Method and system for suppressing air pulsation of liquid-driven compressor

Abstract

The invention provides an airflow pulsation suppression method and system for a liquid-driven compressor, and the method comprises the steps: obtaining a pressure pulsation frequency spectrum and flow data of an outlet pipeline of the liquid-driven compressor; generating a dominant frequency offset rule based on the pressure pulsation spectrum and the flow data; based on the main frequency offset rule and the main peak frequency of the pressure pulsation frequency spectrum, a target position adjusting signal is generated in combination with a fuzzy PID controller; the actual position of a movable baffle arranged in a resonant cavity of the hydraulic drive compressor is monitored in real time, and feedback compensation is conducted on the target position adjusting signal based on the actual position; and the position of the movable baffle is adjusted based on the compensated target position adjusting signal, so that the through-flow area of the resonant cavity is changed, and airflow pulsation of the outlet pipeline is restrained. According to the invention, the airflow pulsation suppression effect of the hydraulic drive compressor under variable working conditions is improved.

Description

Technical Field

[0001] The present application relates to the technical field of airflow pulsation suppression in liquid-driven compressors, and in particular to a method and system for suppressing airflow pulsation in a liquid-driven compressor. Background Art

[0002] During the variable operating conditions of a liquid-driven compressor, airflow pulsation in the outlet pipeline seriously affects system stability and equipment life. This is especially true in scenarios with variable frequency drive or large load fluctuations. Traditional fixed vibration damping structures are unable to effectively suppress wide-band pulsations, and an active suppression method that can dynamically adapt to frequency changes is urgently needed.

[0003] One current solution uses active muffler technology, installing an acoustic wave transmitter on the compressor outlet pipe to generate reverse acoustic waves to offset airflow pulsations. This solution collects pressure fluctuation signals in real time, uses a digital signal processor to calculate the required reverse acoustic wave parameters, and then generates the canceling sound waves through a speaker array.

[0004] This solution requires extremely high precision in acoustic wave phase matching, which can easily lead to acoustic interference under complex operating conditions, exacerbating local pulsation. Furthermore, high-frequency acoustic wave transmitters consume a lot of power, leading to reduced energy efficiency over long periods of operation. They are also sensitive to piping structure vibrations, limiting their installation locations. Summary of the Invention

[0005] The present application provides a method and system for suppressing airflow pulsation of a liquid-driven compressor, so as to solve the problem in the prior art that the liquid-driven compressor has poor airflow pulsation suppression effect under variable working conditions.

[0006] In a first aspect, the present application provides a method for suppressing airflow pulsation in a liquid-driven compressor, comprising: Obtain the pressure pulsation spectrum and flow rate data of the outlet pipeline of the liquid-driven compressor; generating a main frequency deviation law based on the pressure pulsation spectrum and the flow data; Based on the main frequency offset law and the main peak frequency of the pressure pulsation spectrum, a target position adjustment signal is generated in combination with a fuzzy PID controller; monitoring in real time the actual position of a movable baffle disposed in a resonant cavity of the liquid-driven compressor, and performing feedback compensation on the target position adjustment signal based on the actual position; Based on the compensated target position adjustment signal, the position of the movable baffle is adjusted to change the flow area of ​​the resonance cavity, thereby suppressing air flow pulsation in the outlet pipeline.

[0007] Optionally, the generating of the target position adjustment signal based on the main frequency offset rule and the main peak frequency of the pressure pulsation spectrum in combination with a fuzzy PID controller includes: According to the flow data, query the corresponding reference main peak frequency from the main frequency offset rule; Superimposing the reference main peak frequency and the preset offset to obtain a target resonant frequency; Subtracting the main peak frequency of the pressure pulsation spectrum from the target resonance frequency to obtain a frequency difference; The absolute value of the frequency difference is input into the input interface of the fuzzy PID controller, and a target position adjustment signal is output.

[0008] Optionally, inputting the absolute value of the frequency difference into an input interface of a fuzzy PID controller and outputting a target position adjustment signal includes: Performing dynamic dead zone processing on the absolute value to obtain a valid difference; According to the effective difference, matching a corresponding fuzzy interval from a control rule library of a fuzzy PID controller; According to the current operating condition of the liquid-driven compressor, an optimal parameter combination matching the fuzzy interval and the operating condition is selected from a plurality of preset parameter groups; Based on the optimal parameter combination, performing signal conversion on the effective difference to generate an initial position adjustment signal; Amplitude limiting processing is performed on the initial position adjustment signal to generate a target position adjustment signal.

[0009] Optionally, performing signal conversion on the effective difference based on the optimal parameter combination to generate an initial position adjustment signal includes: Performing weighted operations on the effective difference and the proportional coefficient, integral coefficient, and differential coefficient in the optimal parameter combination to generate a proportional term, an integral term, and a differential term; Performing superposition calculation on the proportional term, the integral term, and the differential term, and outputting an initial control variable; quantizing the initial control amount into a target pulse number according to the pulse equivalent resolution of the liquid-driven compressor; Based on the target pulse number and in combination with the polarity of the control amount, a pulse control sequence is generated, and the pulse control sequence is used as an initial position adjustment signal.

[0010] Optionally, generating a main frequency deviation rule based on the pressure pulsation spectrum and the flow data includes: Dividing the pressure pulsation spectrum into a plurality of characteristic frequency bands, and extracting the main peak frequency under each operating condition from the plurality of characteristic frequency bands; Analyze the main peak frequency distribution patterns in different flow intervals based on the flow data and the main peak frequencies under corresponding operating conditions to generate a frequency offset feature library; The main frequency offset rule is output through the frequency offset feature library.

[0011] Optionally, analyzing the main peak frequency distribution patterns in different flow intervals based on the flow data and the main peak frequencies under corresponding operating conditions to generate a frequency shift feature library includes: Discretize the flow data into multiple flow intervals according to a preset division rule; For each flow interval, the distribution density of all main peak frequencies in the flow interval is counted to generate a probability density distribution graph; Identifying a frequency range corresponding to a probability density peak from the probability density distribution graph, and using the frequency range as a concentrated distribution interval of a main peak frequency; Extracting the median frequency of the concentrated distribution interval as the representative frequency value of the corresponding flow interval; The flow interval is mapped to the representative frequency value to generate a frequency offset feature library.

[0012] Optionally, adjusting the position of the movable baffle based on the compensated target position adjustment signal includes: Inputting the compensated target position adjustment signal into a drive circuit provided in the liquid-driven compressor; converting the compensated target position adjustment signal into a rotation angle instruction of the liquid-driven compressor through the drive circuit; According to the rotation angle instruction, adjusting the rotation angle and rotation direction of the output shaft of the liquid-driven compressor; The adjusted rotation angle is converted into an axial displacement of the screw nut through direct transmission between the output shaft of the liquid-driven compressor and the screw mechanism; Based on the axial displacement, the size of the gap between the movable baffle and the wall of the resonant cavity is adjusted.

[0013] In a second aspect, the present application provides an air flow pulsation suppression system for a liquid-driven compressor, comprising: An acquisition module, used to acquire pressure pulsation spectrum and flow data of the outlet pipeline of the liquid-driven compressor; A first generating module, configured to generate a main frequency deviation rule based on the pressure pulsation spectrum and the flow data; A second generating module is configured to generate a target position adjustment signal based on the main frequency offset rule and the main peak frequency of the pressure pulsation spectrum in combination with a fuzzy PID controller; a monitoring module, configured to monitor in real time the actual position of a movable baffle disposed in a resonance cavity of the liquid-driven compressor, and perform feedback compensation on the target position adjustment signal based on the actual position; The regulating module is used to regulate the position of the movable baffle based on the compensated target position regulation signal to change the flow area of ​​the resonance cavity, thereby suppressing the air flow pulsation of the outlet pipeline.

[0014] In a third aspect, the present application provides a computing device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute a method for suppressing airflow pulsation in a liquid-driven compressor as described in any one of the first aspects.

[0015] In a fourth aspect, the present application provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement a method for suppressing airflow pulsation of a liquid-driven compressor as described in any one of the first aspects.

[0016] In the present application, a method for suppressing airflow pulsation of a liquid-driven compressor is provided, the method comprising: obtaining a pressure pulsation spectrum and flow data of an outlet pipeline of the liquid-driven compressor; generating a main frequency offset law based on the pressure pulsation spectrum and the flow data; generating a target position adjustment signal based on the main frequency offset law and the main peak frequency of the pressure pulsation spectrum in combination with a fuzzy PID controller; real-time monitoring of the actual position of a movable baffle arranged in a resonance cavity of the liquid-driven compressor, and feedback compensation of the target position adjustment signal based on the actual position; and adjusting the position of the movable baffle based on the compensated target position adjustment signal to change the flow area of ​​the resonance cavity, thereby suppressing the airflow pulsation of the outlet pipeline.

[0017] The technical solution provided by this application has the following beneficial effects: This application accurately captures the airflow pulsation characteristics and operating conditions of the compressor during operation, providing a reliable data foundation for subsequent analysis. It establishes a correspondence between flow rate changes and main peak frequency fluctuations, revealing the changing patterns of the system's pulsation characteristics under different operating conditions. An intelligent control algorithm calculates optimal adjustment instructions in real time, ensuring that the control response matches the current pulsation characteristics. It eliminates mechanical transmission errors and improves the accuracy and stability of baffle position control. It also dynamically optimizes the resonant cavity structural parameters to achieve precise suppression of airflow pulsation.

[0018] Furthermore, the present application also obtains the reference frequency by querying the main frequency offset law, determines the target resonance frequency in combination with the preset offset, calculates the difference between the measured main peak frequency and the target value, and outputs an accurate position adjustment signal after fuzzy PID control processing.

[0019] In addition, this solution realizes intelligent dynamic suppression of compressor airflow pulsation. Through the synergistic effect of frequency tracking and intelligent adjustment, it improves the system's pulsation suppression capability under different working conditions, while ensuring the stability and reliability of the control process.

[0020] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1 A flow chart of a method for suppressing airflow pulsation in a liquid-driven compressor provided in an embodiment of the present application; Figure 2 A schematic structural diagram of an air flow pulsation suppression system for a liquid-driven compressor provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0024] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0025] Existing technologies for suppressing airflow pulsation in liquid-driven compressors, using active mufflers, have significant shortcomings. This technology requires precise matching of the phase and amplitude of the reverse sound wave. However, when the compressor speed fluctuates frequently, the sound wave adjustment often cannot keep up with the changing speed of the pulsation frequency, significantly reducing the suppression effect. Furthermore, this system consumes a lot of energy, significantly increasing energy costs over long periods of operation. Furthermore, the system is very demanding on the installation location; even a slight deviation from the optimal position can affect the overall suppression effect.

[0026] In response to these problems, the present application proposes a method for suppressing airflow pulsation in a liquid-driven compressor. The core of this method is to monitor the airflow pulsation characteristics at the compressor outlet in real time and automatically adjust the position of the movable baffle in the resonance cavity to change the size of the airflow channel. Specifically, the system will first analyze the frequency characteristics of the airflow pulsation, then calculate the optimal baffle adjustment scheme through an intelligent control algorithm, and finally accurately adjust the baffle position through mechanical transmission. This method completely avoids the problem of acoustic wave interference and achieves pulsation suppression by physically changing the airflow channel. It not only has a faster response speed, but also reduces energy consumption and has no special requirements for the installation position. It fundamentally solves the problems of adjustment lag, high energy consumption and installation restrictions in the existing technology, and improves the stability and reliability of pulsation suppression.

[0027] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0028] Figure 1 This is a flow chart of a method for suppressing air flow pulsation of a liquid-driven compressor provided in an embodiment of the present application, such as Figure 1 As shown, the method includes: Step 101: Obtain pressure pulsation spectrum and flow rate data of the outlet pipeline of the liquid-driven compressor.

[0029] In step 101, the pressure pulsation spectrum represents the frequency distribution characteristics of the compressor outlet airflow pressure fluctuations over time, indicating the intensity of pressure fluctuations at different frequencies. The flow rate data records the volume of gas passing through the compressor outlet per unit time, reflecting the system operating conditions.

[0030] In this embodiment, a pressure sensor and flowmeter are installed in the compressor outlet pipeline. The pressure sensor collects pressure fluctuation signals and converts the time-domain signals into frequency-domain signals using a fast Fourier transform to obtain a pressure pulsation spectrum. Simultaneously, the flowmeter measures gas flow in real time. The collected pressure pulsation spectrum and flow rate data are stored in the system buffer for subsequent analysis.

[0031] For example, during the operation of a certain type of liquid-driven compressor, a pressure sensor collects outlet pressure signals at a fixed sampling frequency. After processing by a signal conditioning circuit, this signal is converted into a frequency spectrum using a fast Fourier transform algorithm. The main peak appears at 150 Hz, with an amplitude of 15 kPa. Simultaneously, the flow meter measures the current flow rate at 80 cubic meters per minute. The system then packages and stores these two data points.

[0032] Step 102: Generate a main frequency deviation law based on the pressure pulsation spectrum and the flow data.

[0033] In step 102, the main frequency offset law refers to the corresponding relationship between the main peak frequency in the outlet pipeline pressure pulsation spectrum of the liquid-driven compressor under different flow conditions and the flow rate change. It is specifically manifested as a mapping law between the flow value and the main peak frequency change trend established through historical operation data analysis. This law can reflect the impact characteristics of flow rate changes on the main frequency of airflow pulsation.

[0034] In an embodiment of the present application, a statistical analysis is performed on historical operating data, the flow values ​​are divided into several intervals, the distribution of the main peak frequency is statistically analyzed in each flow interval, the frequency range with the highest probability of occurrence is found as the representative frequency of the interval, and a functional relationship between the flow value and the representative frequency is established through curve fitting to form a main frequency offset law.

[0035] For example, analysis of three months of operational data revealed that when the flow rate was between 70 and 90 cubic meters per minute, the main peak frequency was concentrated in the 145-155 Hz range, with 150 Hz occurring most frequently. This value was taken as the representative frequency. Using the least squares method, the relationship between frequency and flow rate was obtained: 1.2 × flow rate + 54, which was stored in the feature library.

[0036] Step 103: Based on the main frequency offset rule and the main peak frequency of the pressure pulsation spectrum, a target position adjustment signal is generated in combination with a fuzzy PID controller.

[0037] In step 103, the fuzzy PID controller represents an intelligent regulator that combines fuzzy logic and PID control and can adapt to nonlinear systems. The target position adjustment signal represents a command signal for controlling the movement of the baffle.

[0038] In an embodiment of the present application, the reference frequency is obtained according to the main frequency offset rule queried according to the current flow, and the target frequency is obtained by adding the preset offset. The difference between the measured main peak frequency and the target frequency is calculated, and the difference is input into the fuzzy PID controller. The controller selects the control parameters according to the preset rules and outputs the adjustment signal after proportional integral differential operation.

[0039] For example, the current flow rate is 80 cubic meters per minute. The query results in a base frequency of 150 Hz. Adding the preset offset of 10 Hz gives a target frequency of 160 Hz. The actual peak frequency is 155 Hz. The difference of 5 Hz is input into the controller, and a 9-volt adjustment signal is output after calculation.

[0040] Step 104: monitoring the actual position of the movable baffle disposed in the resonant cavity of the liquid-driven compressor in real time, and performing feedback compensation on the target position adjustment signal based on the actual position.

[0041] In step 104, the actual position refers to the specific physical coordinates of the movable baffle within the resonant cavity, as measured in real time by the displacement sensor. This coordinate value reflects the baffle's real-time distance from the cavity wall and is used to compare it with the target position calculated by the control system to determine the position adjustment deviation. Specifically, it represents the baffle's current axial displacement, typically measured in millimeters, and this value changes dynamically with the stepper motor's drive. Feedback compensation involves correcting the control signal based on the deviation between the actual and target positions.

[0042] In the embodiment of the present application, the baffle position is monitored in real time by a displacement sensor, the measured position is compared with the target position to obtain the deviation, and a proportional compensation algorithm is used to correct the original adjustment signal to ensure that the baffle eventually reaches the predetermined position.

[0043] For example, the target position corresponds to a baffle movement of 10 mm, but the actual movement is only 9.5 mm, resulting in a deviation of 0.5 mm. The compensation algorithm adjusts the regulation signal from 9 volts to 9.5 volts.

[0044] Step 105: Based on the compensated target position adjustment signal, adjust the position of the movable baffle to change the flow area of ​​the resonance cavity, thereby suppressing the air flow pulsation of the outlet pipeline.

[0045] In step 105 , the flow area represents the effective cross-sectional area between the baffle and the cavity wall through which the airflow can pass.

[0046] In an embodiment of the present application, the compensated adjustment signal is converted into a driving pulse of a stepper motor, and the rotational motion is converted into a linear displacement of the baffle through a screw mechanism to accurately adjust the gap size between the baffle and the cavity wall, thereby changing the flow area.

[0047] For example, a 9.5-volt signal is converted into 1425 drive pulses, and the stepper motor drives the lead screw to move the baffle 10.1 mm, increasing the gap from 3 mm to 5 mm and expanding the flow area.

[0048] This method achieves dynamic suppression of airflow pulsation in liquid-driven compressors through closed-loop control involving real-time monitoring, intelligent analysis, and precise adjustment, effectively improving system operation stability and extending equipment service life. It also has the advantages of fast response, precise adjustment, and strong adaptability.

[0049] In order to solve the problem of precise control of airflow pulsation suppression in a liquid-driven compressor under variable operating conditions, in some embodiments, step 103: generating a target position adjustment signal based on the main frequency offset law and the main peak frequency of the pressure pulsation spectrum in combination with a fuzzy PID controller includes: Step 201: According to the traffic data, query the corresponding reference main peak frequency from the main frequency offset rule.

[0050] In step 201, the reference main peak frequency refers to a typical value of the pressure pulsation frequency of the compressor under a specific flow condition, which is obtained through historical data analysis and reflects the most likely pulsation main frequency under the flow condition.

[0051] In the embodiment of the present application, the system searches for the corresponding reference main peak frequency in the main frequency offset law database according to the currently detected flow value. The database stores the mapping relationship between different flow intervals and reference frequencies.

[0052] Step 202: superimposing the reference main peak frequency and the preset offset to obtain a target resonance frequency.

[0053] In step 202, the preset offset is a fixed frequency adjustment value set based on the acoustic characteristics of the compressor resonant cavity. It is used to correct the base frequency to the target resonant frequency. The target resonant frequency is the ideal frequency value calculated by adding the base main peak frequency to the preset offset. This frequency is the optimal operating frequency that the control system expects the compressor resonant cavity to ultimately achieve, effectively suppressing airflow pulsation under the current operating conditions. The base main peak frequency reflects typical operating conditions, and the preset offset is an optimized adjustment value set based on the acoustic characteristics of the resonant cavity. The combination of the two ensures that the resonant cavity always operates in an optimally suppressed state.

[0054] In an embodiment of the present application, the reference main peak frequency obtained by the query is arithmetically added to the preset offset, and the calculation result is the target resonance frequency to be achieved. This frequency is the ideal pulsation suppression frequency that the control system hopes to achieve.

[0055] Step 203: Subtract the main peak frequency of the pressure pulsation spectrum from the target resonance frequency to obtain a frequency difference.

[0056] In step 203 , the frequency difference refers to the deviation between the actually detected main peak frequency and the target resonance frequency, reflecting the gap between the current pulsation state and the ideal state.

[0057] In an embodiment of the present application, a subtraction operation is performed on the main peak frequency obtained by real-time spectrum analysis and the target resonance frequency obtained by calculation, and the obtained difference is used as an input signal of the control system.

[0058] Step 204: Input the absolute value of the frequency difference into the input interface of the fuzzy PID controller, and output a target position adjustment signal.

[0059] In an embodiment of the present application, the absolute value of the frequency difference is input into the fuzzy PID controller, and the controller selects appropriate control parameters according to preset fuzzy rules. After proportional, integral, and differential operations, it outputs a target position adjustment signal, which will drive the actuator to operate.

[0060] Here's a specific example: Continuing with a certain type of liquid-driven compressor as an example, the flow meter shows a flow rate of 80 cubic meters per minute under the current operating conditions. The system uses the relationship of frequency = 1.2×flow rate + 54 stored in the pre-established frequency offset feature library, where the flow rate is the current measured value of 80 cubic meters per minute. The calculated reference peak frequency is 1.2×80+54=150 Hz. The fixed frequency offset required by the compressor resonance cavity design is 10 Hz. The reference frequency of 150 Hz is added to the offset of 10 Hz to obtain the target resonance frequency of 160 Hz. At this time, the real-time spectrum collected by the pressure sensor shows that the main peak frequency is 155 Hz. The calculated frequency difference is 155 minus 160, which is equal to negative 5 Hz. The absolute value of 5 Hz is taken as the input signal of the fuzzy PID controller. The controller has three preset control intervals. The 0 to 5 Hz interval uses a proportional coefficient of 0.8, an integral coefficient of 0.05, and a differential coefficient of 0.1. The proportional term is calculated to be 0.8×5=4, the integral term is 0.05×5×control period 0.1 second=0.025, and the differential term is 0.1×5 / 0.1=5. The three terms are added together to obtain an initial control value of 9.025 volts, which is output as a stepper motor drive signal through the digital-to-analog conversion module. The conversion relationship between each volt of voltage and a pulse frequency of 100 Hz is set according to the motor parameters. Finally, a control signal containing 903 positive pulses is generated. This signal drives the stepper motor to rotate and drive the screw mechanism, converting the rotational motion into a linear displacement of the baffle. The design parameter of the screw lead of 5 mm determines that each pulse corresponds to a baffle movement of 0.01 mm. Therefore, 903 pulses cause the baffle to move 9.03 mm, adjusting the flow gap of the resonant cavity from the initial 3 mm to 4.515 mm. The control period of 0.1 second is the sampling interval preset by the system to ensure that the control response speed matches the changes in airflow pulsation.

[0061] In the embodiment of the present application, the control method achieves dynamic suppression of airflow pulsation through intelligent frequency tracking and precise adjustment signal generation, enabling the system to quickly respond to changes in operating conditions and maintain a stable pulsation suppression effect, while avoiding the problems of adjustment lag and insufficient precision in traditional methods.

[0062] In order to improve the control accuracy of airflow pulsation suppression in a liquid-driven compressor, in some embodiments, step 204: inputting the absolute value of the frequency difference into the input interface of the fuzzy PID controller and outputting the target position adjustment signal includes: Step 301: Perform dynamic dead zone processing on the absolute value to obtain a valid difference.

[0063] In step 301, dynamic deadband processing involves setting a minimum valid difference range based on system requirements. Input values ​​below this range are considered invalid fluctuations and are not processed. Subsequent control calculations are performed only when these values ​​exceed this range. The valid difference refers to the absolute value of the frequency difference identified as requiring processing after dynamic deadband processing. Only when this value exceeds the preset deadband threshold will it be adopted by the system for subsequent control calculations, avoiding unnecessary adjustments to minor fluctuations.

[0064] In an embodiment of the present application, the system will first determine whether the absolute value of the input frequency difference exceeds the preset dead zone threshold. If it does not exceed, the output value of the previous control cycle remains unchanged. If it exceeds, the difference is output as a valid difference to the next processing link.

[0065] Step 302: According to the effective difference, a corresponding fuzzy interval is matched from a control rule library of a fuzzy PID controller.

[0066] In step 302 , the fuzzy interval is a plurality of pre-divided difference range intervals, and each interval corresponds to a different control strategy.

[0067] In an embodiment of the present application, a plurality of pre-divided difference intervals are stored inside the controller. The system compares the effective difference with these intervals to determine the interval range to which it belongs, providing a basis for subsequent parameter selection.

[0068] Step 303: According to the current operating condition of the liquid-driven compressor, an optimal parameter combination matching the fuzzy interval and the operating condition is selected from a plurality of preset parameter groups.

[0069] In step 303, the current operating condition refers to the current load state and working conditions of the compressor, which are determined by comprehensive judgment based on real-time monitored flow data, pressure data, and speed data. The system will classify the operating conditions into different categories such as light load, medium load, and heavy load based on these parameters. The optimal parameter combination refers to the three groups of proportional, integral, and differential control parameters optimized for specific operating conditions and differential intervals. The multiple preset parameter groups are different sets of control parameters determined in advance through experiments and optimization. Each group of parameters contains specific proportional coefficients, integral coefficients, and differential coefficients, which are respectively applicable to different differential intervals and operating condition combinations.

[0070] In an embodiment of the present application, the system selects the most suitable proportional coefficient, integral time and differential time combination for the current situation from a preset parameter library according to the current operating conditions of the compressor and the matched fuzzy interval.

[0071] Step 304: Based on the optimal parameter combination, perform signal conversion on the effective difference to generate an initial position adjustment signal.

[0072] In step 304, signal conversion is the process of converting the difference signal into a control output according to selected parameters. The initial position adjustment signal is the raw control output calculated by the fuzzy PID controller based on the optimal parameter combination. This signal undergoes subsequent adjustments, such as limiting, before being converted into the final execution instruction.

[0073] In the embodiment of the present application, the system uses the selected optimal parameter combination to perform proportional, integral, and differential operations on the effective difference, and adds the operation results to obtain the initial control quantity signal.

[0074] Step 305: performing amplitude limiting processing on the initial position adjustment signal to generate a target position adjustment signal.

[0075] In step 305 , the amplitude limiting process is performed to ensure that the output signal is within a safe range and to avoid overload of the actuator.

[0076] In the embodiment of the present application, the system will compare the initial control quantity signal with the preset upper and lower limits. If it exceeds the limit, the limit is taken as the final output; otherwise, the initial value is directly output to ensure the safe operation of the actuator.

[0077] Here's a specific example: After the system obtains the absolute value of the 5 Hz frequency difference, it first performs dynamic deadband processing, using a preset deadband threshold of 2 Hz. Since 5 Hz exceeds the threshold, the system determines the difference as valid and continues processing. The controller internally defines three fuzzy intervals: 0-3 Hz for the small difference interval, 3-7 Hz for the medium difference interval, and 7 Hz and above for the large difference interval. 5 Hz also falls into the medium difference interval. The system also detects that the compressor is currently operating under medium load conditions and selects the optimal parameter combination from a preset parameter library for the medium difference interval and medium load conditions: a proportional coefficient of 0.7, an integral coefficient of 0.06, and a differential coefficient of 0.12. Based on these parameters, the proportional term is 0.7 × 5 = 3.5, the integral term is 0.06 × 5 × the control period of 0.1 seconds = 0.03, and the differential term is 0.12 × 5 / 0.1 = 6. Adding these three terms yields an initial control variable of 9.53 volts. The system preset voltage output upper limit is 10 volts. Since 9.53 volts does not exceed the limit, it is directly output as the target position adjustment signal.

[0078] In the embodiment of the present application, the control method achieves precise suppression of airflow pulsation through intelligent difference processing and parameter optimization selection, enabling the system to automatically adjust the control strategy according to actual working conditions, thereby ensuring both control accuracy and the safety of system operation.

[0079] To further improve the control accuracy of airflow pulsation suppression in a liquid-driven compressor, in some embodiments, step 304: performing signal conversion on the effective difference based on the optimal parameter combination to generate an initial position adjustment signal includes: Step 401: Perform weighted operations on the effective difference and the proportional coefficient, integral coefficient, and differential coefficient in the optimal parameter combination to generate a proportional term, an integral term, and a differential term.

[0080] In step 401, the proportional term reflects the direct impact of the current difference. The integral term is used to eliminate historical accumulated errors. The differential term predicts future change trends.

[0081] In an embodiment of the present application, the system multiplies the effective difference with the three coefficients in the optimal parameter combination respectively. The proportional coefficient is directly multiplied by the difference to obtain the proportional term, the integral coefficient is multiplied by the product of the difference and time to obtain the integral term, and the differential coefficient is multiplied by the rate of change of the difference to obtain the differential term.

[0082] Step 402: Perform superposition calculation on the proportional term, the integral term, and the differential term, and output an initial control variable.

[0083] In step 402 , the initial control amount is a preliminary adjustment instruction obtained by integrating the results of the three operations.

[0084] In an embodiment of the present application, the calculated proportional term, integral term, and differential term are algebraically added, and the sum is the initial control quantity, which reflects the system's comprehensive adjustment requirements for the current deviation.

[0085] Step 403: quantizing the initial control variable into a target pulse number according to the pulse equivalent resolution of the liquid-driven compressor.

[0086] In step 403, pulse equivalent resolution refers to the actual displacement of the movable baffle when the hydraulic compressor receives each pulse signal. This parameter is determined by the hydraulic compressor's step angle, screw lead, and transmission ratio. The specific value is determined by mechanical design based on the required adjustment accuracy of the compressor's resonant cavity. The target pulse number is the total number of pulses required to be sent to the stepper motor, calculated based on the initial control variable and the pulse equivalent resolution. This value determines the final movement distance of the actuator (such as the baffle). The calculation formula is: the target pulse number equals the initial control variable multiplied by the pulse equivalent resolution, where the pulse equivalent resolution is a pre-calibrated number of pulses per voltage unit.

[0087] In the embodiment of the present application, the initial control amount is multiplied by a preset conversion coefficient according to the technical parameters of the actuator to calculate the total number of pulses to be output, thereby ensuring that the mechanical displacement corresponds accurately to the control amount.

[0088] Step 404: Based on the target pulse number and in combination with the polarity of the control variable, a pulse control sequence is generated, and the pulse control sequence is used as an initial position adjustment signal.

[0089] In step 404, the polarity of the control variable refers to the direction of regulation, determined by the sign of the frequency difference. When the main peak frequency is higher than the target frequency, a negative difference corresponds to reverse regulation, while when it is lower than the target frequency, a positive difference corresponds to forward regulation. This polarity is derived from the difference between the main peak frequency and the target resonant frequency and directly determines the direction of rotation of the stepper motor. The pulse control sequence is the specific combination of instructions that drives the stepper motor.

[0090] In an embodiment of the present application, a control sequence including pulse quantity and direction information is generated based on the calculated target pulse number and the positive and negative polarity of the difference, which can directly drive the motor to achieve precise position control.

[0091] Here's a specific example: After the system obtains an initial control variable of 9.53 volts, the pulse equivalent resolution is set to 120 pulses per volt based on the technical specifications of the stepper motor for this model of liquid-driven compressor. The initial control variable of 9.53 volts is multiplied by 120 to obtain a target pulse count of 1143.6, which is rounded to 1144 pulses. Since the frequency difference calculated in the previous step is negative 5 Hz and its absolute value is taken, the sign of the original difference is retained in the control variable polarity. Here, a negative difference indicates a need to reduce the flow area, so the control variable polarity is reversed. Based on the target pulse count of 1144 and the reverse regulation requirement, the system generates a control sequence consisting of 1144 reverse pulses.

[0092] In the embodiment of the present application, the signal conversion method achieves high-precision conversion of electrical signals to mechanical displacements through precise parameter calculations and pulse quantization, ensuring that the airflow pulsation suppression system can execute control instructions quickly and accurately, thereby improving the overall control effect and system stability.

[0093] In order to accurately establish the correlation between the airflow pulsation characteristics and the operating conditions of the liquid-driven compressor, in some embodiments, step 102: generating a main frequency offset law based on the pressure pulsation spectrum and the flow data includes: Step 501: Divide the pressure pulsation spectrum into multiple characteristic frequency bands, and extract the main peak frequency under each operating condition from the multiple characteristic frequency bands.

[0094] In step 501, the pressure pulsation spectrum is divided into multiple characteristic frequency bands by using preset fixed frequency intervals. The division is based on the frequency band range where the pressure pulsation energy is concentrated in the historical operating data of the liquid-driven compressor. It is usually divided into characteristic frequency bands of every 100 Hz, such as 0-100 Hz, 100-200 Hz, etc. Characteristic frequency bands refer to multiple frequency intervals in which the pressure pulsation spectrum is divided according to a fixed bandwidth, and each interval contains a specific range of frequency components. Each operating condition refers to the operating state of the compressor under different load conditions. The number of operating conditions contained in each characteristic frequency band depends on the actual amount of data collected. These operating conditions are known operating condition data obtained by real-time collection of pressure sensors and flow meters.

[0095] In an embodiment of the present application, the system divides the complete pressure pulsation spectrum into several continuous frequency bands according to a preset frequency band division rule, then calculates the sum of the signal energy in each frequency band, selects the frequency band with the largest energy as the characteristic frequency band, and finally extracts the frequency corresponding to the highest energy point in the characteristic frequency band as the main peak frequency.

[0096] Step 502: Analyze the main peak frequency distribution patterns in different flow intervals based on the flow data and the main peak frequencies under corresponding operating conditions to generate a frequency offset feature library.

[0097] In step 502, the flow intervals are the numerically segmented ranges into which the compressor outlet flow data is divided. Each interval represents a flow variation range, and the division is based on the typical flow value distribution characteristics observed during actual compressor operation. The main peak frequency distribution pattern refers to the distribution characteristics of all main peak frequency values ​​within each flow interval, including central tendency and dispersion. This distribution pattern is derived from the distribution pattern obtained by statistically analyzing the main peak frequencies within the same flow interval in historical operating data. The frequency offset feature library is a database that stores the corresponding relationship between flow and main peak frequency under various operating conditions.

[0098] In an embodiment of the present application, the system divides the flow range into several intervals based on the statistical results of historical operating data, and counts the distribution of the main peak frequency in each interval. By analyzing the concentration trend and dispersion of the main peak frequency in different flow intervals, a database of the corresponding relationship between flow and frequency is established.

[0099] Step 503: Output the main frequency offset rule through the frequency offset feature library.

[0100] In an embodiment of the present application, the system performs curve fitting processing on the established flow-frequency relationship data to find the mathematical relationship between the flow change and the main peak frequency change, and stores the relationship in the form of a function in the feature library for query during real-time control. The specific implementation process is: first, the distribution of the main peak frequency in each flow interval is counted, and then a corresponding relationship table between the flow value and the frequency value is established, and finally, the mathematical relationship between the flow change and the frequency change is obtained through curve fitting. For example, in the flow range of 60-80m³ / min, the main peak frequency of a compressor is concentrated in the range of 145-155Hz. The relationship formula of frequency = 1.2×flow+65 is obtained through linear fitting. This formula is the output main frequency offset law.

[0101] Here's a specific example: Taking a certain type of liquid-driven compressor as an example, the system collects data showing a flow rate of 80 cubic meters per minute under the current operating conditions, and the pressure pulsation spectrum shows an obvious peak in the 100-200 Hz frequency band. Analysis has determined that the main peak frequency is 150 Hz. Based on three months of historical operating data analysis, when the flow rate is in the range of 70-90 cubic meters per minute, statistics show that the main peak frequency is mainly distributed in the range of 145-155 Hz, of which 150 Hz has the highest frequency, accounting for 65%. Therefore, 150 Hz is selected as the representative frequency of this flow range. By fitting the historical data using the least squares method, the relationship between the main peak frequency f and the flow rate Q is obtained as f=1.2Q+54, where f is in Hertz and Q is in cubic meters per minute. This formula indicates that for every increase of 1 cubic meter per minute in flow rate, the main peak frequency increases by an average of 1.2 Hz. After storing this relationship in the frequency offset feature library, when the system detects that the current flow rate is 80 cubic meters per minute, the reference frequency is calculated according to the formula as 1.2×80+54=150 Hz, which is consistent with the measured main peak frequency.

[0102] In the embodiment of the present application, the method establishes an accurate flow-frequency correspondence model through systematic data collection and analysis processing, provides a reliable regular basis for subsequent real-time control, and improves the accuracy and adaptability of airflow pulsation suppression.

[0103] In order to more accurately establish the correspondence between flow rate and main peak frequency, in some embodiments, step 502: analyzing the main peak frequency distribution morphology in different flow intervals based on the flow rate data and the main peak frequency under the corresponding operating conditions to generate a frequency offset feature library includes: Step 601: discretize the traffic data into multiple traffic intervals according to a preset division rule.

[0104] In step 601, flow rate interval division is a process that divides the continuous flow rate value into several range segments. Flow intervals refer to the flow rate range during compressor operation divided into several value ranges at fixed intervals. Each interval represents a flow rate variation range and is used to classify and count operating conditions.

[0105] In an embodiment of the present application, the system evenly divides the total flow range into several intervals according to the working flow range and operating characteristics of the compressor, and each interval contains a certain range of flow values ​​for subsequent statistical analysis.

[0106] Step 602: For each flow interval, count the distribution density of all main peak frequencies in the flow interval to generate a probability density distribution graph.

[0107] In step 602, distribution density statistics is a method for calculating the frequency of occurrence of each frequency value within a certain flow interval. A probability density distribution chart is a statistical chart that reflects the probability of occurrence of each main peak frequency value within a certain flow interval. The horizontal axis represents the frequency value and the vertical axis represents the probability density of occurrence. It is used to intuitively display the concentrated distribution of the main peak frequency.

[0108] In the embodiment of the present application, by analyzing the probability density distribution diagram, the frequency range segment with the highest frequency of occurrence is found, and this range is the area where the main peak frequency is most concentrated in the flow interval.

[0109] Step 603: Identify the frequency range corresponding to the probability density peak from the probability density distribution graph, and use the frequency range as the concentrated distribution interval of the main peak frequency.

[0110] In step 603 , the concentrated distribution interval refers to the frequency range where the main peak frequency appears most densely.

[0111] In the embodiment of the present application, by analyzing the probability density distribution diagram, the frequency range segment with the highest frequency of occurrence is found, and this range is the area where the main peak frequency is most concentrated in the flow interval.

[0112] Step 604: extracting the median frequency of the concentrated distribution interval as the representative frequency value of the corresponding flow interval.

[0113] In step 604, the median frequency of the concentrated distribution interval is the middle value of the frequency range where the main peak frequency occurs most densely. It is calculated by adding the upper and lower frequency limits of the interval and dividing by 2. For example, if the concentrated distribution interval is 150-155 Hz, the median frequency is (150 + 155) / 2 = 152.5 Hz. The representative frequency value is the frequency value that represents the typical pulsation characteristics of a flow range.

[0114] In the embodiment of the present application, the middle frequency value of the concentrated distribution interval is taken as the representative value of the flow interval, which can best reflect the main pulsation characteristics of the compressor under the flow rate.

[0115] Step 605: Map the flow interval and the representative frequency value to generate a frequency offset feature library.

[0116] In the embodiment of the present application, the system establishes a mapping relationship between each flow interval and its corresponding representative frequency value to form a queryable database for quickly obtaining the reference frequency during real-time control.

[0117] Here's a specific example: Continuing with the example of a certain type of liquid-driven compressor, the system first divides the flow data into multiple intervals of 20 cubic meters per minute, focusing on the flow range of 70-90 cubic meters per minute. For 50 sets of historical operating data collected within this interval, the number of occurrences of each main peak frequency is counted. A probability density distribution plot shows a significant peak in the 145-155 Hz range, with 150 Hz occurring the most frequently, at 32. 145-155 Hz is identified as the concentrated distribution interval of the main peak frequency, and its median frequency is calculated as 145 plus 155 divided by 2, which equals 150 Hz. This frequency is used as the representative frequency value for this flow range. The system maps the 70-90 cubic meters per minute flow range to the representative frequency value of 150 Hz and stores it in the feature library. Simultaneously, using the least squares method, the system derives the relationship between the main peak frequency f and the flow rate Q: f=1.2Q+54, where f represents the main peak frequency in hertz and Q represents the flow rate in cubic meters per minute. When the current flow rate is detected at 85 cubic meters per minute, the system calculates the base frequency to be 1.2 × 85 + 54 = 156 Hz based on this formula. It then queries the signature database to confirm that the flow rate falls within the 70-90 cubic meter range. The corresponding representative frequency of 150 Hz verifies this calculation, providing a reliable basis for subsequent control. The 20 cubic meter per minute interval is determined based on 30% of the compressor's normal operating flow range, ensuring sufficient data in each interval. The 145-155 Hz range is set based on the statistical results showing that data points within this range account for more than 80%.

[0118] In the embodiment of the present application, the method establishes an accurate flow-frequency correspondence through scientific statistical analysis, provides a reliable reference frequency for airflow pulsation suppression, and improves the accuracy and response speed of the control system.

[0119] In order to more accurately adjust the position of the movable baffle, in some embodiments, step 105: adjusting the position of the movable baffle based on the compensated target position adjustment signal includes: Step 701: Input the compensated target position adjustment signal to a drive circuit provided in a hydraulically driven compressor.

[0120] In step 701, the driving circuit refers to an electronic circuit that converts a control signal into a motor driving signal, and is responsible for converting a voltage-form regulating signal into a pulse sequence and direction signal that can be recognized by the stepping motor.

[0121] In an embodiment of the present application, the system transmits the adjustment signal after the deviation compensation calculation to the signal input end of the driving circuit. The signal includes information about the distance and direction that the baffle needs to move.

[0122] Step 702: The compensated target position adjustment signal is converted into a rotation angle instruction of the liquid-driven compressor through the driving circuit.

[0123] In step 702 , the rotation angle instruction is a motor control command generated by the driving circuit according to the voltage signal conversion.

[0124] In an embodiment of the present application, the driving circuit calculates the angle that the stepper motor needs to rotate according to the size of the input voltage signal and a preset conversion ratio, and determines the rotation direction according to the signal polarity.

[0125] Step 703: Adjust the rotation angle and rotation direction of the output shaft of the liquid-driven compressor according to the rotation angle instruction.

[0126] In step 703, output shaft rotation adjustment is the specific action of the motor executing the angle command. The rotation angle and direction of the hydraulic compressor output shaft refer to the specific angle value and direction that the stepper motor must rotate in response to the drive signal. The angle value is determined by the input voltage, and the direction is determined by the polarity of the control variable: positive polarity corresponds to clockwise rotation, and negative polarity corresponds to counterclockwise rotation.

[0127] In an embodiment of the present application, the stepper motor receives a pulse signal sent by a driving circuit, rotates precisely at a specified angle and direction, and drives the output shaft to rotate synchronously.

[0128] Step 704: The adjusted rotation angle is converted into an axial displacement of the screw nut through direct transmission between the output shaft of the liquid-driven compressor and the screw mechanism.

[0129] In step 704, direct transmission between the output shaft and the lead screw mechanism means that the stepper motor's output shaft directly drives the lead screw through a mechanical connection such as a coupling, without intermediate transmission devices such as a speed reducer, ensuring a 1:1 transmission of rotational motion. Axial displacement refers to the linear movement of the lead screw nut along the screw axis as the screw rotates. This distance is proportional to the screw's rotation angle, with the specific conversion relationship determined by the lead screw's lead. Axial displacement conversion is the process of converting rotational motion into linear motion.

[0130] In an embodiment of the present application, the motor output shaft is connected to the screw through a coupling, and the screw rotates to drive the nut to move axially, converting the rotation angle of the motor into a linear displacement of the nut.

[0131] Step 705: Based on the axial displacement, adjust the gap size between the movable baffle and the wall of the resonant cavity.

[0132] In step 705 , the gap size adjustment is an operation of changing the size of the air flow channel by displacing the baffle.

[0133] In an embodiment of the present application, the baffle connected to the lead screw nut moves with the nut, changing the distance from the wall of the resonance cavity, thereby adjusting the effective cross-sectional area through which the airflow passes.

[0134] Here's a specific example: After generating a compensated 9.5-volt target position adjustment signal, the system inputs this signal into a dedicated stepper motor drive circuit. This signal is converted into 1425 drive pulses based on a preset conversion relationship: 150 pulses per volt. The motor's rotation direction is determined to be forward based on the polarity of the control variable. These pulses drive the stepper motor, which has a step angle of 1.8 degrees and requires 200 pulses per revolution. Therefore, 1425 pulses produce 7.125 motor revolutions. The motor's output shaft is directly connected to a 5-mm lead screw via a coupling, converting the rotational motion into linear displacement of the screw nut. Each screw revolution corresponds to 5 mm of nut movement, so 7.125 revolutions translate to 35.625 mm of displacement. This displacement, through a connecting mechanism, drives the movable baffle, increasing the gap between the baffle and the resonant cavity wall from an initial 3 mm to 8.625 mm. The conversion ratio of 150 pulses per volt is determined based on motor parameters and system response requirements. The 5mm lead is a mechanical design parameter to ensure displacement accuracy meets control requirements. The entire process achieves precise conversion from electrical signal to mechanical displacement, enabling accurate adjustment of the airflow channel area.

[0135] In an embodiment of the present application, the method achieves precise adjustment of the size of the airflow channel through the precise conversion of electrical signals into mechanical displacements, ensuring that the airflow pulsation of the compressor is effectively suppressed, while ensuring the stability and reliability of the adjustment process.

[0136] Figure 2 This is a structural diagram of an air flow pulsation suppression system for a liquid-driven compressor provided in an embodiment of the present application, as shown in FIG. Figure 2 As shown, the system includes: The acquisition module 21 is used to acquire the pressure pulsation spectrum and flow rate data of the outlet pipeline of the liquid-driven compressor.

[0137] The first generating module 22 is configured to generate a main frequency deviation rule based on the pressure pulsation spectrum and the flow data.

[0138] The second generating module 23 is configured to generate a target position adjustment signal based on the main frequency offset rule and the main peak frequency of the pressure pulsation spectrum in combination with a fuzzy PID controller.

[0139] The monitoring module 24 is configured to monitor in real time the actual position of a movable baffle disposed in the resonance cavity of the liquid-driven compressor, and perform feedback compensation on the target position adjustment signal based on the actual position.

[0140] The adjustment module 25 is configured to adjust the position of the movable baffle based on the compensated target position adjustment signal to change the flow area of ​​the resonance cavity, thereby suppressing airflow pulsation in the outlet pipeline.

[0141] Figure 2 The air flow pulsation suppression system of a liquid-driven compressor can be implemented Figure 1 The implementation principles and technical effects of the method for suppressing airflow pulsation in a liquid-driven compressor described in the illustrated embodiment are not further elaborated. The specific manner in which the various modules and units of the airflow pulsation suppression system for a liquid-driven compressor in the aforementioned embodiment operate has been described in detail in the related embodiments of the method and will not be further elaborated here.

[0142] In one possible design, Figure 2 The air flow pulsation suppression system of a liquid-driven compressor of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0143] The processing component 32 is used to perform the above Figure 1 The embodiment provides a method for suppressing air flow pulsation in a liquid-driven compressor.

[0144] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0145] The storage component 31 is configured to store various types of data to support operations on the terminal. The storage component can be implemented by any type of volatile or non-volatile memory 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 read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0146] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0147] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0148] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0149] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0150] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The embodiment shown is a method for suppressing air flow pulsation in a liquid-driven compressor.

[0151] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0152] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0153] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for suppressing air flow pulsation in a liquid-driven compressor, characterized in that: include: Obtain the pressure pulsation spectrum and flow rate data of the outlet pipeline of the liquid-driven compressor; generating a main frequency deviation law based on the pressure pulsation spectrum and the flow data; Based on the main frequency offset law and the main peak frequency of the pressure pulsation spectrum, a target position adjustment signal is generated in combination with a fuzzy PID controller; monitoring in real time the actual position of a movable baffle disposed in a resonant cavity of the liquid-driven compressor, and performing feedback compensation on the target position adjustment signal based on the actual position; Based on the compensated target position adjustment signal, the position of the movable baffle is adjusted to change the flow area of ​​the resonance cavity, thereby suppressing air flow pulsation in the outlet pipeline.

2. The method according to claim 1, characterized in that The generating of the target position adjustment signal based on the main frequency offset rule and the main peak frequency of the pressure pulsation spectrum in combination with a fuzzy PID controller includes: According to the flow data, query the corresponding reference main peak frequency from the main frequency offset rule; Superimposing the reference main peak frequency and the preset offset to obtain a target resonant frequency; Subtracting the main peak frequency of the pressure pulsation spectrum from the target resonance frequency to obtain a frequency difference; The absolute value of the frequency difference is input into the input interface of the fuzzy PID controller, and a target position adjustment signal is output.

3. The method according to claim 2, characterized in that The step of inputting the absolute value of the frequency difference into an input interface of a fuzzy PID controller and outputting a target position adjustment signal comprises: Performing dynamic dead zone processing on the absolute value to obtain a valid difference; According to the effective difference, a corresponding fuzzy interval is matched from a control rule library of a fuzzy PID controller; According to the current operating condition of the liquid-driven compressor, an optimal parameter combination matching the fuzzy interval and the operating condition is selected from a plurality of preset parameter groups; Based on the optimal parameter combination, performing signal conversion on the effective difference to generate an initial position adjustment signal; Amplitude limiting processing is performed on the initial position adjustment signal to generate a target position adjustment signal.

4. The method according to claim 3, characterized in that The performing signal conversion on the effective difference based on the optimal parameter combination to generate an initial position adjustment signal includes: Performing weighted operations on the effective difference and the proportional coefficient, integral coefficient, and differential coefficient in the optimal parameter combination to generate a proportional term, an integral term, and a differential term; Performing superposition calculation on the proportional term, the integral term, and the differential term, and outputting an initial control variable; quantizing the initial control amount into a target pulse number according to the pulse equivalent resolution of the liquid-driven compressor; Based on the target pulse number and in combination with the polarity of the control amount, a pulse control sequence is generated, and the pulse control sequence is used as an initial position adjustment signal.

5. The method according to claim 1, wherein Generating a main frequency deviation rule based on the pressure pulsation spectrum and the flow data includes: Dividing the pressure pulsation spectrum into a plurality of characteristic frequency bands, and extracting the main peak frequency under each operating condition from the plurality of characteristic frequency bands; Analyze the main peak frequency distribution patterns in different flow intervals based on the flow data and the main peak frequencies under corresponding operating conditions to generate a frequency offset feature library; The main frequency offset rule is output through the frequency offset feature library.

6. The method according to claim 5, characterized in that The method of analyzing the main peak frequency distribution patterns of different flow intervals based on the flow data and the main peak frequencies under corresponding operating conditions to generate a frequency offset feature library includes: Discretize the flow data into multiple flow intervals according to a preset division rule; For each flow interval, the distribution density of all main peak frequencies in the flow interval is counted to generate a probability density distribution graph; Identifying a frequency range corresponding to a probability density peak from the probability density distribution graph, and using the frequency range as a concentrated distribution interval of a main peak frequency; Extracting the median frequency of the concentrated distribution interval as the representative frequency value of the corresponding flow interval; The flow interval is mapped to the representative frequency value to generate a frequency offset feature library.

7. The method according to claim 1, characterized in that The adjusting the position of the movable baffle based on the compensated target position adjustment signal includes: Inputting the compensated target position adjustment signal into a drive circuit provided in the liquid-driven compressor; converting the compensated target position adjustment signal into a rotation angle instruction of the liquid-driven compressor through the drive circuit; According to the rotation angle instruction, adjusting the rotation angle and rotation direction of the output shaft of the liquid-driven compressor; The adjusted rotation angle is converted into an axial displacement of the screw nut through direct transmission between the output shaft of the liquid-driven compressor and the screw mechanism; Based on the axial displacement, the size of the gap between the movable baffle and the wall of the resonant cavity is adjusted.

8. An air flow pulsation suppression system for a liquid-driven compressor, characterized in that: include: An acquisition module, used to acquire pressure pulsation spectrum and flow data of the outlet pipeline of the liquid-driven compressor; A first generating module, configured to generate a main frequency deviation rule based on the pressure pulsation spectrum and the flow data; A second generating module is configured to generate a target position adjustment signal based on the main frequency offset rule and the main peak frequency of the pressure pulsation spectrum in combination with a fuzzy PID controller; a monitoring module, configured to monitor in real time the actual position of a movable baffle disposed in a resonance cavity of the liquid-driven compressor, and perform feedback compensation on the target position adjustment signal based on the actual position; The regulating module is used to regulate the position of the movable baffle based on the compensated target position regulation signal to change the flow area of ​​the resonance cavity, thereby suppressing the air flow pulsation of the outlet pipeline.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement the method for suppressing airflow pulsation of a liquid-driven compressor as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the method for suppressing airflow pulsation of a liquid-driven compressor according to any one of claims 1 to 7 is implemented.

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