Temperature control method, device and equipment of aldehyde separation tower based on industrial internet, medium and program product

Abstract

The invention provides a temperature control method, device and equipment of an aldehyde separation tower based on the industrial internet, a medium and a program product, and relates to the technical field of industrial automation. The method comprises the following steps: obtaining parameter values of a plurality of operation parameters of the aldehyde separation tower, and determining a separation effect prediction value of the aldehyde separation tower according to the parameter values of the operation parameters; and determining the optimal tray temperature of the aldehyde separation tower by adopting an optimization algorithm according to the separation effect predicted value and by taking the proportion predicted value of the non-to-be-separated components in the tower top material and the proportion predicted value of the to-be-separated components in the tower bottom material as a target. The method is applied to the industrial internet, the temperature control parameters of the aldehyde separation tower are accurately controlled and optimized in a full-automatic mode, the accuracy and stability of the aldehyde separation process are improved, and then the product quality and the production efficiency are improved.

Description

Technical Field

[0001] The present application relates to the field of industrial automation technology, and in particular to a temperature control method, device, equipment, medium and program product for an aldehyde separation tower based on the industrial Internet. Background Art

[0002] The separation of aldehyde mixtures (such as butyraldehyde and valeraldehyde) plays an important role in chemical production; by taking advantage of the differences in the physical and chemical properties of aldehyde compounds, specific technical means can be used to effectively separate them.

[0003] In chemical separation technology, aldehyde separation tower is a commonly used equipment. Its design and operating parameters are crucial to the separation effect, especially the temperature setting. In traditional separation operations, the adjustment of temperature parameters mainly depends on the operator's experience and intuition.

[0004] However, it is difficult to ensure that the aldehyde separation tower always performs separation at a suitable temperature by manually adjusting the temperature parameters, which results in poor accuracy of the separation effect. Summary of the invention

[0005] The embodiments of the present application provide a temperature control method, device, equipment, medium and program product for an aldehyde separation tower based on the industrial Internet, which are used to achieve precise control and optimization of the temperature control parameters of the aldehyde separation tower, thereby improving the accuracy and stability of the separation process.

[0006] In a first aspect, an embodiment of the present application provides a temperature control method for an aldehyde separation tower based on the industrial Internet, comprising:

[0007] Acquiring parameter values ​​of a plurality of operating parameters of the aldehyde separation tower, wherein the operating parameters include a tray temperature of the aldehyde separation tower and one or more other operating parameters affecting the aldehyde separation effect except the tray temperature;

[0008] Determining a separation effect prediction value of the aldehyde separation tower according to the parameter values ​​of the multiple operating parameters, the separation effect prediction value including a proportion prediction value of each component in the tower top material and a proportion prediction value of each component in the tower bottom material of the aldehyde separation tower;

[0009] According to the predicted value of the separation effect, an optimization algorithm is used to determine the optimal tray temperature of the aldehyde separation tower with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material.

[0010] In a possible implementation, determining the predicted value of the separation effect of the aldehyde separation tower according to the parameter values ​​of the multiple operating parameters includes:

[0011] The parameter values ​​of the multiple operating parameters are input into a pre-trained prediction model to obtain the separation effect prediction value output by the prediction model, wherein the prediction model is trained based on the historical parameter values ​​of the operating parameters of the aldehyde separation tower and the historical separation effect true values ​​corresponding to the historical parameter values.

[0012] In a possible implementation manner, before inputting the parameter values ​​of the plurality of operating parameters into the pre-trained prediction model, the method further includes:

[0013] According to the composition of the aldehyde mixture in the aldehyde separation tower, the corresponding prediction model is determined, wherein the prediction model is trained based on the composition of the aldehyde mixture, the historical parameter values ​​of the operating parameters of the aldehyde separation tower, and the historical separation effect true values ​​corresponding to the historical parameter values.

[0014] In a possible implementation, the optimal tray temperature of the aldehyde separation tower is determined by using an optimization algorithm based on the predicted value of the separation effect with the goal of minimizing the predicted value of the proportion of the non-to-be-separated components in the tower top material and the predicted value of the proportion of the to-be-separated components in the tower bottom material, including:

[0015] When the other operating parameters remain unchanged, the particle swarm optimization algorithm is used to iteratively adjust the tower plate temperature, and the adjusted separation effect prediction value is determined based on the adjusted tower plate temperature and the other operating parameters. The tower plate temperature that minimizes the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of components to be separated in the bottom material is determined as the optimal tower plate temperature.

[0016] In a possible implementation, the temperature control method of the aldehyde separation tower based on the industrial Internet further includes:

[0017] Controlling the aldehyde separation tower to operate according to the optimal tray temperature, and monitoring the actual value of the separation effect of the aldehyde separation tower;

[0018] When the actual value of the separation effect exceeds a preset range, an alarm message is output, and in response to user operation, the tray temperature of the aldehyde separation tower is adjusted.

[0019] In a possible implementation, the obtaining of a plurality of operating parameters of the aldehyde separation tower includes:

[0020] Within a preset time period, collecting the values ​​of the operating parameters of the aldehyde separation tower according to the collection frequency of the operating parameters;

[0021] For each of the operating parameters, an average value of the values ​​collected within the preset time period is determined as the parameter value of the operating parameter.

[0022] In a second aspect, an embodiment of the present application provides a temperature control device for an aldehyde separation tower based on the industrial Internet, comprising:

[0023] The acquisition module is used to acquire parameter values ​​of multiple operating parameters of the aldehyde separation tower, wherein the operating parameters include the tray temperature of the aldehyde separation tower and one or more other operating parameters that affect the aldehyde separation effect except the tray temperature.

[0024] A determination module is used to determine the predicted value of the separation effect of the aldehyde separation tower according to the parameter values ​​of the multiple operating parameters, wherein the predicted value of the separation effect includes the predicted value of the proportion of each component in the top material of the aldehyde separation tower and the predicted value of the proportion of each component in the bottom material.

[0025] The determination module is also used to determine the optimal tray temperature of the aldehyde separation tower using an optimization algorithm based on the separation effect prediction value, with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of to-be-separated components in the bottom material.

[0026] Optionally, the temperature control device of the aldehyde separation tower based on the industrial Internet also includes: a processing module.

[0027] The processing module is used to input the parameter values ​​of the multiple operating parameters into a pre-trained prediction model to obtain the separation effect prediction value output by the prediction model, wherein the prediction model is trained based on the historical parameter values ​​of the operating parameters of the aldehyde separation tower and the historical separation effect true values ​​corresponding to the historical parameter values.

[0028] Optionally, the determination module is also used to determine the corresponding prediction model according to the composition of the aldehyde mixture in the aldehyde separation tower, wherein the prediction model is trained based on the composition of the aldehyde mixture, historical parameter values ​​of the operating parameters of the aldehyde separation tower, and true values ​​of historical separation effects corresponding to the historical parameter values.

[0029] Optionally, the processing module is further used to iteratively adjust the tower plate temperature by using a particle swarm optimization algorithm when the other operating parameters remain unchanged.

[0030] The determination module is also used to determine the adjusted separation effect prediction value based on the adjusted tower plate temperature and the other operating parameters, and to determine the tower plate temperature that minimizes the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of components to be separated in the bottom material as the optimal tower plate temperature.

[0031] Optionally, the processing module is further used to control the aldehyde separation tower to operate according to the optimal tower plate temperature, and monitor the actual value of the separation effect of the aldehyde separation tower.

[0032] The processing module is further used to output an alarm message when the actual value of the separation effect exceeds a preset range, and to adjust the tray temperature of the aldehyde separation tower in response to user operation.

[0033] Optionally, the acquisition module is further used to collect the values ​​of each operating parameter of the aldehyde separation tower within a preset time period according to the collection frequency of each operating parameter of the aldehyde separation tower.

[0034] The determination module is further configured to determine, for each of the operating parameters, an average value of the values ​​collected within the preset time period as a parameter value of the operating parameter.

[0035] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0036] The memory stores computer-executable instructions;

[0037] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0038] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0039] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0040] The temperature control method, device, equipment, medium and program product of the aldehyde separation tower based on the industrial Internet provided in the embodiments of the present application are as follows: within a preset time period, according to the collection frequency of each operating parameter of the aldehyde separation tower, the value of each operating parameter is collected; for each operating parameter, the average value of the values ​​collected within the preset time period is determined as the parameter value of the operating parameter; the parameter values ​​of multiple operating parameters are input into a pre-trained prediction model to obtain the separation effect prediction value output by the prediction model; when other operating parameters remain unchanged, the particle swarm optimization algorithm is used to iteratively adjust the tower plate temperature, and the adjusted separation effect prediction value is determined according to the adjusted tower plate temperature and other operating parameters, and the tower plate temperature that minimizes the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material is determined as the optimal tower plate temperature; the aldehyde separation tower is controlled to operate according to the optimal tower plate temperature, and the true value of the separation effect of the aldehyde separation tower is monitored; when the true value of the separation effect exceeds the preset range, an alarm message is output, and the tower plate temperature of the aldehyde separation tower is adjusted in response to user operation. This method is applied in the Industrial Internet, realizing fully automated precise control and optimization of the temperature control parameters of the aldehyde separation tower, enabling the temperature control parameters to automatically adapt to changes in different production conditions and raw material characteristics, thereby improving the accuracy and stability of the aldehyde separation process, thereby improving product quality and production efficiency, and providing a more efficient and reliable solution for chemical production. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] Figure 1 This is a schematic diagram of the temperature control method of the aldehyde separation tower based on the industrial Internet provided in this application Figure 1 ;

[0043] Figure 2 This is a schematic diagram of the temperature control method of the aldehyde separation tower based on the industrial Internet provided in this application Figure 2 ;

[0044] Figure 3 It is a structural schematic diagram of a temperature control device for an aldehyde separation tower based on the industrial Internet provided in this application;

[0045] Figure 4 It is a structural schematic diagram of the electronic device provided by this application.

[0046] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0048] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein, for example.

[0049] In the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0050] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0051] First, the terms used in this application are explained:

[0052] DCS: Distributed Control System, a technical solution that uses multiple controllers to coordinate with each other to achieve system automation control. DCS is usually used in industrial production, manufacturing and processing, including chemical, pharmaceutical, food, pulp and paper industries.

[0053] LIMS: Laboratory Information Management System; it is a software system that can comprehensively manage laboratory processes, data, instruments, personnel, documents, reports and other information.

[0054] Particle Swarm Optimization Model: Particle Swarm Optimization, referred to as PSO model, is an optimization algorithm based on swarm intelligence. It simulates the behavior of particle swarms in nature to find the optimal solution in the problem space. In the PSO model, each particle represents a potential solution and adjusts its speed and position according to the individual's historical best position and the group's best position to find the optimal solution.

[0055] The separation of aldehyde mixtures (such as butyraldehyde and valeraldehyde) plays an important role in chemical production. Since aldehyde compounds usually have different physical and chemical properties, such as boiling point, solubility, etc., they can be effectively separated by specific separation techniques by utilizing the differences in their physical and chemical properties.

[0056] In chemical separation technology, aldehyde separation tower is a commonly used equipment, which uses the distribution difference of substances at different heights in the tower to separate different aldehydes in the mixture through distillation. The design and operation parameters of aldehyde separation tower have a crucial impact on the separation effect, among which temperature setting is a core control parameter.

[0057] In traditional aldehyde separation tower operation, the adjustment of temperature control parameters mainly depends on the operator's experience and intuition. However, the experience and intuition of different operators vary, which may lead to different separation effects under the same production conditions, and the manual adjustment of temperature control parameters cannot quickly respond to changes in the production process, which will also affect the separation effect of the aldehyde separation tower.

[0058] The temperature control method of the aldehyde separation tower based on the industrial Internet provided in this application is based on historical DCS data and LIMS data, and the mapping relationship between the DCS parameters that affect the separation effect and the separation effect is learned through a deep learning model, so as to realize the prediction of the aldehyde separation effect in the real-time separation process; based on the real-time prediction effect, the temperature control parameters of the aldehyde separation tower are reversely controlled, so as to realize the fully automated precise control and optimization of the temperature control parameters of the aldehyde separation tower, and improve the accuracy and stability of the separation process. This method is applied to the industrial Internet, which solves the technical problems that the adjustment of the temperature control parameters of the traditional aldehyde separation tower relies on manual experience, resulting in poor accuracy of the separation effect and insufficient stability during the separation process.

[0059] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0060] Figure 1Schematic diagram of the temperature control method of the aldehyde separation tower based on the industrial Internet provided in this application Figure 1 The execution subject of this embodiment may be, for example, a central data platform provided with a temperature control module. Figure 1 As shown, the temperature control method of the aldehyde separation tower based on the industrial Internet provided in this embodiment includes:

[0061] S101: Obtain parameter values ​​of multiple operating parameters of the aldehyde separation tower.

[0062] The operating parameters are used to indicate the variables or conditions that need to be monitored and adjusted during the operation and control of the aldehyde separation tower. The operating parameters include the tray temperature of the aldehyde separation tower and one or more other operating parameters that affect the aldehyde separation effect except the tray temperature.

[0063] In the embodiment of the present application, a variety of detection equipment is provided in the aldehyde separation tower for detecting various operating parameters and states in the aldehyde separation tower to ensure the smooth progress of the separation process and the quality of the product; the detection equipment includes: temperature sensor, pressure sensor, flow meter, liquid level meter.

[0064] A DCS system is also provided in the aldehyde separation tower, and the DCS system is connected to various detection devices for communication, and can obtain real-time detection data of the detection devices in real time, so as to realize real-time detection of various operating parameters in the aldehyde separation tower. In addition, the DCS system can also control or adjust the corresponding operating parameters.

[0065] Exemplarily, the operating parameters that can be obtained by the DCS system of the aldehyde separation tower include: feed flow rate, feed temperature, steam flow rate, E120 condensate tank level, aldehyde separation tower top pressure, aldehyde separation tower top reflux flow rate, aldehyde separation tower top reflux material temperature, aldehyde separation tower top reflux tank level, aldehyde separation tower bottom level, aldehyde separation tower sensitive point temperature, tower plate temperature, tower pressure; by setting the detection equipment at the corresponding position, the specific parameter values ​​of the corresponding operating parameters can be obtained, which can be: feed flow rate -500kg / h, feed temperature - 60℃, steam flow-200kg / h, E120 condensate tank level-75%, aldehyde separation tower top pressure-1.2bar, aldehyde separation tower top reflux flow-150kg / h, aldehyde separation tower top reflux material temperature-40℃, aldehyde separation tower top reflux tank level-60%, aldehyde separation tower bottom level-50%, aldehyde separation tower sensitive point temperature-85℃, tower pressure-1.5bar, among which, the tower plate temperature includes: the first tower plate temperature-90℃, the second tower plate temperature-88℃, the third tower plate temperature-86℃.

[0066] It should be noted that the aldehyde separation tower is usually composed of multiple trays. The arrangement of multiple trays can effectively promote the contact between gas and liquid, thereby realizing the separation of the components of the aldehyde mixture, effectively improving the separation efficiency, and ensuring the purity and quality of the product; since the bottom of the tower is usually heated to provide the necessary energy for evaporation, and the top of the tower is the condensation area, therefore, in the aldehyde separation tower, there is usually a temperature gradient from the bottom of the tower to the top of the tower, and the temperature at the bottom of the tower is higher, while the temperature at the top of the tower is lower.

[0067] S102: Determine a predicted value of separation effect of the aldehyde separation tower according to parameter values ​​of a plurality of operating parameters.

[0068] S103: According to the predicted value of separation effect, an optimization algorithm is used to determine the optimal tray temperature of the aldehyde separation tower with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material.

[0069] The separation effect prediction value includes the predicted value of the proportion of each component in the top material of the aldehyde separation tower and the predicted value of the proportion of each component in the bottom material.

[0070] In the embodiment of the present application, the DCS system arranged in the aldehyde separation tower can obtain the corresponding operating parameters in real time, and therefore, the parameter values ​​corresponding to the operating parameters can also be referred to as DCS data; a LIMS system is also arranged in the aldehyde separation tower, and the LIMS system is used to detect and store the separation effects of the corresponding compounds when the aldehyde separation tower separates the compounds with different operating parameters; wherein, the separation effect of the aldehyde separation tower can be determined by the components of different compounds in the top and bottom of the tower, for example, the separation effect of the aldehyde separation tower can be reflected by the proportion of C5 aldehydes at the top of the tower and the proportion of heavy components and butyraldehyde at the bottom of the tower, that is, the LIMS system can determine the actual separation effect of the aldehyde separation tower by detecting the proportion of C5 aldehydes at the top of the tower and the proportion of heavy components and butyraldehyde at the bottom of the tower.

[0071] It can be understood that the temperature control module stores a mapping relationship between multiple operating parameters and separation effects, and the mapping relationship is determined based on historical operating parameters and corresponding historical separation effects; in the actual operation of the aldehyde separation tower, due to the time delay between the DCS system and the LIMS system, in order to ensure the separation effect of the aldehyde separation tower, the central data platform obtains the operating parameters in real time and automatically adjusts the tower plate temperature according to the mapping relationship to maintain or improve the separation efficiency of the aldehyde separation tower.

[0072] According to the parameter values ​​of the multiple operating parameters currently obtained, the mapping relationship stored in the temperature control module is called, and the separation effect corresponding to the current operating parameters is determined by using the mapping relationship, and the separation effect is determined as the separation effect prediction value of the aldehyde separation tower; according to the currently determined separation effect prediction value, with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of to-be-separated components in the bottom material, an optimization algorithm is used to calculate the tower plate temperature that can be used by the aldehyde separation tower under the current operating conditions to minimize the non-to-be-separated components in the top material and minimize the components to be separated in the bottom material, and the tower plate temperature is determined as the optimal tower plate temperature.

[0073] In some embodiments, a percentage threshold is stored in the temperature control module, and the percentage threshold is used to measure the separation effect of the aldehyde separation tower. If the percentage of non-to-be-separated components in the top material and the percentage of to-be-separated components in the bottom material are less than the percentage threshold, it indicates that under the current operating parameters, the separation effect of the aldehyde separation tower reaches the expected effect, and there is no need to adjust the tower plate temperature; if the percentage of non-to-be-separated components in the top material and / or the percentage of to-be-separated components in the bottom material are not less than the percentage threshold, it indicates that under the current operating parameters, the separation effect of the aldehyde separation tower does not reach the expected effect. At this time, it is necessary to recalculate the tower plate temperature corresponding to the current operating parameters, and control the aldehyde separation tower to separate compounds at the corresponding tower plate temperature.

[0074] Exemplarily, according to the parameter values ​​of the multiple operating parameters currently obtained, the mapping relationship stored in the temperature control module is called, and the separation effect corresponding to the current operating parameters is determined by using the mapping relationship, and the separation effect is determined as the separation effect prediction value of the aldehyde separation tower, and the separation effect prediction value can be: "the proportion of C5 aldehydes at the top of the tower is 7%, the proportion of butyraldehyde at the top of the tower is 93%, the proportion of heavy components at the bottom of the tower is 6%, the proportion of butyraldehyde at the bottom of the tower is 6%, and the proportion of valeraldehyde at the bottom of the tower is 88%"; if the proportion threshold is 5%, and the proportion of C5 aldehydes at the top of the tower and the proportion of heavy components at the bottom of the tower are 6%, the proportion of valeraldehyde at the bottom of the tower is 88%, and the proportion of aldehydes at the top of the tower is 7%, and the proportion of aldehydes at the bottom of the tower is 93%. The ratio and the butyraldehyde ratio at the bottom of the tower are all higher than the ratio threshold. At this time, the tower plate temperature needs to be adjusted to achieve the best separation effect. According to the currently determined separation effect prediction value, the objective function is to minimize the predicted ratio of non-to-be-separated components in the top material and the predicted ratio of to-be-separated components in the bottom material. The particle swarm optimization model is used to calculate the tower plate temperature that can be used for the aldehyde separation tower under the operating conditions when the ratio of C5 aldehydes at the top of the tower, the ratio of heavy components at the bottom of the tower, and the ratio of butyraldehyde at the bottom of the tower are all lower than the ratio threshold, and the tower plate temperature is determined as the optimal tower plate temperature.

[0075] The temperature control method of the aldehyde separation tower based on the industrial Internet provided in the embodiment of the present application obtains the parameter values ​​of multiple operating parameters of the aldehyde separation tower, and determines the separation effect prediction value of the aldehyde separation tower according to the parameter values ​​of the multiple operating parameters; according to the separation effect prediction value, the optimization algorithm is used to determine the optimal tray temperature of the aldehyde separation tower with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material. This method is applied to the industrial Internet, realizing fully automated precise control and optimization of the temperature control parameters of the aldehyde separation tower, improving the accuracy and stability of the aldehyde separation process, and thus improving the quality and production efficiency of the product.

[0076] Figure 2 Schematic diagram of the temperature control method of the aldehyde separation tower based on the industrial Internet provided in this application Figure 2 ,like Figure 2 As shown, in this embodiment Figure 1 Based on the embodiment, a temperature control method of an aldehyde separation tower based on the industrial Internet is described in detail, and the method includes:

[0077] S201: within a preset time period, collecting values ​​of various operating parameters of the aldehyde separation tower according to the collection frequency of various operating parameters.

[0078] S202: For each operating parameter, determine an average value of values ​​collected within a preset time period as a parameter value of the operating parameter.

[0079] The preset time period may be, for example, 10 minutes, and the collection frequency may be, for example, 10 seconds per time.

[0080] It is understandable that there are differences in the collection frequencies of different types of operating parameters in the DCS system, and there are also differences in the data collection frequencies of the DCS system and the LIMS system, and the data collection frequency of the LIMS system is lower than that of the DCS system; in order to facilitate the real-time prediction of the separation effect of the aldehyde separation tower, it is necessary to preprocess the acquired DCS data, that is, the specific data of the operating parameters of the aldehyde separation tower, and unify the time format of the DCS data and the LIMS data; in addition, the preprocessing also includes data cleaning, format conversion, outlier detection and data correction.

[0081] Within a preset time period, the specific values ​​of each operating parameter of the aldehyde separation tower are collected according to the collection frequency of each operating parameter; for each operating parameter, the average value of the values ​​collected within the preset time period is calculated, and the average value of the corresponding operating parameter is determined as the parameter value of the corresponding operating parameter.

[0082] Exemplarily, the DCS system obtains specific values ​​of multiple operating parameters corresponding to the aldehyde separation tower within 10 minutes according to the collection frequency of each operating parameter of the aldehyde separation tower; the central data platform obtains the data information transmitted by the DCS system, and preprocesses the multiple DCS data obtained within 10 minutes in time format, that is, for different operating parameters, the average value of multiple values ​​obtained within 10 minutes is calculated respectively, and the average value is determined as the parameter value of the corresponding operating parameter; specifically, the DCS system obtains the aldehyde separation tower top reflux material temperature at a frequency of 10s / time, and obtains 60 specific values ​​of the aldehyde separation tower top reflux material temperature within 10 minutes. The central data platform obtains the 60 DCS data and calculates the average value. The calculated result is 40°C. At this time, the calculated result is determined as the parameter value of the aldehyde separation tower top reflux material temperature.

[0083] S203: Inputting parameter values ​​of multiple operating parameters into a pre-trained prediction model to obtain a separation effect prediction value output by the prediction model.

[0084] Among them, the prediction model is used to predict the separation effect of the aldehyde separation tower under real-time operating conditions.

[0085] Exemplarily, if the parameter values ​​of the currently acquired operating parameters include: feed flow rate -500kg / h, feed temperature -60°C, steam flow rate -200kg / h, E120 condensate tank level -75%, aldehyde separation tower top pressure -1.2bar, aldehyde separation tower top reflux flow rate -150kg / h, aldehyde separation tower top reflux material temperature -40°C, aldehyde separation tower top reflux tank level -60%, aldehyde separation tower bottom level -50%, aldehyde separation tower sensitive point temperature -85°C, tower pressure -1.5bar, wherein the tower plate temperature includes: first tower plate temperature -90°C, second tower plate temperature -88°C, third tower plate temperature -86°C; the parameter values ​​of multiple operating parameters are input into the prediction model to obtain the separation effect prediction values ​​corresponding to the multiple operating parameters, the GIA separation effect prediction values ​​include: "the proportion of C5 aldehydes at the top of the tower is 7%, the proportion of heavy components at the bottom of the tower is 6%, and the proportion of butyraldehyde at the bottom of the tower is 6%".

[0086] In some embodiments, before inputting parameter values ​​of a plurality of operating parameters into a pre-trained prediction model, a corresponding prediction model is determined according to the composition of the aldehyde mixture in the aldehyde separation tower.

[0087] It can be understood that the prediction model is trained based on the composition of the aldehyde mixture, the historical parameter values ​​of the operating parameters of the aldehyde separation tower, and the true values ​​of the historical separation effects corresponding to the historical parameter values; since different aldehyde mixtures may have significant differences in chemical properties and separation behaviors, in order to improve the accuracy of the prediction model, corresponding prediction models are trained for the separation of different aldehyde mixtures, which can more accurately capture and reflect the unique behavior and characteristics of each aldehyde mixture, thereby improving the accuracy of the prediction and the optimization effect of the separation process.

[0088] Exemplarily, based on historical DCS data and historical LIMS data, a machine learning model is used to learn the correlation between parameters affecting separation effect and separation effect, that is, a machine learning model is used to establish a correlation between multiple input data (parameters affecting the separation effect of aldehyde mixtures) and output data (parameters characterizing the separation effect). Optionally, the parameters affecting the separation effect of aldehyde mixtures include: feed flow rate, feed temperature, steam flow rate, E120 condensate tank level, aldehyde separation tower top pressure, aldehyde separation tower top reflux flow rate, aldehyde separation tower top reflux material temperature, aldehyde separation tower top reflux tank level, aldehyde separation tower bottom level, aldehyde separation tower sensitive point temperature, tower plate temperature, tower pressure; parameters characterizing the separation effect include: the proportion of C5 aldehydes at the top of the tower after the aldehyde mixture is separated, the proportion of heavy components at the bottom of the tower, and the proportion of butyraldehyde at the bottom of the tower; the trained machine learning model is used as a prediction model for the corresponding aldehyde mixture, wherein the machine learning model selected for use may be, for example, a linear regression model and catboost.

[0089] S204: When other operating parameters remain unchanged, the particle swarm optimization algorithm is used to iteratively adjust the tower plate temperature, and the adjusted separation effect prediction value is determined based on the adjusted tower plate temperature and other operating parameters. The tower plate temperature that minimizes the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material is determined as the optimal tower plate temperature.

[0090] It can be understood that the aldehyde separation tower utilizes different physical and chemical properties of different aldehyde compounds, and realizes the separation of components of the aldehyde mixture by controlling the change of the tower plate temperature; for example, the main components in the current aldehyde mixture include: butyraldehyde and valeraldehyde, and butyraldehyde and valeraldehyde have different boiling points; when the mixture is heated, due to the difference in boiling points, butyraldehyde will start to evaporate earlier than valeraldehyde, thereby realizing the separation of butyraldehyde and valeraldehyde; after the aldehyde mixture is separated, the top of the aldehyde separation tower mainly contains butyraldehyde, and the bottom of the aldehyde separation tower mainly contains valeraldehyde. Since the aldehyde mixture is not completely separated, the butyraldehyde in the top of the tower is an aldehyde mixture containing C5 aldehydes, and the valeraldehyde in the bottom of the tower is an aldehyde mixture containing butyraldehyde and heavy components; in the actual separation process, in order to ensure the best separation effect, it is necessary to ensure that the proportion of C5 aldehydes in the butyraldehyde in the top of the tower is the lowest, and the proportion of butyraldehyde and heavy components in the valeraldehyde in the bottom of the tower is the lowest, that is, it is necessary to ensure that the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of to-be-separated components in the bottom material are minimized.

[0091] Exemplarily, with other operating parameters unchanged, a particle swarm optimization algorithm is used to iteratively adjust the tower plate temperature, randomly initialize the tower plate temperature of each particle (i.e., the position of each particle), and initialize the speed of each particle to obtain multiple adjusted tower plate temperatures, and re-determine the adjusted separation effect prediction value based on the multiple adjusted tower plate temperatures and other operating parameters; the new separation effect prediction value is compared with the preset range respectively, and the new separation effect prediction value that does not exceed the preset range is screened out, and then the tower plate temperature that will minimize the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of components to be separated in the bottom material is determined, and the tower plate temperature is determined as the optimal tower plate temperature.

[0092] In some embodiments, when a new separation effect prediction value that does not exceed the preset range is screened out, a suitable tray temperature can be determined according to the actual operating environment and operating conditions of the current aldehyde separation tower, and the tray temperature can be determined as the optimal tray temperature.

[0093] S205: Control the aldehyde separation tower to operate according to the optimal tower plate temperature, and monitor the actual value of the separation effect of the aldehyde separation tower.

[0094] S206: When the actual value of the separation effect exceeds a preset range, an alarm message is output, and in response to a user operation, the tray temperature of the aldehyde separation tower is adjusted.

[0095] It can be understood that the separation effect includes the proportion of each component in the top material of the aldehyde separation tower and the proportion of each component in the bottom material, and there are differences in the preset ranges of the top and bottom for the components to be separated and the components not to be separated, wherein the preset range corresponding to the components to be separated can be, for example, 5%-6%.

[0096] In the embodiment of the present application, the true value of the separation effect can be determined by the data information obtained by the LIMS system. The central data platform can obtain in real time the proportion of non-to-be-separated components in the top material and the proportion of to-be-separated components in the bottom material detected by the LIMS system, so as to determine the actual separation effect of the current aldehyde separation tower, and then determine whether the optimal tower plate temperature determined by the prediction model and particle swarm optimization algorithm is accurate.

[0097] The aldehyde separation tower is controlled to operate according to the optimal tower plate temperature, and the actual value of the separation effect of the aldehyde separation tower is monitored, and it is determined in real time whether the actual value of the separation effect exceeds the preset range; if the actual value of the separation effect does not exceed the preset range, it indicates that the current separation effect meets the expected effect. At this time, the aldehyde separation tower is controlled to continue to operate; when the actual value of the separation effect exceeds the preset range, the actual separation effect of the current aldehyde separation tower does not meet expectations. At this time, an alarm message is output, and in response to user operations, the tower plate temperature of the aldehyde separation tower is readjusted.

[0098] It is understandable that when the central data platform generates an alarm message, it can be determined that the current tray temperature used by the aldehyde separation tower is not the optimal tray temperature, and the actual separation effect of the aldehyde separation tower has not reached the expected effect, that is, the proportion of non-to-be-separated components in the top material and the proportion of to-be-separated components in the bottom material. At this time, there is an error in the prediction result of the prediction model, and the prediction model needs to be re-optimized.

[0099] For example, if the currently determined optimal tray temperature is 65°C, the aldehyde separation tower is controlled to operate at 65°C, and the actual value of the separation effect of the aldehyde separation tower is monitored in real time; if the currently acquired actual value of the separation effect is: "the proportion of C5 aldehydes at the top of the tower is 7%, the proportion of heavy components at the bottom of the tower is 7%, and the proportion of butyraldehyde at the bottom of the tower is 8%", that is, the proportion of C5 aldehydes at the top of the tower, the proportion of heavy components at the bottom of the tower, and the proportion of butyraldehyde at the bottom of the tower are all beyond the preset range. At this time, the central data platform generates and outputs an alarm message; after the aldehyde separation tower issues an alarm, the user can manually intervene, and the aldehyde separation tower responds to the user's operation, adjusts the corresponding tray temperature, and continues to separate the aldehyde mixture.

[0100] The temperature control method of an aldehyde separation tower based on the industrial Internet provided in an embodiment of the present application comprises the following steps: collecting the values ​​of each operating parameter of the aldehyde separation tower within a preset time period according to the collection frequency of each operating parameter of the aldehyde separation tower; for each operating parameter, determining the average value of the values ​​collected within the preset time period as the parameter value of the operating parameter; inputting the parameter values ​​of multiple operating parameters into a pre-trained prediction model to obtain a separation effect prediction value output by the prediction model; when other operating parameters remain unchanged, iteratively adjusting the tower plate temperature by using a particle swarm optimization algorithm, and determining the adjusted separation effect prediction value based on the adjusted tower plate temperature and other operating parameters, and determining the tower plate temperature that minimizes the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material as the optimal tower plate temperature; controlling the aldehyde separation tower to operate according to the optimal tower plate temperature, and monitoring the true value of the separation effect of the aldehyde separation tower; when the true value of the separation effect exceeds the preset range, outputting an alarm message, and adjusting the tower plate temperature of the aldehyde separation tower in response to user operation. This method is applied in the Industrial Internet, realizing fully automated precise control and optimization of the temperature control parameters of the aldehyde separation tower, enabling the temperature control parameters to automatically adapt to changes in different production conditions and raw material characteristics, thereby improving the accuracy and stability of the aldehyde separation process, thereby improving product quality and production efficiency, and providing a more efficient and reliable solution for chemical production.

[0101] Figure 3 The schematic diagram of the structure of the temperature control device of the aldehyde separation tower based on the industrial Internet provided in this application is as follows: Figure 3 As shown, the temperature control device 30 of the aldehyde separation tower based on the industrial Internet provided in this embodiment includes:

[0102] The acquisition module 301 is used to acquire parameter values ​​of multiple operating parameters of the aldehyde separation tower, wherein the operating parameters include the tray temperature of the aldehyde separation tower and one or more other operating parameters affecting the aldehyde separation effect except the tray temperature.

[0103] The determination module 302 is used to determine the separation effect prediction value of the aldehyde separation tower according to the parameter values ​​of the multiple operating parameters, and the separation effect prediction value includes the proportion prediction value of each component in the top material of the aldehyde separation tower and the proportion prediction value of each component in the bottom material.

[0104] The determination module 302 is further used to determine the optimal tray temperature of the aldehyde separation tower using an optimization algorithm based on the separation effect prediction value, with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material.

[0105] Optionally, the temperature control device of the aldehyde separation tower based on the industrial Internet also includes: a processing module 303.

[0106] The processing module 303 is used to input the parameter values ​​of the multiple operating parameters into a pre-trained prediction model to obtain the separation effect prediction value output by the prediction model, wherein the prediction model is trained based on the historical parameter values ​​of the operating parameters of the aldehyde separation tower and the historical separation effect true values ​​corresponding to the historical parameter values.

[0107] Optionally, the determination module 302 is also used to determine the corresponding prediction model according to the composition of the aldehyde mixture in the aldehyde separation tower, wherein the prediction model is trained based on the composition of the aldehyde mixture, the historical parameter values ​​of the operating parameters of the aldehyde separation tower, and the true values ​​of the historical separation effects corresponding to the historical parameter values.

[0108] Optionally, the processing module 303 is further configured to iteratively adjust the tray temperature by using a particle swarm optimization algorithm while keeping the other operating parameters unchanged.

[0109] The determination module 302 is also used to determine the adjusted separation effect prediction value based on the adjusted tower plate temperature and the other operating parameters, and to determine the tower plate temperature that minimizes the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of to-be-separated components in the bottom material as the optimal tower plate temperature.

[0110] Optionally, the processing module 303 is further used to control the aldehyde separation tower to operate according to the optimal tower plate temperature, and monitor the actual value of the separation effect of the aldehyde separation tower.

[0111] The processing module 303 is further configured to output an alarm message when the actual value of the separation effect exceeds a preset range, and to adjust the tray temperature of the aldehyde separation tower in response to user operation.

[0112] Optionally, the acquisition module 301 is further used to collect the values ​​of the operating parameters of the aldehyde separation tower within a preset time period according to the collection frequency of the operating parameters of the aldehyde separation tower.

[0113] The determination module 302 is further configured to determine, for each of the operating parameters, an average value of the values ​​collected within the preset time period as a parameter value of the operating parameter.

[0114] The temperature control device of the aldehyde separation tower based on the industrial Internet provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0115] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this application. Figure 4As shown, the electronic device 40 provided in this embodiment includes: at least one processor 401 and a memory 402. Optionally, the device 40 also includes a communication component 403. The processor 401, the memory 402 and the communication component 403 are connected via a bus 404.

[0116] In a specific implementation process, at least one processor 401 executes the computer-executable instructions stored in the memory 402, so that at least one processor 401 executes the above method.

[0117] The specific implementation process of the processor 401 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0118] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0119] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0120] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0121] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0122] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0123] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0124] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0125] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0128] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of 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, etc. Various media that can store program codes.

[0129] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0130] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A temperature control method for an aldehyde separation tower based on the industrial Internet, characterized in that: The method comprises: Acquiring parameter values ​​of a plurality of operating parameters of the aldehyde separation tower, wherein the operating parameters include a tray temperature of the aldehyde separation tower and one or more other operating parameters affecting the aldehyde separation effect except the tray temperature; Determining a separation effect prediction value of the aldehyde separation tower according to the parameter values ​​of the multiple operating parameters, the separation effect prediction value including a proportion prediction value of each component in the tower top material and a proportion prediction value of each component in the tower bottom material of the aldehyde separation tower; According to the predicted value of the separation effect, an optimization algorithm is used to determine the optimal tray temperature of the aldehyde separation tower with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the tower top material and the predicted value of the proportion of to-be-separated components in the tower bottom material.

2. The method according to claim 1, characterized in that: The step of determining the predicted value of the separation effect of the aldehyde separation tower according to the parameter values ​​of the plurality of operating parameters comprises: The parameter values ​​of the multiple operating parameters are input into a pre-trained prediction model to obtain the separation effect prediction value output by the prediction model, wherein the prediction model is trained based on the historical parameter values ​​of the operating parameters of the aldehyde separation tower and the historical separation effect true values ​​corresponding to the historical parameter values.

3. The method according to claim 2, characterized in that Before inputting the parameter values ​​of the plurality of operating parameters into the pre-trained prediction model, the method further comprises: According to the composition of the aldehyde mixture in the aldehyde separation tower, the corresponding prediction model is determined, wherein the prediction model is trained based on the composition of the aldehyde mixture, the historical parameter values ​​of the operating parameters of the aldehyde separation tower, and the historical separation effect true values ​​corresponding to the historical parameter values.

4. The method according to claim 1, characterized in that: The method of determining the optimal tray temperature of the aldehyde separation tower by using an optimization algorithm according to the predicted value of the separation effect with the goal of minimizing the predicted value of the proportion of the non-to-be-separated components in the tower top material and the predicted value of the proportion of the to-be-separated components in the tower bottom material comprises: When the other operating parameters remain unchanged, the particle swarm optimization algorithm is used to iteratively adjust the tower plate temperature, and the adjusted separation effect prediction value is determined based on the adjusted tower plate temperature and the other operating parameters. The tower plate temperature that minimizes the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of components to be separated in the bottom material is determined as the optimal tower plate temperature.

5. The method according to any one of claims 1 to 4, characterized in that: Also includes: Controlling the aldehyde separation tower to operate according to the optimal tray temperature, and monitoring the actual value of the separation effect of the aldehyde separation tower; When the actual value of the separation effect exceeds a preset range, an alarm message is output, and in response to user operation, the tray temperature of the aldehyde separation tower is adjusted.

6. The method according to any one of claims 1 to 4, characterized in that: The obtaining of a plurality of operating parameters of the aldehyde separation tower comprises: Within a preset time period, collecting the values ​​of the operating parameters of the aldehyde separation tower according to the collection frequency of the operating parameters; For each of the operating parameters, an average value of the values ​​collected within the preset time period is determined as the parameter value of the operating parameter.

7. A temperature control device for an aldehyde separation tower based on the industrial Internet, characterized in that: include: An acquisition module, used for acquiring parameter values ​​of a plurality of operating parameters of the aldehyde separation tower, wherein the operating parameters include a tray temperature of the aldehyde separation tower and one or more other operating parameters affecting the aldehyde separation effect except the tray temperature; A determination module, configured to determine a predicted value of a separation effect of the aldehyde separation tower according to the parameter values ​​of the plurality of operating parameters, wherein the predicted value of the separation effect includes a predicted value of a proportion of each component in a tower top material and a predicted value of a proportion of each component in a tower bottom material of the aldehyde separation tower; The determination module is also used to determine the optimal tray temperature of the aldehyde separation tower using an optimization algorithm based on the separation effect prediction value, with the goal of minimizing the predicted value of the proportion of non-to-be-separated components in the top material and the predicted value of the proportion of to-be-separated components in the bottom material.

8. An electronic device, characterized in that: include: Memory; processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

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