Intelligent control method and system for tea oil production and processing

Abstract

The invention discloses an intelligent control method and system for tea oil production and processing, and relates to the technical field of intelligent control. During operation of the system, key quality parameters of tea seed raw materials entering a production line are collected in real time by deploying a plurality of analyzers and serve as a first data set; various technological parameters in the production process are monitored in real time by deploying a plurality of sensors to serve as a second data set, refined tea oil finished products are subjected to quality detection to serve as a third data set, the first data set, the second data set and the third data set are subjected to filtering, denoising and standardization treatment, and intelligent algorithm calculation and analysis are utilized to obtain the refined tea oil finished product. And obtaining a production and processing quality index Cyzl, comparing the production and processing quality index Cyzl with a preset first qualified threshold value M and a preset second qualified threshold value N, automatically evaluating the comprehensive quality level of the tea oil product, and implementing an intelligent optimization control strategy based on the output of the data analysis module and the quality evaluation module.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method and system for tea oil production and processing. Background Art

[0002] Tea oil is a natural plant oil extracted from the seeds of the Camellia family. It has excellent antioxidant and moisturizing properties and is widely used in food, medicine and cosmetics. With the advancement of modern technology and the increasing demand for natural cosmetics, tea oil is increasingly used in cosmetics and skin care products. For example, tea oil is often used in the formulation of cosmetics such as skin care oils, creams, lotions and essences to moisturize, resist oxidation and soothe the skin.

[0003] In the traditional tea oil production process, manual experience is often relied on to adjust and monitor the production process, which has problems such as low production efficiency, unstable product quality, and frequent manual intervention. Since multiple factors in the production process (such as raw material quality, process parameters, and environmental conditions, etc.) will affect the quality of the final product, it is difficult for traditional methods to achieve real-time data analysis and optimization control, resulting in tea oil being difficult to meet the high standards of the cosmetics and skin care industry in terms of ingredient content, acid value, color, and oxidative stability. In the existing tea oil production process, due to the inability to achieve fine process control, the quality of tea oil products fluctuates greatly, and the production efficiency is low, which often leads to a series of abnormal situations. For example, when the raw material quality fluctuates greatly, the pressing and refining parameters are not adjusted in time, resulting in excessive acid value of the finished product, color deviation, and even the problem of increased oxidation; or the production equipment is not effectively predictively maintained, and sudden equipment failures cause production interruptions, affecting the stability of the entire supply chain. The occurrence of such problems not only affects the quality and consistency of the product, but also increases production costs and time, causing economic losses to the company. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent control method and system for tea oil production and processing, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent control system for tea oil production and processing, including a raw material data acquisition module, a production process parameter acquisition module, a finished product quality monitoring module, a data analysis module, a quality assessment module and an intelligent optimization control module;

[0006] The raw material data acquisition module is used to deploy a number of analyzers to collect key quality parameters of tea seed raw materials entering the production line in real time as a first data group, and send the data to the central control system for storage and preliminary analysis;

[0007] The production process parameter acquisition module is used to monitor various process parameters in the production process in real time by deploying a number of sensors as a second data group, and upload the data to the central control system;

[0008] The finished product quality monitoring module is used to perform quality inspection on the refined tea oil finished product through an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and transmit the data to the central control system in real time as a third data group;

[0009] The data analysis module is used to filter, denoise and standardize the first data group, the second data group and the third data group received by the central control system, calculate and analyze the collected raw material data, production process data and finished product quality data using an intelligent algorithm, obtain: production and processing quality index Cyzl, and feed back the calculation results to the central control system;

[0010] The quality assessment module is used to interpret the calculation results output by the data analysis module, automatically assess the comprehensive quality level of the tea oil product by comparing the production and processing quality index Cyzl with the preset first qualified threshold M and second qualified threshold N, and generate an assessment grade strategy;

[0011] The intelligent optimization control module is used to implement intelligent optimization control strategies based on the outputs of the data analysis module and the quality assessment module. The system will automatically adjust the operating parameters of the production equipment, continuously monitor the status of the entire production line, and perform predictive maintenance.

[0012] Preferably, the raw material data acquisition module includes a raw material quality analysis unit;

[0013] The raw material quality analysis unit is used to collect key quality parameters of tea seed raw materials entering the production line in real time by deploying a nuclear magnetic resonance analyzer, an infrared moisture analyzer, a spectrometer and an image recognition system, automatically collect the oil content OCR, impurity content IC, moisture content MC, seed integrity SI and acid value data AV of the tea seeds as the first data group, and send the data to the central control system for storage and preliminary analysis.

[0014] Preferably, the production process parameter acquisition module includes a production process analysis unit;

[0015] The production process analysis unit deploys thermocouple temperature sensors, pressure sensors, time controllers, temperature controllers and rotary encoders to monitor various process parameters in the production process in real time, including pressing temperature PT, pressing pressure PP, extraction time ET, refining temperature RT and stirring speed SS as the second data group, and uploads the data to the central control system.

[0016] Preferably, the finished product quality monitoring module includes a finished product quality analysis unit;

[0017] The finished product quality analysis unit is used to perform quality inspection on the refined tea oil product through an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and to monitor and record the acid value Ac, peroxide value PV, color index CI, viscosity VIS and redox potential RP in real time as the third data group, and transmit the data to the central control system in real time.

[0018] Preferably, the data analysis module includes a data preprocessing unit and a data calculation unit;

[0019] The data preprocessing unit is used to remove abnormal values ​​and incomplete data from the first data group, the second data group and the third data group, clean up the collected data by setting data filtering rules and statistical methods, use signal processing algorithms to denoise the collected raw material, process and finished product data, and convert the processed data into a standardized format through normalization.

[0020] Preferably, the data calculation unit is used to analyze the processed first data group, second data group and third data group based on the use of multiple regression, neural network or support vector machine algorithm to calculate the production and processing quality index Cyzl, raw material quality coefficient Rmql, production process control coefficient Pcc and finished product quality coefficient Fpql;

[0021] Preferably, the quality assessment module includes a quality assessment unit and a comprehensive report generation unit;

[0022] The quality assessment unit is used to compare and analyze the production and processing quality index Cyzl with the preset first qualified threshold value M and second qualified threshold value N, analyze whether the tea oil product meets the qualified standard, automatically generate the corresponding assessment level, and automatically generate a risk warning signal to prompt that the corresponding corrective measures need to be taken immediately;

[0023] When the production and processing quality index Cyzl ≥ the second qualified threshold N, the tea oil product reaches the first level, indicating that the quality of the raw materials, production process and finished products is more than 20% higher than the qualified standard and no further adjustment is required;

[0024] When the first qualified threshold value M≤production and processing quality index Cyzl<second qualified threshold value N, the tea oil product reaches the second level, indicating that the product meets the quality requirements, but there is a gap with the first level, and the production batch is classified as a "qualified" batch;

[0025] When the production and processing quality index Cyzl<the first qualified threshold M, the tea oil product does not reach the qualified grade and there are quality problems. Immediate improvement measures need to be taken. The production batch should be classified as a "needs improvement" batch and the sales and circulation of the batch should be suspended.

[0026] Preferably, the comprehensive report generating unit is used to integrate the evaluation results and strategies into a quality evaluation report, the report content includes quality level, improvement suggestions, potential risks and early warning information, and is automatically sent to the production management system.

[0027] Preferably, the intelligent optimization control module includes a parameter optimization unit and a predictive maintenance unit;

[0028] The parameter optimization unit is used to receive the key production parameters output by the data analysis module and the evaluation level of the quality evaluation module according to the calculation result of the production and processing quality index Cyzl, send instructions to the production equipment control system in real time, and dynamically adjust the parameters, including pressing temperature, pressing pressure and refining time;

[0029] The predictive maintenance unit is used to continuously monitor the operating status of production line equipment, collect equipment operating status data in real time, identify potential failure risks by analyzing equipment operating data and failure history data, collect equipment operating status data in real time, and take maintenance measures in advance.

[0030] A tea oil production and processing intelligent control method comprises the following steps:

[0031] Step 1: By deploying several analyzers, key quality parameters of tea seed raw materials entering the production line are collected in real time as the first data set, and the data are sent to the central control system for storage and preliminary analysis;

[0032] Step 2: Deploy several sensors to monitor various process parameters in the production process in real time as the second data set, and upload the data to the central control system;

[0033] Step 3: The refined tea oil product is tested for quality by using an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and the data is instantly transmitted to the central control system as the third data group;

[0034] Step 4: Filter, denoise and standardize the first data group, the second data group and the third data group received by the central control system, calculate and analyze the collected raw material data, production process data and finished product quality data using an intelligent algorithm to obtain: the production and processing quality index Cyzl, and feed back the calculation results to the central control system;

[0035] Step 5: interpret the calculation results output by the data analysis module, compare the production and processing quality index Cyzl with the preset first qualified threshold M and second qualified threshold N, automatically evaluate the comprehensive quality level of the tea oil product, and generate an evaluation grade strategy;

[0036] Step 6: Based on the output of the data analysis module and the quality assessment module, the intelligent optimization control strategy is implemented. The system will automatically adjust the operating parameters of the production equipment, continuously monitor the status of the entire production line, and perform predictive maintenance.

[0037] The present invention provides a tea oil production and processing intelligent control method and system, which has the following beneficial effects:

[0038] (1) When the system is running, by deploying several analyzers, the key quality parameters of the tea seed raw materials entering the production line are collected in real time as the first data group. By deploying several sensors, the various process parameters in the production process are monitored in real time. As the second data group, the quality of the refined tea oil product is tested. As the third data group, the first data group, the second data group and the third data group are filtered, denoised and standardized, and the intelligent algorithm is used to calculate and analyze to obtain: the production and processing quality index Cyzl. By comparing the production and processing quality index Cyzl with the preset first qualified threshold M and second qualified threshold N, the comprehensive quality level of the tea oil product is automatically evaluated. Based on the output of the data analysis module and the quality evaluation module, the intelligent optimization control strategy is implemented.

[0039] (2) The tea oil production and processing intelligent control system consists of six modules: raw material data acquisition module, production process parameter acquisition module, finished product quality monitoring module, data analysis module, quality assessment module and intelligent optimization control module. Through the collaborative work of these modules, the system can fully realize the real-time monitoring and data acquisition of tea seed raw materials, production process and finished products, use advanced data analysis algorithms to filter, denoise and standardize data at different stages, obtain the production and processing quality index, and automatically evaluate the quality level of tea oil products based on this index. The system finally generates a comprehensive evaluation report and implements intelligent production control strategies based on the evaluation results, thereby completing the intelligent monitoring, optimization and management tasks of the entire tea oil production process.

[0040] (3) Compared with traditional tea oil production technology, this intelligent control system has significantly improved the degree of automation and refinement in data collection, analysis and optimization. Traditional methods often rely on manual experience and manual adjustments, and it is difficult to respond to changes in the production process in a timely manner, resulting in unstable product quality and low production efficiency. In contrast, this system uses a variety of advanced sensors and analytical instruments to achieve real-time data collection and transmission of the entire process from raw materials to finished products; by introducing intelligent algorithms such as multivariate regression and neural networks, the system can accurately analyze and dynamically adjust the key factors affecting the quality of tea oil. Compared with current technical means, this system significantly reduces manual intervention, improves the level of automation and intelligence in production, and reduces the risk of product quality fluctuations.

[0041] (4) Through the comprehensive application of multi-source data analysis, intelligent algorithms and optimization control strategies, the intelligent control system for tea oil production and processing has significantly improved production efficiency, product quality and economic benefits. The system realizes refined control and predictive maintenance of the entire production process, effectively avoiding problems such as production interruptions and quality fluctuations, thereby ensuring the continuous and stable operation of the production line. The system not only brings significant results in improving product consistency and stability, but also reduces resource waste and energy consumption by optimizing production parameters, further reducing production costs. Overall, the intelligent control system provides an advanced solution for tea oil production and processing, enabling tea oil to better meet the high quality standards in the field of cosmetics and skin care products, while enhancing the competitiveness of enterprises in the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a block diagram of an intelligent control system for tea oil production and processing according to the present invention;

[0043] Figure 2 This is a schematic diagram of the steps of an intelligent control method for tea oil production and processing according to the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Example 1

[0046] The present invention provides an intelligent control system for tea oil production and processing. Figure 1 , including raw material data acquisition module, production process parameter acquisition module, finished product quality monitoring module, data analysis module, quality assessment module and intelligent optimization control module;

[0047] The raw material data acquisition module is used to deploy a number of analyzers to collect key quality parameters of tea seed raw materials entering the production line in real time as a first data group, and send the data to the central control system for storage and preliminary analysis;

[0048] The production process parameter acquisition module is used to monitor various process parameters in the production process in real time by deploying a number of sensors as a second data group, and upload the data to the central control system;

[0049] The finished product quality monitoring module is used to perform quality inspection on the refined tea oil finished product through an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and transmit the data to the central control system in real time as a third data group;

[0050] The data analysis module is used to filter, denoise and standardize the first data group, the second data group and the third data group received by the central control system, calculate and analyze the collected raw material data, production process data and finished product quality data using an intelligent algorithm, obtain: production and processing quality index Cyzl, and feed back the calculation results to the central control system;

[0051] The quality assessment module is used to interpret the calculation results output by the data analysis module, automatically assess the comprehensive quality level of the tea oil product by comparing the production and processing quality index Cyzl with the preset first qualified threshold M and second qualified threshold N, and generate an assessment grade strategy;

[0052] The intelligent optimization control module is used to implement intelligent optimization control strategies based on the outputs of the data analysis module and the quality assessment module. The system will automatically adjust the operating parameters of the production equipment, continuously monitor the status of the entire production line, and perform predictive maintenance.

[0053] In this embodiment, by deploying several analyzers, key quality parameters of tea seed raw materials entering the production line are collected in real time. As the first data group, by deploying several sensors, various process parameters in the production process are monitored in real time. As the second data group, the refined tea oil product is quality tested by an automatic titrator, a redox potentiometer, a colorimeter and a viscometer. As the third data group, the first data group, the second data group and the third data group are filtered, denoised and standardized, and calculated and analyzed using intelligent algorithms to obtain: the production and processing quality index Cyzl, by comparing the production and processing quality index Cyzl with the preset first qualified threshold M and the second qualified threshold N, the comprehensive quality level of the tea oil product is automatically evaluated, and an evaluation grade strategy is generated. Based on the output of the data analysis module and the quality evaluation module, an intelligent optimization control strategy is implemented. The system will automatically adjust the operating parameters of the production equipment, continuously monitor the status of the entire production line, and perform predictive maintenance.

[0054] Example 2

[0055] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the raw material data acquisition module includes a raw material quality analysis unit;

[0056] The raw material quality analysis unit is used to collect key quality parameters of tea seed raw materials entering the production line in real time by deploying a nuclear magnetic resonance analyzer, an infrared moisture analyzer, a spectrometer and an image recognition system, automatically collect the oil content OCR, impurity content IC, moisture content MC, seed integrity SI and acid value data AV of the tea seeds as the first data group, and send the data to the central control system for storage and preliminary analysis.

[0057] The production process parameter acquisition module includes a production process analysis unit;

[0058] The production process analysis unit deploys thermocouple temperature sensors, pressure sensors, time controllers, temperature controllers and rotary encoders to monitor various process parameters in the production process in real time, including pressing temperature PT, pressing pressure PP, extraction time ET, refining temperature RT and stirring speed SS as the second data group, and uploads the data to the central control system.

[0059] The finished product quality monitoring module includes a finished product quality analysis unit;

[0060] The finished product quality analysis unit is used to perform quality inspection on the refined tea oil product through an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and to monitor and record the acid value Ac, peroxide value PV, color index CI, viscosity VIS and redox potential RP in real time as the third data group, and transmit the data to the central control system in real time.

[0061] In this implementation, through the synergy of the raw material quality analysis unit, the production process analysis unit and the finished product quality analysis unit, the tea oil production and processing intelligent control system realizes comprehensive real-time monitoring of raw materials, production processes and finished products. The raw material quality analysis unit uses a nuclear magnetic resonance analyzer, an infrared moisture analyzer, a spectrometer and an image recognition system to accurately collect the key quality parameters of tea seeds (such as oil content OCR, impurity content IC, etc.) to ensure the consistency of the quality of raw materials entering the production line. The various sensors deployed by the production process analysis unit monitor the key process parameters in the production process in real time to ensure process stability and precise parameter control. The finished product quality analysis unit uses a variety of high-precision instruments to monitor and record the quality parameters of the finished product (such as acid value Ac, peroxide value PV, etc.) in real time, ensuring the high quality level of the final product. This all-round data collection and monitoring system greatly enhances the system's ability to control the entire production process, reduces data deviation and error rate, and ensures the accuracy and reliability of the data.

[0062] Example 3

[0063] This embodiment is explained in Example 1, please refer to Figure 1,Specifically: the data analysis module includes a data preprocessing unit and a data calculation unit;

[0064] The data preprocessing unit is used to remove abnormal values ​​and incomplete data from the first data group, the second data group and the third data group, clean the collected data by setting data filtering rules and statistical methods, use signal processing algorithms to perform denoising on the collected raw material, process and finished product data, and convert the processed data into a standardized format by normalization;

[0065] The data calculation unit is used to analyze the processed first data group, second data group and third data group based on the use of multiple regression, neural network or support vector machine algorithm to calculate the production and processing quality index Cyzl, raw material quality coefficient Rmql, production process control coefficient Pcc and finished product quality coefficient Fpql;

[0066] The production and processing quality index Cyzl is calculated by the following formula:

[0067] Cyzl=R 1 *Rmql+R 2 *Pcc+R 3 *Fpql;

[0068] In the formula, Cyzl represents the production and processing quality index, Rmql represents the raw material quality coefficient, Pcc represents the production process control coefficient, Fpql represents the finished product quality coefficient, R 1 , R 2 and R 3 They represent the proportional coefficients of the raw material quality coefficient Rmql, the production process control coefficient Pcc and the finished product quality coefficient Fpql respectively;

[0069] The raw material quality coefficient Rmql is calculated by the following formula:

[0070]

[0071] In the formula, OCR represents oil content, IC represents impurity content, MC represents moisture content, SI represents grain integrity, AV represents acid value data, and MC represents ideal Indicates the ideal moisture value, OCR max 、IC max , MC max and AV max Respectively represent the maximum value of each parameter, OCR min 、IC min and MC min Respectively represent the minimum value of each parameter, w 1 、w 2 、w 3 、w4 and w 5 They respectively represent the proportional coefficients of oil content OCR, impurity content IC, moisture content MC, grain integrity SI and acid value data AV.

[0072] The production process control coefficient Pcc is calculated by the following formula:

[0073]

[0074] In the formula, PT represents the pressing temperature, PP represents the pressing pressure, ET represents the extraction time, RT represents the refining temperature, SS represents the stirring speed, and PT represents the ideal PP ideal , RT ideal and SS ideal represents the ideal value of each parameter, σPT, σPP, σRT and σSS represent the tolerance range of each parameter, γ represents the index of the nonlinear influencing factor controlling the extraction time, k 1 , k 2 , k 3 , k 4 and k 5 They represent the proportionality coefficients of pressing temperature PT, pressing pressure PP, extraction time ET, refining temperature RT and stirring speed SS respectively.

[0075] The finished product quality coefficient Fpql is calculated by the following formula:

[0076]

[0077] In the formula, AC represents acid value, PV represents peroxide value, CI represents color index, VIS represents viscosity, RP represents redox potential, AC represents max PV max RP max 、VIS range , CI ideal 、VIS ideal Represent the maximum value and ideal value of each parameter respectively, α represents the slope factor of the effect of adjusting the color index on the result, and m 1 、m 2 、m 3 、m 4 and m 5 They represent the proportional coefficients of acid value AC, peroxide value PV, color index CI, viscosity VIS and redox potential RP respectively.

[0078] In the present embodiment, the data preprocessing unit in the data analysis module cleans the three sets of data collected from the raw materials, the production process and the finished product by setting data filtering rules and statistical methods, and removes abnormal values ​​and incomplete data. The data is denoised using a signal processing algorithm, and the processed data is converted into a standardized format by normalization. This can significantly improve the quality and consistency of the data, and lay a solid foundation for subsequent data calculation and analysis. Compared with the traditional simple data screening method, this preprocessing step is more refined, can effectively remove noise and interference, and makes the subsequent calculation and analysis results more reliable, further improving the ability to accurately control the production process and product quality.

[0079] Example 4

[0080] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the quality assessment module includes a quality assessment unit and a comprehensive report generating unit;

[0081] The quality assessment unit is used to compare and analyze the production and processing quality index Cyzl with the preset first qualified threshold value M and second qualified threshold value N, analyze whether the tea oil product meets the qualified standard, automatically generate the corresponding assessment level, and automatically generate a risk warning signal to prompt that the corresponding corrective measures need to be taken immediately;

[0082] When the production and processing quality index Cyzl ≥ the second qualified threshold N, the tea oil product reaches the first level, indicating that the quality of the raw materials, production process and finished products is more than 20% higher than the qualified standard, and no further adjustment is required. The production batch is classified as a "high-quality" batch, and the quality data is stored as a reference for the best production process;

[0083] When the first qualified threshold M≤production and processing quality index Cyzl<second qualified threshold N, the tea oil product reaches the second level, indicating that the product meets the quality requirements, but there is a gap with the first level. The production batch is classified as a qualified batch, and the key production parameters such as pressing temperature, pressure, and extraction time are adjusted. The impact on Cyzl is verified through small experimental adjustments, and gradually optimized to a high-quality grade. The screening and pretreatment process of raw materials is strengthened, the impurity content and acid value are further reduced, and the raw material quality coefficient Rmql is improved;

[0084] When the production and processing quality index Cyzl < the first qualified threshold M, the tea oil product does not reach the qualified level and has quality problems. It is necessary to take immediate improvement measures, classify the production batch as a "need to be improved" batch, suspend the sale and circulation of the batch, inspect and maintain the production equipment, and eliminate process deviations caused by equipment aging or failure;

[0085] The comprehensive report generation unit is used to integrate the evaluation results and strategies into a quality evaluation report, the report content includes quality level, improvement suggestions, potential risks and early warning information, and is automatically sent to the production management system.

[0086] The intelligent optimization control module includes a parameter optimization unit and a predictive maintenance unit;

[0087] The parameter optimization unit is used to receive the key production parameters output by the data analysis module and the evaluation level of the quality evaluation module according to the calculation result of the production and processing quality index Cyzl, send instructions to the production equipment control system in real time, and dynamically adjust the parameters, including pressing temperature, pressing pressure and refining time;

[0088] The predictive maintenance unit is used to continuously monitor the operating status of production line equipment, collect equipment operating status data in real time, identify potential failure risks by analyzing equipment operating data and failure history data, collect equipment operating status data in real time, and take maintenance measures in advance.

[0089] In this embodiment, the parameter optimization unit in the intelligent optimization control module can optimize the control parameters of the production equipment in real time, such as pressing temperature, pressing pressure, and refining time, based on the evaluation level output by the quality evaluation module and the key production parameters provided by the data analysis module. Through this intelligent optimization control, the system can dynamically adjust various parameters in the production process to keep them in the optimal state, thereby improving product quality and production efficiency. Compared with traditional manual adjustment or regular maintenance methods, this dynamic adjustment mode based on real-time data feedback is more accurate and efficient, and can respond to any abnormal situation in the production process in a timely manner, minimizing the defective rate and resource waste.

[0090] Example 5

[0091] A tea oil production and processing intelligent control method, please refer to Figure 2 , specifically: including the following steps:

[0092] Step 1: By deploying several analyzers, key quality parameters of tea seed raw materials entering the production line are collected in real time as the first data set, and the data are sent to the central control system for storage and preliminary analysis;

[0093] Step 2: Deploy several sensors to monitor various process parameters in the production process in real time as the second data set, and upload the data to the central control system;

[0094] Step 3: The refined tea oil product is tested for quality by using an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and the data is instantly transmitted to the central control system as the third data group;

[0095] Step 4: Filter, denoise and standardize the first data group, the second data group and the third data group received by the central control system, calculate and analyze the collected raw material data, production process data and finished product quality data using an intelligent algorithm to obtain: the production and processing quality index Cyzl, and feed back the calculation results to the central control system;

[0096] Step 5: interpret the calculation results output by the data analysis module, compare the production and processing quality index Cyzl with the preset first qualified threshold M and second qualified threshold N, automatically evaluate the comprehensive quality level of the tea oil product, and generate an evaluation grade strategy;

[0097] Step 6: Based on the output of the data analysis module and the quality assessment module, the intelligent optimization control strategy is implemented. The system will automatically adjust the operating parameters of the production equipment, continuously monitor the status of the entire production line, and perform predictive maintenance.

[0098] In this embodiment, based on data analysis, this system automatically compares and analyzes the production and processing quality index Cyzl with the preset qualified threshold through the quality assessment process of step five, and generates different quality assessment grade strategies. This evaluation mechanism can not only timely judge the comprehensive quality level of tea oil products, but also provide corresponding improvement suggestions and early warning prompts for production management, helping producers to quickly identify quality risks and take effective improvement measures. Through this automated and refined quality assessment and risk control system, the occurrence rate of unqualified products can be effectively reduced, and the overall product qualification rate and market competitiveness can be improved. Compared with traditional manual detection and manual analysis methods, this system has greatly improved the quality control level of tea oil production, making the production process more scientific and intelligent.

[0099] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent control system for tea oil production and processing, characterized in that: It includes raw material data acquisition module, production process parameter acquisition module, finished product quality monitoring module, data analysis module, quality assessment module and intelligent optimization control module; The raw material data acquisition module is used to deploy a number of analyzers to collect key quality parameters of tea seed raw materials entering the production line in real time as a first data group, and send the data to the central control system for storage and preliminary analysis; The production process parameter acquisition module is used to monitor various process parameters in the production process in real time by deploying a number of sensors as a second data group, and upload the data to the central control system; The finished product quality monitoring module is used to perform quality inspection on the refined tea oil finished product through an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and transmit the data to the central control system in real time as a third data group; The data analysis module is used to filter, denoise and standardize the first data group, the second data group and the third data group received by the central control system, calculate and analyze the collected raw material data, production process data and finished product quality data using an intelligent algorithm, obtain: production and processing quality index Cyzl, and feed back the calculation results to the central control system; The quality assessment module is used to interpret the calculation results output by the data analysis module, automatically assess the comprehensive quality level of the tea oil product by comparing the production and processing quality index Cyzl with the preset first qualified threshold M and second qualified threshold N, and generate an assessment grade strategy; The intelligent optimization control module is used to implement intelligent optimization control strategies based on the outputs of the data analysis module and the quality assessment module. The system will automatically adjust the operating parameters of the production equipment, continuously monitor the status of the entire production line, and perform predictive maintenance.

2. The tea oil production and processing intelligent control system according to claim 1, characterized in that: The raw material data acquisition module includes a raw material quality analysis unit; The raw material quality analysis unit is used to collect key quality parameters of tea seed raw materials entering the production line in real time by deploying a nuclear magnetic resonance analyzer, an infrared moisture analyzer, a spectrometer and an image recognition system, automatically collect the oil content OCR, impurity content IC, moisture content MC, seed integrity SI and acid value data AV of the tea seeds as the first data group, and send the data to the central control system for storage and preliminary analysis.

3. The tea oil production and processing intelligent control system according to claim 1 is characterized by: The production process parameter acquisition module includes a production process analysis unit; The production process analysis unit deploys thermocouple temperature sensors, pressure sensors, time controllers, temperature controllers and rotary encoders to monitor various process parameters in the production process in real time, including pressing temperature PT, pressing pressure PP, extraction time ET, refining temperature RT and stirring speed SS as the second data group, and uploads the data to the central control system.

4. The tea oil production and processing intelligent control system according to claim 1 is characterized by: The finished product quality monitoring module includes a finished product quality analysis unit; The finished product quality analysis unit is used to perform quality inspection on the refined tea oil product through an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and to monitor and record the acid value Ac, peroxide value PV, color index CI, viscosity VIS and redox potential RP in real time as the third data group, and transmit the data to the central control system in real time.

5. The tea oil production and processing intelligent control system according to claim 2 is characterized by: The data analysis module includes a data preprocessing unit and a data calculation unit; The data preprocessing unit is used to remove abnormal values ​​and incomplete data from the first data group, the second data group and the third data group, clean up the collected data by setting data filtering rules and statistical methods, use signal processing algorithms to denoise the collected raw material, process and finished product data, and convert the processed data into a standardized format through normalization.

6. The tea oil production and processing intelligent control system according to claim 5, characterized in that: The data calculation unit is used to analyze the processed first data group, second data group and third data group based on the use of multivariate regression, neural network or support vector machine algorithm, and calculate the production and processing quality index Cyzl, raw material quality coefficient Rmql, production process control coefficient Pcc and finished product quality coefficient Fpql.

7. The tea oil production and processing intelligent control system according to claim 1 is characterized by: The quality assessment module includes a quality assessment unit and a comprehensive report generation unit; The quality assessment unit is used to compare and analyze the production and processing quality index Cyzl with the preset first qualified threshold value M and second qualified threshold value N, analyze whether the tea oil product meets the qualified standard, automatically generate the corresponding assessment level, and automatically generate a risk warning signal to prompt that the corresponding corrective measures need to be taken immediately; When the production and processing quality index Cyzl ≥ the second qualified threshold N, the tea oil product reaches the first level, indicating that the quality of the raw materials, production process and finished products is more than 20% higher than the qualified standard and no further adjustment is required; When the first qualified threshold M≤production and processing quality index Cyzl<second qualified threshold N, the tea oil product reaches the second level, indicating that the product meets the quality requirements, but there is a gap with the first level, and the production batch is classified as a "qualified" batch; When the production and processing quality index Cyzl<the first qualified threshold M, the tea oil product does not reach the qualified grade and there are quality problems. Immediate improvement measures need to be taken. The production batch should be classified as a "needs improvement" batch and the sales and circulation of the batch should be suspended.

8. The tea oil production and processing intelligent control system according to claim 1 is characterized by: The comprehensive report generation unit is used to integrate the evaluation results and strategies into a quality evaluation report, the report content includes quality level, improvement suggestions, potential risks and early warning information, and is automatically sent to the production management system.

9. The tea oil production and processing intelligent control system according to claim 1, characterized in that: The intelligent optimization control module includes a parameter optimization unit and a predictive maintenance unit; The parameter optimization unit is used to receive the key production parameters output by the data analysis module and the evaluation level of the quality evaluation module according to the calculation result of the production and processing quality index Cyzl, send instructions to the production equipment control system in real time, and dynamically adjust the parameters, including pressing temperature, pressing pressure and refining time; The predictive maintenance unit is used to continuously monitor the operating status of production line equipment, collect equipment operating status data in real time, identify potential failure risks by analyzing equipment operating data and failure history data, collect equipment operating status data in real time, and take maintenance measures in advance.

10. An intelligent control method for tea oil production and processing, applied to an intelligent control system for tea oil production and processing according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: By deploying several analyzers, key quality parameters of tea seed raw materials entering the production line are collected in real time as the first data set, and the data are sent to the central control system for storage and preliminary analysis; Step 2: Deploy several sensors to monitor various process parameters in the production process in real time as the second data set, and upload the data to the central control system; Step 3: The refined tea oil product is tested for quality by using an automatic titrator, a redox potentiometer, a colorimeter and a viscometer, and the data is instantly transmitted to the central control system as the third data group; Step 4: Filter, denoise and standardize the first data group, the second data group and the third data group received by the central control system, calculate and analyze the collected raw material data, production process data and finished product quality data using an intelligent algorithm to obtain: the production and processing quality index Cyzl, and feed back the calculation results to the central control system; Step 5: interpret the calculation results output by the data analysis module, compare the production and processing quality index Cyzl with the preset first qualified threshold M and second qualified threshold N, automatically evaluate the comprehensive quality level of the tea oil product, and generate an evaluation grade strategy; Step 6: Based on the output of the data analysis module and the quality assessment module, the intelligent optimization control strategy is implemented. The system will automatically adjust the operating parameters of the production equipment, continuously monitor the status of the entire production line, and perform predictive maintenance.

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