Medical power supply active safety control method and device based on digital twinning and storage medium

Abstract

A medical power supply active safety control method and device based on digital twinning and a storage medium, the method comprising: collecting environmental parameters and electrical stress parameters of the power supply system in real time and recording historical stress time; injecting a diagnostic signal into the isolation barrier and synchronously monitoring the response of the diagnostic signal to calculate the current equivalent insulation impedance value of the isolation barrier; inputting the equivalent insulation impedance value and the environmental parameters into a pre-constructed digital twinning model to dynamically correct the aging rate parameter, so that the digital twinning model is synchronized with the physical entity of the medical power supply; using the corrected digital twinning model, combining the electrical stress parameters and the historical stress time to predict the remaining life of the isolation barrier; according to the comparison result of the remaining life and the preset threshold, executing the corresponding active safety control strategy. The method realizes the leap from power-off after failure to intervention before failure, provides data support for predictive maintenance, and reduces operation and maintenance cost.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of medical power supply management, and particularly relates to a medical power supply active safety control method based on digital twinning, a device and a storage medium. BACKGROUND

[0002] In the current safety management practice of medical power supply, it mainly relies on periodic manual detection methods, such as detection of insulation resistance, or passive leakage protection measures. However, these methods have obvious limitations, they often have a lag, and cannot perceive the aging trend of the isolation barrier in real time. In addition, these traditional methods lack the ability to predict potential failure risks, so it is difficult to issue timely warning signals in the early stage of insulation performance degradation. Further, due to the lack of precise life prediction means, it is currently difficult to implement active safety control measures based on prediction results, which to some extent limits the safety and reliability of the medical power supply system. SUMMARY

[0003] Therefore, the embodiments of the present application provide a medical power supply active safety control method based on digital twinning, a device and a storage medium, aiming to solve the core technical problem that the health status of the medical power supply isolation barrier lacks real-time and accurate predictive management, and cannot change passive protection to active prevention.

[0004] The first aspect of the embodiments of the present application provides a medical power supply active safety control method based on digital twinning, the method comprising:

[0005] Real-time collection of environmental parameters and electrical stress parameters of the power supply system and recording of historical stress time;

[0006] Injecting a diagnostic signal into the isolation barrier and synchronously monitoring the response of the diagnostic signal, calculating the current equivalent insulation impedance value of the isolation barrier;

[0007] Inputting the equivalent insulation impedance value and the environmental parameters into the pre-constructed digital twin model to dynamically correct the aging rate parameters, so that the digital twin model is synchronized with the physical entity of the medical power supply;

[0008] Using the corrected digital twin model, combining the electrical stress parameters and the historical stress time, predicting the remaining life of the isolation barrier;

[0009] According to the comparison result of the remaining life and the preset threshold, a corresponding active safety control strategy is executed.

[0010] In one embodiment, the environmental parameters include ambient temperature and relative humidity; the electrical stress parameters include real-time acquired input voltage, output voltage, and operating frequency; and the historical stress time is the cumulative operating time of the power supply system.

[0011] In one embodiment, injecting a diagnostic signal into the isolation barrier and simultaneously monitoring the response of the diagnostic signal to calculate the current equivalent insulation impedance value of the isolation barrier includes:

[0012] A specific high-frequency, low-amplitude diagnostic signal is periodically injected by the power controller into the primary side of the isolation barrier;

[0013] The response of the diagnostic signal is detected on the secondary side of the isolation barrier, and the current equivalent insulation impedance value of the isolation barrier is calculated by analyzing the attenuation amplitude and phase change of the response.

[0014] In one embodiment, the step of dynamically correcting the aging rate parameters by inputting the equivalent insulation resistance value and the environmental parameters into a pre-constructed digital twin model includes:

[0015] The equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters inside the digital twin model.

[0016] In one embodiment, the adaptive algorithm is a Kalman filter; the equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters within the digital twin model, including:

[0017] The equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model. Using the state update and measurement update mechanism of the Kalman filter, the equivalent insulation impedance value is used as an observation variable, and the ambient temperature and relative humidity are used as part of the state variables or as adjustment factors for process noise. The state variables characterizing the aging rate of the insulation material in the digital twin model are estimated to achieve dynamic correction of the aging rate parameter.

[0018] In one embodiment, predicting the remaining lifetime of the isolation barrier using the corrected digital twin model, combined with the electrical stress parameters and the historical stress time, includes:

[0019] Starting from the aging state under the accumulated historical stress time, the electrical stress parameters are used as the stress conditions for continuous action. They are input into the corrected digital twin model for iterative calculation to deduce the change trend of the equivalent insulation impedance value of the isolation barrier over time.

[0020] The calculation terminates when the equivalent insulation resistance value drops to a preset safety threshold; the future time length simulated by the iterative calculation is the predicted remaining lifetime of the isolation barrier.

[0021] In one embodiment, executing a corresponding proactive safety control strategy based on the comparison result of the remaining lifetime and a preset threshold includes:

[0022] When the remaining lifespan is greater than the first preset threshold, the system is determined to be in normal condition and the power supply is controlled to run at full power.

[0023] When the remaining lifespan is greater than the second preset threshold and less than or equal to the first threshold, a level one warning is triggered, and maintenance warning information is sent to the cloud management platform or user interface.

[0024] When the remaining lifespan is less than or equal to the second preset threshold, a level-two warning is triggered and a level-two active response is initiated.

[0025] A second aspect of this application provides a medical power supply active safety control device based on digital twins, the device comprising:

[0026] The acquisition module is used to acquire environmental parameters and electrical stress parameters of the power system in real time and record historical stress times;

[0027] The monitoring module is used to inject diagnostic signals into the isolation barrier, simultaneously monitor the response of the diagnostic signals, and calculate the current equivalent insulation resistance value of the isolation barrier.

[0028] The calibration module is used to dynamically calibrate the aging rate parameters by inputting the equivalent insulation impedance value and the environmental parameters into a pre-built digital twin model, so that the digital twin model is synchronized with the physical entity of the medical power supply.

[0029] The prediction module is used to predict the remaining life of the isolation barrier by using the corrected digital twin model, combined with the electrical stress parameters and the historical stress time.

[0030] The execution module is used to execute corresponding proactive safety control strategies based on the comparison result between the remaining lifespan and the preset threshold.

[0031] In one embodiment, the environmental parameters include ambient temperature and relative humidity; the electrical stress parameters include real-time acquired input voltage, output voltage, and operating frequency; and the historical stress time is the cumulative operating time of the power supply system.

[0032] In one embodiment, the monitoring module includes:

[0033] An injection unit is used to periodically inject a specific high-frequency, low-amplitude diagnostic signal into the primary side of the isolation barrier by the power controller;

[0034] A detection unit is used to detect the response of the diagnostic signal on the secondary side of the isolation barrier, and calculate the current equivalent insulation impedance value of the isolation barrier by analyzing the attenuation amplitude and phase change of the response.

[0035] In one embodiment, the correction module is specifically used for:

[0036] The equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters inside the digital twin model.

[0037] In one embodiment, the adaptive algorithm is a Kalman filter; the correction module is specifically used for:

[0038] The equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model. Using the state update and measurement update mechanism of the Kalman filter, the equivalent insulation impedance value is used as an observation variable, and the ambient temperature and relative humidity are used as part of the state variables or as adjustment factors for process noise. The state variables characterizing the aging rate of the insulation material in the digital twin model are estimated to achieve dynamic correction of the aging rate parameter.

[0039] In one embodiment, the prediction module includes:

[0040] The input unit is used to take the aging state under the historical stress time accumulation as the starting point, take the electrical stress parameters as the stress conditions of continuous action, input them into the corrected digital twin model for iterative calculation, and deduce the change trend of the equivalent insulation impedance value of the isolation barrier over time.

[0041] The calculation unit is used to terminate the calculation when the equivalent insulation resistance value drops to a preset safety threshold; the future time length simulated by the iterative calculation is the predicted remaining lifetime of the isolation barrier.

[0042] In one embodiment, the execution module includes:

[0043] The determination unit is used to determine that the system is in normal condition and control the power supply to run at full power when the remaining lifespan is greater than a first preset threshold.

[0044] The first triggering unit is used to trigger a level one warning and send maintenance warning information to the cloud management platform or user interface when the remaining lifespan is greater than the second preset threshold and less than or equal to the first threshold.

[0045] The second triggering unit is used to trigger a secondary warning and initiate a secondary active response when the remaining lifespan is less than or equal to the second preset threshold.

[0046] A third aspect of this application provides a medical power supply active safety control device based on digital twins, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor; the processor executes the computer program to implement the method described in the first aspect above.

[0047] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0048] This application provides a digital twin-based active safety control method for medical power supplies. The method includes: real-time acquisition of environmental parameters and electrical stress parameters of the power system and recording historical stress times; injecting diagnostic signals into an isolation barrier and simultaneously monitoring the response of the diagnostic signals to calculate the current equivalent insulation resistance value of the isolation barrier; dynamically correcting the aging rate parameters of the equivalent insulation resistance value and the environmental parameters into a pre-constructed digital twin model, synchronizing the digital twin model with the physical entity of the medical power supply; predicting the remaining lifespan of the isolation barrier using the corrected digital twin model, combined with the electrical stress parameters and the historical stress times; and executing a corresponding active safety control strategy based on the comparison result of the remaining lifespan with a preset threshold. By integrating digital twin dynamic correction and active signal injection monitoring, this invention achieves high-precision remaining lifespan prediction and executes a tiered active safety strategy accordingly. This addresses the core technical problem of the lack of real-time, accurate predictive management of the health status of medical power supply isolation barriers, which prevents the transformation from passive protection to proactive prevention. It significantly improves the reliability and safety of medical power supplies, enabling a leap from power outages after a failure to intervention before failure, while providing data support for predictive maintenance and reducing operation and maintenance costs. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 A schematic diagram of a digital twin-based active safety control process for medical power supplies is provided as an embodiment of this application.

[0051] Figure 2 for Figure 1 A schematic diagram illustrating the specific implementation process of S120 in China;

[0052] Figure 3 A schematic diagram of a medical power supply active safety control device based on digital twin provided in an embodiment of this application;

[0053] Figure 4 This is a schematic diagram of a digital twin-based active safety control device for medical power supplies, provided as an embodiment of this application. Detailed Implementation

[0054] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0056] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0057] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0058] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0059] In the description of the embodiments of this application, the term "multiple frames" refers to two or more (including two).

[0060] In the description of the embodiments of this application, the technical terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0061] Please see Figure 1 , Figure 1 This is a schematic flowchart illustrating an embodiment of active safety control for medical power supplies based on digital twins. The active safety control method for medical power supplies based on digital twins is implemented by an active safety control device for medical power supplies based on digital twins. This device can be a medical power supply unit, which has built-in hardware and software. Specifically, it can be implemented by a microcontroller unit (MCU) and its peripheral circuits, or it can be implemented collaboratively with a cloud platform. Specifically, an example of a medical power supply unit will be used for illustrative purposes.

[0062] Depend on Figure 1 As can be seen, the active safety control method for medical power supply based on digital twin provided in this application includes the following steps S110 to S150. Details are as follows:

[0063] The S110 acquires environmental and electrical stress parameters of the power system in real time and records historical stress times.

[0064] In this embodiment, environmental parameters include ambient temperature and relative humidity; electrical stress parameters include real-time monitored input voltage, output voltage, and operating frequency; and historical stress time includes the cumulative operating time of the power supply system.

[0065] Specifically, environmental parameters are acquired using a temperature and humidity sensor installed inside the medical power supply, near the isolation transformer and optocoupler. The sensor is connected to a processor (e.g., a microcontroller unit, MCU) via a communication bus. The processor reads the sensor's measurements at a fixed frequency (e.g., once per minute) to obtain real-time information on ambient temperature and relative humidity.

[0066] The input and output voltages of the medical power supply are sampled and conditioned using a resistor divider network and an operational amplifier circuit. Subsequently, the analog-to-digital converter (ADC) of the processor (such as an MCU) performs data conversion and readout; the operating frequency is directly obtained from the inherent clock frequency parameter within the processor (such as the MCU). For example, all electrical parameters are sampled and monitored in real time at a preset high frequency (e.g., ten times per second).

[0067] Historical stress time is recorded in seconds by a timer inside the processor (such as an MCU). This timer continuously tracks the cumulative runtime of the power system and periodically stores the cumulative time in the processor's internal non-volatile memory (Flash).

[0068] S120: Inject a diagnostic signal into the isolation barrier and simultaneously monitor the response of the diagnostic signal to calculate the current equivalent insulation resistance value of the isolation barrier.

[0069] For example, such as Figure 2 As shown, Figure 2 for Figure 1 A schematic diagram illustrating the specific implementation process of the S120. (By...) Figure 2 It can be seen that in this embodiment, S120 includes:

[0070] S121: A specific high-frequency, low-amplitude diagnostic signal is periodically injected by the power controller onto the primary side of the isolation barrier.

[0071] In this embodiment, the equivalent insulation impedance value is measured by applying a measurable probe excitation, such as a high-frequency, low-amplitude diagnostic signal, so as not to affect the normal operation of the medical power supply.

[0072] Specifically, to ensure that the diagnostic process does not affect the main power conversion performance of the medical power supply, the injection action is selected by the controller to be performed within a specific time window. For example, it is selected to be performed during the turn-off cycle of the power switching transistor (MOSFET) when the load current is relatively light, in order to minimize interference. Moreover, the injection is performed periodically, for example, a complete diagnostic process is executed every 10 minutes, to continuously track aging trends without excessively consuming controller resources.

[0073] The controller triggers a sine wave output from the DAC (Digital-to-Analog Converter) via an internal timer, or generates the required diagnostic signal via a pin in conjunction with an external low-pass filter. The specific high frequency refers to the selected frequency of the signal, typically much higher than the switching frequency of the medical power supply (e.g., 100kHz to 500kHz). High-frequency signals are more sensitive to minute defects in the insulation material, helping to detect potential problems early. Low amplitude means the signal amplitude is strictly limited to a very low level (e.g., 50mV peak). The core principle is that the signal energy must be small enough that even if the isolation barrier is severely aged, its injection will not pose a safety risk (such as excessive leakage current); at the same time, it must be large enough to be clearly and reliably detected on the secondary side.

[0074] The generated diagnostic signal is injected into the primary side of the isolation barrier through a coupling network consisting of a DC blocking capacitor and a current-limiting resistor connected in series. Exemplarily, the injection point is the primary winding of an isolation switching transformer. This coupling network ensures that only AC diagnostic signals can pass through, while isolating the signal generation circuit from the influence of DC high voltage. This step allows for precise measurement of the isolation barrier's response to the diagnostic signal and its conversion into an impedance value.

[0075] S122: Detect the response of the diagnostic signal on the secondary side of the isolation barrier, and calculate the current equivalent insulation impedance value of the isolation barrier by analyzing the attenuation amplitude and phase change of the response.

[0076] Specifically, on the secondary side of the isolation barrier (such as the secondary winding of an isolation transformer), a dedicated high-precision, high common-mode rejection ratio (CMRR) differential amplifier circuit (such as Analog Devices' AD629) is used to capture the response signal. This circuit can suppress large common-mode voltages between the primary and secondary sides while accurately amplifying weak differential diagnostic signals. The amplified signal is then sent to the processor's high-speed analog-to-digital converter pin.

[0077] The processor uses the digital reference signal it generates for the original diagnostic signal to multiply and filter the acquired response signal, thereby accurately extracting the amplitude and phase of the response signal at a specific frequency. This process can greatly suppress noise interference and improve the signal-to-noise ratio.

[0078] Alternatively, by performing an FFT transformation on the response signal, converting it from the time domain to the frequency domain, the amplitude and phase of the signal can be read directly at the frequency point of the diagnostic signal (e.g., 100kHz).

[0079] Based on the above analysis, the amplitude attenuation ratio and phase difference can be obtained. The isolation barrier can be equivalently represented as a parallel RC circuit (where R represents insulation resistance and C represents parasitic capacitance). Based on this model, the equivalent insulation impedance value can be calculated using the following formula:

[0080] Z = (Vin / Vre)×K×cos(Φ); where Z is the equivalent insulation resistance, Vin is the amplitude of the injected diagnostic signal, Vre is the amplitude of the measured response signal, K is a known system constant determined by the coupling network and amplifier gain, and Φ is the phase difference.

[0081] The calculation process is completed in real time within the processor using a software algorithm, ultimately yielding the precise equivalent insulation resistance value Z at the current moment, in MΩ.

[0082] S130: The equivalent insulation resistance value and environmental parameters are input into a pre-built digital twin model to dynamically correct the aging rate parameters, so that the digital twin model is synchronized with the physical entity of the medical power supply.

[0083] In this application, this step ensures that the state of the digital twin model remains consistent with the actual aging state of the physical entity. Specifically, during the initialization of the medical power system, a digital twin model of an isolation barrier is established on the processor or in the cloud based on the physicochemical mechanisms of insulating materials' aging (such as the Arrhenius equation and the electrical stress acceleration model). This digital twin model is a state-space equation, where the state variables are internal parameters characterizing the degree of aging of the insulating materials, such as the degree of polymerization of the insulating materials or an abstract aging degree index (between 0 and 1). The key internal parameter of the model is the aging rate parameter, which determines the rate at which the state variables change over time.

[0084] For example, the equivalent insulation resistance value and environmental parameters are input into a pre-built digital twin model for dynamic correction of aging rate parameters, including: inputting the equivalent insulation resistance value, ambient temperature and relative humidity into an adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters inside the digital twin model.

[0085] By using the calculated equivalent insulation impedance value and the collected ambient temperature and relative humidity as a set of joint inputs, the aging rate parameters inside the digital twin model are continuously iterated in the digital twin model, so that the output of the digital twin model is infinitely close to the equivalent insulation impedance value actually measured by the physical entity.

[0086] Preferably, the adaptive algorithm is a Kalman filter; the equivalent insulation impedance value, ambient temperature, and relative humidity are input into the adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters inside the digital twin model. This includes: inputting the equivalent insulation impedance value, ambient temperature, and relative humidity into the adaptive algorithm of the digital twin model, using the state update and measurement update mechanism of the Kalman filter, taking the equivalent insulation impedance value as an observed variable, and taking the ambient temperature and relative humidity as part of the state variables or process noise adjustment factors, to estimate the state variables characterizing the aging rate of the insulation material in the digital twin model, thereby achieving dynamic correction of the aging rate parameters.

[0087] Specifically, the state variables of the Kalman filter are the aging state variables (such as aging degree indicators) in the digital twin model; the observed variables are the equivalent insulation resistance values. Because the equivalent insulation resistance value can be measured directly or indirectly, it can be used as an observed variable to reflect the physical quantity of the aging state; the adjustment factors for the process noise covariance are ambient temperature and relative humidity. For example, when the ambient humidity is high, increasing the variance of the process noise indicates increased uncertainty in the model, making the filter more confident in the measured values ​​(equivalent insulation resistance values); when the environment is stable, the model's predictions are more trusted.

[0088] The digital twin model predicts the aging state and the predicted observation value (i.e., the predicted equivalent insulation resistance) at the next moment based on its current aging rate. The actual measured equivalent insulation resistance value is compared with the model's predicted equivalent insulation resistance value, and the error (residual) is calculated. The Kalman filter, based on a preset gain, uses this error to optimally correct the state variables and aging rate parameters.

[0089] Through this step, the aging rate parameters within the digital twin model are continuously and dynamically corrected, ensuring that the output of the digital twin model (the predicted equivalent insulation resistance value) approximates the actual measured equivalent insulation resistance value of the physical entity. Thus, the digital twin achieves high-fidelity synchronization with the physical entity.

[0090] S140: Using a corrected digital twin model, combined with electrical stress parameters and historical stress time, the remaining life of the isolation barrier is predicted.

[0091] This step utilizes a calibrated, high-fidelity digital twin model, combined with electrical stress parameters and historical stress time, to simulate and extrapolate the future, thereby predicting the remaining lifespan of the isolation barrier.

[0092] Specifically, using the corrected digital twin model, combined with electrical stress parameters and historical stress time, the remaining life of the isolation barrier is predicted. This includes: starting from the aging state accumulated over historical stress time, using electrical stress parameters as the stress condition for continuous action, inputting them into the corrected digital twin model for iterative calculation, and extrapolating the change trend of the equivalent insulation impedance value of the isolation barrier over time; when the extrapolation reaches the equivalent insulation impedance value dropping to a preset safety threshold, the calculation is terminated; the length of the future time simulated by the iterative calculation is the predicted remaining life of the isolation barrier.

[0093] The current aging state, accumulated over historical stress time, serves as the starting point for prediction. This starting point is the current state variable value obtained after dynamic correction of the digital twin model. It is assumed that future electrical stress parameters (input voltage, output voltage, operating frequency) will remain unchanged from their current values.

[0094] Substitute the current electrical stress parameters and environmental parameters (either historical averages or projected values) into the corrected digital twin model. Based on its internally corrected aging rate, the model calculates the aging state one step ahead and, accordingly, predicts the equivalent insulation resistance value at that future moment. By advancing the time by one step and repeating this process with the new aging state as the initial value, the model can iteratively derive the future curve of the equivalent insulation resistance value changing over time.

[0095] The derived predicted equivalent insulation resistance value is compared with a preset safety threshold. This threshold is the critical value for insulation failure determined according to medical safety standards (such as IEC 60601-1 requirements for leakage current). The iterative calculation terminates when the derived predicted equivalent insulation resistance value is less than or equal to the preset safety threshold. The simulated time length from the current time to the termination time is the predicted remaining lifetime of the isolation barrier.

[0096] S150: Based on the comparison between the remaining lifespan and the preset threshold, execute the corresponding active safety control strategy.

[0097] Based on the comparison result between the remaining lifespan and the preset threshold, the corresponding active safety control strategy is executed, including: when the remaining lifespan is greater than the first preset threshold, the system status is determined to be normal and the power supply is controlled to run at full power; when the remaining lifespan is greater than the second preset threshold and less than or equal to the first threshold, a first-level warning is triggered and maintenance warning information is sent to the cloud management platform or user interface; when the remaining lifespan is less than or equal to the second preset threshold, a second-level warning is triggered and a second-level active response is initiated.

[0098] For example, a level-two warning is triggered, and a level-two active response is initiated, including at least one of power derating, a hard alarm, and logging. Specifically, power derating includes limiting the maximum output power of the medical power supply to 50% or less of its rated power by adjusting the duty cycle of the pulse width modulation. This aims to significantly reduce the electrothermal stress on the isolation barrier, slow down its aging process, and buy time for safe maintenance. The hard alarm includes driving the onboard red LED indicator to remain lit and triggering a buzzer to sound, providing a local audible and visual alarm, and sending an "emergency" level alarm message to the monitoring center. Logging includes writing all key data of this event (timestamp, RUL, all sensor readings, and actions performed) into the non-volatile memory (Flash) inside the MCU, providing a complete data chain for subsequent fault analysis and maintenance.

[0099] As can be seen from the above analysis, the active safety control method for medical power supplies based on digital twins provided in this application includes: real-time acquisition of environmental parameters and electrical stress parameters of the power system and recording historical stress time; injection of diagnostic signals into the isolation barrier and synchronous monitoring of the response of the diagnostic signals, calculating the current equivalent insulation impedance value of the isolation barrier; inputting the equivalent insulation impedance value and the environmental parameters into a pre-constructed digital twin model for dynamic correction of aging rate parameters, so that the digital twin model is synchronized with the physical entity of the medical power supply; using the corrected digital twin model, combined with the electrical stress parameters and the historical stress time, predicting the remaining lifespan of the isolation barrier; and executing a corresponding active safety control strategy based on the comparison result of the remaining lifespan with a preset threshold. By integrating digital twin dynamic correction and active signal injection monitoring, this invention achieves high-precision remaining lifespan prediction and executes a graded active safety strategy accordingly, aiming to address the core technical problem of the lack of real-time and accurate predictive management of the health status of medical power supply isolation barriers, which prevents the transformation from passive protection to active prevention. It significantly improves the reliability and safety of medical power supplies, enabling a leap from power outages after a failure to intervention before failure, while providing data support for predictive maintenance and reducing operation and maintenance costs.

[0100] Please see Figure 3 , Figure 3 This is a schematic diagram of a digital twin-based active safety control device for medical power supplies, provided as an embodiment of this application. The digital twin-based active safety control device for medical power supplies includes modules or units for performing... Figure 1 or Figure 2 The steps in the corresponding embodiments. Please refer to the details. Figure 1 or Figure 2 The relevant descriptions in the corresponding embodiments are shown below. For ease of explanation, only the parts relevant to this embodiment are shown. See also... Figure 3A digital twin-based active safety control device for medical power supplies 300 includes:

[0101] The acquisition module 310 is used to acquire environmental parameters and electrical stress parameters of the power system in real time and record historical stress time.

[0102] The monitoring module 320 is used to inject diagnostic signals into the isolation barrier and simultaneously monitor the response of the diagnostic signals to calculate the current equivalent insulation resistance value of the isolation barrier.

[0103] The calibration module 330 is used to dynamically calibrate the aging rate parameters by inputting the equivalent insulation impedance value and environmental parameters into a pre-built digital twin model, so that the digital twin model is synchronized with the physical entity of the medical power supply.

[0104] The prediction module 340 is used to predict the remaining life of the isolation barrier by using the corrected digital twin model, combined with electrical stress parameters and historical stress time.

[0105] The execution module 350 is used to execute corresponding active safety control strategies based on the comparison result between the remaining lifespan and the preset threshold.

[0106] In one embodiment, environmental parameters include ambient temperature and relative humidity; electrical stress parameters include real-time acquired input voltage, output voltage, and operating frequency; and historical stress time is the cumulative operating time of the power supply system.

[0107] In one embodiment, the monitoring module 320 includes:

[0108] An injection unit is used to periodically inject a specific high-frequency, low-amplitude diagnostic signal onto the primary side of the isolation barrier by the power controller;

[0109] The detection unit is used to detect the response of the diagnostic signal on the secondary side of the isolation barrier. By analyzing the attenuation amplitude and phase change of the response, the current equivalent insulation impedance value of the isolation barrier is calculated.

[0110] In one embodiment, the correction module 330 is specifically used for:

[0111] The equivalent insulation resistance value, ambient temperature, and relative humidity are input into the adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters inside the digital twin model.

[0112] In one embodiment, the adaptive algorithm is a Kalman filter; the correction module 330 is specifically used for:

[0113] The equivalent insulation impedance, ambient temperature, and relative humidity are input into the adaptive algorithm of the digital twin model. Using the state update and measurement update mechanism of the Kalman filter, the equivalent insulation impedance is used as the observed variable, and the ambient temperature and relative humidity are used as part of the state variables or as adjustment factors for process noise. The state variables characterizing the aging rate of the insulation material in the digital twin model are estimated, thereby achieving dynamic correction of the aging rate parameters.

[0114] In one embodiment, the prediction module 340 includes:

[0115] The input unit is used to take the aging state under historical stress time accumulation as the starting point, take the electrical stress parameters as the stress conditions of continuous action, input them into the corrected digital twin model for iterative calculation, and deduce the change trend of the equivalent insulation impedance value of the isolation barrier over time.

[0116] The calculation unit is used to terminate the calculation when the equivalent insulation resistance value drops to a preset safety threshold; the length of the future time simulated by the iterative calculation is the predicted remaining life of the isolation barrier.

[0117] In one embodiment, the execution module 350 includes:

[0118] The determination unit is used to determine that the system is in normal condition and control the power supply to run at full power when the remaining lifespan is greater than the first preset threshold.

[0119] The first triggering unit is used to trigger a level one warning when the remaining lifespan is greater than the second preset threshold and less than or equal to the first threshold, and to send maintenance warning information to the cloud management platform or user interface.

[0120] The second triggering unit is used to trigger a secondary warning and initiate a secondary active response when the remaining lifespan is less than or equal to the second preset threshold.

[0121] Please see Figure 4 , Figure 4 This is a schematic diagram of a medical power supply active safety control device based on digital twins, provided as an embodiment of this application. Figure 4 It is understood that the medical power supply active safety control device 400 based on digital twins includes: a processor 410, a memory 420, and a computer program 430 stored in the memory 420 and executable on the processor 410; when the processor 410 executes the computer program 430, it implements the steps in the above-described embodiments of the medical power supply active safety control method based on digital twins, for example... Figure 1 The steps S110 to S150 are shown. Alternatively, when the processor 410 executes the computer program 430, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 3 The functions of modules 310 to 350 are shown.

[0122] For example, computer program 430 may be divided into one or more modules / units, one or more of which are stored in memory 420 and executed by processor 410 to complete this application. One or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of computer program 430 in a digital twin-based medical power supply active safety control device. For example, computer program 430 may be divided into an acquisition module, a monitoring module, a calibration module, a prediction module, and an execution module.

[0123] The digital twin-based active safety control device for medical power supplies provided in this embodiment may include, but is not limited to, processors and memory. Those skilled in the art will understand that... Figure 4 This is merely an example of a digital twin-based active safety control device for medical power supplies and does not constitute a limitation on digital twin-based active safety control devices for medical power supplies. It may include more or fewer components than shown, or combine certain components, or different components. For example, a digital twin-based active safety control device for medical power supplies may also include input / output devices, network access devices, buses, etc.

[0124] The processor 410 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0125] The memory 420 can be an internal storage unit of the digital twin-based medical power active safety control device, such as a hard drive or RAM. The memory 420 can also be an external storage device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the digital twin-based medical power active safety control device can include both internal and external storage units. The memory 420 is used to store computer programs and other programs and data required by the digital twin-based medical power active safety control device. The memory 420 can also be used to temporarily store data that has been output or will be output.

[0126] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0127] This application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the steps in any of the above method embodiments.

[0128] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0129] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0130] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0131] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0132] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0133] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0134] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0135] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for active safety control of medical power supplies based on digital twins, characterized in that, The method includes: Real-time acquisition of environmental and electrical stress parameters of the power system and recording of historical stress duration; A diagnostic signal is injected into the isolation barrier, and the response of the diagnostic signal is monitored simultaneously to calculate the current equivalent insulation resistance value of the isolation barrier. The equivalent insulation impedance value and the environmental parameters are input into a pre-constructed digital twin model for dynamic correction of the aging rate parameters, so that the digital twin model is synchronized with the physical entity of the medical power supply. Starting from the aging state under the accumulated historical stress time, the electrical stress parameters are used as the stress conditions for continuous action. They are input into the corrected digital twin model for iterative calculation to deduce the change trend of the equivalent insulation impedance value of the isolation barrier over time. The calculation terminates when the equivalent insulation resistance value drops to a preset safety threshold; the future time length simulated by the iterative calculation is the predicted remaining lifetime of the isolation barrier. Based on the comparison result between the remaining lifespan and the preset threshold, the corresponding active safety control strategy is executed.

2. The active safety control method for medical power supplies based on digital twins as described in claim 1, characterized in that, The environmental parameters include ambient temperature and relative humidity; the electrical stress parameters include real-time acquired input voltage, output voltage, and operating frequency; and the historical stress time is the cumulative operating time of the power supply system.

3. The active safety control method for medical power supplies based on digital twins as described in claim 2, characterized in that, The process of injecting diagnostic signals into the isolation barrier and simultaneously monitoring the response of the diagnostic signals to calculate the current equivalent insulation impedance value of the isolation barrier includes: A specific high-frequency, low-amplitude diagnostic signal is periodically injected by the power controller into the primary side of the isolation barrier; The response of the diagnostic signal is detected on the secondary side of the isolation barrier, and the current equivalent insulation impedance value of the isolation barrier is calculated by analyzing the attenuation amplitude and phase change of the response.

4. The active safety control method for medical power supplies based on digital twins as described in claim 2, characterized in that, The step of dynamically correcting the aging rate parameters by inputting the equivalent insulation impedance value and the environmental parameters into a pre-constructed digital twin model includes: The equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters inside the digital twin model.

5. The active safety control method for medical power supplies based on digital twins as described in claim 4, characterized in that, The adaptive algorithm is a Kalman filter; the equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model to dynamically correct the aging rate parameters within the digital twin model, including: The equivalent insulation impedance value, the ambient temperature, and the relative humidity are input into the adaptive algorithm of the digital twin model. Using the state update and measurement update mechanism of the Kalman filter, the equivalent insulation impedance value is used as an observation variable, and the ambient temperature and relative humidity are used as part of the state variables or as adjustment factors for process noise. The state variables characterizing the aging rate of the insulation material in the digital twin model are estimated to achieve dynamic correction of the aging rate parameter.

6. The active safety control method for medical power supplies based on digital twins as described in claim 5, characterized in that, The step of executing a corresponding proactive safety control strategy based on the comparison result between the remaining lifespan and a preset threshold includes: When the remaining lifespan is greater than the first preset threshold, the system is determined to be in normal condition and the power supply is controlled to run at full power. When the remaining lifespan is greater than the second preset threshold and less than or equal to the first preset threshold, a level one warning is triggered, and maintenance warning information is sent to the cloud management platform or user interface. When the remaining lifespan is less than or equal to the second preset threshold, a level-two warning is triggered and a level-two active response is initiated.

7. A medical power supply active safety control device based on digital twin, characterized in that, include: The acquisition module is used to acquire environmental parameters and electrical stress parameters of the power system in real time and record historical stress times; The calculation module is used to inject diagnostic signals into the isolation barrier, synchronously monitor the response of the diagnostic signals, and calculate the current equivalent insulation impedance value of the isolation barrier. The calibration module is used to dynamically calibrate the aging rate parameters by inputting the equivalent insulation impedance value and the environmental parameters into a pre-built digital twin model, so that the digital twin model is synchronized with the physical entity of the medical power supply. The prediction module is used to take the aging state under the historical stress time accumulation as the starting point, take the electrical stress parameters as the stress conditions of continuous action, input them into the corrected digital twin model for iterative calculation, and deduce the change trend of the equivalent insulation resistance value of the isolation barrier over time; when the deduction reaches the equivalent insulation resistance value dropping to a preset safety threshold, the calculation is terminated; the future time length simulated by the iterative calculation is the predicted remaining life of the isolation barrier; The execution module is used to execute corresponding proactive safety control strategies based on the comparison result between the remaining lifespan and the preset threshold.

8. A medical power supply active safety control device based on digital twin, characterized in that, include: Processor, memory, and computer programs stored in said memory and executable on said processor; When the processor executes the computer program, it implements the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 6.

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