Pressure-controlled intelligent micro-pump and pressure control method

Abstract

The application discloses a pressure control intelligent micro pump and a pressure control method, the method collects pressure data, environmental parameter data and running state data through a data acquisition module, a data analysis module calculates an adjustment value of a driving frequency and output power and a pipeline pressure stability factor according to the pressure data and a pipeline pressure fluctuation threshold value, a control center adjusts the driving frequency and output power of the pressure control intelligent micro pump according to the adjustment value and the pipeline pressure stability factor, and judges whether to start a pressure stabilizing buffer module, a health assessment module calculates a health index based on pump body temperature, vibration frequency and energy efficiency data and judges whether to switch a standby pump, in addition, an emergency stop protection mechanism is triggered when pressure overrun or failure is detected, and an alarm signal is sent to a computer terminal; the application realizes high-precision pressure control, stable pipeline pressure and real-time monitoring of the health state of equipment through the pressure control intelligent micro pump, and significantly improves the safety and reliability of a fluid system.

Description

Technical Field

[0001] This invention belongs to the field of industrial automation control technology, and specifically discloses a pressure-controlled intelligent micro pump and a pressure control method. Background Technology

[0002] The pressure-controlled intelligent micro pump features a simple design, small size, and light weight, making it easy to integrate into various devices. In fluid control systems, pressure runaway can damage equipment and pipelines; pressure control can prevent this, protecting the safety of equipment and operators.

[0003] In existing technologies, pressure-controlled intelligent micro pumps mostly use fixed-frequency drive or simple closed-loop feedback control, which are difficult to cope with complex working conditions such as fluid viscosity, changes in ambient temperature and fluctuations in pipeline resistance. This can easily lead to pressure exceeding limits, increased pipeline vibration and shortened equipment life. In addition, the lack of real-time monitoring and fault warning mechanisms for the pump's health status makes it difficult to ensure the continuous and stable operation of the system.

[0004] Therefore, it is necessary to invent a pressure-controlled intelligent micro pump and a pressure control method to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies in the prior art, this invention provides a pressure-controlled intelligent micro pump and a pressure control method. A data acquisition module collects pressure data, environmental parameter data, and operational status data. A data analysis module calculates adjustment values ​​for the drive frequency and output power, as well as a pipeline pressure stability factor, based on the pressure data and pipeline pressure fluctuation threshold. The control center adjusts the drive frequency and output power of the pressure-controlled intelligent micro pump based on the adjustment values ​​and the pipeline pressure stability factor, and determines whether to activate the pressure stabilization buffer module. A health assessment module calculates a health index based on pump body temperature, vibration frequency, and energy efficiency data, and determines whether to switch to a standby pump. Furthermore, an emergency stop protection mechanism is triggered when pressure over-limits or a fault is detected, and an alarm signal is sent to the computer terminal. This invention achieves high-precision pressure control, stable pipeline pressure, and real-time monitoring of equipment health status through the pressure-controlled intelligent micro pump, significantly improving the safety and reliability of the fluid system and effectively solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a pressure control method for a pressure-controlled intelligent micro pump, specifically including the following steps:

[0007] S1. The data acquisition module acquires pressure data, environmental parameter data, and operating status data in real time.

[0008] S2. The data analysis module calculates the adjustment values ​​of drive frequency and output power based on pressure data; and calculates the pipeline pressure stability factor based on operating status data and pipeline pressure fluctuation thresholds stored in the database.

[0009] S3, the micro pump control module adjusts the driving frequency and output power of the pressure-controlled intelligent micro pump, and the pressure stabilization and buffer module determines whether to activate the pressure stabilization and buffer measures based on the pipeline pressure stability factor.

[0010] S4. The health assessment module calculates the health index of the pressure-controlled intelligent micro pump based on the operating status data, and determines whether it is necessary to switch to the standby pump in combination with the preset health threshold.

[0011] S5. Continuously monitor pressure fluctuations. When pressure exceeds the limit or system failure is detected, trigger the emergency stop protection mechanism and send an alarm signal to the computer terminal.

[0012] The specific calculation process for the adjustment values ​​of the driving frequency and output power includes:

[0013] A dynamic pressure correction factor is calculated based on pressure data, and this dynamic pressure correction factor serves as the basis for adjusting the drive frequency and output power.

[0014] The dynamic pressure correction factor is matched with the calibration parameters stored in the database, and the corresponding drive frequency adjustment coefficient and power compensation value are calculated.

[0015] The adjustment values ​​for drive frequency and output power are calculated based on the drive frequency adjustment coefficient and power compensation value.

[0016] The dynamic pressure correction factor is calculated as follows:

[0017] Based on historical data, establish a mapping set between historical ambient temperature, pipeline resistance, and fluid viscosity and ambient temperature compensation coefficient, pipeline resistance compensation coefficient, and viscosity correction factor. Based on the mapping set and real-time data, obtain the corresponding compensation coefficient and correction factor.

[0018] The dynamic pressure correction factor is calculated by substituting the ambient temperature compensation coefficient, pipeline resistance compensation coefficient, and viscosity correction factor into the calculation model of the dynamic pressure correction factor.

[0019] The health index of the pressure-controlled intelligent micro pump is calculated as follows:

[0020] The data acquisition module acquires real-time pump body temperature, vibration amplitude, pump body rated temperature, and energy consumption data.

[0021] The energy efficiency deviation rate is calculated based on energy consumption data. The heat load attenuation coefficient is derived based on the material's thermal expansion coefficient and heat dissipation characteristics. The vibration compensation factor is determined by referring to the vibration level and compensation factor comparison table in the mechanical handbook. A mapping set of energy efficiency and energy efficiency correction factor is established based on historical data. The corresponding correction factor is obtained based on the mapping set and real-time data.

[0022] The health index is obtained by substituting the heat load attenuation coefficient, real-time pump body temperature, rated temperature, vibration amplitude, vibration compensation factor, energy efficiency deviation rate, and energy efficiency correction factor into the health index calculation model.

[0023] Based on the above embodiments, the pressure data specifically includes: real-time fluid pressure value at the output of the pressure-controlled intelligent micro pump, real-time pipeline pressure value, pipeline pressure fluctuation frequency, peak pressure, and pressure gradient change rate; the operating status data specifically includes: pump body temperature, vibration frequency, and energy consumption data; the environmental parameter data specifically includes fluid viscosity, ambient temperature, and pipeline resistance compensation coefficient.

[0024] Based on the above embodiments, the pipeline pressure stability factor is specifically calculated as follows:

[0025] The data acquisition module acquires pipeline pressure fluctuation frequency, peak pressure, valley pressure, pressure gradient change rate, fluid viscosity, pipeline material parameters, and geometric dimensions.

[0026] The damping coefficient is directly calculated based on fluid viscosity, pipeline material parameters, and geometric dimensions using fluid mechanics formulas.

[0027] The pipeline pressure stability factor is calculated by substituting the pipeline pressure fluctuation frequency, peak pressure, valley pressure, pressure gradient change rate, and damping coefficient into the pipeline pressure stability factor calculation model.

[0028] Based on the above embodiments, the specific analysis method for determining whether to activate pressure stabilization and buffering measures according to the pipeline pressure stability factor is as follows:

[0029] The pipeline pressure stability factor is calculated based on the pipeline pressure fluctuation frequency, peak pressure, and pressure gradient change rate, and compared with a preset fluctuation threshold. If the pipeline pressure stability factor is lower than the fluctuation threshold, the pressure stabilization buffer module is activated; if the pipeline pressure stability factor is higher than the fluctuation threshold, the current control mode is maintained.

[0030] Based on the above embodiments, the specific analysis method for determining whether to switch to the standby pump is as follows:

[0031] The system compares the health index of the pressure-controlled intelligent micropump with a preset health threshold. If the health index of the pressure-controlled intelligent micropump is lower than the health threshold, the backup pump is activated. If the health index of the pressure-controlled intelligent micropump is higher than the health threshold, the current mode is maintained.

[0032] Based on the above embodiments, the specific analysis method for triggering the emergency stop protection mechanism and sending an alarm signal to the computer terminal is as follows:

[0033] Based on the comparison between real-time pressure data and the preset safe pressure threshold range, when the pressure value is detected to exceed the safe pressure threshold range or the operating status data is abnormal, the emergency stop protection mechanism is triggered; the emergency stop protection mechanism includes immediately cutting off the drive power of the pressure-controlled intelligent micro pump and activating the mechanical braking device to lock the pump body;

[0034] Simultaneously, an alarm signal is sent to the computer terminal, the alarm signal including the fault type code, the pressure exceeding the limit value, the fault timestamp, and the operating status data;

[0035] After the alarm signal is sent, the control center records the fault data to the database and starts the backup pump to maintain system operation.

[0036] Based on the above embodiments, the pressure-controlled intelligent micro pump includes:

[0037] Data acquisition module: used to acquire pressure data, environmental parameter data, and operating status data in real time;

[0038] Data analysis module: used to calculate the adjustment values ​​of drive frequency and output power based on pressure data; and to calculate the pipeline pressure stability factor based on operating status data and pipeline pressure fluctuation thresholds stored in the database.

[0039] Health assessment module: Used to calculate the health index of the pressure-controlled intelligent micro pump based on the operating status data, and combined with the preset health threshold to determine whether it is necessary to switch to the standby pump;

[0040] Pressure stabilization and buffering module: used to determine whether to activate pressure stabilization and buffering measures based on pipeline pressure stability factors;

[0041] Miniature pump control module: Used to adjust the drive frequency and output power of the pressure-controlled intelligent miniature pump according to the adjustment values ​​of the drive frequency and output power.

[0042] The technical effects and advantages of this invention are as follows:

[0043] 1. High-precision pressure control: The data acquisition module collects pressure data, environmental parameter data, and operating status data in real time. Combined with the calculations of the data analysis module, it can accurately adjust the drive frequency and output power of the intelligent micro pump, thereby achieving high-precision pressure control.

[0044] 2. Stabilize pipeline pressure: The data analysis module calculates the pipeline pressure stability factor based on the pipeline pressure fluctuation threshold. The control center then determines whether to activate the pressure stabilization buffer module to effectively stabilize pipeline pressure and reduce the impact of pressure fluctuations on equipment and pipelines.

[0045] 3. Real-time monitoring of equipment health status: The health assessment module calculates the health index based on pump body temperature, vibration frequency and energy efficiency data, which can monitor the health status of the pressure-controlled intelligent micro pump in real time, detect potential faults in time, and improve the reliability and service life of the equipment.

[0046] 4. Fault warning and emergency stop protection: When pressure over-limit or system fault is detected, the emergency stop protection mechanism is triggered, the drive power is immediately cut off and the mechanical braking device is activated to lock the pump body. At the same time, an alarm signal is sent to the computer terminal to realize fault warning and rapid response. Attached Figure Description

[0047] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the overall structure of the present invention.

[0049] Figure 2 This is a flowchart illustrating the overall steps of the present invention. Detailed Implementation

[0050] 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.

[0051] This invention provides, for example Figure 1 The pressure-controlled intelligent micro pump shown includes a data acquisition module, a data analysis module, a health assessment module, a pressure stabilizing buffer module, and a micro pump control module;

[0052] In a more specific application of the present invention, the data acquisition module is used to acquire pressure data, environmental parameter data, and operating status data in real time. The pressure data specifically includes: real-time fluid pressure value at the output of the pressure-controlled intelligent micro pump, real-time pipeline pressure value, pipeline pressure fluctuation frequency, peak pressure, and pressure gradient change rate. The operating status data specifically includes: pump body temperature, vibration frequency, and energy consumption data. The environmental parameter data specifically includes fluid viscosity, ambient temperature, and pipeline resistance compensation coefficient.

[0053] In a more specific application of the present invention, the data analysis module is used to calculate the adjustment values ​​of the drive frequency and output power based on the pressure data; and to calculate the pipeline pressure stability factor based on the operating status data and the pipeline pressure fluctuation threshold stored in the database.

[0054] In a more specific application of the present invention, the micro pump control module is used to adjust the driving frequency and output power of the pressure-controlled intelligent micro pump according to the adjustment values ​​of the driving frequency and output power, and the pressure stabilization and buffer module is used to determine whether to enable the pressure stabilization and buffer measures based on the pipeline pressure stability factor.

[0055] In a more specific application of the present invention, the health assessment module is used to calculate the health index of the pressure-controlled intelligent micro pump based on the operating status data, and, in combination with a preset health threshold, determine whether it is necessary to switch to the standby pump.

[0056] It should be further noted that this device also requires the cooperation of a database and a computer terminal;

[0057] In a more specific application of the present invention, the database is used to store health thresholds, fluctuation threshold ranges, safe pressure threshold ranges, operating status data, and calibration parameters;

[0058] In a more specific application of the present invention, the computer terminal is used to receive alarm signals and display the fault type, pressure over-limit value and timestamp;

[0059] like Figure 2 As shown, the pressure control method of the pressure-controlled intelligent micro pump specifically includes the following steps:

[0060] S1. The data acquisition module acquires pressure data, environmental parameter data, and operating status data in real time.

[0061] In the preferred embodiment of this application, the pressure data specifically includes: real-time fluid pressure value at the output of the pressure-controlled intelligent micro pump, real-time pipeline pressure value, pipeline pressure fluctuation frequency, peak pressure, and pressure gradient change rate; the operating status data specifically includes: pump body temperature, vibration frequency, and energy consumption data; the environmental parameter data specifically includes fluid viscosity, ambient temperature, and pipeline resistance compensation coefficient.

[0062] Furthermore, in the above technical solution, the real-time fluid pressure value at the output of the pressure-controlled intelligent micro pump is monitored in real time by a piezoelectric pressure sensor installed at the output of the pump. The real-time pipeline pressure value is obtained by installing distributed pressure sensors near key pipeline nodes, such as elbows and valves. The pipeline pressure fluctuation frequency is extracted from the collected raw pressure data using a Fourier transform (FFT) algorithm. The peak and valley pressures are calculated dynamically within a window based on the real-time pressure data stream using a sliding window algorithm. The pressure gradient change rate is based on the time-series data of the pressure sensor, calculated by measuring the pressure change per unit time. The following parameters were obtained: Pump body temperature was acquired using a PT100 thermal resistance sensor installed on the easily heated parts of the pump body; vibration frequency was obtained by measuring the XYZ triaxial vibration acceleration using a piezoelectric accelerometer installed on the pump body base and obtaining the vibration frequency through frequency domain analysis; energy consumption data was obtained by monitoring the input current and voltage of the micropump drive motor using a Hall current sensor to calculate real-time power and cumulative energy consumption; fluid viscosity was directly measured using an online rotary viscometer, ambient temperature was acquired using a digital temperature sensor, and the pipeline resistance compensation coefficient was obtained through experimental calibration: measuring the pipeline pressure drop at a specific flow rate and combining it with the Darcy-Weisbach formula.

[0063] Furthermore, in the above technical solution, the Darcy-Weisbach formula is: In the formula, ρ is the pipeline resistance compensation coefficient, ΔP is the pressure change, D is the pipeline diameter, L is the pipeline length, and ρ fluid ρ is the current fluid density, and v is the fluid velocity.

[0064] S2. The data analysis module calculates the adjustment values ​​of drive frequency and output power based on pressure data; and calculates the pipeline pressure stability factor based on operating status data and pipeline pressure fluctuation thresholds stored in the database.

[0065] In a preferred embodiment of this application, the specific calculation process for the adjustment values ​​of the driving frequency and output power includes:

[0066] A dynamic pressure correction factor is calculated based on pressure data and environmental parameter data, and this dynamic pressure correction factor serves as the basis for adjusting the drive frequency and output power.

[0067] The dynamic pressure correction factor is matched with the calibration parameters stored in the database, and the corresponding drive frequency adjustment coefficient and power compensation value are calculated.

[0068] The adjustment values ​​for drive frequency and output power are calculated based on the drive frequency adjustment coefficient and power compensation value.

[0069] It should be further explained that the calculation model for the dynamic pressure correction factor is as follows: In the formula, P is the dynamic pressure correction factor, and α P β represents the fluid viscosity deviation rate. P ρ is the ambient temperature compensation coefficient, ρ is the pipeline resistance compensation coefficient, and μ is the preset viscosity correction factor.

[0070] In the preferred embodiment of this application, the specific analysis method for calculating the adjustment values ​​of the drive frequency and output power based on the drive frequency adjustment coefficient and power compensation value is as follows:

[0071] Drive frequency adjustment value calculation:

[0072] Let the basic driving frequency be f. base The driving frequency adjustment coefficient is K. f ;

[0073] Adjusted drive frequency f adjusted f adjusted =f base ·K f , where K f Determined by the dynamic pressure correction factor P, the mapping rule is as follows: In the formula, α is the frequency compensation coefficient, and P... low P is the lower limit threshold of the dynamic pressure correction factor. high This is the upper limit threshold for the dynamic pressure correction factor;

[0074] Parameter example: P low =0.5, P high =5.0, α=0.2, K max =2.0;

[0075] Output power adjustment value calculation:

[0076] Let the base output power be W. base The power compensation value is ΔW;

[0077] The adjusted output power is: W adjusted =W base +ΔW, where ΔW is dynamically calculated based on the interval of ΔP: In the formula, β is the power compensation coefficient, and ΔW max This represents the maximum power compensation value.

[0078] Example parameters: β=0.5, ΔW max =10W;

[0079] Example of calculating adjustment values ​​for drive frequency and output power:

[0080] Parameter setting: α P =0.5, β P=2.0, ρ=1.0, μ=0.3, α=0.2, β=0.5, K max =2.0, P low =0.5, P high =5.0, ΔW max =10W, base drive frequency f base =100Hz, basic output power W base =50W;

[0081] Calculation process:

[0082] P=1 / (0.5×2)1 / 2+ln[1+(0.3+1) / ((0.5×2)1 / 2+(0.5×1)1 / 2)]≈1+ln(1+1.3 / 1.707)≈1.57;

[0083] P low <P≤P high ;

[0084] K f =1+α·(PP low =1 + 0.2 × (1.57 - 0.5) = 1.214;

[0085] f adjusted =f base ·K f =1.214×100=121.4Hz;

[0086] ΔW=β·(PP low = 0.5 × (1.57 - 0.5) ≈ 0.54;

[0087] W adjusted =W base +ΔW=50+0.54=50.54W;

[0088] In conclusion, the drive frequency was adjusted to 121.4Hz and the output power was adjusted to 50.54W.

[0089] In the preferred embodiment of this application, the pipeline pressure stability factor is specifically calculated as follows:

[0090] The data acquisition module acquires pipeline pressure fluctuation frequency, peak pressure, valley pressure, pressure gradient change rate, fluid viscosity, pipeline material parameters, and geometric dimensions.

[0091] The damping coefficient is directly calculated based on fluid viscosity, pipeline material parameters, and geometric dimensions using fluid mechanics formulas.

[0092] The pipeline pressure stability factor is calculated by substituting the pipeline pressure fluctuation frequency, peak pressure, valley pressure, pressure gradient change rate, and damping coefficient into the pipeline pressure stability factor calculation model.

[0093] It should be further explained that the calculation model for the pipeline pressure stability factor is as follows: In the formula, S is the pipeline pressure stability factor, λ is the damping coefficient, and F... p P is the frequency of pipeline pressure fluctuation. max With P min Let represent the peak pressure and the trough pressure, respectively, and ∇P be the rate of change of the pressure gradient.

[0094] Example of pipeline pressure stability factor calculation:

[0095] Parameter settings: λ=0.8, F p =2Hz, P max =150kPa, P min =145kPa, ∇P=5kPa / s;

[0096] Calculation process: S = (0.8 × 2) / ((150 - 145) 2 +5 2 ) 1 / 2 ≈1.6 / 7.07≈0.226;

[0097] Conclusion: The pipeline pressure stability factor is 0.226 under the current environment.

[0098] S3, the micro pump control module adjusts the driving frequency and output power of the pressure-controlled intelligent micro pump, and the pressure stabilization and buffer module determines whether to activate the pressure stabilization and buffer measures based on the pipeline pressure stability factor.

[0099] In the preferred embodiment of this application, the specific analysis method for determining whether to activate pressure stabilization and buffering measures based on the pipeline pressure stability factor is as follows:

[0100] The pipeline pressure stability factor is calculated based on the pipeline pressure fluctuation frequency, peak pressure, and pressure gradient change rate, and compared with a preset fluctuation threshold. If the pipeline pressure stability factor is lower than the fluctuation threshold, the pressure stabilization buffer module is activated; if the pipeline pressure stability factor is higher than the fluctuation threshold, the current control mode is maintained.

[0101] S4. The health assessment module calculates the health index of the pressure-controlled intelligent micro pump based on the operating status data, and determines whether it is necessary to switch to the standby pump in combination with the preset health threshold.

[0102] In the preferred embodiment of this application, the health index of the pressure-controlled intelligent micro pump is specifically calculated as follows:

[0103] The data acquisition module acquires real-time pump body temperature, vibration amplitude, pump body rated temperature, and energy consumption data.

[0104] The energy efficiency deviation rate is calculated based on energy consumption data. The heat load attenuation coefficient is derived based on the material's thermal expansion coefficient and heat dissipation characteristics. The vibration compensation factor is determined by referring to the vibration level and compensation factor comparison table in the mechanical handbook. A mapping set of energy efficiency and energy efficiency correction factor is established based on historical data. The corresponding correction factor is obtained based on the mapping set and real-time data.

[0105] The health index is obtained by substituting the heat load attenuation coefficient, real-time pump body temperature, rated temperature, vibration amplitude, vibration compensation factor, energy efficiency deviation rate, and energy efficiency correction factor into the health index calculation model.

[0106] It should be further explained that the calculation model for the health index is as follows: In the formula, H represents the health index, and α... h β is the heat load attenuation coefficient, T is the real-time pump body temperature, T0 is the rated temperature, V is the vibration amplitude, and β is the vibration amplitude. h γ is the vibration compensation factor, E is the energy efficiency deviation rate, and γ is the energy efficiency correction factor.

[0107] Example of health index calculation:

[0108] Parameter setting: α h =0.8, T=70℃, T0=100℃, V=0.5mm / s, β h =0.3, E=0.1, γ=0.2;

[0109] Calculation process: H = 0.8 × e -70 / 100 +(0.5×0.3+1) 2 / (0.1 2 +0.2 2 +1) 1 / 2 ≈0.4 + 1.32 / 1.02 ≈ 1.69;

[0110] Conclusion: The health index under these conditions is 1.69;

[0111] In the preferred embodiment of this application, the specific analysis method for determining whether to switch to the standby pump is as follows:

[0112] The system compares the health index of the pressure-controlled intelligent micro pump with a preset health threshold. If the health index of the pressure-controlled intelligent micro pump is lower than the health threshold, the backup pump is activated. If the health index of the pressure-controlled intelligent micro pump is higher than the health threshold, the current mode is maintained.

[0113] Furthermore, in the above technical solution, the health threshold H threshold Calibration was performed based on historical data.

[0114] S5. Continuously monitor pressure fluctuations. When pressure exceeds limits or system malfunction is detected, trigger the emergency stop protection mechanism and send an alarm signal to the computer terminal.

[0115] In the preferred embodiment of this application, the triggering of the emergency stop protection mechanism and the sending of an alarm signal to the computer terminal are specifically analyzed as follows:

[0116] Based on the comparison between real-time pressure data and the preset safe pressure threshold range, when the pressure value is detected to exceed the safe pressure threshold range or the operating status data is abnormal, the emergency stop protection mechanism is triggered; the emergency stop protection mechanism includes immediately cutting off the drive power of the pressure-controlled intelligent micro pump and activating the mechanical braking device to lock the pump body;

[0117] Simultaneously, an alarm signal is sent to the computer terminal, the alarm signal including the fault type code, the pressure exceeding the limit value, the fault timestamp, and the operating status data;

[0118] After the alarm signal is sent, the control center records the fault data to the database and starts the backup pump to maintain system operation.

[0119] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A pressure control method for a pressure-controlled intelligent micro pump, characterized in that, Specifically, the following steps are included: S1. The data acquisition module acquires pressure data, environmental parameter data, and operating status data in real time. S2. The data analysis module calculates the adjustment values ​​of drive frequency and output power based on pressure data and environmental parameter data; it also calculates the pipeline pressure stability factor based on operating status data and pipeline pressure fluctuation thresholds stored in the database. S3, the micro pump control module adjusts the driving frequency and output power of the pressure-controlled intelligent micro pump, and the pressure stabilization and buffer module determines whether to activate the pressure stabilization and buffer measures based on the pipeline pressure stability factor. S4. The health assessment module calculates the health index of the pressure-controlled intelligent micro pump based on the operating status data, and determines whether it is necessary to switch to the standby pump in combination with the preset health threshold. S5. Continuously monitor pressure fluctuations. When pressure exceeds the limit or system failure is detected, trigger the emergency stop protection mechanism and send an alarm signal to the computer terminal. The specific calculation process for the adjustment values ​​of the driving frequency and output power includes: A dynamic pressure correction factor is calculated based on pressure data, and this dynamic pressure correction factor serves as the basis for adjusting the drive frequency and output power. The dynamic pressure correction factor is matched with the calibration parameters stored in the database, and the corresponding drive frequency adjustment coefficient and power compensation value are calculated. The adjustment values ​​for drive frequency and output power are calculated based on the drive frequency adjustment coefficient and power compensation value. The dynamic pressure correction factor is calculated as follows: Based on historical data, establish a mapping set between historical ambient temperature, pipeline resistance, and fluid viscosity and ambient temperature compensation coefficient, pipeline resistance compensation coefficient, and viscosity correction factor. Based on the mapping set and real-time data, obtain the corresponding compensation coefficient and correction factor. The calculation model for the dynamic pressure correction factor is as follows: In the formula, P is the dynamic pressure correction factor, and α P β represents the fluid viscosity deviation rate. P ρ is the ambient temperature compensation coefficient, ρ is the pipeline resistance compensation coefficient, and μ is the preset viscosity correction factor. The dynamic pressure correction factor is calculated by substituting the ambient temperature compensation coefficient, pipeline resistance compensation coefficient, and viscosity correction factor into the calculation model of the dynamic pressure correction factor. The health index of the pressure-controlled intelligent micro pump is calculated as follows: The data acquisition module acquires real-time pump body temperature, vibration amplitude, pump body rated temperature, and energy consumption data. The energy efficiency deviation rate is calculated based on energy consumption data. The heat load attenuation coefficient is derived based on the material's thermal expansion coefficient and heat dissipation characteristics. The vibration compensation factor is determined by referring to the vibration level and compensation factor comparison table in the mechanical handbook. A mapping set of energy efficiency and energy efficiency correction factor is established based on historical data. The corresponding correction factor is obtained based on the mapping set and real-time data. The health index is obtained by substituting the heat load attenuation coefficient, real-time pump body temperature, rated temperature, vibration amplitude, vibration compensation factor, energy efficiency deviation rate, and energy efficiency correction factor into the health index calculation model. The calculation model for the health index is as follows: In the formula, H represents the health index, and α... h β is the heat load attenuation coefficient, T is the real-time pump body temperature, T0 is the rated temperature, V is the vibration amplitude, and β is the vibration amplitude. h γ is the vibration compensation factor, E is the energy efficiency deviation rate, and γ is the energy efficiency correction factor.

2. The pressure control method of the pressure-controlled intelligent micro pump as described in claim 1, characterized in that: The pressure data specifically includes: real-time fluid pressure value at the output of the pressure-controlled intelligent micro pump, real-time pipeline pressure value, pipeline pressure fluctuation frequency, peak pressure, and pressure gradient change rate; the operating status data specifically includes: pump body temperature, vibration frequency, and energy consumption data; the environmental parameter data specifically includes fluid viscosity, ambient temperature, and pipeline resistance compensation coefficient.

3. The pressure control method of the pressure-controlled intelligent micro pump as described in claim 1, characterized in that: The pipeline pressure stability factor is calculated as follows: The data acquisition module acquires pipeline pressure fluctuation frequency, peak pressure, valley pressure, pressure gradient change rate, fluid viscosity, pipeline material parameters, and geometric dimensions. The damping coefficient is directly calculated based on fluid viscosity, pipeline material parameters, and geometric dimensions using fluid mechanics formulas. The pipeline pressure stability factor is calculated by substituting the pipeline pressure fluctuation frequency, peak pressure, valley pressure, pressure gradient change rate, and damping coefficient into the pipeline pressure stability factor calculation model.

4. The pressure control method of the pressure-controlled intelligent micro pump as described in claim 1, characterized in that: The specific analysis method for determining whether to activate pressure stabilization and buffering measures based on pipeline pressure stability factors is as follows: The pipeline pressure stability factor is calculated based on the pipeline pressure fluctuation frequency, peak pressure, and pressure gradient change rate, and compared with a preset fluctuation threshold. If the pipeline pressure stability factor is lower than the fluctuation threshold, the pressure stabilization buffer module is activated; if the pipeline pressure stability factor is higher than the fluctuation threshold, the current control mode is maintained.

5. The pressure control method of the pressure-controlled intelligent micro pump as described in claim 1, characterized in that: The specific analysis method for determining whether to switch to the standby pump is as follows: The system compares the health index of the pressure-controlled intelligent micropump with a preset health threshold. If the health index of the pressure-controlled intelligent micropump is lower than the health threshold, the backup pump is activated. If the health index of the pressure-controlled intelligent micropump is higher than the health threshold, the current mode is maintained.

6. The pressure control method of the pressure-controlled intelligent micro pump as described in claim 1, characterized in that: The specific analysis method for triggering the emergency stop protection mechanism and sending an alarm signal to the computer terminal is as follows: Based on the comparison between real-time pressure data and the preset safe pressure threshold range, when the pressure value is detected to exceed the safe pressure threshold range or the operating status data is abnormal, the emergency stop protection mechanism is triggered; the emergency stop protection mechanism includes immediately cutting off the drive power of the pressure-controlled intelligent micro pump and activating the mechanical braking device to lock the pump body; Simultaneously, an alarm signal is sent to the computer terminal, the alarm signal including the fault type code, the pressure exceeding the limit value, the fault timestamp, and the operating status data; After the alarm signal is sent, the control center records the fault data to the database and starts the backup pump to maintain system operation.

7. A pressure-controlled intelligent micro pump, employing the pressure control method of the pressure-controlled intelligent micro pump according to any one of claims 1-6, characterized in that: include: Data acquisition module: used to acquire pressure data, environmental parameter data, and operating status data in real time; Data analysis module: used to calculate the adjustment values ​​of drive frequency and output power based on pressure data; and to calculate the pipeline pressure stability factor based on operating status data and pipeline pressure fluctuation thresholds stored in the database. Health assessment module: Used to calculate the health index of the pressure-controlled intelligent micro pump based on the operating status data, and combined with the preset health threshold to determine whether it is necessary to switch to the standby pump; Pressure stabilization and buffering module: used to determine whether to activate pressure stabilization and buffering measures based on pipeline pressure stability factors; Miniature pump control module: Used to adjust the drive frequency and output power of the pressure-controlled intelligent miniature pump according to the adjustment values ​​of the drive frequency and output power.

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