Gate valve pressure balance control method and device, electronic equipment and storage medium

Abstract

The invention provides a gate valve pressure balance control method and device, electronic equipment and a storage medium, and relates to the technical field of gate valve pressure control. The method comprises the steps of monitoring a gate valve control signal and a pressure difference between two sides of a gate valve; calculating a gate valve control signal change rate according to the gate valve control signal, and setting a control signal amplitude threshold value and a change rate threshold value; according to the gate valve control signal change rate, the control signal amplitude threshold value and the change rate threshold value, the gate valve switching action is predicted; based on the predicted gate valve switching action, according to the pressure difference of the two sides of the gate valve, the number of balance channels needing to be opened when the pressure balance is achieved on the two sides of the gate valve is judged; the controller is controlled in advance to open the corresponding number of balance channels to balance the pressure on the two sides of the gate valve. According to the gate valve pressure balance control method, the problem that in the prior art, the response speed is insufficient in the aspect of gate valve pressure balance control is solved, and the effects of remarkably improving the pressure balance response speed and effectively restraining hydraulic impact and vibration are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of gate valve pressure control, and in particular to a gate valve pressure balance control method, device, electronic equipment and storage medium. Background Art

[0002] In the wave of modern industrial automation, industrial robots have become the key driving force for improving production efficiency and product quality. Hydraulic systems have played an important role in the field of industrial robot drive due to their excellent power density, fast response speed and precise control capabilities. In the hydraulic system of industrial robots, gate valves are the core reversing components, especially gate valves with multiple balancing channels inside (the balancing channels are used to make the pressure difference between the front and rear sides of the gate valve more evenly distributed, aiming to reduce the fluid resistance and pressure difference during opening and closing). They are widely used to control the movement of hydraulic cylinders, thereby realizing fast and precise movements of robot arms.

[0003] In order to meet the growing demand for work efficiency of industrial robots, the switching frequency of gate valves continues to rise, especially in operating scenarios that require frequent and rapid movements. Gate valves are often in high-frequency switching conditions. However, during the high-frequency switching process, the frequent and rapid movements of the gate valve will cause an instantaneous pressure difference on both sides of the valve inlet and outlet. This instantaneous pressure difference is the source of shock and vibration in the hydraulic system, which will not only significantly reduce the positioning accuracy and running stability of the robot, but in the long run, it will also accelerate the wear of hydraulic components, shorten the service life of the system, and may even cause potential safety hazards.

[0004] Although traditional hydraulic systems are also equipped with pressure balancing mechanisms to alleviate pressure differential shocks, the response speed of the pressure balancing mechanisms in the existing technology is relatively slow, making it difficult to effectively meet the application requirements of high-frequency switching of industrial robots. Therefore, how to significantly improve the response speed of the gate valve pressure balancing mechanism under high-frequency switching conditions while meeting the requirements of the industrial robot hydraulic system, so as to quickly balance the pressure on both sides of the valve, effectively suppress hydraulic shocks, and ensure the robot's motion performance, has become a core technical bottleneck that needs to be broken through in the field of industrial robot hydraulics. Summary of the invention

[0005] The purpose of the present invention is to provide a gate valve pressure balance control method, device, electronic equipment and storage medium, which solves the problem of insufficient response speed in the prior art for gate valve pressure balance control, and achieves the effect of significantly improving the pressure balance response speed and effectively suppressing hydraulic shock and vibration.

[0006] In a first aspect, the present invention provides a gate valve pressure balance control method for pressure balance control of a gate valve in a hydraulic system of an industrial robot, wherein a plurality of balance channels are arranged inside the gate valve, and all balance channels are controlled by a controller, comprising the following steps: S1. Monitor the gate valve control signal and the pressure difference on both sides of the gate valve; S2. Calculate the gate valve control signal change rate according to the gate valve control signal, and set the control signal amplitude threshold and change rate threshold; S3. predicting the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; S4. Based on the predicted gate valve switching action and the pressure difference on both sides of the gate valve, determine the number of balancing channels that need to be opened when the pressure on both sides of the gate valve is balanced; S5. According to the number of balancing channels, the controller is controlled in advance to open the corresponding number of balancing channels and establish a pressure balancing passage to balance the pressure on both sides of the gate valve.

[0007] The gate valve pressure balance control method provided by the present invention can significantly improve the pressure balance response speed, effectively suppress hydraulic shock and vibration, and ensure the positioning accuracy and operation stability of the industrial robot without significantly increasing the complexity and cost of the system.

[0008] Furthermore, the specific steps in step S2 include: S21. Monitor the noise of hydraulic system; S22. Adopting an adaptive filtering algorithm to filter the gate valve control signal; wherein the adaptive filtering algorithm dynamically adjusts the filtering parameters according to the monitored hydraulic system noise to reduce noise interference; S23. Calculate the gate valve control signal change rate based on the gate valve control signal after filtering, and set the control signal amplitude threshold and change rate threshold.

[0009] This helps ensure that the gate valve can still achieve fast and stable pressure balance control under high-frequency switching conditions, thereby ensuring the performance and reliability of the industrial robot hydraulic system.

[0010] Furthermore, the specific steps in step S22 include: S221. Analyze the noise frequency of the hydraulic system noise and determine whether the noise frequency overlaps with the gate valve control signal frequency; S222. If the frequencies overlap, perform the following steps: S2221. Decompose the gate valve control signal using wavelet transform to obtain multiple frequency band components; S2222. Adopt an adaptive notch filter to filter the frequency band components corresponding to the overlapping part of the gate valve control signal frequency and the noise frequency, and dynamically adjust the center frequency and bandwidth of the notch filter according to the monitored hydraulic system noise to reduce noise interference; S2223. Reconstruct the filtered frequency band component and the unfiltered frequency band component to obtain a filtered gate valve control signal; S223. If the frequencies do not overlap, the gate valve control signal is directly output.

[0011] It achieves effective noise filtering under the condition where the noise frequency and the control signal frequency overlap, improves the quality of the control signal, and ensures the accuracy and performance of the gate valve pressure balance control.

[0012] Furthermore, the specific steps in step S2222 include: A1. Monitor the convergence speed of the adaptive notch filter to determine whether the convergence speed is lower than a preset convergence speed threshold, and when the convergence speed is lower than the preset convergence speed threshold, adjust the step size factor of the adaptive notch filter according to the minimum mean square error algorithm to speed up the convergence speed.

[0013] The changes in noise frequency can be tracked faster, the filtering effect can be improved, and the accuracy of the gate valve switching action prediction can be improved.

[0014] Furthermore, the specific steps in step S2222 include: B1. Monitor the hydraulic oil temperature of the hydraulic system; B2. After establishing a mapping relationship between the hydraulic oil temperature and the hydraulic system noise frequency drift, determine the hydraulic system noise frequency drift according to the hydraulic oil temperature; B3. According to the frequency drift, dynamically adjust the center frequency and bandwidth of the adaptive notch filter to compensate for the noise frequency drift caused by oil temperature changes.

[0015] Furthermore, the specific steps in step A1 include: A1A1. Obtaining a first error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1A2. According to the minimum mean square error algorithm, the first step length adjustment coefficient is calculated based on the first error signal; the first step length adjustment coefficient is proportional to the amplitude of the first error signal, and the first step length adjustment coefficient is within a preset limit range; A1A3. According to the first step length adjustment coefficient, adjust the step length factor of the adaptive notch filter, and the adjusted step length factor is equal to the current step length factor plus the first step length adjustment coefficient.

[0016] Furthermore, the specific steps in step A1 include: A1B1. Calculate the second error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1B2. Determine whether the hydraulic system noise exhibits non-stationary characteristics, and if the hydraulic system noise exhibits non-stationary characteristics, dynamically set the upper and lower thresholds of the limit range according to the noise frequency change rate; otherwise, keep the preset limit range unchanged; wherein, the noise frequency change rate is negatively correlated with the upper threshold, and the noise frequency change rate is positively correlated with the lower threshold; A1B3. According to the minimum mean square error algorithm, a second step adjustment coefficient is calculated based on the second error signal; the second step adjustment coefficient is proportional to the amplitude of the second error signal, and the second step adjustment coefficient is within the limit range; A1B4. According to the second step size adjustment coefficient, adjust the step size factor of the adaptive notch filter, and the adjusted step size factor is equal to the current step size factor plus the second step size adjustment coefficient.

[0017] In a second aspect, the present invention provides a gate valve pressure balance control device, which is used for pressure balance control of a gate valve in a hydraulic system of an industrial robot. A plurality of balance channels are arranged inside the gate valve, and all balance channels are controlled by a controller, including: Monitoring module, used to monitor the gate valve control signal and the pressure difference on both sides of the gate valve; A calculation module, used for calculating the gate valve control signal change rate according to the gate valve control signal, and setting the control signal amplitude threshold and change rate threshold; A prediction module, used to predict the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; A judgment module is used to judge the number of balancing channels that need to be opened when the pressure on both sides of the gate valve is balanced based on the predicted gate valve switching action and the pressure difference on both sides of the gate valve; The control module is used to control the controller to open a corresponding number of balancing channels in advance according to the number of balancing channels, and to establish a pressure balancing passage to balance the pressure on both sides of the gate valve.

[0018] The gate valve pressure balance control device provided by the present invention can significantly improve the response speed of the gate valve pressure balance control, effectively solve the problem of response lag in traditional technology, reduce hydraulic shock, and improve the performance of the industrial robot hydraulic system under high-frequency switching conditions.

[0019] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the gate valve pressure balance control method provided in the first aspect are executed.

[0020] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in the gate valve pressure balance control method provided in the first aspect are executed.

[0021] From the above, it can be seen that the gate valve pressure balance control method provided by the present invention is based on an advance control strategy based on the prediction of the control signal change rate threshold, which breaks the lag of traditional pressure balance control and can achieve millisecond-level rapid pressure balance response under high-frequency switching conditions. Combined with the gate valve design with multiple balance channels, it greatly reduces the instantaneous pressure difference during gate valve switching, thereby significantly suppressing hydraulic shock and vibration, and improving the stability and reliability of the hydraulic system.

[0022] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A flow chart of a gate valve pressure balance control method provided in an embodiment of the present invention.

[0024] Figure 2 A schematic structural diagram of a gate valve pressure balance control device provided in an embodiment of the present invention.

[0025] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0026] Description of labels: 100, monitoring module; 200, calculation module; 300, prediction module; 400, judgment module; 500, control module; 13, electronic device; 1301, processor; 1302, memory; 1303, communication bus. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0028] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0029] Reference Figure 1 The present invention provides a gate valve pressure balance control method, which is used for the pressure balance control of the gate valve in the hydraulic system of an industrial robot. A plurality of balance channels are arranged inside the gate valve, and all the balance channels are controlled by a controller, comprising the following steps: S1. Monitor the gate valve control signal and the pressure difference on both sides of the gate valve; S2. Calculate the gate valve control signal change rate according to the gate valve control signal, and set the control signal amplitude threshold and change rate threshold; S3. predicting the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; S4. Based on the predicted gate valve switching action and the pressure difference on both sides of the gate valve, determine the number of balancing channels that need to be opened when the pressure on both sides of the gate valve is balanced; S5. According to the number of balancing channels, the controller is controlled in advance to open the corresponding number of balancing channels and establish a pressure balancing passage to balance the pressure on both sides of the gate valve.

[0030] In step S1, the gate valve control signal and the pressure difference on both sides of the gate valve are monitored by sensors. The pressure sensors are arranged on both sides of the gate valve inlet and outlet for real-time pressure difference detection; the gate valve control signal is obtained from the controller of the industrial robot hydraulic system, reflecting the control command of the gate valve.

[0031] In step S2, the calculation of the control signal change rate is performed by a data processing unit, such as a programmable logic controller or a microcontroller. The change rate threshold and the control signal amplitude threshold are pre-set parameters, which can be adjusted according to the specific working conditions of the hydraulic system and the gate valve characteristics.

[0032] In step S3, the prediction of the gate valve switching action is based on the set thresholds (i.e., the change rate threshold and the control signal amplitude threshold) and the calculated change rate. For example, when it is detected that the control signal change rate exceeds the change rate threshold and the control signal amplitude exceeds the amplitude threshold, the system predicts that the gate valve is about to switch.

[0033] In step S4, the number of balancing channels is determined based on the predicted gate valve switching action and combined with the measured pressure difference on both sides of the gate valve. A mapping relationship between the pressure difference and the number of balancing channels is established in advance, for example, through experiments or simulations. The greater the pressure difference, the more balancing channels need to be opened.

[0034] In step S5, the controller issues a control instruction in advance according to the number of balancing channels determined in step S4, and drives the balancing channel valves to open a corresponding number of balancing channels, thereby establishing a pressure balancing passage in advance before the gate valve performs a switching action, thereby achieving pre-balancing of the pressure on both sides of the gate valve.

[0035] The technical solution is to solve the technical problem that the gate valve in the hydraulic system of the industrial robot has insufficient pressure balance control response speed under high-frequency switching conditions, which easily leads to hydraulic shock.

[0036] By monitoring the gate valve control signal and the pressure difference on both sides of the gate valve in step S1, the system can grasp the working status and pressure distribution of the gate valve in real time, providing a data basis for subsequent pressure balance control.

[0037] Step S2 calculates the gate valve control signal change rate and sets a threshold value, the purpose is to accurately predict the gate valve switching timing. The control signal change rate can sensitively reflect the gate valve action trend, and the set threshold value is used as a criterion for predicting the switching action.

[0038] Step S3 predicts the gate valve switching action based on the change rate and the threshold value, thereby realizing the early prediction of the gate valve action. This prediction mechanism is the key to realizing the early pressure balance control.

[0039] After predicting the gate valve switching action, step S4 determines the number of balancing channels that need to be opened according to the pressure difference on both sides of the gate valve, thereby ensuring the accuracy and effectiveness of pressure balance control.

[0040] Step S5 controls the opening of the balancing channel in advance according to the determined number of balancing channels, and pre-establishes a pressure balancing channel before the gate valve actually operates. Thus, at the moment of gate valve switching, the pressure shock on both sides of the valve can be effectively reduced or eliminated, the vibration and noise of the hydraulic system can be reduced, and the stability and reliability of the system operation can be improved.

[0041] In summary, this technical solution significantly improves the response speed of gate valve pressure balance control through predictive control and advance action, effectively solves the problem of response lag in traditional technology, reduces hydraulic shock, and improves the performance of industrial robot hydraulic system under high-frequency switching conditions.

[0042] As an example, first, the pressure sensor is installed at the oil inlet and return port of the gate valve, and the control signal is read from the robot's motion controller. The controller sets the control signal amplitude threshold to 2V and the change rate threshold to 1V / ms. When the controller detects that the control signal amplitude exceeds 2V and the change rate exceeds 1V / ms, it predicts that the gate valve will switch after 5ms. At this time, the controller reads the pressure difference on both sides of the gate valve, for example, 3MPa. According to the preset mapping relationship between the pressure difference and the number of balancing channels, a pressure difference of 3MPa corresponds to the need to open two balancing channels. The controller immediately controls the balancing channel control valve of the gate valve to open the two balancing channels in advance. Before the actual switching action of the gate valve occurs, the balancing channel has been established, and the pressure on both sides of the gate valve tends to be balanced. In actual applications, after adopting this control method, the pressure shock during gate valve switching is reduced by about 60%, the vibration and noise of the hydraulic system are significantly reduced, and the positioning accuracy and running stability of the robot arm are improved.

[0043] In some embodiments, the specific steps in step S2 include: S21. Monitor the noise of hydraulic system; S22. Adopting an adaptive filtering algorithm to filter the gate valve control signal; wherein the adaptive filtering algorithm dynamically adjusts the filtering parameters according to the monitored hydraulic system noise to reduce noise interference; S23. Calculate the change rate of the gate valve control signal based on the gate valve control signal after filtering (it should be noted that the gate valve control signal is considered to have been filtered as long as it has been processed by the following steps S221-S223, even if the gate valve control signal has not been filtered by the adaptive filtering algorithm), and set the control signal amplitude threshold and change rate threshold.

[0044] In step S21, the monitoring of the hydraulic system noise may be achieved via a noise sensor arranged near the hydraulic system. The noise sensor may be, for example, an acoustic sensor for collecting noise signals generated during the operation of the hydraulic system.

[0045] In step S22, the adaptive filtering algorithm is used to process the gate valve control signal to reduce the interference of noise on the signal. As an implementation method, the adaptive filtering algorithm can use the minimum mean square error algorithm, which minimizes the mean square error between the output signal of the filter and the expected signal by continuously iteratively adjusting the filter parameters, thereby achieving noise filtering. The process of dynamically adjusting the filter parameters is that the adaptive filter will adjust its own filter parameters, such as the filter coefficient or the step size factor, in real time according to the noise signal characteristics monitored in step S21, such as the noise intensity or frequency. When the noise intensity is detected to increase, the adaptive filter can adjust the parameters to enhance the filtering effect; conversely, when the noise decreases, the parameters can be adjusted to avoid excessive filtering and signal distortion.

[0046] In step S23, after the adaptive filtering process, the noise component in the gate valve control signal is effectively suppressed. At this time, the gate valve control signal change rate is calculated based on the filtered control signal to obtain a more accurate change rate value. The control signal amplitude threshold and the change rate threshold are pre-set parameters, which are used as the basis for predicting the gate valve switching action in subsequent steps. The amplitude threshold can be set according to the normal working range of the gate valve control signal, and the change rate threshold can be set according to the dynamic response characteristics of the gate valve and the sensitivity of the system to the change of the control signal.

[0047] Specifically, in the hydraulic system of an industrial robot, when the gate valve control signal is disturbed by the noise of the hydraulic system, the directly calculated signal change rate may contain false changes caused by the noise component, which will reduce the accuracy of the subsequent gate valve switching action prediction and ultimately affect the accuracy of the pressure balance control. By first monitoring the hydraulic system noise and pre-processing the gate valve control signal based on the monitored noise information using an adaptive filtering algorithm, the noise interference can be effectively filtered out and the signal-to-noise ratio of the control signal can be improved. The gate valve control signal after filtering can more truly reflect the actual control state of the gate valve, and the gate valve control signal change rate calculated on this basis is also more accurate and reliable. With the accurate signal change rate, the subsequent gate valve switching action prediction and pressure balance control strategy can be executed more accurately, thereby improving the anti-interference ability and control accuracy of the entire gate valve pressure balance control method, ensuring that the gate valve can still achieve fast and stable pressure balance control under high-frequency switching conditions, thereby ensuring the performance and reliability of the industrial robot hydraulic system.

[0048] In some embodiments, the specific steps in step S22 include: S221. Analyze the noise frequency of the hydraulic system noise and determine whether the noise frequency overlaps with the gate valve control signal frequency; S222. If the frequencies overlap, perform the following steps: S2221. Decompose the gate valve control signal using wavelet transform to obtain multiple frequency band components; S2222. Adopt an adaptive notch filter to filter the frequency band components corresponding to the overlapping part of the gate valve control signal frequency and the noise frequency, and dynamically adjust the center frequency and bandwidth of the notch filter according to the monitored hydraulic system noise to reduce noise interference; S2223. Reconstruct the filtered frequency band component and the unfiltered frequency band component to obtain a filtered gate valve control signal; S223. If the frequencies do not overlap, the gate valve control signal is directly output.

[0049] In step S221, the noise frequency analysis can be implemented by using tools such as a spectrum analyzer or a fast Fourier transform to determine the main frequency components of the hydraulic system noise.

[0050] In step S2221, the wavelet transform specifically uses the db4 wavelet basis or the sym8 wavelet basis to perform a three-layer decomposition on the gate valve control signal, thereby obtaining multiple frequency band components such as an approximate component and a detail component.

[0051] In step S2222, the adaptive notch filter uses the minimum mean square error algorithm to adjust parameters, the initial value of the center frequency of the notch filter is set to the main frequency in the noise frequency analysis result, and the initial value of the bandwidth is set to the width of the noise frequency range. The process of dynamically adjusting the center frequency and bandwidth of the notch filter is specifically to monitor the change of the hydraulic system noise frequency in real time, and adjust the center frequency and bandwidth of the notch filter according to the change, so as to ensure that the notch filter can accurately track and filter out noise.

[0052] In step S2223, the reconstruction of the frequency band components is achieved by inverse wavelet transform, and the frequency band components processed by notch filtering and the unfiltered frequency band components are subjected to inverse wavelet transform, thereby obtaining a filtered gate valve control signal.

[0053] In step S223, if the noise frequency does not overlap with the gate valve control signal frequency, the gate valve control signal is directly processed, thereby avoiding unnecessary filtering operations and simplifying the control process.

[0054] Specifically, in order to solve the problem of the overlap between the noise frequency of the hydraulic system and the frequency of the gate valve control signal, this solution first analyzes the noise frequency of the hydraulic system to determine whether frequency overlap occurs. When the frequencies do not overlap, the original solution is used to directly calculate the control signal change rate and set the threshold. When the frequencies overlap, the control signal is decomposed into multiple frequency band components using wavelet transform. For the frequency band components with overlapping frequencies, an adaptive notch filter is used for precise filtering, and the center frequency and bandwidth of the notch filter are dynamically adjusted to adapt to noise changes. The filtered frequency band components are reconstructed with the unfiltered frequency band components to obtain the final filtered control signal, which is used for subsequent control signal change rate calculation and threshold setting. In this way, effective noise filtering is achieved under the condition where the noise frequency and the control signal frequency overlap, the control signal quality is improved, and the accuracy and performance of the gate valve pressure balance control are guaranteed.

[0055] In some specific implementations, the results of the hydraulic system noise frequency analysis show that the main frequency of the noise is concentrated around 100Hz, and there is an overlap with the gate valve control signal frequency. At this time, the control system first uses a spectrum analyzer to monitor the hydraulic system noise in real time and determines that the noise frequency range is 90Hz-110Hz. Then, the gate valve control signal is decomposed into three layers of wavelets using the db4 wavelet basis to obtain the detail component D3 containing the noise frequency. For the D3 component, an adaptive notch filter with an initial center frequency of 100Hz and an initial bandwidth of 20Hz is designed, and the minimum mean square error algorithm is used to dynamically adjust the filter parameters. After filtering the D3 component with an adaptive notch filter, the filtered D3 component and the unfiltered approximate component A3, detail components D1, and D2 are subjected to wavelet inverse transformation to reconstruct the filtered gate valve control signal. Finally, the control signal change rate calculation and threshold setting are performed based on the filtered gate valve control signal, and accurate gate valve pressure balance control under high noise conditions is achieved. By adopting the method of this embodiment, the hydraulic system noise overlapping with the control signal frequency can be effectively filtered out, the signal-to-noise ratio of the control signal can be improved, and the anti-interference ability and control accuracy of the gate valve pressure balance control system can be improved.

[0056] In some embodiments, the specific steps in step S2222 include: A1. Monitor the convergence speed of the adaptive notch filter to determine whether the convergence speed is lower than a preset convergence speed threshold, and when the convergence speed is lower than the preset convergence speed threshold, adjust the step size factor of the adaptive notch filter according to the minimum mean square error algorithm to speed up the convergence speed.

[0057] In order to solve the problem of slow convergence speed of adaptive notch filter, the convergence speed is monitored to provide a basis for the subsequent step factor adjustment. When the convergence speed is lower than the preset threshold, it is judged that the convergence speed is too slow and the step factor needs to be adjusted to speed up the convergence. Therefore, the step factor is adjusted through the minimum mean square error algorithm to achieve faster convergence. Specifically, the monitoring of convergence speed can be achieved in a variety of ways. For example, the error signal of the filter can be monitored. When the error signal does not decrease significantly within a period of time, it can be judged that the convergence speed has decreased. The preset convergence speed threshold can be set according to actual application requirements. For example, it can be set to the minimum decrease in the filter error signal per unit time. The minimum mean square error algorithm is a commonly used adaptive filtering algorithm. By continuously iteratively adjusting the filter parameters, the mean square error between the output signal of the filter and the expected signal is minimized. In this scheme, the minimum mean square error algorithm is used to adjust the step factor of the adaptive notch filter. The step factor determines the adjustment amplitude of the filter parameters for each iteration. The larger the step factor, the faster the convergence speed, but the stability may be reduced. The smaller the step factor, the slower the convergence speed, but the stability is higher. By dynamically adjusting the step factor using the minimum mean square error algorithm, a balance can be achieved between convergence speed and stability.

[0058] Specifically, in response to the problem that the hydraulic system noise in the hydraulic system of the industrial robot is time-varying, the convergence speed of the adaptive notch filter may slow down, resulting in untimely noise filtering, affecting the accuracy of the gate valve switching action prediction. To solve this problem, this scheme monitors the convergence speed of the adaptive notch filter and determines whether the convergence speed is lower than the preset convergence speed threshold. When the convergence speed is lower than the preset convergence speed threshold, the step size factor of the adaptive notch filter is adjusted according to the minimum mean square error algorithm to speed up the convergence speed. The minimum mean square error algorithm can dynamically adjust the step size factor according to the error signal, thereby speeding up the convergence speed. As a result, the changes in noise frequency can be tracked more quickly, the filtering effect can be improved, and the accuracy of the gate valve switching action prediction can be improved.

[0059] In some specific embodiments, the convergence speed monitoring can be performed by calculating the mean square value of the error signal between the output signal of the adaptive notch filter and the expected signal, and monitoring the change rate of the mean square value. When the change rate of the mean square value is lower than the preset threshold, it is determined that the convergence speed is lower than the preset convergence speed threshold. The preset convergence speed threshold can be set to a value dynamically adjusted according to the operating state of the hydraulic system. For example, in the startup phase of the hydraulic system, the noise changes greatly, and the preset convergence speed threshold can be set to a relatively high value to ensure that the filter can quickly track the noise change. In the stable operation phase of the hydraulic system, the noise changes less, and the preset convergence speed threshold can be set to a relatively low value to improve the filtering accuracy. When adjusting the step factor, the minimum mean square error algorithm can adaptively adjust the value and sign of the step factor according to the amplitude and direction of the error signal to ensure that the step factor can be adjusted in the direction of reducing the error signal, and the adjustment amplitude is proportional to the amplitude of the error signal. In this way, the dynamic adjustment of the convergence speed of the adaptive notch filter can be achieved, and the noise filtering effect and gate valve control accuracy can be improved.

[0060] In some embodiments, the specific steps in step S2222 include: B1. Monitor the hydraulic oil temperature of the hydraulic system; B2. After establishing a mapping relationship between the hydraulic oil temperature and the hydraulic system noise frequency drift, determine the hydraulic system noise frequency drift according to the hydraulic oil temperature; B3. According to the frequency drift, dynamically adjust the center frequency and bandwidth of the adaptive notch filter to compensate for the noise frequency drift caused by oil temperature changes.

[0061] In step B1, the monitoring of the hydraulic oil temperature can be achieved via a temperature sensor. The temperature sensor is arranged at a key position of the hydraulic system, such as a position close to a gate valve or a hydraulic oil tank, to collect temperature data of the hydraulic oil in real time.

[0062] In step B2, the mapping relationship between the hydraulic oil temperature and the noise frequency drift of the hydraulic system can be established through experimental data analysis or theoretical modeling. For example, under different oil temperature conditions, the noise frequency data of the hydraulic system is collected, the relationship between the oil temperature and the noise frequency drift is analyzed, and a mathematical model is fitted or a lookup table is established.

[0063] In step B3, the center frequency and bandwidth of the adaptive notch filter can be dynamically adjusted via a control algorithm. The control algorithm calculates the center frequency and bandwidth values ​​that need to be adjusted for the adaptive notch filter based on the frequency drift determined in step B2, and updates these values ​​to the filter parameters in real time, thereby achieving dynamic adaptive adjustment of the filter parameters.

[0064] Specifically, in order to solve the problem of noise frequency drift caused by oil temperature changes in the hydraulic system, this solution predicts the noise frequency drift by monitoring the hydraulic oil temperature and using the pre-established mapping relationship between oil temperature and noise frequency drift. As a result, the adaptive notch filter can dynamically adjust its center frequency and bandwidth according to the predicted frequency drift to compensate for the noise frequency drift caused by oil temperature changes. This frequency drift compensation mechanism based on oil temperature changes enables the adaptive notch filter to track and filter out noise more accurately, improving the performance of the filter and the noise suppression effect. Therefore, even in an environment where the oil temperature of the hydraulic system changes, this solution can ensure the effectiveness and stability of the filtering process and ensure the stable operation of the system.

[0065] In some specific embodiments, the temperature sensor can be a thermocouple temperature sensor, which is installed on the outer surface of the hydraulic valve body to monitor the hydraulic oil temperature in real time. The mapping relationship between the hydraulic oil temperature and the noise frequency drift of the hydraulic system is pre-calibrated as a quadratic polynomial function, and the parameters of the function are obtained by fitting experimental data. The control system reads the value of the temperature sensor every 10 milliseconds, calculates the noise frequency drift according to the quadratic polynomial function, and adjusts the center frequency and bandwidth of the adaptive notch filter in real time according to the drift. For example, when the oil temperature rises and causes the noise frequency to drift in the high-frequency direction, the control system controls the center frequency of the adaptive notch filter to also adjust in the high-frequency direction to ensure that the center frequency of the filter is always aligned with the noise frequency to achieve the best filtering effect.

[0066] In some embodiments, the specific steps in step A1 include: A1A1. Obtaining a first error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1A2. According to the minimum mean square error algorithm, the first step length adjustment coefficient is calculated based on the first error signal; the first step length adjustment coefficient is proportional to the amplitude of the first error signal, and the first step length adjustment coefficient is within a preset limit range; A1A3. According to the first step length adjustment coefficient, adjust the step length factor of the adaptive notch filter, and the adjusted step length factor is equal to the current step length factor plus the first step length adjustment coefficient.

[0067] Step A1A1 is configured to obtain a first error signal between the output signal of the adaptive notch filter at the current moment and the expected signal. The expected signal is defined as a frequency band component that has not been processed by the adaptive notch filter, which can be understood as an original noise signal. Thus, the first error signal can accurately reflect the current filtering effect of the adaptive notch filter.

[0068] In step A1A2, the first step length adjustment coefficient is calculated based on the minimum mean square error algorithm according to the first error signal, which ensures the correlation between the step length adjustment coefficient and the filtering error and realizes dynamic adjustment based on the error. At the same time, the first step length adjustment coefficient is limited within a preset limit range to avoid excessive adjustment of the step length factor and cause system instability.

[0069] In step A1A3, the step size factor is updated by adding the first step size adjustment coefficient to the current step size factor, which provides a specific implementation method for the dynamic adjustment of the step size factor of the adaptive notch filter.

[0070] Through the above steps, the step size factor of the adaptive notch filter can be dynamically adjusted according to the filtering error, thereby accelerating the convergence speed of the filter.

[0071] Specifically, the present scheme obtains the first error signal through step A1A1, and the first error signal represents the filtering effect of the current filter. The larger the error signal is, the worse the filtering effect is and the slower the convergence speed is. Then, in step A1A2, the first step length adjustment coefficient is calculated based on the first error signal using the minimum mean square error algorithm. The minimum mean square error algorithm ensures that the step length adjustment coefficient can be adjusted in the direction of reducing the error, thereby realizing the optimization adjustment of the step length factor. The first step length adjustment coefficient is proportional to the amplitude of the first error signal, ensuring that the larger the error is, the larger the step length adjustment amplitude is, thereby accelerating the convergence speed. At the same time, the first step length adjustment coefficient is limited within a preset limit range, avoiding system divergence or instability caused by excessive step length adjustment. Finally, in step A1A3, the step length factor is updated by adding the calculated first step length adjustment coefficient to the current step length factor. As a result, the step length factor of the adaptive notch filter can be dynamically adjusted according to the filtering error, thereby realizing a faster convergence speed and improving the filtering efficiency.

[0072] In some embodiments, the specific steps in step A1 include: A1B1. Calculate the second error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1B2. Determine whether the hydraulic system noise exhibits non-stationary characteristics, and if the hydraulic system noise exhibits non-stationary characteristics, dynamically set the upper and lower thresholds of the limit range according to the noise frequency change rate; otherwise, keep the preset limit range unchanged; wherein, the noise frequency change rate is negatively correlated with the upper threshold, and the noise frequency change rate is positively correlated with the lower threshold; A1B3. According to the minimum mean square error algorithm, the second step adjustment coefficient is calculated based on the second error signal; the second step adjustment coefficient is proportional to the amplitude of the second error signal, and the second step adjustment coefficient is within the limit range; A1B4. According to the second step size adjustment coefficient, adjust the step size factor of the adaptive notch filter, and the adjusted step size factor is equal to the current step size factor plus the second step size adjustment coefficient.

[0073] In step A1B1, the second error signal is calculated by subtracting the output signal of the adaptive notch filter at the current moment from the expected signal, wherein the expected signal refers to the frequency band component that has not been processed by the adaptive notch filter and represents the ideal signal state. Thus, the second error signal can accurately reflect the filtering effect of the adaptive notch filter and the degree of deviation from the ideal signal.

[0074] Step A1B2 is a key step for dynamically adjusting the limit range. The judgment of the non-stationary characteristics of the hydraulic system noise can be achieved by monitoring the changes in the spectral characteristics or statistical characteristics of the noise signal over time. For example, a noise frequency change rate threshold can be set. When the monitored noise frequency change rate exceeds the threshold, it is determined that the noise presents a non-stationary characteristic. When the noise presents a non-stationary characteristic, the dynamic setting of the limit range is performed. The upper and lower thresholds are dynamically set according to the noise frequency change rate. The noise frequency change rate is negatively correlated with the upper threshold, and the noise frequency change rate is positively correlated with the lower threshold. This means that when the noise frequency changes faster, the upper threshold decreases, the lower threshold increases, and the limit range narrows, and vice versa. The dynamic adjustment of the limit range makes the adjustment of the step factor more refined and adaptive to adapt to the characteristics of non-stationary noise.

[0075] In step A1B3, the second step adjustment coefficient is calculated based on the minimum mean square error algorithm and the second error signal, ensuring that the adjustment direction of the step factor is in the direction of reducing the error. The second step adjustment coefficient is proportional to the amplitude of the second error signal, which means that the larger the error, the larger the step adjustment amplitude, and vice versa, which accelerates the convergence process. At the same time, the second step adjustment coefficient is limited to the limit range dynamically set in step A1B2, ensuring the stability of the adjustment process and avoiding excessive step adjustment of the step factor leading to system divergence.

[0076] Step A1B4 describes the updating method of the step size factor. The adjusted step size factor is obtained by adding the current step size factor to the second step size adjustment coefficient, thus realizing iterative updating of the step size factor, so that the adaptive notch filter can continuously adjust its own parameters to adapt to noise changes.

[0077] Specifically, during the operation of the hydraulic system, the monitoring module monitors the noise of the hydraulic system in real time, and the calculation module analyzes the noise signal to determine whether the noise presents non-stationary characteristics and calculates the noise frequency change rate. When the noise is determined to be non-stationary, the calculation module dynamically adjusts the preset step factor limit range according to the noise frequency change rate. The specific adjustment strategy is: when the noise frequency change rate increases, the limit range is reduced, otherwise the limit range is expanded or remains unchanged. The prediction module receives the filtered gate valve control signal for subsequent gate valve switching action prediction. The judgment module and the control module work together to control the opening of the balance channel according to the predicted gate valve switching action and the pressure difference on both sides of the gate valve to achieve gate valve pressure balance control. In the adaptive filtering link, when the noise presents non-stationary characteristics, step A1B2 is triggered to dynamically set the limit range. For example, assuming that the preset limit range is [−0.1, 0.1], when the noise frequency change rate increases to a certain extent, the limit range may be adjusted to [−0.05, 0.05], and the adjustment range of the step factor is reduced, so that the filter can track the changing noise frequency more stably. On the contrary, when the noise frequency change rate decreases, the limit range can be appropriately expanded to speed up the convergence speed. In step A1B3, the minimum mean square error algorithm is used to calculate the second step adjustment coefficient. For example, the step adjustment coefficient can be set to the product of the second error signal and a proportional coefficient and limited to the dynamic limit range. In step A1B4, the step factor is iteratively updated according to the calculated second step adjustment coefficient to complete the parameter adjustment process of the adaptive notch filter. Therefore, by dynamically adjusting the step factor limit range, the adaptive notch filter can better adapt to the non-stationary noise environment, improve the filtering performance, and ensure the accuracy and stability of the gate valve pressure balance control.

[0078] In some specific embodiments, the determination of the non-stationary characteristics of the hydraulic system noise is achieved by analyzing the spectral change rate of the noise signal. Specifically, the fast Fourier transform is used to analyze the spectrum of the noise signal in real time, and the spectral change rate is obtained by calculating the spectral difference measure between two adjacent spectra. The spectral difference measure can adopt methods such as spectral energy difference and spectral correlation coefficient. When the spectral change rate exceeds a preset threshold, the system determines that the noise exhibits non-stationary characteristics. The dynamic adjustment strategy of the limit range can be preset as a piecewise function. For example, when the noise frequency change rate is in a low speed range, the limit range is set to [−0.1, 0.1]; when the noise frequency change rate is in a medium speed range, the limit range is set to [−0.05, 0.05]; when the noise frequency change rate is in a high speed range, the limit range is set to [−0.02, 0.02]. The initial value of the step size factor can be set to a small positive number, such as 0.01. In the minimum mean square error algorithm, the proportional coefficient can be determined according to the actual system noise characteristics and the expected convergence speed. Through the above specific implementation, when the hydraulic system noise presents non-stationary characteristics, the adaptive notch filter can dynamically adjust the step factor limit range to effectively suppress the non-stationary noise and improve the performance of the gate valve pressure balance control system.

[0079] In some embodiments, the specific steps in step A1 include: A1C1. Calculate the third error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1C2. Determine whether the hydraulic system noise presents a sudden change (it should be noted that the non-stationary characteristics of the system noise include the sudden change of the hydraulic system noise), and when the hydraulic system noise presents a sudden change, set the upper and lower thresholds of the limit range according to the amplitude of the sudden change; otherwise, keep the preset limit range unchanged; wherein, the amplitude of the sudden change is negatively correlated with the upper threshold, and the amplitude of the sudden change is positively correlated with the lower threshold; A1C3. According to the minimum mean square error algorithm, a third step adjustment coefficient is calculated based on the third error signal; the third step adjustment coefficient is proportional to the amplitude of the third error signal, and the third step adjustment coefficient is within the limit range; A1C4. According to the third step adjustment coefficient, adjust the step factor of the adaptive notch filter, and the adjusted step factor is equal to the current step factor plus the third step adjustment coefficient.

[0080] In step A1C1, the third error signal is calculated by subtracting the output signal of the adaptive notch filter from the desired signal. The desired signal is the frequency band component that has not been processed by the adaptive notch filter, representing the original, noisy signal component. The output signal of the adaptive notch filter is the signal processed by the filter, and ideally, it should remove the noise component as much as possible. The difference between the two, i.e., the third error signal, reflects the current filtering effect of the filter and the direction and amplitude that need to be further adjusted.

[0081] In step A1C2, it is judged whether the hydraulic system noise presents a sudden change. The sudden change can be understood as a sharp fluctuation in the amplitude or frequency of the noise signal in a short period of time. The judgment method can adopt the method of setting a threshold, such as monitoring the energy or amplitude change rate of the noise signal. When it exceeds the preset threshold, it is judged that a sudden change has occurred. After it is judged as a sudden change, the limit range is dynamically adjusted. The limit range is used to constrain the value range of the step adjustment coefficient, and the setting of the upper and lower thresholds is associated with the amplitude of the sudden change. The larger the amplitude of the sudden change, the smaller the upper threshold is set, and the larger the lower threshold is set, thereby expanding the limit range. This dynamic adjustment makes the adjustment of the step factor more flexible and can quickly adapt to sudden changes in noise.

[0082] In step A1C3, the minimum mean square error algorithm is used to calculate the third step adjustment coefficient. The algorithm aims to minimize the mean square value of the error signal, and by iteratively adjusting the step factor, the output signal of the filter gradually approaches the pure signal component in the desired signal. The third step adjustment coefficient is proportional to the amplitude of the third error signal. The larger the error signal, the larger the adjustment coefficient, but the value of the adjustment coefficient is limited to the limit range dynamically set in step A1C2.

[0083] In steps A1C4, the step factor is updated by adding the third step adjustment coefficient to the current step factor. The step factor is a key parameter in the adaptive filter, which controls the amplitude of each iterative adjustment of the filter parameters. Through the above steps, the step factor can be adaptively adjusted according to the sudden changes in the hydraulic system noise, thereby optimizing the performance of the filter.

[0084] Specifically, during the operation of the hydraulic system, the noise monitoring module continuously monitors the noise signal of the hydraulic system. When a sudden change in the noise signal is detected, for example, the noise amplitude suddenly increases in a very short time, the control system determines that the noise of the hydraulic system presents a sudden change. At this time, according to the amplitude of the sudden change, the limit range of the step adjustment coefficient of the adaptive notch filter is dynamically adjusted. For example, if the amplitude of the sudden noise is large, the limit range is expanded to allow the step adjustment coefficient to change within a larger range. Subsequently, based on the third error signal and the minimum mean square error algorithm, the third step adjustment coefficient is calculated, and the adjustment coefficient is constrained by the dynamic limit range. Finally, according to the calculated third step adjustment coefficient, the step factor of the adaptive notch filter is adjusted. The adjusted step factor is used for the next iteration of the filter, so that the filter can adapt to the sudden noise faster and effectively suppress noise interference. On the contrary, if the noise of the hydraulic system does not present a sudden change, the preset limit range is maintained unchanged, and the adjustment of the step factor is performed within the original limit range.

[0085] In some specific embodiments, when the hydraulic system operates normally, the preset step adjustment coefficient limit range is [-0.01, 0.01]. When the noise monitoring module detects that the hydraulic system noise has a sudden change, and the amplitude of the sudden change exceeds the preset threshold, for example, the noise amplitude increases by 5 decibels within 1 millisecond, the system determines it as a sudden change. At this time, the limit range is dynamically adjusted according to the amplitude of the sudden change. If the amplitude of the sudden change is large, for example, 5 decibels, the limit range is expanded to [-0.05, 0.05]. The expansion of the limit range is achieved by adjusting the upper and lower thresholds, for example, the upper threshold is adjusted from 0.01 to 0.05, and the lower threshold is adjusted from -0.01 to -0.05. The adjusted limit range is used to constrain the calculation of the subsequent step adjustment coefficient, so that the step factor can be adjusted within a larger range, thereby accelerating the convergence speed of the adaptive notch filter and quickly adapting to sudden noise. In this way, even when there are sudden changes in the hydraulic system noise, the adaptive notch filter can still maintain fast response and effective filtering performance, ensuring the stable operation of the hydraulic system.

[0086] In some embodiments, the specific steps in step S4 include: S41. After establishing a mapping relationship between the gate valve switching speed and the number of balancing channel openings, determining the number of balancing channel openings required to achieve pressure balance at different gate valve switching speeds, and dividing the gate valve switching speed into multiple speed intervals, each speed interval corresponds to a number of balancing channel openings, based on the predicted gate valve switching action, determine the number of balancing channel openings corresponding to the speed interval in which the predicted gate valve switching speed is located according to the mapping relationship.

[0087] The key feature of this embodiment is to establish a mapping relationship between the gate valve switching speed and the number of balancing channels opened. This mapping relationship is established by determining the number of balancing channels required to achieve pressure balance at different gate valve switching speeds. The gate valve switching speed is divided into multiple speed intervals, each interval is associated with a specific number of balancing channels opened. In actual operation, based on the predicted gate valve switching action and the speed interval in which the predicted switching speed is located, the system can directly determine the corresponding number of balancing channels opened from the pre-established mapping relationship.

[0088] Specifically, in the prior art, the determination of the number of pressure balance channels usually relies on the real-time detection and feedback of the pressure difference. This method has a delayed response under fast switching conditions and is difficult to meet the needs. To solve this problem, this solution proposes to pre-calibrate the corresponding relationship between the gate valve switching speed and the number of balance channels. In specific implementation, experiments or simulations can be first performed to obtain the number of balance channels required to achieve a pressure balance state at different gate valve switching speeds. For example, multiple different gate valve switching speeds can be set, and the number of balance channels opened can be gradually adjusted until the pressure on both sides of the gate valve is balanced, and the number of balance channels corresponding to each speed is recorded. Thus, a mapping relationship table or function between the gate valve switching speed and the number of balance channels opened is established. Further, in order to simplify the control, the gate valve switching speed can be divided into several intervals, such as a low speed interval, a medium speed interval, and a high speed interval, and each interval corresponds to a preferred number of balance channels opened. In the actual control process, after predicting the switching action of the gate valve, the speed interval in which it is located is determined according to the predicted gate valve switching speed, and then the mapping relationship is directly consulted to obtain the number of balance channels opened corresponding to the speed interval, and the controller is controlled to open the corresponding number of balance channels in advance. This pre-calibration method avoids the delay in real-time detection of pressure difference and calculation adjustment, and improves the response speed of pressure balance control.

[0089] In some specific embodiments, the gate valve switching speed is divided into three intervals: the low speed interval is 0 to 10 Hz, the medium speed interval is 10 to 30 Hz, and the high speed interval is 30 to 50 Hz. Through experimental calibration, the low speed interval corresponds to the opening of one balancing channel, the medium speed interval corresponds to the opening of two balancing channels, and the high speed interval corresponds to the opening of three balancing channels. When the control system predicts that the gate valve is about to switch and the predicted switching speed is 25 Hz, it determines that it is in the medium speed interval, and then consults the mapping relationship table to determine that two balancing channels need to be opened. The controller controls the gate valve to open two balancing channels in advance and establish a pressure balance passage. As a result, the pressure has been initially balanced before the gate valve is officially switched, effectively reducing the hydraulic shock. Using this method, the response speed of the pressure balance control is significantly improved, which can better meet the application requirements of high-frequency switching of the hydraulic system of the industrial robot.

[0090] Please refer to Figure 2, Figure 2 A gate valve pressure balance control device in some embodiments of the present invention is used for pressure balance control of a gate valve in a hydraulic system of an industrial robot. A plurality of balance channels are arranged inside the gate valve, and all balance channels are controlled by a controller. The gate valve pressure balance control device is integrated in a back-end control device in the form of a computer program, and includes: Monitoring module 100, used to monitor the gate valve control signal and the pressure difference between the two sides of the gate valve; The calculation module 200 is used to calculate the gate valve control signal change rate according to the gate valve control signal, and set the control signal amplitude threshold and the change rate threshold; A prediction module 300, for predicting the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; The judgment module 400 is used to judge the number of balance channels that need to be opened when the pressure on both sides of the gate valve is balanced based on the predicted gate valve switching action and the pressure difference on both sides of the gate valve; The control module 500 is used to control the controller to open a corresponding number of balancing channels in advance according to the number of balancing channels, and to establish a pressure balancing passage so as to balance the pressure on both sides of the gate valve.

[0091] In some embodiments, the calculation module 200 is used to calculate the gate valve control signal change rate according to the gate valve control signal and set the control signal amplitude threshold and the change rate threshold when executing: S21. Monitor the noise of hydraulic system; S22. Adopting an adaptive filtering algorithm to filter the gate valve control signal; wherein the adaptive filtering algorithm dynamically adjusts the filtering parameters according to the monitored hydraulic system noise to reduce noise interference; S23. Calculate the gate valve control signal change rate based on the gate valve control signal after filtering, and set the control signal amplitude threshold and change rate threshold.

[0092] In some embodiments, the calculation module 200 performs the following when filtering the gate valve control signal using the adaptive filtering algorithm: S221. Analyze the noise frequency of the hydraulic system noise and determine whether the noise frequency overlaps with the gate valve control signal frequency; S222. If the frequencies overlap, perform the following steps: S2221. Decompose the gate valve control signal using wavelet transform to obtain multiple frequency band components; S2222. Adopt an adaptive notch filter to filter the frequency band components corresponding to the overlapping part of the gate valve control signal frequency and the noise frequency, and dynamically adjust the center frequency and bandwidth of the notch filter according to the monitored hydraulic system noise to reduce noise interference; S2223. Reconstruct the filtered frequency band component and the unfiltered frequency band component to obtain a filtered gate valve control signal; S223. If the frequencies do not overlap, the gate valve control signal is directly output.

[0093] In some embodiments, the calculation module 200 performs filtering processing using an adaptive notch filter for a frequency band component corresponding to an overlapping portion of the gate valve control signal frequency and the noise frequency and dynamically adjusts the center frequency and bandwidth of the notch filter according to the monitored hydraulic system noise to reduce noise interference: A1. Monitor the convergence speed of the adaptive notch filter to determine whether the convergence speed is lower than a preset convergence speed threshold, and when the convergence speed is lower than the preset convergence speed threshold, adjust the step size factor of the adaptive notch filter according to the minimum mean square error algorithm to speed up the convergence speed.

[0094] In some embodiments, the calculation module 200 performs filtering processing using an adaptive notch filter for a frequency band component corresponding to an overlapping portion of the gate valve control signal frequency and the noise frequency and dynamically adjusts the center frequency and bandwidth of the notch filter according to the monitored hydraulic system noise to reduce noise interference: B1. Monitor the hydraulic oil temperature of the hydraulic system; B2. After establishing a mapping relationship between the hydraulic oil temperature and the hydraulic system noise frequency drift, determine the hydraulic system noise frequency drift according to the hydraulic oil temperature; B3. According to the frequency drift, dynamically adjust the center frequency and bandwidth of the adaptive notch filter to compensate for the noise frequency drift caused by oil temperature changes.

[0095] In some embodiments, the calculation module 200 is used to monitor the convergence speed of the adaptive notch filter, determine whether the convergence speed is lower than a preset convergence speed threshold, and when the convergence speed is lower than the preset convergence speed threshold, adjust the step size factor of the adaptive notch filter according to the minimum mean square error algorithm to speed up the convergence speed when executing: A1A1. Obtaining a first error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1A2. According to the minimum mean square error algorithm, the first step length adjustment coefficient is calculated based on the first error signal; the first step length adjustment coefficient is proportional to the amplitude of the first error signal, and the first step length adjustment coefficient is within a preset limit range; A1A3. According to the first step length adjustment coefficient, adjust the step length factor of the adaptive notch filter, and the adjusted step length factor is equal to the current step length factor plus the first step length adjustment coefficient.

[0096] In some embodiments, the calculation module 200 is used to monitor the convergence speed of the adaptive notch filter, determine whether the convergence speed is lower than a preset convergence speed threshold, and when the convergence speed is lower than the preset convergence speed threshold, adjust the step size factor of the adaptive notch filter according to the minimum mean square error algorithm to speed up the convergence speed when executing: A1B1. Calculate the second error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1B2. Determine whether the hydraulic system noise exhibits non-stationary characteristics, and if the hydraulic system noise exhibits non-stationary characteristics, dynamically set the upper and lower thresholds of the limit range according to the noise frequency change rate; otherwise, keep the preset limit range unchanged; wherein, the noise frequency change rate is negatively correlated with the upper threshold, and the noise frequency change rate is positively correlated with the lower threshold; A1B3. According to the minimum mean square error algorithm, the second step adjustment coefficient is calculated based on the second error signal; the second step adjustment coefficient is proportional to the amplitude of the second error signal, and the second step adjustment coefficient is within the limit range; A1B4. According to the second step size adjustment coefficient, adjust the step size factor of the adaptive notch filter, and the adjusted step size factor is equal to the current step size factor plus the second step size adjustment coefficient.

[0097] In some embodiments, the calculation module 200 is used to monitor the convergence speed of the adaptive notch filter, determine whether the convergence speed is lower than a preset convergence speed threshold, and when the convergence speed is lower than the preset convergence speed threshold, adjust the step size factor of the adaptive notch filter according to the minimum mean square error algorithm to speed up the convergence speed when executing: A1C1. Calculate the third error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1C2. Determine whether the hydraulic system noise presents a sudden change, and when the hydraulic system noise presents a sudden change, set the upper and lower thresholds of the limit range according to the amplitude of the sudden change; otherwise, keep the preset limit range unchanged; wherein, the amplitude of the sudden change is negatively correlated with the upper threshold, and the amplitude of the sudden change is positively correlated with the lower threshold; A1C3. According to the minimum mean square error algorithm, a third step adjustment coefficient is calculated based on the third error signal; the third step adjustment coefficient is proportional to the amplitude of the third error signal, and the third step adjustment coefficient is within the limit range; A1C4. According to the third step adjustment coefficient, adjust the step factor of the adaptive notch filter, and the adjusted step factor is equal to the current step factor plus the third step adjustment coefficient.

[0098] In some embodiments, the determination module 400 is used to determine the number of balancing channels that need to be opened when the pressure on both sides of the gate valve is balanced based on the predicted gate valve switching action and the pressure difference on both sides of the gate valve, when performing the following operations: S41. After establishing a mapping relationship between the gate valve switching speed and the number of balancing channel openings, determining the number of balancing channel openings required to achieve pressure balance at different gate valve switching speeds, and dividing the gate valve switching speed into multiple speed intervals, each speed interval corresponds to a number of balancing channel openings, based on the predicted gate valve switching action, determine the number of balancing channel openings corresponding to the speed interval in which the predicted gate valve switching speed is located according to the mapping relationship.

[0099] Please refer to Figure 3 , Figure 3 The present invention provides a structural schematic diagram of an electronic device provided by an embodiment of the present invention. The present invention provides an electronic device 13, including: a processor 1301 and a memory 1302. The processor 1301 and the memory 1302 are interconnected and communicate with each other through a communication bus 1303 and / or other forms of connection mechanisms (not shown). The memory 1302 stores computer-readable instructions executable by the processor 1301. When the electronic device is running, the processor 1301 executes the computer-readable instructions to execute the gate valve pressure balance control method in any optional implementation of the above embodiment to achieve the following functions: monitoring the gate valve control signal and the pressure difference on both sides of the gate valve; calculating the gate valve control signal change rate according to the gate valve control signal, and setting the control signal amplitude threshold and the change rate threshold; predicting the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; based on the predicted gate valve switching action, judging the number of balance channels required to be opened when the pressure on both sides of the gate valve is balanced according to the pressure difference on both sides of the gate valve; and controlling the controller to open a corresponding number of balance channels in advance according to the number of balance channels to establish a pressure balance path so that the pressure on both sides of the gate valve is balanced.

[0100] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the gate valve pressure balance control method in any optional implementation of the above-mentioned embodiment is executed to achieve the following functions: monitoring the gate valve control signal and the pressure difference on both sides of the gate valve; calculating the gate valve control signal change rate according to the gate valve control signal, and setting the control signal amplitude threshold and the change rate threshold; predicting the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; based on the predicted gate valve switching action, judging the number of balancing channels that need to be opened when the pressure balance is reached on both sides of the gate valve according to the pressure difference on both sides of the gate valve; and controlling the controller to open a corresponding number of balancing channels in advance according to the number of balancing channels to establish a pressure balancing passage so as to balance the pressure on both sides of the gate valve.

[0101] Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0102] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0103] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0104] Furthermore, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0105] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0106] The above description is only an embodiment of the present invention and is not intended to limit the protection scope of the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A gate valve pressure balance control method is used for the pressure balance control of the gate valve in the hydraulic system of an industrial robot. A plurality of balance channels are arranged inside the gate valve, and all balance channels are controlled by a controller. The method is characterized in that: The following steps are involved: S1. Monitor the gate valve control signal and the pressure difference on both sides of the gate valve; S2. Calculate the gate valve control signal change rate according to the gate valve control signal, and set the control signal amplitude threshold and change rate threshold; S3. predicting the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; S4. Based on the predicted gate valve switching action and the pressure difference on both sides of the gate valve, determine the number of balancing channels that need to be opened when the pressure on both sides of the gate valve is balanced; S5. According to the number of balancing channels, the controller is controlled in advance to open the corresponding number of balancing channels and establish a pressure balancing passage to balance the pressure on both sides of the gate valve.

2. The gate valve pressure balance control method according to claim 1, characterized in that: The specific steps in step S2 include: S21. Monitor the noise of hydraulic system; S22. Adopting an adaptive filtering algorithm to filter the gate valve control signal; wherein the adaptive filtering algorithm dynamically adjusts the filtering parameters according to the monitored hydraulic system noise to reduce noise interference; S23. Calculate the gate valve control signal change rate based on the gate valve control signal after filtering, and set the control signal amplitude threshold and change rate threshold.

3. The gate valve pressure balance control method according to claim 2, characterized in that: The specific steps in step S22 include: S221. Analyze the noise frequency of the hydraulic system noise and determine whether the noise frequency overlaps with the gate valve control signal frequency; S222. If the frequencies overlap, perform the following steps: S2221. Decompose the gate valve control signal using wavelet transform to obtain multiple frequency band components; S2222. Adopt an adaptive notch filter to filter the frequency band components corresponding to the overlapping part of the gate valve control signal frequency and the noise frequency, and dynamically adjust the center frequency and bandwidth of the notch filter according to the monitored hydraulic system noise to reduce noise interference; S2223. Reconstruct the filtered frequency band component and the unfiltered frequency band component to obtain a filtered gate valve control signal; S223. If the frequencies do not overlap, the gate valve control signal is directly output.

4. The gate valve pressure balance control method according to claim 3, characterized in that: The specific steps in step S2222 include: A1. Monitor the convergence speed of the adaptive notch filter to determine whether the convergence speed is lower than a preset convergence speed threshold, and when the convergence speed is lower than the preset convergence speed threshold, adjust the step size factor of the adaptive notch filter according to the minimum mean square error algorithm to speed up the convergence speed.

5. The gate valve pressure balance control method according to claim 3, characterized in that: The specific steps in step S2222 include: B1. Monitor the hydraulic oil temperature of the hydraulic system; B2. After establishing a mapping relationship between the hydraulic oil temperature and the hydraulic system noise frequency drift, determine the hydraulic system noise frequency drift according to the hydraulic oil temperature; B3. According to the frequency drift, dynamically adjust the center frequency and bandwidth of the adaptive notch filter to compensate for the noise frequency drift caused by oil temperature changes.

6. The gate valve pressure balance control method according to claim 4, characterized in that: The specific steps in step A1 include: A1A1. Obtaining a first error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1A2. According to the minimum mean square error algorithm, the first step length adjustment coefficient is calculated based on the first error signal; the first step length adjustment coefficient is proportional to the amplitude of the first error signal, and the first step length adjustment coefficient is within a preset limit range; A1A3. According to the first step length adjustment coefficient, adjust the step length factor of the adaptive notch filter, and the adjusted step length factor is equal to the current step length factor plus the first step length adjustment coefficient.

7. The gate valve pressure balance control method according to claim 4, characterized in that: The specific steps in step A1 include: A1B1. Calculate the second error signal between the output signal of the adaptive notch filter and the desired signal at the current moment; wherein the desired signal is a frequency band component that has not been processed by the adaptive notch filter; A1B2. Determine whether the hydraulic system noise exhibits non-stationary characteristics, and if the hydraulic system noise exhibits non-stationary characteristics, dynamically set the upper and lower thresholds of the limit range according to the noise frequency change rate; otherwise, keep the preset limit range unchanged; wherein, the noise frequency change rate is negatively correlated with the upper threshold, and the noise frequency change rate is positively correlated with the lower threshold; A1B3. According to the minimum mean square error algorithm, a second step adjustment coefficient is calculated based on the second error signal; the second step adjustment coefficient is proportional to the amplitude of the second error signal, and the second step adjustment coefficient is within the limit range; A1B4. According to the second step size adjustment coefficient, adjust the step size factor of the adaptive notch filter, and the adjusted step size factor is equal to the current step size factor plus the second step size adjustment coefficient.

8. A gate valve pressure balance control device, used for pressure balance control of gate valves in hydraulic systems of industrial robots, wherein a plurality of balance channels are arranged inside the gate valve, and all balance channels are controlled by a controller, characterized in that: include: Monitoring module, used to monitor the gate valve control signal and the pressure difference on both sides of the gate valve; A calculation module, used for calculating the gate valve control signal change rate according to the gate valve control signal, and setting the control signal amplitude threshold and change rate threshold; A prediction module, used to predict the gate valve switching action according to the gate valve control signal change rate, the control signal amplitude threshold and the change rate threshold; A judgment module is used to judge the number of balancing channels that need to be opened when the pressure on both sides of the gate valve is balanced based on the predicted gate valve switching action and the pressure difference on both sides of the gate valve; The control module is used to control the controller to open a corresponding number of balancing channels in advance according to the number of balancing channels, and to establish a pressure balancing passage to balance the pressure on both sides of the gate valve.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the gate valve pressure balance control method according to any one of claims 1 to 7 are executed.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the gate valve pressure balance control method according to any one of claims 1 to 7 are executed.

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