Intelligent pressure self-adaptive adjusting system and fractionation method in low-temperature dealkylation of LNG (Liquefied Natural Gas)

Abstract

The invention discloses an intelligent pressure self-adaptive adjusting system in LNG low-temperature dealkylation and a fractionation method, and relates to the technical field of LNG low-temperature dealkylation. The pressure change in the LNG low-temperature dealkylation process is monitored in real time, detection data are transmitted to a control system in real time, the stability and low delay of data transmission are ensured, an early warning signal is automatically triggered when abnormal fluctuation is detected, and therefore the reliability of the system is improved, and the response speed is adjusted; the intelligent control unit is used for processing pressure data in real time, ensuring the real-time performance and accuracy of analysis, automatically triggering a correction program when detecting data abnormity or algorithm deviation, generating an accurate adjustment instruction and sending the adjustment instruction to the execution unit so as to adjust the opening degree of a valve or the pump speed, so that the rapid response of pressure self-adaption and the improvement of the overall reliability of the system are realized; the temperature compensation unit corrects a pressure measurement value in real time according to sensor data, errors caused by temperature fluctuation are eliminated, and the accuracy of pressure self-adaptive adjustment and the system stability are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of LNG cryogenic dealkylation, in particular to an intelligent pressure self-adaptive adjustment system and fractionation method in LNG cryogenic dealkylation. BACKGROUND

[0002] LNG cryogenic dealkylation refers to liquefying natural gas at-162℃ ultra-low temperature under normal pressure, and removing light hydrocarbons (such as ethane, propane, etc.) and impurities (such as sulfides, acid gases) through physical or chemical methods to improve fuel quality.

[0003] The existing intelligent pressure self-adaptive adjustment system in LNG cryogenic dealkylation has the following main drawbacks:

[0004] 1) Insufficient control precision: the system is difficult to achieve high-precision control when dynamically adjusting fuel supply and engine parameters due to the influence of marine environment (such as waves, wind), which will lead to increased fuel consumption and reduced ship economy; 2) Poor environmental adaptability: the existing technology does not fully consider the influence of environmental temperature and humidity on the performance of cold insulation support materials, and cannot dynamically adjust the internal pressure parameters of the tank, thereby affecting the stability and balance of the gasification storage system; 3) Limited data processing capability: the system needs to process a large amount of sensor data (such as environmental monitoring, running state), but the current data processing capability is insufficient, making it difficult to quickly respond to dynamic changes, resulting in a lag in response speed and affecting overall performance optimization. That is, the existing intelligent pressure self-adaptive adjustment system has shortcomings in precision, environmental adaptability, data processing, and algorithm optimization, and needs to be upgraded to improve system performance. Therefore, we propose an intelligent pressure self-adaptive adjustment system and fractionation method in LNG cryogenic dealkylation. SUMMARY

[0005] The purpose of the present application is to solve the problems mentioned in the background art, and the present application provides an intelligent pressure self-adaptive adjustment system and fractionation method in LNG cryogenic dealkylation.

[0006] In order to achieve the above-mentioned purpose, the present application specifically adopts the following technical solutions:

[0007] An intelligent pressure self-adaptive adjustment system in LNG cryogenic dealkylation, comprising:

[0008] A pressure detection unit for real-time monitoring of pressure changes during LNG cryogenic dealkylation and transmitting detection data to a control system;

[0009] An intelligent control unit for receiving pressure data and performing self-adaptive analysis based on a preset algorithm to generate adjustment instructions;

[0010] An execution unit for adjusting the opening of a valve or pump according to the instructions to achieve automatic stabilization of the pressure;

[0011] a data storage unit for recording historical pressure values and adjustment processes, facilitating subsequent optimization and fault diagnosis;

[0012] a temperature compensation unit for real-time correction of pressure measurement values based on sensor data, eliminating errors caused by temperature fluctuations, ensuring the accuracy of pressure adaptive adjustment and system stability;

[0013] a communication interface for communication with external monitoring systems or control networks, transmitting real-time pressure data, temperature correction values, and system status information, and receiving remote control instructions, ensuring remote management and integration of the system.

[0014] Further, the pressure detection unit is a high-precision piezoresistive sensor.

[0015] Further, the intelligent control unit adopts a fuzzy PID algorithm to dynamically adjust control parameters based on the output of the pressure detection module. The fuzzy PID algorithm dynamically adjusts the proportional coefficient K_p, the integral coefficient K_i, and the differential coefficient K_d based on the deviation e and its rate of change ec between the compensated pressure value P_c and the set pressure value P_set.

[0016] Further, the execution unit includes an electric regulating valve and a stepper motor driver, which responds to the instructions of the adaptive control module to achieve pressure adaptive adjustment, and the execution unit is equipped with a redundant control mechanism, including a main and backup electric regulating valve switching function, which automatically activates the backup valve when the main valve fails, ensuring the continuity of pressure regulation and system stability.

[0017] Further, the temperature compensation unit integrates a thermocouple sensor to perform real-time compensation and correction of pressure data in low-temperature environments based on the following function formula:

[0018] P_c = P_m + k * (T - T_{\text{ref}}),

[0019] where P_c represents the compensated pressure value,

[0020] P_m represents the measured pressure value,

[0021] T represents the real-time temperature value measured by the thermocouple sensor,

[0022] T_{\text{ref}} represents the preset reference temperature (usually set to -162℃ to match the LNG environment),

[0023] k is the temperature compensation coefficient (value range: 0.005-0.02 MPa / ℃, determined by low-temperature calibration experiments for optimization).

[0024] Further, the communication interface supports the Modbus protocol and interacts with the host computer system to realize remote monitoring and fault diagnosis.

[0025] Further, the safety protection unit automatically triggers an emergency shutdown mechanism when the pressure exceeds the preset threshold.

[0026] Further, the fault warning unit generates a warning signal in real time when it detects abnormal pressure fluctuations or unit operating parameters deviating from the normal range, and pushes it to the monitoring system through the communication interface.

[0027] A fractionation method of an intelligent pressure self-adaptive regulation system for LNG low-temperature dealkylation, characterized in that it comprises the following steps:

[0028] Step 1: Start the LNG low-temperature dealkylation fractionation system, and collect the pressure data P_m of the fractionation tower and associated pipelines in real time through the pressure detection unit, and obtain the real-time temperature value T measured by the thermocouple sensor from the temperature compensation unit;

[0029] Step 2: The temperature compensation unit compensates and corrects the measured pressure value P_m in real time based on the preset function formula P_c=P_m+k×(T-T_ref), to obtain the accurate compensated pressure value P_c, where T_ref is the preset reference temperature, and k is the calibrated and optimized temperature compensation coefficient;

[0030] Step 3: The intelligent control unit receives the compensated pressure value P_c, and performs self-adaptive analysis based on the fuzzy PID algorithm, dynamically adjusts the proportional, integral, and differential control parameters, and generates adjustment instructions matched with the current working condition;

[0031] Step 4: The execution unit receives the adjustment instructions, drives the stepper motor of the electric regulating valve to change the opening degree, accurately adjusts the LNG flow or reflux ratio entering the fractionation tower, and stabilizes the system pressure in the set value range;

[0032] Step 5: During the adjustment process, the data storage unit continuously records the compensated pressure value P_c, temperature value T, adjustment instructions, and valve opening degree and other key parameters to form a historical operation database;

[0033] Step 6: The safety protection unit monitors the compensated pressure value P_c in real time, and if it exceeds the preset safety threshold range, immediately triggers an emergency shutdown mechanism and closes the key valve; at the same time, the fault warning unit analyzes the pressure fluctuation trend and unit operating parameters, and if it detects continuous abnormalities or deviates from the normal range, it generates a warning signal;

[0034] Step 7: The communication interface uploads the real-time compensation pressure value P_c, temperature value T, system state, early warning signal and historical operation data to the upper computer monitoring system through the Modbus protocol, and receives remote control instructions; if the main electric regulating valve in the execution unit fails, the redundant control mechanism automatically switches to the standby valve to maintain the continuity of pressure regulation.

[0035] The beneficial effects of the present application are as follows:

[0036] 1. The present application adopts a high-precision piezoresistive sensor to monitor the pressure changes in the LNG low-temperature dealkylation process in real time, including inlet pressure, tower pressure and outlet pressure, and transmits the detection data to the control system in real time through the RS485 communication protocol, ensuring the stability and low delay of data transmission; the unit has a self-calibration function, which can maintain a measurement accuracy of ±0.1% FS in a wide temperature range of -196°C to 50°C, and integrates overpressure protection and fault diagnosis mechanism, which automatically triggers an early warning signal when abnormal fluctuations are detected, thereby improving the reliability and regulation response speed of the system.

[0037] 2. The intelligent control unit of the present application adopts a fuzzy PID control algorithm to process the inlet pressure, tower pressure and outlet pressure data from the pressure detection unit in real time, realizes low-delay data interaction through the RS485 communication protocol, ensures the real-time and accuracy of the analysis, integrates a fault diagnosis module, which automatically triggers a correction program when data anomalies or algorithm deviations are detected, and generates accurate regulation instructions to send to the execution unit to adjust the valve opening or pump speed, realizing fast response and overall system reliability improvement.

[0038] 3. The temperature compensation unit of the present application corrects the pressure measurement value in real time according to the sensor data, eliminates the error caused by temperature fluctuations, ensures the accuracy of pressure adaptive regulation and system stability, and interacts with the intelligent control unit at high speed, feeds back the compensated pressure value in real time, and has a built-in temperature anomaly monitoring mechanism, which automatically triggers an alarm or switches to a redundant backup when temperature fluctuations exceed the threshold or the sensor fails, reducing the risk of system misoperation. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is the working block diagram of the system in the present application;

[0040] Figure 2 is the method flowchart in the present application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application.

[0042] Please refer toFigure 1 The application provides an intelligent pressure self-adaptive adjustment system in LNG cryogenic dealkylation, comprising:

[0043] A pressure detection unit is used for real-time monitoring of pressure changes in the LNG cryogenic dealkylation process and transmitting detection data to a control system; a high-precision piezoresistive sensor is used to real-time monitor pressure changes in the LNG cryogenic dealkylation process, including inlet pressure, tower internal pressure and outlet pressure, and detection data is transmitted in real time to the control system through an RS485 communication protocol to ensure the stability and low delay of data transmission; the unit has a self-calibration function and can maintain a measurement accuracy of ±0.1% FS in a wide temperature range of -196°C to 50°C, and integrates overpressure protection and fault diagnosis mechanisms, and automatically triggers a warning signal when abnormal fluctuations are detected, thereby improving the reliability and adjustment response speed of the system.

[0044] An intelligent control unit is used for receiving pressure data and performing adaptive analysis based on a preset algorithm to generate adjustment instructions. The unit uses a fuzzy PID control algorithm to real-time process inlet pressure, tower internal pressure and outlet pressure data from the pressure detection unit, realizes low-delay data interaction through an RS485 communication protocol, and ensures the real-time and accuracy of analysis; the algorithm has a built-in adaptive mechanism to dynamically adjust control parameters such as proportional gain, integral time and differential coefficient according to pressure change trends and historical operation data, thereby optimizing the stability and energy efficiency of the dealkylation process; at the same time, a fault diagnosis module is integrated to automatically trigger a correction program and generate accurate adjustment instructions when data anomalies or algorithm deviations are detected, and the instructions are sent to the execution unit to adjust valve opening or pump speed, so as to realize fast response of pressure adaptation and overall system reliability improvement.

[0045] An execution unit is used for adjusting the opening of a valve or a pump according to instructions to realize automatic stabilization of pressure. The unit receives adjustment instructions from the intelligent control unit in real time through an RS485 communication protocol, and uses a high-precision stepper motor or a variable frequency drive system to drive changes in valve opening or pump speed, to ensure millisecond-level response speed and accurate position control to adapt to dynamic fluctuations in inlet pressure, tower internal pressure and outlet pressure; at the same time, the unit integrates a position feedback sensor to real-time monitor valve opening or pump speed state and returns feedback data to the control unit through RS485 to form a closed-loop adjustment mechanism to improve the accuracy and robustness of pressure stabilization; in addition, the unit has a fault protection module built-in to automatically trigger a safety mode such as limit protection or emergency reset when overload, jamming or communication interruption is detected, to ensure continuous operation and overall reliability of the system under abnormal working conditions.

[0046] A data storage unit is used to record historical pressure values and adjustment processes for subsequent optimization and fault diagnosis. The data storage unit receives pressure monitoring data and adjustment instruction history from the intelligent control unit in real time through a high-speed data bus, uses embedded flash memory or SD card storage media, records time stamps, pressure values, valve opening or pump speed states, adjustment parameters, and operation logs at a millisecond-level sampling frequency, ensures the integrity and timing accuracy of the data, and supports continuous data recording for several months through a large-capacity storage space built-in the unit. The unit supports data export through a standard data interface (such as USB or Ethernet) to facilitate integration with upper computer analysis software, realizes trend analysis, pattern recognition, and performance optimization, and at the same time, the unit integrates data compression algorithms and encryption mechanisms to reduce storage occupation and protect data security. When detecting storage abnormalities or insufficient capacity, the unit automatically triggers an alarm and uses log backtracking functions to assist fault diagnosis, improving system maintainability and decision support efficiency.

[0047] A temperature compensation unit is used to correct pressure measurement values in real time based on sensor data, eliminate errors caused by temperature fluctuations, and ensure the accuracy and stability of pressure adaptive adjustment. The unit collects environmental temperature data in real time through high-precision temperature sensors (such as thermocouples or RTDs) and dynamically adjusts pressure measurement values within milliseconds by combining embedded compensation algorithms (such as polynomial fitting or lookup table method). The compensation coefficient is pre-set and adaptively optimized based on the temperature-pressure relationship model. The unit integrates self-calibration functions to periodically correct zero drift and gain error through reference standard sources to ensure long-term measurement stability. At the same time, the unit interacts with the intelligent control unit at high speed to feed back the compensated pressure value in real time, and has a built-in temperature anomaly monitoring mechanism. When detecting that the temperature fluctuation exceeds the threshold or the sensor fails, the unit automatically triggers an alarm or switches to a redundant backup to reduce the risk of system misoperation. In addition, the unit supports remote parameter configuration and log recording to facilitate performance analysis and optimization through upper computer software, thereby comprehensively improving the environmental adaptability and robustness of the adjustment system.

[0048] The communication interface is used for communication with an external monitoring system or control network, transmission of real-time pressure data, temperature correction values and system state information, and reception of remote control instructions, to ensure remote management and integration of the system. The communication interface supports multiple industrial standard protocols (such as Modbus TCP, OPC UA or CAN bus) to adapt to the compatibility requirements of different monitoring systems, and the data transmission frequency can be configured to update at a millisecond level to ensure the timeliness of real-time feedback; a built-in data verification mechanism (such as CRC verification and retransmission protocol) is provided to effectively reduce the communication error rate, and automatically enable the local cache function in the event of network interruption to avoid loss of critical data; the interface is equipped with security protection measures (such as SSL / TLS encryption and user authentication) to prevent unauthorized access or malicious instruction injection, and to improve the network security level of the system; at the same time, the interface cooperates closely with the intelligent control unit and the temperature compensation unit to synchronize real-time pressure adjustment instructions and compensation parameters, supports remote batch parameter configuration, log export and system diagnosis through the host computer software, and further enhances the maintainability of the system and the integration efficiency with the factory control network.

[0049] In this embodiment, preferably, the pressure detection unit is a high-precision piezoresistive sensor. The high-precision piezoresistive sensor has excellent low-temperature adaptability and stability, can accurately capture pressure fluctuations in an LNG environment of -196°C, and has a measurement accuracy of ±0.1% FS, ensuring high reliability of real-time data; the high-precision piezoresistive sensor has a built-in temperature compensation function, seamlessly integrates with the temperature compensation unit in the system, automatically corrects measurement deviations caused by temperature changes, thereby improving the accuracy of pressure self-adaptive adjustment, and simultaneously transmits detection data in real time to the intelligent control unit through a high-speed response mechanism (response time

[0050] <10 ms) to support the system to quickly generate adjustment instructions. In addition, the sensor adopts an explosion-proof and corrosion-resistant design to adapt to the harsh working conditions of the LNG dealkylation process, and shares data with the external monitoring system through the communication interface for remote diagnosis and maintenance optimization.

[0051] In this embodiment, preferably, the intelligent control unit adopts a fuzzy PID algorithm to dynamically adjust control parameters according to the output of the pressure detection module. When the fuzzy PID algorithm is executed, the proportional coefficient K_p, the integral coefficient K_i and the differential coefficient K_d are dynamically adjusted according to the deviation e and the change rate ec of the compensated pressure value P_c and the set pressure value P_set.

[0052] The specific adjustment rules are based on a pre-set fuzzy rule base, which includes 49 fuzzy rules. The input variables are the fuzzy values of the deviation e (domain: -0.5-0.5 MPa) and the change rate ec (domain: -0.2-0.2 MPa / s), and the output variable is the correction amount fuzzy value of ΔK_p, ΔK_i and ΔK_d. The fuzzy rule base realizes parameter self-adaptation through the following logic:

[0053] When |e| is large, increase K_p and decrease K_d to quickly reduce the deviation;

[0054] When |e| is medium, appropriately increase K_i and adjust K_p to suppress overshoot;

[0055] When |e| is small, increase K_i and K_d to improve steady-state accuracy;

[0056] The final output PID control parameters are:

[0057] K_p = K_p0 + ΔK_p;

[0058] K_i = K_i0 + ΔK_i;

[0059] K_d = K_d0 + ΔK_d;

[0060] Wherein, K_p0, K_i0, K_d0 are initial PID parameter reference values, which are set by low-temperature hydrocarbon removal process simulation model optimization; The parameter adjustment period is 100 ms, ensuring rapid response to pressure fluctuations.

[0061] In this embodiment, the execution unit preferably includes an electric regulating valve and a stepper motor driver, which realize pressure adaptive adjustment in response to instructions from the adaptive control module, and the execution unit is equipped with a redundant control mechanism, including a main and backup electric regulating valve switching function, which automatically activates the backup valve when the main valve fails, ensuring the continuity and stability of pressure regulation. The electric regulating valve in the execution unit adopts a high-precision proportional valve structure, with a linear regulation accuracy of 0.1%, a response time of less than 50 ms, and ensures rapid execution of the adaptive control module instructions; The stepper motor driver precisely controls the valve opening through pulse signals, and cooperates with real-time pressure feedback to realize closed-loop regulation, avoiding overshoot or lag phenomenon. The redundant control mechanism integrates a fault detection module, which automatically triggers main and backup switching based on pressure deviation threshold (such as ±0.5 MPa) and abnormal valve current signals, and the switching process is completed within 10 ms, and the fault events are recorded through system log; The backup valve is designed with the same specifications, supporting online hot plug function, further strengthening the system robustness; In addition, the execution unit is built-in temperature compensation algorithm, which eliminates the influence of material deformation in low temperature environment, and guarantees the stability and continuity of pressure regulation in all working conditions.

[0062] In this embodiment, the temperature compensation unit integrates a thermocouple sensor to real-time compensate and correct pressure data in low temperature environment, based on the following function formula:

[0063] P_c = P_m + k * (T - T_ref),

[0064] wherein P_c represents the compensated pressure value,

[0065] P_m represents the measured pressure value,

[0066] T represents the real-time temperature value measured by the thermocouple sensor,

[0067] T_{\text{ref}} represents the preset reference temperature (usually set to -162℃ to match the LNG environment),

[0068] k is the temperature compensation coefficient (with a value range of 0.005-0.02 MPa / ℃, determined by low-temperature calibration experiment optimization).

[0069] The formula is based on the linear relationship model between piezoresistive effect and temperature change, which real-time calculates the compensation amount and corrects the pressure data, effectively eliminates the measurement deviation caused by temperature fluctuation in LNG process, and ensures the accuracy and system stability of pressure adaptive adjustment. The compensation process is executed by an embedded microprocessor, updated once every second to adapt to rapidly changing working conditions.

[0070] In this embodiment, the communication interface preferably uses Modbus RTU protocol, supports RS-485 physical layer interface, and transmits data at a baud rate of 9600bps to ensure that the real-time data after pressure compensation (such as P_c, P_m and T values) are updated to the host computer system every second; the host computer system integrates SCADA software, dynamically displays the pressure curve, temperature fluctuation and compensation state through the graphical interface, and has built-in fault diagnosis algorithm, which can automatically identify sensor abnormalities or communication interruption, generate alarm logs and push to mobile terminal, improving remote operation efficiency; in addition, the interface supports data encryption and identity verification mechanism to ensure the security of industrial network in LNG process and avoid data leakage or system interference caused by unauthorized access.

[0071] In this embodiment, preferably, it also includes a safety protection unit that automatically triggers an emergency shutdown mechanism when the pressure exceeds a preset threshold. The safety protection unit integrates high-precision pressure sensors and redundant control circuits to monitor system pressure changes in real time; when the detected pressure exceeds the preset safety threshold (such as 5.0 MPa), the unit immediately triggers the emergency shutdown mechanism through a hard-wired signal, including closing critical valves, cutting off power sources and activating pressure relief devices to prevent equipment overpressure risk during LNG low-temperature dealkylation process. At the same time, this mechanism is linked with the host computer SCADA software, automatically records shutdown events, generates detailed alarm reports, and pushes them to mobile terminals through encrypted communication interfaces, ensuring that maintenance personnel respond in a timely manner and further improving the reliability and safety redundancy of the system under extreme working conditions.

[0072] In this embodiment, preferably, the system further comprises a fault early warning unit, which adopts a multi-sensor fusion technology, combines a pressure transmitter and a temperature sensor to collect data in real time, and analyzes fluctuation patterns through a built-in fuzzy logic algorithm; when detecting that a parameter offset exceeds a set tolerance (such as pressure fluctuation ±0.2 MPa or temperature deviation ±5℃), the unit automatically generates a graded early warning signal (such as a primary yellow early warning and a senior red early warning), and pushes the signal to a SCADA monitoring system through a Modbus TCP / IP communication interface. Meanwhile, the unit is linked with the upper computer software, and updates an early warning log in real time, including a time stamp, an abnormal parameter value and potential cause analysis, and supports synchronization to a mobile terminal APP through an encrypted API interface, so that remote real-time monitoring and early intervention are realized, thereby effectively preventing equipment failure and optimizing the running stability of the LNG fractionation process.

[0073] Working principle and use flow of the application:

[0074] When the system starts, the inlet pressure, tower pressure and outlet pressure data are first collected by the pressure detection unit in real time through a high-precision piezoresistive sensor, ensuring a measurement accuracy of ±0.1% FS in a wide temperature range of -196℃ to 50℃; the data are transmitted to the intelligent control unit through the RS485 communication protocol, and the temperature compensation unit dynamically corrects the pressure measurement value through a thermocouple sensor to eliminate the error caused by temperature fluctuations, and the compensation formula is P_c = P_m + k x (T - T_ref), wherein k is a compensation coefficient (0.005-0.02 MPa / ℃) optimized through a low-temperature calibration experiment, and is updated once per second to adapt to rapid working condition changes. The intelligent control unit processes the deviation e and its change rate ec of the compensated pressure value P_c and the set pressure value P_set based on the fuzzy PID algorithm, dynamically adjusts the proportional coefficient K_p, the integral coefficient K_i and the differential coefficient K_d according to the pre-set 49 fuzzy rule bases, generates an adjustment instruction every 100 ms, ensures the rapid response to pressure fluctuations and the stability of the optimized dealkylation process; the instruction is sent to the execution unit through the RS485 protocol, drives the electric regulating valve or pump speed change, realizes millisecond-level response and accurate position control, and at the same time, the position feedback sensor forms a closed-loop mechanism to feed back the valve opening degree or pump speed state to the control unit in real time. The data storage unit records the pressure value, adjustment parameter and operation log at a millisecond-level sampling frequency, supports continuous storage for up to several months, and exports data through a USB or Ethernet interface, which is convenient for the upper computer software to perform trend analysis and performance optimization; the communication interface adopts the Modbus RTU protocol to transmit pressure data, temperature correction value and system status to the external SCADA system in real time at a baud rate of 9600 bps, supporting remote monitoring and parameter configuration. The safety protection unit monitors the pressure change in real time, and when it exceeds the pre-set threshold (such as 5.0 MPa), an emergency shutdown mechanism is triggered immediately, including closing the valve and activating the pressure relief device; the fault early warning unit analyzes the parameter deviation (such as ±0.2 MPa pressure fluctuation or ±5℃ temperature deviation) through the fuzzy logic algorithm combined with the multi-sensor data, generates a graded early warning signal and pushes it to the SCADA system, ensuring early intervention. The use process includes setting the initial PID parameter reference values K_p0, K_i0, K_d0 and the reference temperature T_ref in the initialization stage, and after starting the operation, the system automatically performs the pressure adaptive adjustment cycle, the operator monitors the real-time curve and log through the upper computer interface, performs remote parameter adjustment or fault diagnosis, and after shutdown, the historical records are traced back by using the data storage unit to optimize the process parameters, thereby improving the overall efficiency and reliability of the LNG fractionation process.

[0075] Please refer to Figure 2 The application further provides a fractionation method of the intelligent pressure adaptive adjustment system in the LNG low-temperature dealkylation, characterized by comprising the following steps:

[0076] Step 1: Start the LNG low-temperature dealkylation fractionation system, and collect the pressure data P_m of the fractionation column and associated pipelines in real time through the pressure detection unit, and obtain the real-time temperature value T measured by the thermocouple sensor from the temperature compensation unit and transmit it to the central processing unit for preprocessing; then, the system corrects the pressure data P_m according to the preset reference temperature T_ref and pressure reference value, and eliminates the influence of environmental temperature by combining the temperature compensation algorithm; at the same time, the PID parameter reference values K_p0, K_i0 and K_d0 set in the initialization stage are loaded into the adjustment module, laying a foundation for subsequent pressure adaptive control cycle; the operator can monitor the data fluctuation in real time through the upper computer interface to ensure the collection accuracy and system stability.

[0077] Step 2: The temperature compensation unit compensates and corrects the measured pressure value P_m in real time based on the preset function formula P_c=P_m+k×(T-T_ref), to obtain the accurate compensated pressure value P_c, wherein T_ref is the preset reference temperature, and k is the temperature compensation coefficient optimized by calibration; the coefficient k is obtained through strict laboratory calibration process, and the pressure deviation at different temperatures is analyzed based on historical operation data to ensure the compensation accuracy after optimization; at the same time, T_ref is set as the standard temperature value (such as 20℃) under the design condition of the system, to eliminate the disturbance of environmental fluctuation. The compensated P_c value is directly input into the adjustment module as the key input of the PID control algorithm, to realize the dynamic matching of the pressure set value and the actual value, thereby improving the stability and response speed of the fractionation process.

[0078] Step 3: The intelligent control unit receives the compensated pressure value P_c, and performs adaptive analysis based on the fuzzy PID algorithm to dynamically adjust the proportional, integral and differential control parameters, and generates adjustment instructions matched with the current working condition; specifically, the fuzzy reasoning engine built-in the unit calculates the deviation e between the pressure set value P_set and the compensated value P_c and its change rate ec in real time, makes online decision according to the preset fuzzy rule base, and outputs the proportional coefficient correction amount ΔK_p, the integral coefficient correction amount ΔK_i and the differential coefficient correction amount ΔK_d. The adjusted control parameters K_p=K_p0+ΔK_p, K_i=K_i0+ΔK_i and K_d=K_d0+ΔK_d are updated to the PID controller in real time, so that the control law u(t)=K_p·e(t)+K_i·∫e(t)dt+K_d·de(t) / dt can accurately respond to the pressure fluctuation in the fractionation column. The generated adjustment instructions are transmitted to the actuator (such as the regulating valve) through 4-20 mA analog signal or Modbus RTU protocol, to drive the valve opening to adjust as needed, to ensure that the system pressure quickly converges to the set interval, and significantly improve the control accuracy and anti-interference ability of the fractionation process.

[0079] Step 4: The execution unit receives the adjustment instruction, drives the stepper motor of the electric regulating valve to change the opening degree, accurately adjusts the LNG flow or reflux ratio entering the fractionating tower, and stabilizes the system pressure within the set value range. The stepper motor uses a high-precision encoder feedback mechanism to ensure that the opening degree adjustment resolution reaches ±0.1%, effectively suppressing pressure drift caused by flow fluctuations; at the same time, the execution unit integrates overload protection and position calibration functions, automatically compensates for torque output when detecting abnormal valve resistance, and maintains linear response during the adjustment process. Through the closed-loop control system, the pressure sensor collects real-time values inside the fractionating tower and feeds back to the intelligent control unit for deviation analysis, forming a dynamic optimization loop, significantly shortening the pressure convergence time to within 5 seconds, and improving the energy efficiency ratio and operation reliability of the fractionation process.

[0080] Step 5: During the adjustment process, the data storage unit continuously records key parameters such as the compensated pressure value P_c, temperature value T, adjustment instruction, and valve opening degree, forming a historical operation database; this database supports offline data analysis functions, and through built-in algorithms, it mines the correlation between operation modes and pressure fluctuations, providing a data foundation for subsequent control strategy optimization; at the same time, the system supports real-time retrieval of historical records through the human-machine interface (HMI), assisting operators in diagnosing abnormal conditions (such as valve sticking or flow sudden changes), and combining with the machine learning module to predict potential failures, achieving preventive maintenance. In addition, historical data and real-time control loops cooperate to dynamically correct the adaptive threshold of PID parameters, further improving the robustness and long-term stability of fractionating tower pressure regulation, ensuring high energy efficiency operation of the LNG dealkylation process under varying conditions.

[0081] Step 6: The safety protection unit monitors the compensated pressure value P_c in real time, and if it exceeds the preset safety threshold range, it immediately triggers the emergency shutdown mechanism and closes the key valve; at the same time, the fault warning unit analyzes the pressure fluctuation trend and unit operating parameters, and if it detects continuous abnormalities or deviations from the normal range, it generates a warning signal; the generated warning signal is pushed to the operator console in real time through the human-machine interface (HMI), and automatically associates with the historical operation database to generate a detailed abnormal report; at the same time, the signal triggers the machine learning module for in-depth analysis, combined with historical pressure fluctuation patterns to predict potential failure points (such as valve wear or sensor drift), and outputs maintenance suggestions, achieving proactive intervention; in addition, the warning signal cooperates with the real-time control loop to dynamically adjust the PID parameter threshold, enhancing the system's adaptive ability under abnormal conditions, ensuring the safety and continuity of the LNG dealkylation process.

[0082] Step 7: The communication interface uploads the real-time compensation pressure value P_c, temperature value T, system status, warning signals, and historical operation data to the upper computer monitoring system through the Modbus protocol and receives remote control instructions; if the main electric regulating valve in the execution unit fails, the redundant control mechanism automatically switches to the standby valve to maintain the continuity of pressure regulation. At the same time, the uploaded data is processed in real time on the upper computer for visualization, generating dynamic curves and reports to facilitate remote monitoring and decision-making by operators; during the redundant switching process, the system automatically records the type of fault event, the time of occurrence, and the switching log, and triggers a maintenance alert, which is pushed to the control console through HMI and cooperates with the fault warning unit to generate a repair work order; in addition, the remote control instructions received by the communication interface are linked with the real-time control loop to dynamically optimize the PID parameter set value, ensuring that pressure fluctuations are minimized during valve switching; the upper computer monitoring system also predicts potential equipment degradation trends based on historical operation data and warning signals using a machine learning module to suggest preventive maintenance measures in advance, thereby enhancing the reliability and long-term operating efficiency of the system.

[0083] The above description of disclosed embodiments enables one of ordinary skill in the art to make or use the application. Various modifications to these embodiments will be readily apparent to those of ordinary skill in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Accordingly, the application is not to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent pressure self-adaptive regulating system in LNG cryogenic dealkylation, characterized in that, The application relates to a pressure self-adaptive control system for LNG low-temperature hydrocarbon removal, which comprises the following parts: a pressure detection unit for monitoring the pressure change in the LNG low-temperature hydrocarbon removal process in real time and transmitting the detection data to a control system; an intelligent control unit for receiving the pressure data and performing self-adaptive analysis based on a preset algorithm to generate adjustment instructions; an execution unit for adjusting the opening degree of a valve or a pump according to the instructions to realize automatic stabilization of the pressure; a data storage unit for recording historical pressure values and adjustment processes to facilitate subsequent optimization and fault diagnosis; a temperature compensation unit for correcting the pressure measurement value in real time according to sensor data, eliminating the error caused by temperature fluctuation and ensuring the accuracy of pressure self-adaptive adjustment and the stability of the system; a communication interface for communicating with an external monitoring system or a control network, transmitting real-time pressure data, temperature correction values and system state information and receiving remote control instructions to ensure remote management and integration of the system.

2. The intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to claim 1, characterized in that, The pressure detection unit is a high-precision piezoresistive sensor.

3. The intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to claim 1, characterized in that, The intelligent control unit adopts a fuzzy PID algorithm to dynamically adjust control parameters according to the output of the pressure detection module; when the fuzzy PID algorithm is executed, the proportional coefficient Kp, the integral coefficient Ki and the differential coefficient Kd are dynamically adjusted according to the deviation e and the change rate ec of the compensated pressure value P_c and the set pressure value P_set.

4. The intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to claim 1, characterized in that, The execution unit comprises an electric regulating valve and a stepping motor driver and realizes pressure self-adaptive adjustment in response to the instructions of the adaptive control module; the execution unit is equipped with a redundant control mechanism, including a main and standby electric regulating valve switching function, which automatically activates the standby valve when the main valve fails to guarantee the continuity of pressure adjustment and the stability of the system.

5. The intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to claim 1, characterized in that, The temperature compensation unit integrates a thermocouple sensor to compensate and correct the pressure data in a low-temperature environment based on the following function formula: P_c=P_m+k\times(T-T_{\text{ref}}), wherein P_c represents the compensated pressure value, P_m represents the measured pressure value, T represents the real-time temperature value measured by the thermocouple sensor, T_ref represents a preset reference temperature (usually set to -162 DEG C to match the LNG environment) and k is a temperature compensation coefficient (the value range is 0.005-0.02 MPa / DEG C and is determined by low-temperature calibration experiment optimization). The communication interface supports the Modbus protocol and realizes data interaction with an upper computer system, remote monitoring and fault diagnosis. The application further comprises a safety protection unit which automatically triggers an emergency shutdown mechanism when the pressure exceeds a preset threshold. The application further comprises: a fault early warning unit which generates a warning signal in real time when pressure fluctuation abnormality or unit operation parameter deviation from the normal range is detected and pushes the warning signal to a monitoring system through the communication interface.

6. The intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to claim 1, characterized in that, The application comprises the following steps:

7. The intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to claim 1, characterized in that Step 1: start the LNG low-temperature hydrocarbon removal fractionation system, collect the pressure data P_m of the fractionation tower and associated pipelines in real time through the pressure detection unit and acquire the real-time temperature value T measured by the thermocouple sensor through the temperature compensation unit.

8. The intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to claim 1, characterized in that, ​ ​ 9. A fractionation method of the intelligent pressure self-adaptive regulating system for LNG low-temperature dealkylation according to any one of claims 1-8, characterized in that, ​ ​ Step 2: The temperature compensation unit compensates and corrects the measured pressure value P_m in real time based on a preset function formula P_c = P_m + k x (T - T_ref) to obtain an accurate compensated pressure value P_c, wherein T_ref is a preset reference temperature, and k is a calibrated and optimized temperature compensation coefficient; Step 3: The intelligent control unit receives the compensated pressure value P_c, performs adaptive analysis based on the fuzzy PID algorithm, dynamically adjusts the proportional, integral, and differential control parameters, and generates adjustment instructions matching the current working condition; Step 4: The execution unit receives the adjustment instructions, drives the stepper motor of the electric regulating valve to change the opening degree, accurately adjusts the LNG flow or reflux ratio entering the fractionating tower, and stabilizes the system pressure within the set value range; Step 5: During the adjustment process, the data storage unit continuously records the compensated pressure value P_c, temperature value T, adjustment instructions, and valve opening degree, etc. key parameters to form a historical operation database; Step 6: The safety protection unit monitors the compensated pressure value P_c in real time, and if it exceeds the preset safety threshold range, it immediately triggers the emergency shutdown mechanism and closes the key valve; at the same time, the fault warning unit analyzes the pressure fluctuation trend and unit operating parameters, and if it detects continuous abnormalities or deviations from the normal range, it generates a warning signal; Step 7: The communication interface uploads the real-time compensated pressure value P_c, temperature value T, system status, warning signal, and historical operation data to the upper computer monitoring system through the Modbus protocol, and receives remote control instructions; if the main electric regulating valve in the execution unit fails, the redundant control mechanism automatically switches to the backup valve to maintain the continuity of pressure regulation.

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