Fault diagnosis method and fault diagnosis system for dilution refrigerator

Abstract

The invention provides a fault diagnosis method and system for a dilution refrigerator, and relates to the technical field of low-temperature engineering, the technical field of quantum information and the technical field of signal processing. The method comprises the steps that a quantum bit sensor is used for collecting vibration signals of multiple components of the dilution refrigerator, the quantum bit sensor is arranged on a cold disc of the dilution refrigerator, and the vibration signals of the multiple components are transmitted to the cold disc through a connecting pipeline; performing spectral analysis on the vibration signals, and determining respective frequency distribution characteristics of the plurality of components; determining a target component with abnormal vibration based on the respective frequency distribution characteristics of the plurality of components; and based on the frequency distribution characteristics of the target component and a preset fault frequency characteristic table of the target component, a fault diagnosis result of the dilution refrigerator is determined, and the fault frequency characteristic table comprises multiple fault types of the target component and reference frequency characteristics corresponding to the multiple fault types. Therefore, the accuracy and intelligence of fault diagnosis of the dilution refrigerator are improved.

Description

Technical Field

[0001] The present invention relates to the fields of cryogenic engineering technology, quantum information technology and signal processing technology, and in particular to a fault diagnosis method and a fault diagnosis system for a dilution refrigerator. Background Art

[0002] A dilution refrigerator is a device that uses the properties of a mixture of helium-3 and helium-4 to achieve extremely low temperature refrigeration. Its lowest temperature can reach the mK (milliKelvin) level. When the mixture of helium-3 and helium-4 is at 0.86K, it will separate into two phases. The upper layer is called the concentrated phase, which is mainly composed of helium-3, and the lower layer is called the dilute phase, which is mainly composed of a mixture of helium-3 and helium-4. When helium-3 atoms are removed from the dilute phase, in order to maintain the balance of the two phases, the helium-3 atoms in the concentrated phase will enter the dilute phase through the phase interface to replenish the removed helium-3 atoms. This process is endothermic, and this endothermic phenomenon can be used to make a dilution refrigerator.

[0003] Due to the long-term low-temperature operation, the dilution refrigerator may produce various faults, resulting in interruption of equipment operation. However, due to the complexity of the components of the dilution refrigerator, the failure is sudden and difficult to distinguish with the naked eye, and there has been a lack of effective early warning measures for a long time. In addition, as a key component of the quantum computing system, the dilution refrigerator has long been a pain point for researchers in related fields due to the sudden failure of the dilution refrigerator in the measurement and control experiments of quantum processors, which has caused unplanned downtime. Summary of the invention

[0004] In view of this, the present invention provides a fault diagnosis method and a fault diagnosis system for a dilution refrigerator.

[0005] In one aspect of the present invention, a fault diagnosis method for a dilution refrigerator is provided, the method comprising: collecting vibration signals of multiple components of the dilution refrigerator using a quantum bit sensor, wherein the quantum bit sensor is arranged on a cold plate of the dilution refrigerator, and the vibration signals of each of the multiple components are transmitted to the cold plate through a connecting pipe; performing spectrum analysis on the vibration signal to determine the frequency distribution characteristics of each of the multiple components; determining a target component with abnormal vibration based on the frequency distribution characteristics of each of the multiple components; determining a fault diagnosis result of the dilution refrigerator based on the frequency distribution characteristics of the target component and a fault frequency characteristic table preset for the target component, wherein the fault frequency characteristic table includes multiple fault types of the target component and reference frequency characteristics corresponding to each of the multiple fault types.

[0006] According to an embodiment of the present invention, the vibration signals of the multiple components include vibration signals of the pulse tube cold head, the compressor assembly, the pump assembly, the valve assembly and the pipeline, and the multiple components transmit their respective vibration signals to the cold plate in different vibration directions.

[0007] According to an embodiment of the present invention, the quantum bit sensor includes a quantum bit chip that integrates resonant cavities in three orthogonal directions of X-axis, Y-axis and Z-axis to collect vibration signals in multiple different directions from the pulse tube cold head, compressor assembly, pump assembly, valve assembly and pipeline.

[0008] According to an embodiment of the present invention, a spectral analysis is performed on a vibration signal to determine the frequency distribution characteristics of each of the multiple components, including: performing Fourier transform or cepstrum analysis on the vibration signal to determine the initial frequency distribution characteristics of the vibration signal; obtaining reference frequency characteristics of each of the multiple components, wherein the reference frequency characteristics include a reference frequency of the target component and an amplitude corresponding to the reference frequency; and using the reference frequency characteristics of each of the multiple components to normalize the initial frequency distribution characteristics respectively to obtain the frequency distribution characteristics of each of the multiple components.

[0009] According to an embodiment of the present invention, initial frequency distribution characteristics are respectively normalized using respective reference frequency characteristics of a plurality of components to obtain respective frequency distribution characteristics of the plurality of components, including: respectively normalizing initial frequency distribution characteristics using respective reference frequency characteristics of a plurality of components to obtain respective normalized frequency distribution characteristics of the plurality of components; and determining respective frequency distribution characteristics of the plurality of components based on respective reference frequencies of the plurality of components and frequencies that are integer multiples of the reference frequencies in the normalized frequency distribution characteristics.

[0010] According to an embodiment of the present invention, based on the frequency distribution characteristics of each of the multiple components, the target component of abnormal vibration is determined, including: obtaining the operating frequency characteristics of the multiple components in a normal state, the operating frequency characteristics are obtained by respectively collecting the vibration signals of the multiple components in a normal state using a quantum bit sensor; based on the frequency distribution characteristics of each of the multiple components and the operating frequency characteristics of the multiple components, the target component of abnormal vibration is determined.

[0011] According to an embodiment of the present invention, based on the frequency distribution characteristics of the target component and the fault frequency characteristic table of the target component, determining the fault diagnosis result of the dilution refrigerator includes: calculating the average value of the amplitude in the frequency distribution characteristics; based on the average value, screening the frequency distribution characteristics of the target component to obtain the target frequency characteristics of the target component; and determining the fault diagnosis result of the dilution refrigerator based on the target frequency characteristics of the target component and the fault frequency characteristic table of the target component.

[0012] According to an embodiment of the present invention, based on the target frequency characteristics of the target component and the fault frequency characteristic table of the target component, the fault diagnosis result of the dilution refrigerator is determined, including: sorting the target frequency characteristics and the fault frequency characteristic table to obtain the target characteristic vector of the target component and the reference characteristic vectors of each of the multiple fault types; and determining the fault diagnosis result of the target component according to the similarity between the target characteristic vector and the reference characteristic vectors of each of the multiple fault types.

[0013] According to an embodiment of the present invention, the method further comprises: determining a collection frequency of the vibration signal according to respective reference frequencies of the plurality of components; and collecting the vibration signals of the plurality of components of the dilution refrigerator according to the collection frequency.

[0014] In another aspect, the present invention further provides a dilution refrigerator fault diagnosis system, comprising: a dilution refrigerator; a quantum bit sensor, disposed on a cold plate of the dilution refrigerator;

[0015] An electronic device is used to receive the vibration signal collected by the quantum bit sensor and execute the above method.

[0016] According to the embodiments of the present invention, based on the sensitivity of the quantum bit sensor to vibration, the vibration signals of multiple components of the dilution refrigerator can be collected with high sensitivity, and the frequency distribution characteristics of each of the multiple components can be determined through spectrum analysis. It can be preliminarily determined whether the multiple components are in a normal vibration state and the target component with abnormal vibration can be determined. Then, by comparing with the preset fault frequency characteristic table of the target component, the fault type of the target component can be accurately and quickly determined. Thus, the accuracy and intelligence of the dilution refrigerator fault diagnosis are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a fault diagnosis method according to an embodiment of the present invention is shown;

[0018] Figure 2a A spectrum diagram obtained by performing spectrum analysis on a vibration signal according to an embodiment of the present invention is shown;

[0019] Figure 2b shows a frequency spectrum diagram obtained after normalizing the initial frequency distribution characteristics according to an embodiment of the present invention;

[0020] Figure 3 A structural block diagram of a dilution refrigerator according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0021] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0022] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0023] All terms used herein, including technical and scientific terms, have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0024] When using expressions such as "at least one of A, B, and C, etc.", it should generally be interpreted as the meaning of the expression generally understood by those skilled in the art. For example, "a system having at least one of A, B, and C" should include but not be limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc. When using expressions such as "at least one of A, B, or C, etc.", it should generally be interpreted as the meaning of the expression generally understood by those skilled in the art. For example, "a system having at least one of A, B, or C" should include but not be limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.

[0025] It should also be noted that the directional terms mentioned in the embodiments, such as "upper", "lower", "front", "back", "left", "right", etc., are only reference directions of the drawings and are not intended to limit the scope of protection of the present invention. Throughout the drawings, the same elements are represented by the same or similar reference numerals. Conventional structures or configurations will be omitted when they may cause confusion in the understanding of the present invention.

[0026] Figure 1 A flow chart of a fault diagnosis method according to an embodiment of the present invention is shown.

[0027] like Figure 1 As shown, the method includes: operations S110~S140.

[0028] In operation S110, a qubit sensor is used to collect vibration signals of multiple components of the dilution refrigerator. The qubit sensor is disposed on a cold plate of the dilution refrigerator, and the multiple components are connected to the cold plate respectively.

[0029] In operation S120 , a spectrum analysis is performed on the vibration signal to determine frequency distribution characteristics of each of the plurality of components.

[0030] In operation S130 , a target component of abnormal vibration is determined based on the frequency distribution characteristics of each of the plurality of components.

[0031] In operation S140, a fault diagnosis result of the dilution refrigerator is determined based on the frequency distribution characteristics of the target component and a fault frequency characteristic table preset for the target component, wherein the fault frequency characteristic table includes multiple fault types of the target component and reference frequency characteristics corresponding to each of the multiple fault types.

[0032] The qubit sensor is a quantum sensor that uses qubits as core components. Its principle is to use the sensitivity of quantum states to external mechanical disturbances, and to infer vibration parameters (frequency, amplitude, direction) by monitoring changes in quantum states (such as energy levels, phases, or entangled states). Since qubits are extremely sensitive to external environmental disturbances (such as mechanical vibrations) when they are in a superposition state, and tiny vibrations can cause the energy levels of qubits to shift or the phases to change, qubit sensors can be used to achieve high-sensitivity detection of multiple components, thereby improving the diagnostic accuracy of the components. In addition, qubits can still detect sub-nanometer displacements or micro-strains at millikelvin temperatures, avoiding the sensitivity loss or failure of traditional sensors due to extremely low temperatures, and have strong compatibility with extremely low temperatures.

[0033] Performing spectrum analysis on vibration signals may include preprocessing the vibration signals. The preprocessing may include denoising, filtering and other operations on the vibration signals, which may eliminate interference and noise in the signals and improve the quality of the signals.

[0034] After preprocessing the vibration signal, the vibration signal can be converted from a time domain signal to a frequency domain signal through spectrum analysis, and then the frequency distribution characteristics of each of the multiple components can be determined based on the frequency domain signal.

[0035] The frequency distribution feature includes multiple frequency distributions and the amplitudes of the multiple frequencies. The frequency distribution in the frequency distribution feature can reflect the structural characteristics and working status of the component. The abnormally vibrating component may have harmonics (including integer multiples of the reference frequency). The amplitude can reflect the vibration intensity of the component. The abnormal increase in the harmonic amplitude may mean that the component is faulty or the wear is more serious. According to the frequency distribution and corresponding amplitude of the component, it can be preliminarily judged whether the component is abnormal.

[0036] The preset fault frequency characteristic table of the target component can be determined based on historical data and experimental data, and includes multiple fault types and their corresponding reference frequency characteristics. The fault diagnosis result of the target component can be determined by comparing the frequency distribution characteristics of the target component with the reference frequency characteristics corresponding to each of the multiple fault types one by one.

[0037] According to the embodiments of the present invention, based on the sensitivity of the quantum bit sensor to vibration, the vibration signals of multiple components of the dilution refrigerator can be collected with high sensitivity, and the frequency distribution characteristics of each of the multiple components can be determined by spectrum analysis. It is possible to preliminarily determine whether the multiple components are in a normal vibration state and determine the target component with abnormal vibration, and then compare it with the preset fault frequency characteristic table of the target component to accurately and quickly determine the fault type of the target component. Thus, the accuracy and automation of dilution refrigerator fault diagnosis are improved.

[0038] Moreover, the vibration information measured by the quantum bit sensor can be measured with an accuracy close to the Heisenberg limit, which can capture abnormal signals earlier than conventional sensors and help to achieve early warning of abnormal components. In addition, this method can be used to diagnose the dilution refrigerator when it is not shut down, and can be used to warn and avoid the risk of unplanned shutdown of superconducting quantum computers.

[0039] According to an embodiment of the present invention, the vibration signals of the multiple components include vibration signals of the pulse tube cold head, the compressor assembly, the pump assembly, the valve assembly and the pipeline, and the multiple components transmit their respective vibration signals to the cold plate in different vibration directions.

[0040] The chip of the quantum bit can be installed on the cold plate (temperature <30 mK) of the mixing chamber of the dilution refrigerator. Since the cold plate is the key transmission path of the mechanical vibration of the dilution refrigerator, the vibration of multiple components can be transmitted to the quantum bit through the cold plate. The broadband response of the quantum bit can capture the vibration information of multiple components at the same time.

[0041] Specifically, the pulse tube refrigerator generates cooling capacity through the reciprocating compression-expansion of helium. The vibration signal of the pulse tube cold head mainly causes mechanical vibration through the periodic motion of the internal piston, and the axial vibration can be directly transmitted through the rigid connection between the cold head and the cold plate. The compressor assembly mainly generates high-frequency mechanical vibration through the reciprocating motion of the piston or the rotation of the scroll plate, which is transmitted to the cold plate through the supporting structure. The pump assembly is mainly caused by fluid pressure pulsation and mechanical unbalanced vibration caused by the rotation of the impeller, which can be transmitted to the cold plate through the pipeline connection. The valve assembly mainly generates transient impact vibration through fast switching (such as solenoid valves or expansion valves), which is transmitted to the cold plate through the valve body and pipeline connection, which may be transient multi-directional vibration. The vibration signal of the pipeline mainly comes from fluid turbulence, which is transmitted to the cold plate through the pipeline support or flange connection, and may be vibration in multiple directions.

[0042] According to an embodiment of the present invention, the quantum bit sensor includes a quantum bit chip that integrates resonant cavities in three orthogonal directions of X-axis, Y-axis and Z-axis to collect vibration signals in multiple different directions from the pulse tube cold head, compressor assembly, pump assembly, valve assembly and pipeline.

[0043] According to an embodiment of the present invention, by deploying quantum bit chips in three orthogonal directions of X-axis, Y-axis and Z-axis, full degree of freedom coverage can be achieved, lateral, longitudinal and vertical vibrations can be captured, and accurate and comprehensive collection of vibration signals can be achieved.

[0044] In some embodiments, the qubit sensor can also use a planar waveguide superconducting qubit sensor. The installation method of the superconducting qubit sensor on the refrigerator determines its sensitivity to the direction of the spatial vibration signal. For example, the plane of the superconducting qubit sensor is set to be perpendicular to the cold plate and parallel to the working direction of the working fluid gas in the pulse tube cold head, perpendicular to the cold plate and perpendicular to the working direction of the working fluid gas in the pulse tube cold head, parallel to the cold plate, and sensitive to vibrations in the X-axis (horizontal), Y-axis (longitudinal), and Z-axis (vertical) directions respectively. In other embodiments, the superconducting qubit chip can also be installed at an angle, and the tilt angle can be optimized according to the actual spatial vibration mode distribution to obtain the best signal detection effect.

[0045] According to an embodiment of the present invention, before using sensors to collect vibration signals of multiple components of the dilution refrigerator, the method may further include: determining a collection frequency of the vibration signal according to respective reference frequencies of the multiple components; and collecting vibration signals of the multiple components of the dilution refrigerator according to the collection frequency.

[0046] The reference frequency represents the natural vibration frequency of the component under normal working conditions. The acquisition frequency represents the sampling rate used by the sensor when collecting vibration signals, that is, the number of vibration data points collected per second. Since the selection of the acquisition frequency can directly affect the resolution and accuracy of the vibration signal, the acquisition frequency should be high enough to ensure that all frequency components in the vibration signal can be accurately captured.

[0047] When using quantum bits as sensors to collect vibration signals, the sampling frequency can be determined based on the maximum reference frequency among multiple components.

[0048] Preferably, the acquisition frequency is not less than 20 times the reference frequency. For example, the reference operating frequency of the reciprocating work of the pulse tube cold head working fluid gas of a typical pulse tube refrigerator is 1.4 Hz, and the upper limit of the acquisition frequency of its vibration signal should be not less than 28 Hz. The present invention is not limited to this, and the multiple relationship between the acquisition frequency and the reference frequency can also be adjusted according to specific circumstances and needs.

[0049] According to the embodiment of the present invention, by determining the acquisition frequency according to the reference frequency, it can be ensured that the sensor can accurately capture the vibration signal of the component, thereby improving the accuracy and reliability of the signal. The acquisition frequency is not less than 20 times the reference frequency, which can ensure that all frequency components can be collected to improve the integrity of the information.

[0050] According to an embodiment of the present invention, a spectral analysis is performed on a vibration signal to determine the frequency distribution characteristics of each of the multiple components, including: performing Fourier transform or cepstrum analysis on the vibration signal to determine the initial frequency distribution characteristics of the vibration signal; obtaining reference frequency characteristics of each of the multiple components, wherein the reference frequency characteristics include a reference frequency of the target component and an amplitude corresponding to the reference frequency; and using the reference frequency characteristics of each of the multiple components to normalize the initial frequency distribution characteristics respectively to obtain the frequency distribution characteristics of each of the multiple components.

[0051] In some embodiments, performing spectrum analysis on the vibration signal of a preset time period to determine the initial frequency distribution characteristics of the vibration signal may include: performing discrete Fourier transform processing on the vibration signal to obtain the initial frequency distribution characteristics of the vibration signal. Alternatively, performing cepstrum processing on the vibration signal to obtain the initial frequency distribution characteristics of the vibration signal.

[0052] Specifically, when the vibration signal preprocessing is simple, the real-time requirements are high, or the characteristics of the vibration signal (such as resonance frequency, fault frequency, etc.) are obvious in the frequency domain and easy to identify and extract, the discrete Fourier transform can be used. The discrete Fourier transform can convert the vibration signal from the time domain to the frequency domain, so that the amplitude and phase information of different frequency components in the signal can be intuitively observed.

[0053] When it is necessary to analyze the periodic structure of a vibration signal, especially when the signal contains multiple harmonic components, or there is noise, interference or nonlinear distortion in the vibration signal, and these components are not easy to remove directly in the frequency domain, or when the original signal is a non-stationary signal and the spectrum diagram may contain a complex periodic structure that is difficult to identify directly, techniques such as cepstrum, filtering, Hilbert-Huang transform, and time-dependent Fourier transform can be used to analyze the vibration signal of a preset time period and extract frequency features that are helpful for diagnosis.

[0054] In some embodiments, the reference frequency and derived frequency combination characteristics of the component under normal working conditions can be obtained through theoretical calculation, experimental measurement or reference to relevant technical data. The reference frequency characteristics can also be determined by vibration signal measurement when the component is in normal operation. Since the reference frequency of each mechanical component is determined by its inherent physical parameters (such as the number of gear teeth, the number of bearing balls, and the rotational speed), the reference frequency and derived frequency combination of the component under normal working conditions is unique.

[0055] The reference frequency and the amplitude corresponding to the reference frequency can be used as normalization factors. The normalization factor is applied to each frequency and amplitude in the initial frequency distribution characteristics. After the initial frequency distribution characteristics are normalized, the amplitude and frequency of the reference frequency are standardized to 1 (or a fixed reference value), and other derived frequency components are scaled in the same proportion. This unifies the quantitative analysis scale of vibration signals of different components.

[0056] Since the reference frequency of each component under normal working conditions is unique, the initial frequency distribution characteristics are normalized using the reference frequency of the target component, so that the frequency distribution characteristics of each component occupy an independent position in its respective frequency domain. In this way, the frequency distribution characteristics of different components can be distinguished, and then the frequency distribution characteristics of the target component can be distinguished from the initial frequency distribution characteristics.

[0057] According to an embodiment of the present invention, by using the reference frequency of the target component to normalize the initial frequency distribution characteristics, the uniqueness of the reference frequency can be utilized to avoid confusion of spectra of different components, thereby improving the accuracy of fault diagnosis of the target component.

[0058] According to an embodiment of the present invention, initial frequency distribution characteristics are normalized using respective reference frequency characteristics of multiple components to obtain respective frequency distribution characteristics of the multiple components, including: using respective reference frequency characteristics of multiple components to normalize initial frequency distribution characteristics to obtain respective normalized frequency distribution characteristics of each component; determining respective frequency distribution characteristics of each component based on respective reference frequencies of each component and frequencies that are integer multiples of the reference frequencies in the normalized frequency distribution characteristics.

[0059] The initial frequency distribution characteristics are normalized using the respective reference frequencies of multiple components. Since the reference frequencies of different components are different, the normalized frequency distribution characteristics of each component occupy an independent position in the spectrum diagram, and the frequency distribution characteristics of each component can be distinguished.

[0060] Since local damage to mechanical parts will produce periodic shocks, they appear as harmonics of the reference frequency in the spectrum diagram. By using the frequency distribution characteristics composed of the reference frequency and the integer multiples of the reference frequency, the fault type of the target component can be accurately reflected.

[0061] Figure 2a A spectrum diagram obtained by performing spectrum analysis on a vibration signal according to an embodiment of the present invention is shown.

[0062] like Figure 2a As shown in the figure, the frequency distribution contained in the vibration signal and the quantum bit flux noise spectral density (i.e., amplitude) of each frequency can be read out through the spectrum diagram, thereby obtaining the initial frequency distribution characteristics of the vibration signal. For example, there are multiple characteristic peaks in the range of 0-1000Hz and one characteristic peak at 2000Hz.

[0063] Figure 2b The diagram shows a frequency spectrum obtained after normalizing the initial frequency distribution features according to an embodiment of the present invention.

[0064] like Figure 2b As shown, the reference frequency f of the target component is used to normalize multiple frequencies in the initial frequency distribution characteristics, and the amplitudes corresponding to the reference frequency are used to normalize the amplitudes of the multiple frequencies to obtain a normalized spectrum diagram, and the frequency distribution characteristics of the target component can be obtained based on the spectrum diagram.

[0065] Specifically, according to Figure 2b The frequencies and corresponding amplitudes of integer multiples of the reference frequency of the target component can be read out. For example, the amplitude of the reference frequency f is 1, the amplitude of 2f is 0.87, the amplitude of 3f is 0.58, the amplitude of 4f is 0.79, the amplitude of 5f is 0.35, the amplitude of 6f is 0.53, the amplitude of 7f is 0.35, the amplitude of 8f is 0.38, the amplitude of 9f is 0.58, the amplitude of 10f is 0.41, and so on. Thus, the frequency distribution characteristics of the vibration signal can be obtained.

[0066] According to an embodiment of the present invention, based on the frequency distribution characteristics of each of the multiple components, the target component of abnormal vibration is determined, including: obtaining the operating frequency characteristics of the multiple components in a normal state, the operating frequency characteristics are obtained by respectively collecting the vibration signals of the multiple components in a normal state using a quantum bit sensor; based on the frequency distribution characteristics of each of the multiple components and the operating frequency characteristics of the multiple components, the target component of abnormal vibration is determined.

[0067] The quantum bit sensor can be used to collect the working frequency characteristics of multiple components in a normal state, and a working frequency characteristic library of multiple components can be constructed based on the working frequency characteristics of the multiple components. After determining the frequency characteristics of the multiple components, the working frequency characteristics of the multiple components in the working frequency characteristic library are called and compared with the frequency distribution characteristics of the multiple components. When the working frequency characteristics and frequency distribution characteristics of a certain component are inconsistent, the component is determined to be a target component with abnormal vibration.

[0068] According to an embodiment of the present invention, based on the frequency distribution characteristics of the target component and the fault frequency characteristic table of the target component, determining the fault diagnosis result of the dilution refrigerator includes: calculating the average value of the amplitude in the frequency distribution characteristics; based on the average value, screening the frequency distribution characteristics of the target component to obtain the target frequency characteristics of the target component; and determining the fault diagnosis result of the dilution refrigerator based on the target frequency characteristics of the target component and the fault frequency characteristic table of the target component.

[0069] In the embodiment of the present invention, since the signal contains multiple frequency components, only a few of which play a dominant role in the characteristics or behaviors of the vibration signal. By calculating the average value and screening based on the average value, the dominant frequency component can be more easily identified and used as the target frequency feature.

[0070] In some embodiments, the screening criteria can be set according to the average value, for example, the frequency whose amplitude is several times higher than the average value can be selected, which can be 3 times, 5 times or 10 times higher than the average value, etc. The present invention is not limited to this, and the frequency whose amplitude is within a certain ratio (such as the average value plus or minus a certain standard deviation) can also be selected. The screening criteria may not be fixed. It can be dynamically adjusted according to specific needs or data characteristics, for example, according to the distribution of data, the existence of outliers or specific application scenarios.

[0071] According to the embodiment of the present invention, based on the average value of the amplitudes of the multiple frequencies, the dominant frequency component can be screened out from the multiple frequencies, thereby improving the accuracy and reliability of fault diagnosis.

[0072] According to an embodiment of the present invention, based on the target frequency characteristics of the target component and the fault frequency characteristic table of the target component, the fault diagnosis result of the dilution refrigerator is determined, including: sorting the target frequency characteristics and the fault frequency characteristic table to obtain the target characteristic vector of the target component and the reference characteristic vectors of each of the multiple fault types; and determining the fault diagnosis result of the target component according to the similarity between the target characteristic vector and the reference characteristic vectors of each of the multiple fault types.

[0073] Based on the difference of components, different fault frequency characteristic tables can be formulated to adapt to different equipment and different working conditions. Table 1 and Table 2 schematically show the fault frequency characteristic tables of two components respectively.

[0074] Table 1:

[0075]

[0076] Table 2:

[0077]

[0078] The target frequency feature and fault frequency feature table can be sorted by sorting multiple target frequencies according to the magnitude of the frequencies to obtain a two-dimensional matrix composed of multiple target frequencies and their respective amplitudes, thereby obtaining a target feature vector.

[0079] Similarly, in the same manner as the target frequency features, the reference frequency features are also sorted according to the magnitude of the frequencies to obtain reference feature vectors for each of the multiple fault types.

[0080] The fault diagnosis result of the target component is determined according to the similarity between the target feature vector and the reference feature vectors of the multiple fault types, such as cosine similarity, Euclidean distance, correlation coefficient, etc.

[0081] In some embodiments, a threshold of similarity may be preset, and if the similarity is higher than the threshold, the fault corresponding to the diagnosis table is output in a preset format.

[0082] According to an embodiment of the present invention, the fault diagnosis result of the target component is determined based on the similarity between the target feature vector and the reference feature vectors of multiple fault types, which can accurately and efficiently detect potential faults at an early stage, thereby avoiding equipment operation interruption and improving the reliability and stability of the equipment.

[0083] Figure 3 A structural block diagram of a dilution refrigerator according to an embodiment of the present invention is shown.

[0084] The present invention also provides a dilution refrigerator fault diagnosis system, comprising a dilution refrigerator; a quantum bit sensor, disposed on a cold plate of the dilution refrigerator; and an electronic device, for receiving a vibration signal collected by the quantum bit sensor and executing the above-mentioned fault diagnosis method.

[0085] In some embodiments, Figure 3 As shown, the dilution refrigerator includes a core unit 310, a pulse tube cold head 320 and a gas control system 330. The gas control system 330 includes multiple components such as a mechanical pump, a molecular pump, a compressor and a pneumatic valve.

[0086] The core unit 310 of the dilution refrigerator includes a cold plate 311 of the dilution refrigerator and a qubit sensor 312. The qubit sensor 312 is arranged on the cold plate 311 of the mixing chamber of the dilution refrigerator. The qubit sensor 312 can collect vibration signals of multiple components such as the pulse tube cold head 320, mechanical pump, molecular pump, compressor, pneumatic valve and pipeline. The vibration signals are transmitted to the electronic device, and the vibration signals of multiple components are processed by the electronic device, and fault diagnosis is performed.

[0087] In some embodiments, the electronic device may include one or more processors and a memory. The memory is used to store one or more computer programs, and the one or more processors execute the one or more computer programs to implement the above-mentioned fault diagnosis method.

[0088] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination. The scope of the present invention is defined by the attached claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A dilution refrigerator fault diagnosis method, characterized in that: The method comprises: Using a quantum bit sensor to collect vibration signals of multiple components of a dilution refrigerator, wherein the quantum bit sensor is disposed on a cold plate of the dilution refrigerator, and multiple components are connected to the cold plate respectively; Performing spectrum analysis on the vibration signal to determine frequency distribution characteristics of each of the plurality of components; determining a target component of abnormal vibration based on the frequency distribution characteristics of each of the plurality of components; The fault diagnosis result of the dilution refrigerator is determined based on the frequency distribution characteristics of the target component and a fault frequency characteristic table preset for the target component, wherein the fault frequency characteristic table includes multiple fault types of the target component and reference frequency characteristics corresponding to each of the multiple fault types.

2. The method according to claim 1, characterized in that The vibration signals of the plurality of components include vibration signals of a pulse tube cold head, a compressor assembly, a pump assembly, a valve assembly and a pipeline, and the plurality of components transmit their respective vibration signals to the cold plate in different vibration directions.

3. The method according to claim 2, characterized in that The quantum bit sensor includes a quantum bit chip that integrates resonant cavities in three orthogonal directions of X-axis, Y-axis and Z-axis to collect vibration signals in multiple different directions from the pulse tube cold head, compressor assembly, pump assembly, valve assembly and pipeline.

4. The method according to claim 1, characterized in that: The performing spectrum analysis on the vibration signal to determine the frequency distribution characteristics of each of the plurality of components comprises: Performing Fourier transform or cepstrum analysis on the vibration signal to determine initial frequency distribution characteristics of the vibration signal; Acquire reference frequency characteristics of each of the plurality of components, wherein the reference frequency characteristics include a reference frequency and an amplitude corresponding to the reference frequency; The initial frequency distribution characteristics are respectively normalized using the respective reference frequency characteristics of the plurality of components to obtain the respective frequency distribution characteristics of the plurality of components.

5. The method according to claim 4, characterized in that The method of using the respective reference frequency characteristics of the plurality of components to respectively normalize the initial frequency distribution characteristics to obtain the respective frequency distribution characteristics of the plurality of components includes: Using the respective reference frequency characteristics of the plurality of components, respectively normalizing the initial frequency distribution characteristics to obtain respective normalized frequency distribution characteristics of the plurality of components; Based on the reference frequencies of the plurality of components and the frequencies of integer multiples of the reference frequencies in the normalized frequency distribution characteristics, the frequency distribution characteristics of the plurality of components are determined.

6. The method according to claim 1, characterized in that The step of determining a target component with abnormal vibration based on the frequency distribution characteristics of each of the plurality of components comprises: Acquiring operating frequency characteristics of multiple components in a normal state, wherein the operating frequency characteristics are obtained by respectively collecting vibration signals of multiple components in a normal state using the quantum bit sensor; Based on the frequency distribution characteristics of each of the plurality of components and the operating frequency characteristics of each of the plurality of components, a target component of abnormal vibration is determined.

7. The method according to claim 1, characterized in that The method of determining the fault diagnosis result of the dilution refrigerator based on the frequency distribution characteristics of the target component and a fault frequency characteristic table preset for the target component includes: Calculating the average value of the amplitude in the frequency distribution feature; Based on the average value, the frequency distribution characteristics of the target component are screened to obtain the target frequency characteristics of the target component; and A fault diagnosis result of the dilution refrigerator is determined based on a target frequency feature of the target component and a fault frequency feature table for the target component.

8. The method according to claim 7, characterized in that The method of determining the fault diagnosis result of the dilution refrigerator based on the target frequency characteristic of the target component and the fault frequency characteristic table for the target component includes: Arrange the target frequency characteristics and the fault frequency characteristics table to obtain the target characteristic vector of the target component and the reference characteristic vectors of each of the multiple fault types; The fault diagnosis result of the target component is determined according to the similarities between the target feature vector and the reference feature vectors of multiple fault types.

9. The method according to claim 1, characterized in that: The method further comprises: Determine the collection frequency of the vibration signal according to the respective reference frequencies of the multiple components; According to the acquisition frequency, vibration signals of multiple components of the dilution refrigerator are acquired.

10. A fault diagnosis system for a dilution refrigerator, characterized in that: include: Dilution refrigerator; A quantum bit sensor is arranged on a cold plate of the dilution refrigerator; An electronic device for receiving the vibration signal collected by the quantum bit sensor and executing the method according to any one of claims 1 to 9.

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