Liquid cooling system control method and system

Abstract

The embodiment of the invention provides a liquid cooling system control method and system, and belongs to the technical field of equipment temperature control. The method is applied to liquid cooling system control of refining heating furnace monitoring equipment and comprises the steps that real-time operation information of a refining heating furnace is collected, and all working conditions of the refining heating furnace are simulated based on the real-time operation information; based on the simulated working condition, determining operation state information of each monitoring device; based on the operation state information, generating an adjustment rule of the liquid cooling system corresponding to each monitoring device through a fuzzy control rule; and adjusting the operation state of each liquid cooling system based on the adjustment rule. According to the scheme, the problems that an existing liquid cooling system control scheme of refining heating furnace monitoring equipment cannot be suitable for the hearth working environment and the refined control performance is poor are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment temperature control, and in particular to a liquid cooling system control method and a liquid cooling system control system. Background Art

[0002] In a refining enterprise, the refining heating furnace is a very important equipment. The tubular refining heating furnace uses the high-temperature flame and flue gas generated by the combustion of fuel in the furnace as a heat source to heat the medium flowing at high speed in the furnace tube to reach the temperature specified by the refining process. The refining heating furnace accounts for a very high proportion of the energy consumption in the entire refining enterprise, so how to improve the system power consumption of the heating furnace is of significant significance to improving the power consumption of the entire enterprise. In order to achieve the improvement of the thermal efficiency of the refining heating furnace, it is essential to achieve the refined control of the heating furnace, and in order to achieve the refined operation of the heating furnace, the corresponding system operation status is also essential. Full perception. In the existing scheme, in order to improve the perception effect of the entire heating furnace, a variety of monitoring systems are set up in the entire heating furnace, and real-time monitoring of equipment operation data is carried out during the operation of the heating furnace to achieve full perception of the operation status of the entire heating furnace.

[0003] Although adding a large number of monitoring systems is conducive to the realization of refined control of the heating furnace, because the heating furnace itself is a high-temperature operating equipment, its monitoring environment is extremely harsh, and the monitoring system needs to continue to work under high temperature conditions, which places extremely high requirements on the operating stability of the monitoring system. In order to ensure the stable operation of the independent monitoring system, it is necessary to configure a corresponding cooling device for the monitoring system. The liquid cooling system has an excellent cooling effect. It absorbs the heat of the monitoring equipment through the flowing liquid cooling medium to ensure that the monitoring equipment is within the normal working temperature range. In the existing liquid cooling system control scheme for monitoring equipment of the refining heating furnace, the conventional control method is mainly used to simply use the liquid cooling system and the monitoring equipment to start and stop synchronously to achieve protection during the operation of the monitoring equipment. However, for the monitoring equipment of the refining heating furnace, especially the equipment set in the furnace, because it needs to directly monitor the flame state of the furnace nozzle or the heating state of the furnace tube in the furnace, the harshness of its operating environment is far greater than the operating environment of the liquid cooling system in other existing fields. If it is only the liquid cooling system control scheme of the existing scheme, it cannot cope with the variable temperature state in the furnace, and the protection of the monitoring equipment cannot meet the design requirements. In addition, the existing liquid cooling control system cannot be finely linked based on the load control of the refining heating furnace due to the different refining loads, and it is also impossible to improve the power consumption of the entire system through fine control. In view of the problems that the existing liquid cooling system control scheme of the refining heating furnace monitoring equipment cannot be applied to the furnace working environment and has poor fine control performance, it is necessary to create a new liquid cooling system control scheme suitable for refining heating furnaces. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a liquid cooling system control method and system to at least solve the problems of the existing liquid cooling system control scheme of the refining heating furnace monitoring equipment being unable to adapt to the furnace working environment and having poor refined control performance.

[0005] In order to achieve the above-mentioned purpose, the first aspect of the present invention provides a liquid cooling system control method, which is applied to the liquid cooling system control of the refining heating furnace monitoring equipment, and the method includes: collecting real-time operation information of the refining heating furnace, and simulating the full working condition of the refining heating furnace based on the real-time operation information; based on the simulated working condition, determining the operating status information of each monitoring device; based on the operating status information, generating adjustment rules for the liquid cooling system corresponding to each monitoring device through fuzzy control rules; based on the adjustment rules, adjusting the operating status of each liquid cooling system.

[0006] Optionally, the real-time operation information of the refining heating furnace includes: heating furnace load control information, combustion status information of each furnace nozzle, furnace tube temperature information and furnace design information.

[0007] Optionally, the full operating condition simulation of the refining heating furnace based on the real-time operating information includes: constructing a corresponding virtual model based on the furnace design information; in the virtual model, simulating the temperature field based on the combustion state information of each furnace nozzle and the furnace tube temperature information, and obtaining the real-time temperature field information in the furnace; in the virtual model, predicting the temperature field in a future preset time period based on the heating furnace load control information and the real-time temperature field information in the furnace, and obtaining the predicted temperature field information in the furnace; using the real-time temperature field information and the predicted temperature field information in the furnace as the full operating condition simulation result of the refining heating furnace.

[0008] Optionally, the operation status information of each monitoring device is determined based on the simulated working conditions, including: reading the setting position information of each monitoring device based on the furnace design information; determining the real-time ambient temperature information of each monitoring device based on the setting position information and the real-time temperature field information in the furnace; determining the real-time working temperature information of each monitoring device based on the real-time operation information of each monitoring device; determining the real-time temperature information of each monitoring device based on the real-time ambient temperature information and the real-time working temperature information of each monitoring device; determining the predicted ambient temperature information of each monitoring device based on the setting position information of each monitoring device and the predicted temperature field information in the furnace; simulating the working status of each monitoring device in a preset time period in the future based on the heating furnace load control information, and identifying the predicted working temperature information of each monitoring device based on the simulation results; determining the predicted temperature information of each monitoring device based on the predicted ambient temperature information and the predicted working temperature information of each monitoring device; using the real-time temperature information and the predicted temperature information of each monitoring device as the operation status information of each monitoring device.

[0009] Optionally, the adjustment rules of the liquid cooling system include: the coolant medium type of the liquid cooling system, the coolant flow rate and the pressure in the coolant pipe; wherein the coolant medium type of the liquid cooling system is cooling water or cooling oil.

[0010] Optionally, based on the operating status information, adjustment rules for the liquid cooling system corresponding to each monitoring device are generated through fuzzy control rules, including: based on the operating status information, identifying association rules in a preset fuzzy control rule table; based on the identified association rules, performing fuzzy set operations on each association rule to obtain multiple fuzzy matrices; taking the union of the multiple fuzzy matrices obtained to obtain fuzzy relations; based on a preset error vector and the fuzzy relations, outputting a fuzzy decision quantity; performing defuzzification processing based on the fuzzy decision quantity to obtain fuzzy control rules as adjustment rules for the liquid cooling system corresponding to each monitoring device; wherein, the adjustment rules for the liquid cooling system corresponding to each monitoring device include real-time control rules and predictive control rules for the liquid cooling system corresponding to each monitoring device.

[0011] Optionally, the method also includes generating the preset fuzzy control rule table, including: respectively presetting an expert library and the coolant medium type of the liquid cooling system, the coolant flow rate and the pressure in the coolant pipe to generate a corresponding variable partition table; wherein, in the variable partition table, there are multiple output levels determined based on the difference between the target state and the actual state of the expected liquid cooling system under the operating status information of different monitoring devices, and the larger the level, the greater the difference between the target state and the actual state; based on the preset expert library, multiple control output levels are preset, and the control output levels are matched one-to-one with the rules in each variable partition table, and a fuzzy control rule table is generated based on the matched rules.

[0012] Optionally, the fuzzy relationship solution formula is:

[0013] S=(N 1 ×T 1 ×F 1 ×P 1 )∪(N 2 ×T 2 ×F 2 ×P 2 )∪…∪(N i ×T j ×F k ×P m )

[0014] Among them, S is a fuzzy relationship; N i is the i-th control output level; T j is the jth coolant medium type; F k is the flow rate level of the kth coolant flow; P mis the pressure level of the pressure in the mth coolant pipe.

[0015] Optionally, the operating status of each liquid cooling system is adjusted based on the adjustment rules, including: based on the determined coolant medium type of the liquid cooling system, opening the circulating pipe valve of the corresponding coolant type, and closing the circulating pipe valves of other coolant types; based on the determined coolant flow rate and pressure in the coolant pipe, adjusting the opening and closing degree of the circulating pipe valve of the current coolant type.

[0016] Optionally, if there is a difference between the predictive control rule and the real-time control rule, the corresponding state correction time is determined; based on the predictive control rule, a control instruction is generated in advance, and a corresponding control timing table is generated based on the generated control instruction and the state correction time; the control timing table is sent to the liquid cooling control system of the corresponding monitoring device, and the execution process of the corresponding liquid cooling system state control based on the control timing table is monitored.

[0017] The second aspect of the present invention provides a liquid cooling system control system, which is applied to the liquid cooling system control of the refining heating furnace monitoring equipment, and the system includes: an acquisition unit, which is used to acquire the real-time operation information of the refining heating furnace, and simulate the full working condition of the refining heating furnace based on the real-time operation information; a processing unit, which is used to determine the operating status information of each monitoring device based on the simulated working condition; a generation unit, which is used to generate adjustment rules for the liquid cooling system corresponding to each monitoring device through fuzzy control rules based on the operating status information; and an execution unit, which is used to adjust the operating status of each liquid cooling system based on the adjustment rule.

[0018] On the other hand, the present invention provides a computer-readable storage medium, on which instructions are stored, which, when executed on a computer, enable the computer to execute the above-mentioned liquid cooling system control method.

[0019] Through the above technical solution, the solution of the present invention simulates the full working conditions of the refining heating furnace based on the real-time operating information, ensuring full perception of the temperature distribution in the furnace. Based on the full perception of the temperature field, the operating environment of each monitoring device is differentiated, and then the liquid cooling system is differentiated according to the differentiated operating environment of each monitoring device and the operating status of each monitoring device, so as to achieve refined control of the entire system.

[0020] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0022] Figure 1 is a flow chart of steps of a liquid cooling system control method provided by one embodiment of the present invention;

[0023] Figure 2 It is a system structure diagram of a liquid cooling system control system provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0024] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0025] In the refining enterprise, the refining heating furnace is a very important equipment. The tubular refining heating furnace uses the high-temperature flame and flue gas generated by the combustion of fuel in the furnace as the heat source to heat the medium flowing at high speed in the furnace tube to reach the temperature specified by the refining process. The refining heating furnace accounts for a very high proportion of the energy consumption in the entire refining enterprise, so how to improve the system power consumption of the heating furnace is of great significance to improving the power consumption of the entire enterprise.

[0026] In order to improve the thermal efficiency of the refining heating furnace, it is essential to achieve refined control of the heating furnace. In order to achieve refined operation of the heating furnace, full perception of the corresponding system operation status is also essential. In the existing solution, in order to improve the perception effect of the entire heating furnace, a variety of monitoring systems are set up in the entire heating furnace to monitor the equipment operation data in real time during the operation of the heating furnace, so as to achieve full perception of the operation status of the entire heating furnace.

[0027] Although adding a large number of monitoring systems is conducive to the realization of refined control of the heating furnace, the heating furnace itself is a high-temperature operating equipment, and its monitoring environment is extremely harsh. The monitoring system needs to work continuously at high temperatures, which places extremely high demands on the operating stability of the monitoring system. In order to ensure the stable operation of the independent monitoring system, it is necessary to configure the corresponding cooling device for the monitoring system. The liquid cooling system has an excellent cooling effect. It absorbs the heat of the monitoring equipment through the flowing liquid cooling medium to ensure that the monitoring equipment is within the normal working temperature range.

[0028] In the existing liquid cooling system control scheme for monitoring equipment of refining and heating furnaces, conventional control methods are mainly simply used, and the liquid cooling system and the monitoring equipment are started and stopped synchronously to achieve protection of the monitoring equipment during operation. However, for the monitoring equipment of the refining and heating furnace, especially the equipment installed in the furnace, because it needs to directly monitor the flame state of the nozzle or the heating state of the furnace tube in the furnace, the severity of its operating environment is much greater than the operating environment of the liquid cooling system in other existing fields. If it is only the liquid cooling system control scheme of the existing scheme, it cannot cope with the changeable temperature state in the furnace, and the protection of the monitoring equipment cannot meet the design requirements. In addition, in view of different refining loads, the existing liquid cooling control system cannot perform refined linkage based on the load regulation of the refining and heating furnace, and it is also impossible to improve the power consumption of the entire system through refined control.

[0029] In view of the problems that the existing liquid cooling system control scheme of the monitoring equipment of the refining heating furnace cannot be applied to the working environment of the furnace and has poor refined control performance, the scheme of the present invention proposes a new liquid cooling system control method, which is applied to the liquid cooling system control of the monitoring equipment of the refining heating furnace. The scheme of the present invention simulates its full working conditions based on the real-time operation information of the refining heating furnace to ensure full perception of the temperature distribution in the furnace. Based on the full perception of the temperature field, the operating environment of each monitoring device is differentiatedly perceived, and then the differentiated liquid cooling system control is carried out according to the differentiated operating environment of each monitoring device and the operating status of each monitoring device, so as to realize refined control of the entire system.

[0030] Figure 1 FIG. 1 is a flow chart of a method for controlling a liquid cooling system provided by an embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a liquid cooling system control method, the method comprising:

[0031] Step S10: collecting real-time operation information of the refining heating furnace, and performing full-operation simulation of the refining heating furnace based on the real-time operation information.

[0032] Specifically, the scheme of the present invention aims to achieve refined control of the liquid cooling system of the refining heating furnace monitoring equipment, and the corresponding solution is to achieve differentiated control of each monitoring device. Different monitoring devices are set in different locations, and the corresponding working environment temperatures are different. The normal working temperatures of different monitoring devices are also different. In order to achieve differentiated management of the liquid cooling system in view of the difference in working environment temperature and working temperature, while ensuring the minimum normal operation of each monitoring device, the operating power consumption of each liquid cooling system is minimized as much as possible, which can bring huge benefits to the entire enterprise in terms of energy conservation and emission reduction.

[0033] Embodiment 1:

[0034] Preferably, the real-time operation information of the refining heating furnace includes: heating furnace load control information, combustion status information of each furnace nozzle, furnace tube temperature information, and furnace design information.

[0035] In the embodiment of the present invention, in order to fully perceive the temperature distribution in the furnace, the operating status of the entire refining heating furnace needs to be fully perceived. Based on this, it is necessary to collect the combustion status information of each furnace nozzle and the temperature information of the furnace tube. This information can directly simulate the heat source in the furnace. Collecting the furnace design information can accurately understand the temperature field distribution in the entire furnace based on the location and status of the heat source. The purpose of collecting the heating furnace load control information is to perceive the operating information of the heating furnace in advance, to ensure that before the heating furnace state is corrected, the corresponding liquid cooling system can complete the linkage in advance, to avoid the monitoring equipment being temporarily in a state where the liquid cooling system cannot protect it, to reduce equipment damage, and to improve the intelligence of the entire system.

[0036] Embodiment 2:

[0037] Preferably, the full-operating-condition simulation of the refining heating furnace based on the real-time operating information includes: constructing corresponding virtual model information based on the furnace design information; in the virtual model, simulating the temperature field based on the combustion state information of each furnace nozzle and the furnace tube temperature information, and obtaining the real-time temperature field information in the furnace; in the virtual model, predicting the temperature field in a future preset time period based on the heating furnace load control information and the real-time temperature field information, and obtaining the predicted temperature field information in the furnace; and using the real-time temperature field information and the predicted temperature field information as the full-operating-condition simulation result of the refining heating furnace.

[0038] In the embodiment of the present invention, it has been explained above that the solution of the present invention wants to solve two technical problems, namely, while protecting the stable operation of the current monitoring equipment, it is necessary to perceive the load adjustment state of the heating furnace in advance, and then realize the early linkage of the liquid cooling system. Therefore, when performing full working condition simulation, on the one hand, it is necessary to simulate the existing state, and on the other hand, it is necessary to predict and simulate the future full working conditions based on the control data. Obtain the corresponding two working condition simulation results, and determine the subsequent control rules for different simulation results.

[0039] Step S20: Based on the simulated working conditions, determine the operating status information of each monitoring device.

[0040] Specifically, based on the furnace design information, the setting position information of each monitoring device is read; based on the setting position information and the real-time temperature field information, the real-time ambient temperature information of each monitoring device is determined; based on the real-time operation information of each monitoring device, the real-time working temperature information of each monitoring device is determined; based on the real-time ambient temperature information and the real-time working temperature information, the real-time temperature information of each monitoring device is determined; based on the setting position information and the predicted temperature field information, the predicted ambient temperature information of each monitoring device is determined; based on the heating furnace load control information, the working state of the monitoring device for a predetermined future time period is simulated, and the predicted working temperature information of each monitoring device is identified based on the simulation results; based on the predicted ambient temperature information and the predicted working temperature information, the predicted temperature information of each monitoring device is determined; and the real-time temperature information and the predicted temperature information are used as the operating state information of each monitoring device.

[0041] In the embodiment of the present invention, in order to effectively solve the real-time adjustment and advance linkage adjustment of the liquid cooling system, when the present invention determines the operating status of the monitoring device, the real-time temperature information and predicted temperature information of the environment in which it is located are predicted respectively, and combined with the working temperature information results of the monitoring device, the actual working status information of each monitoring device can be accurately known. Then, based on the actual working status information, the corresponding liquid cooling system control can be performed to ensure that each monitoring device can maintain a normal working state.

[0042] Step S30: Based on the operation status information, an adjustment rule for each monitoring device corresponding to the liquid cooling system is generated through fuzzy control rules.

[0043] Preferably, the adjustment rules of the liquid cooling system include: the coolant medium type of the liquid cooling system, the coolant flow rate and the pressure in the coolant pipe; wherein the coolant medium type of the liquid cooling system is cooling water or cooling oil.

[0044] In the embodiment of the present invention, water has a better specific heat capacity than oil, so theoretically the cooling effect of water is better than that of oil. However, when water leaks, it is easy to cause damage to the equipment, while oil can avoid this problem. Therefore, when selecting a medium, it is necessary to choose between the cooling effect and the equipment protection effect. The liquid cooling system of the present invention has two media. When the operating temperature of the equipment is too high and a better cooling effect is required, cooling water is switched to be used as the cooling medium. When the operating temperature of the equipment is moderate and the cooling demand is not high, cooling oil can be selected as the cooling medium.

[0045] Of course, in other application embodiments, if one of the cooling media is damaged, another medium may be selected to perform cooling. If one of the cooling media has risks, such as aging of the pipeline, cooling hot oil easily ignited, etc., another cooling medium may be selected accordingly.

[0046] Embodiment 3:

[0047] Specifically, the adjustment rules for the liquid cooling system corresponding to each monitoring device are generated through fuzzy control rules based on the operating status information, including: based on the operating status information, identifying association rules in a preset fuzzy control rule table; based on the identified association rules, performing fuzzy set operations on each association rule to obtain multiple fuzzy matrices; obtaining a fuzzy relationship by taking the union of the multiple fuzzy matrices obtained; outputting a fuzzy decision quantity after synthesizing the fuzzy relationship based on a preset error vector; performing defuzzification processing based on the fuzzy decision quantity to obtain fuzzy control rules as adjustment rules for the liquid cooling system corresponding to each monitoring device; wherein, the adjustment rules for the liquid cooling system corresponding to each monitoring device include real-time control rules and predictive control rules for the liquid cooling system corresponding to each monitoring device.

[0048] In the embodiment of the present invention, fuzzy control is an intelligent control method based on fuzzy set theory, fuzzy language variables and fuzzy logic reasoning. It is an intelligent control method that imitates the fuzzy reasoning and decision-making process of people in terms of behavior. The method first compiles the operator or expert experience into fuzzy rules, then fuzzifies the real-time signal from the sensor, uses the fuzzified signal as the input of the fuzzy rule, completes the fuzzy reasoning, and adds the output obtained after reasoning to the actuator. Fuzzy control has strong robustness, and because it does not require an accurate mathematical model, its rule generation speed is fast. When generating the control rules for the liquid cooling system, the response speed is fast, which makes the protection performance of the monitoring equipment more stable.

[0049] Preferably, the method also includes generating the preset fuzzy control rule table, including: respectively presetting an expert library and the coolant medium type of the liquid cooling system, the coolant flow rate and the pressure in the coolant pipe to generate a corresponding variable partition table; in the variable partition table, there are multiple output levels determined based on the difference between the target state and the actual state of the expected liquid cooling system under the operating status information of different monitoring devices, and the larger the level, the greater the difference between the target state and the actual state; based on the preset expert library, multiple control output levels are preset, and the control output levels are matched one-to-one with the rules in each variable partition table, and a fuzzy control rule table is generated based on the matched rules.

[0050] Preferably, the fuzzy relationship solution formula is:

[0051] S=(N 1 ×T 1 ×F 1 ×P 1 )∪(N 2 ×T 2 ×F 2×P 2 )∪…∪(N i ×T j ×F k ×P m )

[0052] Among them, S is a fuzzy relationship; N i is the i-th control output level; T j is the jth coolant medium type; F k is the flow rate level of the kth coolant flow; P m is the pressure level of the pressure in the mth coolant pipe.

[0053] Embodiment 4:

[0054] In a possible real-time method, the variable partition table of the coolant medium type of the liquid cooling system is as follows:

[0055] As shown in Table 1:

[0056]

[0057] Table 1 Variable classification table of coolant medium types of liquid cooling system

[0058] Among them, the variable level is set to two levels, which are determined based on the expert database. For example, when it is determined that the cooling demand meets the preset amount, it is determined that the corresponding cooling medium is water, then the corresponding N 1 The fuzzy set of water as the medium has a corresponding level of 0 and a membership of 1. This membership is a control quantity preset based on the expert database. For the medium, 1 means selecting the medium. For the flow control rule, there may be multiple memberships. Different memberships represent different opening and closing degrees of the valve. Based on the membership, the preset valve opening and closing degree can be directly corresponded. After the anti-fuzzy rule is passed, the corresponding integrated membership needs to be inferred, and the control rule is determined based on the membership.

[0059] For rule operation, the fuzzy set operation within the rule takes the intersection, and the fuzzy set operation between the rules takes the union. After obtaining the fuzzy relationship, the fuzzy decision quantity can be output based on the fuzzy relationship and the preset error vector. The formula is:

[0060] u=e*S

[0061] Among them, u is the fuzzy decision quantity; e is the preset error vector.

[0062] Furthermore, defuzzification processing is performed based on the fuzzy decision quantity to obtain fuzzy control rules as adjustment rules for the liquid cooling system corresponding to each monitoring device.

[0063] Step S40: Based on the adjustment rule, the operating status of each liquid cooling system is adjusted.

[0064] Specifically, based on the determined coolant medium type of the liquid cooling system, the circulating pipeline valve of the corresponding coolant type is opened, and the circulating pipeline valves of other coolant types are closed; based on the determined coolant flow rate and the pressure in the coolant pipe, the opening and closing degree of the circulating pipeline valve of the current coolant type is adjusted.

[0065] Preferably, if there is a difference between the predictive control rule and the real-time control rule, the corresponding state correction time is determined; based on the predictive control rule, a control instruction is generated in advance, and a corresponding control timing table is generated based on the generated control instruction and the state correction time; the control timing table is sent to the liquid cooling control system of the corresponding monitoring device, and it is monitored to execute the corresponding liquid cooling system state control based on the control timing table.

[0066] Embodiment 5:

[0067] Figure 2 1 is a system structure diagram of a liquid cooling system control system provided by an embodiment of the present invention. Figure 2 As shown, an embodiment of the present invention provides a system of a liquid cooling system control system, the system comprising: an acquisition unit, used to acquire real-time operation information of a refining heating furnace, and perform full-condition simulation of the refining heating furnace based on the real-time operation information; a processing unit, used to determine the operation status information of each monitoring device based on the simulated working condition; a generation unit, used to generate adjustment rules for the liquid cooling system corresponding to each monitoring device through fuzzy control rules based on the operation status information; and an execution unit, used to adjust the operation status of each liquid cooling system based on the adjustment rule.

[0068] Specifically, the scheme of the present invention aims to achieve refined control of the liquid cooling system of the refining heating furnace monitoring equipment, and the corresponding solution is to achieve differentiated control of each monitoring device. Different monitoring devices are set in different locations, and the corresponding working environment temperatures are different. The normal working temperatures of different monitoring devices are also different. In order to achieve differentiated management of the liquid cooling system in view of the difference in working environment temperature and working temperature, while ensuring the minimum normal operation of each monitoring device, the operating power consumption of each liquid cooling system is minimized as much as possible, which can bring huge benefits to the entire enterprise in terms of energy conservation and emission reduction.

[0069] Preferably, the real-time operation information of the refining heating furnace includes: heating furnace load control information, combustion status information of each furnace nozzle, furnace tube temperature information, and furnace design information.

[0070] In the embodiment of the present invention, in order to fully perceive the temperature distribution in the furnace, the operating status of the entire refining heating furnace needs to be fully perceived. Based on this, it is necessary to collect the combustion status information of each furnace nozzle and the temperature information of the furnace tube. This information can directly simulate the heat source in the furnace. Collecting the furnace design information can accurately understand the temperature field distribution in the entire furnace based on the location and status of the heat source. The purpose of collecting the heating furnace load control information is to perceive the operating information of the heating furnace in advance, to ensure that before the heating furnace state is corrected, the corresponding liquid cooling system can complete the linkage in advance, to avoid the monitoring equipment being temporarily in a state where the liquid cooling system cannot protect it, to reduce equipment damage, and to improve the intelligence of the entire system.

[0071] Preferably, the full-operating-condition simulation of the refining heating furnace based on the real-time operating information includes: constructing corresponding virtual model information based on the furnace design information; in the virtual model, simulating the temperature field based on the combustion state information of each furnace nozzle and the furnace tube temperature information, and obtaining the real-time temperature field information in the furnace; in the virtual model, predicting the temperature field in a future preset time period based on the heating furnace load control information and the real-time temperature field information, and obtaining the predicted temperature field information in the furnace; and using the real-time temperature field information and the predicted temperature field information as the full-operating-condition simulation result of the refining heating furnace.

[0072] In the embodiment of the present invention, it has been explained above that the solution of the present invention wants to solve two technical problems, namely, while protecting the stable operation of the current monitoring equipment, it is necessary to perceive the load adjustment state of the heating furnace in advance, and then realize the early linkage of the liquid cooling system. Therefore, when performing full working condition simulation, on the one hand, it is necessary to simulate the existing state, and on the other hand, it is necessary to predict and simulate the future full working conditions based on the control data. Obtain the corresponding two working condition simulation results, and determine the subsequent control rules for different simulation results.

[0073] Furthermore, the processing unit is used to determine the operating status information of each monitoring device based on the simulated working conditions.

[0074] Specifically, based on the furnace design information, the setting position information of each monitoring device is read; based on the setting position information and the real-time temperature field information, the real-time ambient temperature information of each monitoring device is determined; based on the real-time operation information of each monitoring device, the real-time working temperature information of each monitoring device is determined; based on the real-time ambient temperature information and the real-time working temperature information, the real-time temperature information of each monitoring device is determined; based on the setting position information and the predicted temperature field information, the predicted ambient temperature information of each monitoring device is determined; based on the heating furnace load control information, the working state of the monitoring device for a predetermined future time period is simulated, and the predicted working temperature information of each monitoring device is identified based on the simulation results; based on the predicted ambient temperature information and the predicted working temperature information, the predicted temperature information of each monitoring device is determined; and the real-time temperature information and the predicted temperature information are used as the operating state information of each monitoring device.

[0075] In the embodiment of the present invention, in order to effectively solve the real-time adjustment and advance linkage adjustment of the liquid cooling system, when the present invention determines the operating status of the monitoring device, the real-time temperature information and predicted temperature information of the environment in which it is located are predicted respectively, and combined with the working temperature information results of the monitoring device, the actual working status information of each monitoring device can be accurately known. Then, based on the actual working status information, the corresponding liquid cooling system control can be performed to ensure that each monitoring device can maintain a normal working state.

[0076] Furthermore, the generating unit is used to generate adjustment rules for the liquid cooling system corresponding to each monitoring device through fuzzy control rules based on the operating status information.

[0077] Preferably, the adjustment rules of the liquid cooling system include: the coolant medium type of the liquid cooling system, the coolant flow rate and the pressure in the coolant pipe; wherein the coolant medium type of the liquid cooling system is cooling water or cooling oil.

[0078] In the embodiment of the present invention, water has a better specific heat capacity than oil, so theoretically the cooling effect of water is better than that of oil. However, when water leaks, it is easy to cause damage to the equipment, while oil can avoid this problem. Therefore, when selecting a medium, it is necessary to choose between the cooling effect and the equipment protection effect. The liquid cooling system of the present invention has two media. When the operating temperature of the equipment is too high and a better cooling effect is required, cooling water is switched to be used as the cooling medium. When the operating temperature of the equipment is moderate and the cooling demand is not high, cooling oil can be selected as the cooling medium.

[0079] Of course, in other application embodiments, if one of the cooling media is damaged, another medium may be selected to perform cooling. If one of the cooling media has risks, such as aging of the pipeline, cooling hot oil easily ignited, etc., another cooling medium may be selected accordingly.

[0080] Specifically, the adjustment rules for the liquid cooling system corresponding to each monitoring device are generated through fuzzy control rules based on the operating status information, including: based on the operating status information, identifying association rules in a preset fuzzy control rule table; based on the identified association rules, performing fuzzy set operations on each association rule to obtain multiple fuzzy matrices; obtaining a fuzzy relationship by taking the union of the multiple fuzzy matrices obtained; outputting a fuzzy decision quantity after synthesizing the fuzzy relationship based on a preset error vector; performing defuzzification processing based on the fuzzy decision quantity to obtain fuzzy control rules as adjustment rules for the liquid cooling system corresponding to each monitoring device; wherein, the adjustment rules for the liquid cooling system corresponding to each monitoring device include real-time control rules and predictive control rules for the liquid cooling system corresponding to each monitoring device.

[0081] In the embodiment of the present invention, fuzzy control is an intelligent control method based on fuzzy set theory, fuzzy language variables and fuzzy logic reasoning. It is an intelligent control method that imitates the fuzzy reasoning and decision-making process of people in terms of behavior. The method first compiles the operator or expert experience into fuzzy rules, then fuzzifies the real-time signal from the sensor, uses the fuzzified signal as the input of the fuzzy rule, completes the fuzzy reasoning, and adds the output obtained after reasoning to the actuator. Fuzzy control has strong robustness, and because it does not require an accurate mathematical model, its rule generation speed is fast. When generating the control rules for the liquid cooling system, the response speed is fast, which makes the protection performance of the monitoring equipment more stable.

[0082] Preferably, the method also includes generating the preset fuzzy control rule table, including: respectively presetting an expert library and the coolant medium type of the liquid cooling system, the coolant flow rate and the pressure in the coolant pipe to generate a corresponding variable partition table; in the variable partition table, there are multiple output levels determined based on the difference between the target state and the actual state of the expected liquid cooling system under the operating status information of different monitoring devices, and the larger the level, the greater the difference between the target state and the actual state; based on the preset expert library, multiple control output levels are preset, and the control output levels are matched one-to-one with the rules in each variable partition table, and a fuzzy control rule table is generated based on the matched rules.

[0083] Preferably, the fuzzy relationship solution formula is:

[0084] S=(N 1 ×T 1 ×F1 ×P 1 )∪(N 2 ×T 2 ×F 2 ×P 2 )∪…∪(N i ×T j ×F k ×P m )

[0085] Among them, S is a fuzzy relationship; N i is the i-th control output level; T j is the jth coolant medium type; F k is the flow rate level of the kth coolant flow; P m is the pressure level of the pressure in the mth coolant pipe.

[0086] For rule operation, the fuzzy set operation within the rule takes the intersection, and the fuzzy set operation between the rules takes the union, and after obtaining the fuzzy relationship, the fuzzy decision quantity can be output based on the fuzzy relationship and the preset error vector. The formula is:

[0087] u=e*S

[0088] Among them, u is the fuzzy decision quantity; e is the preset error vector.

[0089] Furthermore, defuzzification processing is performed based on the fuzzy decision quantity to obtain fuzzy control rules as adjustment rules for the liquid cooling system corresponding to each monitoring device.

[0090] Furthermore, the execution unit is used to adjust the operating status of each liquid cooling system based on the adjustment rule.

[0091] Specifically, based on the determined coolant medium type of the liquid cooling system, the circulating pipeline valve of the corresponding coolant type is opened, and the circulating pipeline valves of other coolant types are closed; based on the determined coolant flow rate and the pressure in the coolant pipe, the opening and closing degree of the circulating pipeline valve of the current coolant type is adjusted.

[0092] Preferably, if there is a difference between the predictive control rule and the real-time control rule, the corresponding state correction time is determined; based on the predictive control rule, a control instruction is generated in advance, and a corresponding control timing table is generated based on the generated control instruction and the state correction time; the control timing table is sent to the liquid cooling control system of the corresponding monitoring device, and it is monitored to execute the corresponding liquid cooling system state control based on the control timing table.

[0093] The embodiment of the present invention further provides a computer-readable storage medium, on which instructions are stored, which, when executed on a computer, enable the computer to execute the above-mentioned liquid cooling system control method.

[0094] Those skilled in the art will understand that all or part of the steps in the method for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions for making a single-chip microcomputer, a chip or a processor (processor) perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0095] The optional embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the technical concept of the embodiments of the present invention, the technical scheme of the embodiments of the present invention can be subjected to a variety of simple modifications, and these simple modifications all belong to the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0096] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A liquid cooling system control method, applied to the liquid cooling system control of a refining heating furnace monitoring device, characterized in that: The method comprises: Collecting real-time operation information of the refining heating furnace, and simulating the full working condition of the refining heating furnace based on the real-time operation information; Based on the simulated working conditions, determine the operating status information of each monitoring device; Based on the operation status information, generating adjustment rules for the liquid cooling system corresponding to each monitoring device through fuzzy control rules; Based on the adjustment rules, the operating status of each liquid cooling system is adjusted.

2. The method according to claim 1, characterized in that The real-time operation information of the refining heating furnace includes: Heating furnace load control information, combustion status information of each furnace nozzle, furnace tube temperature information and furnace design information.

3. The method according to claim 2, characterized in that The full working condition simulation of the refining heating furnace based on the real-time operation information includes: Building a corresponding virtual model based on the furnace design information; In the virtual model, a temperature field simulation is performed based on the combustion state information of each furnace nozzle and the temperature information of the furnace tube to obtain real-time temperature field information in the furnace; In the virtual model, based on the heating furnace load control information and the real-time temperature field information in the furnace, the temperature field in the future preset time period is predicted to obtain the predicted temperature field information in the furnace; The real-time temperature field information and predicted temperature field information in the furnace are used as the full-operating condition simulation results of the refining heating furnace.

4. The method according to claim 3, characterized in that Determining the operating status information of each monitoring device based on the simulated working condition includes: Based on the furnace design information, read the setting location information of each monitoring device; Based on the setting position information and the real-time temperature field information in the furnace, determining the real-time ambient temperature information of each monitoring device; Determine the real-time operating temperature information of each monitoring device based on the real-time operation information of each monitoring device; Determine the real-time temperature information of each monitoring device based on the real-time ambient temperature information and the real-time operating temperature information of each monitoring device; Based on the setting position information of each monitoring device and the predicted temperature field information in the furnace, determine the predicted ambient temperature information of each monitoring device; Based on the heating furnace load control information, simulate the working state of each monitoring device in a preset future period, and identify the predicted working temperature information of each monitoring device based on the simulation result; Determine predicted temperature information of each monitoring device based on predicted ambient temperature information and predicted operating temperature information of each monitoring device; The real-time temperature information and predicted temperature information of each monitoring device are used as the operation status information of each monitoring device.

5. The method according to claim 1, characterized in that The adjustment rules of the liquid cooling system include: The type of coolant medium, coolant flow rate and pressure in the coolant pipe of the liquid cooling system; The coolant medium type of the liquid cooling system is cooling water or cooling oil.

6. The method according to claim 5, characterized in that The adjusting rules of the liquid cooling system corresponding to each monitoring device are generated based on the operating status information through fuzzy control rules, including: Based on the operation status information, identifying association rules in a preset fuzzy control rule table; Based on the identified association rules, fuzzy set operations are performed on each association rule to obtain multiple fuzzy matrices; The fuzzy relationship is obtained by obtaining a union of the obtained multiple fuzzy matrices; Outputting a fuzzy decision amount based on a preset error vector and the fuzzy relationship; Based on the fuzzy decision quantity, defuzzification processing is performed to obtain fuzzy control rules as adjustment rules for the liquid cooling system corresponding to each monitoring device; wherein, The adjustment rules of the liquid cooling system corresponding to each monitoring device include real-time control rules and predictive control rules of the liquid cooling system corresponding to each monitoring device.

7. The method according to claim 6, characterized in that The method further includes generating the preset fuzzy control rule table, including: The expert database and the coolant medium type of the liquid cooling system, the coolant flow rate and the pressure in the coolant pipe are respectively preset to generate a corresponding variable partition table; wherein, in the variable partition table, there are multiple output quantity levels determined based on the difference between the target state and the actual state of the expected liquid cooling system under the operation state information of different monitoring devices, and the larger the level, the greater the difference between the target state and the actual state; Based on the preset expert database, multiple control output levels are preset, and the control output levels are matched one by one with the rules in each variable division table, and a fuzzy control rule table is generated based on the matched rules.

8. The method according to claim 6, characterized in that The fuzzy relationship solution formula is: S=(N1×T1×F1×P1)∪(N2×T2×F2×P2)∪…∪(N i ×T j ×F k ×P m ) Among them, S is a fuzzy relationship; N i is the i-th control output level; T j is the jth coolant medium type; F k is the flow rate level of the kth coolant flow; P m is the pressure level of the pressure in the mth coolant pipe.

9. The method according to claim 6, characterized in that The adjusting the operating state of each liquid cooling system based on the adjustment rule includes: Based on the determined coolant medium type of the liquid cooling system, a circulation pipeline valve of the corresponding coolant type is opened, and circulation pipeline valves of other coolant types are closed; Based on the determined coolant flow rate and the pressure in the coolant pipe, the opening and closing degree of the circulation pipeline valve of the current coolant type is adjusted.

10. The method according to claim 9, characterized in that If there is a difference between the prediction control rule and the real-time control rule, then determining the corresponding state correction time; Based on the predictive control rule, a control instruction is generated in advance, and a corresponding control timing table is generated based on the generated control instruction and the state correction time; The control timing table is sent to the liquid cooling control system of the corresponding monitoring device, and the execution process of the corresponding liquid cooling system state control based on the control timing table is monitored.

11. A liquid cooling system control system, applied to the liquid cooling system control of a refining heating furnace monitoring device, characterized in that: The system comprises: A collection unit, used to collect real-time operation information of the refining heating furnace, and perform full-condition simulation of the refining heating furnace based on the real-time operation information; A processing unit, used to determine the operating status information of each monitoring device based on the simulated working condition; A generating unit, configured to generate, based on the operating status information, an adjustment rule for the liquid cooling system corresponding to each monitoring device through a fuzzy control rule; The execution unit is used to adjust the operating status of each liquid cooling system based on the adjustment rule. 12 . A computer-readable storage medium having instructions stored thereon, which, when executed on a computer, enables the computer to execute the liquid cooling system control method according to any one of claims 1 to 10.

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