, there is currently no system that can comprehensively monitor the operating conditions of multiple flywheels in real time.

[0005] It can be seen that automatic detection of flywheel energy storage devices is crucial to ensuring their performance and reliability. How to create a multi-flywheel automatic testing and monitoring system has become a technology urgently needed in the industry. Summary of the invention

[0006] In view of this, an embodiment of the present disclosure provides a multi-flywheel automatic testing and monitoring system, which at least partially solves the problems existing in the prior art.

[0007] The present disclosure provides a multi-flywheel automatic test monitoring system, the system comprising:

[0008] A data acquisition module, used to acquire information of the flywheel device to be tested, and to acquire operating parameters of the flywheel device to be tested in real time;

[0009] A data processing module, used for preprocessing the operating parameters of the flywheel device to be tested;

[0010] An evaluation module, used for inputting the information of the flywheel device to be tested and the preprocessed operating parameters into a pre-trained fault diagnosis model to perform fault evaluation and output an evaluation result;

[0011] A control module is used to match preset operation instructions based on the evaluation result of the fault diagnosis model.

[0012] According to a specific implementation of the embodiment of the present disclosure, the data acquisition module includes: an information acquisition unit and a sensor unit;

[0013] Wherein, the information acquisition unit is used for the information of the flywheel device to be tested; the information of the flywheel device to be tested includes: geometric parameters, material properties and thermal properties of the flywheel rotor;

[0014] The sensor unit is used to collect the operating parameters and environmental parameters of the flywheel device to be tested in real time; the sensor unit includes: a speed sensor for measuring the speed of the flywheel rotor in the flywheel device to be tested; a vibration sensor for detecting the vibration of the flywheel device to be tested; a temperature sensor for monitoring the temperature of the flywheel device to be tested; a power sensor for measuring the charging and discharging power of the flywheel device to be tested; a humidity sensor for monitoring the humidity of the operating environment of the flywheel device to be tested; a sound sensor for monitoring the operating sound of the flywheel device to be tested; and a vacuum sensor for monitoring the vacuum degree of the operating environment of the flywheel device to be tested.

[0015] Wherein, the vibration sensor includes an acceleration sensor and a displacement sensor; the power sensor includes a voltage sensor and a current sensor.

[0016] According to a specific implementation of the embodiment of the present disclosure, the preprocessing of the operating parameters of the flywheel device to be tested includes:

[0017] Converting the analog signal data collected by the sensor unit into digital signal data;

[0018] The digital signal data is cleaned and normalized.

[0019] According to a specific implementation of the embodiment of the present disclosure, the evaluation module further includes: an energy storage capacity detection module, which is used to calculate the energy state of the flywheel device to be tested through the information of the flywheel device to be tested and the preprocessed operating parameters.

[0020] According to a specific implementation of the embodiment of the present disclosure, the energy storage capacity detection module obtains the charging and discharging power of the flywheel device to be tested based on the power sensor; calculates the energy change of the flywheel device to be tested based on the charging and discharging power; calculates the energy state of the flywheel device to be tested based on the energy change of the flywheel device to be tested;

[0021] The energy change is calculated by the following formula:

[0022] Energy changes during charging process:

[0023] Energy changes during discharge process:

[0024] Energy state of the flywheel device to be tested:

[0025] in, Energy change during the charging process; is the charging efficiency, and ; is the charging power; For charging time; is the energy change during the discharge process; is the discharge efficiency, and ; is the discharge power; is the discharge time; is the energy state of the flywheel device to be tested.

[0026] According to a specific implementation of the embodiment of the present disclosure, the energy state of the flywheel device to be tested is calculated by using the information of the flywheel device to be tested and the preprocessed operating parameters, further comprising:

[0027] The energy change of the flywheel device to be tested is calculated by the following formula:

[0028]

[0029] in, is the energy change of the flywheel device to be tested; is the rotational inertia of the flywheel rotor in the flywheel device to be tested; is the angular velocity of the flywheel rotor in the flywheel device to be tested, and the angular velocity is obtained by rotating speed conversion.

[0030] According to a specific implementation of the embodiment of the present disclosure, the moment of inertia of the flywheel rotor in the flywheel device to be tested is obtained based on the information of the flywheel device to be tested; wherein, when the flywheel device to be tested is not marked with the moment of inertia, the shape of the flywheel rotor in the flywheel device to be tested is obtained;

[0031] Wherein, when the flywheel rotor is a solid cylinder, the moment of inertia of the flywheel rotor in the flywheel device to be tested is calculated by the following formula:

[0032]

[0033] in, is the moment of inertia of the solid cylindrical flywheel rotor; is the mass of the flywheel, is the radius of the flywheel;

[0034] When the flywheel rotor is in a circular ring shape, the moment of inertia of the flywheel rotor in the flywheel device to be tested is calculated by the following formula:

[0035]

[0036] in, is the moment of inertia of the annular flywheel rotor; is the mass of the flywheel, is the outer radius of the ring.

[0037] According to a specific implementation of the embodiment of the present disclosure, the information of the flywheel device to be tested and the preprocessed operating parameters are input into a pre-trained fault diagnosis model for fault assessment, and the assessment result is output, including:

[0038] Inputting information of the flywheel device to be tested and preprocessed operating parameters into a pre-trained fault diagnosis model;

[0039] The pre-trained fault diagnosis model is matched based on the information of the flywheel device to be tested to obtain a preset normal operating parameter range of the flywheel device to be tested;

[0040] The pre-trained fault diagnosis model determines the pre-processed operating parameters based on the preset normal operating parameter interval range;

[0041] Among them, when the pre-processed operating parameters are within the preset normal operating parameter range, it is determined that the flywheel device to be tested is operating normally; when the pre-processed operating parameters exceed the preset normal operating parameter range, the risk level is scored; wherein, when the risk level score is within the threshold range, the fault diagnosis model automatically selects to execute the solution corresponding to the fault type according to the pre-given authority, and issues a fault prompt; when the risk level score exceeds the threshold range, the fault diagnosis model sends an alarm signal through the alarm device, stops running and waits for manual processing.

[0042] According to a specific implementation of the embodiment of the present disclosure, the pre-trained fault diagnosis model includes:

[0043] Acquire historical operation data and fault data of flywheels of different models as training data; wherein the fault data is data pre-classified according to the risk level of the fault;

[0044] The training data is divided into a training set, a validation set, and a test set in a ratio of 6:3:1;

[0045] The training set is input into the fault diagnosis model for training. During the training process, the model parameters are adjusted and the performance of the model is monitored through the validation set until the preset accuracy is met. The finalized model is verified using the test set data.

[0046] According to a specific implementation method of an embodiment of the present disclosure, a monitoring module; the monitoring module includes a display screen and an alarm device, the display screen is used to display the operating status and operating data of the flywheel device to be tested in the form of graphics, charts and / or numerical values; the alarm device is used to emit an audible and visual alarm signal when the risk level score exceeds a preset threshold.

[0047] The multi-flywheel automatic test and monitoring system in the disclosed embodiment can monitor various types of flywheel devices in real time, promptly detect faults and problems in the system, and ensure that the flywheel energy storage device always maintains good performance and reliability, which is essential to ensure the continuous operation of key equipment and the stability of the power system. At the same time, by detecting and promptly handling potential problems, damage to the system can be reduced, the service life of the flywheel energy storage device can be extended, and maintenance costs can be reduced and the return on investment can be improved. It is also possible to promptly detect safety hazards such as overheating, overvoltage, overcurrent, etc., and take corresponding protective measures to ensure the safety of personnel and equipment. In addition, by detecting the energy storage capacity and energy status, optimized energy management of the flywheel energy storage device can be achieved, which helps to improve energy utilization efficiency, reduce energy costs, and provide better support for the integration of renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram of a multi-flywheel automatic testing and monitoring system provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0049] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0050] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0051] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement a device and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0052] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0053] The embodiment of the present invention provides a multi-flywheel automatic test and monitoring system, which can timely discover faults and problems in the system by automatically monitoring the operating data of the flywheel device in real time, ensuring that the flywheel energy storage device always maintains good performance and reliability. This is crucial to ensure the continuous operation of key equipment and the stability of the power system.

[0054] Figure 1 A schematic diagram of a multi-flywheel automatic testing and monitoring system provided in an embodiment of the present disclosure.

[0055] like Figure 1 As shown, the multi-flywheel automatic test and monitoring system proposed in the present invention includes: a data acquisition module, used to collect information of the flywheel device to be tested, and real-time collection of operating parameters of the flywheel device to be tested; a data processing module, used to pre-process the operating parameters of the flywheel device to be tested; an evaluation module, used to input the information of the flywheel device to be tested and the pre-processed operating parameters into a pre-trained fault diagnosis model for fault evaluation, and output an evaluation result; a control module, used to match preset operating instructions based on the evaluation result of the fault diagnosis model.

[0056] In an embodiment of the present invention, the data acquisition module includes: an information acquisition unit and a sensor unit; wherein the information acquisition unit is used for information of the flywheel device to be tested; the information of the flywheel device to be tested includes: geometric parameters, material properties and thermal properties of the flywheel rotor; the sensor unit is used to collect the operating parameters and environmental parameters of the flywheel device to be tested in real time; the sensor unit includes: a speed sensor for measuring the speed of the flywheel rotor in the flywheel device to be tested; a vibration sensor for detecting the vibration of the flywheel device to be tested; a temperature sensor for monitoring the temperature of the flywheel device to be tested; a power sensor for measuring the charging and discharging power of the flywheel device to be tested; a humidity sensor for monitoring the humidity of the operating environment of the flywheel device to be tested; a sound sensor for monitoring the operating sound of the flywheel device to be tested; a vacuum sensor for monitoring the vacuum degree of the operating environment of the flywheel device to be tested; wherein the vibration sensor includes an acceleration sensor and a displacement sensor; the power sensor includes a voltage sensor and a current sensor.

[0057] The information of the flywheel device to be tested mainly includes the following aspects: geometric parameters (such as shape, size, mass, etc.), material properties (such as density, strength, elastic modulus, Poisson's ratio, etc.), thermal properties (such as heat capacity, thermal conductivity, temperature distribution, etc.).

[0058] More specifically, the data detected by the sensor can reflect the operating status and possible problems of the flywheel device in real time. The rotation speed of the flywheel can be monitored in real time by the speed sensor to ensure that it is within the normal working range. Abnormal speed may indicate that there is a fault in the system, such as motor failure, transmission system problem, etc. The vibration sensor can detect the vibration of the flywheel during operation. Excessive vibration may be caused by flywheel imbalance, bearing damage or improper installation, which may affect the stability and life of the system. The temperature of the flywheel, motor and other key components is monitored by the temperature sensor. Excessive temperature may indicate that the system has an overheating problem, which may be caused by friction, overload or poor heat dissipation. The input power (or charging power) and output power (or discharging power) of the flywheel energy storage device are measured by the power sensor, which can confirm the energy conversion efficiency of the flywheel device under different working conditions. The input and output voltages and currents are monitored by the voltage sensor and the current sensor to ensure that they are within the safe range, and whether there are electrical faults, such as short circuits and open circuits, can be detected.

[0059] In an embodiment of the present invention, the preprocessing of the operating parameters of the flywheel device to be tested includes: converting the analog signal data collected by the sensor unit into digital signal data; cleaning the digital signal data and performing normalization processing.

[0060] More specifically, data cleaning includes: identifying outliers, observing the distribution of data, marking data points that are obviously deviated from the normal range, for example, the flywheel speed has extremely high or extremely low values, the temperature exceeds the reasonable range, etc., and statistical methods can be used to identify outliers, such as calculating the mean, median and standard deviation, and treating data points that exceed a certain multiple of the standard deviation as outliers; processing outliers: eliminating outliers: if the number of outliers is small and the impact on the overall data is small, they can be directly deleted from the data set; replacing outliers: using a reasonable method to replace outliers. For example, outliers can be replaced with values ​​calculated by the mean, median or interpolation method; processing missing values: checking whether there are missing values ​​in the data set. Missing values ​​may be caused by sensor failure, data transmission problems, etc. For a small number of missing values, interpolation can be used to fill them. Common interpolation methods include linear interpolation, polynomial interpolation, spline interpolation, etc. If there are many missing values, model-based methods can be used to fill them, such as using regression models or machine learning algorithms to predict missing values ​​based on other variables. This is not limited by the present invention.

[0061] In an embodiment of the present invention, the evaluation module further includes: an energy storage capacity detection module, which is used to calculate the energy state of the flywheel device to be tested through the information of the flywheel device to be tested and the pre-processed operating parameters.

[0062] More specifically, the energy storage capacity detection module obtains the charging and discharging power of the flywheel device to be tested based on the power sensor; calculates the energy change of the flywheel device to be tested based on the charging and discharging power; calculates the energy state of the flywheel device to be tested based on the energy change of the flywheel device to be tested;

[0063] The energy change is calculated by the following formula:

[0064] Energy changes during charging process: …………Formula 1

[0065] Energy changes during discharge process: …………Formula 2

[0066] Energy state of the flywheel device to be tested: …………Formula 3

[0067] in, Energy change during the charging process; is the charging efficiency, and ; is the charging power; For charging time; is the energy change during the discharge process; is the discharge efficiency, and ; is the discharge power; is the discharge time; is the energy state of the flywheel device to be tested.

[0068] More specifically, the charging efficiency measurement includes the following steps:

[0069] Connect the flywheel unit to a charging source to start the charging process.

[0070] Use a power meter to measure the power output of the charging power source .

[0071] At the same time, the input power of the flywheel device is monitored (Calculated by measuring voltage and current).

[0072] Charging time Can be recorded by timer.

[0073] Charging efficiency …………Formula 4.

[0074] The discharge efficiency measurement includes the following steps:

[0075] Connect the fully charged flywheel unit to the discharge load to start the discharge process.

[0076] Measuring the power output of a flywheel device .

[0077] At the same time, the actual power consumed by the discharge load is monitored .

[0078] Discharge time Also record with a timer.

[0079] Discharge efficiency …………Formula 5.

[0080] In order to improve the accuracy, multiple charging and discharging experiments can be carried out and the average value can be taken as the final charging efficiency and discharging efficiency.

[0081] Estimating the current energy storage capacity of the flywheel energy storage device through energy status monitoring can help users understand the available energy of the system and perform reasonable energy management.

[0082] In an embodiment of the present invention, the step of calculating the energy state of the flywheel device to be tested by using the information of the flywheel device to be tested and the preprocessed operating parameters further includes:

[0083] The energy change of the flywheel device to be tested is calculated by the following formula:

[0084] …………Formula 6

[0085] in, is the energy change of the flywheel device to be tested; is the rotational inertia of the flywheel rotor in the flywheel device to be tested; is the angular velocity of the flywheel rotor in the flywheel device to be tested, and the angular velocity is obtained by rotating speed conversion.

[0086] The moment of inertia of the flywheel rotor in the flywheel device to be tested is obtained based on the information of the flywheel device to be tested; wherein, when the moment of inertia of the flywheel device to be tested is not marked, the shape of the flywheel rotor in the flywheel device to be tested is obtained.

[0087] Wherein, when the flywheel rotor is a solid cylinder, the moment of inertia of the flywheel rotor in the flywheel device to be tested is calculated by the following formula:

[0088] …………Formula 7

[0089] in, is the moment of inertia of the solid cylindrical flywheel rotor; is the mass of the flywheel, is the radius of the flywheel.

[0090] When the flywheel rotor is in a circular ring shape, the moment of inertia of the flywheel rotor in the flywheel device to be tested is calculated by the following formula:

[0091] …………Formula 8

[0092] in, is the moment of inertia of the annular flywheel rotor; is the mass of the flywheel, is the outer radius of the ring.

[0093] Based on the energy storage capacity of the flywheel device to be tested Energy changes during charging and discharging and Verify, when the error value is less than the preset error, it is considered and Accurate; when the error value is greater than the preset error, the flywheel device to be tested is adjusted based on the data displayed by the monitoring module.

[0094] In an embodiment of the present invention, the information of the flywheel device to be tested and the preprocessed operating parameters are input into a pretrained fault diagnosis model for fault assessment, and the assessment result is output, including: inputting the information of the flywheel device to be tested and the preprocessed operating parameters into the pretrained fault diagnosis model; the pretrained fault diagnosis model performs matching based on the information of the flywheel device to be tested, and obtains a preset normal operating parameter interval range of the flywheel device to be tested; the pretrained fault diagnosis model determines the preprocessed operating parameters based on the preset normal operating parameter interval range; wherein, when the preprocessed operating parameters are within the preset normal operating parameter interval range, it is determined that the flywheel device to be tested is operating normally; when the preprocessed operating parameters exceed the preset normal operating parameter interval range, the risk level is scored; wherein, when the risk level score is within the threshold range, the fault diagnosis model automatically selects to execute the solution corresponding to the fault type according to the pre-given authority, and gives a fault prompt; when the risk level score exceeds the threshold range, the fault diagnosis model sends an alarm signal through the alarm device, stops running and waits for manual processing, and outputs the fault type and recommends a solution.

[0095] In an embodiment of the present invention, the system also includes: a monitoring module; the monitoring module includes a display screen and an alarm device, the display screen is used to display the operating status and operating data of the flywheel device to be tested in the form of graphics, charts and / or numerical values; the alarm device is used to emit an audible and visual alarm signal when the risk level score exceeds a preset threshold.

[0096] In an embodiment of the present invention, a pre-trained fault diagnosis model includes: obtaining historical operating data and fault data of flywheels of different models as training data; wherein the fault data is data pre-classified according to the risk level of the fault; dividing the training data into a training set, a validation set and a test set in a ratio of 6:3:1; inputting the training set into the fault diagnosis model for training; during the training process, adjusting the model parameters and monitoring the performance of the model through the validation set until it meets the preset accuracy; and using the test set data to verify the final model.

[0097] More specifically, the collected data is divided into training set, validation set and test set. The training set is used for model learning and parameter adjustment, the validation set is used to evaluate model performance and select the best hyperparameters during training, and the test set is used to finally evaluate the generalization ability of the model. The model is trained using the training set data, and the loss function is minimized by continuously adjusting the model's parameters. During the training process, the validation set is used to monitor the performance of the model to avoid overfitting.

[0098] When dividing the data set, we must ensure the independence of the data, that is, there is no overlap between the data sets to avoid overfitting the model to a specific data subset.

[0099] The multi-flywheel automatic test and monitoring system proposed in the present invention can monitor various types of flywheel devices in real time, promptly detect faults and problems in the system, and ensure that the flywheel energy storage device always maintains good performance and reliability, which is essential for ensuring the continuous operation of key equipment and the stability of the power system. At the same time, by detecting and promptly dealing with potential problems, damage to the system can be reduced, the service life of the flywheel energy storage device can be extended, and maintenance costs can be reduced and the return on investment can be improved. It is also possible to promptly detect safety hazards such as overheating, overvoltage, overcurrent, etc., and take corresponding protective measures to ensure the safety of personnel and equipment. In addition, by detecting the energy storage capacity and energy status, optimized energy management of the flywheel energy storage device can be achieved, which helps to improve energy utilization efficiency, reduce energy costs, and provide better support for the integration of renewable energy.

[0100] The above is only a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present disclosure should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A multi-flywheel automatic test monitoring system, characterized in that: The system comprises: A data acquisition module, for acquiring information of the flywheel device to be tested, and acquiring operating parameters of the flywheel device to be tested in real time; the data acquisition module comprises: an information acquisition unit and a sensor unit; wherein the information acquisition unit is used for acquiring information of the flywheel device to be tested; the information of the flywheel device to be tested comprises: geometric parameters, material properties and thermal properties of the flywheel rotor; the sensor unit is used for acquiring operating parameters and environmental parameters of the flywheel device to be tested in real time; the sensor unit comprises: a speed sensor, for measuring the speed of the flywheel rotor in the flywheel device to be tested; a vibration sensor, for detecting the vibration of the flywheel device to be tested; a temperature sensor, for monitoring the temperature of the flywheel device to be tested; a power sensor, for measuring the charging and discharging power of the flywheel device to be tested; a humidity sensor, for monitoring the humidity of the operating environment of the flywheel device to be tested; a sound sensor, for monitoring the operating sound of the flywheel device to be tested; a vacuum sensor, for monitoring the vacuum degree of the operating environment of the flywheel device to be tested; wherein the vibration sensor comprises an acceleration sensor and a displacement sensor; the power sensor comprises a voltage sensor and a current sensor; A data processing module, used for preprocessing the operating parameters of the flywheel device to be tested; An evaluation module, used for inputting the information of the flywheel device to be tested and the preprocessed operating parameters into a pre-trained fault diagnosis model to perform fault evaluation and output an evaluation result; A control module, used for matching preset operation instructions based on the evaluation result of the fault diagnosis model; An energy storage capacity detection module, used to calculate the energy state of the flywheel device to be tested through the information of the flywheel device to be tested and the pre-processed operating parameters; The energy storage capacity detection module obtains the charging and discharging power of the flywheel device to be tested based on the power sensor; calculates the energy change of the flywheel device to be tested based on the charging and discharging power; and calculates the energy state of the flywheel device to be tested based on the energy change of the flywheel device to be tested; The energy change is calculated by the following formula: Energy changes during charging process: Energy changes during discharge process: Energy state of the flywheel device to be tested: ΔE = ΔE charge +ΔE discharge Where, ΔE charge is the energy change during the charging process; η charge is the charging efficiency, and η charge <1; P charge is the charging power; t1 is the charging time; ΔE discharge is the energy change during the discharge process; η discharge is the discharge efficiency, and η discharge <1; P discharge is the discharge power; t2 is the discharge time; ΔE is the energy state of the flywheel device to be tested; The step of calculating the energy state of the flywheel device to be tested by using the information of the flywheel device to be tested and the preprocessed operating parameters also includes: The energy change of the flywheel device to be tested is calculated by the following formula: Wherein, E is the energy change of the flywheel device to be tested; I is the moment of inertia of the flywheel rotor in the flywheel device to be tested; ω is the angular velocity of the flywheel rotor in the flywheel device to be tested, and the angular velocity is obtained by speed conversion; Based on the information of the flywheel device to be tested, the moment of inertia of the flywheel rotor in the flywheel device to be tested is obtained; wherein, when the flywheel device to be tested is not marked with the moment of inertia, the shape of the flywheel rotor in the flywheel device to be tested is obtained; Wherein, when the flywheel rotor is a solid cylinder, the moment of inertia of the flywheel rotor in the flywheel device to be tested is calculated by the following formula: Where, I1 is the moment of inertia of the solid cylindrical flywheel rotor; m is the mass of the flywheel, and r is the radius of the flywheel; When the flywheel rotor is in a circular ring shape, the moment of inertia of the flywheel rotor in the flywheel device to be tested is calculated by the following formula: I2=mR 2 Where I2 is the moment of inertia of the annular flywheel rotor; m is the mass of the flywheel, and R is the outer radius of the annular ring; Energy change ΔE during the charging and discharging process based on the energy storage capacity E of the flywheel device to be tested charge and ΔE discharge Verify that when the error value is less than the preset error, it is considered that ΔE charge and ΔE discharge Accurate; when the error value is greater than the preset error, the flywheel device to be tested is adjusted based on the data displayed by the monitoring module.

2. The multi-flywheel automatic test monitoring system according to claim 1, characterized in that: The preprocessing of the operating parameters of the flywheel device to be tested includes: Converting the analog signal data collected by the sensor unit into digital signal data; The digital signal data is cleaned and normalized.

3. The multi-flywheel automatic test monitoring system according to claim 1, characterized in that: The step of inputting the information of the flywheel device to be tested and the preprocessed operating parameters into a pretrained fault diagnosis model for fault assessment and outputting the assessment result comprises: Inputting information of the flywheel device to be tested and preprocessed operating parameters into a pre-trained fault diagnosis model; The pre-trained fault diagnosis model is matched based on the information of the flywheel device to be tested to obtain a preset normal operating parameter range of the flywheel device to be tested; The pre-trained fault diagnosis model determines the pre-processed operating parameters based on the preset normal operating parameter interval range; Among them, when the pre-processed operating parameters are within the preset normal operating parameter range, it is determined that the flywheel device to be tested is operating normally; when the pre-processed operating parameters exceed the preset normal operating parameter range, the risk level is scored; wherein, when the risk level score is within the threshold range, the fault diagnosis model automatically selects to execute the solution corresponding to the fault type according to the pre-given authority, and issues a fault prompt; when the risk level score exceeds the threshold range, the fault diagnosis model sends an alarm signal through the alarm device, stops running and waits for manual processing.

4. The multi-flywheel automatic test monitoring system according to claim 3, characterized in that: Pre-trained fault diagnosis models include: Acquire historical operation data and fault data of flywheels of different models as training data; wherein the fault data is data pre-classified according to the risk level of the fault; The training data is divided into a training set, a validation set, and a test set in a ratio of 6:3:1; The training set is input into the fault diagnosis model for training. During the training process, the model parameters are adjusted and the performance of the model is monitored through the validation set until the preset accuracy is met. The finalized model is verified using the test set data.

5. The multi-flywheel automatic test monitoring system according to any one of claims 1 to 4, characterized in that: The system also includes: a monitoring module; the monitoring module includes a display screen and an alarm device, the display screen is used to display the operating status and operating data of the flywheel device to be tested in the form of graphics, charts and / or numerical values; the alarm device is used to emit an audible and visual alarm signal when the risk level score exceeds a preset threshold.

Images