Hot water system in lycopene production process

Abstract

The invention relates to the technical field of agricultural product processing automation control, and provides a hot water system used in a lycopene production process, the hot water system used in the lycopene production process comprises an equipment end, a monitoring end and a control end, and the equipment end, the monitoring end and the control end are connected through real-time monitoring and data analysis; according to the method, the waste heat utilization prediction model is constructed, the actual waste heat recovery amount and the predicted waste heat recovery amount are predicted and compared, and accurate regulation and control are achieved. Recycled waste heat is used for preheating raw materials and maintaining system temperature, and energy consumption is reduced. According to the method, the problem that the waste heat recovery efficiency is difficult to count is solved, the energy utilization efficiency in the lycopene production process is remarkably improved, and energy conservation, emission reduction and optimization of the production process are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of automatic control of agricultural product processing, and in particular to a hot water system in a lycopene production process. Background Art

[0002] Lycopene is a carotenoid that occurs naturally in plants. It is widely found in a variety of plant foods, especially in the ripe fruit of tomatoes, a plant of the Solanaceae family. In addition, fruits and vegetables such as carrots, watermelons, grapefruits, papayas, and guavas also contain a certain amount of lycopene.

[0003] In the production process of lycopene, the thermal water system plays an auxiliary role in the production process, and a large amount of waste heat is generated in the production process of lycopene. The thermal water system can be used to recycle this waste heat and convert it into usable heat energy or hot water through heat exchange and other methods, which can be used in other production links or heating purposes, thereby achieving energy conservation and recycling. Before extracting lycopene, tomato skins and tomato products usually need to be dried. The thermal water system is used to provide the heat source required in the drying process, although hot air drying or other heat conduction methods are more commonly used. However, in special processes, hydrothermal pretreatment of raw materials is required to increase the dissolution rate of lycopene.

[0004] The production process of lycopene usually includes multiple steps such as raw material selection, drying, crushing, extraction, purification, etc. The role of the hot water system in this process may be relatively limited, and it is more of an auxiliary means to support the smooth progress of the production process. Although the direct role of the thermal water system in the lycopene production process is not obvious, it may play a role in raw material pretreatment, cleaning and disinfection, energy recovery and recycling, and auxiliary equipment cooling.

[0005] At present, the hot water system in the lycopene production process has the following technical pain points: in the lycopene production process, although the hot water system can be used to recover waste heat, the recovery efficiency may be limited by many factors, such as the design of the heat exchanger, the temperature and quality of the waste heat, etc. The waste heat recovery efficiency is difficult to calculate, resulting in the inability to fully utilize the recovered waste heat in the lycopene production process. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a hot water system in a lycopene production process to solve the problem that it is difficult to calculate the waste heat recovery efficiency, resulting in the inability to fully utilize the recovered waste heat in the lycopene production process.

[0007] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0008] The present invention provides a hot water system in a lycopene production process, comprising: a device end, a monitoring end and a control end, wherein the control end establishes communication connections with the device end, the monitoring end and a background control end, the control end receives and analyzes and processes the hot water system parameter information in the lycopene production process preset by the background control end and the lycopene production equipment temperature data collected by the monitoring end, obtains the modified hot water system parameter information in the lycopene production process, and the device end executes the modified hot water system parameter information in the lycopene production process. The control end comprises:

[0009] an acquisition unit, for acquiring historical operation data of a lycopene production equipment, configuration information of a hot water system in a historical lycopene production process, and historical waste heat data, wherein the lycopene production equipment includes a hot water storage tank, a hot water storage tank pump, a hot water atmospheric pressure boiler, a hot water circulation pump, an extraction heat exchanger, a separation heat exchanger, an extraction kettle, and a separation kettle, and constructing a lycopene production equipment utilization prediction model according to the historical operation data of the lycopene production equipment, configuration information of a hot water system in a historical lycopene production process, and historical waste heat data;

[0010] The monitoring unit establishes a lycopene production equipment monitoring zone, determines the lycopene production equipment within the lycopene production equipment monitoring location zone according to the location information of the lycopene production equipment, monitors the lycopene production equipment within each lycopene production equipment monitoring zone, and obtains real-time operation data and real-time waste heat data of the lycopene production equipment under operation status;

[0011] a data comparison unit, receiving preset hot water system parameter information in the lycopene production process, using the prediction model of the lycopene production equipment to obtain the predicted waste heat recovery information of the hot water system in the lycopene production process, collecting the real-time waste heat recovery information of the lycopene production equipment, comparing the real-time waste heat recovery information of the lycopene production equipment with the predicted waste heat recovery information of the hot water system in the lycopene production process, and obtaining the real-time waste heat recovery error information of the hot water system in the lycopene production process;

[0012] The heat control unit corrects the preset parameter information of the hot water system in the lycopene production process according to the waste heat recovery error information of the hot water system in the real-time lycopene production process, and obtains the modified parameter information of the hot water system in the lycopene production process;

[0013] The parameter adjustment optimization unit executes the modified hot water system parameter information in the lycopene production process on the equipment side to recover the waste heat in the lycopene production process. The waste heat discharged from the extraction heat exchanger and the separation heat exchanger is introduced into the preheating device and the hot water storage tank through a circulation pump. The recovered waste heat is used to preheat the raw materials and maintain the temperature of the hot water system in the lycopene production process.

[0014] Furthermore, the hot water system and the acquisition unit in the lycopene production process provided by the present invention include:

[0015] Preprocessing the historical operation data of the lycopene production equipment, the hot water system configuration information in the historical lycopene production process, and the historical waste heat data to obtain a preprocessed data set, and dividing the preprocessed data set into a training set and a test set;

[0016] Analyze historical operation data, hot water system configuration information and waste heat data to determine the waste heat prediction characteristics of the lycopene production equipment, which include the equipment's operating time, temperature, pressure, flow parameters, as well as the hot water system's configuration and waste heat recovery;

[0017] Select a neural network model as a training model, and use the training set data to train the neural network model;

[0018] The trained model is evaluated using the test set data. The prediction ability of the model is evaluated by calculating the error between the predicted value and the actual value. The prediction model for waste heat utilization of lycopene production equipment is obtained, and the trained prediction model for waste heat utilization of lycopene production equipment is deployed to the control end.

[0019] The control end uses the deployed model to make real-time predictions on the waste heat utilization of the lycopene production equipment and dynamically adjusts the parameters of the hot water system based on the waste heat prediction results.

[0020] Furthermore, the hot water system and monitoring unit in the lycopene production process provided by the present invention include:

[0021] Obtaining location information of lycopene production equipment, where the location information of lycopene production equipment includes coordinates of the equipment, the area where it is located, and the production line;

[0022] Associating the collected device location information with the device name to obtain a device information database;

[0023] According to the lycopene production process steps and the connection relationship between the equipment, the production equipment is divided into several monitoring zones. The control end uses the location information of the equipment to configure the corresponding monitoring parameters for each monitoring zone, including the monitoring frequency and data collection points.

[0024] The control end collects the operation data and waste heat data of the lycopene production equipment in each monitoring zone in real time through the monitoring end.

[0025] Furthermore, the hot water system and data comparison unit in the lycopene production process provided by the present invention include:

[0026] The control end loads the trained lycopene production equipment utilization prediction model;

[0027] The received preset hot water system parameter information is used as input and transmitted to the prediction model of the lycopene production equipment, and the prediction model performs calculations based on the input parameter information to obtain the predicted waste heat recovery information of the hot water system in the lycopene production process;

[0028] The estimated waste heat recovery amount is extracted from the prediction model and the prediction results are stored in the database of the control end.

[0029] Furthermore, the hot water system and heat control unit in the lycopene production process provided by the present invention include:

[0030] The data comparison unit receives waste heat recovery error information, wherein the waste heat recovery error information includes a difference between an actual waste heat recovery amount and an expected waste heat recovery amount;

[0031] Evaluate the impact of errors on the lycopene production process and hot water system performance, determine whether parameter correction is needed, and obtain error analysis results;

[0032] According to the error analysis result, the parameter correction target is determined, and the preset hot water system parameter information in the lycopene production process is adjusted to obtain the modified hot water system parameter information in the lycopene production process;

[0033] The modified hot water system parameter information in the lycopene production process is applied to the hot water system in the actual lycopene production process. The waste heat recovery of the hot water system after correction is monitored in real time through the data monitoring unit. The waste heat recovery data before and after correction are compared to evaluate whether the parameter information of the hot water system in the lycopene production process after the parameter modification reaches the expected target.

[0034] Furthermore, the hot water system and parameter adjustment optimization unit in the lycopene production process provided by the present invention include:

[0035] The device receives the parameter adjustment instruction from the control end and analyzes it. According to the parameter information in the instruction, the device adjusts the temperature setting value and flow setting value of the hot water system;

[0036] The equipment side monitors the waste heat information discharged by the extraction heat exchanger and the separation heat exchanger in real time through sensors. When waste heat is detected, the equipment side automatically starts the circulation pump to introduce the waste heat into the preheating device and the hot water storage tank through the pipeline;

[0037] The waste heat is introduced into the preheating device to preheat the raw materials entering the production process and increase the initial temperature of the raw materials;

[0038] At the same time, waste heat is also introduced into the hot water storage tank for storage to maintain the temperature of the hot water system in the lycopene production process. The equipment end monitors the waste heat recovery effect in real time through sensors, including the recovery amount and recovery efficiency, and feeds back the monitored waste heat recovery effect data to the control end.

[0039] Furthermore, the hot water system and parameter adjustment optimization unit in the lycopene production process provided by the present invention include:

[0040] The lycopene production equipment is encoded using the parameters of the prediction model, and each parameter of the model is mapped to a gene in the chromosome;

[0041] The fitness function is set to evaluate the quality of each individual. The fitness function is a quantitative indicator of prediction accuracy.

[0042] A certain number of individuals are randomly generated as the initial population, each of which represents a set of parameter combinations of the prediction model used by the lycopene production equipment as the search starting point of the genetic algorithm;

[0043] Perform selection, crossover and mutation operations on the initial population to generate a new population. In each generation, the fitness of each individual is evaluated, and individuals with higher fitness are selected for reproduction in the next generation.

[0044] Repeat the iterative process of the genetic algorithm until the stopping condition is met or the maximum number of iterations is reached and the fitness reaches the preset threshold;

[0045] After the iteration of the genetic algorithm, the individual with the highest fitness is selected as the optimal solution, which represents the best combination of the parameters of the lycopene production equipment utilization prediction model:

[0046] The parameters in the optimal individuals are used to update the prediction model of lycopene production equipment, and the optimal parameter combination is applied to the model.

[0047] Beneficial effects of the present invention: The present invention constructs a waste heat utilization prediction model for lycopene production equipment, and dynamically adjusts the hot water system parameters based on real-time operation data and prediction results, effectively solving the problem of statistical difficulties in waste heat recovery efficiency, and significantly improving waste heat recovery efficiency. The present invention recovers and utilizes waste heat discharged from the extraction heat exchanger and the separation heat exchanger, and introduces it into the preheating device and the hot water storage tank, which not only reduces energy consumption, but also reduces production costs, and conforms to the concept of green production. The waste heat of the present invention is used to preheat raw materials, which increases the initial temperature of the raw materials, thereby accelerating the subsequent processing process, shortening the production cycle, and improving the overall production efficiency. The system collects equipment data in real time through the monitoring unit, and the control end performs intelligent analysis and parameter adjustment, thereby realizing the automation and intelligent control of the production process and reducing the error and cost of manual operation. The dynamic parameter adjustment mechanism ensures that the hot water system can maintain a high waste heat recovery efficiency and system stability under different working conditions, and improves the adaptability and reliability of the system. The prediction model is optimized by genetic algorithm, which improves the prediction accuracy of the model, provides a more scientific basis for parameter regulation of the hot water system, and further improves the waste heat recovery efficiency.

[0048] In summary, the present invention not only improves the waste heat recovery efficiency in the lycopene production process, but also promotes energy conservation and emission reduction and optimization of the production process through the comprehensive effects of multiple links such as intelligent control, real-time monitoring and data collection, data comparison and error analysis, dynamic parameter regulation, waste heat recovery and utilization, and optimization algorithm application, which has significant economic and environmental benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0050] Figure 1 A schematic diagram of the system structure provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0052] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0053] See also Figure 1 The present invention provides a hot water system in a lycopene production process, comprising: an equipment end, a monitoring end, a control end and a background control end, the control end establishes communication connections with the equipment end, the monitoring end and the background control end, the control end receives and analyzes the preset hot water system parameter information in the lycopene production process of the background control end and the lycopene production equipment temperature data collected by the monitoring end, obtains the modified hot water system parameter information in the lycopene production process, the equipment end executes the modified hot water system parameter information in the lycopene production process, and the control end comprises:

[0054] Through wired or wireless means (such as industrial Ethernet, Wi-Fi, Bluetooth, etc.), a stable and reliable communication connection is established between the control end and the device end, the monitoring end, and the background control end. This enables real-time information exchange between components, making subsequent data analysis and parameter adjustment possible.

[0055] Receiving preset parameters: the control end receives preset hot water system parameter information in the lycopene production process from the background control end.

[0056] Collect real-time data: The monitoring end collects the temperature data of the lycopene production equipment in real time and sends this data to the control end.

[0057] Data analysis and processing: The control end conducts comprehensive analysis and processing on the received preset parameters and monitoring data to evaluate the operating status and efficiency of the current hot water system.

[0058] The present invention can timely discover system deviations through real-time analysis of data, providing a basis for subsequent parameter adjustments. Based on the data analysis results, the control end makes necessary adjustments to the preset hot water system parameter information and generates modified parameter information. The modified parameter information is sent to the device end in the form of instructions to guide the device end to make corresponding operational adjustments. Through intelligent parameter adjustment, the system can automatically optimize the operating state of the hot water system and improve its efficiency and stability.

[0059] After receiving the parameter adjustment instruction from the control end, the device end adjusts the operating parameters of the hot water system according to the parameter information in the instruction. After the parameter adjustment, the device end continues to feedback the adjusted operating status data in real time through the monitoring end. The control end evaluates the effect of the parameter adjustment based on the feedback data and makes further optimization adjustments if necessary.

[0060] an acquisition unit, for acquiring historical operation data of a lycopene production equipment, configuration information of a hot water system in a historical lycopene production process, and historical waste heat data, wherein the lycopene production equipment includes a hot water storage tank, a hot water storage tank pump, a hot water atmospheric pressure boiler, a hot water circulation pump, an extraction heat exchanger, a separation heat exchanger, an extraction kettle, and a separation kettle, and constructing a lycopene production equipment utilization prediction model according to the historical operation data of the lycopene production equipment, configuration information of a hot water system in a historical lycopene production process, and historical waste heat data;

[0061] Use data collection tools or system interfaces to extract required data from various data sources. Clean, deduplicate, and format the collected data. Data collection and organization are the basis for building a prediction model. High-quality data sets are crucial to improving the accuracy of model predictions.

[0062] According to business needs and data characteristics, select features that are useful for the prediction model from the original data (such as equipment operating time, temperature, pressure, flow parameters, hot water system configuration, and waste heat recovery, etc.). Standardize or normalize the selected features to eliminate the dimensional differences between different features. Divide the preprocessed data set into training sets and test sets for subsequent model training and evaluation. Data preprocessing is a key step to improve model performance. Reasonable feature selection and data processing can significantly improve the prediction ability of the model.

[0063] According to the characteristics of the data and business needs, select a suitable machine learning model as the training target, such as a neural network model. According to the selected model type, build the basic framework of the model, set parameters and layer structure. The choice of model directly affects the final prediction effect. Choosing a suitable model is crucial to improving prediction accuracy.

[0064] The model is trained using the training set data, and the model parameters are optimized through multiple iterations. During the training process, the prediction performance of the model is regularly evaluated, such as using cross-validation and other methods to prevent overfitting. Model training is the core step in building a prediction model. Through continuous optimization and adjustment, the model can better fit the data and predict unknown results.

[0065] Use the test set data to evaluate the trained model and calculate the error between the predicted value and the actual value. Optimize the model based on the evaluation results, such as adjusting model parameters, changing model structure, etc. Repeat the above steps until the model performance meets business requirements.

[0066] Deploy the trained and optimized model to the control end or the corresponding computing platform. Use the deployed model to make real-time predictions on new input data to guide actual production operations. The deployment and application of the model is the key to transforming research results into actual productivity. Real-time predictions are used to guide production operations and improve production efficiency and product quality.

[0067] The monitoring unit establishes a lycopene production equipment monitoring zone, determines the lycopene production equipment within the lycopene production equipment monitoring location zone according to the location information of the lycopene production equipment, monitors the lycopene production equipment within each lycopene production equipment monitoring zone, and obtains real-time operation data and real-time waste heat data of the lycopene production equipment under operation status;

[0068] Through geographic information system (GIS) or other positioning technologies, the exact location information of lycopene production equipment, including the coordinates of the equipment, the area where it is located, and the production line, is obtained. According to the connection relationship between the various steps of the lycopene production process and the equipment, it is clear which equipment is interrelated or works together in the production process. Based on the equipment location information and the production process flow, the production equipment is divided into several monitoring zones, and each zone should contain a group of equipment with similar geographical locations, related functions, or mutual influence.

[0069] Reasonable planning of monitoring zones helps to centrally manage similar or related equipment, improve monitoring efficiency, and facilitate subsequent data analysis and parameter adjustment. Integrate the collected equipment location information with basic information such as equipment name, model, and function to form an equipment information database. Ensure that each equipment record in the equipment information database can be accurately associated with its actual location, production line, and monitoring zone.

[0070] The establishment of the equipment information database provides basic data support for the real-time data collection and subsequent analysis of the monitoring unit. According to the characteristics and monitoring requirements of the lycopene production equipment, determine the real-time operation data and waste heat data indicators that need to be collected, such as temperature, pressure, flow, waste heat emission, etc. Configure the corresponding monitoring parameters for the equipment in each monitoring zone, including monitoring frequency (such as collecting data once a minute), data collection point (such as where the temperature sensor is installed on the equipment), etc.

[0071] Necessary monitoring equipment such as temperature sensors and data collectors are deployed in each monitoring zone to ensure that the required data can be collected in real time. The collected real-time data is transmitted to the control terminal or data center via wired or wireless means and stored in real time.

[0072] a data comparison unit, receiving preset hot water system parameter information in the lycopene production process, using the prediction model of the lycopene production equipment to obtain the predicted waste heat recovery information of the hot water system in the lycopene production process, collecting the real-time waste heat recovery information of the lycopene production equipment, comparing the real-time waste heat recovery information of the lycopene production equipment with the predicted waste heat recovery information of the hot water system in the lycopene production process, and obtaining the real-time waste heat recovery error information of the hot water system in the lycopene production process;

[0073] The data comparison unit receives the preset hot water system parameter information in the lycopene production process from the background control terminal, and the parameter information includes the temperature setting value, flow setting value, operating frequency of the circulation pump, etc. of the hot water system. The preset parameter information is the basis for subsequent prediction and comparison, which reflects the expected operating status and performance of the hot water system.

[0074] The data comparison unit loads the trained lycopene production equipment utilization prediction model, which is built based on the historical operation data, system configuration information and waste heat data of the lycopene production equipment, and can predict the waste heat recovery of the hot water system under given parameters. The prediction model is the core tool of the data comparison unit, which uses historical data to simulate and predict the performance of the hot water system.

[0075] The received preset parameter information is passed as input to the prediction model, and the model calculates based on these parameters to obtain the expected waste heat recovery information of the hot water system in the lycopene production process. The prediction result reflects the amount of waste heat recovery that the hot water system should theoretically achieve under given preset parameters. The data comparison unit collects waste heat recovery information of the lycopene production equipment in real time through the monitoring end, including key indicators such as the actual waste heat recovery amount and recovery efficiency. Real-time waste heat recovery information is an important basis for evaluating the actual performance of the hot water system, which reflects the performance of the hot water system in actual operation.

[0076] The predicted waste heat recovery information is compared with the real-time collected waste heat recovery information. By calculating the difference or ratio between the two, the waste heat recovery error information of the hot water system in the real-time lycopene production process is obtained. The comparison results reveal the difference between the actual performance and the expected performance of the hot water system, providing a key basis for subsequent parameter adjustment and optimization.

[0077] The data comparison unit receives preset parameter information from the background and uses the prediction model to derive the theoretical waste heat recovery amount; at the same time, it also collects the waste heat recovery information of the equipment in real time to evaluate the actual performance of the hot water system. By comparing the prediction results with the real-time information, the data comparison unit can promptly detect deviations and problems in the operation of the hot water system and generate a detailed error report for subsequent analysis and optimization. This process not only improves the operating efficiency of the hot water system, but also helps to reduce energy waste and improve overall production performance.

[0078] The heat control unit corrects the preset parameter information of the hot water system in the lycopene production process according to the waste heat recovery error information of the hot water system in the real-time lycopene production process, and obtains the modified parameter information of the hot water system in the lycopene production process;

[0079] The heat control unit receives the waste heat recovery error information of the hot water system in the real-time lycopene production process from the data comparison unit. The error information includes the difference between the actual waste heat recovery amount and the expected waste heat recovery amount. The error information is a key indicator for evaluating the performance of the current hot water system. By comparing the actual recovery amount with the expected recovery amount, it intuitively reflects the operation deviation of the system.

[0080] The heat control unit analyzes the received error information and evaluates the specific impact of the error on the lycopene production process and hot water system performance, including analyzing the cause of the error, the scope of impact, and the potential impact on product quality and production efficiency. Error impact assessment helps the heat control unit to more accurately determine whether parameter correction is needed, as well as the urgency and importance of the correction.

[0081] Based on the results of the error impact assessment, the heat control unit determines the specific goals of parameter correction, including reducing waste heat recovery errors, improving hot water system efficiency, and optimizing energy utilization. Clarifying the goals of parameter correction is the premise and basis for subsequent adjustment work, which helps the heat control unit to adjust the preset parameters in a targeted manner.

[0082] Based on the correction target, the heat control unit adjusts the hot water system parameters in the preset lycopene production process. The parameters include the temperature setting value, flow setting value, and operating frequency of the circulation pump of the hot water system. By adjusting the preset parameters, the heat control unit improves the performance of the hot water system, reduces waste heat recovery errors, and improves overall operating efficiency.

[0083] The adjusted parameter information is applied to the hot water system in the actual lycopene production process, and the waste heat recovery of the corrected system is monitored in real time through the data monitoring unit. At the same time, the waste heat recovery data before and after the correction is compared to evaluate whether the parameter correction has achieved the expected goal. Parameter verification and feedback is that the heat control unit can timely discover the effect of parameter adjustment through real-time data monitoring and comparative analysis, providing a basis for subsequent further optimization.

[0084] The parameter adjustment optimization unit executes the modified hot water system parameter information in the lycopene production process on the equipment side to recover the waste heat in the lycopene production process. The waste heat discharged from the extraction heat exchanger and the separation heat exchanger is introduced into the preheating device and the hot water storage tank through a circulation pump. The recovered waste heat is used to preheat the raw materials and maintain the temperature of the hot water system in the lycopene production process.

[0085] After receiving the parameter adjustment instruction from the control end, the device side first parses the instruction to clarify the hot water system parameter information that needs to be adjusted, such as temperature setting value, flow setting value, etc. Based on the parameter information obtained by parsing, the device side adjusts the corresponding parameters of the hot water system. For example, adjust the operating frequency of the hot water circulation pump to change the water flow, or adjust the power of the heating element to change the water temperature. The waste heat recovery efficiency can be improved through parameter adjustment.

[0086] The equipment side uses sensors to monitor the working status of the extraction heat exchanger and the separation heat exchanger in real time, especially their waste heat discharge. When waste heat discharge is detected, the equipment side prepares to perform waste heat recovery operations. Real-time monitoring is the key to ensure that waste heat can be recovered and effectively utilized in a timely manner to avoid energy waste.

[0087] When waste heat is detected, the equipment automatically starts the circulation pump to introduce the waste heat discharged from the extraction heat exchanger and the separation heat exchanger into the preheating device and the hot water storage tank through the pipeline. The circulation pump enables the waste heat to be smoothly transferred and used in other production links.

[0088] The waste heat introduced into the preheating unit is used to preheat the raw materials entering the production process, such as tomato skins or other extract raw materials, to increase their initial temperature and thus accelerate the subsequent processing process. The use of waste heat in the preheating unit not only reduces energy consumption, but also improves the efficiency of raw material processing.

[0089] The waste heat introduced into the hot water storage tank is stored and used to maintain the temperature of the hot water system in the lycopene production process. When the system needs to add heat, hot water can be directly drawn from the hot water storage tank. The hot water storage tank acts as a thermal energy buffer device to ensure that the hot water system can maintain a stable operating temperature under different working conditions.

[0090] The equipment side monitors the waste heat recovery effect in real time through sensors, including key indicators such as recovery volume and recovery efficiency, and feeds these data back to the control side. Real-time monitoring helps evaluate the actual performance of the waste heat recovery system and provides a basis for subsequent parameter adjustment and optimization.

[0091] Based on the real-time monitoring of waste heat recovery effect data, the control end conducts evaluation and analysis, and further adjusts the hot water system parameters or optimizes the waste heat recovery process as needed. This process may be iterative until the optimal waste heat recovery efficiency and system stability are achieved. Through continuous adjustment and optimization, the maximum utilization of waste heat resources can be achieved.

[0092] The parameter adjustment optimization unit receives and analyzes the parameter adjustment instructions from the control end, adjusts the operating parameters of the hot water system, monitors and recovers the waste heat discharged from the extraction heat exchanger and the separation heat exchanger in real time, and uses it to preheat the raw materials and maintain the system temperature. Through this process, not only the effective utilization of waste heat resources is achieved, but also the energy efficiency and production performance of the entire lycopene production process are improved. At the same time, by real-time monitoring and evaluation of the waste heat recovery effect, the system can be further iterated and optimized to achieve more efficient waste heat recovery and utilization.

[0093] Specifically, the hot water system and the acquisition unit in the lycopene production process provided by the present invention include:

[0094] Preprocessing the historical operation data of the lycopene production equipment, the hot water system configuration information in the historical lycopene production process, and the historical waste heat data to obtain a preprocessed data set, and dividing the preprocessed data set into a training set and a test set;

[0095] Analyze historical operation data, hot water system configuration information and waste heat data to determine the waste heat prediction characteristics of the lycopene production equipment, which include the equipment's operating time, temperature, pressure, flow parameters, as well as the hot water system's configuration and waste heat recovery;

[0096] Select a neural network model as a training model, and use the training set data to train the neural network model;

[0097] The trained model is evaluated using the test set data. The prediction ability of the model is evaluated by calculating the error between the predicted value and the actual value. The prediction model for waste heat utilization of lycopene production equipment is obtained, and the trained prediction model for waste heat utilization of lycopene production equipment is deployed to the control end.

[0098] The control end uses the deployed model to make real-time predictions on the waste heat utilization of the lycopene production equipment and dynamically adjusts the parameters of the hot water system based on the waste heat prediction results.

[0099] Specifically, the hot water system and monitoring unit in the lycopene production process provided by the present invention include:

[0100] Obtaining location information of lycopene production equipment, where the location information of lycopene production equipment includes coordinates of the equipment, the area where it is located, and the production line;

[0101] Associating the collected device location information with the device name to obtain a device information database;

[0102] According to the lycopene production process steps and the connection relationship between the equipment, the production equipment is divided into several monitoring zones. The control end uses the location information of the equipment to configure the corresponding monitoring parameters for each monitoring zone, including the monitoring frequency and data collection points.

[0103] The control end collects the operation data and waste heat data of the lycopene production equipment in each monitoring zone in real time through the monitoring end.

[0104] Specifically, the hot water system and data comparison unit in the lycopene production process provided by the present invention include:

[0105] The control end loads the trained lycopene production equipment utilization prediction model;

[0106] The received preset hot water system parameter information is used as input and transmitted to the prediction model of the lycopene production equipment, and the prediction model performs calculations based on the input parameter information to obtain the predicted waste heat recovery information of the hot water system in the lycopene production process;

[0107] The estimated waste heat recovery amount is extracted from the prediction model and the prediction results are stored in the database of the control end.

[0108] Specifically, the hot water system and heat control unit in the lycopene production process provided by the present invention include:

[0109] The data comparison unit receives waste heat recovery error information, wherein the waste heat recovery error information includes a difference between an actual waste heat recovery amount and an expected waste heat recovery amount;

[0110] Evaluate the impact of errors on the lycopene production process and hot water system performance, determine whether parameter correction is needed, and obtain error analysis results;

[0111] According to the error analysis result, the parameter correction target is determined, and the preset hot water system parameter information in the lycopene production process is adjusted to obtain the modified hot water system parameter information in the lycopene production process;

[0112] The modified hot water system parameter information in the lycopene production process is applied to the hot water system in the actual lycopene production process. The waste heat recovery of the hot water system after correction is monitored in real time through the data monitoring unit. The waste heat recovery data before and after correction are compared to evaluate whether the parameter information of the hot water system in the lycopene production process after the parameter modification reaches the expected target.

[0113] Specifically, the hot water system and parameter adjustment optimization unit in the lycopene production process provided by the present invention include:

[0114] The device receives the parameter adjustment instruction from the control end and analyzes it. According to the parameter information in the instruction, the device adjusts the temperature setting value and flow setting value of the hot water system;

[0115] The equipment side monitors the waste heat information discharged by the extraction heat exchanger and the separation heat exchanger in real time through sensors. When waste heat is detected, the equipment side automatically starts the circulation pump to introduce the waste heat into the preheating device and the hot water storage tank through the pipeline;

[0116] The waste heat is introduced into the preheating device to preheat the raw materials entering the production process and increase the initial temperature of the raw materials;

[0117] At the same time, waste heat is also introduced into the hot water storage tank for storage to maintain the temperature of the hot water system in the lycopene production process. The equipment end monitors the waste heat recovery effect in real time through sensors, including the recovery amount and recovery efficiency, and feeds back the monitored waste heat recovery effect data to the control end.

[0118] Specifically, the hot water system and parameter adjustment optimization unit in the lycopene production process provided by the present invention include:

[0119] The lycopene production equipment is encoded using the parameters of the prediction model, and each parameter of the model is mapped to a gene in the chromosome;

[0120] The fitness function is set to evaluate the quality of each individual. The fitness function is a quantitative indicator of prediction accuracy.

[0121] A certain number of individuals are randomly generated as the initial population, each of which represents a set of parameter combinations of the prediction model used by the lycopene production equipment as the search starting point of the genetic algorithm;

[0122] Perform selection, crossover and mutation operations on the initial population to generate a new population. In each generation, the fitness of each individual is evaluated, and individuals with higher fitness are selected for reproduction in the next generation.

[0123] Repeat the iterative process of the genetic algorithm until the stopping condition is met or the maximum number of iterations is reached and the fitness reaches the preset threshold;

[0124] After the iteration of the genetic algorithm, the individual with the highest fitness is selected as the optimal solution, which represents the best combination of the parameters of the lycopene production equipment utilization prediction model:

[0125] The parameters in the optimal individuals are used to update the prediction model of lycopene production equipment, and the optimal parameter combination is applied to the model.

[0126] The technical solution of the present invention solves the problem that it is difficult to make statistical calculations on the waste heat recovery efficiency, which results in the inability to fully utilize the recovered waste heat in the lycopene production process:

[0127] The present invention constructs a waste heat utilization prediction model for lycopene production equipment by acquiring historical operation data, hot water system configuration information and historical waste heat data of the lycopene production equipment. The waste heat utilization prediction model for lycopene production equipment can predict the waste heat recovery amount based on historical data, providing a basis for subsequent parameter adjustment.

[0128] The present invention establishes lycopene production equipment monitoring partitions through monitoring units, and collects the operating data and waste heat data of each device in real time. This method ensures the real-time and accuracy of the data, and provides a reliable data source for the statistics of waste heat recovery efficiency. The estimated waste heat recovery amount obtained by the prediction model is compared with the waste heat recovery amount collected in real time, and the waste heat recovery error information is calculated, which helps to timely discover deviations in the waste heat recovery process and provide direction for subsequent regulation.

[0129] According to the waste heat recovery error information, the heat control unit dynamically adjusts the preset hot water system parameters to reduce errors and improve waste heat recovery efficiency. The dynamic adjustment mechanism ensures that the hot water system can maintain a high waste heat recovery efficiency under different working conditions. Through the parameter adjustment optimization unit, the waste heat discharged from the extraction heat exchanger and the separation heat exchanger is introduced into the preheating device and the hot water storage tank to preheat the raw materials and maintain the temperature of the hot water system. The waste heat recovery method not only reduces energy waste, but also improves energy efficiency in the production process. The prediction model is optimized through genetic algorithms to improve the prediction accuracy of the model. This helps to more accurately predict the amount of waste heat recovery and provide a more scientific basis for parameter control of the hot water system, thereby further improving the waste heat recovery efficiency.

[0130] In summary, the technical solution of the present invention effectively solves the problem of statistical difficulties in waste heat recovery efficiency through the comprehensive effects of multiple links such as constructing a prediction model, real-time monitoring and data collection, data comparison and error analysis, dynamic parameter control, waste heat recovery and utilization, and optimization algorithm application, and significantly improves the recovery and utilization efficiency of waste heat in the lycopene production process.

[0131] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations, and the above-described embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention.

Claims

1. A hot water system in a lycopene production process, characterized in that: include: The equipment end, the monitoring end, the control end and the background control end establish communication connections with the equipment end, the monitoring end and the background control end. The control end receives and analyzes the hot water system parameter information in the preset lycopene production process of the background control end and the lycopene production equipment temperature data collected by the monitoring end to obtain the modified hot water system parameter information in the lycopene production process. The equipment end executes the modified hot water system parameter information in the lycopene production process. The control end includes: an acquisition unit, for acquiring historical operation data of a lycopene production equipment, configuration information of a hot water system in a historical lycopene production process, and historical waste heat data, wherein the lycopene production equipment includes a hot water storage tank, a hot water storage tank pump, a hot water atmospheric pressure boiler, a hot water circulation pump, an extraction heat exchanger, a separation heat exchanger, an extraction kettle, and a separation kettle, and constructing a waste heat utilization prediction model for the lycopene production equipment according to the historical operation data of the lycopene production equipment, configuration information of a hot water system in a historical lycopene production process, and historical waste heat data; The monitoring unit establishes a lycopene production equipment monitoring zone, determines the lycopene production equipment within the lycopene production equipment monitoring location zone according to the location information of the lycopene production equipment, monitors the lycopene production equipment within each lycopene production equipment monitoring zone, and obtains real-time operation data and real-time waste heat data of the lycopene production equipment under operation status; a data comparison unit, receiving preset hot water system parameter information in the lycopene production process, using the prediction model of the lycopene production equipment to obtain the predicted waste heat recovery information of the hot water system in the lycopene production process, collecting the real-time waste heat recovery information of the lycopene production equipment, comparing the real-time waste heat recovery information of the lycopene production equipment with the predicted waste heat recovery information of the hot water system in the lycopene production process, and obtaining the real-time waste heat recovery error information of the hot water system in the lycopene production process; The heat control unit corrects the preset parameter information of the hot water system in the lycopene production process according to the waste heat recovery error information of the hot water system in the real-time lycopene production process, and obtains the modified parameter information of the hot water system in the lycopene production process; The parameter adjustment optimization unit executes the modified hot water system parameter information in the lycopene production process on the equipment side to recover the waste heat in the lycopene production process. The waste heat discharged from the extraction heat exchanger and the separation heat exchanger is introduced into the preheating device and the hot water storage tank through a circulation pump. The recovered waste heat is used to preheat the raw materials and maintain the temperature of the hot water system in the lycopene production process.

2. The hot water system in the lycopene production process according to claim 1, characterized in that: Get unit, including: Preprocessing the historical operation data of the lycopene production equipment, the hot water system configuration information in the historical lycopene production process, and the historical waste heat data to obtain a preprocessed data set, and dividing the preprocessed data set into a training set and a test set; Analyze historical operation data, hot water system configuration information and waste heat data to determine the waste heat prediction characteristics of the lycopene production equipment, which include the equipment's operating time, temperature, pressure, flow parameters, as well as the hot water system's configuration and waste heat recovery; Select a neural network model as a training model, and use the training set data to train the neural network model; The trained model is evaluated using the test set data. The prediction ability of the model is evaluated by calculating the error between the predicted value and the actual value. The prediction model for waste heat utilization of lycopene production equipment is obtained, and the trained prediction model for waste heat utilization of lycopene production equipment is deployed to the control end. The control end uses the deployed model to make real-time predictions on the waste heat utilization of the lycopene production equipment and dynamically adjusts the parameters of the hot water system based on the waste heat prediction results.

3. The hot water system in the lycopene production process according to claim 1, characterized in that: Monitoring unit, including: Obtaining location information of lycopene production equipment, where the location information of lycopene production equipment includes coordinates of the equipment, the area where it is located, and the production line; Associating the collected device location information with the device name to obtain a device information database; According to the lycopene production process steps and the connection relationship between the equipment, the production equipment is divided into several monitoring zones. The control end uses the location information of the equipment to configure the corresponding monitoring parameters for each monitoring zone, including the monitoring frequency and data collection points. The control end collects the operation data and waste heat data of the lycopene production equipment in each monitoring zone in real time through the monitoring end.

4. The hot water system in the lycopene production process according to claim 1, characterized in that: Data comparison unit, including: The control end loads the trained lycopene production equipment utilization prediction model; The received preset hot water system parameter information is used as input and transmitted to the prediction model of the lycopene production equipment, and the prediction model performs calculations based on the input parameter information to obtain the predicted waste heat recovery information of the hot water system in the lycopene production process; The estimated waste heat recovery amount is extracted from the prediction model and the prediction results are stored in the database of the control end.

5. The hot water system in the lycopene production process according to claim 1, characterized in that: Heat control unit, comprising: The data comparison unit receives waste heat recovery error information, wherein the waste heat recovery error information includes a difference between an actual waste heat recovery amount and an expected waste heat recovery amount; Evaluate the impact of errors on the lycopene production process and hot water system performance, determine whether parameter correction is needed, and obtain error analysis results; According to the error analysis result, the parameter correction target is determined, and the preset hot water system parameter information in the lycopene production process is adjusted to obtain the modified hot water system parameter information in the lycopene production process; The modified hot water system parameter information in the lycopene production process is applied to the hot water system in the actual lycopene production process. The waste heat recovery of the hot water system after correction is monitored in real time through the data monitoring unit. The waste heat recovery data before and after correction are compared to evaluate whether the parameter information of the hot water system in the lycopene production process after the parameter modification reaches the expected target.

6. The hot water system in the lycopene production process according to claim 1, characterized in that: Parameter adjustment and optimization unit, including: The device receives the parameter adjustment instruction from the control end and analyzes it. According to the parameter information in the instruction, the device adjusts the temperature setting value and flow setting value of the hot water system; The equipment side monitors the waste heat information discharged by the extraction heat exchanger and the separation heat exchanger in real time through sensors. When waste heat is detected, the equipment side automatically starts the circulation pump to introduce the waste heat into the preheating device and the hot water storage tank through the pipeline; The waste heat is introduced into the preheating device to preheat the raw materials entering the production process and increase the initial temperature of the raw materials; At the same time, waste heat is also introduced into the hot water storage tank for storage to maintain the temperature of the hot water system in the lycopene production process. The equipment end monitors the waste heat recovery effect in real time through sensors, including the recovery amount and recovery efficiency, and feeds back the monitored waste heat recovery effect data to the control end.

7. The hot water system in the lycopene production process according to claim 1, characterized in that: Parameter adjustment and optimization unit, including: The lycopene production equipment is encoded using the parameters of the prediction model, and each parameter of the model is mapped to a gene in the chromosome; The fitness function is set to evaluate the quality of each individual. The fitness function is a quantitative indicator of prediction accuracy. A certain number of individuals are randomly generated as the initial population, each of which represents a set of parameter combinations of the prediction model used by the lycopene production equipment as the search starting point of the genetic algorithm; Perform selection, crossover and mutation operations on the initial population to generate a new population. In each generation, the fitness of each individual is evaluated, and individuals with higher fitness are selected for reproduction in the next generation. Repeat the iterative process of the genetic algorithm until the stopping condition is met or the maximum number of iterations is reached and the fitness reaches the preset threshold; After the iteration of the genetic algorithm, the individual with the highest fitness is selected as the optimal solution, which represents the best combination of the parameters of the prediction model for lycopene production equipment: The parameters in the optimal individuals are used to update the prediction model of lycopene production equipment, and the optimal parameter combination is applied to the model.

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