Gas detection method and apparatus based on effective viscosity inversion of core path

Abstract

The application is suitable for the field of measurement test technology, and provides a gas detection method and equipment based on effective viscosity inversion of shaft center locus, the method comprising: controlling to maintain constant rotor speed and bearing radial load during operation of a rotor test bench; collecting radial displacement data of shaft neck in horizontal and vertical directions in real time when it is determined that a stable lubrication state is reached; synthesizing a steady-state shaft center locus of the rotor and calculating rotor eccentricity characteristic parameters; constructing a viscosity reverse mapping model suitable for liquid metal turbulent flow conditions; combining rotor eccentricity characteristic parameters, rotor speed, bearing radial load and bearing groove structure parameters; and using a dichotomy iteration method to obtain effective viscosity of the liquid metal inside the bearing; collecting real-time temperature of the liquid metal inside the bearing; calling ideal viscosity of pure liquid metal without bubbles at the temperature; and obtaining a gas detection result based on effective viscosity and ideal viscosity, so as to realize precise indirect detection of trace gas of the liquid metal bearing.

Description

Technical Field

[0001] This application belongs to the field of measurement and testing technology, and in particular relates to a gas detection method and equipment based on effective viscosity inversion from the axis trajectory. Background Technology

[0002] Computed Tomography (CT) equipment is a core medical device for clinical radiological diagnosis. It relies on a CT tube to emit high-energy X-rays that penetrate human tissue, and the signals are reconstructed to generate tomographic images, enabling non-invasive and accurate screening and diagnosis of lesions in internal organs, bones, and soft tissues. The CT tube, as the core heat-generating rotating component of the entire machine, typically uses a gallium-based herringbone groove liquid metal radial sliding bearing for its rotor support. This bearing uses a room-temperature liquid gallium-based alloy as the lubricating medium, suitable for high-speed, sealed operation at tens of thousands of revolutions per minute. However, this type of bearing is entirely sealed. If air or water vapor seeps in during the sealing process, or if micro-bubbles precipitate from the liquid metal under high-temperature conditions, it will directly change the equivalent viscosity of the lubricating medium, disrupt the uniformity of the dynamic pressure oil, and cause problems such as increased rotor vibration, localized overheating of the tube, unstable X-ray output, and blurred imaging artifacts. These issues severely reduce the accuracy of image diagnosis and may even directly cause premature tube failure and equipment downtime, affecting clinical diagnosis and treatment. Therefore, real-time and accurate identification of whether trace amounts of gas are mixed inside sealed liquid metal, and quantitative acquisition of the gas volume fraction, are core technical requirements for ensuring stable output of CT bulbs and guaranteeing the quality of image diagnosis.

[0003] Currently, methods for detecting trace gases in liquid metal bearings are mainly divided into two categories: invasive sensing detection and conventional qualitative monitoring of lubrication conditions. Invasive methods require openings in the bearing housing and installing specialized gas and pressure detection elements. Although they can directly measure the gas content, they damage the original sealing structure of the bearing, easily causing liquid metal leakage and media oxidation, making them completely unsuitable for CT tube integrated sealed liquid metal bearings. On the other hand, the bearing viscosity calculation models used in conventional qualitative monitoring of lubrication conditions are all based on the laminar flow conditions of lubricating oil, which are not adapted to the high-speed turbulent flow characteristics of gallium-based liquid metals, nor do they take into account the specific structural parameters of the bearing's internal structure, such as herringbone grooves, making it difficult to achieve quantitative detection of trace gases.

[0004] Therefore, how to achieve accurate indirect detection of trace gases in liquid metal bearings has become an urgent problem to be solved. Summary of the Invention

[0005] To address at least one of the aforementioned technical problems and achieve accurate detection of trace gases in liquid metal bearings, especially gallium-based liquid metal bearings with herringbone grooves in CT tubes, this application proposes a gas detection method and device based on effective viscosity derived from shaft center trajectory inversion.

[0006] In a first aspect, this application provides a gas detection method based on effective viscosity derived from shaft trajectory inversion, implemented on a rotor test bench equipped with a grooved bearing in liquid metal, the method comprising: S1, during the operation of the rotor test bench, the rotor speed and bearing radial load are controlled and maintained at a constant speed. When it is determined that a stable lubrication state has been reached, the radial displacement data of the journal in the horizontal and vertical directions are collected in real time to synthesize the steady-state shaft center trajectory of the rotor. S2, based on the steady-state shaft center trajectory, calculate the rotor eccentricity characteristic parameters, which include at least one of eccentricity, eccentricity ratio, and minimum lubricating film thickness; S3. Construct a viscosity inverse mapping model adapted to the turbulent flow condition of liquid metal. Combine the rotor eccentricity characteristic parameters, the rotor speed, the bearing radial load and the bearing groove structure parameters, and use the bisection iteration method to inversely obtain the effective viscosity of the liquid metal inside the bearing. S4. Collect the real-time temperature of the liquid metal inside the bearing, and retrieve the ideal viscosity of the bubble-free pure liquid metal at that temperature; based on the effective viscosity and the ideal viscosity, obtain the gas detection result.

[0007] In one possible implementation, step S3, the process of constructing the viscosity inverse mapping model, includes: Establish a dimensionless turbulent modified Reynolds equation adapted to the turbulent flow conditions of liquid metal; The dimensionless turbulent modified Reynolds equation is discretized using the finite difference method to divide the bearing into circumferential and axial differential meshes. Based on the bearing groove structure parameters, the groove structure boundary conditions are set. The global dimensionless oil film thickness distribution is determined by the rotor eccentricity characteristic parameters. Combined with the journal surface linear velocity obtained from the rotor speed, the global dimensionless oil film pressure under different viscosities is solved and integrated to obtain the theoretical bearing capacity. Calibration tests were conducted under multiple working conditions, including varying rotor speed, bearing radial load, liquid metal temperature, and bubble content. The measured rotor eccentricity characteristic parameters and corresponding actual load-bearing capacity were collected for each working condition. Based on the binary iterative algorithm, the bearing radial load is used as the convergence constraint to correlate the theoretical bearing capacity with the actual bearing capacity, and the viscosity inverse mapping model is fitted and established.

[0008] In one possible implementation, step S3, which involves using a bisection iterative method to invert the effective viscosity, includes: Set upper and lower limits for viscosity iteration and calculate the midpoint viscosity; Based on the dimensionless turbulent modified Reynolds equation, and combined with the midpoint viscosity, the rotor eccentricity characteristic parameters, the rotor speed, and the bearing groove structure parameters, the dimensionless oil film pressure over the entire domain is solved by the finite difference method, and the current theoretical bearing capacity is obtained by integration after dimensional reduction. Using the radial load of the bearing as the convergence target value, the relative error between the current theoretical bearing capacity and the radial load of the bearing is calculated. If the relative error is less than the preset convergence tolerance, the current midpoint viscosity is taken as the effective viscosity of the liquid metal. If the relative error is not less than the preset convergence tolerance, when the current theoretical bearing capacity is less than the radial load of the bearing, the lower limit of viscosity iteration is updated to the midpoint viscosity, and when the current theoretical bearing capacity is greater than the radial load of the bearing, the upper limit of viscosity iteration is updated to the midpoint viscosity. This process is repeated until the convergence condition is met.

[0009] In one possible implementation, the dimensionless turbulent modified Reynolds equation is: ; in, , These are the circumferential and axial liquid metal turbulence correction coefficients, respectively. Circumferential dimensionless coordinates; , where the coordinates are dimensionless along the axis; The dimensionless oil film thickness is determined by the spatial distribution of rotor eccentricity characteristic parameters; The pressure is a dimensionless oil film pressure. Where the bearing radius is; This refers to the bearing length. Dimensionless oil film pressure The transformation formula is: ; in, This refers to the bearing radius clearance. The linear velocity of the shaft diameter surface is calculated from the rotor speed. Midpoint viscosity; This represents the actual oil film pressure.

[0010] In one possible implementation, the rules for determining a stable lubrication state in step S1 include: If all four conditions are met simultaneously, the rotor-bearing system is deemed to have reached a stable lubrication state: the rotor speed fluctuation range does not exceed ±2%, the bearing radial load fluctuation range does not exceed ±2%, the temperature fluctuation of the liquid metal inside the bearing does not exceed ±1℃, and the overlap of the shaft center trajectory is not less than 90% for at least three consecutive complete rotation cycles.

[0011] In one possible implementation, prior to step S2, the method further includes: The steady-state shaft center trajectory is purified by bandpass filtering to remove zero-point drift, test bench vibration, and low-frequency interference caused by slow thermal expansion below 0.1 to 0.2 times the rotor frequency; at the same time, sensor electrical noise and high-frequency electromagnetic interference from the motor above 3 to 5 times the rotor frequency are removed, retaining only the effective trajectory component corresponding to the deformation of the liquid oil film.

[0012] In one possible implementation, step S4 includes: The real-time temperature of the liquid metal inside the bearing is collected, the ideal viscosity of the bubble-free pure liquid metal at the same temperature is obtained, and the relative viscosity deviation between the effective viscosity and the ideal viscosity is calculated. When the relative viscosity deviation is greater than or equal to a preset deviation threshold, it is determined that trace amounts of gas have been mixed into the liquid metal. The viscosity relative deviation and trace gas volume fraction correspondence obtained by pre-fitting through multi-temperature and multi-bubble content calibration tests are used to match and obtain the current trace gas volume fraction in the liquid metal.

[0013] In one possible implementation, the rotor test bench includes a pneumatic drive system, a rotor-bearing assembly, an electromagnetic loading device, and a displacement, temperature, and speed measurement system. The pneumatic drive system includes a base, an air inlet, and a turbine. The turbine is coaxially and fixedly connected to the rotor shaft, and is used to achieve constant rotor speed locking through closed-loop regulation of the air inlet pressure. The rotor-bearing device includes a pair of liquid metal grooved bearings and a rotor shaft. The bearing cavity is sealed and filled with liquid metal to simulate the actual bearing lubrication operation conditions. The electromagnetic loading device includes an electromagnetic loader and a tension sensor. The electromagnetic loader is used to apply a controllable radial load to the rotor shaft, and the tension sensor is used to collect the radial load in real time and form a closed-loop feedback to achieve constant locking of the bearing radial load. The displacement-temperature-speed measurement system includes orthogonally arranged X-axis eddy current displacement sensors, Y-axis eddy current displacement sensors, thermocouples, reflective pads, and photoelectric speed sensors. The two sets of orthogonally arranged eddy current displacement sensors are positioned opposite the rotor journal and are used to collect radial displacement data in the horizontal and vertical directions of the journal to synthesize the shaft center trajectory. The temperature measuring end of the thermocouple extends into the bearing sealing cavity to collect the real-time temperature of the liquid metal. The photoelectric speed sensor obtains the rotor speed in real time by recognizing the pulse signal of the rotor reflective pad.

[0014] In one possible implementation, the liquid metal is a gallium indium tin alloy gallium-based liquid metal; the liquid metal grooved bearing is a CT tube-specific herringbone groove radial dynamic pressure sliding bearing, and the bearing groove structure parameters include at least groove depth, groove width, number of circumferential grooves, bearing radius, bearing length, bearing radius clearance, and bearing width, all of which are used as the groove structure boundary conditions of the viscosity inverse mapping model.

[0015] Secondly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in the first aspect or any of the implementations thereof.

[0016] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method as described in the first aspect or any of the implementations thereof.

[0017] Fourthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to execute the method described in the first aspect or any of its implementations.

[0018] Compared with existing technologies, the advantages of this application are as follows: It relies solely on the collected rotor shaft trajectory data for detection, eliminating the need for additional trace gas sensing elements placed inside and outside the bearing. This avoids damaging the bearing's sealing structure by installing sensors through openings, making it particularly suitable for the use of CT tube integrated sealed liquid metal bearings. Specifically, based on rotor eccentricity characteristic parameters, rotor speed, bearing radial load, and bearing groove structure parameters, a viscosity inverse mapping model is employed. Combined with modeling logic adapted to liquid metal turbulent flow conditions and a bisection iterative algorithm, the effective viscosity of the medium is inverted. Compared to traditional calculation methods relying on a single parameter and based on laminar flow assumptions, this significantly reduces viscosity calculation errors. By matching the real-time medium temperature to the ideal viscosity of bubble-free pure liquid metal, the viscosity difference between the two is used to complete trace gas detection. No additional excitation or invasive measurement operations are required, resulting in a simple detection process with strong adaptability to operating conditions, significantly improving the detection accuracy and practicality of trace gases in sealed liquid metal bearings.

[0019] It is understood that the electronic devices, computer-readable storage media, and computer program products provided in the embodiments of this application have the same beneficial effects as the gas detection method based on the effective viscosity derived from the axis trajectory described above, and will not be repeated here. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in this application, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A schematic flowchart of a gas detection method based on effective viscosity derived from axis trajectory inversion, provided in an embodiment of this application; Figure 2 A schematic diagram of a herringbone groove radial hydrodynamic sliding bearing for CT X-ray tubes provided in one embodiment of this application; Figure 3 This is a schematic diagram of the structure of a rotor test bench provided in one embodiment of this application; In the figure: sensor bracket 10, base 20, air inlet 30, turbine 40, liquid metal grooved bearing 50, Y-axis eddy current displacement sensor 60, tension sensor 70, electromagnetic loader 80, rotor 90, reflective sticker 100, photoelectric speed sensor 110, X-axis eddy current displacement sensor 120. Detailed Implementation

[0022] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0023] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0024] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0026] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0028] For ease of understanding, the technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0029] Figure 1 This is a schematic flowchart illustrating a gas detection method based on effective viscosity derived from axis trajectory inversion, as provided in an embodiment of this application. Figure 1 As shown, for ease of explanation, only the parts relevant to this embodiment are shown. The method provided in this embodiment is implemented based on a rotor test bench equipped with a liquid metal grooved bearing, and includes the following steps: S1, during the operation of the rotor test bench, controls and maintains a constant rotor speed and bearing radial load. When it is determined that a stable lubrication state has been reached, the radial displacement data of the journal in the horizontal and vertical directions are collected in real time to synthesize the steady-state shaft center trajectory of the rotor.

[0030] Optionally, after the rotor test bench is started and running, the rotor speed is controlled by the closed-loop regulation of the air intake pressure through the pneumatic drive system. At the same time, the electromagnetic loading device is controlled to output a stable radial load, and four types of operating parameters, namely rotor speed, bearing radial load, liquid metal temperature, and rotor radial displacement, are continuously and synchronously monitored. After the system meets the judgment rules for stable lubrication state and the rotor-bearing system is confirmed to have entered a stable lubrication state, the displacement signal acquisition is started to acquire the radial displacement data of the journal in the horizontal and vertical directions in real time and synthesize the steady-state shaft center trajectory.

[0031] In one possible implementation, the rules for determining a stable lubrication state include: If all four conditions are met simultaneously, the rotor-bearing system is deemed to have reached a stable lubrication state and enters the data acquisition phase: the rotor speed fluctuation range does not exceed ±2%, the bearing radial load fluctuation range does not exceed ±2%, the temperature fluctuation range of the liquid metal inside the bearing does not exceed ±1℃, and the overlap of the shaft center trajectory corresponding to at least three consecutive complete rotor rotation cycles is not less than 90%.

[0032] For example, two sets of high-precision eddy current displacement sensors are orthogonally arranged on both sides of the journal. Only the original radial vibration displacement signal of the rotor is collected. No holes are opened inside or outside the bearing cavity or special detection elements for trace gas are added. Based on the collected radial displacement data in the horizontal and vertical directions, a complete steady-state shaft center trajectory is calculated and synthesized, thus avoiding damage to the sealing structure of the liquid metal bearing from the source.

[0033] S2. Based on the steady-state shaft center trajectory, calculate the rotor eccentricity characteristic parameters, which include at least one of eccentricity, eccentricity ratio, and minimum lubricating film thickness.

[0034] In one possible implementation, prior to step S2, the method further includes: The steady-state shaft center trajectory is purified by bandpass filtering to remove zero drift, test bench vibration, and low-frequency interference caused by slow thermal expansion below 0.1 to 0.2 times the rotor frequency; at the same time, sensor electrical noise and high-frequency electromagnetic interference from the motor above 3 to 5 times the rotor frequency are also removed, leaving only the effective trajectory component corresponding to the deformation of the liquid oil film.

[0035] As an example, before performing characteristic parameter calculations, the synthesized original steady-state shaft center trajectory is first subjected to segmented bandpass filtering purification: the low-frequency cutoff interval is set to 0.1-0.2 times the rotor real-time rotation frequency to filter out zero-point temperature drift, low-frequency vibration of the test bench foundation, and slow-varying offset interference caused by bearing thermal expansion; the high-frequency cutoff interval is set to 3-5 times the rotor real-time rotation frequency to filter out high-frequency interference such as inherent electrical noise of the eddy current sensor and electromagnetic noise of the drive motor. After filtering, only the effective trajectory components generated by the deformation of the liquid metal lubricating film and the actual effect of rotor eccentricity are retained, eliminating the influence of irrelevant interference on the error of subsequent parameter calculations.

[0036] For example, take the horizontal displacement x(t) and vertical displacement y(t) of the journal at any sampling time after filtering, and substitute them into the instantaneous eccentricity calculation formula: ; Traverse all sampling points within the steady-state sampling period and solve for the instantaneous eccentricity one by one. Then, the arithmetic mean of all instantaneous eccentricities is calculated to obtain the rotor average eccentricity under this constant operating condition; combined with the bearing radial clearance, the steady-state eccentricity and the minimum global lubricating film thickness are further calculated, and at least one of them is selected as the input feature parameter of the subsequent viscosity inverse mapping model.

[0037] S3. Construct a viscosity inverse mapping model adapted to the turbulent flow conditions of liquid metal. Combine the rotor eccentricity characteristic parameters, rotor speed, bearing radial load and bearing groove structure parameters, and use the bisection iteration method to inversely obtain the effective viscosity of the liquid metal inside the bearing.

[0038] Optionally, in this embodiment, the adapted liquid metal is a gallium indium tin alloy gallium-based liquid metal; the grooved bearing of the liquid metal is a herringbone groove radial dynamic pressure sliding bearing specifically for CT X-ray tubes. The bearing groove structure parameters include at least groove depth, groove width, number of circumferential grooves, bearing radius, bearing length, bearing radius clearance, and bearing width, all of which are used as the groove structure boundary conditions in the viscosity inverse mapping model and participate in the calculation of oil film pressure and bearing capacity throughout the process. An example of a herringbone groove radial dynamic pressure sliding bearing specifically for CT X-ray tubes is as follows: Figure 2 As shown.

[0039] In one possible implementation, step S3, the construction process of the viscosity inverse mapping model, includes: S31. Establish a dimensionless turbulent modified Reynolds equation adapted to the turbulent flow conditions of liquid metal.

[0040] Specifically, unlike the traditional Reynolds equation for laminar flow of lubricating oil, the dimensionless turbulent modified Reynolds equation provided in this application adds circumferential and axial turbulent correction coefficients to match the high-velocity flow characteristics of liquid metal.

[0041] S32 uses the finite difference method to discretize the dimensionless turbulent modified Reynolds equation into a mesh, dividing the bearing into circumferential and axial differential meshes. Based on the bearing groove structure parameters, the groove structure boundary conditions are set. The dimensionless oil film thickness distribution in the whole domain is determined by the rotor eccentricity characteristic parameters. Combined with the journal surface linear velocity obtained by converting the rotor speed, the dimensionless oil film pressure in the whole domain under different viscosities is solved and integrated to obtain the theoretical bearing capacity.

[0042] Optionally, the dimensionless turbulent modified Reynolds equation is numerically discretized using the finite difference method. A two-dimensional difference grid is uniformly divided along the bearing circumferential φ and axial λ. The solution domain is set by combining the bearing groove structure parameters and the pressure boundary conditions at both ends of the bearing. The dimensionless oil film pressure field of the whole domain is numerically solved by traversing different viscosities. The corresponding theoretical radial bearing capacity is obtained by integrating along the circumferential and axial directions.

[0043] As an example, the rotor eccentricity characteristic parameters can be selected from any one of eccentricity, eccentricity ratio, and minimum lubricating film thickness. The eccentricity ratio can be calculated first, and the dimensionless oil film thickness can be solved by combining the bearing circumferential spatial angle, so as to completely determine the spatial distribution of the oil film in the whole domain.

[0044] For example, given the bearing radius clearance C and circumferential angle θ (spatial position), when selecting the eccentricity e, first calculate the eccentricity ε = e / C, then substitute it into the distribution formula: H = 1 - εcosθ, to obtain the dimensionless oil film thickness H at all positions in the entire domain; when selecting the eccentricity ε, no conversion is needed, directly use ε and the spatial angle θ, substitute them into the above distribution formula to calculate the dimensionless oil film thickness at any position, obtaining the spatial distribution of the oil film in one step; when selecting the minimum dimensionless oil film thickness H... min When the minimum thickness occurs at θ=0, H satisfies min =1-ε, first solve for the eccentricity ε=1-H min Substituting back into the above distribution formula, we obtain the spatial distribution of the oil film in the entire circumference.

[0045] S33 was calibrated by changing multiple working conditions, including rotor speed, bearing radial load, liquid metal temperature, and bubble content. The measured rotor eccentricity characteristic parameters and corresponding actual load-bearing capacity were collected for each working condition.

[0046] Optionally, multivariable calibration tests can be carried out using a rotor test bench. Multiple working conditions, such as rotor speed, bearing radial load, liquid metal temperature, and internal bubble content, can be adjusted in a gradient manner. Measured rotor eccentricity characteristic parameters and corresponding real radial bearing capacity data under each steady-state working condition can be collected simultaneously to form a calibration sample database.

[0047] S34, based on the bisection iterative algorithm, uses the radial load of the bearing as a convergence constraint, correlates the theoretical bearing capacity with the actual bearing capacity, and fits to establish a viscosity inverse mapping model.

[0048] Optionally, a binary iterative algorithm can be used to solve the problem, and the theoretical bearing capacity obtained from the simulation can be matched with the actual bearing capacity obtained from the experiment to obtain a viscosity inverse mapping model that corresponds one-to-one with the input (including rotor eccentricity characteristic parameters, rotor speed, bearing radial load, and bearing groove structure parameters) and the output (effective viscosity of liquid metal).

[0049] In one possible implementation, step S3, which involves retrieving the effective viscosity of the liquid metal using a bisection iterative method based on the established viscosity inverse mapping model, includes: S35 sets the upper and lower limits for viscosity iteration and calculates the midpoint viscosity.

[0050] Specifically, the upper and lower boundaries of the liquid metal viscosity iteration are pre-defined, and the midpoint viscosity of the current iteration is calculated.

[0051] As an example, the formula for calculating midpoint viscosity is: ; in, This is the lower limit for viscosity iteration. This represents the upper limit of viscosity iteration. This is the midpoint viscosity.

[0052] S36, based on the dimensionless turbulent modified Reynolds equation, combined with midpoint viscosity, rotor eccentricity characteristic parameters, rotor speed, and bearing groove structure parameters, solves the dimensionless oil film pressure over the entire domain using the finite difference method, and obtains the current theoretical bearing capacity after dimensional reduction and integration.

[0053] Optionally, the dimensionless turbulent modified Reynolds equation constructed in this application is the core governing equation for solving the pressure field of liquid metal lubrication. The differential operator expression of the equation itself is mainly used to describe the rheological coupling relationship between oil film pressure and oil film thickness, and does not directly list all working conditions, geometric and iterative parameters. In this embodiment, various input parameters and the viscosity at the midpoint of the iteration are all represented in the form of initial field distribution, dimensionless conversion quantity, geometric boundary conditions, iterative convergence constraints, and dimensional restoration parameters, and participate together in the global numerical solution of the equation and the viscosity inverse mapping modeling. The specific correlation and iterative calculation logic are as follows: The rotor eccentricity characteristic parameter is used to calculate and determine the spatial distribution law of the dimensionless oil film thickness H in the entire bearing domain. It is the most important initial field input condition in the solution domain of the dimensionless turbulent modified Reynolds equation, and directly determines the oil film thickness value at each grid position. The rotor speed can be converted into the journal surface linear velocity U, which participates in the normalization conversion of the dimensionless oil film pressure and determines the velocity boundary magnitude of the oil film dynamic pressure generation. The bearing groove structure parameter is used for finite difference mesh generation and boundary condition setting of slotted and smooth regions, limiting the geometric boundary range of the numerical solution of the equation. The bearing radial load is not used as a differential term parameter of the equation, but as a convergence judgment target constraint of the theoretical bearing capacity in the bisection iteration process.

[0054] The midpoint viscosity during the iteration process is the core variable to be solved in each iteration. It does not participate in the field distribution solution of the dimensionless Reynolds equation, but it is a key input parameter for the dimensional reduction of oil film pressure and the correction of the theoretical bearing capacity amplitude. After obtaining the dimensionless oil film pressure of the whole domain through finite difference solution, the midpoint viscosity of the current iteration needs to be substituted into the inverse transformation formula of the dimensionless oil film pressure to complete the reduction and conversion of dimensionless pressure to actual physical pressure. The viscosity value directly determines the overall amplitude of oil film pressure, and thus determines the magnitude of the theoretical bearing capacity obtained by the final integral. It is the core adjustment parameter for correcting errors in the binary iteration and approximating the true effective viscosity.

[0055] The preferred dimensionless turbulent modified Reynolds equation is: ; in, , These are the circumferential and axial liquid metal turbulence correction coefficients, respectively. Circumferential dimensionless coordinates; , where the coordinates are dimensionless along the axis; The dimensionless oil film thickness is determined by the spatial distribution of rotor eccentricity characteristic parameters; The pressure is a dimensionless oil film pressure. Where the bearing radius is; For bearing length

[0056] Dimensionless oil film pressure The transformation formula is: ; in, This refers to the bearing radius clearance. The linear velocity of the shaft diameter surface is calculated from the rotor speed. Midpoint viscosity; This represents the actual oil film pressure.

[0057] S37. Using the radial load of the bearing as the convergence target value, calculate the relative error between the current theoretical bearing capacity and the radial load of the bearing. If the relative error is less than the preset convergence tolerance, then the current midpoint viscosity is taken as the effective viscosity of the liquid metal. If the relative error is not less than the preset convergence tolerance, then when the current theoretical bearing capacity is less than the radial load of the bearing, update the lower limit of viscosity iteration to the midpoint viscosity. When the current theoretical bearing capacity is greater than the radial load of the bearing, update the upper limit of viscosity iteration to the midpoint viscosity. Iterate in this way until the convergence condition is met.

[0058] Specifically, the relative error between the current theoretical bearing capacity obtained from the simulation and the actual target bearing capacity obtained from the experiment (i.e., the locked radial load of the bearing) is compared with the preset convergence tolerance to determine whether the iteration should terminate; if it does not converge, the upper and lower limits of viscosity are updated, and the iteration is repeated until the convergence condition is met.

[0059] As an example, the relative error between the current theoretical bearing capacity and the radial load of the bearing is calculated using the following formula. : ; in, For the current theoretical carrying capacity, This represents the radial load on the bearing.

[0060] For example, a preset convergence tolerance is used. ,when Record the current midpoint viscosity. And end the iteration, current midpoint viscosity This is the effective viscosity of the liquid metal under this operating condition. ;like If the load-bearing capacity is mismatched, it is determined that the load-bearing capacity is not matched. This indicates that the current viscosity value is too low, and the viscosity needs to be increased to update the lower limit of viscosity iteration. Midpoint viscosity ;if This indicates that the current viscosity value is too high, and the viscosity needs to be reduced, thus updating the viscosity iteration upper limit. Midpoint viscosity After the update, continue with the next iteration until the desired result is met. Output the final effective viscosity .

[0061] S4: Collect the real-time temperature of the liquid metal inside the bearing, and retrieve the ideal viscosity of the bubble-free pure liquid metal at that temperature; based on the effective viscosity and the ideal viscosity, obtain the gas detection result.

[0062] In one possible implementation, step S4 includes: S41: Collect the real-time temperature of the liquid metal inside the bearing, retrieve the ideal viscosity of the bubble-free pure liquid metal at the same temperature, and calculate the relative viscosity deviation between the effective viscosity and the ideal viscosity.

[0063] Optionally, the real-time operating temperature of the liquid metal inside the bearing cavity can be collected by the built-in thermocouple, and the ideal viscosity of the pure medium corresponding to the temperature-pure medium ideal viscosity data table pre-calibrated and stored in the laboratory can be retrieved to obtain the ideal viscosity of the bubble-free liquid metal at the current temperature.

[0064] As an example, the relative viscosity deviation between the effective viscosity and the ideal viscosity is calculated using the following formula. : ; in, For ideal viscosity, This is the effective viscosity.

[0065] S42, when the relative viscosity deviation is greater than or equal to the preset deviation threshold, it is determined that trace amounts of gas have been mixed into the liquid metal.

[0066] As an example, the preset viscosity deviation threshold is preferably 5%; when the calculated relative viscosity deviation δ≥5%, it is determined that trace amounts of gas are mixed in the liquid metal inside the bearing sealing cavity; when δ<5%, it is considered that no bubbles are generated in the current liquid metal medium, the sealing condition is good, and no trace amounts of gas have infiltrated.

[0067] S43, retrieve the viscosity relative deviation-trace gas volume fraction correspondence obtained in advance through multi-temperature and multi-bubble content calibration test, and match it to obtain the current trace gas volume fraction in the liquid metal.

[0068] Specifically, if trace gases are determined to be present, the mapping relationship between the relative viscosity deviation and the volume fraction of trace gases, which was previously established through multi-condition calibration tests, is retrieved, and the volume fraction of trace gases in the current liquid metal is calculated to achieve quantitative detection of trace gases.

[0069] As an example, the correspondence between the relative viscosity deviation and the volume fraction of trace gases was obtained by fitting calibration tests conducted on a rotor test bench under multiple ambient temperatures and varying bubble contents. Throughout the test, the bearing sealing structure was kept intact. Data on the shaft trajectory corresponding to different bubble volume fractions and temperatures were collected. The relative viscosity deviation under each set of conditions was obtained through the same parameter solving and viscosity inversion process as described above. A one-to-one mapping database between the two was established through data fitting. During testing, the real-time calculated relative viscosity deviation is simply input into this mapping relationship to match and obtain the actual volume fraction of trace gases inside the liquid metal, thus completing the non-destructive quantitative detection of trace gases in the sealed bearing.

[0070] For example, multiple sets of calibration data can be fitted into a mapping relationship in the form of a polynomial function. The volume fraction of trace gases can be directly solved by inputting the relative viscosity deviation. Alternatively, a lookup table interpolation method can be used to retrieve the closest deviation value in the calibration database and obtain an accurate gas volume fraction value through linear interpolation.

[0071] In one embodiment, this application also provides a rotor test bench for the above-described gas detection method based on shaft trajectory inversion of effective viscosity, such as... Figure 3 As shown, the rotor test bench includes a pneumatic drive system, a rotor-bearing assembly, an electromagnetic loading device, and a displacement, temperature, and speed measurement system. The pneumatic drive system includes a base, an air inlet, and a turbine. The base is used for the overall installation and fixation of the rotor test bench. The air inlet achieves closed-loop control of the rotor speed by adjusting the air inlet pressure. The turbine, as a power component, is coaxially fixedly connected to the rotor shaft to drive the rotor shaft to rotate at high speed and, in conjunction with the pressure adjustment of the air inlet, achieves constant locking of the rotor speed. The rotor-bearing assembly is equipped with a pair of liquid metal grooved bearings and a rotor shaft. The liquid metal grooved bearings are radial rotation support components for the rotor shaft, supporting and limiting the high-speed rotating rotor shaft. The power input end of the rotor shaft is coaxially connected to the turbine. The bearing cavity is sealed and filled with liquid metal, which can simulate the actual bearing lubrication operation conditions. The electromagnetic loading device includes an electromagnetic loader and a tension sensor. The electromagnetic loader is used to apply a controllable radial load to the rotor shaft, and the tension sensor is used to collect the actual radial loading force in real time and form a closed-loop feedback, thereby achieving constant locking of the radial load on the bearing and restoring the actual stress state of the rotor. The displacement-temperature-speed measurement system includes a sensor bracket, an X-axis eddy current displacement sensor, a Y-axis eddy current displacement sensor, a thermocouple, a reflective pad, and a photoelectric speed sensor. The X-axis and Y-axis eddy current displacement sensors are orthogonally fixed on the sensor bracket and positioned facing the rotor journal surface. They collect radial displacement data in the horizontal and vertical directions of the journal to synthesize the shaft center trajectory. The temperature measuring end of the thermocouple extends into the bearing sealing cavity to collect the real-time temperature of the liquid metal lubricating medium. The reflective pad is fixed to the rotor journal surface, and the photoelectric speed sensor collects the rotor speed in real time by capturing the pulse signal from the reflective pad.

[0072] The technical solution provided in this application relies solely on the collected rotor shaft trajectory data for detection, eliminating the need for additional trace gas sensing elements placed inside and outside the bearing. This avoids damaging the bearing's sealing structure by installing sensors through openings, making it particularly suitable for the use of CT tube integrated sealed liquid metal bearings. Specifically, based on rotor eccentricity characteristic parameters, rotor speed, bearing radial load, and bearing groove structure parameters, a viscosity inverse mapping model is employed. This model, combined with modeling logic adapted to turbulent liquid metal conditions and a bisection iterative algorithm, is used to invert the effective viscosity of the medium. Compared to traditional calculation methods relying on a single parameter and based on laminar flow assumptions, this significantly reduces viscosity calculation errors. By matching the real-time medium temperature to the ideal viscosity of bubble-free pure liquid metal, the viscosity difference between the two is used to complete trace gas detection. No additional excitation or invasive measurement operations are required, resulting in a simple detection process with strong adaptability to various operating conditions, significantly improving the detection accuracy and practicality of trace gases in sealed liquid metal bearings.

[0073] On the other hand, this application also provides a computer storage medium storing executable program code; the executable program code is used to execute any of the above-mentioned gas detection methods based on axis trajectory inversion to determine effective viscosity.

[0074] On the other hand, this application also provides an electronic device, including a memory and a processor; the memory stores program code that can be executed by the processor; the program code is used to execute any of the above-mentioned gas detection methods based on axis trajectory inversion to determine effective viscosity.

[0075] For example, the program code may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the program code in an electronic device.

[0076] The electronic device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The electronic device may include, but is not limited to, processors and memory. Those skilled in the art will understand that the electronic device may also include input / output devices, network access devices, buses, etc.

[0077] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0078] The memory can be an internal storage unit of the electronic device, such as a hard drive or RAM. It can also be an external storage device, such as a plug-in hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory can include both internal and external storage units. The memory is used to store the program code and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or will be output.

[0079] The computer storage medium and electronic device described above are created based on the above method. Their technical functions and beneficial effects will not be elaborated here. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0080] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A gas detection method based on effective viscosity derived from axis trajectory inversion, characterized in that, The method, implemented using a rotor test bench equipped with a grooved bearing made of liquid metal, includes: S1, during the operation of the rotor test bench, the rotor speed and bearing radial load are controlled and maintained at a constant speed. When it is determined that a stable lubrication state has been reached, the radial displacement data of the journal in the horizontal and vertical directions are collected in real time to synthesize the steady-state shaft center trajectory of the rotor. S2, based on the steady-state shaft center trajectory, calculate the rotor eccentricity characteristic parameters, which include at least one of eccentricity, eccentricity ratio, and minimum lubricating film thickness; S3. Construct a viscosity inverse mapping model adapted to the turbulent flow condition of liquid metal. Combine the rotor eccentricity characteristic parameters, the rotor speed, the bearing radial load and the bearing groove structure parameters, and use the bisection iteration method to inversely obtain the effective viscosity of the liquid metal inside the bearing. S4. Collect the real-time temperature of the liquid metal inside the bearing, and retrieve the ideal viscosity of the bubble-free pure liquid metal at that temperature; based on the effective viscosity and the ideal viscosity, obtain the gas detection result.

2. The method according to claim 1, characterized in that, In step S3, the process of constructing the viscosity inverse mapping model includes: Establish a dimensionless turbulent modified Reynolds equation adapted to the turbulent flow conditions of liquid metal; The dimensionless turbulent modified Reynolds equation is discretized using the finite difference method to divide the bearing into circumferential and axial differential meshes. Based on the bearing groove structure parameters, the groove structure boundary conditions are set. The global dimensionless oil film thickness distribution is determined by the rotor eccentricity characteristic parameters. Combined with the journal surface linear velocity obtained from the rotor speed, the global dimensionless oil film pressure under different viscosities is solved and integrated to obtain the theoretical bearing capacity. Calibration tests were conducted under multiple working conditions, including varying rotor speed, bearing radial load, liquid metal temperature, and bubble content. The measured rotor eccentricity characteristic parameters and corresponding actual load-bearing capacity were collected for each working condition. Based on the binary iterative algorithm, the bearing radial load is used as the convergence constraint to correlate the theoretical bearing capacity with the actual bearing capacity, and the viscosity inverse mapping model is fitted and established.

3. The method according to claim 2, characterized in that, Step S3, the process of inverting the effective viscosity using the bisection iterative method, includes: Set upper and lower limits for viscosity iteration and calculate the midpoint viscosity; Based on the dimensionless turbulent modified Reynolds equation, and combined with the midpoint viscosity, the rotor eccentricity characteristic parameters, the rotor speed, and the bearing groove structure parameters, the dimensionless oil film pressure over the entire domain is solved by the finite difference method, and the current theoretical bearing capacity is obtained by integration after dimensional reduction. Using the radial load of the bearing as the convergence target value, the relative error between the current theoretical bearing capacity and the radial load of the bearing is calculated. If the relative error is less than the preset convergence tolerance, the current midpoint viscosity is taken as the effective viscosity of the liquid metal. If the relative error is not less than the preset convergence tolerance, when the current theoretical bearing capacity is less than the radial load of the bearing, the lower limit of viscosity iteration is updated to the midpoint viscosity, and when the current theoretical bearing capacity is greater than the radial load of the bearing, the upper limit of viscosity iteration is updated to the midpoint viscosity. This process is repeated until the convergence condition is met.

4. The method according to claim 3, characterized in that, The dimensionless turbulent modified Reynolds equation is: ； in, , These are the circumferential and axial liquid metal turbulence correction coefficients, respectively. Circumferential dimensionless coordinates; , where the coordinates are dimensionless along the axis; The dimensionless oil film thickness is determined by the spatial distribution of rotor eccentricity characteristic parameters; The pressure is a dimensionless oil film pressure. Where the bearing radius is; This refers to the bearing length. Dimensionless oil film pressure The transformation formula is: ； in, This refers to the bearing radius clearance. The linear velocity of the shaft diameter surface is calculated from the rotor speed. Midpoint viscosity; This represents the actual oil film pressure.

5. The method according to claim 1, characterized in that, In step S1, the rules for determining a stable lubrication state include: If all four conditions are met simultaneously, the rotor-bearing system is deemed to have reached a stable lubrication state: the rotor speed fluctuation range does not exceed ±2%, the bearing radial load fluctuation range does not exceed ±2%, the temperature fluctuation of the liquid metal inside the bearing does not exceed ±1℃, and the overlap of the shaft center trajectory is not less than 90% for at least three consecutive complete rotation cycles.

6. The method according to claim 1, characterized in that, Before step S2, the method further includes: The steady-state shaft center trajectory is purified by bandpass filtering to remove zero-point drift, test bench vibration, and low-frequency interference caused by slow thermal expansion below 0.1 to 0.2 times the rotor frequency; at the same time, sensor electrical noise and high-frequency electromagnetic interference from the motor above 3 to 5 times the rotor frequency are removed, retaining only the effective trajectory component corresponding to the deformation of the liquid oil film.

7. The method according to claim 1, characterized in that, Step S4 includes: The real-time temperature of the liquid metal inside the bearing is collected, the ideal viscosity of the bubble-free pure liquid metal at the same temperature is obtained, and the relative viscosity deviation between the effective viscosity and the ideal viscosity is calculated. When the relative viscosity deviation is greater than or equal to a preset deviation threshold, it is determined that trace amounts of gas have been mixed into the liquid metal. The viscosity relative deviation and trace gas volume fraction correspondence obtained by pre-fitting through multi-temperature and multi-bubble content calibration tests are used to match and obtain the current trace gas volume fraction in the liquid metal.

8. The method according to claim 1, characterized in that, The rotor test bench includes a pneumatic drive system, a rotor-bearing device, an electromagnetic loading device, and a displacement, temperature, and speed measurement system. The pneumatic drive system includes a base, an air inlet, and a turbine. The turbine is coaxially and fixedly connected to the rotor shaft, and is used to achieve constant rotor speed locking through closed-loop regulation of the air inlet pressure. The rotor-bearing device includes a pair of liquid metal grooved bearings and a rotor shaft. The bearing cavity is sealed and filled with liquid metal to simulate the actual bearing lubrication operation conditions. The electromagnetic loading device includes an electromagnetic loader and a tension sensor. The electromagnetic loader is used to apply a controllable radial load to the rotor shaft, and the tension sensor is used to collect the radial load in real time and form a closed-loop feedback to achieve constant locking of the bearing radial load. The displacement-temperature-speed measurement system includes orthogonally arranged X-axis eddy current displacement sensors, Y-axis eddy current displacement sensors, thermocouples, reflective pads, and photoelectric speed sensors. The two sets of orthogonally arranged eddy current displacement sensors are positioned opposite the rotor journal and are used to collect radial displacement data in the horizontal and vertical directions of the journal to synthesize the shaft center trajectory. The temperature measuring end of the thermocouple extends into the bearing sealing cavity to collect the real-time temperature of the liquid metal. The photoelectric speed sensor obtains the rotor speed in real time by recognizing the pulse signal of the rotor reflective pad.

9. The method according to any one of claims 1 to 8, characterized in that, The liquid metal is a gallium indium tin alloy gallium-based liquid metal; the liquid metal grooved bearing is a CT tube-specific herringbone groove radial dynamic pressure sliding bearing, and the bearing groove structure parameters include at least groove depth, groove width, number of circumferential grooves, bearing radius, bearing length, bearing radius clearance, and bearing width, all of which are used as the groove structure boundary conditions of the viscosity inverse mapping model.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

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