Leakage detection methods, devices, electronic equipment and storage media for blood pressure simulators

Abstract

This invention discloses a method, device, electronic equipment, and storage medium for leak detection of a blood pressure simulator, comprising: inflating the target instrument to a preset pressure, acquiring the pressure signal of the target instrument under static conditions at preset time intervals to obtain a pressure decay signal sequence; mapping the pressure signal in the pressure decay signal sequence to quantum states through quantum phase encoding to obtain a pressure signal quantum sequence; performing multi-scale decomposition of the pressure signal quantum sequence using hybrid wavelet basis functions and calculating the decomposition coefficients corresponding to each decomposition scale; calculating the quantum Shannon entropy corresponding to each decomposition scale based on the decomposition coefficients; solving for the optimal decomposition scale using a quantum annealing algorithm based on the quantum Shannon entropy corresponding to all decomposition scales; calculating the leakage rate based on the pressure decay rate and the entropy change rate of the quantum Shannon entropy corresponding to the optimal decomposition scale; and obtaining the leakage result based on the leakage rate. This method can improve the sensitivity and accuracy of leak detection.

Description

Technical Field

[0001] This invention belongs to the field of equipment testing, and specifically relates to a method, device, electronic equipment and storage medium for detecting leaks in a blood pressure simulator. Background Technology

[0002] As a critical medical measuring instrument, the airtightness of the gas circuit system in a non-invasive blood pressure simulator directly affects the accuracy and reliability of blood pressure simulation. Currently, the industry commonly uses the oscillometric method, employing static pressure decay as a criterion for leak detection. This method determines the sealing status by monitoring whether the linear decay rate at a fixed pressure point exceeds a threshold. However, existing detection methods have the following drawbacks:

[0003] The sensitivity limitations of static detection: Traditional methods cannot effectively capture nonlinear leakage characteristics (such as micropore leakage and intermittent leakage under dynamic pressure fluctuations). When the leakage amount is lower than the detection threshold, it is easy to produce false negatives, causing small leaks to accumulate into systematic errors over long-term use.

[0004] Risk of false positives due to environmental interference: Pressure sensors are susceptible to interference from ambient temperature drift, electromagnetic noise, and other factors, resulting in signal attenuation characteristics similar to actual leaks. Conventional filtering algorithms lack sufficient signal-to-noise separation capabilities in complex noise environments, leading to a significantly increased false detection rate.

[0005] High-dimensional signal processing is inefficient: Conventional wavelet transform requires a large amount of computation when processing high-dimensional pressure signals, making it difficult to dynamically compensate for errors in real time, resulting in low detection sensitivity.

[0006] Therefore, the sensitivity and accuracy of existing leak detection methods need to be improved. Summary of the Invention

[0007] The purpose of this invention is to provide a method, apparatus, electronic device, and computer-readable storage medium for detecting leaks in a blood pressure simulator, which can improve the sensitivity and accuracy of leak detection in a blood pressure simulator.

[0008] The first aspect of this invention discloses a method for detecting leakage in a blood pressure simulator, comprising:

[0009] After inflating the target instrument to a preset pressure, the pressure signal of the target instrument under static conditions is collected at preset time intervals to obtain a pressure decay signal sequence.

[0010] The pressure signal in the pressure decay signal sequence is mapped to a quantum state by quantum phase encoding to obtain the pressure signal quantum sequence.

[0011] The pressure signal quantum sequence is decomposed into multiple scales using hybrid wavelet basis functions, and the decomposition coefficients corresponding to each decomposition scale are calculated.

[0012] Calculate the quantum Shannon entropy for each decomposition scale based on the decomposition coefficients corresponding to each decomposition scale.

[0013] Based on the quantum Shannon entropy corresponding to all decomposition scales, the optimal decomposition scale is solved using the quantum annealing algorithm.

[0014] The leakage rate is calculated based on the entropy change rate of the quantum Shannon entropy corresponding to the pressure decay rate and the optimal decomposition scale, and the leakage result is obtained based on the leakage rate.

[0015] In some embodiments, the formula for calculating quantum phase encoding is:

[0016] ;

[0017] in, The quantum state of the pressure signal, The length of the pressure attenuation signal sequence. For the first The ground state of a quantum bit The imaginary unit, The first in the pressure decay signal sequence The phase modulation factor of a pressure signal. This is the index of the pressure signal in the pressure decay signal sequence.

[0018] In some embodiments, the formula for calculating the decomposition coefficients is:

[0019] ;

[0020] in, For decomposition scale The corresponding decomposition coefficients, For translation parameters, wavelet basis functions The conjugate transpose of the corresponding quantum state, , , The maximum number of decomposition levels. , The length of the pressure attenuation signal sequence. This is the index of the pressure signal in the pressure decay signal sequence.

[0021] In some embodiments, the formula for calculating quantum Shannon entropy is:

[0022] ;

[0023] in, For decomposition scale The quantum Shannon entropy below, For decomposition scale Translation parameters The corresponding decomposition coefficients.

[0024] In some embodiments, the expression for solving the optimal decomposition scale is:

[0025] ;

[0026] in, This is the optimal decomposition scale. The regularization coefficient is . For decomposition scale The variance of the underentropy value For decomposition scale The quantum Shannon entropy below.

[0027] In some embodiments, the formula for calculating the leakage rate is:

[0028] ;

[0029] in, For leakage rate, The corrected pressure value for the target instrument. The pressure decay rate, , The measured pressure value of the target instrument. Due to environmental interference, The coupling coefficient is... The quantum Shannon entropy at the optimal decomposition scale. Let be the entropy change rate of quantum Shannon entropy.

[0030] In some embodiments, obtaining the leakage result based on the leakage rate includes:

[0031] When the leakage rate is greater than or equal to the first leakage threshold and less than the second leakage threshold, the leakage result is that the target instrument has a minor leakage; when the leakage rate is greater than or equal to the second leakage threshold, the leakage result is that the target instrument has a significant leakage.

[0032] A second aspect of the present invention discloses a leakage detection device for a blood pressure simulator, comprising:

[0033] The acquisition module is used to inflate the target instrument to a preset pressure and then acquire the pressure signal of the target instrument under static conditions at preset time intervals to obtain a pressure decay signal sequence.

[0034] A quantum phase encoding module is used to map the pressure signal in the pressure decay signal sequence into a quantum state through quantum phase encoding to obtain a pressure signal quantum sequence.

[0035] The multi-scale decomposition module is used to perform multi-scale decomposition of the pressure signal quantum sequence using hybrid wavelet basis functions, and to calculate the decomposition coefficients corresponding to each decomposition scale.

[0036] The quantum Shannon entropy calculation module is used to calculate the quantum Shannon entropy corresponding to each decomposition scale based on the decomposition coefficients corresponding to each decomposition scale.

[0037] The optimal decomposition scale module is used to solve for the optimal decomposition scale based on the quantum Shannon entropy corresponding to all decomposition scales using the quantum annealing algorithm.

[0038] The leakage rate module is used to calculate the leakage rate based on the pressure decay rate and the entropy change rate of the quantum Shannon entropy corresponding to the optimal decomposition scale, and to obtain the leakage result based on the leakage rate.

[0039] A third aspect of the present invention discloses an electronic device, including a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the blood pressure simulator leakage detection method disclosed in the first aspect.

[0040] The fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the blood pressure simulator leakage detection method disclosed in the first aspect.

[0041] The beneficial effects of this invention are as follows: First, a pressure decay signal sequence is acquired under static conditions. This sequence contains information about the pressure change of the target instrument over time, reflecting whether a leak exists and the degree of leakage. Then, quantum phase encoding maps the pressure signal in the pressure decay signal sequence to a quantum state, enhancing the signal's characterization ability and improving the sensitivity to identify minute leak characteristics. Next, a multi-scale decomposition of the pressure signal quantum sequence is performed using hybrid wavelet basis functions. The quantum Shannon entropy corresponding to different decomposition scales is calculated, and the optimal decomposition scale is selected using a quantum annealing algorithm. At the optimal decomposition scale, the pressure signal is decomposed into frequency components that best distinguish leak characteristics from normal pressure decay. Furthermore, since quantum Shannon entropy is a measure of signal uncertainty, its entropy change rate directly reflects changes in signal complexity. By fusing the entropy change rate and pressure decay rate as dual indicators to jointly evaluate the leakage rate in both the time and frequency domains, the robustness of leak detection is significantly improved, resulting in higher sensitivity and accuracy. Attached Figure Description

[0042] The accompanying drawings illustrate specific examples of the technical solutions described in this invention and, together with the detailed embodiments, form part of the specification, serving to explain the technical solutions, principles, and effects of this invention.

[0043] Unless otherwise specified or defined, the same reference numerals in different figures represent the same or similar technical features, and different reference numerals may be used to represent the same or similar technical features.

[0044] Figure 1 This is a flowchart of an embodiment of a blood pressure simulator leakage detection method according to an embodiment of the present invention;

[0045] Figure 2 This is a schematic diagram of the structure of a blood pressure simulator leakage detection device according to an embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0047] Unless otherwise specified or defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. When combined with the technical solutions of the invention in a real-world scenario, all technical and scientific terms used herein may also have meanings corresponding to the purpose of achieving the technical solutions of the invention. The terms "first," "second," etc., used herein are merely for distinguishing names and do not represent a specific number or order. The term "and / or," as used herein, includes any and all combinations of one or more of the associated listed items.

[0048] It should be noted that when a component is considered "fixed" to another component, it can be directly fixed to the other component or there can be an intervening component; when a component is considered "connected" to another component, it can be directly connected to the other component or there can be an intervening component; when a component is considered "mounted" on another component, it can be directly mounted on the other component or there can be an intervening component; when a component is considered "placed" on another component, it can be directly placed on the other component or there can be an intervening component.

[0049] Unless otherwise specified or defined, the terms "described" or "the" as used herein refer to the technical features or technical content mentioned or described prior to the relevant section, which may be the same as or similar to the technical features or technical content mentioned herein. Furthermore, the terms "comprising" and "having," and any variations thereof, as used herein, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0050] To facilitate understanding of the present invention, specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings.

[0051] To improve the sensitivity and accuracy of leak detection in blood pressure simulators, this invention utilizes the high efficiency and parallel processing capabilities of quantum computing to significantly enhance the sensitivity of identifying weak leak signals. It also combines the localization characteristics and multi-scale analysis capabilities of wavelet analysis to accurately extract multi-dimensional leak features. Furthermore, it integrates the entropy change rate and pressure decay rate as dual indicators to jointly calculate the leak rate from both the time domain (pressure change) and the frequency domain (complexity change), significantly improving the robustness of the leak detection method and resulting in higher sensitivity and accuracy.

[0052] This invention discloses a method for detecting leaks in a blood pressure simulator, used to detect leaks in a non-invasive blood pressure simulator. This method can be implemented through computer programming, functioning as a standalone blood pressure simulator leak detection system. The executing device of this method can be an electronic device such as a computer, laptop, or tablet, or a control chip embedded in an electronic device; this invention does not limit this. It should be noted that this method is not limited to non-invasive blood pressure simulators, but can also be used for other medical instruments and devices with airway systems, such as ventilators.

[0053] like Figure 1 As shown, an embodiment of the blood pressure simulator leakage detection method includes the following steps:

[0054] Step S100: After inflating the target instrument to a preset pressure, collect the pressure signal of the target instrument under static conditions at preset time intervals to obtain a pressure decay signal sequence;

[0055] The target instrument is a non-invasive blood pressure simulator. The static condition means that the gas system must be in a completely static state, that is, all inflation and deflation valves are closed and any airflow exchange is stopped. In other words, the gas system is in a state of no gas flow and no active inflation or deflation operation.

[0056] The preset pressure can be determined based on the actual situation of the target instrument. First, the target instrument is inflated to the preset pressure, and then the pressure signal is acquired. During acquisition, data is collected at preset time intervals; in this embodiment, the preferred time interval is 0.1 seconds, resulting in a pressure decay signal sequence. , .

[0057] Step S200: Map the pressure signal in the pressure decay signal sequence to a quantum state through quantum phase encoding to obtain the pressure signal quantum sequence;

[0058] Quantum phase encoding is a method of storing information in the phase portion of a quantum state by adjusting the phase modulation factor. It can encode different information.

[0059] Specifically, the formula for calculating the quantum phase encoding is as follows:

[0060] ;

[0061] in, The quantum state of the pressure signal, The length of the pressure attenuation signal sequence. For the first The ground state of a quantum bit The imaginary unit, The first in the pressure decay signal sequence The phase modulation factor of a pressure signal. This is the index of the pressure signal in the pressure decay signal sequence.

[0062] in, The calculation formula is:

[0063] ,

[0064] in, This represents the maximum pressure value in the pressure decay signal sequence. This represents the minimum pressure value in the pressure decay signal sequence. The first in the pressure decay signal sequence The pressure value of each pressure signal.

[0065] In a pressure decay signal sequence, the pressure value varies at different times, resulting in its corresponding... Different. By continuously calculating at different times The value can encode information about the dynamic changes in pressure decay over time. When a non-invasive blood pressure simulator is in a normal leak-free state, a slight leak state, and a significant leak state, its corresponding pressure decay signal sequences differ, thus... The distribution of these signals also differs. Therefore, by extracting and analyzing the characteristics of the encoded pressure signal quantum sequence, this difference can be accurately identified, and the leakage of the non-invasive blood pressure simulator can be further determined.

[0066] After quantum phase encoding is completed, the pressure signal quantum sequence is obtained. , .

[0067] Step S300: Use hybrid wavelet basis functions to perform multi-scale decomposition on the pressure signal quantum sequence, and calculate the decomposition coefficients corresponding to each decomposition scale;

[0068] Hybrid wavelet basis functions are a function system formed by combining or fusing different types of wavelet basis functions. They combine the characteristics of multiple wavelet bases to better adapt to the diverse needs of complex signal processing, image analysis, and other fields. This embodiment describes a hybrid wavelet basis function. For adaptive Haar-Daubechies hybrid wavelet basis (a mixture of Haar and Daubechies wavelet basis), satisfying And the energy is normalized.

[0069] Mixed wavelet basis functions The calculation formula is:

[0070] ;

[0071] in, To decompose the scale, For translation parameters, It is a time variable.

[0072] By changing the decomposition scale The value of can be adjusted to change the frequency range of the wavelet basis function, thereby enabling multi-scale analysis of different frequency components of the signal. This can be achieved by changing the translation parameter. The value of allows the wavelet basis function to be shifted along the time axis, enabling analysis of different time periods of the signal. Therefore, the hybrid wavelet basis function exhibits excellent localization characteristics in both the time and frequency domains, allowing for the decomposition and analysis of signals from multiple scales and perspectives.

[0073] The decomposition coefficients reflect the magnitude of the projection of the pressure signal quantum sequence onto the wavelet basis function. Different leakage states produce different projections onto the wavelet basis function; therefore, the decomposition coefficients can extract key features related to the leakage state in the pressure signal, providing a highly sensitive analytical basis for micro-leakage detection. Since the scale parameter (i.e., the decomposition scale) and translation parameter of the wavelet basis function can vary, the decomposition coefficients can demonstrate the characteristics of the pressure signal at different scales and time locations.

[0074] Specifically, the formula for calculating the decomposition coefficients corresponding to a certain decomposition scale is as follows:

[0075] ;

[0076] in, For decomposition scale The corresponding decomposition coefficients, ; For translation parameters, This is used to locate the temporal location of the leak event; wavelet basis functions The conjugate transpose of the corresponding quantum state; The maximum number of decomposition levels. The corresponding pressure signal frequency band is 0.1~10Hz. The length of the pressure attenuation signal sequence; This is the index of the pressure signal in the pressure decay signal sequence.

[0077] Step S400: Calculate the quantum Shannon entropy corresponding to each decomposition scale based on the decomposition coefficients corresponding to each decomposition scale.

[0078] Step S500: Based on the quantum Shannon entropy corresponding to all decomposition scales, the quantum annealing algorithm is used to solve for the optimal decomposition scale;

[0079] Quantum Shannon entropy measures the uncertainty or complexity of the quantum state corresponding to a pressure signal quantum sequence at a given decomposition scale. By calculating the quantum Shannon entropy at different decomposition scales, the optimal decomposition scale can be found using the quantum annealing algorithm. The optimal decomposition scale is the one that best distinguishes between the normal pressure decay state and the leaking pressure state. At the optimal decomposition scale, the quantum Shannon entropy and other characteristics of the pressure signal quantum sequences corresponding to the normal and leaking states will be significantly different, thus helping to accurately determine whether a leak exists.

[0080] The formula for calculating quantum Shannon entropy is:

[0081] ;

[0082] in, Represents the decomposition scale The quantum Shannon entropy below, For decomposition scale Translation parameters The corresponding decomposition coefficients.

[0083] The expression for finding the optimal decomposition scale using the quantum annealing algorithm is as follows:

[0084] ;

[0085] in, This is the optimal decomposition scale. This is the regularization coefficient, which can be determined based on experience and the actual situation. For decomposition scale The variance of the downentropy value reflects the stability of the decomposition. For decomposition scale The quantum Shannon entropy below.

[0086] Step S600: Calculate the leakage rate based on the entropy change rate of the quantum Shannon entropy corresponding to the pressure decay rate and the optimal decomposition scale, and obtain the leakage result based on the leakage rate.

[0087] This embodiment calculates the leakage rate based on the pressure decay rate of the non-invasive blood pressure simulator and the entropy change rate of the quantum Shannon entropy at the optimal decomposition scale, and judges the leakage status of the non-invasive blood pressure simulator based on the leakage rate.

[0088] Specifically, the formula for calculating the leakage rate is:

[0089] ;

[0090] in, For leakage rate, For the correction pressure value of the non-invasive blood pressure simulator, The pressure decay rate of the non-invasive blood pressure simulator. , This is the measured pressure value from a non-invasive blood pressure simulator. Due to environmental interference, This is the coupling coefficient, used to adjust the proportion of the pressure decay rate in the leakage rate of the non-invasive blood pressure simulator. Its value can be set empirically. The quantum Shannon entropy at the optimal decomposition scale reflects the true leakage characteristics after denoising. Let be the entropy change rate of quantum Shannon entropy.

[0091] The leakage rate is calculated by combining the conventional pressure decay rate with the entropy change rate of quantum Shannon entropy, resulting in the final leakage rate. It can more comprehensively and accurately reflect the leakage level of non-invasive blood pressure simulators, thus improving the accuracy of leakage detection.

[0092] Among them, environmental interference The calculation formula is:

[0093] ;

[0094] in, This is the temperature interference coefficient. For real-time temperature, In this embodiment, the reference temperature is set to 20°C. Electromagnetic interference coefficient, The intensity of the ambient electromagnetic field.

[0095] The temperature interference coefficient (unit: kPa / ℃) and electromagnetic interference coefficient (unit: kPa / dB) can be obtained through training a quantum neural network. Specifically, the quantum neural network encodes historical pressure, temperature, and electromagnetic field data into quantum states, extracts environmental interference features using quantum gate operations, and trains and optimizes the quantum neural network parameters to minimize the error between predicted and actual interference. After training, the quantum neural network outputs the temperature interference coefficient. and electromagnetic interference coefficient .

[0096] Traditional detection methods often overlook environmental factors such as temperature drift and electromagnetic noise that interfere with pressure sensors, leading to insufficient detection accuracy. This embodiment corrects the measured pressure values ​​collected by the sensor based on real-time ambient temperature and electromagnetic field strength when calculating the leakage rate, eliminating the impact of environmental fluctuations on the detection results and improving detection accuracy and stability.

[0097] After calculating the leakage rate, the leakage result is obtained by analyzing the leakage rate. Specifically: when the leakage rate is greater than or equal to the first leakage threshold and less than the second leakage threshold, the leakage result is that there is a minor leakage; when the leakage rate is greater than or equal to the second leakage threshold, the leakage result is that there is a significant leakage. In this embodiment, determining the leakage status of the non-invasive blood pressure simulator includes:

[0098] when At that time, it was determined that the non-invasive blood pressure simulator had a minor leak;

[0099] when At that time, it was determined that the non-invasive blood pressure simulator had significant leakage;

[0100] in, The first leakage threshold, The second leakage threshold is defined as follows: the specific values ​​of the first and second leakage thresholds can be determined based on the actual situation.

[0101] In summary, this embodiment first acquires a pressure decay signal sequence under static conditions. This sequence contains information about the pressure change of the non-invasive blood pressure simulator over time, reflecting the presence and extent of leakage. Then, quantum phase encoding maps the pressure signal in the decay signal sequence to quantum states, enhancing the signal's characterization ability and improving the sensitivity to identify minute leaks. Next, a multi-scale decomposition of the pressure signal quantum sequence is performed using hybrid wavelet basis functions. The quantum Shannon entropy corresponding to different decomposition scales is calculated, and the optimal decomposition scale is selected using a quantum annealing algorithm. At the optimal decomposition scale, the pressure signal is decomposed into frequency components that best distinguish leakage features from normal pressure decay. Furthermore, since quantum Shannon entropy is a measure of signal uncertainty, its entropy change rate directly reflects changes in signal complexity. Therefore, the entropy change rate of the quantum Shannon entropy corresponding to the optimal decomposition scale can more accurately reflect the dynamic changes during pressure decay. Leakage causes transient fluctuations in the pressure signal; these fluctuations manifest as an abnormal increase in the entropy change rate at the optimal scale, thus enabling precise location of leakage events. By integrating the entropy change rate and pressure decay rate as dual indicators to jointly evaluate the leakage rate in both the time domain (pressure change) and the frequency domain (complexity change), the robustness of leakage detection is significantly improved.

[0102] like Figure 2 As shown, based on the above-described method for detecting leaks in a blood pressure simulator, this embodiment of the invention discloses a device for detecting leaks in a blood pressure simulator, comprising:

[0103] The acquisition module 600 is used to acquire the pressure signal of the target instrument under static conditions at preset time intervals after the target instrument is inflated to a preset pressure, and to obtain a pressure decay signal sequence.

[0104] The quantum phase encoding module 610 is used to map the pressure signal in the pressure decay signal sequence into a quantum state through quantum phase encoding to obtain a pressure signal quantum sequence.

[0105] The multi-scale decomposition module 620 is used to perform multi-scale decomposition on the pressure signal quantum sequence using hybrid wavelet basis functions, and to calculate the decomposition coefficients corresponding to each decomposition scale.

[0106] The quantum Shannon entropy calculation module 630 is used to calculate the quantum Shannon entropy corresponding to each decomposition scale based on the decomposition coefficients corresponding to each decomposition scale.

[0107] The optimal decomposition scale module 640 is used to solve for the optimal decomposition scale based on the quantum Shannon entropy corresponding to all decomposition scales using the quantum annealing algorithm.

[0108] Leakage rate module 650 is used to calculate the leakage rate based on the pressure decay rate and the entropy change rate of the quantum Shannon entropy corresponding to the optimal decomposition scale, and obtain the leakage result based on the leakage rate.

[0109] like Figure 3 As shown, an embodiment of the present invention discloses an electronic device, including a memory 401 storing executable program code and a processor 402 coupled to the memory 401;

[0110] The processor 402 calls the executable program code stored in the memory 401 to execute the blood pressure simulator leakage detection method described in the above embodiments.

[0111] This invention also discloses a computer-readable storage medium storing a computer program that causes a computer to execute the blood pressure simulator leakage detection method described in the above embodiments.

[0112] The purpose of the above embodiments is to reproduce and derive the technical solution of the present invention by way of example, and to fully describe the technical solution, purpose and effect of the present invention. The purpose is to enable the public to have a more thorough and comprehensive understanding of the disclosure of the present invention, and not to limit the scope of protection of the present invention.

[0113] The above embodiments are not an exhaustive list based on the present invention, and there may be many other embodiments not listed. Any substitutions and improvements made without departing from the concept of the present invention are within the protection scope of the present invention.

Claims

1. A method for detecting leakage in a blood pressure simulator, characterized in that, include: After inflating the target instrument to a preset pressure, the pressure signal of the target instrument under static conditions is collected at preset time intervals to obtain a pressure decay signal sequence. The pressure signal in the pressure decay signal sequence is mapped to a quantum state by quantum phase encoding to obtain the pressure signal quantum sequence. The pressure signal quantum sequence is decomposed into multiple scales using hybrid wavelet basis functions, and the decomposition coefficients corresponding to each decomposition scale are calculated. Calculate the quantum Shannon entropy for each decomposition scale based on the decomposition coefficients corresponding to each decomposition scale. Based on the quantum Shannon entropy corresponding to all decomposition scales, the optimal decomposition scale is solved using the quantum annealing algorithm. The leakage rate is calculated based on the entropy change rate of the quantum Shannon entropy corresponding to the pressure decay rate and the optimal decomposition scale, and the leakage result is obtained based on the leakage rate. The formula for calculating the leakage rate is: ； in, Leakage rate, The corrected pressure value for the target instrument. The pressure decay rate, , The measured pressure value of the target instrument. Due to environmental interference, The coupling coefficient is... The quantum Shannon entropy at the optimal decomposition scale. Let be the entropy change rate of quantum Shannon entropy.

2. The method for detecting leakage in a blood pressure simulator as described in claim 1, characterized in that, The formula for calculating quantum phase encoding is: ； in, The quantum state of the pressure signal, The length of the pressure attenuation signal sequence. For the first The ground state of a quantum bit The imaginary unit, The first in the pressure attenuation signal sequence The phase modulation factor of a pressure signal. This is the index of the pressure signal in the pressure decay signal sequence.

3. The method for detecting leakage in a blood pressure simulator as described in claim 1, characterized in that, The formula for calculating the decomposition coefficients is: ； in, For decomposition scale Translation parameters The corresponding decomposition coefficients, wavelet basis functions The conjugate transpose of the corresponding quantum state, The quantum state of the pressure signal, , , The maximum number of decomposition levels. , The length of the pressure attenuation signal sequence. This is the index of the pressure signal in the pressure decay signal sequence. The imaginary unit, The first in the pressure attenuation signal sequence The phase modulation factor of a pressure signal.

4. The method for detecting leakage in a blood pressure simulator as described in claim 1, characterized in that, The formula for calculating quantum Shannon entropy is: ； in, For decomposition scale The quantum Shannon entropy below, For decomposition scale Translation parameters The corresponding decomposition coefficients, is the length of the pressure attenuation signal sequence.

5. The method for detecting leakage in a blood pressure simulator as described in claim 1, characterized in that, The expression for solving the optimal decomposition scale is: ； in, This is the optimal decomposition scale. The regularization coefficient is . For decomposition scale The variance of the underentropy value For decomposition scale The quantum Shannon entropy below.

6. The method for detecting leakage in a blood pressure simulator as described in claim 1, characterized in that, The method of obtaining leakage results based on leakage rate includes: When the leakage rate is greater than or equal to the first leakage threshold and less than the second leakage threshold, the leakage result is that the target instrument has a minor leakage; when the leakage rate is greater than or equal to the second leakage threshold, the leakage result is that the target instrument has a significant leakage.

7. A leak detection device for a blood pressure simulator, characterized in that, include: The acquisition module is used to inflate the target instrument to a preset pressure and then acquire the pressure signal of the target instrument under static conditions at preset time intervals to obtain a pressure decay signal sequence. A quantum phase encoding module is used to map the pressure signal in the pressure decay signal sequence into a quantum state through quantum phase encoding to obtain a pressure signal quantum sequence. The multi-scale decomposition module is used to perform multi-scale decomposition of the pressure signal quantum sequence using hybrid wavelet basis functions, and to calculate the decomposition coefficients corresponding to each decomposition scale. The quantum Shannon entropy calculation module is used to calculate the quantum Shannon entropy corresponding to each decomposition scale based on the decomposition coefficients corresponding to each decomposition scale. The optimal decomposition scale module is used to solve for the optimal decomposition scale based on the quantum Shannon entropy corresponding to all decomposition scales using the quantum annealing algorithm. The leakage rate module is used to calculate the leakage rate based on the pressure decay rate and the entropy change rate of the quantum Shannon entropy corresponding to the optimal decomposition scale, and to obtain the leakage result based on the leakage rate. The formula for calculating the leakage rate is: ； in, Leakage rate, The corrected pressure value for the target instrument. The pressure decay rate, , The measured pressure value of the target instrument. Due to environmental interference, The coupling coefficient is... The quantum Shannon entropy at the optimal decomposition scale. Let be the entropy change rate of quantum Shannon entropy.

8. An electronic device, characterized in that, It includes a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the blood pressure simulator leakage detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program causes a computer to perform the blood pressure simulator leakage detection method according to any one of claims 1 to 6.

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