Leakage detection method and device for blood pressure simulator, electronic equipment and storage medium

Abstract

The invention discloses a blood pressure simulator leakage detection method and device, electronic equipment and a storage medium, and the method comprises the steps: inflating a target instrument to a preset pressure, collecting pressure signals of the target instrument under a static condition according to a preset time interval, and obtaining a pressure attenuation signal sequence; mapping pressure signals in the pressure attenuation signal sequence into a quantum state through quantum phase coding to obtain a pressure signal quantum sequence; performing multi-scale decomposition on the pressure signal quantum sequence by adopting a hybrid wavelet basis function, and calculating a decomposition coefficient corresponding to each decomposition scale; calculating a quantum Shannon entropy corresponding to each decomposition scale according to the decomposition coefficient corresponding to each decomposition scale; based on the quantum Shannon entropy corresponding to all the decomposition scales, solving an optimal decomposition scale by adopting a quantum annealing algorithm; and calculating a leakage rate based on the pressure attenuation rate and the entropy change rate of the quantum Shannon entropy corresponding to the optimal decomposition scale, and obtaining a leakage result based on the leakage rate. The sensitivity and the accuracy during leakage detection can be improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of equipment detection, and particularly relates to a blood pressure simulator leakage detection method and device, electronic equipment and storage medium. BACKGROUND

[0002] As a key medical measuring instrument, the sealing performance of the gas path system of a non-invasive blood pressure simulator directly affects the accuracy and reliability of blood pressure simulation. The current industry generally adopts the oscillographic method principle, and uses static pressure attenuation as the basis for leakage judgment. This method determines the sealing state by monitoring whether the linear decay rate at a fixed pressure point exceeds the threshold value. However, the existing detection method has the following defects:

[0003] Sensitivity limitation of static detection: The traditional method cannot effectively capture the nonlinear leakage characteristics (such as micro-pore leakage and intermittent leakage under dynamic pressure fluctuation). When the leakage is below the detection threshold, false negatives are easy to occur, causing small leaks to accumulate into systematic errors over a long period of use.

[0004] Misjudgment risk caused by environmental interference: Pressure sensors are susceptible to environmental temperature drift, electromagnetic noise and other interference, producing signal decay characteristics similar to real leakage. Conventional filtering algorithms have insufficient signal-to-noise separation capability in complex noise backgrounds, resulting in a significant increase in false detection rates.

[0005] Low efficiency of high-dimensional signal processing: Conventional wavelet transform processing of high-dimensional pressure signals has a large amount of calculation, making it difficult to dynamically compensate for errors in real time, resulting in low detection sensitivity.

[0006] Therefore, the detection sensitivity and accuracy of the existing leakage detection method need to be improved. SUMMARY

[0007] The present application aims to provide a blood pressure simulator leakage detection method, device, electronic equipment and computer readable storage medium, which can improve the sensitivity and accuracy of blood pressure simulator leakage detection.

[0008] The present application discloses a blood pressure simulator leakage detection method, comprising:

[0009] After inflating the target instrument to a preset pressure, the pressure signal of the target instrument under static conditions is collected at a preset time interval 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 a pressure signal quantum sequence;

[0011] The pressure signal quantum sequence is decomposed at multiple scales using a hybrid wavelet basis function, and the decomposition coefficients corresponding to each decomposition scale are calculated;

[0012] According to the decomposition coefficient corresponding to each decomposition scale, the quantum Shannon entropy corresponding to each decomposition scale is calculated;

[0013] Based on the quantum Shannon entropy corresponding to all decomposition scales, the quantum annealing algorithm is used to solve the optimal decomposition scale;

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

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

[0016] ;

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

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

[0019] ;

[0020] in, Decomposition scale The corresponding decomposition coefficients are, is the translation parameter, is the wavelet basis function The conjugate transpose of the corresponding quantum state, , , is the maximum number of decomposition levels, , is the length of the pressure decay signal sequence, 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, Decomposition scale The quantum Shannon entropy under Decomposition scale , translation parameters corresponding decomposition coefficients.

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

[0025] ;

[0026] wherein, is the optimal decomposition scale, is a regularization coefficient, is the decomposition scale is the variance of the lower entropy value, is the quantum Shannon entropy under the decomposition scale .

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

[0028] ;

[0029] wherein, is the leakage rate, is the corrected pressure value of the target instrument, is the pressure decay rate, , is the measured pressure value of the target instrument, is the environmental disturbance, is the coupling coefficient, is the quantum Shannon entropy under the optimal decomposition scale, is the entropy change rate of the quantum Shannon entropy.

[0030] In some embodiments, the leakage result is obtained based on the leakage rate, comprising:

[0031] When the leakage rate is greater than or equal to a first leakage threshold and less than a second leakage threshold, the leakage result is that the target instrument has a small 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] The second aspect of the present application discloses a blood pressure simulator leakage detection device, comprising:

[0033] The acquisition module is configured to acquire the pressure signal of the target instrument under static conditions at a preset time interval after inflating the target instrument to a preset pressure, and obtain a pressure decay signal sequence.

[0034] The quantum phase encoding module is configured to map the pressure signal in the pressure decay signal sequence into a quantum state through quantum phase encoding, and obtain a pressure signal quantum sequence.

[0035] a multi-scale decomposition module, configured to perform multi-scale decomposition on the pressure signal quantum sequence by using a hybrid wavelet basis function, and calculate decomposition coefficients corresponding to each decomposition scale;

[0036] a quantum Shannon entropy calculation module, configured to calculate quantum Shannon entropy corresponding to each decomposition scale according to the decomposition coefficients corresponding to each decomposition scale;

[0037] an optimal decomposition scale module, configured to solve an optimal decomposition scale by using a quantum annealing algorithm based on the quantum Shannon entropy corresponding to all decomposition scales;

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

[0039] The third aspect of the present application discloses an electronic device, comprising a memory storing executable program codes and a processor coupled with the memory; the processor invokes the executable program codes stored in the memory, and is configured to execute the blood pressure simulator leakage detection method disclosed in the first aspect.

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

[0041] The present application has the following beneficial effects: firstly, the pressure decay signal sequence is collected under static conditions, which contains information about the change of pressure of the target instrument over time, and the information can reflect whether the target instrument has leakage and the degree of leakage; then the pressure signal in the pressure decay signal sequence is mapped to a quantum state through quantum phase encoding, which enhances the representation ability of the signal and improves the recognition sensitivity of the characteristics of small leakage; then the pressure signal quantum sequence is decomposed by using a hybrid wavelet basis function, the quantum Shannon entropy corresponding to different decomposition scales is calculated, and the optimal decomposition scale is selected by using a quantum annealing algorithm; under the optimal decomposition scale, the pressure signal is decomposed into frequency components that can best distinguish the leakage characteristics and normal pressure decay, and since the quantum Shannon entropy is a measure of signal uncertainty, the entropy change rate can directly reflect the change of signal complexity, and the robustness of the leakage detection is significantly improved by fusing the entropy change rate and the pressure decay rate to jointly evaluate the leakage rate in the time domain and the frequency domain, which has higher sensitivity and accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0042] The drawings herein show specific examples of the technical solutions of the present application, and constitute part of the specification together with the specific embodiments, for explaining the technical solutions, principles and effects of the present application.

[0043] Unless specifically stated or otherwise as clear from the context of the entire disclosure, the same reference numerals and characters mean the same techniques, regardless of whether they are shown in different accompanying drawings. It is to be noted, like reference numerals and characters refer to components having similar functions in the drawings. The components denoted by different reference numerals and characters can represent similar or identical components.

[0044] Figure 1 is a flow chart of a blood pressure simulator leakage detection method embodiment of the present application;

[0045] Figure 2 is a structural schematic diagram of a blood pressure simulator leakage detection device embodiment of the present application;

[0046] Figure 3 is a structural schematic diagram of an electronic device embodiment of the present application. DETAILED DESCRIPTION

[0047] Unless specifically stated or otherwise as clear from the context of the entire disclosure, 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 belongs. In the case of combining the technical solutions of the present application with the real scene, all technical and scientific terms used herein can also have meanings corresponding to the purpose of implementing the technical solutions of the present application. The terms "first, second" used herein are only used to distinguish the names and do not represent the specific quantity or order. The term "and / or" used herein includes any and all combinations of one or more related listed items.

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

[0049] Unless specifically stated or otherwise as clear from the context of the entire disclosure, "the", "this" used herein refer to the technical features or technical contents mentioned or described before the corresponding position or the technical features or technical contents mentioned or described before the corresponding position. The technical features or technical contents can be the same as the technical features or technical contents mentioned or described before the corresponding position, or can be similar. In addition, the terms "include" and "have" used herein, as well as any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device.

[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] In order to improve the sensitivity and accuracy of leak detection in blood pressure simulators, the present invention utilizes the high efficiency and parallel processing capabilities of quantum computing to significantly improve the identification sensitivity of weak leakage signals. It also combines the localization characteristics and multi-scale analysis capabilities of wavelet analysis to accurately extract multi-dimensional leakage characteristics, and integrates the dual indicators of entropy change rate and pressure decay rate to jointly calculate the leakage rate from the time domain (pressure change) and frequency domain (complexity change), significantly improving the robustness of the leakage detection method and having higher sensitivity and accuracy.

[0052] The present invention discloses a blood pressure simulator leak detection method for leak detection of non-invasive blood pressure simulators. This method can be implemented through computer programming as a standalone blood pressure simulator leak detection system. The method can be performed by an electronic device such as a computer, laptop, or tablet computer, or a control chip embedded in an electronic device, but the present invention is not limited to this. It should be noted that this method is not limited to non-invasive blood pressure simulators and can also be used for other medical 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 the target instrument is inflated to a preset pressure, a pressure signal of the target instrument under static conditions is collected at preset time intervals to obtain a pressure decay signal sequence;

[0055] The target instrument is a non-invasive blood pressure simulator. Static conditions mean the gas circuit system must be completely static, with all inflation and deflation valves closed and any airflow stopped. This means there is no gas flow and no active inflation or deflation operations.

[0056] The preset pressure can be determined according to the actual situation of the target instrument. First, the target instrument is inflated to the preset pressure, and then the pressure signal is collected. When collecting, the collection is carried out according to the preset time interval. In this embodiment, the time interval is preferably 0.1s, and the pressure decay signal sequence is obtained. , .

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

[0058] Quantum phase encoding is a way to store information in the phase part of a quantum state by adjusting the phase modulation factor , can encode different information.

[0059] Specifically, the calculation formula of quantum phase encoding is:

[0060] ;

[0061] wherein, is the quantum state of the pressure signal, is the length of the pressure decay signal sequence, is the th quantum bit ground state, is the imaginary unit, is the phase modulation factor of the th pressure signal in the pressure decay signal sequence, is the index of the pressure signal in the pressure decay signal sequence.

[0062] wherein, the calculation formula is:

[0063] ,

[0064] wherein, is the maximum pressure value in the pressure decay signal sequence, is the minimum pressure value in the pressure decay signal sequence, is the pressure value of the th pressure signal in the pressure decay signal sequence.

[0065] In the pressure decay signal sequence, the pressure values at different times are different, resulting in different values corresponding to them. By continuously calculating the values at different times, the dynamic change information of the pressure decay over time can be encoded. When the non-invasive blood pressure simulator is in normal no-leakage state, small leakage state and significant leakage state, the corresponding pressure decay signal sequence is different, and distribution is also different. Therefore, by extracting and analyzing the features of the encoded pressure signal quantum sequence, the difference can be accurately identified, and the leakage condition of the non-invasive blood pressure simulator can be further judged.

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

[0067] Step S300: using a hybrid wavelet basis function to perform multi-scale decomposition on the pressure signal quantum sequence, and calculating the decomposition coefficients corresponding to each decomposition scale;

[0068] The hybrid wavelet basis function is a function system formed by combining or fusing different types of wavelet basis functions. It combines the characteristics of multiple wavelet bases to better adapt to the diverse needs of complex signal processing, image analysis and other fields. is an adaptive Haar-Daubechies mixed wavelet basis (a mixture of Haar wavelet basis 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, is the translation parameter, is the time variable.

[0072] By changing the decomposition scale The value of can adjust the frequency range of the wavelet basis function, thereby realizing multi-scale analysis of different frequency components of the signal. The value of can make the wavelet basis function move on the time axis, so as to analyze the signal in different time periods. Therefore, the hybrid wavelet basis function has good localization characteristics in both time domain and frequency domain, and can decompose and analyze the signal from multiple scales and angles.

[0073] The decomposition coefficients reflect the projection size 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 leak-related features from the pressure signal, providing a highly sensitive analytical basis for microleak detection. Because the scale parameter (i.e., decomposition scale) and translation parameter of the wavelet basis function can be varied, the decomposition coefficients can reveal the characteristics of the pressure signal at different scales and time locations.

[0074] Specifically, the calculation formula for the decomposition coefficient corresponding to a certain decomposition scale is:

[0075] ;

[0076] in, Decomposition scale The corresponding decomposition coefficients are, ; is the translation parameter, , used to locate the time domain position of the leakage event; is the wavelet basis function The conjugate transpose of the corresponding quantum state; is the maximum number of decomposition levels, , corresponding to the pressure signal frequency band (0.1~10Hz), is the length of the pressure decay signal sequence; is the index of the pressure signal in the pressure decay signal sequence.

[0077] Step S400: Calculating the quantum Shannon entropy corresponding to each decomposition scale according to the decomposition coefficient corresponding to each decomposition scale;

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

[0079] Quantum Shannon entropy measures the uncertainty or complexity of the quantum state corresponding to the pressure signal quantum sequence at a given decomposition scale. By calculating the quantum Shannon entropy at different decomposition scales, a quantum annealing algorithm can be used to find the optimal decomposition scale. The optimal decomposition scale is the one that maximizes the distinction between the normal pressure decay state and the leak pressure state. At this optimal decomposition scale, characteristics such as the quantum Shannon entropy corresponding to the pressure signal quantum sequences in the normal and leak states are clearly distinct, helping to accurately determine whether a leak exists.

[0080] The calculation formula of quantum Shannon entropy is:

[0081] ;

[0082] in, Representative decomposition scale The quantum Shannon entropy under Decomposition scale , translation parameters The corresponding decomposition coefficient.

[0083] The expression for solving the optimal decomposition scale by quantum annealing algorithm is:

[0084] ;

[0085] in, is the optimal decomposition scale, is the regularization coefficient, which can be determined based on experience in combination with actual conditions; Decomposition scale The variance of the lower entropy value reflects the decomposition stability, Decomposition scale Quantum Shannon entropy under .

[0086] Step S600: 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.

[0087] The embodiment is based on the pressure decay rate of the non-invasive blood pressure simulator and the entropy change rate of the quantum Shannon entropy of the optimal decomposition scale to calculate the leakage rate, and based on the leakage rate to judge the leakage of the non-invasive blood pressure simulator.

[0088] Specifically, the calculation formula of the leakage rate is:

[0089] ;

[0090] wherein, is the leakage rate, is the corrected pressure value of the non-invasive blood pressure simulator, is the pressure decay rate of the non-invasive blood pressure simulator, , is the measured pressure value of the non-invasive blood pressure simulator, is the environmental disturbance, is the coupling coefficient, used to adjust the proportion of the pressure decay rate of the non-invasive blood pressure simulator in the leakage rate, and the value can be set according to experience, is the quantum Shannon entropy under the optimal decomposition scale, reflecting the real leakage characteristics after denoising, is the entropy change rate of the quantum Shannon entropy.

[0091] By combining the traditional pressure decay rate with the entropy change rate of the quantum Shannon entropy to calculate the leakage rate, the final leakage rate can more comprehensively and accurately reflect the leakage degree of the non-invasive blood pressure simulator, and the accuracy of the leakage detection is improved.

[0092] wherein, the environmental disturbance is calculated by the formula:

[0093] ;

[0094] wherein, is the temperature disturbance coefficient, is the real-time temperature, is the reference temperature, in the embodiment, the reference temperature is 20℃, is the electromagnetic interference coefficient, is the environmental electromagnetic field intensity.

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

[0096] Compared to traditional detection methods, which tend to overlook interference from environmental factors such as temperature drift and electromagnetic noise on pressure sensors, resulting in insufficient detection accuracy, this embodiment corrects the measured pressure value collected by the sensor based on the current real-time 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 the leakage rate is calculated, 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 a slight leakage; when the leakage rate is greater than or equal to the second leakage threshold, the leakage result is a significant leakage. In this embodiment, the leakage of the non-invasive blood pressure simulator is determined, including:

[0098] when When the non-invasive blood pressure simulator is detected, it is determined that there is a slight leak;

[0099] when When the non-invasive blood pressure simulator is detected, it is determined that there is a significant leakage;

[0100] in, is the first leakage threshold, The specific values ​​of the first leakage threshold and the second leakage threshold can be determined according to actual conditions.

[0101] In summary, this embodiment first acquires a pressure decay signal sequence under static conditions. This pressure decay signal sequence contains information about the pressure changes over time in the non-invasive blood pressure simulator, indicating whether the simulator is leaking and the extent of the leak. Quantum phase encoding is then used to map the pressure signal in the pressure decay signal sequence to a quantum state, enhancing the signal's characterization capabilities and improving the sensitivity of identifying subtle leaks. A mixed wavelet basis function is then used to perform a multi-scale decomposition of the pressure signal quantum sequence. The quantum Shannon entropy corresponding to different decomposition scales is then 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 the quantum Shannon entropy, as a measure of signal uncertainty, directly reflects changes in signal complexity, the entropy change rate corresponding to the optimal decomposition scale more accurately reflects the dynamic changes in the pressure decay process. Leaks can cause transient fluctuations in the pressure signal, which manifest as an abnormal increase in the entropy change rate at the optimal scale, enabling precise location of leak events. By integrating the dual indicators of entropy change rate and pressure decay rate to jointly evaluate the leakage rate in the time domain (pressure change) and frequency domain (complexity change), the robustness of leakage detection is significantly improved.

[0102] As Figure 2 shown, based on the above blood pressure simulator leakage detection method, the embodiment of the application discloses a blood pressure simulator leakage detection device, comprising:

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

[0104] The quantum phase encoding module 610 is configured to map the pressure signal in the pressure decay signal sequence into a quantum state by quantum phase encoding, and obtain a pressure signal quantum sequence.

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

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

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

[0108] The leakage rate module 650 is configured 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 a leakage result based on the leakage rate.

[0109] As Figure 3 shown, the embodiment of the application discloses an electronic device, comprising a memory 401 storing executable program codes and a processor 402 coupled with the memory 401.

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

[0111] The embodiment of the application also discloses a computer readable storage medium storing a computer program, wherein the computer program enables the computer to execute the blood pressure simulator leakage detection method described in the above embodiments.

[0112] The purpose of the above embodiments is to exemplarily reproduce and deduce the technical solutions of the application, and to completely describe the technical solutions, purposes and effects of the application. The purpose is to make the public understand the disclosure of the application more thoroughly and comprehensively, and not to limit the protection scope of the application.

[0113] The above embodiments are also not exhaustive enumeration based on the present application, in addition to which, there can be a plurality of other embodiments not listed. Any substitution and improvement made without violating the concept of the present application is within the scope of protection of the present application.

Claims

1. A blood pressure simulator leakage detection method, characterized in that: include: After the target instrument is inflated 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; Mapping the pressure signal in the pressure decay signal sequence into a quantum state through quantum phase encoding to obtain a pressure signal quantum sequence; Using a mixed wavelet basis function to perform multi-scale decomposition on the pressure signal quantum sequence, and calculating the decomposition coefficient corresponding to each decomposition scale; According to the decomposition coefficient corresponding to each decomposition scale, the quantum Shannon entropy corresponding to each decomposition scale is calculated; Based on the quantum Shannon entropy corresponding to all decomposition scales, the quantum annealing algorithm is used to solve the optimal decomposition scale; The leakage rate is calculated based on the pressure decay rate and the entropy change rate of the quantum Shannon entropy corresponding to the optimal decomposition scale, and the leakage result is obtained based on the leakage rate.

2. The blood pressure simulator leakage detection method according to claim 1, wherein: The calculation formula of quantum phase encoding is: ； in, is the quantum state of the pressure signal, is the length of the pressure decay signal sequence, For the quantum bit ground state, is the imaginary unit, The first The phase modulation factor of the pressure signal, is the index of the pressure signal in the pressure decay signal sequence.

3. The blood pressure simulator leakage detection method according to claim 1, wherein: The formula for calculating the decomposition coefficient is: ； in, Decomposition scale The corresponding decomposition coefficients are, is the translation parameter, is the wavelet basis function The conjugate transpose of the corresponding quantum state, , , is the maximum number of decomposition levels, , is the length of the pressure decay signal sequence, is the index of the pressure signal in the pressure decay signal sequence.

4. The blood pressure simulator leakage detection method according to claim 1, wherein: The formula for calculating quantum Shannon entropy is: ； in, Decomposition scale The quantum Shannon entropy under Decomposition scale , translation parameters The corresponding decomposition coefficient.

5. The blood pressure simulator leakage detection method according to claim 1, wherein: The expression for solving the optimal decomposition scale is: ； in, is the optimal decomposition scale, is the regularization coefficient, Decomposition scale The variance of the lower entropy value, Decomposition scale Quantum Shannon entropy under .

6. The blood pressure simulator leakage detection method according to claim 1, wherein: The formula for calculating the leakage rate is: ； in, is the leakage rate, is the corrected pressure value of the target instrument, is the pressure decay rate, , is the measured pressure value of the target instrument, For environmental interference, is the coupling coefficient, is the quantum Shannon entropy at the optimal decomposition scale, is the entropy change rate of quantum Shannon entropy.

7. The blood pressure simulator leakage detection method according to claim 1, wherein: The obtaining of leakage results based on the 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 slight 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.

8. A blood pressure simulator leakage detection device, characterized in that: include: An acquisition module is used to acquire the pressure signal of the target instrument under static conditions at preset time intervals after inflating the target instrument to a preset pressure, thereby obtaining a pressure decay signal sequence; a quantum phase encoding module, configured to map the pressure signal in the pressure attenuation signal sequence into a quantum state through quantum phase encoding to obtain a pressure signal quantum sequence; A multi-scale decomposition module, configured to perform multi-scale decomposition on the pressure signal quantum sequence using a mixed wavelet basis function and calculate a decomposition coefficient corresponding to each decomposition scale; The quantum Shannon entropy calculation module is used to calculate the quantum Shannon entropy corresponding to each decomposition scale according to the decomposition coefficient corresponding to each decomposition scale; The optimal decomposition scale module is used to solve the optimal decomposition scale using the quantum annealing algorithm based on the quantum Shannon entropy corresponding to all decomposition scales; 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 obtain the leakage result based on the leakage rate.

9. An electronic device, characterized in that: It comprises 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 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute the blood pressure simulator leakage detection method according to any one of claims 1 to 7.

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