Intelligent control system for polyether production line

Abstract

The invention provides an intelligent control system for a polyether production line, which relates to the technical field of polyether production control, and comprises a data acquisition module for acquiring state parameters, a feature extraction module for extracting state parameter features from the state parameters, and an intelligent control module for adjusting temperature, pressure and pH value to corresponding allowable intervals, the performance evaluation module is used for comprehensively evaluating the performance of the polyether production line, and the threshold judgment module is used for judging whether the polyether production line is subjected to optimization adjustment or not. The energy consumption excellence degree, the reaction environment excellence degree, the raw material use condition and the finished product excellence degree of the polyether production line are respectively evaluated through four indexes; the four indexes are integrated into a performance evaluation index through an analytic hierarchy process, so that the effect of comprehensively evaluating the polyether production line is achieved, a judgment basis and theoretical support are provided for subsequently adjusting and optimizing the operation performance of the polyether production line, and the quality and production efficiency of polyether products are improved.

Description

Technical Field

[0001] The invention relates to the technical field of polyether production control, in particular to an intelligent control system for a polyether production line. Background Art

[0002] Polyether is a type of polymer compound with ether bonds as the main structural unit. Due to its good flexibility, chemical stability, thermal stability and processability, it is widely used in furniture, sports equipment, automotive interior, building insulation, electronic product packaging and other fields. However, in the production process of polyether, it is often difficult to adjust factors such as temperature, pressure, and pH value to the optimal state, resulting in quality problems in the produced polyether products, which seriously affects the production efficiency of the polyether production line.

[0003] In the prior art, a full-process intelligent control system (G05B19) for preparing polyetheretherketone filaments with a publication number of "CN115407734A" is designed to solve the problems of many factors affecting temperature changes in the production of PEEK fibers, which are difficult, require personnel to conduct regular inspections at high frequencies, consume more manpower and material resources, and the process parameters cannot be stably controlled. The key points of its technical solution are: including: a parameter monitoring module, which obtains environmental parameters and real-time parameters of each production process to output control parameters as digital signals or analog signals; a model module is established, which is connected to the data of the parameter monitoring module and receives control parameters to establish a data module. The system establishes a database of the collected control parameters, which can record abnormal changes in the control parameters, making it convenient for operators to review the changes in equipment data throughout the process, conduct fault analysis, and adjust the equipment in a timely manner to improve the stability of fiber production.

[0004] However, the existing technology still has major defects. For example, when adjusting and controlling the polyether production line, the existing technology only measures the operating performance of the polyether production line from factors such as temperature, pressure, and material level. The evaluation criteria are relatively single and cannot fully reflect the operating performance of the polyether production line. There is a lack of overall grasp of the operating performance of the polyether production line, which is not convenient for subsequent adjustment and optimization of the polyether production line to improve its operating performance.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The object of the present invention is to provide an intelligent control system for a polyether production line to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions: An intelligent control system for a polyether production line, comprising: A data acquisition module, which is used to collect state parameters of the polyether production line within the monitoring period, the state parameters including total energy consumption of the equipment, flow rate of raw materials, flow rate and viscosity of finished products, concentration of products, concentration of by-products, pressure at the top of the reactor, temperature of the reaction solution in the reactor, pH value and concentration of raw materials in the reaction solution; A feature extraction module, wherein the feature extraction module is used to extract features of the state parameters to obtain state parameter features, wherein the state parameter features include an energy consumption evaluation index, and means and standard deviations of other state parameters except the total energy consumption of the equipment within a monitoring period; An intelligent control module, which is used to control the polyether production line according to the comparison results of the pressure mean, temperature mean, pH mean and the corresponding allowable range in the state parameter characteristics, so that the corresponding parameters are adjusted to the corresponding allowable range; A performance evaluation module, which calculates the reaction environment evaluation index, raw material evaluation index, and finished product evaluation index of the polyether production line within the monitoring period based on the state parameter characteristics, and combines the above indexes with the energy consumption evaluation index to generate a performance evaluation index for evaluating the comprehensive performance of the polyether production line; The threshold judgment module is used to compare the performance evaluation index with the performance evaluation threshold and to generate an alarm when the performance evaluation index is higher than the performance evaluation threshold.

[0008] Furthermore, the data acquisition module includes an online optical concentration sensor, a temperature sensor, a pressure gauge and a pH meter installed in the reactor, a flow meter installed at each raw material delivery pipeline, and a flow meter, a viscometer and an online optical concentration sensor installed at the finished product delivery pipeline.

[0009] Furthermore, the calculation formula of the energy consumption evaluation index is as follows:

[0010] In the formula, is the energy consumption index, is the total energy consumption of the equipment during the monitoring period. , They are the mean flow rate and concentration of the finished product during the monitoring period, is the duration of the monitoring period, is the preset energy consumption evaluation threshold, It is the energy consumption evaluation index.

[0011] Furthermore, the performance evaluation module includes a reaction environment evaluation module, a raw material evaluation module, a finished product evaluation model and a comprehensive evaluation module.

[0012] Furthermore, the reaction environment evaluation module is used to generate a reaction environment evaluation index for evaluating the quality of the reaction environment according to the state parameter characteristics. The calculation formula of the reaction environment evaluation index is as follows:

[0013] In the formula, is the average temperature during the monitoring period, is the standard deviation of temperature during the monitoring period, is the lower limit of the suitable temperature range, is the upper limit of the suitable temperature range, is the temperature deviation value; In the formula, is the mean pressure during the monitoring period, is the standard deviation of pressure during the monitoring period, is the lower limit of the suitable pressure range, is the upper limit of the suitable pressure range, is the pressure deviation value; In the formula, is the average pH value during the monitoring period, is the standard deviation of pH value during the monitoring period, is the lower limit of the suitable pH value range, is the upper limit of the suitable pH range, is the pH deviation; In the formula, is the reaction environment evaluation index during the monitoring period, , , and are preset scaling factors, and ,and .

[0014] Furthermore, the raw material evaluation module is used to generate a raw material evaluation index for evaluating the use of raw materials according to the state parameter characteristics. The calculation formula of the raw material evaluation index is as follows:

[0015] In the formula, is the mean flow rate of the i-th raw material during the monitoring period, is the mean concentration of the i-th raw material in the reaction solution during the monitoring period, i is the index of the raw material type, and , I is the number of raw material types; In the formula, is the raw material evaluation index within the monitoring period, is the weight of the i-th raw material in the calculation of the raw material evaluation index.

[0016] Furthermore, the finished product evaluation model is used to generate a finished product evaluation index for evaluating the excellence of the finished product according to the state parameter characteristics. The method for obtaining the finished product evaluation index is as follows: The state parameter characteristics within the monitoring time period are processed to obtain a finished product feature vector, which includes the flow mean of the finished product, the viscosity deviation of the finished product, the ratio of the mean product concentration to the mean by-product concentration in the finished product, the flow standard deviation of the finished product and the interaction term of the product concentration standard deviation. The finished product feature vector is input into the finished product evaluation model to obtain a finished product evaluation index reflecting the excellence of the finished product within the monitoring time period.

[0017] Furthermore, the calculation formula of the viscosity deviation value is as follows:

[0018] In the formula, is the average viscosity during the monitoring period, is the standard deviation of viscosity during the monitoring period, is the lower limit of the optimal viscosity range, is the upper limit of the optimal viscosity range, is the viscosity deviation value; The formula for calculating the ratio of product concentration to by-product concentration in the finished product is as follows:

[0019] In the formula, is the ratio of the product concentration to the by-product concentration in the finished product, is the mean concentration of the product, is the mean concentration of the jth byproduct during the monitoring period, j is the index of the byproduct type, and , J is the number of by-product types; The formula for calculating the interaction term between the standard deviation of the finished product flow rate and the standard deviation of the product concentration is as follows:

[0020] In the formula, is the interaction term between the standard deviation of the finished product flow rate and the standard deviation of the product concentration, is the flow standard deviation of the finished product, is the standard deviation of product concentration.

[0021] Furthermore, the comprehensive evaluation module is used to combine the energy consumption evaluation index, the reaction environment evaluation index, the raw material evaluation index and the finished product evaluation index to generate a performance evaluation index for evaluating the comprehensive performance of the polyether production line. The calculation formula of the performance evaluation index is as follows:

[0022] In the formula, , , , and They are the performance evaluation index, energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index, and finished product evaluation index within the monitoring period; In the formula, , , , are the weights of energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index and finished product evaluation index in the calculation of performance evaluation index, and , , , The specific value of is determined by the hierarchical analysis method.

[0023] Compared with the prior art, the present invention has the following beneficial effects: The intelligent control system for a polyether production line of the present invention first adjusts the temperature, pressure and pH value to the corresponding allowable ranges through an intelligent control module to ensure the safety of the production process of the polyether production line, and then evaluates the energy consumption excellence, reaction environment excellence, raw material usage and finished product excellence of the polyether production line respectively through the energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index and finished product evaluation index obtained by the feature extraction module and the performance evaluation module, and integrates the above four indexes into a performance evaluation index through a hierarchical analysis method to achieve the effect of comprehensively evaluating the polyether production line, provide a judgment basis and theoretical support for subsequent adjustment and optimization of the operating performance of the polyether production line, and help improve the quality and production efficiency of polyether products. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the intelligent control system of the polyether production line in the present invention; Figure 2 It is a schematic diagram of the performance evaluation module in the present invention. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0026] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0027] Example: See also Figure 1-2 The present invention provides an intelligent control system for a polyether production line, comprising the following modules: Data acquisition module, the data acquisition module is used to collect the state parameters of the polyether production line within the monitoring period, the state parameters include the total energy consumption of the equipment, the flow rate of raw materials, the flow rate and viscosity of finished products, the concentration of products, the concentration of by-products, the pressure at the top of the reactor, the temperature of the reaction solution in the reactor, the pH value and the concentration of raw materials in the reaction solution; It should be noted that the monitoring time period is the time period before the current moment, and the monitoring time period can be three minutes, five minutes, 10 minutes, etc., without limitation here. The acquisition frequency of various status parameters is aligned on the timestamp, and the specific acquisition frequency can be set to once per second, once per three seconds, once per five seconds, once per half a minute, etc., without limitation here. Furthermore, after obtaining the total energy consumption of the equipment, the concentration of the raw materials, the temperature, pressure and pH value of the reaction solution, the flow rate of the raw materials, the flow rate and viscosity of the finished products, the concentration of the finished products and the concentration of the by-products at different collection times within the monitoring time period, these types of data are subjected to maximum-minimum normalization processing respectively, and then the normalized data are used for subsequent analysis and processing, so that in the subsequent analysis and processing process, various data are analyzed and processed under the same dimension to avoid the problem of some data being neglected due to different dimensions, and when performing the maximum-minimum normalization processing, the status data in the current monitoring time period and the status data in the historical monitoring time period are subjected to maximum-minimum normalization processing together. The minimum normalization process is performed to maintain the consistency of data processing, and the minimum allowable temperature, the maximum allowable temperature, the upper limit value and the lower limit value of the suitable temperature range and the collected temperature are subjected to the maximum-minimum normalization process, and the minimum allowable pressure, the maximum allowable pressure, the upper limit value and the lower limit value of the suitable pressure range and the collected pressure are subjected to the maximum-minimum normalization process, and the minimum allowable pH value, the maximum allowable pH value, the upper limit value and the lower limit value of the suitable pH range and the collected pH value are subjected to the maximum-minimum normalization process, and the upper limit value and the lower limit value of the optimal viscosity range and the collected viscosity data are subjected to the maximum-minimum normalization process to ensure the rationality of the calculation formula in the following text; The data acquisition module includes an online optical concentration sensor, a temperature sensor, a pressure gauge and a pH meter installed in the reactor. The online optical concentration sensor, the temperature sensor and the pH meter are used to collect the concentration of raw materials (such as propylene oxide, polyether alcohol, etc.) in the reaction solution of the reactor, the temperature of the reaction solution and the pH value of the reaction solution, respectively. The pressure gauge is used to collect the pressure on the top of the reactor. The online optical concentration sensor, the temperature sensor, the pressure gauge and the pH meter can all use existing equipment. For example, the online optical concentration sensor can use Yokogawa, SITRANS series, OPTIMASS series, Metrohm 880 IC series and other series of equipment. The temperature sensor can use a thermocouple or RTO (resistance temperature detector). The pressure gauge can use a strain sensor or a piezoelectric sensor. The pH meter can use a glass electrode pH meter or a solid electrode pH sensor, etc., without limitation. Furthermore, there are multiple (e.g., 5) online optical concentration sensors, temperature sensors, and pH meters that are evenly arranged inside the reactor to measure the reaction solution at different positions in the reactor, and then the same data collected from different positions are averaged, and the final average is used as the corresponding data in the state parameter, so as to avoid accidental errors of individual points; The data acquisition module includes a flow meter installed at each raw material delivery pipeline, and the flow meter is used to collect the flow of the raw material in the corresponding raw material delivery pipeline, and then integrate the flow measured at each raw material delivery pipe to obtain the flow of various raw materials. For example, if there are two raw material delivery pipelines to transport propylene oxide to the reactor, the flow measured from the two raw material delivery pipelines will be added, and the result of the addition will be used as the flow of the raw material propylene oxide. The flow meter can be an electromagnetic flow meter, a turbine flow meter or an ultrasonic flow meter, which is not limited here; The data acquisition module includes a flow meter, a viscometer and an online optical concentration sensor installed at the finished product delivery pipeline. The flow meter, the viscometer and the online optical concentration sensor are used to collect the flow rate, viscosity, concentration of the product in the finished product and the concentration of the by-product, respectively. The finished product includes the product (i.e., polyether) and by-products (such as water, alcohol compounds, unreacted raw materials, catalyst residues, etc.). The flow meter can be an electromagnetic flow meter, a turbine flow meter or an ultrasonic flow meter, which is not limited here. The viscometer can be a rotational viscometer or a tubular viscometer, which is not limited here. The online optical concentration sensor can be a Yokogawa, SITRANS series, OPTIMASS series, Metrohm 880 IC series and other series of equipment, which is not limited here. Among them, the total energy consumption of the equipment is the total energy consumption of each energy-consuming equipment on the polyether production line during the monitoring period, including the power consumption of lighting equipment, the power consumption of heaters and coolers, the steam consumption in the reactor, the natural gas consumption, etc. For unified expression, the consumption of various energy sources is converted into tons of standard coal and then added up. The result of the cumulative sum is used as the total energy consumption of the equipment during the monitoring period.

[0028] The feature extraction module is used to extract the features of the state parameters to obtain the state parameter features. The state parameter features include the energy consumption evaluation index, the mean and standard deviation of other state parameters except the total energy consumption of the equipment during the monitoring period; The calculation formula of energy consumption evaluation index is as follows:

[0029] In the formula, is the energy consumption index, is the total energy consumption of the equipment during the monitoring period. , They are the mean flow rate and concentration of the finished product during the monitoring period, The energy consumption index is the duration of the monitoring period. It indicates the energy consumed to produce a unit volume (or weight) of polyether products. The larger the energy consumption index, the greater the energy consumed to produce a unit volume (or weight) of polyether products, which means that the polyether production line consumes more energy and has worse operating performance. It should be noted that when the concentration in the state parameter is volume concentration, the energy consumption index represents the energy consumed to produce a unit volume of polyether products. Conversely, when the concentration in the state parameter is mass concentration, the energy consumption index represents the energy consumed to produce a unit weight of polyether products. However, the units of various concentrations collected in the state parameters remain consistent, which is convenient for subsequent comparative analysis. In the formula, The energy consumption evaluation threshold is the preset energy consumption evaluation threshold, which is the ideal energy consumption index of the polyether production line, that is, the minimum energy consumption index that the polyether production line can achieve. Its value can be evaluated by relevant experts or obtained from manufacturers. The minimum energy consumption index of the polyether production line in previous production can also be selected as the energy consumption evaluation threshold. There is no restriction here. The energy consumption evaluation index is used to evaluate the energy consumption excellence of the polyether production line. The larger the energy consumption evaluation index, the worse the energy consumption excellence of the polyether production line, that is, the greater the energy consumption of the polyether production line during the monitoring period, the worse the operating performance; It should be noted that the calculation methods of the mean and standard deviation are existing technologies and will not be described in detail here. The feature extraction module includes a data input terminal, a calculation engine, a user interaction interface and a data output terminal. Its core is constructed based on existing data processing software, such as MATLAB software, SPSS software, etc. This is existing technology and will not be described in detail here. In this way, the feature extraction module extracts corresponding state parameter features from the state parameters.

[0030] Intelligent control module: The intelligent control module is used to control the polyether production line according to the comparison results of the pressure mean, temperature mean, pH mean and the corresponding allowable range in the state parameter characteristics, so as to adjust the corresponding parameters to the corresponding allowable range. The specific logic is as follows: If the mean pressure is lower than the minimum allowable pressure, the pressure regulating device of the polyether production line is started to increase the pressure in the reactor. Specifically, the pressure regulating degree of the pressure regulating device can be controlled according to the difference between the mean pressure and the minimum allowable pressure, so that the mean pressure rises to between the minimum allowable pressure and the maximum allowable pressure. The specific adjustment and control can adopt existing technologies, such as PLC controller. At the same time, the heating power of the heater in the polyether production line to the reactor can be increased to increase the pressure by heating the reactor, or the flow rate of the raw material can be increased or the stirring rate of the stirring mechanism in the reactor can be accelerated to increase the pressure by accelerating the reaction rate. The specific setting is made by the staff according to the actual situation and will not be repeated here. If the mean pressure is between the minimum allowable pressure and the maximum allowable pressure, it means that the pressure is within the corresponding allowable interval (pressure allowable interval), and no pressure adjustment is performed; If the mean pressure is higher than the maximum allowable pressure, the pressure regulating device of the polyether production line is started to reduce the pressure in the reactor. Specifically, the pressure regulating degree of the pressure regulating device can be controlled according to the difference between the mean pressure and the maximum allowable pressure, so that the mean pressure drops to between the minimum allowable pressure and the maximum allowable pressure. The specific regulation and control can adopt existing technologies, such as PLC controller. At the same time, the heating power of the heater in the polyether production line to the reactor can be reduced, and the cooling power of the cooler in the polyether production line to the reactor can be increased to reduce the pressure by cooling the reactor, or the flow rate of the raw material can be reduced or the stirring rate of the stirring mechanism in the reactor can be slowed down to reduce the pressure by slowing down the reaction rate. The specific setting is made by the staff according to the actual situation and is not limited here. If the temperature average is lower than the minimum allowable temperature, the heating power of the heater in the polyether production line to the reactor is increased to increase the temperature of the reactor. Specifically, the heating power of the heater can be increased according to the difference between the temperature average and the minimum allowable temperature, so that the temperature average rises to between the minimum allowable temperature and the maximum allowable temperature. The specific adjustment and control can adopt existing technologies, such as PLC controller, which will not be elaborated here. If the temperature mean is between the minimum allowable temperature and the maximum allowable temperature, it means that the temperature is within the corresponding allowable interval (temperature allowable interval), and no temperature adjustment is performed; If the temperature mean is higher than the maximum allowable temperature, the heating power of the heater in the polyether production line to the reactor is reduced to cool the reactor. Specifically, the heating power of the heater can be reduced according to the difference between the temperature mean and the maximum allowable temperature, so that the temperature mean drops to between the minimum allowable temperature and the maximum allowable temperature. The specific adjustment and control can adopt the existing technology, such as PLC controller, which will not be described in detail here. At the same time, the cooling power of the cooler in the polyether production line to the reactor can also be increased to speed up the cooling of the reactor. The specific setting is made by the staff according to the actual situation and is not limited here. If the average pH value is lower than the minimum allowable pH value, an alkaline substance (such as sodium hydroxide) is added to the reactor to increase the pH value, so that the average pH value rises to between the minimum allowable pH value and the maximum allowable pH value. Specifically, the amount of alkaline substance added can be determined according to the average pH value, the minimum allowable pH value and the volume of the solution in the reactor. In addition, the amount and rate of addition of the alkaline substance can also be controlled by a PLC controller. This is a prior art and will not be described in detail here. If the mean pH value is between the minimum allowable pH value and the maximum allowable pH value, it means that the pH value is within the corresponding allowable interval (pH value allowable interval), and no pH adjustment is performed; If the average pH value is higher than the maximum allowable pH value, an acidic substance (such as sulfuric acid and hydrochloric acid) is added to the reactor to lower the pH value, so that the average pH value drops to between the minimum allowable pH value and the maximum allowable pH value. Specifically, the amount of the acidic substance added can be determined according to the average pH value, the maximum allowable pH value and the volume of the solution in the reactor. In addition, the amount and rate of the acidic substance added can also be controlled by a PLC controller. This is a prior art and will not be described in detail here. It should be noted that the specific values ​​of the minimum allowable pressure, the maximum allowable pressure, the minimum allowable temperature, the maximum allowable temperature, the minimum allowable pH value and the maximum allowable pH value can be obtained from the technical manual of the reactor equipment or the process standards related to polyether production, and will not be elaborated here.

[0031] A performance evaluation module, which calculates the reaction environment evaluation index, raw material evaluation index, and finished product evaluation index of the polyether production line within the monitoring period based on the state parameter characteristics, and combines the above indexes with the energy consumption evaluation index to generate a performance evaluation index for evaluating the comprehensive performance of the polyether production line. The performance evaluation module includes a reaction environment evaluation module, a raw material evaluation module, a finished product evaluation model, and a comprehensive evaluation module; Among them, the reaction environment evaluation module is used to generate a reaction environment evaluation index for evaluating the quality of the reaction environment according to the state parameter characteristics. The calculation formula of the reaction environment evaluation index is as follows:

[0032] In the formula, The temperature average value during the monitoring period is used to reflect the average temperature of the reaction solution inside the reactor during the monitoring period. is the temperature standard deviation, which is used to reflect the temperature fluctuation degree of the reaction solution inside the reactor during the monitoring period. is the lower limit of the suitable temperature range for the reaction solution, is the upper limit of the suitable temperature range for the reaction of the reaction solution, is the temperature deviation value, which is used to measure the degree to which the reaction solution temperature deviates from the appropriate temperature range during the monitoring period. The larger the temperature deviation value, the more unsuitable the temperature of the reaction solution is during the monitoring period, and the more unfavorable it is for polyether production. In the formula, is the average pressure during the monitoring period. The average pressure is used to reflect the average pressure condition at the top of the reactor during the monitoring period. is the pressure standard deviation, which is used to reflect the pressure fluctuation degree at the top of the reactor during the monitoring period. is the lower limit of the suitable pressure range at the top of the reactor suitable for the reaction of the reaction solution, is the upper limit of the suitable pressure range at the top of the reactor suitable for the reaction of the reaction solution, is the pressure deviation value, which is used to measure the degree to which the pressure at the top of the reactor deviates from the appropriate pressure range during the monitoring period. The larger the pressure deviation value, the more unsuitable the pressure of the reaction solution is during the monitoring period, and the more unfavorable it is for polyether production. In the formula, The average pH value during the monitoring period is used to reflect the average pH value of the reaction solution inside the reactor during the monitoring period. is the pH standard deviation, which is used to reflect the pH fluctuation of the reaction solution in the reactor during the monitoring period. is the lower limit of the suitable pH value range for the reaction solution, is the upper limit of the suitable pH value range for the reaction solution, is the pH deviation value, which is used to measure the degree to which the pH value of the reaction solution deviates from the appropriate pH value range during the monitoring period. The larger the pH deviation value, the more unsuitable the pH value of the reaction solution is during the monitoring period, and the more unfavorable it is for polyether production. It should be noted that the lower limit and upper limit of the suitable temperature range, the lower limit and upper limit of the suitable pressure range, and the lower limit and upper limit of the suitable pH range can be obtained from the safety operation manual of the polyether production line, or determined by senior technical personnel; In the formula, The reaction environment evaluation index within the monitoring period is used to comprehensively evaluate the quality of the reaction environment of the reaction solution in the reactor when producing polyether from three levels: temperature, pressure and pH value. The larger the reaction environment evaluation index, the worse the reaction environment during polyether production, which is more unfavorable for polyether production. It should be noted that the larger the temperature deviation value, the more unsuitable the temperature environment of the reaction solution is during the monitoring period, and the more unfavorable it is for polyether production, that is, the worse the reaction environment is. On this basis, the larger the temperature standard deviation, the greater the temperature fluctuation during the monitoring period. Polyether production requires a stable and suitable temperature environment. Therefore, the larger the temperature standard deviation, the more unfavorable it is for polyether production, and the less reliable the quality of the polyether product produced. The more unsuitable the temperature environment of the reaction solution is, the worse the reaction environment is. The combination of the two can fully express the suitability of the temperature environment of the reaction solution, and because the temperature deviation value can fundamentally express the suitability of the temperature environment of the reaction solution, As the base number, As an index, The nonlinear effect of temperature deviation and temperature standard deviation on the quality of reaction environment is comprehensively expressed in the form of 1. The setting of 1 is to avoid the problem of base less than 1. The larger the temperature deviation and temperature standard deviation, The larger it is, the more unsuitable the temperature environment of the reaction solution is, that is, the worse the reaction environment is, and the larger the reaction environment evaluation index is; It should be noted that the larger the pressure deviation value, the more unsuitable the pressure environment of the reaction solution is during the monitoring period, and the more unfavorable it is for polyether production, that is, the worse the reaction environment is. On this basis, the larger the pressure standard deviation, the greater the pressure fluctuation during the monitoring period. Polyether production requires a stable and suitable pressure environment. Therefore, the larger the pressure standard deviation, the more unfavorable it is for polyether production, and the more unreliable the quality of the polyether product produced is. The more unsuitable the pressure environment of the reaction solution is, the worse the reaction environment is. The combination of the two can fully express the suitability of the pressure environment of the reaction solution. Moreover, because the pressure not only affects the reaction rate of the reaction solution, but also has a significant impact on the safety of the reactor structure, too high or too low pressure will cause serious risk accidents. Therefore, based on the previous article, the natural constant e is taken as the base, and the product of the pressure deviation value and the pressure standard deviation is taken as the exponent. The influence of pressure on the reaction environment evaluation index is magnified in the form of. Then, in the reactor, due to the influence of factors such as temperature, raw material flow rate, and reaction solution stirring rate, the pressure in the reactor fluctuates greatly and is difficult to maintain smoothly within a certain range. Take the square root of The nonlinear effect of pressure on the quality of the reaction environment is smoothed in the form of, and the larger the pressure deviation and the pressure standard deviation, The larger it is, the more unsuitable the pressure environment of the reaction solution is, that is, the worse the reaction environment is, and the larger the reaction environment evaluation index is; It should be noted that the larger the pH deviation is, the more unsuitable the pH environment of the reaction solution is during the monitoring period, and the more unfavorable it is for polyether production, that is, the worse the reaction environment is. On this basis, the larger the pH standard deviation is, the greater the pH fluctuation is during the monitoring period. Polyether production requires a stable and suitable pH environment. Therefore, the larger the pH standard deviation is, the more unfavorable it is for polyether production, and the less reliable the quality of the produced polyether product is. The more unsuitable the pH environment of the reaction solution is, the worse the reaction environment is. The combination of the two can fully express the suitability of the pH environment of the reaction solution, and because the pH deviation can fundamentally express the suitability of the pH environment of the reaction solution, As the base number, As an index, The nonlinear effect of pH deviation and pH standard deviation on the quality of the reaction environment is comprehensively expressed in the form of 1. The setting of 1 is to avoid the problem of the base being less than 1. The larger the pH deviation and pH standard deviation, The larger it is, the more unsuitable the pH environment of the reaction solution is, that is, the worse the reaction environment is, and the larger the reaction environment evaluation index is; It should be noted that in the internal environment of the reactor for producing polyether, temperature and pressure have a strong correlation. For example, a temperature increase will lead to an increase in pressure, and a temperature decrease will lead to a decrease in pressure, and vice versa. Therefore, based on the previous article, the product of the temperature deviation value and the pressure deviation value is introduced as an interaction term to achieve a comprehensive evaluation of the reaction environment in which the reaction solution is located. Since both temperature and pressure have a significant impact on the reaction solution, the natural constant e is used as the base and As an index, The nonlinear effect of the interaction term on the quality of the reaction environment is comprehensively expressed in the form of The larger it is, that is, the worse the reaction environment is, the greater the reaction environment evaluation index is; In the formula, , , and are preset proportional factors. Specifically, it is the weight of the temperature factor in the evaluation of the quality of the reaction environment. Specifically, it is the weight of the pressure factor in the evaluation of the quality of the reaction environment. Specifically, it is the weight of pH factor in the evaluation of the quality of the reaction environment. Specifically, it is the weight of the interaction factor of temperature and pressure in the evaluation of the quality of the reaction environment. Because the pressure factor not only affects the reaction rate of the reaction solution, but also significantly affects the operating safety of the reactor, the pressure is given the highest weight. Because the temperature in the reactor is more sudden and difficult to control than the Ph value, the temperature is given the second highest weight. Because the temperature and pressure have been considered separately before considering the interaction term, in order to avoid excessively increasing the weight of pressure and temperature in the evaluation of the quality of the reaction environment, the interaction term is given the lowest weight, and the pH value is given the third highest weight. On the basis of ; As an implementation method, The value range is 0.2-0.3, The value range is 0.45-0.65, The value range is 0.1-0.2. The value range is 0.05-0.1. The specific value is set by the staff according to the actual situation and is not limited here; Among them, the raw material evaluation module is used to generate a raw material evaluation index for evaluating the use of raw materials according to the state parameter characteristics. The calculation formula of the raw material evaluation index is as follows:

[0033] In the formula, is the mean flow rate of the i-th raw material during the monitoring period, is the mean concentration of the i-th raw material in the reaction solution during the monitoring period, i is the index of the raw material type, and , I is the number of raw material types; In the formula, The raw material evaluation index within the monitoring period is used to comprehensively evaluate the use of raw materials in the reactor to produce polyether from two aspects: the raw material flow rate and the concentration of raw materials in the reaction solution. The larger the raw material evaluation index, the better the use of raw materials and the better the production efficiency of polyether. It should be noted that, under ideal production conditions, the greater the flow rate of the raw materials (that is, the more raw materials are added and the faster the polyether is produced), the more polyether can be produced, the better the utilization of the raw materials, and the more conducive to the production of polyether products. However, in actual production, due to the limitations of factors such as reaction rate, the raw materials cannot be completely reacted immediately after being added to the reactor. Therefore, when using the average flow rate of the raw materials to evaluate the utilization of the raw materials, the concentration of the raw materials in the reaction solution is introduced for correction. The greater the concentration of the raw materials in the reaction solution, the more raw materials are accumulated in the reactor without reacting. Therefore, the greater the concentration of the raw materials in the reaction solution, the worse the utilization of the raw materials. Therefore, the utilization of the raw materials is expressed by the ratio of the flow rate of the raw materials to the concentration of the raw materials in the reaction solution. In addition, under the premise that the concentration of the raw materials in the reaction solution is relatively large, adding a larger flow rate of raw materials to the reactor will not have the expected beneficial effect, but will have an adverse effect on the reactor (such as causing the pressure of the reactor to increase and posing a safety hazard). Moreover, because the concentration of the raw materials in the reaction solution reflects the quality of the utilization of the raw materials from the result, the natural constant e is taken as the base, and As an index, The adverse effect of the concentration of the raw materials in the reaction solution on the use of the raw materials is expressed in the form of To characterize the use of raw materials, the greater the flow rate of the raw materials, the lower the concentration of the raw materials in the reaction solution, indicating that the use of the raw materials is better, and the greater the raw material evaluation index; In the formula, It is the weight of the ith raw material in the calculation of the raw material evaluation index. If the concentration of the ith raw material in the reaction solution is greater, it means that the reaction of the ith raw material is more incomplete, that is, the utilization of the ith raw material is worse, and the adverse factors caused by it on the polyether production efficiency are greater. When calculating the raw material evaluation index, it is necessary to give this raw material a greater weight so that the raw material evaluation index can more sensitively reflect the utilization of the raw materials. Therefore, the ratio of the mean concentration of the ith raw material in the reaction solution to the sum of the mean concentrations of all raw materials is used as the weight of the ith raw material in the calculation of the raw material evaluation index.

[0034] Among them, the finished product evaluation model is used to generate a finished product evaluation index for evaluating the excellence of the finished product according to the state parameter characteristics. The finished product evaluation model is constructed based on a deep neural network. The method for obtaining the finished product evaluation index is as follows: The state parameter characteristics within the monitoring period are processed to obtain a finished product feature vector, which includes the flow mean of the finished product, the viscosity deviation of the finished product, the ratio of the mean product concentration to the mean by-product concentration in the finished product, the flow standard deviation of the finished product and the interaction term of the product concentration standard deviation. The finished product feature vector is input into the finished product evaluation model to obtain a finished product evaluation index reflecting the excellence of the finished product within the monitoring period; It should be noted that the finished product evaluation index is used to comprehensively evaluate the excellence of the finished products produced by the polyether production line from four aspects: the flow rate, viscosity, concentration of products in the finished products, and concentration of by-products. The larger the finished product evaluation index, the better the performance of the finished product produced by the polyether production line, that is, the better the working performance of the polyether production line. The calculation formula of viscosity deviation is as follows:

[0035] In the formula, The viscosity average value during the monitoring period is used to reflect the average viscosity of the finished product during the monitoring period. is the viscosity standard deviation, which is used to reflect the viscosity fluctuation of the finished product during the monitoring period. is the lower limit of the optimal viscosity range, is the upper limit of the optimal viscosity range, The viscosity deviation value is used to measure the degree to which the viscosity of the finished product deviates from the optimal viscosity range during the monitoring period. The larger the viscosity deviation value, the worse the viscosity index of the finished product during the monitoring period, that is, the worse the quality of the finished product. Therefore, the viscosity deviation value is used as an influencing factor in calculating the finished product evaluation index. It should be noted that the optimal viscosity range is the viscosity range of excellent finished products. Excellent finished products are products with high product concentrations. Here, finished products with a product concentration between 90% and 100% are regarded as excellent finished products, and the maximum viscosity and the minimum viscosity of the finished products with a product concentration between 90% and 100% are respectively used as the upper limit and the lower limit of the optimal viscosity range. Of course, the evaluation criteria for excellent finished products can also be other product concentration ranges, which are set by the staff according to the actual situation and are reasonable; It should be noted that the larger the mean flow rate of the finished product is, the more finished products the polyether production line produces per unit time, that is, the higher the production efficiency of the polyether production line is. Therefore, the mean flow rate of the finished product is used as an influencing factor in calculating the finished product evaluation index. The formula for calculating the ratio of product concentration to by-product concentration in the finished product is as follows:

[0036] In the formula, is the ratio of the product concentration to the by-product concentration in the finished product, is the mean concentration of the product, is the mean concentration of the jth byproduct during the monitoring period, j is the index of the byproduct type, and , J is the number of by-product types; It should be noted that The bigger, The smaller, The larger the value is, the higher the proportion of the product in the finished product is, that is, the higher the purity of the polyether product in the finished product is. Therefore, the ratio of the product concentration to the by-product concentration in the finished product is used as an influencing factor for calculating the finished product evaluation index. The formula for calculating the interaction term between the standard deviation of the finished product flow rate and the standard deviation of the product concentration is as follows:

[0037] In the formula, is the interaction term between the standard deviation of the finished product flow rate and the standard deviation of the product concentration, is the flow standard deviation of the finished product, is the concentration standard deviation of the product; It should be noted that the larger the standard deviation of the finished product flow rate, the more unstable the finished product flow rate is during the monitoring period, and the larger the standard deviation of the product concentration is, the more unstable the quality of the finished product is during the monitoring period. Both indicate that the more unstable the finished product produced by the polyether production line is during the monitoring period, the more likely it is to have quality problems. Therefore, when calculating the finished product evaluation index, the standard deviation of the finished product flow rate and the standard deviation of the product concentration are taken into consideration. In addition, under normal production conditions, the fluctuations in the finished product flow rate and the concentration of the product in the finished product are small, and it is generally difficult to capture such subtle changes. Therefore, the natural constant e is used as the base number and the standard deviation of the finished product concentration is taken into account. As an index, The interaction term is constructed in the form of to amplify this subtle change and improve the sensitivity of finished product quality evaluation; It should be noted that the finished product evaluation model includes an input layer for receiving a finished product feature vector, one or more hidden layers for processing the finished product feature vector, and a ReLU activation function is used in the hidden layer to increase nonlinearity, and the hidden layer includes 64 or 32 neurons, and an output layer for outputting a finished product evaluation index, and the output layer uses a LeakyReLU activation function to output a finished product evaluation index according to the finished product feature vector; Before using the finished product evaluation model to output the finished product evaluation index corresponding to the current monitoring time period, the finished product evaluation model needs to be trained first. The training process is as follows: first obtain the state parameters in multiple historical monitoring time periods, and perform data processing on the state parameters to obtain the finished product feature vector corresponding to the historical monitoring time period, and then comprehensively evaluate the excellence of the finished products produced by the polyether production line from four levels: the flow rate, viscosity, concentration of products in the finished products, and concentration of by-products based on the expert scoring method, and obtain the finished product evaluation index corresponding to the historical monitoring time period, and mark the finished product evaluation index on the corresponding finished product feature vector to form a data set , divide the data set into training set, validation set and test set in a ratio of 70:15:15, use the root mean square error as the loss function, use the training set to train the finished product evaluation model, and monitor the loss and accuracy of the training process, use the validation set to adjust the hyperparameters and prevent overfitting, and use the test set to evaluate the performance of the finished product evaluation model. Specifically, the performance of the finished product evaluation model is evaluated by calculating indicators such as accuracy and recall. When the relevant indicators reach the threshold (such as the accuracy reaches 95%), the training of the finished product evaluation model is considered to be completed. The specific training, validation and testing processes are conventional technical means of those skilled in the art and will not be elaborated here. Among them, the comprehensive evaluation module is used to combine the energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index and finished product evaluation index to generate a performance evaluation index for evaluating the comprehensive performance of the polyether production line. The calculation formula of the performance evaluation index is as follows:

[0038] In the formula, is the performance evaluation index within the monitoring period, The performance evaluation index is the finished product evaluation index within the monitoring period. The performance evaluation index is used to combine the reaction environment evaluation index, the raw material evaluation index, the finished product evaluation index and the energy consumption evaluation index to comprehensively evaluate the performance of the polyether production line. The larger the performance evaluation index, the worse the comprehensive performance of the polyether production line, which is more unfavorable for polyether production. It should be noted that, from the above description, the larger the energy consumption evaluation index and the reaction environment evaluation index, the worse the comprehensive performance of the polyether production line, and the more unfavorable it is for polyether production, while the larger the raw material evaluation index and the finished product evaluation index, the better the comprehensive performance of the polyether production line, and the more favorable it is for polyether production. Therefore, the performance evaluation index is positively correlated with the energy consumption evaluation index and the reaction environment evaluation index, and negatively correlated with the raw material evaluation index and the finished product evaluation index. Therefore, the performance evaluation index calculation formula in the form of weighted summation is set; In the formula, , , , are the weights of energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index and finished product evaluation index in the calculation of performance evaluation index, and , , , The specific value of is determined by the hierarchical analysis method, and the specific logic is as follows: The four indicators of energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index and finished product evaluation index are marked, and the relative importance values ​​between them are determined by the nine-scale method to construct a judgment matrix, in which the index of the energy consumption evaluation index is marked as 1, the index of the reaction environment evaluation index is marked as 2, the index of the raw material evaluation index is marked as 3, and the index of the finished product evaluation index is marked as 4. The constructed judgment matrix is:

[0039] Among them, f and v both represent the index of the index, and , , Indicates the importance of the index f relative to the index v in the performance evaluation index. The specific value is determined by relevant experts using a 1-9 scoring method. Indicates that the index f is more important for performance evaluation than the index v. Indicates that the index f is extremely unimportant to the performance evaluation index compared to the index v; Divide each element value in the judgment matrix by the sum of its columns to obtain a normalized judgment matrix, calculate the mean of the element values ​​in each row of the normalized judgment matrix, and use the mean of the element values ​​in the first row as the proportional coefficient of the energy consumption evaluation index, the mean of the element values ​​in the second row as the proportional coefficient of the reaction environment evaluation index, the mean of the element values ​​in the third row as the proportional coefficient of the raw material evaluation index, and the mean of the element values ​​in the fourth row as the proportional coefficient of the finished product evaluation index. With the sum of the scaled values ​​being equal to 1 as a constraint condition, scale the four proportional coefficients in equal proportions, and use the values ​​obtained after scaling as weights of the corresponding indexes; The threshold judgment module is used to compare the performance evaluation index and the performance evaluation threshold, and to alarm when the performance evaluation index is higher than the performance evaluation threshold, prompting the staff to adjust the status parameters of the polyether production line until the performance evaluation index is no higher than the performance evaluation threshold. The performance evaluation threshold is determined by relevant experts based on the previous status parameters of the polyether production line. For example, the performance evaluation index corresponding to the status parameters of the polyether production line when the production performance was excellent and there was no fault in the past is selected as the performance evaluation threshold. The threshold judgment module includes a sonic alarm for issuing an alarm, a single-chip microcomputer for comparative judgment, etc. Existing equipment can be used specifically and is not limited here.

[0040] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0041] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0042] 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, and 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.

[0043] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An intelligent control system for a polyether production line, characterized in that: include: A data acquisition module, which is used to collect state parameters of the polyether production line within the monitoring period, the state parameters including total energy consumption of the equipment, flow rate of raw materials, flow rate and viscosity of finished products, concentration of products, concentration of by-products, pressure at the top of the reactor, temperature of the reaction solution in the reactor, pH value and concentration of raw materials in the reaction solution; A feature extraction module, wherein the feature extraction module is used to extract features of the state parameters to obtain state parameter features, wherein the state parameter features include an energy consumption evaluation index, and means and standard deviations of other state parameters except the total energy consumption of the equipment within a monitoring period; An intelligent control module, which is used to control the polyether production line based on a PLC controller according to a comparison result of the pressure mean, temperature mean, pH mean and the corresponding allowable range in the state parameter characteristics, so that the corresponding parameters are adjusted to within the corresponding allowable range; A performance evaluation module, which calculates the reaction environment evaluation index, raw material evaluation index, and finished product evaluation index of the polyether production line within the monitoring period based on the state parameter characteristics, and combines the above indexes with the energy consumption evaluation index to generate a performance evaluation index for evaluating the comprehensive performance of the polyether production line; The threshold judgment module is used to compare the performance evaluation index with the performance evaluation threshold and to generate an alarm when the performance evaluation index is higher than the performance evaluation threshold.

2. The intelligent control system for a polyether production line according to claim 1, characterized in that: The data acquisition module includes an online optical concentration sensor, a temperature sensor, a pressure gauge and a pH meter installed in the reactor, a flow meter installed at each raw material delivery pipeline, and a flow meter, a viscometer and an online optical concentration sensor installed at the finished product delivery pipeline.

3. The intelligent control system for a polyether production line according to claim 1 is characterized in that: The calculation formula of the energy consumption evaluation index is as follows: , In the formula, is the energy consumption index, is the total energy consumption of the equipment during the monitoring period. , They are the mean flow rate and concentration of the finished product during the monitoring period, is the duration of the monitoring period, is the preset energy consumption evaluation threshold, It is the energy consumption evaluation index.

4. The intelligent control system for a polyether production line according to claim 1, characterized in that: The performance evaluation module includes a reaction environment evaluation module, a raw material evaluation module, a finished product evaluation model and a comprehensive evaluation module.

5. The intelligent control system for a polyether production line according to claim 4 is characterized in that: The reaction environment evaluation module is used to generate a reaction environment evaluation index for evaluating the quality of the reaction environment according to the state parameter characteristics. The calculation formula of the reaction environment evaluation index is as follows: ; In the formula, is the average temperature during the monitoring period, is the standard deviation of temperature during the monitoring period, is the lower limit of the suitable temperature range, is the upper limit of the suitable temperature range, is the temperature deviation value; In the formula, is the mean pressure during the monitoring period, is the standard deviation of pressure during the monitoring period, is the lower limit of the suitable pressure range, is the upper limit of the suitable pressure range, is the pressure deviation value; In the formula, is the average pH value during the monitoring period, is the standard deviation of pH value during the monitoring period, is the lower limit of the suitable pH value range, is the upper limit of the suitable pH range, is the pH deviation; In the formula, is the reaction environment evaluation index during the monitoring period, , , and are preset scaling factors, and ,and .

6. The intelligent control system for a polyether production line according to claim 4 is characterized in that: The raw material evaluation module is used to generate a raw material evaluation index for evaluating the use of raw materials according to the state parameter characteristics. The calculation formula of the raw material evaluation index is as follows: ; In the formula, is the mean flow rate of the i-th raw material during the monitoring period, is the mean concentration of the i-th raw material in the reaction solution during the monitoring period, i is the index of the raw material type, and , I is the number of raw material types; In the formula, is the raw material evaluation index within the monitoring period, is the weight of the i-th raw material in the calculation of the raw material evaluation index.

7. The intelligent control system for a polyether production line according to claim 4 is characterized in that: The finished product evaluation model is used to generate a finished product evaluation index for evaluating the excellence of the finished product according to the state parameter characteristics. The method for obtaining the finished product evaluation index is as follows: The state parameter characteristics within the monitoring time period are processed to obtain a finished product feature vector, which includes the flow mean of the finished product, the viscosity deviation of the finished product, the ratio of the mean product concentration to the mean by-product concentration in the finished product, the flow standard deviation of the finished product and the interaction term of the product concentration standard deviation. The finished product feature vector is input into the finished product evaluation model to obtain a finished product evaluation index reflecting the excellence of the finished product within the monitoring time period.

8. The intelligent control system for a polyether production line according to claim 7, characterized in that: The calculation formula of the viscosity deviation value is as follows: ; In the formula, is the average viscosity during the monitoring period, is the standard deviation of viscosity during the monitoring period, is the lower limit of the optimal viscosity range, is the upper limit of the optimal viscosity range, is the viscosity deviation value; The formula for calculating the ratio of product concentration to by-product concentration in the finished product is as follows: ; In the formula, is the ratio of the product concentration to the by-product concentration in the finished product, is the mean concentration of the product, is the mean concentration of the jth byproduct during the monitoring period, j is the index of the byproduct type, and , J is the number of by-product types; The formula for calculating the interaction term between the standard deviation of the finished product flow rate and the standard deviation of the product concentration is as follows: ; In the formula, is the interaction term between the standard deviation of the finished product flow rate and the standard deviation of the product concentration, is the flow standard deviation of the finished product, is the standard deviation of product concentration.

9. The intelligent control system for a polyether production line according to claim 4, characterized in that: The comprehensive evaluation module is used to combine the energy consumption evaluation index, the reaction environment evaluation index, the raw material evaluation index and the finished product evaluation index to generate a performance evaluation index for evaluating the comprehensive performance of the polyether production line. The calculation formula of the performance evaluation index is as follows: ; In the formula, , , , and They are the performance evaluation index, energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index, and finished product evaluation index within the monitoring period; In the formula, , , , are the weights of energy consumption evaluation index, reaction environment evaluation index, raw material evaluation index and finished product evaluation index in the calculation of performance evaluation index, and , , , The specific value of is determined by the hierarchical analysis method.

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