Method for adjusting shaft gap size of hybrid bearing based on pump set blade gap

Abstract

The invention relates to the technical field of intelligent regulation and state modeling of large rotating machinery, and discloses a method for adjusting the shaft gap size of a hybrid bearing based on a pump set blade gap, which comprises the following steps: establishing a main shaft eccentric track model, constructing a blade gap dynamic response function, and establishing a dynamic response model; a multi-source sensing signal is used for achieving spindle-blade-static pressure cavity coupling state recognition, the working clearance of a bearing is dynamically adjusted through a pressure difference feedback linkage control strategy, and therefore real-time optimization adjustment of the system operation state is achieved. By means of the method, under the simultaneous action of eccentric change and multi-source disturbance, the system can rapidly recognize the axial clearance change trend, accurately implement a pressure regulation compensation strategy and maintain the stable working state of the hydrostatic bearing. Compared with an existing regulation and control method depending on a static threshold value and single-source signal response, the method has the advantages that the regulation precision is improved, the anti-disturbance capability of the system is enhanced, and the problems of response delay and regulation and control mismatch under complex working conditions are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control and state modeling of large-scale rotating machinery, and in particular to a method for adjusting the clearance size of a dynamic and static pressure bearing shaft based on the clearance of pump group blades. Background Art

[0002] In recent years, the rapid development of large-scale pumped-storage power plants and high-performance reversible pump-turbine units has placed higher demands on dynamic monitoring, intelligent control, and fault warning capabilities for unit operation. Especially during unit startup, transition, and steady-state operation, main shaft eccentricity, blade clearance fluctuations, and the accuracy of the static pressure system response become key factors affecting overall unit stability and operating efficiency. To improve equipment reliability, the industry generally attaches great importance to modeling the state of rotating components, optimizing the response speed of the pressure regulation system, and optimizing signal fusion and judgment capabilities.

[0003] Currently, most control systems on the market utilize fixed sensor locations and preset threshold control logic, typically adjusting controls through single-point speed monitoring, static gap detection, or pressure limit feedback. During the initial commissioning phase of equipment, control models often rely on manual calibration and static measurement data. While some systems incorporate feedback paths for axial or radial eccentricity, these are mostly open-loop logic controls and lack closed-loop control mechanisms based on real-time data modeling. Furthermore, during operation, if multiple disturbance sources occur simultaneously, such as increased eccentricity, temperature rise, or superimposed vibrations, existing systems often struggle to accurately identify and effectively intervene.

[0004] Existing technologies generally lack a unified control solution that can accurately model, rapidly identify, and adaptively regulate voltage under the dynamic coupling of eccentricity and blade clearance. This is particularly true when encountering nonlinear operating conditions such as sudden axis changes or complex interference. This can lead to inefficient restoration of system balance, resulting in control response delays and regulation overshoot, which can even cause equipment shutdowns in severe cases. This is the key technical difficulty addressed and solved by the present invention. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a method for adjusting the clearance size of the dynamic and static pressure bearing shaft based on the blade clearance of the pump group, which solves the problems of control response hysteresis and insufficient system stability under the coupling conditions of eccentricity change and blade clearance.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for adjusting the clearance size of a dynamic and static pressure bearing shaft based on the clearance of a pump group blade, comprising the following steps:

[0007] The raw data of the clearance of the blades at different positions are obtained by multiple laser displacement sensors arranged inside the pump housing;

[0008] Performing filtering and error compensation on the raw clearance data to obtain a blade clearance measurement value;

[0009] A mapping relationship between blade clearance measurement and bearing clearance is established, and corrections are made based on operating condition parameters.

[0010] Determine whether to trigger dynamic pressure or static pressure fluid supply control based on the corrected bearing clearance data;

[0011] When the liquid supply control is triggered, the optimal liquid supply pressure setting value is determined according to the objective function;

[0012] A composite control algorithm is used to control the fluid supply system to dynamically adjust the bearing clearance.

[0013] Preferably, the blade clearance detection system includes four groups of laser displacement sensors, which are fixedly installed at the leading edge, middle, trailing edge and distal end of the corresponding blades inside the pump casing. The laser displacement sensors are reflective laser triangulation ranging type with a measurement frequency of not less than 10kHz and a measurement resolution better than 0.05 microns. Each group of sensors is mechanically fixed and spatially calibrated by a corresponding mounting base and positioning calibration device to ensure that the measurement direction is perpendicular to the moving surface of the blade.

[0014] Preferably, the filtering process adopts a sliding window weighted average algorithm, the sliding window size is 5-15 consecutive sampling points, and the filtering result is updated in real time and smoothly via a hardware circuit for subsequent modeling and compensation.

[0015] Preferably, the error compensation includes sensor static offset correction and temperature drift compensation, the compensation value is preset based on the sensor installation deviation and corrected in combination with the ambient temperature, and after compensation, the blade clearance measurement error is no more than ±0.2 microns.

[0016] Preferably, the mapping relationship between the blade clearance and the bearing clearance is constructed using a linear regression model, and the proportional factor and the offset are obtained by fitting data under at least three typical operating conditions, with the fitting residual not exceeding ±1 micron.

[0017] Preferably, the conditions for triggering the liquid supply strategy include any one of the following:

[0018] The bearing clearance change is greater than 5 microns within three consecutive control cycles;

[0019] or the detected blade clearance changes at a rate exceeding 1 mm per second,

[0020] When the triggering conditions are met, the static pressure liquid supply system is started, the response delay of the system is less than 10 milliseconds, and the liquid supply pressure control error does not exceed ±0.2 MPa.

[0021] Preferably, the optimal liquid supply pressure setting value is obtained by the following objective function:

[0022] F=a·P 2 +b·(Δd) 2 ;

[0023] Wherein, P is the fluid supply pressure, Δd is the difference between the current bearing clearance and the preset target value, a and b are preset weight coefficients, and the ratio of a to b ranges from 1:10 to 1:100.

[0024] Preferably, the set value of the optimal fluid supply pressure is determined by a comprehensive objective function, which takes into account both the fluid supply pressure and the gap error, and the weight of the objective function is determined through experiments based on system stability and energy-saving efficiency. The set value of the optimal fluid supply pressure is determined by a comprehensive objective function, which takes into account both the fluid supply pressure and the gap error, and the weight of the objective function is determined through experiments based on system stability and energy-saving efficiency.

[0025] Preferably, the liquid supply system control adopts a model predictive control and incremental PID composite control strategy, with a control period of 10 milliseconds, a feedback delay of no more than 20 milliseconds, and a control accuracy of no less than ±0.2 MPa.

[0026] An intelligent bearing clearance control device, comprising:

[0027] A laser displacement detection system is used to collect raw data on the clearance of the leading edge, middle, trailing edge, and distal end of the blades inside the pump casing. The detection system uses a reflective laser triangulation sensor with the measurement direction perpendicular to the blade's moving surface.

[0028] Data processing module, used to perform sliding window weighted average filtering, static offset and temperature drift error compensation, gap mapping model fitting and correction calculation;

[0029] The control unit adopts a microcontroller and FPGA collaborative structure, and is configured with model predictive control and incremental PID control algorithms for determining the liquid supply strategy and real-time regulation of the liquid supply pressure;

[0030] The fluid supply module includes a dynamic pressure pump, a static pressure pump, a proportional valve, and a fast-response switching component, which is used to dynamically adjust the bearing fluid supply status;

[0031] The communication and feedback interface module supports the RS485 industrial bus protocol and is used for inter-module data transmission and control closed-loop feedback. The control refresh rate is not less than 100Hz.

[0032] The present invention provides a method for adjusting the clearance size of a dynamic and static pressure bearing shaft based on the clearance of pump group blades. It has the following beneficial effects:

[0033] 1. This invention introduces a multi-point angle consistency acquisition mechanism based on synchronous encoders, ensuring precise sub-millisecond alignment of various sensor data, thereby achieving the technical goal of continuous state reconstruction throughout the entire spindle cycle. Existing technologies often rely on single-point time window acquisition, which suffers from misaligned responses at different sensor points and makes it difficult to restore the true eccentric trajectory.

[0034] 2. By constructing an elliptical fitting model of the axis trajectory and a blade clearance function library, this invention successfully achieves explicit modeling of the shaft-blade-cavity coupling response relationship, significantly improving the accuracy and response efficiency of the control logic. Traditional methods only perform single-dimensional parameter voltage regulation, ignoring the dynamic clearance response caused by nonlinear axial eccentricity changes, resulting in severe model distortion.

[0035] 3. This invention utilizes a multi-event fusion scoring mechanism and a fuzzy decision-making engine. The system automatically switches to the optimal control mode in the presence of concurrent interference signals such as eccentricity, vibration, and temperature rise, enhancing the system's ability to withstand sudden disturbances. Compared to existing strategies based on single-abnormality threshold judgments, this significantly reduces the false alarm rate and the probability of control failure, improving project stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A perspective view of the present invention;

[0037] Figure 2 Schematic diagram of the present invention. DETAILED DESCRIPTION

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0039] Please see the attached Figure 1 -Attached Figure 2 The embodiment of the present invention provides a method for adjusting the clearance size of a dynamic and static pressure bearing shaft based on the clearance of a pump group blade, comprising:

[0040] This structure is suitable for installation in the guide bearings of long-shaft pumps, such as large vertical axial-flow and mixed-flow pumps, to provide spindle support and adjustable clearance control. The structural design takes into account spindle eccentricity, blade swing amplitude, and the load-bearing characteristics of the liquid film between the bearing and the shaft, resulting in a multifunctional coupled bearing system.

[0041] The structure involved in this invention primarily includes: a dynamic and static pressure water guide bearing assembly, a static pressure water supply system, a main shaft position detection device, an impeller clearance monitoring module, and a control actuator that cooperates with it. This structure, together with the real-time closed-loop regulation method described later, forms a complete integrated system.

[0042] The dynamic and static pressure water guide bearing assembly is arranged inside the pump barrel housing to provide radial support for the pump main shaft. It includes:

[0043] The outer shell is cylindrical in shape, with an inner diameter that matches the radial clearance of the spindle. The initial clearance is typically designed to be 0.3mm-0.6mm. The outer shell can be made of stainless steel, copper alloy, or a composite ceramic-metal laminate structure, offering high strength and corrosion resistance.

[0044] Multiple bearing shells are evenly spaced along the inner circumference of the housing. Each shell is typically 80mm to 150mm long in the axial direction. Four or six shells can be selected based on the pump's structure. Each shell features a segmented structure for ease of installation and maintenance, with its inner surface creating a clearance between the shell and the main shaft.

[0045] Each bearing shell is equipped with multiple hydrostatic water supply chambers, preferably 2 to 3 chambers. These chambers are eccentrically distributed within the shell, in a spiral or symmetrically staggered arrangement. Chamber dimensions typically range from 10mm to 12mm in diameter and 20mm to 25mm in depth. The chamber structure is precision machined, and its inner surface is ground to a surface roughness of Ra 0.2μm or less to ensure stable hydrostatic water film formation.

[0046] Each static pressure chamber is connected to the external clean water static pressure supply system through a micro water supply channel. The channel diameter is φ3mm~φ5mm. The end of the channel is equipped with a micro throttling orifice plate or an adjustable electric pressure regulating valve to accurately control the water inlet pressure of each chamber.

[0047] In some embodiments, to enhance water film formation and system responsiveness, the static pressure water supply system features two parallel pumps. Each pump independently controls the chamber on one side of the bearing, creating a static pressure field with an adjustable left-right pressure differential. The water supply pressure can be set between 0.5 MPa and 1.2 MPa, with a maximum transient response rate of less than 200 ms.

[0048] In this embodiment, in order to realize spindle displacement monitoring and axis trajectory judgment, the system is provided with a multi-point spindle radial displacement sensor module, which includes:

[0049] Four radial eddy current displacement sensors are installed at four equally spaced positions between the inner wall of the housing and the main shaft, forming an orthogonal distribution in the XY plane. The accuracy of each sensor is preferably not less than 10μm and the response frequency is not less than 1kHz.

[0050] The sensor is connected to the central FPGA control unit and calculates the spindle eccentricity e(t) in real time through the voltage-displacement conversion model. The specific calculation expression is as follows:

[0051]

[0052] in:

[0053] x1(t), x1(t), x3(t), x4(t): are the displacement data collected by the four eddy current sensors at time t;

[0054] e(t): Real-time eccentricity of the spindle at time t.

[0055] In some embodiments, the system is further provided with an axial sensor to monitor the axial movement of the spindle to prevent the axial force change from interfering with the radial clearance control strategy.

[0056] In this embodiment, a blade clearance detection module is incorporated into the structure to dynamically detect the gap between the pump blades and the pump casing. This module contains multiple non-contact clearance sensors, such as laser displacement meters, capacitive sensors, or ultrasonic sensors, mounted on fixed locations on the pump casing, forming a monitoring area corresponding to the rotational trajectory of each blade. The sensor signal output is connected to the main control system, and the output blade clearance value is used to assist in determining the direction of shaft center drift.

[0057] The blade clearance value is used to construct a three-dimensional clearance change model, and combined with the spindle offset to form a multi-dimensional state judgment basis. For example, the judgment logic can be set as follows:

[0058] If any blade clearance δ i Requirements:

[0059] δ i (t)<δ min +k·σ i ;

[0060] The control system then triggers the static pressure chamber pressure increase operation.

[0061] in:

[0062] δ i (t): instantaneous clearance of the i-th impeller;

[0063] δ min : Impeller design minimum safety clearance;

[0064] σ i : Historical volatility standard deviation;

[0065] k: Sensitivity coefficient, ranging from 0.8 to 1.5.

[0066] In this embodiment, an FPGA-based real-time control processing module is employed to enhance system control capabilities and response speed. This module integrates an analog acquisition unit, a digital calculation unit, and a PWM electronic control output interface, enabling precise regulation of the pressure in each static water supply chamber. It also incorporates a reconfigurable control logic unit and supports dynamic programming updates.

[0067] The following are the specific contents:

[0068] This step is the ultra-stable stage in the method of the present invention. The execution time is generally set before the first cold start after the initial installation and commissioning of the system. During this stage, the system collects initial data between the main shaft dynamics and the impeller in a no-load state, and establishes a benchmark database for subsequent state identification and dynamic comparison.

[0069] In this experiment, the system drives the spindle at a constant, low speed through a hydraulic drive disk device, usually controlled at 20 to 30 rpm, in order to avoid structural deformation and vibration interference caused by rotational inertia.

[0070] In this process, the system mainly performs the following technical processes:

[0071] Multi-point axial tilt data acquisition

[0072] During the main shaft rotation cycle, four eddy current displacement sensors arranged in the dynamic and static pressure water guide bearing housing synchronously record the changes in the radial clearance between the main shaft and the bearing shell;

[0073] The acquisition frequency is preferably set to ≥1kHz to ensure that at least ≥1000 sets of displacement data are obtained per revolution. The following parameters are recorded for each data point:

[0074] Current angle θ k ;

[0075] The gap value x1(θ k ),x2(θ k ),x3(θ k ),x4(θ k );

[0076] Sensing timestamp t0.

[0077] In a complete speed cycle, the following basic radial clearance matrix is formed:

[0078] X={x i (θ0)|i=1,k=1-N};

[0079] Where N is the total number of sampling points in the periodic interval.

[0080] In some practical examples, the sliding average filter method can be used to process the original signal:

[0081]

[0082] Where M is the sliding window length, which is generally set to 3 to 5.

[0083] Modeling of spindle eccentric trajectory:

[0084] According to the above radial clearance data, the two-dimensional offset trajectory of the spindle eccentricity during one circle of rotation can be restored.

[0085] The trajectory calculation model is as follows:

[0086]

[0087] Construct the spindle center trajectory set at all angle points θ0:

[0088] E = {e(θ0) | k = 1-N};

[0089] This trajectory can be fitted into an elliptical trajectory or annular trajectory through least squares, which represents the natural running posture of the spindle under the ideal no-bias load state.

[0090] In some practical applications, Fourier transform can be introduced to e x The (θ0) curve is analyzed in the frequency domain to extract the structural adjustment frequency components of the system for structural fault diagnosis and correction.

[0091] During the same time period, the gap value δi (θ k ), each blade has an independent sampling channel.

[0092] In one rotation cycle, record the complete clearance change curve of each blade:

[0093] Δ i ={δ i (θ k )|k=1~N};

[0094] The system is based on the current spindle angle θ k , combined with e(θ k ) and δi(θ k ), establish the “axis position-blade clearance” relationship matrix:

[0095] M i =((e(θ k ),δ i (θ k ))|k=1~N);

[0096] This matrix is used to construct multivariate linear fits or nonlinear shift functions:

[0097] δi(θ)=f i (e x ,e y )+ε;

[0098] in:

[0099] f i () is the clearance response function of the i-th blade offset relative to the main axis;

[0100] ε is the model error term, which is generally compressed to within 0.05 mm through minimum variance fitting.

[0101] This model forms the basis of the subsequent dynamic adjustment algorithm, which is used to predict the possible clearance reduction of a specific blade under a certain axial center offset state, thereby guiding the direction and amplitude of static pressure chamber pressure adjustment.

[0102] To ensure comparability and traceability during system operation, the system establishes a set of baseline state parameters and records the following:

[0103] Initial spindle eccentricity trajectory function E(θ);

[0104] Initial clearance curve δ of each impeller i0 (θ);

[0105] Gap response function set f i (e x ,e y );

[0106] Maximum and minimum clearance statistics during the spindle rotation cycle;

[0107] Initial static pressure chamber water supply pressure value P i0 ;

[0108] Spindle angle-axis center offset stable range;

[0109] The parameter table is stored in the cache area of the FPGA control unit and is also backed up to the system non-volatile storage and locked as version V0.

[0110] In some optional embodiments, the system provides a "benchmark reconstruction" function to meet the need for recalibration after operations such as equipment maintenance, shaft replacement, or impeller replacement.

[0111] Example 1:

[0112] In this embodiment, the present invention is applied to a 500MW horizontal reversible pump-turbine unit in a large-scale hydropower station pumped storage project. The unit is a newly built device and enters the first cold state modeling stage after the unit commissioning and installation are completed.

[0113] The specific operation process is as follows:

[0114] Device configuration parameters:

[0115] The spindle length is 5.2m and the maximum design speed is 600rpm;

[0116] The dynamic and static pressure hybrid water-guided bearing is equipped with four KEYENCE-EZ-HV eddy current sensors, which are spaced 90 degrees apart.

[0117] Twelve laser gap sensors are installed on the top and circumference of the pump casing (two on each impeller), model SICK-OD5000 series;

[0118] All sensors are linked to high-precision encoders for sampling, and a unified synchronous clock module is set inside the system (error < ±100μs).

[0119] Turning and data collection process:

[0120] The hydraulic drive device slowly starts the spindle turning, the speed is constantly controlled at 25 rpm, and the turning time is set to 240 seconds;

[0121] Collect ≥2000 points of radial gap data per rotation cycle, and record the timestamp, angle code and gap voltage signal;

[0122] Synchronously record the non-contact clearance value of the blade at each angle;

[0123] The collected data is stored in the FPGA on-chip cache and synchronously uploaded to the host PC for modeling calculations.

[0124] Data processing and model building:

[0125] The original radial data were smoothed using a fifth-order sliding average filter algorithm;

[0126] The spindle axis trajectory is restored by ellipse fitting (least square method), and the fitting error is controlled within ±0.03mm;

[0127] The response function of each blade δ i =f i (e x ,e γ ) Fitting R 2 Values ≥ 0.97, meeting the model stability criteria;

[0128] After model fitting, a linear + second-order mixed function response model is established inside the controller to adapt to small-scale nonlinear offsets.

[0129] Benchmark parameter solidification and management:

[0130] Establish a complete benchmark parameter table, including E(θ), δi0 (θ), response function f i (), static initial pressure P0, etc.;

[0131] The parameters are solidified into the FPGA control unit and encrypted into version V0;

[0132] Back up to the non-volatile FLASH storage of the control system, and record the modeling time, operator and working condition number.

[0133] Through the above embodiments, the present invention realizes high-precision reconstruction of the natural eccentricity of the main shaft and closed-loop modeling of the initial state space data, which significantly improves the efficiency of dynamic offset recognition and the accuracy of static pressure control response in subsequent operation.

[0134] Example 2:

[0135] This embodiment is used to demonstrate the rapid response and closed-loop control capabilities of the system when encountering a combined situation of "transient eccentricity mutation + sharp reduction of gap" during unit operation.

[0136] Scenario simulation:

[0137] The equipment is running stably at 460 rpm;

[0138] A sudden short-term water hammer caused the main shaft to have an axial deviation of 1.6mm in the θ=45° direction (the normal maximum eccentricity is 1.0mm);

[0139] At the same time, the current gap of blade number 7 is changed from the original value δ 07 =1.8mm dropped sharply to 1.2mm.

[0140] The system response process is as follows:

[0141] FPGA abnormality judgment logic:

[0142] If e(θ=45°)>1.2mm is detected for two consecutive cycles, “eccentricity abnormality” is triggered;

[0143] At the same time, δ7(θ) decreases by more than 0.5 mm, triggering “local compression risk”;

[0144] The event fusion module comprehensively determines that this is a "sudden change and shrinkage joint event" and enters the emergency control state.

[0145] 2. Static pressure chamber adjustment strategy:

[0146] The control system calculates the eccentricity direction vector in real time and determine the direction of regulation;

[0147] The chamber pressure setting in the X+ and Y+ directions is increased by ΔP = +0.4 MPa;

[0148] The PWM duty cycle of the pressure regulating valve is increased from the initial 60% to 80%, and the regulation is completed within the sampling period;

[0149] 3. Feedback control closed loop execution:

[0150] The system enters 1ms closed-loop execution mode;

[0151] Continuously monitor the dynamic recovery curves of e(t) and δ7(t);

[0152] After about 125ms, e(t) drops back to 0.85mm and δ7(t) recovers to above 1.6mm;

[0153] The controller records the response process and updates the pressure difference-offset empirical function table for subsequent optimization.

[0154] This embodiment demonstrates the system's ability to quickly identify joint risk events, perform directional control, perform closed-loop recovery, and perform self-learning. It has extremely high practical engineering value and is particularly suitable for pump-water turbine devices with high reliability requirements.

[0155] Example 3:

[0156] This embodiment mainly focuses on the system's stable response capability under complex disturbance conditions, including multi-source information fusion judgment such as eccentricity growth, structural vibration enhancement, and abnormal temperature increase.

[0157] Working condition simulation data:

[0158] The spindle eccentricity curve e(t) exceeds 1.1mm and has entered the baseline warning value (e max =1.0mm);

[0159] δ4(t) is smaller than the initial value δ 04 Reduced by 0.45mm, it is close to the minimum safety gap;

[0160] The vibration sensor recorded that the lateral vibration frequency of the bearing seat was 1.8 times that of the normal operating condition;

[0161] At the same time, the bearing oil temperature rises to 75°C, exceeding the threshold of 65°C.

[0162] The system's multi-event fusion judgment and response are as follows:

[0163] Signal fusion and criterion superposition recognition:

[0164] The controller is equipped with a "multi-source event fusion judgment unit" that uses a fuzzy weight mechanism to make decisions;

[0165] Eccentricity (weight 0.4), vibration (weight 0.3), temperature rise (weight 0.3);

[0166] The superposition score index R = 0.4×1.1+0.3×1.8+0.3×(75 / 65)≈1.52, which exceeds the set threshold of 1.3 and triggers the protection mode.

[0167] One-button control mechanism starts:

[0168] The system suspends fine-tuning control and switches to "unified boost protection mode";

[0169] The pressure of all static pressure chambers rises rapidly and uniformly to P i =1.3MPa;

[0170] Synchronously start the spindle motor temperature control system and the bearing cooling water boost pump;

[0171] Subsequent stability monitoring and rollback:

[0172] The controller enters a 60-second transition observation window;

[0173] If during this period, e(t), δ4(t), vibration and temperature signals all return to the normal range, it will automatically fall back to the normal adjustment strategy;

[0174] At the same time, the "compound disturbance event" number and process curve are recorded for operation and maintenance personnel to trace the source and conduct analysis.

[0175] This scenario demonstrates that the system has the ability to make decisions through multi-source sensor data fusion, fault trend warning, and global protection control, significantly enhancing the system's ability to resist complex disturbances and making it suitable for deployment in key pump station operation safety scenarios.

[0176] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for adjusting the clearance size of a dynamic and static pressure bearing shaft based on the clearance of a pump group blade, characterized in that: The following steps are involved: The raw data of the clearance of the blades at different positions are obtained by multiple laser displacement sensors arranged inside the pump housing; Performing filtering and error compensation on the raw clearance data to obtain a blade clearance measurement value; A mapping relationship between blade clearance measurement and bearing clearance is established, and corrections are made based on operating condition parameters. Determine whether to trigger dynamic pressure or static pressure fluid supply control based on the corrected bearing clearance data; When the liquid supply control is triggered, the optimal liquid supply pressure setting value is determined according to the objective function; A composite control algorithm is used to control the fluid supply system to dynamically adjust the bearing clearance.

2. The method for adjusting the clearance size of the dynamic and static pressure bearing shafts based on the clearance of the pump group blades according to claim 1 is characterized in that: The blade clearance detection system includes four groups of laser displacement sensors, which are fixedly installed inside the pump casing at the leading edge, middle, trailing edge and distal end of the corresponding blades. The laser displacement sensors are reflective laser triangulation ranging type with a measurement frequency of not less than 10kHz and a measurement resolution better than 0.05 microns. Each group of sensors is mechanically fixed and spatially calibrated by a corresponding mounting base and positioning calibration device to ensure that the measurement direction is perpendicular to the blade moving surface.

3. The method for adjusting the clearance size of the dynamic and static pressure bearing shafts based on the clearance of the pump group blades according to claim 1 is characterized in that: The filtering process adopts a sliding window weighted average algorithm, the sliding window size is 5-15 consecutive sampling points, and the filtering result is updated in real time and smoothly via a hardware circuit for subsequent modeling and compensation.

4. The method for adjusting the clearance size of the dynamic and static pressure bearing shaft based on the clearance of the pump group blades according to claim 1 is characterized in that: The error compensation includes sensor static offset correction and temperature drift compensation. The compensation value is preset based on the sensor installation deviation and corrected in combination with the ambient temperature. After compensation, the blade gap measurement error is no more than ±0.2 microns.

5. The method for adjusting the clearance size of the dynamic and static pressure bearing shafts based on the clearance of the pump group blades according to claim 1, characterized in that: The mapping relationship between the blade clearance and the bearing clearance is constructed using a linear regression model, and the proportional factor and offset are obtained by fitting data under at least three typical operating conditions, with the fitting residual not exceeding ±1 micron.

6. The method for adjusting the clearance size of the dynamic and static pressure bearing shafts based on the clearance of the pump group blades according to claim 1, characterized in that: The conditions that trigger the fluid supply strategy include any of the following: The bearing clearance change is greater than 5 microns within three consecutive control cycles; or the detected blade clearance changes at a rate exceeding 1 mm per second, When the triggering conditions are met, the static pressure liquid supply system is started, the response delay of the system is less than 10 milliseconds, and the liquid supply pressure control error does not exceed ±0.2 MPa.

7. The method for adjusting the clearance size of the dynamic and static pressure bearing shafts based on the clearance of the pump group blades according to claim 1, characterized in that: The optimal liquid supply pressure setting value is obtained through the following objective function: F=a·P 2 +b·(Δd) 2 ; Wherein, P is the fluid supply pressure, Δd is the difference between the current bearing clearance and the preset target value, a and b are preset weight coefficients, and the ratio of a to b ranges from 1:10 to 1:

100.

8. The method for adjusting the clearance size of the dynamic and static pressure bearing shafts based on the clearance of the pump group blades according to claim 1, characterized in that: The set value of the optimal fluid supply pressure is determined by a comprehensive objective function, which takes into account both the fluid supply pressure and the gap error. The weight of the objective function is determined through experiments based on system stability and energy-saving efficiency. The set value of the optimal fluid supply pressure is determined by a comprehensive objective function, which takes into account both the fluid supply pressure and the gap error. The weight of the objective function is determined through experiments based on system stability and energy-saving efficiency.

9. The method for adjusting the clearance size of the dynamic and static pressure bearing shaft based on the clearance of the pump group blades according to claim 1, characterized in that: The liquid supply system control adopts a model predictive control and incremental PID composite control strategy, with a control period of 10 milliseconds, a feedback delay of no more than 20 milliseconds, and a control accuracy of no less than ±0.2 MPa.

10. An intelligent bearing clearance control device, according to the method for adjusting the clearance size of a dynamic and static pressure bearing shaft based on the clearance of a pump group blade according to any one of claims 1 to 9, characterized in that: include: A laser displacement detection system is used to collect raw data on the clearance of the leading edge, middle, trailing edge, and distal end of the blades inside the pump casing. The detection system uses a reflective laser triangulation sensor with the measurement direction perpendicular to the blade's moving surface. Data processing module, used to perform sliding window weighted average filtering, static offset and temperature drift error compensation, gap mapping model fitting and correction calculation; The control unit adopts a microcontroller and FPGA collaborative structure, and is configured with model predictive control and incremental PID control algorithms for determining the liquid supply strategy and real-time regulation of the liquid supply pressure; The fluid supply module includes a dynamic pressure pump, a static pressure pump, a proportional valve, and a fast-response switching component, which is used to dynamically adjust the bearing fluid supply status; The communication and feedback interface module supports the RS485 industrial bus protocol and is used for inter-module data transmission and control closed-loop feedback. The control refresh rate is not less than 100Hz.

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