High-precision electric temperature control valve

Abstract

The high-precision electric temperature control valve relates to the technical field of electric temperature control valves and comprises a temperature control valve body and a valve element body, a valve rod cavity is formed in the front face of the temperature control valve body, a liquid inlet IN opening is formed in one side of the top face of the temperature control valve body, and a connecting base is arranged at the position, vertically corresponding to the liquid inlet IN opening, of the bottom face of the temperature control valve body; a liquid inlet FC port is formed in the side, away from the connecting base, of the bottom face of the temperature control valve body, an electric control guide valve rod is arranged on the surface of the temperature control valve body in a penetrating mode, and the end of the electric control guide valve rod is connected with a valve element body. A system structure composed of a single-chip microcomputer master control system, an intelligent control system, a feedback mechanism and data and analysis system, a self-adaptive algorithm system and an auxiliary intelligent decision-making system is arranged in the temperature control valve body, and a multi-system cooperative control technology is adopted. Therefore, centralized control and management of the whole temperature control valve body are achieved, the effect of comprehensively, accurately and intelligently controlling the temperature control valve body is achieved, and the function of efficient and intelligent regulation and control of the temperature control valve body is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of electric temperature control valves, in particular to a high-precision electric temperature control valve. Background Art

[0002] According to a bidirectionally connected double valve core shut-off memory alloy spring temperature control valve disclosed in China Publication No. "CN117847298B", a symmetrical, series-connected hinged double valve core driven by a memory alloy spring and a damping cylinder for damping the movement speed of the valve core are arranged in the valve body to realize the opening and closing control of the temperature control valve; the temperature control valve realizes double series shut-off sealing by connecting the double valve cores in series, which greatly improves the trace leakage of the temperature control valve, and the symmetrical double valve core structure also enables the temperature control valve to achieve no installation direction requirements; through the cooperation of the hinged double valve core and the damping cylinder during the working process, the asymmetric delay of the opening and closing of the temperature control valve is realized, and the influence of the external environmental temperature fluctuation on the working reliability of the temperature control valve is eliminated, and at the same time, it has the advantage of short opening time; when the temperature control valve is applied to the nine small fire places, it has the advantages of timely response to the initial fire, small leakage, and no reverse installation, which improves the speed of the automatic fire protection repeated opening and closing intelligent temperature control fire extinguishing system to respond to the initial fire and the effective service life of the fire extinguishing agent storage bottle.

[0003] The above documents and prior art have the following technical problems when used:

[0004] Problem 1: Although the temperature control valve in the above documents and the prior art can realize functions such as double series shut-off and sealing, it is insufficient in terms of temperature control accuracy. It is difficult to realize real-time accurate monitoring and prediction of temperature and flow by relying only on the symmetrical, series-structured hinged double valve core and damping cylinder driven by memory alloy springs;

[0005] Question 2: The temperature control valve in the above document has certain limitations in response speed and control accuracy. It is difficult to achieve rapid response and precise control of temperature changes only through the cooperation between the hinged double valve core and the damping cylinder during operation.

[0006] Question three: In the above-mentioned documents and prior arts, the temperature control valve lacks adaptability and stability under different environmental changes and usage conditions. Since the control parameters cannot be adjusted in real time, when the external environment changes significantly, it will affect the working reliability of the temperature control valve.

[0007] Problem 4: The temperature control valve is not perfect in fault detection and processing. The fault detection and processing capabilities are weak. There is a lack of mechanisms to evaluate the probability of faults in real time, and the ability to automatically adjust the control strategy when an abnormal state is detected. Summary of the invention

[0008] Technical issues solved

[0009] In view of the shortcomings of the prior art, the present invention provides a high-precision electric temperature control valve to solve the following problems:

[0010] 1. Single mechanical connection leads to insufficient control accuracy;

[0011] 2. It is difficult to achieve rapid response and precise control of temperature changes by only cooperating with the valve core and the drive structure;

[0012] 3. The temperature control valve has insufficient adaptability and stability under different environmental changes and usage conditions;

[0013] 4. The temperature control valve has weak fault detection and processing capabilities.

[0014] Technical Solution

[0015] To achieve the above objectives, the present invention is implemented through the following technical solutions: a high-precision electric temperature control valve, comprising a temperature control valve body and a valve core body, the temperature control valve body is provided with a valve stem cavity on the front side, a liquid inlet IN port is provided on one side of the top surface of the temperature control valve body, a connecting base is provided on the bottom surface of the temperature control valve body at a position vertically corresponding to the liquid inlet IN port, a liquid inlet FC port is provided on the side of the bottom surface of the temperature control valve body away from the connecting base, a liquid outlet OUT port and a liquid outlet TC port are provided on both sides of the temperature control valve body, and the end of the liquid inlet IN port, the end of the liquid outlet OUT port, and the outlet TC port are provided on the bottom surface of the temperature control valve body. Both the liquid TC port end and the liquid inlet FC port end are provided with a material guide channel penetrating the valve stem cavity, the inner wall of the guide valve groove and the inner wall surface of the material guide channel are provided with sensors, an electric control guide valve stem is penetrated through the surface of the temperature control valve body, and a valve core body is connected to the end of the electric control guide valve stem, and a system structure consisting of a single-chip microcomputer main control system, an intelligent control system, a feedback mechanism and a data and analysis system, an adaptive algorithm system and an auxiliary intelligent decision-making system is arranged inside the temperature control valve body, and the single-chip microcomputer main control system is electrically connected to the electric control guide valve stem and the sensor.

[0016] Preferably, both ends of the valve stem cavity are provided with electrically controlled guide valve stems, adjacent electrically controlled guide valve stems are connected with a valve core body, a valve core cavity is provided inside the valve core body, and a guide valve groove corresponding to the end of the guide channel is opened on the surface of the valve core cavity.

[0017] Preferably, a positioning plate is provided at the connection position between the connection base and the temperature control valve body, and the positioning plate is bolted to the bottom surface of the temperature control valve body, a filter is threadedly connected to the surface of the connection base, and an aviation wiring plug is provided on the surface of the connection base near the bottom end.

[0018] Preferably, each system structure inside the temperature control valve body further includes the following contents:

[0019] The single-chip microcomputer main control system, as the control center of the system, connects various systems and controls the transmission and connection between various systems through the single-chip microcomputer structure set inside;

[0020] The intelligent control system adopts a PID control program, uses a single-chip microcomputer to regularly collect temperature and flow and store data, and integrates the LSTN deep learning model to monitor and predict the temperature and flow rate of the material guide channel inside the temperature control valve body;

[0021] The feedback mechanism and data analysis system integrates high-precision temperature sensors and big data analysis to monitor and analyze fluid temperature in real time and use a predictive model to actively adjust the opening degree of the valve core body;

[0022] The adaptive algorithm system introduces an adaptive algorithm to adjust control parameters in real time according to environmental changes and usage conditions;

[0023] The auxiliary intelligent decision-making system optimizes the valve adjustment strategy by combining weather forecasts and market demand data.

[0024] Preferably, the intelligent control system combines the PID control program to perform data prediction, and the formula is as follows:

[0025]

[0026] in:

[0027] u(t) is the control output, i.e. the valve opening adjustment;

[0028] K p is the proportional gain, which affects the system’s response to the current error;

[0029] e(t) is the current error, the difference between the set temperature and the actual temperature, in °C;

[0030] K i is the integral gain, accumulating past errors;

[0031] is the integral of the error, indicating the accumulation of past errors and helping to eliminate steady-state errors. The unit is ℃·s;

[0032] K d is the differential gain, which affects the system's response to the rate of change of the error;

[0033] It is the derivative of the error, indicating the speed at which the current error changes, in units of °C / s.

[0034] Preferably, the feedback mechanism and the data analysis system Python's Pandas library analyze and collect data, identify temperature change patterns and update the control strategy. The formula of the prediction model is as follows:

[0035] T pred =a·T current +b·T past +c

[0036] Where: T pred To predict the temperature, T current is the current temperature, T past is the historical temperature, a, b, c are the regression coefficients;

[0037] The fault detection probability formula is as follows:

[0038] P fail =1-e -λt

[0039] in:

[0040] P fail is the probability of failure, ranging from 0 to 1;

[0041] λ is the failure rate, the expected number of failures per unit time, in 1 / s;

[0042] t is the running time, detection cycle, in seconds;

[0043] e is a natural constant, approximately equal to 2.71828, and represents the base of the exponential function.

[0044] Preferably, the adaptive algorithm system performs multiple tests based on the parameters of the monitored environmental variables and compares the temperature control effects under different environments to optimize the algorithm parameters. The formula corresponding to the algorithm is as follows:

[0045]

[0046] in:

[0047] K adaptive is the adaptive gain, the gain adjusted in real time;

[0048] K base is the basic gain, the initial setting of the system;

[0049] α is the adjustment coefficient, which affects the sensitivity of gain change;

[0050] d is the current environmental change, indicating the change in temperature or pressure, in ℃ or Pa;

[0051] d maxIt is the maximum variation, the maximum acceptable variation in system design, in ℃ or Pa.

[0052] Preferably, the valve is optimized and adjusted in the auxiliary intelligent decision-making system, and the optimization target formula is as follows:

[0053]

[0054] in:

[0055] J is the optimization target and comprehensive performance index;

[0056] L is the loss function, which defines the performance metrics, including temperature error and energy consumption;

[0057] x(t) is the system state, describing the temperature and flow rate of the fluid, in °C, L / s;

[0058] u(t) is the control input, i.e. the opening of the valve;

[0059] T is the time range, the duration of optimization, in seconds;

[0060] Preferably, the operation process of the system is as follows:

[0061] Sp1: System startup: the MCU main control system starts, loads initial parameters, checks the working status of each sensor and actuator, and ensures that the system is normal;

[0062] Sp2: User input setting, the user enters the desired temperature target T through the graphical user interface connected to the external microcontroller main control system set ;

[0063] Sp3: Data monitoring, the sensor continuously monitors the current temperature T of the fluid inside the temperature control valve body current and pressure, storing data into the database regularly and recording the running time t to evaluate the failure rate;

[0064] Sp4: Error calculation, according to the formula e(t) = T set -T current Calculate the current error;

[0065] Sp5: application of control algorithm, the intelligent control system uses PID control algorithm to calculate control output u(t), adjusts valve opening according to output command, and controls the opening state of valve core body through electric control guide valve stem;

[0066] Sp6: Adaptive gain adjustment. The adaptive algorithm system monitors the environmental change d and adjusts the gain according to the formula K adaptive Calculate adaptive gain, update gain parameters in PID control, and optimize control response;

[0067] Sp7: Feedback mechanism, the feedback mechanism and the data analysis system continuously monitor the system status, using formula P fail =1-e -λt Assess the probability of failure and, if an abnormal condition is detected, trigger an alarm and automatically adjust the control strategy;

[0068] Sp8: Data analysis and decision-making, the auxiliary intelligent decision-making system uses historical data and identifies trends, regularly analyzes temperature and pressure changes, and automatically adjusts valve strategies based on analysis results and weather forecasts;

[0069] Sp9: System feedback and optimization, the MCU main control system collects user feedback on system performance, continuously optimizes control algorithms and decision models, and adapts to changing operating conditions.

[0070] Beneficial Effects

[0071] The present invention provides a high-precision electric temperature control valve. It has the following beneficial effects:

[0072] 1. The present invention adopts innovative multi-system collaborative control technology inside the temperature control valve body. By setting up a single-chip microcomputer main control system to connect various systems, centralized control and management of the entire temperature control valve body is realized. The intelligent control system adopts a PID control program and an LSTN deep learning model, which can collect temperature and flow data in real time, and perform accurate monitoring and prediction to ensure that the temperature and flow rate of the material guide channel inside the temperature control valve body are always in the best state. The feedback mechanism and data analysis system integrate high-precision temperature sensors and big data analysis, which can monitor and analyze the fluid temperature in real time, and actively adjust the opening degree of the valve core body using the prediction model to achieve accurate control of the temperature. The adaptive algorithm system introduces an adaptive algorithm, which can adjust the control parameters in real time according to environmental changes and usage conditions, thereby improving the adaptability and stability of the temperature control valve body. The auxiliary intelligent decision-making system combines weather forecasts and market demand data to optimize the valve adjustment strategy and realize intelligent management of the temperature control valve body. This multi-system collaborative control method achieves the effect of comprehensive, accurate and intelligent control of the temperature control valve body, realizes the function of efficient and intelligent regulation for the temperature control valve body, and improves the performance and reliability of the temperature control valve body.

[0073] 2. The present invention combines the PID control algorithm with the LSTN deep learning model. The temperature and flow data are regularly collected through the single-chip microcomputer main control system, and the temperature and flow rate of the material guide channel are monitored in real time, thereby achieving more precise temperature control and reducing temperature fluctuations. The control output is calculated through a formula to adjust the valve opening. The opening of the temperature control valve body can be accurately controlled according to the current error, the accumulation of past errors, and the speed of error change, thereby achieving precise adjustment of the temperature, minimizing the temperature error in the fluid processing process, and optimizing the overall operating efficiency.

[0074] 3. The present invention adopts an adaptive algorithm system set inside the temperature control valve body. According to environmental changes and usage conditions, the control parameters are adjusted in real time, including gain adjustment and dynamic adjustment of valve opening. The adaptive gain is calculated according to the formula, and the gain parameters in the PID control are adjusted in real time, so that the temperature control valve body can quickly adapt to environmental changes and maintain the best control performance. The setting of the adjustment coefficient can affect the sensitivity of the gain change, and it is adjusted according to the actual situation, which improves the adaptability and stability of the temperature control valve body and the adaptability of the system. It can still maintain efficient temperature control performance under different operating conditions, thereby reducing the risk of manual intervention and setting errors.

[0075] 4. The present invention adopts a feedback mechanism and a data analysis system set up inside the temperature control valve body, and monitors the system status in real time through high-precision temperature sensors and fault detection probability formulas, identifies temperature change patterns, and the application of prediction models can predict future temperatures based on current temperatures and historical temperatures, helping the system to make adjustments in advance, thereby improving the response speed and control accuracy of the temperature control valve body. The use of the fault detection probability formula can evaluate the probability of a fault in real time. Once an abnormal state is detected, it can trigger an alarm in time and automatically adjust the control strategy to ensure the safe and reliable operation of the temperature control valve body, identify potential fault risks in advance, optimize the valve adjustment strategy, reduce downtime, and improve the reliability and safety of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 It is a three-dimensional structural diagram of the present invention;

[0077] Figure 2 It is a bottom structure diagram of the present invention;

[0078] Figure 3 This is a diagram showing the internal structure of the temperature control valve body of the present invention;

[0079] Figure 4 This is a front structural diagram of the interior of the temperature control valve body of the present invention;

[0080] Figure 5 This is the bottom axonometric view of the present invention;

[0081] Figure 6 This is a back structural diagram of the present invention;

[0082] Figure 7 It is a structural diagram of the temperature control valve body of the present invention;

[0083] Figure 8 This is a structural diagram of the internal system of the temperature control valve body of the present invention;

[0084] Fig. 9 This is a flow chart of the operation of the internal system of the temperature control valve body of the present invention;

[0085] Fig.10 It is a visualization chart of the temperature response curve of the present invention;

[0086] Fig.11 This is a visualization chart of the relationship between temperature and control of the present invention.

[0087] Legend:

[0088] 1. Temperature control valve body; 2. Electric control guide valve stem; 3. Valve stem cavity; 4. Valve core body; 5. Guide valve groove; 6. Valve core cavity; 7. Liquid inlet IN port; 8. Liquid outlet OUT port; 9. Liquid outlet TC port; 10. Liquid inlet FC port; 11. Positioning plate; 12. Aviation wiring plug; 13. Connection base; 14. Filter; 15. Material guide channel. DETAILED DESCRIPTION

[0089] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Specific embodiment one:

[0091] like Figure 1-11As shown, a high-precision electric temperature control valve comprises a temperature control valve body 1 and a valve core body 4, a valve stem cavity 3 is provided on the front of the temperature control valve body 1, a liquid inlet IN port 7 is provided on one side of the top surface of the temperature control valve body 1, a connecting base 13 is provided on the bottom surface of the temperature control valve body 1 at a position vertically corresponding to the liquid inlet IN port 7, a liquid inlet FC port 10 is provided on the side of the bottom surface of the temperature control valve body 1 away from the connecting base 13, a liquid outlet OUT port 8 and a liquid outlet TC port 9 are provided on both sides of the temperature control valve body 1, a material guide channel 15 penetrating the valve stem cavity 3 is provided at the ends of the liquid inlet IN port 7, the ends of the liquid outlet OUT port 8, the ends of the liquid outlet TC port 9 and the ends of the liquid inlet FC port 10, sensors are provided on the inner wall of the guide valve groove 5 and the inner wall surface of the material guide channel 15, an electric control guide valve stem 2 is penetrated on the surface of the temperature control valve body 1, and an electric control A valve core body 4 is connected to the end of the guide valve stem 2, and four liquid inlets and outlets are arranged on the surface of the entire temperature control valve body 1. Four liquid inlets and outlets are arranged on the temperature control valve body 1 to form two sets of independent flow channels. This design not only improves the flexibility of the system, but also allows specific channels to be selectively opened or closed according to needs under different working conditions to meet diverse application needs, wherein the liquid inlet IN port 7 is used to enter the liquid from the inside of the oil and gas barrel into the temperature control valve body 1, the liquid outlet OUT port 8 is used to guide the liquid from the liquid inlet IN port 7 into the machine head, the liquid inlet FC port 10 is used for the liquid from the cooler to enter the temperature control valve body 1, and the liquid outlet TC port 9 is used to circulate the liquid into the cooler. The entire temperature control valve body 1 is provided with four inlets and outlets to form two sets of flow channels. , the opening and closing of the channel is controlled by the electric-controlled guide valve stem 2 cooperating with the valve core body 4. In order to facilitate the control of the valve core body 4, a unique double-valve stem and guide valve groove 5 design technology is adopted. By arranging the electric-controlled guide valve stem 2 at both ends of the valve stem cavity 3, the position of the valve core body 4 can be controlled more accurately. At the same time, the guide valve groove 5 inside the valve core body 4 corresponds to the end of the guide channel 15, so that the flow of the fluid is smoother and more controllable. This design method not only improves the control accuracy of the temperature control valve body 1 on the fluid flow, but also ensures the stability and reliability of the valve core body 4 under different working conditions, thereby achieving the effect of accurately controlling the position of the valve core body 4 and the opening and closing degree of the guide channel 15, realizing the function of accurate material guiding for the temperature control valve body 1, and effectively improving the temperature control In order to improve the working efficiency and performance of the valve body 1, an electrically controlled guide valve stem 2 is provided at both ends of the valve stem cavity 3, a valve core body 4 is connected between adjacent electrically controlled guide valve stems 2, a valve core cavity 6 is provided inside the valve core body 4, a guide valve groove 5 corresponding to the end of the material guide channel 15 is provided on the surface of the valve core cavity 6, the electrically controlled guide valve stem 2 is installed through the valve stem cavity 3, the valve core body 4 is clamped inside the valve stem cavity 3, the valve core body 4 is connected to the internal valve core cavity 6 through the guide valve groove 5 provided on the surface, so as to guide the flow of liquid or gas, and the valve core body 4 is driven to rotate by rotating the electrically controlled guide valve stem 2 to adjust the overlapping position of the guide valve groove 5 and the material guide channel 15. When the guide valve groove 5 overlaps with the material guide channel 15, the two overlapping material guide channels 15 are connected through the valve core cavity 6.The gas or liquid connection is guided by the correspondingly connected inlet and outlet ports at the ends of the two material guide channels 15. When the guide valve groove 5 is not connected to the end of the material guide channel 15, the end of the material guide channel 15 is kept sealed by the outer wall of the valve core body 4. At this time, the material guide channel 15 remains in a closed state, so that the connected material guide channel 15 is closed. The overlapping range of the valve core body 4 and the material guide channel 15 is adjusted by rotating the electrically controlled guide valve stem 2 to adjust the degree of opening, thereby controlling and adjusting the opening and closing of the two groups of flow channels. When the guide valve groove 5 is not connected to the end of the material guide channel 15, the outer wall of the valve core body 4 can remain in a sealed state to effectively prevent fluid leakage. This design ensures the high sealing performance of the temperature control valve body 1 in the closed state, and improves the reliability and safety of the system. In order to facilitate the electric control of the temperature control valve body 1, a positioning plate 11 is provided at the connection position between the connecting base 13 and the temperature control valve body 1, and the positioning plate 11 is bolted to the bottom surface of the temperature control valve body 1, and the surface of the connecting base 13 is threaded. The connection is provided with a filter 14, and an aviation wiring plug 12 is provided near the bottom of the surface of the connection base 13. The entire temperature control valve body 1 is electrically connected and controlled through the aviation wire plug, which is convenient for the system of the entire temperature control valve body 1 to be connected to the circuit and electrically control the temperature control valve body 1. The reliable positioning disk 11 and filter 14 connection technology are adopted. By setting the positioning disk 11 at the connection between the connection base 13 and the temperature control valve body 1, the stability and sealing of the connection are greatly enhanced, and fluid leakage is effectively prevented. At the same time, the connected filter 14 can filter the fluid flowing into the temperature control valve body 1, remove impurities and pollutants, and protect the various components inside the temperature control valve body 1 from damage. In addition, the setting of the aviation wiring plug 12 makes wiring more convenient and quick, and improves the efficiency of installation and maintenance. The application of this connection technology achieves the effect of stable connection, impurity filtering and easy wiring, realizes the functions of connection stability and filtering protection for the temperature control valve body 1, and prolongs the service life of the temperature control valve body 1. Specific embodiment 2:

[0093] like Figure 1-11 As shown, according to the contents in the above specific embodiments, the following contents are further disclosed:

[0094] In order to facilitate the further electric control structure of the temperature control valve body 1, a system structure consisting of a single-chip microcomputer main control system, an intelligent control system, a feedback mechanism and a data and analysis system, an adaptive algorithm system and an auxiliary intelligent decision-making system is set inside the temperature control valve body 1. The single-chip microcomputer main control system is electrically connected to the electric control guide valve stem 2 and the sensor. Innovative multi-system collaborative control technology is adopted. By setting up a single-chip microcomputer main control system to connect various systems, centralized control and management of the entire temperature control valve body 1 is realized. The intelligent control system adopts a PID control program and LSTN deep learning model, which can collect temperature and flow data in real time, and perform accurate monitoring and prediction to ensure that the temperature and flow rate of the guide channel 15 inside the temperature control valve body 1 are always in the best state. The feedback mechanism and data analysis system are integrated with high-precision The temperature sensor and big data analysis can monitor and analyze the fluid temperature in real time, and actively adjust the opening degree of the valve core body 4 using the prediction model to achieve precise control of the temperature. The adaptive algorithm system introduces an adaptive algorithm, which can adjust the control parameters in real time according to environmental changes and usage conditions, thereby improving the adaptability and stability of the temperature control valve body 1. The auxiliary intelligent decision-making system combines weather forecasts and market demand data to optimize the valve adjustment strategy and realize intelligent management of the temperature control valve body 1. This multi-system collaborative control method achieves the effect of comprehensive, precise and intelligent control of the temperature control valve body 1, realizes the function of efficient and intelligent regulation for the temperature control valve body 1, and improves the performance and reliability of the temperature control valve body 1. The various system structures inside the temperature control valve body 1 further include the following contents:

[0095] The single-chip microcomputer main control system, as the control center of the system, connects various systems and controls the transmission and connection between various systems through the internal single-chip microcomputer structure;

[0096] The intelligent control system adopts a PID control program, uses a single-chip microcomputer to regularly collect temperature and flow and store data, and integrates the LSTN deep learning model to monitor and predict the temperature and flow rate of the guide channel 15 inside the temperature control valve body 1. The intelligent control system combines the PID control program to predict the data. The formula is as follows:

[0097]

[0098] in:

[0099] u(t) is the control output, i.e. the valve opening adjustment;

[0100] K p is the proportional gain, which affects the system’s response to the current error;

[0101] e(t) is the current error, the difference between the set temperature and the actual temperature, in °C;

[0102] K iis the integral gain, accumulating past errors;

[0103] is the integral of the error, indicating the accumulation of past errors and helping to eliminate steady-state errors. The unit is ℃·s;

[0104] K d is the differential gain, which affects the system's response to the rate of change of the error;

[0105] is the derivative of the error, indicating the speed at which the current error changes, in ℃ / s;

[0106] The intelligent control system includes the following steps in actual use:

[0107] Sp1: Set the target, set the input target temperature through the microcontroller main control system;

[0108] Sp2: Real-time monitoring, using sensors to obtain the current temperature in real time and calculate the temperature error;

[0109] Sp3: Apply PID control, calculate the control output u(t), and generate the opening instruction of the valve core body 4 according to the weighted sum of the proportional, integral and differential terms;

[0110] Sp4: adjust the valve core body 4, adjust the opening of the valve core body 4 through the electronically controlled guide valve stem 2, change the fluid flow rate, and reach the target temperature;

[0111] Sp5: Feedback adjustment, continuous monitoring of temperature and flow, and continuous adjustment of control strategies based on real-time data to ensure stability.

[0112] By adopting precise PID control algorithm technology, the control output is calculated through formula to adjust the valve opening. The opening of the temperature control valve body 1 can be accurately controlled according to the current error, the accumulation of past errors and the speed of error change, thereby realizing precise temperature regulation. The reasonable setting of proportional gain, integral gain and differential gain enables the system to respond quickly to temperature changes, eliminate steady-state errors, and respond promptly to the error change rate. The application of this control algorithm achieves the effect of precise temperature control, realizes the function of precise temperature regulation for the temperature control valve body 1, and improves the control accuracy and stability of the temperature control valve body 1.

[0113] The feedback mechanism and data analysis system integrates high-precision temperature sensors and big data analysis to monitor and analyze fluid temperature in real time, and uses the prediction model to actively adjust the opening degree of the valve core body 4. The feedback mechanism and data analysis system Python's Pandas library analyzes and collects data, identifies temperature change patterns and updates control strategies. The formula of the prediction model is as follows:

[0114] T pred=a·T current +b·T past +c

[0115] Where: T pred To predict the temperature, T current is the current temperature, T past is the historical temperature, a, b, c are the regression coefficients;

[0116] The fault detection probability formula is as follows:

[0117] P fail =1-e -λt

[0118] in:

[0119] P fail is the probability of failure, ranging from 0 to 1;

[0120] λ is the failure rate, the expected number of failures per unit time, in 1 / s;

[0121] t is the running time, detection cycle, in seconds;

[0122] e is a natural constant, approximately equal to 2.71828, representing the base of the exponential function;

[0123] The feedback mechanism and data analysis, when used, includes the following steps:

[0124] Sp1: Data collection, regularly collect temperature and pressure data and store them in the database;

[0125] Sp2: Fault detection, according to formula P fail =1-e -λt , regularly evaluate the failure probability of the system, monitor abnormal conditions such as overheating or low pressure, and record the failure rate λ;

[0126] Sp3: Data analysis, using Python to analyze historical data, identify temperature change patterns, and make trend predictions;

[0127] Sp4: Update the control strategy, adjust PID parameters in real time according to the analysis results, and optimize the control response.

[0128] By adopting efficient data analysis and prediction technology and analyzing and collecting data through Python's Pandas library, it is possible to quickly process and analyze a large amount of temperature and pressure data, identify temperature change patterns, and provide an accurate basis for the control of the temperature control valve body 1. The application of the prediction model can predict the future temperature based on the current temperature and historical temperature, helping the system to make adjustments in advance, thereby improving the response speed and control accuracy of the temperature control valve body 1. The use of the fault detection probability formula can evaluate the probability of fault occurrence in real time. Once an abnormal state is detected, it can trigger an alarm in time and automatically adjust the control strategy to ensure the safe and reliable operation of the temperature control valve body 1. The application of this data analysis and prediction technology achieves the effect of real-time monitoring of temperature, identifying change patterns, and predicting faults, thereby realizing the function of reliable operation guarantee for the temperature control valve body 1 and improving the safety and reliability of the temperature control valve body 1.

[0129] Adaptive algorithm system, introduces adaptive algorithm, adjusts control parameters in real time according to environmental changes and usage conditions. The adaptive algorithm system is based on the parameters of monitored environmental variables, conducts multiple tests and compares the temperature control effects under different environments, optimizes the algorithm parameters, and the formula corresponding to the algorithm is as follows:

[0130]

[0131] in:

[0132] K adaptive is the adaptive gain, the gain adjusted in real time;

[0133] K base is the basic gain, the initial setting of the system;

[0134] α is the adjustment coefficient, which affects the sensitivity of gain change;

[0135] d is the current environmental change, indicating the change in temperature or pressure, in ℃ or Pa;

[0136] d max is the maximum variation, the maximum acceptable variation in system design, in °C or Pa;

[0137] The steps of the adaptive algorithm system in actual use are as follows:

[0138] Sp1: monitor environmental changes, obtain environmental parameters in real time, and calculate the current change d;

[0139] Sp2: Gain calculation, according to formula K adaptive , calculate the adaptive gain;

[0140] Sp3: Apply gain, the new gain is applied to PID control, the control algorithm is updated, and the system response is optimized;

[0141] Sp4: Verify the effect, conduct multiple experiments to verify the effect of gain adjustment, and readjust the parameters if necessary;

[0142] By adopting intelligent adaptive algorithm adjustment technology, by monitoring environmental variables such as temperature, pressure and other changes, the adaptive gain is calculated according to the formula, and the gain parameters in the PID control are adjusted in real time, so that the temperature control valve body 1 can quickly adapt to environmental changes and maintain the best control performance. The setting of the adjustment coefficient can affect the sensitivity of the gain change. Adjustment is made according to actual conditions, which improves the adaptability and stability of the temperature control valve body 1 and achieves the effect of real-time adjustment of control parameters to adapt to environmental changes. The function of adaptive optimization control is realized for the temperature control valve body 1, and the performance and reliability of the temperature control valve body 1 are improved.

[0143] The auxiliary intelligent decision-making system combines weather forecasts and market demand data to optimize the valve adjustment strategy. The auxiliary intelligent decision-making system optimizes the valve adjustment. The optimization target formula is as follows:

[0144]

[0145] in:

[0146] J is the optimization target and comprehensive performance index;

[0147] L is the loss function, which defines the performance metrics, including temperature error and energy consumption;

[0148] x(t) is the system state, describing the temperature and flow rate of the fluid, in °C, L / s;

[0149] u(t) is the control input, i.e. the opening of the valve;

[0150] T is the time range, the duration of optimization, in seconds;

[0151] The actual steps of using the decision support system are as follows:

[0152] Sp1: Data integration, integrating weather forecasts, market demand and real-time data, and using API interfaces to obtain information;

[0153] Sp2: Optimize model training, select the optimized model to train the decision model;

[0154] Sp3: Decision logic application, automatically adjusts valve strategy based on prediction results and real-time data, such as reducing valve opening in advance in hot weather;

[0155] Sp4: Continuously optimize model parameters based on user feedback and historical performance.

[0156] By adopting advanced intelligent decision-making optimization technology, the loss function and optimization target formula are defined, and factors such as temperature error and energy consumption are comprehensively considered to comprehensively optimize the performance of the temperature control valve body 1. The description of the system state can accurately reflect the temperature, flow rate and other information of the fluid, and provide an accurate basis for control input. The setting of the optimization target can enable the temperature control valve body 1 to reduce energy consumption as much as possible while meeting the temperature requirements, and improve energy utilization efficiency. The application of this intelligent decision-making optimization technology has achieved the effect of comprehensively optimizing the valve performance, realized the performance optimization function for the temperature control valve body 1, and improved the energy saving and reliability of the temperature control valve body 1.

[0157] The entire temperature control valve body 1 adopts a system structure composed of a single-chip microcomputer main control system, an intelligent control system, a feedback mechanism and data analysis system, an adaptive algorithm system and an auxiliary intelligent decision-making system. Through the collaborative work and closed-loop control between the systems, efficient, stable and precise control of the temperature control valve body 1 is achieved, and the control of the temperature control valve body 1 has the effect of comprehensively improving the performance, reliability and intelligence level. Specific embodiment three:

[0159] like Figure 1-11 As shown, based on the contents in the above specific embodiments, the following contents are further disclosed:.

[0160] Preferably, the operation process of the system is as follows:

[0161] Sp1: System startup, the MCU main control system starts, loads initial parameters, checks the working status of each sensor and actuator, and ensures that the system is normal;

[0162] Sp2: User input setting, the user enters the desired temperature target T through the graphical user interface connected to the external microcontroller main control system set ;

[0163] Sp3: Data monitoring, the sensor continuously monitors the current temperature T of the fluid inside the temperature control valve body 1 current and pressure, storing the data into the database regularly and recording the running time t to evaluate the failure rate;

[0164] Sp4: Error calculation, according to the formula e(t) = T set -T current Calculate the current error;

[0165] Sp5: Control algorithm application, the intelligent control system uses the PID control algorithm to calculate the control output u(t), adjusts the valve opening according to the output command, and controls the opening state of the valve core body 4 through the electronically controlled guide valve stem 2;

[0166] Sp6: Adaptive gain adjustment, the adaptive algorithm system monitors the environmental change d and adjusts according to the formula Kadaptive Calculate adaptive gain, update gain parameters in PID control, and optimize control response;

[0167] Sp7: Feedback mechanism, the feedback mechanism and data analysis system continuously monitor the system status, using formula P fail =1-e -λt Assess the probability of failure and, if an abnormal condition is detected, trigger an alarm and automatically adjust the control strategy;

[0168] Sp8: Data analysis and decision-making, the auxiliary intelligent decision-making system uses historical data and identifies trends, regularly analyzes temperature and pressure changes, and automatically adjusts valve strategies based on analysis results and weather forecasts;

[0169] Sp9: System feedback and optimization, the MCU main control system collects user feedback on system performance, continuously optimizes control algorithms and decision models, and adapts to changing operating conditions.

[0170] The scientific and systematic operation process technology is adopted, and the stable operation and precise control of the temperature control valve body 1 are ensured through clear steps such as system startup, user input setting, data monitoring, error calculation, control algorithm application, adaptive gain adjustment, feedback mechanism, data analysis and decision-making, system feedback and optimization. The initialization and inspection work at system startup can ensure the normal working state of each sensor and actuator. The user input setting enables the temperature control valve body 1 to meet the needs of different users. Data monitoring and error calculation provide an accurate basis for the control algorithm. The synergy of control algorithm application, adaptive gain adjustment and feedback mechanism can achieve precise control of temperature and rapid adaptation to environmental changes. Data analysis and decision-making can automatically adjust the valve strategy according to historical data and weather forecasts, which improves the intelligence level of the temperature control valve body 1. System feedback and optimization can continuously collect feedback on user system performance, continuously optimize control algorithms and decision-making models, and adapt to changing operating conditions. The application of this systematic operation process technology has achieved the effect of ensuring stable operation of the system, accurately controlling temperature, adapting to environmental changes and continuous optimization, realizing the function of stable, reliable and intelligent regulation for the temperature control valve body 1, and improving the performance and reliability of the temperature control valve body 1.

[0171] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprising a reference structure" do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0172] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A high-precision electric temperature control valve, comprising a temperature control valve body (1) and a valve core body (4), characterized in that: The front side of the temperature control valve body (1) is provided with a valve stem cavity (3); one side of the top surface of the temperature control valve body (1) is provided with a liquid inlet IN port (7); the bottom surface of the temperature control valve body (1) is provided with a connection base (13) at a position vertically corresponding to the liquid inlet IN port (7); the side of the bottom surface of the temperature control valve body (1) away from the connection base (13) is provided with a liquid inlet FC port (10); the two sides of the temperature control valve body (1) are respectively provided with a liquid outlet OUT port (8) and a liquid outlet TC port (9); the ends of the liquid inlet IN port (7), the ends of the liquid outlet OUT port (8), the ends of the liquid outlet TC port (9) and the liquid inlet FC port (10) are A material guide channel (15) penetrating the valve stem cavity (3) is provided at each end, and sensors are provided on the inner wall of the guide valve groove (5) and the inner wall of the material guide channel (15). An electric control guide valve stem (2) is provided penetrating the surface of the temperature control valve body (1), and a valve core body (4) is connected to the end of the electric control guide valve stem (2). A system structure composed of a single-chip microcomputer main control system, an intelligent control system, a feedback mechanism and a data and analysis system, an adaptive algorithm system and an auxiliary intelligent decision-making system is provided inside the temperature control valve body (1), and the single-chip microcomputer main control system is electrically connected to the electric control guide valve stem (2) and the sensor.

2. A high-precision electric temperature control valve according to claim 1, characterized in that: Both ends of the valve stem cavity (3) are provided with an electrically controlled guide valve stem (2), and a valve core body (4) is connected between adjacent electrically controlled guide valve stems (2). A valve core cavity (6) is provided inside the valve core body (4), and a guide valve groove (5) corresponding to the end of the material guide channel (15) is provided on the surface of the valve core cavity (6).

3. A high-precision electric temperature control valve according to claim 1, characterized in that: A positioning plate (11) is provided at the connection position between the connection base (13) and the temperature control valve body (1), and the positioning plate (11) is bolted to the bottom surface of the temperature control valve body (1). A filter (14) is threadedly connected on the surface of the connection base (13), and an aviation wiring plug (12) is provided on the surface of the connection base (13) near the bottom end.

4. A high-precision electric temperature control valve according to claim 1, characterized in that: The various system structures inside the temperature control valve body (1) further include the following contents: The single-chip microcomputer main control system, as the control center of the system, connects various systems and controls the transmission and connection between various systems through the single-chip microcomputer structure set inside; The intelligent control system adopts a PID control program, uses a single-chip microcomputer to regularly collect temperature and flow and store data, and integrates an LSTN deep learning model to monitor and predict the temperature and flow rate of the material guide channel (15) inside the temperature control valve body (1); The feedback mechanism and data analysis system integrates high-precision temperature sensors and big data analysis to monitor and analyze fluid temperature in real time and use a prediction model to actively adjust the opening degree of the valve core body (4); The adaptive algorithm system introduces an adaptive algorithm to adjust control parameters in real time according to environmental changes and usage conditions; The auxiliary intelligent decision-making system optimizes the valve adjustment strategy by combining weather forecasts and market demand data.

5. A high-precision electric temperature control valve according to claim 4, characterized in that: The intelligent control system combines the PID control program to perform data prediction, and the formula is as follows: in: u(t) is the control output, i.e. the valve opening adjustment; K p is the proportional gain, which affects the system’s response to the current error; e(t) is the current error, the difference between the set temperature and the actual temperature, in °C; K i is the integral gain, accumulating past errors; is the integral of the error, indicating the accumulation of past errors and helping to eliminate steady-state errors. The unit is ℃·s; K d is the differential gain, which affects the system's response to the rate of change of the error; It is the derivative of the error, indicating the speed at which the current error changes, in units of °C / s.

6. A high-precision electric temperature control valve according to claim 4, characterized in that: The feedback mechanism and data analysis system Python's Pandas library analyzes the collected data, identifies the temperature change pattern and updates the control strategy. The formula of the prediction model is as follows: T pred =a·T current +b·T past +c Where: T pred To predict the temperature, T current is the current temperature, T past is the historical temperature, a, b, c are the regression coefficients; The fault detection probability formula is as follows: P fail =1-e -λt in: P fail is the probability of failure, ranging from 0 to 1; λ is the failure rate, the expected number of failures per unit time, in 1 / s; t is the running time, detection cycle, in seconds; e is a natural constant, approximately equal to 2.71828, and represents the base of the exponential function.

7. A high-precision electric temperature control valve according to claim 4, characterized in that: The adaptive algorithm system conducts multiple tests based on the parameters of the monitored environmental variables and compares the temperature control effects under different environments to optimize the algorithm parameters. The formula corresponding to the algorithm is as follows: in: K adaptive is the adaptive gain, the gain adjusted in real time; K base is the basic gain, the initial setting of the system; α is the adjustment coefficient, which affects the sensitivity of gain change; d is the current environmental change, indicating the change in temperature or pressure, in ℃ or Pa; d max It is the maximum variation, the maximum acceptable variation in system design, in ℃ or Pa.

8. The high-precision electric temperature control valve according to claim 4, characterized in that: The valve is optimized and adjusted in the auxiliary intelligent decision-making system, and the optimization target formula is as follows: in: J is the optimization target and comprehensive performance index; L is the loss function, which defines the performance metrics, including temperature error and energy consumption; x(t) is the system state, describing the temperature and flow rate of the fluid, in °C, L / s; u(t) is the control input, i.e. the opening of the valve; T is the time range, the duration of optimization, in seconds.

9. The high-precision electronically controlled temperature control valve according to claim 1, characterized in that: The operation process of the system is as follows: Sp1: System startup: the MCU main control system starts, loads initial parameters, checks the working status of each sensor and actuator, and ensures that the system is normal; Sp2: User input setting, the user enters the desired temperature target T through the graphical user interface connected to the external microcontroller main control system set ; Sp3: Data monitoring, the sensor continuously monitors the current temperature T of the fluid inside the temperature control valve body (1) current and pressure, storing data into the database regularly and recording the running time t to evaluate the failure rate; Sp4: Error calculation, according to the formula e(t) = T set -T current Calculate the current error; Sp5: application of control algorithm, the intelligent control system uses PID control algorithm to calculate control output u(t), adjusts valve opening according to output command, and controls the opening state of valve core body (4) through electric control guide valve stem (2); Sp6: Adaptive gain adjustment. The adaptive algorithm system monitors the environmental change d and adjusts the gain according to the formula K adaptive Calculate adaptive gain, update gain parameters in PID control, and optimize control response; Sp 7: Feedback mechanism, the feedback mechanism and the data analysis system continuously monitor the system status, using formula P fail =1-e -λt Assess the probability of failure and, if an abnormal condition is detected, trigger an alarm and automatically adjust the control strategy; Sp8: Data analysis and decision-making, the auxiliary intelligent decision-making system uses historical data and identifies trends, regularly analyzes temperature and pressure changes, and automatically adjusts valve strategies based on analysis results and weather forecasts; Sp9: System feedback and optimization, the MCU main control system collects user feedback on system performance, continuously optimizes control algorithms and decision models, and adapts to changing operating conditions.

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