A method for automatic parameter adjustment for cryogenic operation of a fluid system

Abstract

The application relates to the technical field of automatic control of fluid systems, and discloses a parameter automatic adjusting method for low-temperature operation of a fluid system, which comprises the following steps: calculating a feedback deviation sequence according to a target set value and a feedback sampling value; isolating a slow-changing trend component and a fast component sequence through a parallel window queue; adjusting a hysteresis judgment threshold by using fluctuation energy of the fast component, and adjusting a short-period window length by using an absolute value of the slow-changing trend, so as to cooperatively judge a motion hysteresis state and a constraint level; searching for a gain correction coefficient to correct a control output when the state takes effect, and generating a driving control instruction. The application eliminates time-domain aliasing distortion of a signal, can accurately suppress extremely low-frequency physical sticking and extremely high-frequency phase change disturbance without adding external physical sensors, shortens system convergence time, suppresses overshoot, eliminates high-frequency limiting oscillation of a control loop near a balance point, and maintains adjusting quality.

Description

Technical Field

[0001] This invention relates to an automatic parameter adjustment method for cryogenic operation of fluid systems, belonging to the field of fluid system automation control technology. Background Technology

[0002] When fluid transport and transfer systems operate under cryogenic and high-pressure liquefaction conditions, they typically rely on regulating loops to stabilize pressure and flow. The control system acquires target setpoints and feedback sampled values, calculates feedback deviations, and then generates control commands according to preset control gains to drive valve actions. Under normal steady-state conditions, this closed-loop regulation method based on feedback deviations can maintain stable loop operation.

[0003] When a system operates in a low-temperature environment, the fluid medium exhibits strong nonlinear and time-varying characteristics. Due to the contraction of metals during cooling, the clearance of the regulating valve components changes, leading to sudden changes in friction and valve dead zone drift. These effects typically accumulate slowly over time. Simultaneously, high-pressure media flowing through the pressure drop region of the valve are prone to local phase transitions, generating flash evaporation and forming vapor locks, resulting in high-frequency disturbance pulses. To address these low-temperature disturbances, conventional solutions typically add external physical sensors, using the measurement results from multiple sensors as the control input. However, external physical sensors are prone to signal drift or hardware failure in low-temperature environments, increasing the probability of system malfunctions and potentially causing control loop divergence. For example, in China... Patent application CN121761694A discloses a phase change antifreeze control method based on state equation constraints. By real-time acquisition of refrigerant cavity pressure and combining it with thermodynamic state equations, the delayed freezing risk is mapped to a saturation temperature boundary to trigger overdrive logic. Although this scheme establishes a safety boundary at the macroscopic thermodynamic level, it essentially relies on global pressure measurement and a single state equation criterion. When dealing with complex time-domain signals where high-frequency phase change disturbances and extremely low-frequency physical jamming coexist within the fluid system, it is difficult to effectively separate slow-changing trends and fast-changing noise through mathematical means. This can easily lead to frequent malfunctions or high-frequency amplitude-limited oscillations in the control loop due to signal aliasing, making it difficult to achieve precise control of the system convergence time while maintaining adjustment accuracy.

[0004] Therefore, the technical problem to be solved by this invention is how to distinguish and identify the slow changing trend formed by valve contraction and high-frequency pulses generated by flash vapor resistance using only the feedback deviation data of the control loop itself, avoid confusion between the two types of signals, and automatically adjust the control parameters according to the actual working conditions. Summary of the Invention

[0005] To address the problems in the background art, the technical solution of the present invention is as follows: An automatic parameter adjustment method for cryogenic operation of a fluid system, comprising the following steps:

[0006] Step S1: The signal sampling input interface acquires the target setpoint and feedback sampling value of the fluid control controlled object under cryogenic conditions, calculates the feedback deviation value at the current moment, and updates the feedback deviation sequence within the sampling period in a time-series cumulative manner.

[0007] Step S2: Calculate and extract the low-frequency envelope component in the feedback deviation sequence as a slow-varying trend component, and subtract the slow-varying trend component from the feedback deviation sequence item by item to generate a fast component sequence.

[0008] Step S3: Calculate the mean square fluctuation energy within the short period sliding window based on the fast component sequence as the high frequency fluctuation energy characteristic value. Use the high frequency fluctuation energy characteristic value to monotonically adjust the action hysteresis judgment limit threshold in the same direction. At the same time, use the absolute value of the slow trend component to dynamically reduce the short period sliding window length in the opposite direction. Compare and judge the current action hysteresis state of the feedback control loop.

[0009] Step S4: When the number of continuous sampling cycles in which the feedback control loop is in a state of hysteresis is determined by comparison reaches the number of transient filtering cycles, the current low temperature constraint state of the feedback control loop is established to be effective, and the corresponding constraint level is divided according to the discretization interval where the absolute value of the slow-changing trend component is located.

[0010] Step S5: When the low temperature constraint state is in effect, retrieve the corresponding gain correction coefficient according to the constraint level, and use the gain correction coefficient to multiply and adjust the control output of the adjustment loop to generate drive control command.

[0011] Preferably, in step S2, extracting the slow-varying trend component of the feedback deviation sequence includes: step S21, the signal sampling input interface acquires the feedback sampling value according to the set sampling period and calculates the feedback deviation value at the current time, and splices the feedback deviation values ​​at the current time and the historical time through time-series sliding to construct the feedback deviation sequence; step S22, the arithmetic mean of the feedback deviation sequence is calculated within a fixed sliding window length, and the calculated average value is used as the slow-varying trend component.

[0012] Preferably, in step S3, when determining the action lag state, the action lag determination limit threshold is dynamically adjusted using high-frequency fluctuation energy characteristic values, and the short-period sliding window length is dynamically adjusted using the absolute value of the slow-changing trend component, including: step S31, under the state of continuous fluctuation of the feedback deviation sequence, the fluctuation variance of the high-frequency fluctuation energy characteristic values ​​within the monitoring period is calculated in real time, and when the fluctuation variance exceeds the set fluctuation threshold value, the action lag determination limit threshold is monotonically increased in the same direction; step S32, the absolute value of the slow-changing trend component is monitored in real time, and when the absolute value monotonically increases, the short-period sliding window length used for action lag state determination is monotonically shortened in the opposite direction.

[0013] Preferably, in step S5, generating the drive control command includes: while monitoring the change in the sign of the control deviation in real time to determine the initial moment of control direction reversal, calculating the discrete step compensation amount based on the slow-changing trend component and the constraint level corresponding to the currently effective low-temperature constraint state, and superimposing the discrete step compensation amount into the final drive control command, including: step S51, monitoring the positive and negative signs of the feedback deviation value at the current moment and the feedback deviation value at the previous moment in real time, and determining that the initial moment of control direction reversal has arrived when the positive and negative signs change to opposite signs; step S52, calculating the discrete step compensation amount through a preset monotonically increasing function mapping based on the constraint level corresponding to the currently effective low-temperature constraint state and the absolute value of the slow-changing trend component, and algebraically adding the discrete step compensation amount to the control output of the adjustment loop to generate the drive control command.

[0014] Preferably, after the current low-temperature constraint state of the feedback control loop is established, the variance change rate of the high-frequency fluctuation energy characteristic value within the continuous verification period is calculated in real time. When the variance change rate exceeds the set transient pulse threshold value, it is determined that the feedback control loop is in a phase change air resistance interference state. The integral term gain in the control output of the adjustment loop is reduced, and the reverse constraint weight coefficient is increased to shorten the short-cycle sliding window length.

[0015] Preferably, in step S5, retrieving the corresponding gain correction coefficient according to the constraint level includes: step S53, establishing a discrete control parameter gain compensation matrix, which stores multiple sets of gain correction coefficients corresponding to different constraint levels; step S54, retrieving the control parameter gain compensation matrix and outputting the corresponding gain correction coefficient according to the constraint level corresponding to the currently effective low temperature constraint state.

[0016] Preferably, the target setpoint and feedback sampled value include the pressure setpoint and pressure sampled value in the cryogenic conveying channel, or the flow rate setpoint and flow rate sampled value in the cryogenic conveying channel.

[0017] Preferably, the sampling period is set to 10ms to 50ms, and the number of transient filtering cycles is set to 3 to 10.

[0018] Preferably, after correcting the control output of the adjustment loop and generating the drive control command, the drive control command is output to the opening control regulator, which serves as the control output adjustment terminal, to change the medium transport flow rate in the controlled channel, so that the feedback deviation sequence converges and stabilizes within the set fluctuation threshold range within the set convergence period.

[0019] Compared with the prior art, the beneficial effects of the present invention are:

[0020] 1. In the automatic parameter adjustment of fluid systems operating at low temperatures, the slow-changing trend component and the fast component sequence are extracted from the feedback deviation sequence. This allows the slow changes caused by valve contraction and the rapid fluctuations caused by fluid phase change to be identified separately. Compared with the method of using a single sampling window, this method can avoid high-frequency fluctuations masking slow changes and avoid long-term averaging weakening transient fluctuations. This reduces the misjudgment of operating conditions caused by the confusion between different signals. This method can complete the state identification using only the feedback deviation data of the control loop itself, without the need to add external physical sensors. This can reduce the impact of sensor drift or failure on the control loop in low-temperature environments and improve the robustness of system operation.

[0021] 2. This invention adjusts the action hysteresis judgment limit threshold based on the energy characteristic value of high-frequency fluctuations and adjusts the short-cycle sliding window length according to the slow-changing trend component, so that the state judgment conditions can change with the actual working conditions. When the high-frequency fluctuations suddenly increase, the action hysteresis judgment limit threshold increases accordingly, which can avoid misjudging transient disturbances such as flashing as valve action hysteresis. When the slow-changing deviation continues to increase, the short-cycle sliding window length is shortened accordingly, which can identify rapid fluctuations more promptly. Thus, it can reduce misjudgments caused by the mismatch between fixed judgment conditions and actual operating conditions, and improve the accuracy of determining the low-temperature constraint state, constraint level, and gain correction coefficient.

[0022] 3. When the control direction reverses, the present invention determines the discrete step compensation amount based on the slow-changing trend component and the constraint level, so that the compensation amount can be adapted to the degree of action lag caused by valve cold contraction. This compensation can reduce the response delay caused by the fit clearance and static friction during valve reversal, avoid the control loop from oscillating repeatedly near the target set value, and enable the regulating valve to respond to small control commands more timely and accurately, thereby improving the stability of pressure or flow regulation. Attached Figure Description

[0023] Figure 1 This is a flowchart of the parameter adjustment steps for the low-temperature operation feedback control loop of the present invention;

[0024] Figure 2 This is a structural diagram of the hardware and software components of the automatic parameter adjustment system of the present invention.

[0025] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0027] An automatic parameter adjustment method for cryogenic operation of fluid systems includes the following steps:

[0028] Step S1: The signal sampling input interface acquires the target setpoint and feedback sampling value of the fluid control controlled object under cryogenic conditions, calculates the feedback deviation value at the current moment, and updates the feedback deviation sequence within the sampling period in a time-series cumulative manner.

[0029] Step S2: Calculate and extract the low-frequency envelope component in the feedback deviation sequence as a slow-varying trend component, and subtract the slow-varying trend component from the feedback deviation sequence item by item to generate a fast component sequence.

[0030] Step S3: Calculate the mean square fluctuation energy within the short period sliding window based on the fast component sequence as the high frequency fluctuation energy characteristic value. Use the high frequency fluctuation energy characteristic value to monotonically adjust the action hysteresis judgment limit threshold in the same direction. At the same time, use the absolute value of the slow trend component to dynamically reduce the short period sliding window length in the opposite direction. Compare and judge the current action hysteresis state of the feedback control loop.

[0031] Step S4: When the number of continuous sampling cycles in which the feedback control loop is in a state of hysteresis is determined by comparison reaches the number of transient filtering cycles, the current low temperature constraint state of the feedback control loop is established to be effective, and the corresponding constraint level is divided according to the discretization interval where the absolute value of the slow-changing trend component is located.

[0032] Step S5: When the low temperature constraint state is in effect, retrieve the corresponding gain correction coefficient according to the constraint level, and use the gain correction coefficient to multiply and adjust the control output of the adjustment loop to generate drive control command.

[0033] Preferably, in step S2, extracting the slow-varying trend component of the feedback deviation sequence includes: step S21, the signal sampling input interface acquires the feedback sampling value according to the set sampling period and calculates the feedback deviation value at the current time, and splices the feedback deviation values ​​at the current time and the historical time through time-series sliding to construct the feedback deviation sequence; step S22, the arithmetic mean of the feedback deviation sequence is calculated within a fixed sliding window length, and the calculated average value is used as the slow-varying trend component.

[0034] Preferably, in step S3, when determining the action lag state, the action lag determination limit threshold is dynamically adjusted using high-frequency fluctuation energy characteristic values, and the short-period sliding window length is dynamically adjusted using the absolute value of the slow-changing trend component, including: step S31, under the state of continuous fluctuation of the feedback deviation sequence, the fluctuation variance of the high-frequency fluctuation energy characteristic values ​​within the monitoring period is calculated in real time, and when the fluctuation variance exceeds the set fluctuation threshold value, the action lag determination limit threshold is monotonically increased in the same direction; step S32, the absolute value of the slow-changing trend component is monitored in real time, and when the absolute value monotonically increases, the short-period sliding window length used for action lag state determination is monotonically shortened in the opposite direction.

[0035] Preferably, in step S5, generating the drive control command includes: while monitoring the change in the sign of the control deviation in real time to determine the initial moment of control direction reversal, calculating the discrete step compensation amount based on the slow-changing trend component and the constraint level corresponding to the currently effective low-temperature constraint state, and superimposing the discrete step compensation amount into the final drive control command, including: step S51, monitoring the positive and negative signs of the feedback deviation value at the current moment and the feedback deviation value at the previous moment in real time, and determining that the initial moment of control direction reversal has arrived when the positive and negative signs change to opposite signs; step S52, calculating the discrete step compensation amount through a preset monotonically increasing function mapping based on the constraint level corresponding to the currently effective low-temperature constraint state and the absolute value of the slow-changing trend component, and algebraically adding the discrete step compensation amount to the control output of the adjustment loop to generate the drive control command.

[0036] Preferably, after the current low-temperature constraint state of the feedback control loop is established, the variance change rate of the high-frequency fluctuation energy characteristic value within the continuous verification period is calculated in real time. When the variance change rate exceeds the set transient pulse threshold value, it is determined that the feedback control loop is in a phase change air resistance interference state. The integral term gain in the control output of the adjustment loop is reduced, and the reverse constraint weight coefficient is increased to shorten the short-cycle sliding window length.

[0037] Preferably, in step S5, retrieving the corresponding gain correction coefficient according to the constraint level includes: step S53, establishing a discrete control parameter gain compensation matrix, which stores multiple sets of gain correction coefficients corresponding to different constraint levels; step S54, retrieving the control parameter gain compensation matrix and outputting the corresponding gain correction coefficient according to the constraint level corresponding to the currently effective low temperature constraint state.

[0038] Preferably, the target setpoint and feedback sampled value include the pressure setpoint and pressure sampled value in the cryogenic conveying channel, or the flow rate setpoint and flow rate sampled value in the cryogenic conveying channel.

[0039] Preferably, the sampling period is set to 10ms to 50ms, and the number of transient filtering cycles is set to 3 to 10.

[0040] Preferably, after correcting the control output of the adjustment loop and generating the drive control command, the drive control command is output to the opening control regulator, which serves as the control output adjustment terminal, to change the medium transport flow rate in the controlled channel, so that the feedback deviation sequence converges and stabilizes within the set fluctuation threshold range within the set convergence period.

[0041] Example 1: This example uses the cryogenic operation of an outdoor oil transportation system as an example. The external ambient temperature of the pipeline is -20℃. The controller confirms the cryogenic operating condition based on the real-time temperature of the medium in the cryogenic transportation channel. The external ambient temperature is used to characterize the heat dissipation conditions of the pipeline. The fluid control is controlled by the pressure feedback control loop or flow feedback control loop of the cryogenic transportation channel. The dynamic viscosity of crude oil in the cryogenic environment increases non-linearly, and the flow resistance inside the transportation pipeline increases accordingly. An electric heating tape is installed outside the pipeline to supplement heat and maintain the fluidity of crude oil. Changes in fluid flow rate and ambient wind speed will cause fluctuations in the real-time heat dissipation rate. It is difficult for a constant power heating tape to match this fluctuation. Long-term high heating power will increase energy consumption, while insufficient heating power may cause local blockage of the pipeline due to decreased fluidity. The pipeline inlet pressure of the fluid system used in this example is 1.6MPa, and the designed maximum transportation flow rate is 50m³ / h.

[0042] During the automatic parameter adjustment process, the controller's signal sampling input interface acquires the target setpoint and feedback sampling value of pressure or flow in the cryogenic conveying channel according to a sampling period of 10ms to 50ms. The controller subtracts the feedback sampling value from the target setpoint at the current moment to obtain the feedback deviation value at the current moment. Then, the feedback deviation values ​​of the current moment and the historical moments, a total of 30 sampling periods, are sequentially shifted and spliced ​​to form a feedback deviation sequence of length 30.

[0043] The controller performs an arithmetic mean on the feedback deviation sequence within a fixed sliding window length. This fixed sliding window length, together with the short-period sliding window length (described later), forms a virtual data processing architecture called a parallel window queue in the controller's internal storage area. This queue uses two independently allocated shift registers to asynchronously slide sample the same feedback deviation sequence to achieve spatial parallel isolation. In this embodiment, the fixed sliding window length is first set to 20 sampling periods. The arithmetic mean of the feedback deviation values ​​within these 20 sampling periods is used as the low-frequency envelope component to obtain the slow-changing trend component reflecting the slow change process of valve cold contraction and jamming. Subsequently, the slow-changing trend component is subtracted from each item in the feedback deviation sequence to generate a fast component sequence reflecting the high-frequency pulses of fluid flash evaporation. Within a short-period sliding window length of 5 sampling periods, the controller adds the squares of each fast component and calculates the arithmetic mean. The resulting mean square fluctuation energy is used as the characteristic value of high-frequency fluctuation energy.

[0044] The controller uses the sampling interval covered by a set of continuously acquired high-frequency fluctuation energy characteristic values ​​as the monitoring period, and calculates the fluctuation variance of the high-frequency fluctuation energy characteristic values ​​within the monitoring period. When the fluctuation variance exceeds the set fluctuation threshold of 5%, the controller monotonically increases the action hysteresis judgment limit threshold in the same direction, gradually increasing it from the initial 1% to a maximum of 3%. At the same time, the controller monitors the absolute value of the slow-changing trend component. When the absolute value monotonically increases, the short-cycle sliding window length is monotonically shortened in the opposite direction from 5 sampling periods to 3 sampling periods. The controller compares the absolute value of the fast component within the short-cycle sliding window length with the current action hysteresis judgment limit threshold to determine whether the feedback control loop is in an action hysteresis state.

[0045] When the hysteresis state persists for a certain number of transient filtering cycles, the controller establishes a low-temperature constraint state. In this embodiment, the number of transient filtering cycles is set to 5 sampling cycles. After the low-temperature constraint state takes effect, the controller classifies the constraint level according to the discretization range of the absolute value of the slow-changing trend component. Specifically, the discretization numerical boundary of the dual-object track is preset in the register configuration area of ​​the controller. When the controlled object is a pressure control loop and the absolute value is between 0.01MPa and 0.05MPa, or when the controlled object is a flow control loop and the absolute value is between 0.5m³ / h and 2.0m³ / h, it is uniformly classified as a first-level constraint. When the absolute value under flow control is between 2.0m³ / h and 5.0m³ / h, or when the absolute value under flow control is greater than 5.0m³ / h, it is classified as a second-level or third-level constraint, respectively. In order to maintain logical synchronization with the pressure control track, when the system is under pressure control and the absolute value is between 0.05MPa and 0.10MPa, it is classified as a second-level constraint, and when it is greater than 0.10MPa, it is classified as a third-level constraint.

[0046] The controller establishes a discrete control parameter gain compensation matrix and retrieves the gain correction coefficient according to the constraint level. The gain correction coefficient corresponding to the first-level constraint is 0.95, the gain correction coefficient corresponding to the second-level constraint is 0.85, and the gain correction coefficient corresponding to the third-level constraint is 0.75. The controller multiplies the retrieved gain correction coefficient with the control output of the adjustment loop of the pressure or flow feedback control loop to generate a drive control command, and outputs the drive control command to the opening control regulator to change the medium transport flow rate in the cryogenic transport channel.

[0047] The controller starts counting the preset convergence period from the sampling period of generating drive control commands and continuously updates the feedback deviation sequence. The fluctuation threshold range is preset according to the control accuracy of pressure feedback deviation or flow feedback deviation. When the feedback deviation sequence enters the corresponding fluctuation threshold range within the convergence period and remains there until the end of the convergence period, the controller determines that the feedback deviation sequence has converged and stabilized.

[0048] During the operation of the automatic parameter adjustment method, a platinum resistance temperature sensor installed at the inlet of the delivery pipeline acquires the real-time fluid temperature at a sampling frequency of 10Hz. A differential pressure transmitter with a measurement accuracy of not less than 0.1% and an electromagnetic flowmeter acquire the real-time differential pressure and real-time flow rate of the 10m-long delivery pipeline according to a control cycle of 100ms. The controller reads the real-time temperature, real-time differential pressure, and real-time flow rate, and calculates the dynamic viscosity of the fluid at the current temperature based on the pressure loss relationship. The formula for calculating the dynamic viscosity is: ,in, The dynamic viscosity at the current temperature. For calibration coefficients, This refers to the real-time differential pressure of the pipeline. To ensure real-time flow, and assuming that the physical dimensions of both ends of the formula are consistent, the calibration coefficient is calibrated offline: standard viscosity silicone oil at room temperature is injected into the delivery pipeline, the pressure drop under different flow rates is measured, and the calibration coefficient is determined based on the measurement results. In this embodiment, the calibration coefficient is set to 0.085.

[0049] When the dynamic viscosity exceeds 1.2 Pa·s, the system initiates thermal compensation and inputs the deviation between the dynamic viscosity and the target viscosity into the proportional-integral controller for heat tracing. The formula for calculating the deviation is: ,in, For deviation, The dynamic viscosity at the current temperature. The target viscosity is set to 1.0 Pa·s in this embodiment. The formula for calculating the adjustment command of the heat tracing proportional integral controller is as follows: ,in, This is a heat tracing power adjustment command, used to control the thyristor voltage regulator to change the output power of the external electric heat tracing tape in the conveying pipeline; This is the heat tracing ratio factor, and its value is set to 45; For deviation, This is the heat tracing integral coefficient, and its value is set to 12; The historical deviation is the cumulative value. The thyristor voltage regulator adjusts the output power of the electric heating tape according to the heat tracing power adjustment command, so as to increase the fluid temperature and reduce the dynamic viscosity to below 1.2 Pa·s.

[0050] The controller also has a preset linearly increasing mapping function between the high-frequency fluctuation energy characteristic value and the action hysteresis judgment limit threshold. The controller inputs the high-frequency fluctuation energy characteristic value into the threshold calculation control area of ​​the static random access memory. First, it directly multiplies by a value of 0.15 to obtain the threshold basic adjustment component. When the fluctuation variance of the high-frequency fluctuation energy characteristic value calculated in step S31 exceeds the set fluctuation threshold value of 5%, the controller starts the incremental compensation logic. On the basis of the threshold basic adjustment component, an additional variance disturbance correction amount of 0.5% is added in a monotonic manner in the same direction to complete the dynamic adjustment of the action hysteresis judgment limit threshold. The intermediate characteristic value after the collaborative adjustment is transmitted to the processor's dedicated data register. The initial action hysteresis judgment limit threshold of 1% is added to it, and the result is used as the current action hysteresis judgment limit threshold. The result is limited to between 1% and 3%. When the high-frequency fluctuation energy characteristic value increases, the action hysteresis judgment limit threshold increases accordingly to reduce the influence of the gas-liquid two-phase flash pulse on the action hysteresis judgment.

[0051] The controller also has a preset reverse step reduction rule. When the absolute value of the slow-changing trend component is less than or equal to 0.05 MPa, the short-cycle sliding window length is maintained at 5 sampling periods. When the absolute value is greater than 0.05 MPa and less than or equal to 0.1 MPa, the short-cycle sliding window length is shortened to 4 sampling periods. When the absolute value is greater than 0.1 MPa, the short-cycle sliding window length is shortened to 3 sampling periods. Each time the action hysteresis state determination is performed, the controller extracts the fast component within the current short-cycle sliding window length and calculates its absolute value. If the absolute value of the fast component exceeds the current action hysteresis determination limit threshold for 3 consecutive sampling periods, the feedback control loop is determined to be in an action hysteresis state; otherwise, it is determined to be in a normal state.

[0052] Crude oil has shear-thinning properties. When the dynamic viscosity is in the transition range of 1.0 Pa·s to 1.2 Pa·s, the output power of the thyristor regulator remains unchanged. The controller increases the operating frequency of the pump motor from 40 Hz to 48 Hz to increase the internal shear rate of the fluid. The controller utilizes the shear-thinning effect of crude oil to reduce the dynamic viscosity of the fluid while keeping the output power of the electric heating tape constant. After the flow rate increases, the residence time of the fluid in the pipeline for heat dissipation is shortened, and the temperature rise compensation required at the pipeline outlet is reduced accordingly. At this time, the electric heating tape is maintained at 30% of the rated power. The controller controls the energy consumption during the fluid transportation process by adjusting the pump motor frequency and the heating power.

[0053] When the cryogenic medium passes through the pressure reduction section, local phase change flash evaporation will generate high-frequency disturbance pulses. After the cryogenic constraint state takes effect, the controller continuously calculates the variance of the high-frequency fluctuation energy characteristic value in the last 5 verification cycles with a period of 50ms. Then, the variance change rate is obtained by dividing the difference between the variance of the current cycle and the variance of the previous cycle by the variance of the previous cycle. When the variance change rate exceeds the transient pulse threshold value of 15%, the controller determines that the feedback control loop is in the phase change gas resistance interference state.

[0054] After entering the phase change resistance interference state, the controller reduces the integral term gain in the pressure or flow feedback control loop used to form the control output of the regulating loop from the initial value of 12 to 3. This integral term gain is set separately from the heat tracing integral coefficient in the heat tracing proportional-integral regulator, and the two correspond to different control loops. At the same time, the controller increases the reverse constraint weight coefficient from the initial 1.0 to 2.5, and performs a logical product operation on this amplified reverse constraint weight coefficient value and the absolute value of the slow-varying trend component read from the data register. When the product result is between 0.01MPa and 0.04MPa, the controller output corresponds to 4. The window length configuration parameter is set for each sampling period. When the product result is between 0.04MPa and 0.08MPa, the controller outputs the window length configuration parameter corresponding to 3 sampling periods. When the product result is greater than 0.08MPa, the controller directly truncates the window length to the minimum of 2 sampling periods. This establishes a closed-loop mapping flow relationship from continuous floating-point coefficient values ​​to discrete integer sampling period step size, thereby shortening the short-period sliding window length from 5 sampling periods to 2 sampling periods. When the variance change rate falls below 15%, the controller restores the integral term gain and reverse constraint weight coefficient to the initial set value.

[0055] After long-term operation of the pipeline, changes in the inner wall condition, such as wax buildup, can cause calibration coefficient drift. When the cumulative operating time reaches 240 hours and the instantaneous flow rate stabilizes at 40 m³ / h for 5 minutes, the controller collects the outlet and inlet temperatures of the pipeline. When the temperature difference between the outlet and inlet is less than 0.5℃, the controller performs dynamic calculation of the flow cross-sectional area in its hardware calculation core based on the current flow rate and inlet pressure. Using the collected current flow rate of 40 m³ / h and the decreasing gradient of the inlet pressure, the controller compares the baseline flow resistance characteristics of a clean pipeline without wax buildup to calculate the velocity increment and friction increment caused by the wax buildup on the inner wall. This allows the actual equivalent flow inner diameter of the pipeline to be calculated in reverse, and the corresponding pipe diameter reduction in millimeters is output to correct the flow correction coefficient in the control loop. This engineering action initiates the pipe inner diameter compensation calculation based on the fluid continuity equation.

[0056] Unlike the 30-cycle sliding time window used for pipe diameter compensation calculation, when extracting the slow-varying trend component of the feedback deviation sequence, the controller sets a fixed sliding window length of 50 sampling cycles and continuously performs an arithmetic average on the 50 feedback deviation values ​​formed by time-series sliding splicing. This window length is determined based on the decoupling test results of the slow-varying trend of cold contraction and the rapid fluctuation frequency. When the fixed sliding window length is less than 20 sampling cycles, high-frequency flash noise cannot be sufficiently filtered out, and low-frequency envelopes will aliasing. When the fixed sliding window length is greater than 100 sampling cycles, the extraction of the slow-varying trend component will produce phase lag, affecting the timeliness of identifying frictional force abrupt changes. This embodiment uses a fixed sliding window length of 50 sampling cycles to extract the slow-varying trend component.

[0057] The controller uses a sliding time window of 30 cycles to discard historical calibration data outside the sliding time window and update the calibration coefficients. The update formula for the calibration coefficients is as follows: ,in, For the updated calibration coefficients, This is the number of cycles within the sliding time window, and its value is set to 30. For the first time within the sliding time window Calibration data for each cycle.

[0058] When the differential pressure transmitter experiences an overload or disconnection fault in its analog input channel, the control system switches to the alternative control mode. The control parameter gain compensation matrix is ​​stored in the controller's non-volatile memory as a two-dimensional array. Its rows correspond to different constraint levels, and its columns correspond to the gain correction coefficient, proportional term correction coefficient, and integral term correction coefficient, respectively. When the low-temperature constraint is not in effect, the gain correction coefficient, proportional term correction coefficient, and integral term correction coefficient are all 1.0. When the low-temperature constraint is in effect and the constraint level is Level 1, the three coefficients are 0.95, 0.90, and 0.85, respectively. When the constraint level is Level 2, the three coefficients are 0.85, 0.80, and 0.70, respectively. When the constraint level is Level 3, the three coefficients are 0.75, 0.65, and 0.55, respectively.

[0059] The controller first multiplies the proportional and integral term correction coefficients with the initial proportional and integral coefficients of the pressure or flow feedback control loop, respectively, to form the current control output of the regulation loop. Then, it multiplies the gain correction coefficient of the corresponding constraint level with the control output of the regulation loop to generate the drive control command. Thus, each set of coefficients in the control parameter gain compensation matrix corresponds to the corresponding constraint level, and the gain correction coefficient directly corrects the control output of the regulation loop according to the constraint level.

[0060] After entering the alternative control mode, the controller stops calculating the dynamic viscosity based on the real-time pressure difference and instead reads the temperature-viscosity table in the electrically erasable programmable read-only memory. The controller retrieves the estimated equivalent dynamic viscosity of the current fluid based on the real-time fluid temperature collected by the platinum resistance temperature sensor and inputs the estimated value into the proportional-integral controller to enable the proportional-integral heat tracing control to continue operating.

[0061] Under the above control conditions, when the external ambient temperature drops to -20℃ and the flow rate fluctuates, the total pressure fluctuation amplitude of the fluid system remains within 0.15MPa, the dynamic viscosity of the monitoring nodes along the pipeline remains between 0.95Pa·s and 1.05Pa·s, the daily power consumption of the electric heat tracing system is reduced by 35%, and the action deviation of the valve control mechanism remains within 1.5%.

[0062] To compensate for the mechanical dead zone and commutation static friction lag caused by the physical contraction of the cryogenic actuator, the controller applies discrete step compensation at the commutation moment. The controller monitors the feedback deviation between the current moment and the previous moment in real time. When the positive and negative signs of the two change to opposite signs, it determines that the initial moment of control direction reversal has arrived, and calls the preset monotonically increasing function to calculate the discrete step compensation amount.

[0063] The discrete step compensation amount is the product of the basic compensation step size and the step compensation correction coefficient. The basic compensation step size is set to 1.5% of the valve opening control amount and increases linearly and monotonically with the absolute value of the slow-varying trend component. For every 0.05 MPa increase in the absolute value of the slow-varying trend component, the basic compensation step size increases by 0.5%. The step compensation correction coefficient monotonically corresponds to the constraint level corresponding to the current low-temperature constraint state, where 1.0 corresponds to Level 1 constraint, 1.4 corresponds to Level 2 constraint, and 1.8 corresponds to Level 3 constraint. The controller algebraically adds the discrete step compensation amount to the current regulation loop control output of the pressure or flow feedback control loop to generate the final drive control command. The discrete step compensation amount is applied all at once at the moment of reversal. The transient driving force generated is used to overcome the sudden change in static friction force and compensate for the fit clearance caused by valve cold contraction, so as to suppress the low-frequency limit loop oscillation of the feedback control loop near the equilibrium point.

[0064] Example 2: This example uses a fluid circulation test system to test the parameter adjustment process. The system includes a storage tank, a variable frequency delivery pump, a check valve, a flow meter, a temperature sensor, a differential pressure sensor, and a controller. The variable frequency delivery pump is connected to the storage tank and the check valve through a pipeline. The flow meter, temperature sensor, and differential pressure sensor are installed on the pipeline at the outlet end of the variable frequency delivery pump. The temperature sensor collects the fluid temperature inside the pipeline, the differential pressure sensor collects the pressure difference in the pipeline before and after the check valve, the flow meter records the output flow rate of the pipeline, and the controller is electrically connected to the temperature sensor, differential pressure sensor, and variable frequency delivery pump respectively. Based on the collected data, the target pumping frequency is calculated, and drive control commands are output to the variable frequency delivery pump.

[0065] During system operation, the temperature sensor collects fluid temperature in real time. Differential pressure sensors synchronously collect pipeline pressure differentials. The collected data is then transmitted to the controller, which calculates the target pumping frequency using the following formula. : ,in, The reference pumping frequency is set to 19.0Hz; The temperature compensation coefficient is set to -0.5 Hz / ℃. For fluid temperature, The differential pressure compensation coefficient is set to 0.1 Hz / kPa. This represents the pressure difference in the pipeline before and after the check valve.

[0066] The controller limits the calculated target pumping frequency between 15.0Hz and 50.0Hz. When the calculated value is less than 15.0Hz, the target pumping frequency is set to 15.0Hz; when the calculated value is greater than 50.0Hz, the target pumping frequency is set to 50.0Hz. After limiting the frequency, the controller outputs a drive control command corresponding to the target pumping frequency. The variable frequency pump adjusts its speed according to this command to maintain the fluid flow rate in the pipeline within the set range. The actual test pumping frequency recorded during the experiment is denoted as [missing value]. .

[0067] In the first group of experiments, the fluid temperature The temperature is -40.0℃, and the pipeline pressure difference is... The controller substitutes two sampled data points into the adjustment formula to calculate the target pumping frequency, which is 110.0 kPa. The actual pumping frequency was 50.0Hz after the variable frequency delivery pump executed the drive control command. The frequency is 50.1 Hz and the output flow rate is 12.1 L / min.

[0068] During the simultaneous decrease of fluid temperature and pipeline pressure differential, the second group of experiments will reduce the fluid temperature. Set to -30.0℃, pipeline pressure difference Set at 90.0 kPa, the target pumping frequency is calculated. The actual pumping frequency was 43.0 Hz. The frequency was 42.8 Hz, corresponding to an output flow rate of 10.3 L / min. The fluid temperature in the third group of experiments was... The temperature is -15.0℃, and the pipeline pressure difference is... The controller calculates the target pumping frequency at 60.0 kPa. The actual test pumping frequency of the variable frequency delivery pump is 32.5Hz. The frequency is 32.6 Hz and the output flow rate is 7.8 L / min.

[0069] To examine frequency compensation when pipeline pressure differential increases, the fourth group of tests will adjust the fluid temperature. Set to -10.0℃, and simultaneously adjust the pipeline pressure differential. After increasing the pressure to 150.0 kPa, and with both temperature and differential pressure compensation terms involved in the calculation, the target pumping frequency is... The actual pumping frequency was 39.0 Hz; The frequency was 39.2 Hz and the output flow rate was 9.4 L / min. This set of data shows that when the fluid temperature is higher than that of the third group and the pipeline pressure difference increases significantly, the pressure difference compensation term makes the target pumping frequency increase with the increase of flow resistance.

[0070] In the fifth group of tests, the fluid temperature The temperature is 0.0℃, and the pipeline pressure difference is... The controller calculates the target pumping frequency at 40.0 kPa. The actual test pumping frequency of the variable frequency delivery pump is 23.0Hz. The frequency was 23.1 Hz, the output flow rate was 5.5 L / min, and the fluid temperature was set in the 6th group of experiments. Set to 10.0℃, pipeline pressure difference Set to 10.0 kPa, the calculated target pumping frequency The frequency was 15.0Hz, which is at the lower limit of the set amplitude range; the actual tested pumping frequency was... The frequency is 14.9 Hz and the output flow rate is 3.6 L / min.

[0071] The above tests covered a fluid temperature range of -40.0℃ to 10.0℃ and a pipeline pressure difference range of 10.0kPa to 150.0kPa. When the fluid temperature decreased or the pipeline pressure difference increased, the temperature compensation term and the pressure difference compensation term increased the target pumping frequency accordingly. When the fluid temperature increased and the pipeline pressure difference decreased, the target pumping frequency decreased accordingly and was kept between 15.0Hz and 50.0Hz by amplitude limiting. The actual test pumping frequency of each group varied around the corresponding target pumping frequency. The fluctuation amplitude in the test records was less than 0.2Hz. This frequency fluctuation came from the combined effect of the rotor inertia of the variable frequency delivery pump and the fluid resistance. The actual test pumping frequency and the target pumping frequency maintained the same trend of change.

[0072] Example 3: The fluid system in this example includes a controller, a circulating pump, a heating bypass valve, a pressure sensor installed at the outlet of the circulating pump, and a temperature sensor installed at the fluid pipeline. The circulating pump and the heating bypass valve are respectively connected to the controller. During system operation, the temperature sensor collects the fluid temperature. The corresponding analog electrical signal is converted into a digital signal and transmitted to the controller; the pressure sensor synchronously collects the pressure drop at the outlet of the circulating pump. The converted digital signal is then transmitted to the controller, which presets a reference temperature. At 25℃, the viscosity temperature coefficient It is 0.035.

[0073] The controller determines the fluid temperature based on the received fluid temperature. Calculate viscosity compensation coefficient The calculation formula is: ,in, This is the viscosity compensation coefficient; The viscosity temperature coefficient; Reference temperature; The fluid temperature is the fluid temperature. As the fluid temperature decreases, the fluid viscosity and flow resistance increase accordingly. The viscosity compensation coefficient increases exponentially, and the controller completes this calculation through its internal data processing chip.

[0074] After obtaining the viscosity compensation coefficient, the controller combines it with the currently collected pressure drop. Calculate the target speed of the circulating pump The reference speed pre-stored by the controller The pressure drop adjustment coefficient is 1200 r / min. The target rotational speed is 1.5 r / (min·kPa), calculated using the following formula: ,in, The target speed of the circulating pump; The reference speed; This is the viscosity compensation coefficient; This is the pressure drop adjustment coefficient; This refers to the pressure drop at the outlet of the circulating pump.

[0075] During low-temperature operation, when the fluid temperature The temperature dropped to 4.2℃, and the pressure drop measured by the pressure sensor... When the pressure rises to 42.5 kPa, the theoretical value obtained according to the viscosity compensation coefficient calculation formula is 2.07093. The controller truncates this theoretical value to two significant decimal places to reduce the floating-point operation load of the low-power microprocessor, truncating it to 2.07 for subsequent calculations. Substituting 2.07, 1200 r / min, and 42.5 kPa into the target speed calculation formula, the target speed is obtained. The speed is 2547.75 r / min.

[0076] By using truncated, fixed-length data in the calculations, the controller can output speed control commands in integer or fixed-bit form, reducing register overflow or computational delays caused by continuous floating-point operations. The controller sends speed control commands to the circulating pump, adjusting its operating speed to 2547.75 r / min. Increased pump speed increases fluid shear force and fluid velocity within the pipe, decreasing the apparent viscosity of the cryogenic fluid and thus reducing the likelihood of localized freezing within the pipe.

[0077] While adjusting the circulating pump speed, the controller also adjusts the fluid temperature. Adjust the opening of the heating bypass valve; the controller presets a low-temperature threshold. 6.5℃, reference opening degree The thermal compensation gain is 10%. It is 2.5% / ℃, and this is determined by comparing the fluid temperature. With low temperature threshold Determine the target opening .

[0078] When the fluid temperature Below the low temperature threshold At that time, the controller calculates the target opening degree of the heating bypass valve according to the following formula: ,in, To determine the target opening degree of the heating bypass valve; As the reference opening; For thermal compensation gain; Low temperature threshold; The controller will adjust the target opening degree based on the fluid temperature. When the fluid temperature is greater than or equal to the low-temperature threshold, the controller will adjust the target opening degree. Set as the reference opening .

[0079] When the fluid temperature When the temperature drops to 4.2℃, which is below the low-temperature threshold of 6.5℃, the controller substitutes 4.2℃, 6.5℃, 10%, and 2.5% / ℃ into the target opening calculation formula to obtain the target opening. The opening is set at 15.75%. Subsequently, an opening control command is sent to the heating bypass valve to adjust its opening to 15.75%. After the opening of the heating bypass valve increases, the high-temperature fluid enters the pipeline and mixes with the low-temperature fluid, causing the overall temperature of the fluid system to rise.

[0080] The controller is also connected to a field display terminal to display the system's operating status, including the current target speed. and target opening The system is compared with the corresponding rated safety limit value to determine the freezing risk level. When the fluid temperature decreases and the flow resistance increases, causing the target speed to reach 90% of the maximum rated speed of the circulating pump, or the target opening to reach 95% of the maximum rated opening of the heating bypass valve, the controller outputs a warning signal to the display terminal. The display terminal displays a red limit alarm prompt box in the center of the screen and marks the current system status as a high-risk anti-freezing manual intervention state.

[0081] When the target speed does not reach 90% of the maximum rated speed of the circulating pump and the target opening does not reach 95% of the maximum rated opening of the heating bypass valve, the controller outputs a normal operation signal to the display terminal. The display terminal displays a green safety operation status prompt box. Based on the color and status text of the prompt box, the on-site operator can determine within 3 seconds whether manual intervention is required for maintenance without having to recalculate the target speed and target opening.

[0082] Example 4: This example combines Figures 1 to 2 This describes an automatic parameter adjustment method for cryogenic operation of fluid systems, such as... Figure 1 As shown, step S1 obtains the target setpoint and feedback sample value of the controlled object under cryogenic conditions through the signal sampling input interface, calculates the feedback deviation value at the current moment, and generates a feedback deviation sequence through time-series cumulative updates. Step S2 calculates and extracts the low-frequency envelope component in the feedback deviation sequence as a slow-varying trend component, and subtracts the slow-varying trend component from the feedback deviation sequence item by item to generate a fast component sequence. Step S3 calculates the mean square fluctuation energy within a short-period sliding window based on the fast component sequence as a high-frequency characteristic value to monotonically adjust the action hysteresis limit threshold in the same direction. The absolute value of the slow-varying trend component is used to reduce the short-period sliding window length in the opposite direction, and the current action hysteresis state is compared and determined. Step S4 establishes the low-temperature constraint state as effective when the action hysteresis state is determined to have reached the number of transient filtering cycles, and divides the corresponding constraint level according to the discretization interval of the absolute value of the slow-varying trend component. Step S5 retrieves the corresponding gain correction coefficient according to the constraint level when the low-temperature constraint state is effective, multiplies it to correct the control output of the adjustment loop to generate a drive control command.

[0083] like Figure 2 As shown, the physical sensor group measures data from the platinum resistance temperature sensor, differential pressure transmitter signal, and electromagnetic flowmeter, and transmits this data to the signal sampling input interface hardware board. After conversion by the signal sampling input interface hardware circuit, the digital feedback sampled value is transmitted to the parameter automatic adjustment and algorithm execution component deployed in the controller industrial control computer / core operating node. The parameter automatic adjustment and algorithm execution component software reads data from read-only memory and static random access memory, and the data reading includes control parameter gain compensation matrix retrieval and equivalent dynamic viscosity lookup table reading. The parameter automatic adjustment and algorithm execution component software module reads data based on the data... The digitized feedback sampling value is calculated and output to the opening control regulator terminal execution component for gain correction control output. The opening control regulator terminal execution component then outputs drive control commands to the physical actuator pipeline adjustment component. Simultaneously, the parameter automatic adjustment and algorithm execution component software outputs heat tracing power adjustment commands to the thyristor voltage regulator power drive component. The thyristor voltage regulator power drive component then outputs electric heat tracing power output adjustment to the external heat tracing mechanism heat dissipation compensation component to change the electric heat tracing power output. The parameter automatic adjustment and algorithm execution component is connected to the field display terminal for bidirectional control interaction and fault warning status display.

[0084] Example 5: During the initial commissioning of the fluid system, the controller runs a temperature gradient calibration program to obtain the viscosity temperature coefficient of the fluid medium. During the calibration process, the controller maintains the speed of the circulating pump at 1200 r / min and gradually reduces the fluid temperature from 25.0℃ to 0.0℃ at a rate of 1℃ / min through an external heat exchanger. The temperature sensor installed at the pipeline and the pressure sensor installed at the outlet of the circulating pump synchronously collect multiple sets of corresponding temperature measurements and pressure drops.

[0085] The controller reads the temperature measurement and pressure drop from two consecutive data acquisitions and calculates the change in temperature measurement. and the logarithmic change in pressure drop , then calculate and The absolute value of the ratio is used as the viscosity temperature coefficient. Saved to memory, where, It is the difference between two consecutive temperature measurements. This represents the difference in the logarithmic values ​​of the pressure drop corresponding to the two data collections. Used to characterize the sensitivity of fluid medium viscosity to temperature changes; subscript Indicates the change in temperature measurement value, subscript Indicates the logarithmic change in pressure drop, subscript Indicates viscosity.

[0086] Complete viscosity temperature coefficient After calibration, the controller was calibrated with the fluid temperature maintained at 25°C to determine the pressure drop adjustment coefficient. The controller gradually adjusts the valve opening at the pipeline, changing the system flow resistance to keep the pressure drop measured by the pressure sensor between 10.0 kPa and 50.0 kPa. At each pressure point, the controller automatically adjusts the circulating pump speed to maintain the design flow rate of the fluid system and records the speed increase between adjacent pressure points. and the corresponding increase in pressure drop .

[0087] Controller calculation and ratio Then, for each pressure node... Calculate the average value and use this average value as the pressure drop adjustment coefficient. Saved to memory, where, This represents the difference in circulating pump speed between two adjacent pressure nodes. This represents the difference in pressure drop measured by the pressure sensor at these two pressure points. This indicates the amount of speed adjustment corresponding to a unit change in pressure drop. Used to compensate for pressure fluctuations during operation; subscript Indicates rotational speed, subscript Indicates a decrease in pressure, subscript Indicates the ratio of rotational speed to pressure drop, subscript This indicates pressure drop adjustment.

[0088] Example 6: During the calibration of the valve opening in a cryogenic liquid pipeline, calibration medium is injected into a 50L cryogenic vacuum insulated jacketed container with a working pressure of 2MPa. A Pt100 temperature sensor installed at the downstream outlet of the valve collects initial fluid temperature data. The ARM Cortex-M4 processor in the industrial control computer reads the target temperature setpoint of 110K from the read-only memory. After receiving the start signal, the processor collects the resistance signal output by the temperature sensor through the analog-to-digital conversion channel and converts it into the measured fluid temperature. This is used to determine the correspondence between the valve adjustment step size and the parameters of the proportional-integral-derivative controller.

[0089] The processor calculates the adaptive proportional gain according to the following formula: ,in, For adaptive proportional gain, As the reference proportional gain, This is the temperature-sensitive adjustment coefficient. For temperature deviation, The target temperature is set at 110K. For measured fluid temperature, subscript Indicates the proportion, subscript Indicates the reference, subscript Indicates temperature, subscript Indicates the target value, subscript This represents the measured value.

[0090] During the cooling control process, the processor takes the absolute value of the difference between the measured fluid temperature and the target temperature, and uses the resulting positive value as the temperature deviation in the adaptive proportional gain calculation. When the measured fluid temperature is 150K and the target temperature is 110K, the temperature deviation is 40K; the temperature sensitivity adjustment coefficient... The adaptive proportional gain calculated when the value is 0.04% / K² With a value of 3.1% / K, after absolute value processing, the adaptive proportional gain remains positive throughout the entire cooling range, and the direction of proportional adjustment is consistent with the direction of negative feedback of the control system.

[0091] In the calibration test, the reference proportional gain is... Fixed at 1.5% / K, the temperature sensitivity adjustment coefficient is changed. Five sets of gradient tests were conducted, with the five temperature sensitivity adjustment coefficients set to 0.02% / K², 0.04% / K², 0.06% / K², 0.08% / K², and 0.10% / K², respectively. Each set of tests used the same initial conditions, with the initial fluid temperature set to 150K, and the dynamic response curves of the fluid temperature being adjusted from 150K to 110K were recorded.

[0092] The first group of experiments will adjust the temperature sensitivity coefficient. When the temperature sensitivity coefficient was set to 0.02% / K², the adaptive proportional gain was small, the valve opening response was slow, and the adjustment time required for the fluid temperature to drop to 110K was 420s. In the second group of experiments, the temperature sensitivity coefficient was set to 0.04% / K², the adjustment time was 210s, and no temperature overshoot occurred. In the third group of experiments, the temperature sensitivity coefficient was set to 0.06% / K², the adjustment time was 155s, and the temperature overshoot was 0.1K.

[0093] The fourth group of experiments adjusted the temperature sensitivity coefficient. When the temperature sensitivity coefficient was set to 0.08% / K², the system exhibited simple harmonic oscillation, the adjustment time was extended to 310s, and the maximum temperature overshoot reached 0.6K, exceeding the process upper limit of 0.2K. In the fifth test, the temperature sensitivity coefficient was set to 0.10% / K², and the system exhibited divergent self-excited oscillation. The regulating valve switched between the maximum and minimum opening, and the fluid pressure fluctuated accordingly, leading to the termination of the test.

[0094] Based on the operating parameters that the settling time is no more than 160 seconds and the temperature overshoot is no more than 0.2 K, the temperature sensitivity adjustment coefficient is... The selection range was determined to be 0.04% / K² to 0.06% / K². The calibrated system operating parameters and monitoring indicators included: initial container pressure of 2 MPa, initial fluid temperature of 150 K, target temperature of 110 K, temperature sensor sampling frequency of 10 Hz, and reference proportional gain. The standard deviation of temperature fluctuation is 1.5% / K; the standard deviation of temperature fluctuation is no greater than 0.05K, and the corresponding sampling window is 120s; the temperature overshoot limit is less than 0.2K.

[0095] During long-term system operation, the processor reads the input register connected to the temperature sensor every 100ms. When the read resistance value is lower than 18.5Ω or higher than 148.2Ω, the processor determines that the temperature sensor is in a fault state and executes the interrupt protection program. The processor writes a clear control word to the control bus address corresponding to the regulating valve, blocking the control pulse sent to the servo driver, causing the regulating valve to close to zero opening. At the same time, it sends an alarm code 0xEA to the industrial control computer and displays a sensor open circuit fault on the monitor screen, prompting the operator to replace the temperature sensor.

[0096] Temperature calibration data and historical operation records are temporarily stored in the local static random access memory of the industrial controller. Each time a new calibration cycle is started, the processor sends a sector erase command to the corresponding memory chip to clear the historical data of the previous calibration cycle, and does not send this data to the external network interface.

[0097] After parameter calibration and safety boundary configuration were completed, the fluid control system operated continuously for 72 hours under the design condition of 110K. During this period, the outlet temperature collected by the temperature sensor remained between 109.9K and 110.1K, the adjustment step of the control valve remained between 0.1mm and 0.3mm, and no low-temperature medium leakage or overpressure occurred in the fluid pipeline.

[0098] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for automatic parameter adjustment in cryogenic operation of fluid systems, characterized in that, Includes the following steps: Step S1: The signal sampling input interface acquires the target setpoint and feedback sampling value of the fluid control controlled object under cryogenic conditions, calculates the feedback deviation value at the current moment, and updates the feedback deviation sequence within the sampling period in a time-series cumulative manner. Step S2: Calculate and extract the low-frequency envelope component in the feedback deviation sequence as a slow-varying trend component, and subtract the slow-varying trend component from the feedback deviation sequence item by item to generate a fast component sequence. Step S3: Calculate the mean square fluctuation energy within the short period sliding window based on the fast component sequence as the high frequency fluctuation energy characteristic value. Use the high frequency fluctuation energy characteristic value to monotonically adjust the action hysteresis judgment limit threshold in the same direction. At the same time, use the absolute value of the slow trend component to dynamically reduce the short period sliding window length in the opposite direction. Compare and judge the current action hysteresis state of the feedback control loop. Step S4: When the number of continuous sampling cycles in which the feedback control loop is in a state of hysteresis is determined by comparison reaches the number of transient filtering cycles, the current low temperature constraint state of the feedback control loop is established to be effective, and the corresponding constraint level is divided according to the discretization interval where the absolute value of the slow-changing trend component is located. Step S5: When the low temperature constraint state is in effect, retrieve the corresponding gain correction coefficient according to the constraint level, and use the gain correction coefficient to multiply and adjust the control output of the adjustment loop to generate drive control command.

2. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, In step S2, extracting the slow-varying trend component of the feedback deviation sequence includes: step S21, the signal sampling input interface acquires the feedback sampling value according to the set sampling period and calculates the feedback deviation value at the current time, and splices the feedback deviation values ​​at the current time and the historical time through time-series sliding to construct the feedback deviation sequence; step S22, the arithmetic mean of the feedback deviation sequence is calculated within a fixed sliding window length, and the calculated average value is used as the slow-varying trend component.

3. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, In step S3, when determining the action lag state, the action lag determination limit threshold is dynamically adjusted using the high-frequency fluctuation energy characteristic value, and the short-period sliding window length is dynamically adjusted using the absolute value of the slow-changing trend component. This includes: Step S31, under the condition of continuous fluctuation of the feedback deviation sequence, the fluctuation variance of the high-frequency fluctuation energy characteristic value within the monitoring period is calculated in real time. When the fluctuation variance exceeds the set fluctuation threshold value, the action lag determination limit threshold is monotonically increased in the same direction. Step S32, the absolute value of the slow-changing trend component is monitored in real time. When the absolute value monotonically increases, the short-period sliding window length used for action lag state determination is monotonically shortened in the opposite direction.

4. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, In step S5, generating the drive control command includes: while monitoring the change in the sign of the control deviation in real time to determine the initial moment of control direction reversal, calculating the discrete step compensation amount based on the slow-changing trend component and the constraint level corresponding to the currently effective low-temperature constraint state, and superimposing the discrete step compensation amount into the final drive control command, including: step S51, monitoring the positive and negative signs of the feedback deviation value at the current moment and the feedback deviation value at the previous moment in real time, and determining that the initial moment of control direction reversal has arrived when the positive and negative signs change to opposite signs; step S52, calculating the discrete step compensation amount through a preset monotonically increasing function mapping based on the constraint level corresponding to the currently effective low-temperature constraint state and the absolute value of the slow-changing trend component, and algebraically adding the discrete step compensation amount to the control output of the adjustment loop to generate the drive control command.

5. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, After the current low-temperature constraint state of the feedback control loop is established, the variance change rate of the high-frequency fluctuation energy characteristic value within the continuous verification period is calculated in real time. When the variance change rate exceeds the set transient pulse threshold value, it is determined that the feedback control loop is in a phase change air resistance interference state. The integral term gain in the control output of the adjustment loop is reduced, and the reverse constraint weight coefficient is increased to shorten the short-cycle sliding window length.

6. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, In step S5, the process of retrieving the corresponding gain correction coefficient based on the constraint level includes: step S53, establishing a discrete control parameter gain compensation matrix, which stores multiple sets of gain correction coefficients corresponding to different constraint levels; step S54, retrieving the control parameter gain compensation matrix and outputting the corresponding gain correction coefficient based on the constraint level corresponding to the currently effective low-temperature constraint state.

7. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, The target setpoints and feedback sampled values ​​include the pressure setpoints and pressure sampled values ​​in the cryogenic transport channel, or the flow rate setpoints and flow rate sampled values ​​in the cryogenic transport channel.

8. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, The sampling period is set to 10ms to 50ms, and the number of transient filtering cycles is set to 3 to 10.

9. The automatic parameter adjustment method for cryogenic operation of a fluid system according to claim 1, characterized in that, After correcting the control output of the regulating loop and generating the drive control command, the drive control command is output to the opening control regulator, which is the control output regulation terminal, to change the medium transport flow rate in the controlled channel, so that the feedback deviation sequence converges and stabilizes within the set fluctuation threshold range within the set convergence period.

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