Intelligent hydraulic test system for servo valve

Abstract

The invention provides an intelligent hydraulic test system for a servo valve, and belongs to the technical field of hydraulic test of servo valves. Comprising a hydraulic test execution assembly and a test control assembly. The hydraulic test execution assembly comprises a pressure source used for providing hydraulic pressure, a test board used for being connected with a servo valve, a hydraulic channel used for being connected with the pressure source and the test board, a flow meter used for detecting a flow value and a pressure meter used for detecting a pressure value. The execution controller is connected with the servo valve and outputs a control signal to the servo valve; the test control assembly can automatically complete the hydraulic test of the servo valve according to a preset instruction; by using the intelligent hydraulic test system for the servo valve, the hydraulic test of the servo valve can be automatically completed; before testing is started, the intelligent hydraulic testing system can automatically complete centering control and valve element position compensation.

Description

Technical Field

[0001] The present invention belongs to the technical field of servo valve hydraulic testing, and more particularly relates to an intelligent hydraulic testing system for a servo valve. Background Art

[0002] In hydraulic control systems, servo valves are core precision components, and their static performance (zero bias, linearity, and hysteresis) directly affects system control accuracy. Existing technologies have the following drawbacks: Single function 1) Traditional testing equipment can only collect pressure-flow curves and cannot make real-time corrections to substandard valve bodies; 2) Calibration requires external software or modification of embedded firmware; Inefficiency Manual adjustment takes up to 2-3 hours per valve and requires cross-platform operation (test → analysis → parameter adjustment → retest) Insufficient precision 1) It is difficult to achieve a standard straight line through manual adjustment; 2) Unable to meet the stringent requirements of scenarios such as aviation hydraulics. Summary of the Invention

[0003] To overcome the above problems, one object of the present invention is to provide an intelligent hydraulic test system for a servo valve, comprising a hydraulic test execution component and a test control component: The hydraulic test execution assembly includes a pressure source for providing hydraulic pressure, a test bench for connecting to a servo valve, a hydraulic channel for connecting the pressure source and the test bench, a flow meter for detecting a flow value, a pressure gauge for detecting a pressure value, and an execution controller connected to the servo valve and outputting a control signal to the servo valve; The test control component is connected to the pressure source and can configure the output pressure and output flow of the pressure source; the test control component is connected to the flow meter and the pressure gauge and can obtain the flow value and pressure value detected by the flow meter and the pressure gauge; the test control component is connected to the execution controller and is used to output the configuration signal; The test control component can automatically complete the hydraulic test of the servo valve according to preset instructions.

[0004] Preferably, the test control component further comprises a centering control module, wherein the centering control module dynamically generates a valve core position compensation signal based on the zero bias error; The centering control module adopts a fuzzy PID self-tuning algorithm. The input of the fuzzy PID self-tuning algorithm is the zero offset and change rate of the pressure-flow curve; the output of the fuzzy PID self-tuning algorithm is the real-time compensation of the servo valve spool displacement increment and is converted into a signal offset of the execution controller through the servo valve spool displacement.

[0005] Preferably, the test control component also includes a linearity adjustment module, which includes a curve distortion identification unit and a dynamic adjustment unit; the dynamic adjustment unit can obtain the static curve of the servo valve and obtain a correction linearity equation based on the static curve; the curve distortion identification unit decomposes the nonlinear harmonic components of the static curve through wavelet transform.

[0006] Preferably, the test control component further comprises an intelligent control core, which is used to perform performance deviation identification, link flow meters and pressure gauges to perform servo valve calibration and verification testing.

[0007] Preferably, the intelligent control core includes a digital twin engine, which includes a digital model of the servo valve; the digital twin engine is used to perform correction simulation based on the digital model of the servo valve in a virtual environment before performing servo valve calibration, simulate the adjustment effect and optimize the parameters.

[0008] Preferably, the digital twin engine is used to perform the following operations: Build a multi-physics model of the servo valve; Acquire test data from hydraulic test execution components and test control components to drive simulation; Output the optimal correction parameter combination to the physical system.

[0009] Preferably, the correction parameter combination includes: a compensation current value for zero bias error, a correction coefficient for linearity distortion, and a PID parameter for dynamic response.

[0010] Preferably, the test control component also includes a cloud-edge collaboration platform, which is used to connect the local test control component with the cloud database and can perform remote algorithm updates and big data analysis.

[0011] Preferably, the cloud-edge collaborative platform includes a distributed learning unit and an elastic parameter library; The distributed learning unit can aggregate correction data from multiple test control components to train shared models; the flexible parameter library can call preset optimization parameter packages according to servo valve models or working conditions.

[0012] Preferably, the intelligent hydraulic test system writes the correction parameters into the controller inside the servo valve, so that the servo valve can operate with the tested optimal parameters when it operates independently.

[0013] As described above, the intelligent hydraulic testing system for a servo valve of the present invention can automatically complete the hydraulic testing of the servo valve; before the test begins, the intelligent hydraulic testing system can automatically complete centering control and valve core position compensation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be more fully understood from the following detailed description taken in conjunction with the accompanying drawings, in which like elements are numbered in a similar manner, and in which: Figure 1 is a schematic diagram of an intelligent hydraulic test system for a servo valve; Figure 2 It is a schematic diagram of a linearity adjustment module of an intelligent hydraulic test system for a servo valve; Figure 3 Schematic diagram of a digital twin engine for an intelligent hydraulic test system for servo valves. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 any creative efforts shall fall within the scope of protection of the present invention.

[0016] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indications will also change accordingly. Unless otherwise clearly specified and limited, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific circumstances.

[0017] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" or "second" may explicitly or implicitly include at least one of such features. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0018] The technical solutions of the present invention are further described in detail below through examples and in conjunction with the accompanying drawings, but the present invention is not limited to the following examples.

[0019] In hydraulic control systems, servo valves are core precision components, and their static performance (zero bias, linearity, and hysteresis) directly affects system control accuracy. Existing technologies have the following drawbacks: Single function 1) Traditional testing equipment can only collect pressure-flow curves and cannot make real-time corrections to substandard valve bodies; 2) Calibration requires external software or modification of embedded firmware.

[0020] Inefficiency Manual adjustment takes up to 2-3 hours per valve and requires cross-platform operation (test → analysis → parameter adjustment → retest) Insufficient precision 1) It is difficult to achieve a standard straight line through manual adjustment; 2) Unable to meet the stringent requirements of scenarios such as aviation hydraulics.

[0021] To overcome the above problems, one object of the present invention is to provide an intelligent hydraulic test system for a servo valve, comprising a hydraulic test execution component and a test control component: The hydraulic test execution assembly includes a pressure source for providing hydraulic pressure, a test bench for connecting to a servo valve, a hydraulic channel for connecting the pressure source and the test bench, a flow meter for detecting a flow value, a pressure gauge for detecting a pressure value, and an execution controller connected to the servo valve and outputting a control signal to the servo valve; The test control component is connected to the pressure source and can configure the output pressure and output flow of the pressure source; the test control component is connected to the flow meter and the pressure gauge and can obtain the flow value and pressure value detected by the flow meter and the pressure gauge; the test control component is connected to the execution controller and is used to output the configuration signal; The test control component can automatically complete the hydraulic test of the servo valve according to preset instructions.

[0022] A servo valve is a high-precision hydraulic control component that converts electrical signals into hydraulic signals, enabling precise control of parameters such as displacement, speed, and force of hydraulic actuators. It is widely used in industrial automation, aerospace, and precision manufacturing.

[0023] The servo valve hydraulic test system is a professional device designed to comprehensively test and evaluate the performance indicators of servo valves. It simulates the hydraulic environment and electrical control conditions of the servo valve in actual operation, accurately measures its various performance parameters, and verifies whether the servo valve meets the design standards, factory requirements, or maintenance needs.

[0024] The servo valve hydraulic test system mainly plays the following roles: 1) During the servo valve production process, we conduct tests to confirm whether the product meets the design performance indicators, screen out unqualified products, and ensure the factory quality; 2) During the servo valve production process, we conduct tests to confirm whether the product meets the design performance indicators, screen out unqualified products, and ensure the factory quality; 3) During the use or maintenance phase of the servo valve, determine the degree of performance degradation and the cause of the failure (such as sticking, leakage, slow response, etc.) through testing, and provide guidance on repair or replacement; 4) Test the servo valve according to international or industry standards to ensure that it meets the application specifications in specific fields.

[0025] The servo valve hydraulic test system is primarily used to test the static and dynamic performance of servo valves. Static performance refers to the relationship between the servo valve's output hydraulic parameters, such as flow rate and pressure, and the input signal when the input signal is stable. This includes indicators such as zero-position characteristics, pressure gain / flow gain, linearity, hysteresis, consistency, and internal leakage.

[0026] Among the above indicators, zero-position characteristics include zero offset and zero drift. Zero offset is the control signal (voltage / current) required to maintain the servo valve at zero position, excluding the effects of hysteresis. It is expressed as a percentage of the rated current / voltage and reflects the valve's zero adjustment accuracy. Zero drift is the change in zero offset, expressed as a percentage of the rated current / voltage, and affects control stability.

[0027] Pressure gain refers to the rate of change of load pressure drop with input current when the flow rate at the control ports (ports A and B) is zero. A higher pressure gain in a servo valve increases the stiffness of the servo system, strengthens its load-carrying capacity, and reduces system error. Low pressure gain indicates high zero-position leakage and poor fit between the valve core and sleeve, resulting in a slow and sluggish servo system response.

[0028] Linearity refers to the degree of agreement between the nominal flow curve and the nominal flow gain curve, assuming all other operating variables remain constant. The nominal flow curve represents the position of the curve within the full cycle flow curve, i.e., the zero-hysteresis flow curve. With sufficiently low hysteresis, one side of the flow curve can generally be used as the nominal flow curve. The nominal flow gain is the slope of a straight line drawn from the zero flow point of the nominal flow curve across the rated current range of one polarity, minimizing the deviation of the nominal flow curve from the straight line.

[0029] Hysteresis is the maximum difference in flow rate that occurs during a positive or negative control signal (voltage / current), expressed as a percentage of the control signal.

[0030] Consistency (repeatability) refers to the consistency of output parameters when the same signal is input multiple times under the same conditions. Poor repeatability will lead to unstable control error.

[0031] Internal leakage is the total flow rate inside the valve from the oil supply port to the oil return port when the control port flow is zero.

[0032] Dynamic performance refers to the response characteristics of the servo valve's output parameters when the input signal changes with time (such as step, sine, and pulse signals). It reflects the valve's ability to follow rapidly changing signals and mainly includes: response time, frequency response characteristics, overshoot, and dynamic hysteresis.

[0033] Response time includes rise time and adjustment time. Rise time refers to the time required for the output parameter to rise from the initial value to the stable value when the input signal changes stepwise, reflecting the valve's rapid response capability. Adjustment time refers to the time required for the output parameter to reach and stabilize within the allowable error range.

[0034] Frequency response characteristics include amplitude-frequency and phase-frequency characteristics. The amplitude-frequency characteristic refers to how the ratio of the output parameter amplitude to the input signal amplitude varies with frequency under a sinusoidal input signal. The "-3 dB cutoff frequency" is usually used to represent the highest signal frequency that a valve can follow. Higher frequencies indicate better dynamic response. The phase-frequency characteristic refers to how the phase difference between the output and input signals varies with frequency. The smaller the phase difference, the better the followability.

[0035] Overshoot refers to the maximum deviation of the output parameter from the stable value when a step signal is input. Excessive overshoot can cause system oscillation and affect stability.

[0036] Dynamic hysteresis refers to the difference between the output parameters corresponding to the same input amplitude during the rising and falling processes under a dynamic input signal, reflecting the reverse accuracy of the valve during rapid changes.

[0037] In this embodiment, Figure 1 As shown, an intelligent hydraulic test system for a servo valve according to this embodiment includes a hydraulic test execution component and a test control component. Specifically, the hydraulic test execution component and the test control component operate at the physical layer.

[0038] The hydraulic test execution component includes a pressure source for providing hydraulic pressure, a test bench for connecting to a servo valve, a hydraulic channel for connecting the pressure source and the test bench, a flow meter for detecting flow values, a pressure gauge for detecting pressure values, and an execution controller connected to the servo valve and outputting a control signal to the servo valve.

[0039] In this embodiment, the pressure source can be a device capable of providing hydraulic power, such as a hydraulic pump. The test bench is connected to the servo valve. The test bench and pressure source are connected via a hydraulic channel, and the test bench and servo valve are mounted in a matching manner. A servo valve is a high-precision, high-frequency hydraulic control valve. Its core function is to accurately and quickly convert weak electrical signals into high-power hydraulic output, thereby achieving precise closed-loop control of the position, speed, or force of the hydraulic actuator. The servo valve in this embodiment uses a motor to control the movement of the valve core within the valve body or valve sleeve, thereby controlling the direction and magnitude of fluid flow.

[0040] Specifically, the servo valve of this embodiment includes an oil supply port (P port) connected to a pressure source, an oil return port (T port) connected to an oil tank, and two control ports (A and B ports) connected to an actuator.

[0041] The flow meter and the pressure gauge can be set inside the test bench, and the execution controller is connected to the control interface of the servo valve to output a control signal that matches the servo valve.

[0042] The test control component is connected to the pressure source and can configure the output pressure and output flow of the pressure source; the test control component is connected to the flow meter and pressure gauge and can obtain the flow value and pressure value detected by the flow meter and pressure gauge; the test control component is connected to the execution controller and is used to output the configuration signal.

[0043] The test control component can automatically complete the hydraulic test of the servo valve according to preset instructions.

[0044] In a specific implementation process, the preset instructions include static performance test instructions and dynamic performance test instructions for executing a servo valve hydraulic test.

[0045] Static performance tests include: 1. No-load flow characteristic test The control pressure source maintains a stable supply pressure and a return pressure close to zero. The control signal sent to the servo valve changes stepwise from negative full-scale to positive full-scale (or vice versa), and the corresponding output flow rate is recorded. The control signal can be voltage or current. A curve is generated showing the relationship between the control signal voltage / current and the flow rate.

[0046] This test can reflect the flow gain information, linearity information, and symmetry information of the servo valve.

[0047] 2. Pressure gain test The control test bench closes the control ports (ports A and B), sends a small control signal to the servo valve, such as ±1% full-scale current, and detects the pressure difference between the two control ports.

[0048] This test can reflect the pressure gain information of the servo valve, that is, the pressure difference change caused by unit current.

[0049] 3. Internal leakage test Send a zero-position control signal to the servo valve, close the control ports (ports A and B), and measure the leakage flow from the oil supply port (port P) to the oil return port (port T).

[0050] This test can reflect the degree of valve core wear or manufacturing / assembly accuracy.

[0051] 4. Threshold test Slowly increase / decrease the control signal (current / voltage) and record the minimum current increment at which the flow rate begins to change.

[0052] This test can reflect the threshold, that is, the minimum input current that causes flow change; resolution, the current value corresponding to the minimum flow change that can be accurately controlled.

[0053] Dynamic testing is used to evaluate the servo valve's ability to respond to rapidly changing signals (frequency response, step response), including: 1. Frequency response test Sends a sinusoidal control signal to the servo valve; sweeps the frequency within a specified frequency range.

[0054] This test can reflect the amplitude ratio, that is, the output flow amplitude / input current amplitude; as well as the phase lag, the phase difference between the output and the input; and the bandwidth, the frequency when the gain drops to the low-frequency gain, to reflect the response speed; and the resonance peak, the frequency and peak value at the maximum gain. If it is too high, it means poor stability.

[0055] 2. Step response test Sending an input step current signal to the servo valve; High-speed recording of output flow or valve core displacement, and its curve over time.

[0056] This test can reflect response time; overshoot, which is the maximum percentage the output exceeds the steady-state value; and settling time, which is the time it takes the output to reach and remain at the steady-state value.

[0057] The test control component can automatically complete the hydraulic test of the servo valve according to the above preset instructions.

[0058] Furthermore, the test control component further includes a centering control module, which dynamically generates a valve core position compensation signal based on the zero bias error; The centering control module adopts a fuzzy PID self-tuning algorithm. The input of the fuzzy PID self-tuning algorithm is the zero offset and change rate of the pressure-flow curve; the output of the fuzzy PID self-tuning algorithm is the real-time compensation of the servo valve spool displacement increment and is converted into a signal offset of the execution controller through the servo valve spool displacement.

[0059] Servo valve zero offset error occurs when the valve core fails to maintain its precise neutral position when the control signal is zero. This results in a slight opening of the valve orifice, which in turn causes the actuator to produce undesirable small flows or displacements. It is a key indicator in servo valve performance evaluation, directly impacting the system's control accuracy and stability.

[0060] The control module includes two functions: detecting the zero bias error and generating a compensation signal according to the magnitude of the zero bias error.

[0061] Zero offset error is not a fixed value and can vary due to factors such as temperature, load, and aging. Therefore, the centering control module must continuously monitor real-time changes in zero offset and update the compensation signal in real time. For example, if the hydraulic system heats up and the valve core thermally deforms, causing an increase in zero offset, the centering control module will immediately adjust the compensation to prevent error accumulation.

[0062] The PID self-tuning algorithm combines fuzzy control technology and PID control technology to adaptively adjust control parameters to cope with the nonlinear and time-varying characteristics of the system.

[0063] PID control refers to the ability to adaptively adjust control parameters to cope with the nonlinear and time-varying characteristics of the system.

[0064] Fuzzy control simulates human experience and judgment, transforming complex nonlinear relationships into fuzzy rules. This solves the problem of traditional PID controllers' poor adaptability to nonlinear systems. For example, if the zero-bias error is large and rapidly increasing, the compensation strength is significantly increased.

[0065] Self-tuning refers to automatically optimizing the P, I, and D parameters of the PID to stably compensate for the zero bias according to the changing trend of the zero bias error.

[0066] Specifically, the centering control module generates a zero offset compensation signal based on two parameters, one is the zero offset of the pressure-flow curve, and the other is the rate of change of the zero offset.

[0067] The pressure-flow characteristic of a servo valve is its core performance curve, reflecting the relationship between valve output flow and valve core displacement at different pressures. When zero offset exists, this curve deviates from the ideal zero position. This manifests as a small flow rate when zero signal should indicate no flow. Zero offset, or the degree to which this curve deviates from the ideal state, can be considered the current offset.

[0068] The rate of change of zero bias refers to the speed at which the zero bias changes over time.

[0069] Offset alone is insufficient for accurate compensation. For example, if the same 0.02mm offset changes rapidly or slowly, different compensation strategies are required. Incorporating the trend of zero-bias error into the equation allows for predicting the development of the zero-bias error and enabling more timely and stable compensation adjustments.

[0070] Real-time compensation of the servo valve spool displacement increment refers to calculating the displacement of the spool to compensate for the zero bias error.

[0071] In some embodiments, the servo valve is a sliding valve, and the rotation of the motor drives the valve core to move through the transmission mechanism, and the movement amount of the valve core is related to the angle of the motor.

[0072] In other embodiments, the servo valve is a rotary valve, and the rotation of the motor directly drives the rotation of the valve core, and the angle of the valve core is related to the angle of the motor.

[0073] The servo valve controller is required to drive the valve spool's movement / rotation. This requires converting the displacement increment into a signal that the controller can interpret. The controller then drives the valve spool to the correct position based on this signal offset.

[0074] Furthermore, the test control component also includes a linearity adjustment module, which includes a curve distortion identification unit and a dynamic adjustment unit; the dynamic adjustment unit can obtain the static curve of the servo valve and obtain a correction linearity equation based on the static curve; the curve distortion identification unit decomposes the nonlinear harmonic components of the static curve through wavelet transform.

[0075] In some embodiments, as Figure 2 The curve shown in Figure 1 represents the relationship between the control signal (voltage / current) and flow rate. Ideally, the control signal and flow rate are positively correlated, resulting in a straight line. The linearity adjustment module identifies curve distortion and generates a correction linearity equation to convert the curve to a near-straight line.

[0076] Specifically, ideally, this curve should be a strictly straight line. However, in actual use, due to factors such as valve core wear, changes in valve port throttling characteristics, and nonlinear magnetic circuits, the curve may exhibit distortions such as bending and fluctuations.

[0077] The wavelet transform is a mathematical tool that can simultaneously analyze the time-frequency characteristics of a signal. It excels at decomposing local distortion or nonlinear components in a signal. For a static curve, the ideal linear portion can be seen as a low-frequency component, while the distorted portion can be seen as a nonlinear harmonic component, which is also a high-frequency or sudden change component.

[0078] The curve distortion identification unit decomposes the static curve into components of different frequencies through wavelet transform, thereby accurately extracting the nonlinear harmonic components that deviate from linearity and clarifying the position, amplitude and characteristics of the distortion.

[0079] The dynamic adjustment unit obtains the servo valve's static curve and constructs a linearity correction equation based on the static curve and the nonlinear components extracted by the curve distortion identification unit. Specifically, this unit uses mathematical models, such as polynomial fitting and piecewise linearization, to describe the deviation between the actual static curve and the ideal straight line, and then reversely generates a compensation formula.

[0080] Furthermore, the test control component also includes an intelligent control core, which is used to perform performance deviation identification, link flow meters and pressure gauges to perform servo valve calibration and verification testing.

[0081] In this embodiment, the calibration of the servo valve is to adjust the performance of the servo valve in a broad sense, and may specifically include the aforementioned centering control, linearity adjustment, or other operations to adjust the performance of the servo valve.

[0082] Furthermore, the intelligent control core includes a digital twin engine, which includes a digital model of the servo valve; the digital twin engine is used to perform correction simulation based on the digital model of the servo valve in a virtual environment before performing servo valve calibration, simulate the adjustment effect and optimize the parameters.

[0083] The digital twin engine is used to perform the following operations: Build a multi-physics model of the servo valve; Acquire test data from hydraulic test execution components and test control components to drive simulation; Output the optimal correction parameter combination to the physical system.

[0084] In this embodiment, Figure 3 As shown in the figure, the introduction of a digital twin engine in intelligent servo valve testing improves the efficiency and accuracy of the servo valve calibration process through a closed-loop logic of virtual simulation-optimization-physical execution. Acting as a bridge between the virtual and physical worlds, the digital twin engine enables an intelligent adjustment model that prioritizes virtual verification followed by physical execution.

[0085] Traditional physical calibration can be costly, requiring high trial-and-error costs and blind parameter adjustments. The digital twin engine, however, builds a virtual model that perfectly mirrors the physical servo valve. Before actually adjusting the physical device, it simulates the effects of various calibration solutions in a virtual environment, repeatedly optimizing parameters and ultimately applying the optimal solution verified virtually to the physical system. This reduces the risk of trial and error and improves calibration efficiency.

[0086] The servo valve multiphysics model is a coupling of multiple physical processes involved in the operation of the servo valve, including: 1. Mechanical field: mainly includes the mechanical changes when the valve core moves, such as the movement of the valve core and the friction between the valve core and the valve sleeve; 2. Hydraulic field: mainly includes the flow of fluid inside the servo valve, the pressure loss of the fluid, and the characteristics of the oil; 3. Electromagnetic field: mainly includes the electromagnetic force and magnetic circuit distribution of the motor / torque motor; 4. Temperature field: mainly includes the impact of oil temperature rise and thermal deformation of servo valve components on performance.

[0087] Building a multi-physics field model of a servo valve based on historical data requires a large amount of basic data support, such as: the design parameters of the servo valve, including valve core size and valve port shape; factory test data, including pressure-flow curves under different operating conditions; historical operating data, including performance degradation patterns after long-term use, etc. These historical data can make the virtual model closer to the real physical characteristics.

[0088] Test data from the hydraulic test actuator and control components includes servo valve performance data collected by the physical test system at the current moment, such as real-time control current, actual valve port pressure, output flow, valve core displacement, oil temperature, etc. This data reflects the current true state of the servo valve.

[0089] The digital twin engine is not a fixed virtual model, but a living model that is dynamically updated.

[0090] By importing real-time data, the virtual model adjusts its parameters in real time based on the current state of the physical system, ensuring synchronization between the virtual simulation and the physical system. For example, if real-time data indicates that rising oil temperature causes a decrease in oil viscosity, the virtual model will immediately update the viscosity parameters in the hydraulic field, ensuring that the simulation results accurately reflect the correction effect at the current oil temperature. This real-time data-driven approach elevates virtual simulation from offline to online, synchronous simulation, ensuring both timeliness and accuracy.

[0091] The optimal correction parameter combination refers to a set of adjustment parameters that, after virtual simulation optimization, can achieve the best performance for the servo valve. For example: the compensation current value for zero bias error, the correction coefficient for linear distortion, and the PID parameters for dynamic response.

[0092] In the virtual model, the digital twin engine simulates multiple possible correction parameter combinations. By comparing the simulation results, such as the corrected linearity error, response speed, and stability, it selects the best set of parameters and sends this set of parameters to the controller of the physical system for direct use in actual correction operations.

[0093] Furthermore, the correction parameter combination includes: a compensation current value for zero bias error, a correction coefficient for linearity distortion, and a PID parameter for dynamic response.

[0094] Furthermore, the test control component also includes a cloud-edge collaboration platform, which is used to connect the local test control component with the cloud database and can perform remote algorithm updates and big data analysis.

[0095] The cloud-edge collaborative platform includes a distributed learning unit and an elastic parameter library; The distributed learning unit can aggregate correction data from multiple test control components to train shared models; the flexible parameter library can call preset optimization parameter packages according to servo valve models or working conditions.

[0096] In this embodiment, the test control component refers to the hardware deployed at the test site, such as the servo valve controller, sensors, actuators, and local control software, which is responsible for real-time data collection and execution of correction operations, such as the centering control module and linearity adjustment module mentioned above.

[0097] A cloud database refers to a large database deployed on a remote server, which is used to centrally store the test data of all local components, such as servo valve models, operating parameters, correction effects, fault records, etc.

[0098] By connecting local and cloud systems, the platform breaks down the data silos of individual test devices, enabling cloud-optimized algorithms to be pushed to local components. This improves local control capabilities and the cloud's ability to mine patterns in massive data, feeding back test strategies and allowing distributed test systems to form a collaborative intelligent network.

[0099] The distributed learning unit can aggregate the correction data of multiple test control components, which refers to the correction data of a single local test component. For example, the zero bias compensation parameters and linearity correction results of a servo valve are affected by the model, working conditions, and individual differences of the equipment, and have limitations. The distributed learning unit can aggregate the correction data of multiple different test sites and different servo valve models to the cloud.

[0100] Training a shared model involves leveraging aggregated multi-source data in the cloud to retrain or optimize control models, such as the fuzzy PID algorithm model and linearity correction model mentioned above. Originally, a model for a single device was only applicable to a specific servo valve model. However, through multi-source data training, the shared model can adapt to a wider range of models and more complex operating conditions, significantly improving calibration accuracy and adaptability. The trained shared model is then pushed back to each local test component, enabling all devices to benefit from the optimized parameters derived from the collective data.

[0101] The Elastic Parameter Library is a collection of parameter packages stored in the cloud. It contains preset optimized parameters for different servo valve models and different test conditions, such as the zero compensation baseline value, PID initial parameters, and linearity correction coefficients mentioned above. When the local test component needs to test the same servo valve model under the same or similar operating conditions, it can directly call the preset parameter package for that model at the corresponding pressure from the Elastic Parameter Library, eliminating the need for re-debugging.

[0102] In some embodiments, as Figure 2 、 Figure 3 As shown, after the hydraulic pressure test of the servo valve is completed, the correction parameters are written into the controller inside the servo valve. When the servo valve operates independently, it can operate with the tested optimal parameters.

[0103] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the above-mentioned processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0104] The flow charts and block diagrams in the accompanying drawings of the present invention illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementation schemes, the functions marked in the box can also occur in a different order than those marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which is determined based on the functions involved. It should be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0105] The above description is merely an exemplary embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformation made by utilizing the contents of the present invention's description and drawings under the technical concept of the present invention, or directly / indirectly applied in other related technical fields, is included in the patent protection scope of the present invention.

[0106] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An intelligent hydraulic test system for a servo valve, characterized in that: Including hydraulic test execution components and test control components: The hydraulic test execution assembly includes a pressure source for providing hydraulic pressure, a test bench for connecting to a servo valve, a hydraulic channel for connecting the pressure source and the test bench, a flow meter for detecting a flow value, a pressure gauge for detecting a pressure value, and an execution controller connected to the servo valve and outputting a control signal to the servo valve; The test control component is connected to the pressure source and can configure the output pressure and output flow of the pressure source; the test control component is connected to the flow meter and the pressure gauge and can obtain the flow value and pressure value detected by the flow meter and the pressure gauge; the test control component is connected to the execution controller and is used to output the configuration signal; The test control component can automatically complete the hydraulic test of the servo valve according to preset instructions.

2. The intelligent hydraulic testing system for a servo valve according to claim 1, characterized in that: The test control assembly further includes a centering control module, which dynamically generates a valve core position compensation signal based on the zero bias error; The centering control module adopts a fuzzy PID self-tuning algorithm. The input of the fuzzy PID self-tuning algorithm is the zero offset and change rate of the pressure-flow curve; the output of the fuzzy PID self-tuning algorithm is the real-time compensation of the servo valve spool displacement increment and is converted into a signal offset of the execution controller through the servo valve spool displacement.

3. The intelligent hydraulic testing system for a servo valve according to claim 1, characterized in that: The test control component also includes a linearity adjustment module, which includes a curve distortion identification unit and a dynamic adjustment unit; the dynamic adjustment unit can obtain the static curve of the servo valve and obtain a correction linearity equation based on the static curve; the curve distortion identification unit decomposes the nonlinear harmonic components of the static curve through wavelet transform.

4. The intelligent hydraulic testing system for a servo valve according to claim 1, characterized in that: The test control component also includes an intelligent control core, which is used to perform performance deviation identification, link flow meters and pressure gauges to perform servo valve calibration and verification testing.

5. The intelligent hydraulic testing system for a servo valve according to claim 4, characterized in that: The intelligent control core includes a digital twin engine, which includes a digital model of the servo valve; the digital twin engine is used to perform correction simulation based on the digital model of the servo valve in a virtual environment before performing servo valve calibration, simulate the adjustment effect and optimize the parameters.

6. The intelligent hydraulic testing system for a servo valve according to claim 5, characterized in that: The digital twin engine is used to perform the following operations: Build a multi-physics model of the servo valve; Acquire test data from hydraulic test execution components and test control components to drive simulation; Output the optimal correction parameter combination to the physical system.

7. The intelligent hydraulic testing system for a servo valve according to claim 6, characterized in that: The correction parameter combination includes: a compensation current value for zero bias error, a correction coefficient for linearity distortion, and a PID parameter for dynamic response.

8. The intelligent hydraulic testing system for a servo valve according to claim 1, characterized in that: The test control component also includes a cloud-edge collaboration platform, which is used to connect the local test control component with the cloud database and can perform remote algorithm updates and big data analysis.

9. The intelligent hydraulic testing system for a servo valve according to claim 8, characterized in that: The cloud-edge collaborative platform includes a distributed learning unit and an elastic parameter library; The distributed learning unit can aggregate correction data from multiple test control components to train shared models; the flexible parameter library can call preset optimization parameter packages according to servo valve models or working conditions.

10. The intelligent hydraulic testing system for a servo valve according to claim 1, characterized in that: The intelligent hydraulic test system writes the correction parameters into the controller inside the servo valve. When the servo valve operates independently, it can operate with the tested optimal parameters.

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