Dynamic precision compensation method for servo hydraulic actuator based on bus protocol

Abstract

The application discloses a dynamic precision compensation method of a servo hydraulic actuator based on a bus protocol and relates to the technical field of servo hydraulic precision compensation, which is used to solve the problem of reduced operation stability of the servo hydraulic actuator. In the servo hydraulic operation, the oil temperature of the oil cylinder is obtained, the database threshold is called and combined with the oil temperature classification, when the oil state is normal, the viscosity is detected through the viscosity sensor, the pressure wave is analyzed by receiving the multi-pressure sensor data through the bus protocol, the potential temperature rise index is evaluated by comprehensively considering the pressure wave and the viscosity, whether the threshold is adjusted is judged according to the potential temperature rise index, the filter backwashing frequency is obtained within the statistical time to analyze the cooling efficiency, the compensation weight is set in combination with the historical oil temperature data, the correction ratio is generated in combination with the cooling efficiency, and the threshold is adjusted. Through multi-data monitoring and analysis, the accurate evaluation of the potential temperature rise trend and the dynamic adjustment of the threshold are realized, the stability of the servo hydraulic actuator is improved, the oil life is prolonged, and the dynamic precision is optimized.

Description

Technical Field

[0001] This invention relates to the field of servo hydraulic precision compensation technology, and more specifically, to a method for dynamic precision compensation of servo hydraulic actuators based on a bus protocol. Background Technology

[0002] Servo hydraulic actuators, as key power units in modern equipment systems, are widely used in aerospace, precision machine tools, ship control, and large-scale engineering machinery. These actuators typically use hydraulic oil as the energy transmission medium to achieve high-power, high-response speed, and high-precision position, speed, and force control.

[0003] The existing technology has the following shortcomings:

[0004] Currently, existing technologies only detect hydraulic oil temperature using a single temperature sensor, which cannot be combined with oil viscosity and pressure ripple for comprehensive analysis. They also lack a dynamic correction mechanism based on historical databases and cooling efficiency values, resulting in reduced operational stability and increased dynamic errors in servo hydraulic actuators. Therefore, a dynamic accuracy compensation method for servo hydraulic actuators based on bus protocols is proposed.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a dynamic accuracy compensation method for servo hydraulic actuators based on a bus protocol. This method addresses the problems mentioned in the background by employing a dynamic correction mechanism for oil temperature thresholds driven by multi-source sensor data fusion analysis and a historical database.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol, comprising the following steps:

[0008] Step S1: During the servo hydraulic operation, the hydraulic oil temperature of the cylinder is obtained, the oil temperature threshold in the oil database is retrieved, and the hydraulic oil status is classified in combination with the hydraulic oil temperature.

[0009] Step S2: When the hydraulic oil is in a normal state, the viscosity of the oil is detected by a viscosity sensor, and pressure data from multiple pressure sensors is received via a bus protocol. The pressure ripple characteristics are analyzed based on the pressure data.

[0010] Step S3: Evaluate the latent temperature rise index by combining the pressure ripple characteristics and oil viscosity, determine whether to adjust the oil temperature threshold based on the latent temperature rise index, set the statistical time, obtain the number of backwashes of the filter, and analyze the cooling effect based on the number of backwashes.

[0011] Step S4: Obtain historical oil temperature data from the historical database, set temperature compensation weights based on the historical oil temperature data, generate correction ratios by combining cooling efficiency values, and adjust the oil temperature thresholds using the correction ratios.

[0012] In a preferred embodiment, during the operation of the servo hydraulic actuator in step S1, the hydraulic oil temperature is obtained in real time by a temperature sensor installed inside the cylinder.

[0013] After obtaining the hydraulic oil temperature, the oil temperature threshold from the oil database is called.

[0014] In a preferred embodiment, in step S1, the hydraulic oil temperature and the oil temperature threshold are compared:

[0015] When the hydraulic oil temperature is less than or equal to the oil temperature threshold, the hydraulic oil condition is determined to be normal.

[0016] When the hydraulic oil temperature exceeds the oil temperature threshold, the hydraulic oil condition is determined to be abnormal.

[0017] In a preferred embodiment, in step S2, when the hydraulic oil condition is determined to be normal, the viscosity of the hydraulic oil is detected by a viscosity sensor installed in the hydraulic oil circuit.

[0018] Pressure data, including hydraulic oil pressure, is received from pressure sensors located at different spatial positions on the servo hydraulic actuator via a bus protocol.

[0019] The pressure sensor is in direct contact with the hydraulic oil through its sensing element. It senses the static pressure generated by the hydraulic oil under the current operating conditions and uses it as the hydraulic oil pressure.

[0020] In a preferred embodiment, in step S2, a sampling time is set, and the hydraulic oil pressure at multiple spatial positions in the servo hydraulic actuator is obtained within the sampling time.

[0021] Calculate the difference between the highest and lowest hydraulic oil pressure values ​​at each spatial location within the sampling time to obtain the peak-to-peak value at each spatial location;

[0022] The peak-to-peak values ​​at all spatial locations are calculated by arithmetic mean, and the result is used as the pressure ripple characteristic.

[0023] In a preferred embodiment, in step S3, the viscosity threshold of the corresponding oil product type is obtained through the oil database, and the ratio of the absolute value of the difference between the oil viscosity and the oil viscosity threshold to the oil viscosity threshold is used as the viscosity deviation coefficient.

[0024] The latent temperature rise index is obtained by weighting the pressure ripple characteristics and viscosity deviation coefficient after standardization.

[0025] If the latent temperature rise index is greater than the preset latent temperature rise threshold, then the oil temperature threshold is adjusted.

[0026] Conversely, it is determined that the oil temperature threshold should not be adjusted.

[0027] In a preferred embodiment, in step S3, when it is determined that the oil temperature threshold is being adjusted, a statistical time is preset, and the backwashing event of the filter is collected through the hydraulic controller;

[0028] The backwashing action events are accumulated over a preset statistical period to obtain the number of backwashing events for the filter;

[0029] The cooling efficiency value is calculated based on the number of backwashes and the preset baseline number of backwashes.

[0030] In a preferred embodiment, in step S4, historical oil temperature data is retrieved from a historical database, including events where the hydraulic oil temperature exceeds the oil temperature threshold.

[0031] The cumulative number of times the hydraulic oil temperature exceeds the oil temperature threshold is obtained by summing up the events.

[0032] Calculate the temperature compensation weight using the cumulative number of times the limit is exceeded: ,in, To accumulate the number of times the limit is exceeded, As a preset adjustment factor, This is the temperature compensation weight.

[0033] In a preferred embodiment, in step S4, the comprehensive temperature compensation weight is combined with the cooling effect value to generate a correction ratio, and the product of the difference between 1 and the correction ratio and the oil temperature threshold is used as the adjustment oil temperature threshold.

[0034] The oil temperature threshold is stored in the oil database and then replaced.

[0035] The technical effects and advantages of this invention are as follows:

[0036] This invention acquires the hydraulic oil temperature of the cylinder during servo hydraulic operation, retrieves oil temperature thresholds from the oil database, and classifies the hydraulic oil state based on the hydraulic oil temperature. When the hydraulic oil state is normal, the viscosity of the oil is detected by a viscosity sensor, and pressure data from multiple pressure sensors is received via a bus protocol. The pressure ripple characteristics are analyzed based on the pressure data, and the latent temperature rise index is evaluated by combining the pressure ripple characteristics and oil viscosity. The latent temperature rise index determines whether to adjust the temperature threshold. A statistical time is set, and the number of backwashes of the filter is acquired. The cooling effectiveness is analyzed based on the number of backwashes, and historical oil temperature data is acquired from a historical database. Temperature compensation weights are set based on the historical oil temperature data, and a correction ratio is generated based on the cooling effectiveness. The correction ratio is used to adjust the oil temperature threshold. Through comprehensive monitoring and analysis of various data, the potential temperature rise trend can be accurately assessed and the oil temperature threshold can be dynamically adjusted, thereby effectively improving the operational stability of the servo hydraulic actuator, extending the service life of the hydraulic oil, and optimizing dynamic accuracy. Attached Figure Description

[0037] Figure 1 This is a flowchart illustrating the implementation of the dynamic accuracy compensation method for servo hydraulic actuators based on bus protocols according to the present invention.

[0038] Figure 2 This is a schematic diagram illustrating the steps of the dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] This invention acquires the hydraulic oil temperature of the cylinder during servo hydraulic operation, retrieves oil temperature thresholds from the oil database, and classifies the hydraulic oil state based on the hydraulic oil temperature. When the hydraulic oil state is normal, the viscosity of the oil is detected by a viscosity sensor, and pressure data from multiple pressure sensors is received via a bus protocol. The pressure ripple characteristics are analyzed based on the pressure data, and the latent temperature rise index is evaluated by combining the pressure ripple characteristics and oil viscosity. The latent temperature rise index determines whether to adjust the temperature threshold. A statistical time is set, and the number of backwashes of the filter is acquired. The cooling effectiveness is analyzed based on the number of backwashes, and historical oil temperature data is acquired from a historical database. Temperature compensation weights are set based on the historical oil temperature data, and a correction ratio is generated based on the cooling effectiveness. The correction ratio is used to adjust the oil temperature threshold. Through comprehensive monitoring and analysis of various data, the potential temperature rise trend can be accurately assessed and the oil temperature threshold can be dynamically adjusted, thereby effectively improving the operational stability of the servo hydraulic actuator.

[0041] Example 1

[0042] Please see Figures 1 to 2 A method for dynamic accuracy compensation of servo hydraulic actuators based on bus protocol includes the following steps:

[0043] Step S1: During the servo hydraulic operation, the hydraulic oil temperature of the cylinder is obtained, the oil temperature threshold in the oil database is retrieved, and the hydraulic oil status is classified in combination with the hydraulic oil temperature.

[0044] Step S2: When the hydraulic oil is in a normal state, the viscosity of the oil is detected by a viscosity sensor, and pressure data from multiple pressure sensors is received via a bus protocol. The pressure ripple characteristics are analyzed based on the pressure data.

[0045] Step S3: Evaluate the latent temperature rise index by combining the pressure ripple characteristics and oil viscosity, determine whether to adjust the oil temperature threshold based on the latent temperature rise index, set the statistical time, obtain the number of backwashes of the filter, and analyze the cooling effect based on the number of backwashes.

[0046] Step S4: Obtain historical oil temperature data from the historical database, set temperature compensation weights based on the historical oil temperature data, generate correction ratios by combining cooling efficiency values, and adjust the oil temperature thresholds using the correction ratios.

[0047] The specific implementation is as follows:

[0048] In step S1, during the operation of the servo hydraulic actuator, the hydraulic oil temperature is obtained in real time by a temperature sensor installed inside the cylinder;

[0049] Among them, the temperature sensor is a physical quantity detection device used to measure the temperature of hydraulic oil. Its function is to convert the actual temperature of hydraulic oil into an electrical or digital signal that can be used for control and judgment. It is set in the oil chamber inside the hydraulic cylinder to obtain the hydraulic oil temperature in real time, so as to ensure the immediacy and accuracy of the measurement.

[0050] After obtaining the hydraulic oil temperature, the oil temperature threshold in the oil database is called. The oil temperature threshold is a fixed reference value used to determine whether the hydraulic oil is within the safe operating temperature range. The viscosity-temperature curve of the hydraulic oil is obtained through experiments to obtain the viscosity change relationship of the hydraulic oil at different temperatures. Combined with the heat resistance limit and wear resistance limit of the servo hydraulic actuator, the safe operating temperature range of the hydraulic oil is determined. The upper limit of the high temperature is corrected according to the cooling capacity parameters of the servo hydraulic actuator and the maximum load condition. The correction range is calculated based on the ratio between load intensity and cooling efficiency to reflect the temperature rise trend under actual working conditions. Finally, the corrected upper limit temperature is determined as the oil temperature threshold and stored in the oil database as a reference for hydraulic oil condition judgment and dynamic accuracy compensation.

[0051] It should be noted that the oil database is a structured information library used to store relevant oil characteristic parameters of servo hydraulic actuators. Its contents include, but are not limited to, viscosity-temperature curves, density, heat capacity, oil temperature threshold and performance data of different types of hydraulic oil. It is stored digitally in the control system and can be called by the control system in real time to support hydraulic oil status judgment and dynamic compensation decision-making.

[0052] Compare the hydraulic oil temperature with the oil temperature threshold:

[0053] When the hydraulic oil temperature is less than or equal to the oil temperature threshold, the hydraulic oil condition is determined to be normal.

[0054] When the hydraulic oil temperature exceeds the oil temperature threshold, the hydraulic oil condition is determined to be abnormal.

[0055] In step S2, when the hydraulic oil condition is determined to be normal, the viscosity of the hydraulic oil is detected by a viscosity sensor installed in the hydraulic oil circuit. The viscosity sensor has an internally installed controllable rotating element that rotates in the hydraulic oil at a constant angular velocity. Due to internal friction, the hydraulic oil generates a resistance torque on the rotating element. The magnitude of this resistance torque is proportional to the viscosity of the hydraulic oil. The viscosity sensor measures the resistance torque required by the rotating element at a constant angular velocity and converts the obtained resistance torque with a pre-calibrated curve to obtain the viscosity of the hydraulic oil.

[0056] Hydraulic oil viscosity reflects the magnitude of the flow resistance between hydraulic oil molecules. The lower the value, the stronger the fluidity and the weaker the lubrication of the hydraulic oil; the higher the value, the weaker the fluidity and the stronger the lubrication of the hydraulic oil.

[0057] It should be noted that a viscosity sensor is a physical quantity detection device used to detect the viscosity parameters of hydraulic oil. Its function is to convert the viscosity state of hydraulic oil under the current temperature and pressure conditions into a digital signal that can be recognized and processed by the control system. It is set at the detection position in the hydraulic oil circuit and obtains the viscosity value of hydraulic oil in real time through direct contact with the hydraulic oil to characterize the internal friction resistance and flow characteristics between hydraulic oil molecules.

[0058] Simultaneously, pressure data, including hydraulic oil pressure, is received from pressure sensors located at different spatial positions on the servo hydraulic actuator via a bus protocol.

[0059] The pressure sensor is in direct contact with the hydraulic oil through its sensing element, sensing the static pressure generated by the hydraulic oil under the current operating conditions and taking it as the hydraulic oil pressure.

[0060] It should be noted that the bus protocol is a standardized communication rule used to realize data interaction between various detection devices and the control system in a servo hydraulic actuator. Its function is to ensure that the signals collected by multiple pressure sensors can be transmitted to the control system in a unified data format and timing rules. A pressure sensor is a physical quantity detection device used to measure the hydraulic oil pressure parameter in a servo hydraulic actuator. It is used to convert the pressure value of hydraulic oil at a specific spatial location into a digital signal that can be recognized and processed by the control system. It is arranged at different spatial locations such as the oil inlet, oil outlet, oil circuit branch point, and oil return line of the hydraulic cylinder.

[0061] A sampling time is set, and the hydraulic oil pressure at multiple spatial positions in the servo hydraulic actuator is obtained within the sampling time. The peak-to-peak value of each spatial position is calculated. The peak-to-peak value refers to the difference between the highest and lowest hydraulic oil pressure values ​​within the sampling time. The specific calculation formula is as follows:

[0062] ;

[0063] in, Let be the peak value at the i-th spatial location. Let be the highest hydraulic oil pressure value at the i-th spatial location during the sampling time. Let be the minimum hydraulic oil pressure at the i-th spatial location within the sampling time. Let be the hydraulic oil pressure value at the i-th spatial location at sampling time t within the sampling time.

[0064] Peak-to-peak value reflects the amplitude of pressure fluctuation at each spatial position of the servo hydraulic actuator within the sampling time. The larger the value, the more significant the change in hydraulic oil pressure at that spatial position, and the stronger the instantaneous energy fluctuation that the hydraulic oil experiences at that spatial position. This means that the possibility of increased local energy dissipation is greater, resulting in a greater tendency for oil temperature to rise. Conversely, the smaller the value, the more gradual the change in hydraulic oil pressure at that spatial position, and the weaker the instantaneous energy fluctuation that the hydraulic oil experiences at that spatial position. This means that the possibility of increased local energy dissipation is smaller, resulting in a smaller tendency for oil temperature to rise.

[0065] It should be noted that the sampling time refers to the length of a continuous time period used for pressure ripple characteristic analysis during the operation of the servo hydraulic actuator. This ensures that the pressure sensor collects sufficient pressure data within the same time window to reflect the instantaneous fluctuation characteristics of the hydraulic oil at various spatial locations. The sampling time is determined based on the typical working cycle of the servo hydraulic actuator, the output frequency of the hydraulic pump, and the operating cycle of the hydraulic valve. This ensures that at least one complete working cycle is covered within this time period, thereby accurately characterizing the pressure fluctuation amplitude. For example, for a servo hydraulic actuator with a pump frequency of 50Hz and a valve operating cycle of 0.1 seconds, the sampling time is set to 0.2 seconds. This means that the hydraulic oil pressure at each spatial location is recorded several times within each sampling time period, such as once per millisecond, to calculate the peak-to-peak value and reflect the pressure fluctuation amplitude.

[0066] The arithmetic mean of the peak-to-peak values ​​at all spatial locations is calculated, and the result is used as the pressure ripple characteristic. The calculation formula is as follows:

[0067] ;

[0068] in, It is a pressure ripple characteristic. Let be the peak value of the i-th spatial location, where i is the index of the spatial location and n is the total number of spatial locations.

[0069] Pressure ripple characteristics are used to quantify the synchronous pressure fluctuation amplitude of the hydraulic circuit during operation. The larger the pressure ripple characteristics, the more obvious the pressure fluctuations are at various spatial positions of the servo hydraulic actuator. The higher the shear stress and energy dissipation of the hydraulic oil during the flow process, that is, the oil temperature shows a potential upward trend.

[0070] In step S3, the viscosity threshold of the corresponding oil type is obtained through the oil database. The ratio of the absolute value of the difference between the oil viscosity and the oil viscosity threshold to the oil viscosity threshold is used as the viscosity deviation coefficient.

[0071] Higher oil viscosity indicates increased oil flow resistance and increased shear heating power; lower oil viscosity indicates a reduced lubricating film thickness, causing internal leakage power in pumps and valves to be converted into heat; the larger the viscosity deviation coefficient, the greater the degree to which the oil viscosity deviates from the oil viscosity threshold, and the more obvious the driving effect on the increase of hydraulic oil temperature.

[0072] It should be explained that the oil database is a database used to store the oil type and viscosity threshold of the hydraulic system. In this embodiment, it is used to retrieve the corresponding oil viscosity threshold according to the current oil type.

[0073] The latent temperature rise index is obtained by weighting the pressure ripple characteristics and viscosity deviation coefficient after standardization. ,in, The pressure ripple characteristics after standardization. The viscosity deviation coefficient after standardization. and For preset weighting coefficients, The latent temperature rise index;

[0074] A higher latent temperature rise index indicates a larger pressure ripple characteristic, a greater degree of deviation of the oil viscosity from the threshold, and a greater risk of subsequent rise in hydraulic oil temperature. This triggers a reduction in the oil temperature threshold to avoid deterioration of oil performance and deviations in the execution accuracy of the servo hydraulic system.

[0075] It should be explained that the preset weighting coefficient is used to limit the influence of pressure ripple characteristics and viscosity deviation coefficient on the latent temperature rise index. The value range is from 0 to 1 and is set according to the structural characteristics and historical operating data of the servo hydraulic system. For example, when the servo hydraulic system is in a state of significant oil viscosity fluctuation, the weight of the viscosity deviation coefficient can be increased. The standardization processing methods include, but are not limited to, standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. The application methods of standardization processing will not be elaborated here.

[0076] The preset latent temperature rise threshold is compared with the latent temperature rise index to determine whether to adjust the oil temperature threshold:

[0077] If the latent temperature rise index is greater than the preset latent temperature rise threshold, then the oil temperature threshold is adjusted.

[0078] Conversely, it is determined that the oil temperature threshold should not be adjusted.

[0079] When it is determined that the oil temperature threshold needs to be adjusted, a preset statistical time is set, and the backwashing events of the filter are collected through the hydraulic controller. The backwashing action events are accumulated within the preset statistical time to obtain the number of backwashing events of the filter.

[0080] The more times the filter is backwashed, the greater the amount of impurities deposited in the filter within the statistical time or the faster the pipeline resistance increases. This leads to a decrease in the heat exchange efficiency of the cooling circuit and a risk of accelerated rise in hydraulic oil temperature.

[0081] The cooling efficiency value is calculated based on the number of backflushing cycles and the preset baseline number of cycles. ,in, This is the cooling efficiency value. This refers to the number of backwashes. To preset the baseline number of times, This is the preset cooling adjustment factor.

[0082] It should be noted that the preset statistical time is a time window used to count the number of filter backwashes, which can be set according to the oil circulation cycle and shift length of the servo hydraulic system; the hydraulic controller is a control unit used to collect multi-source status signals of the servo hydraulic system and execute logic control. In this embodiment, it is used to collect the backwash action signal of the filter in real time; the preset benchmark backwash count is a reference value used to evaluate the smoothness of the cooling circuit, which can be set according to historical operating data. For example, the backwash count of each statistical period in the past 30 days is used to obtain a backwash count sample. The standard deviation and mean are calculated based on the backwash count sample, and the combination of the mean and standard deviation is used as the preset benchmark backwash count; the preset cooling adjustment factor is used to ensure that the cooling efficiency value is not zero. The value range is 0 to 1, and it can be set by calibration according to the sensitivity of the cooling capacity.

[0083] In step S4, historical oil temperature data is retrieved from the historical database. Historical oil temperature data refers to oil temperature-related information collected and stored in the historical database, including events where the hydraulic oil temperature exceeds the oil temperature threshold. The cumulative number of events where the hydraulic oil temperature exceeds the oil temperature threshold is accumulated.

[0084] Calculate the temperature compensation weight using the cumulative number of times the limit is exceeded: ,in, To accumulate the number of times the limit is exceeded, As a preset adjustment factor, Temperature compensation weights;

[0085] When the cumulative number of times the limit is exceeded is high, it indicates that the hydraulic oil temperature frequently exceeds the oil temperature threshold. The temperature compensation weight needs to be increased to make the oil temperature threshold lowered more significantly. When the cumulative number of times the limit is exceeded is low, the temperature compensation weight can be reduced to keep the oil temperature threshold stable.

[0086] The correction ratio is generated by combining the overall temperature compensation weight with the cooling efficiency value: ,in, To correct the proportions, The preset correction adjustment coefficient;

[0087] It should be explained that the historical database is used to store historical data related to the servo hydraulic system, including events where the hydraulic oil temperature exceeds the oil temperature threshold; the preset adjustment factor is used to adjust the growth rate of the temperature compensation weight with the cumulative number of over-limits. When the temperature compensation weight is more sensitive to the cumulative number of over-limits, the value of the preset adjustment factor can be increased; the preset correction adjustment coefficient is used to control the adjustment range of the correction ratio on the oil temperature threshold. It can be set according to historical operating data or control sensitivity requirements. For example, oil temperature over-limit events and cooling effect records can be retrieved from the historical database, and the deviation of the oil temperature threshold before and after adjustment can be statistically analyzed. The preset correction adjustment coefficient can then be analyzed based on the deviation.

[0088] The product of the difference between 1 and the correction ratio and the oil temperature threshold is used as the adjusted oil temperature threshold and stored in the oil database. The adjusted oil temperature threshold is then used to replace the oil temperature threshold, so that subsequent oil temperature monitoring uses the adjusted oil temperature threshold as the judgment benchmark.

[0089] By combining temperature compensation weights with cooling effectiveness to generate a correction ratio and adjust the oil temperature threshold, potential overheating risks can be identified in advance when the hydraulic oil is in a normal state. Lowering the oil temperature threshold can trigger cooling or an alarm, thus preventing the hydraulic oil from rising too quickly.

[0090] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0091] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0092] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0093] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0094] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A dynamic accuracy compensation method for servo hydraulic actuators based on a bus protocol, characterized in that: Includes the following steps: Step S1: During the servo hydraulic operation, the hydraulic oil temperature of the cylinder is obtained, the oil temperature threshold in the oil database is retrieved, and the hydraulic oil status is classified in combination with the hydraulic oil temperature. Step S2: When the hydraulic oil is in a normal state, the viscosity of the oil is detected by a viscosity sensor, and pressure data from multiple pressure sensors is received via a bus protocol. The pressure ripple characteristics are analyzed based on the pressure data. Step S3: Evaluate the latent temperature rise index by combining the comprehensive pressure ripple characteristics and oil viscosity, determine whether to adjust the oil temperature threshold based on the latent temperature rise index, set the statistical time, obtain the number of backwashes of the filter, and analyze the cooling effect value based on the number of backwashes. Step S4: Obtain historical oil temperature data from the historical database, set temperature compensation weights based on the historical oil temperature data, generate correction ratios by combining cooling efficiency values, and adjust the oil temperature thresholds using the correction ratios.

2. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 1, characterized in that: In step S1, during the operation of the servo hydraulic actuator, the hydraulic oil temperature is obtained in real time by a temperature sensor installed inside the cylinder; After obtaining the hydraulic oil temperature, the oil temperature threshold from the oil database is called.

3. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 2, characterized in that: In step S1, the hydraulic oil temperature is compared with the oil temperature threshold: When the hydraulic oil temperature is less than or equal to the oil temperature threshold, the hydraulic oil condition is determined to be normal. When the hydraulic oil temperature exceeds the oil temperature threshold, the hydraulic oil condition is determined to be abnormal.

4. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 1, characterized in that: In step S2, when the hydraulic oil condition is determined to be normal, the viscosity of the hydraulic oil is detected by a viscosity sensor installed in the hydraulic oil circuit. Pressure data, including hydraulic oil pressure, is received from pressure sensors located at different spatial positions on the servo hydraulic actuator via a bus protocol. The pressure sensor is in direct contact with the hydraulic oil through its sensing element. It senses the static pressure generated by the hydraulic oil under the current operating conditions and uses it as the hydraulic oil pressure.

5. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 4, characterized in that: In step S2, a sampling time is set, and the hydraulic oil pressure at multiple spatial positions in the servo hydraulic actuator is obtained within the sampling time. Calculate the difference between the highest and lowest hydraulic oil pressure values ​​at each spatial location within the sampling time to obtain the peak-to-peak value at each spatial location; The peak-to-peak values ​​at all spatial locations are calculated by arithmetic mean, and the result is used as the pressure ripple characteristic.

6. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 5, characterized in that: In step S3, the viscosity threshold of the corresponding oil type is obtained through the oil database. The ratio of the absolute value of the difference between the oil viscosity and the oil viscosity threshold to the oil viscosity threshold is used as the viscosity deviation coefficient. The latent temperature rise index is obtained by weighting the pressure ripple characteristics and viscosity deviation coefficient after standardization. If the latent temperature rise index is greater than the preset latent temperature rise threshold, then the oil temperature threshold is adjusted. Conversely, it is determined that the oil temperature threshold should not be adjusted.

7. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 6, characterized in that: In step S3, when it is determined that the oil temperature threshold is being adjusted, a preset statistical time is set, and the backwashing event of the filter is collected through the hydraulic controller; The backwashing action events are accumulated over a preset statistical period to obtain the number of backwashing events for the filter; The cooling efficiency value is calculated based on the number of backwashes and the preset baseline number of backwashes.

8. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 1, characterized in that: In step S4, historical oil temperature data is retrieved from the historical database, including events where the hydraulic oil temperature exceeds the oil temperature threshold. The cumulative number of times the hydraulic oil temperature exceeds the oil temperature threshold is obtained by summing up the events. Calculate the temperature compensation weight using the cumulative number of times the limit is exceeded: ,in, To accumulate the number of times the limit is exceeded, As a preset adjustment factor, This is the temperature compensation weight.

9. The dynamic accuracy compensation method for a servo hydraulic actuator based on a bus protocol according to claim 8, characterized in that: In step S4, the comprehensive temperature compensation weight is combined with the cooling effect value to generate a correction ratio. The product of the difference between 1 and the correction ratio and the oil temperature threshold is used as the adjustment oil temperature threshold. The oil temperature threshold is stored in the oil database and then replaced.

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