Regulation and control method and system for food purification

Abstract

The invention discloses a regulation and control method and system for food purification, and relates to the technical field of food purification regulation and control. The regulation and control method for food purification comprises the following steps: collecting initial ozone purification data; calculating an ozone correlation coefficient; and formulating a regulation and control strategy. The method comprises the following steps: collecting initial ozone purification data of an ozone reaction experiment through a sensor, preprocessing the initial ozone purification data to obtain ozone purification data, performing data analysis on the ozone purification data to obtain an ozone correlation coefficient, and performing comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index; finally, a regulation and control strategy is obtained according to the comprehensive ozone evaluation index, and the regulation and control strategy is sent to preset personnel for processing, so that the effect of improving the regulation and control accuracy of food purification is achieved, and the problem of low ozone utilization rate in the food purification process in the prior art is solved.

Description

[0001] This application is a divisional application of the application filed on September 6, 2024, with application number 202411246454.7 and invention name “A control method and system for food purification”. Technical Field

[0002] The present invention relates to the technical field of food purification and control, and in particular to a control method and system for food purification. Background Art

[0003] As consumers pay more and more attention to food safety and health, food purification technology has gradually become a highly watched field. Food purification aims to remove harmful substances in food, such as pesticide residues, heavy metals, bacteria, viruses, mycotoxins and undesirable additives, through physical, chemical or biological methods, so as to improve the safety and quality of food. Food purification has a wide range of application scenarios, covering all aspects from raw material processing to production and processing, packaging and storage, and family catering. By removing harmful substances and microbial contamination, it ensures food safety, improves food quality, enhances consumer confidence, and promotes the healthy development of the food industry.

[0004] Existing food purification technologies achieve the effective removal of harmful substances in food through the use of a variety of physical, chemical and biological methods, such as ultraviolet irradiation, ozone treatment, ultrasonic cleaning, and bio-enzyme degradation, thereby ensuring the safety and hygienic quality of food; these technologies can not only reduce pesticide residues, bacteria and viruses and other pollutants in food, but also retain the nutritional content and flavor of food to a certain extent.

[0005] For example, the air purification method and device disclosed in the patent application with publication number: CN106909156A includes: obtaining the concentration of the disinfectant; upon receiving a cleaning instruction, controlling the cleaning mechanism of the sweeping robot to clean the current cleaning area; when the cleaning of the current cleaning area is finished, controlling the purifier linked to the sweeping robot to turn on to purify the air around the current cleaning area. Through the above technical method disclosed in the present invention, the sweeping robot and the purifier are combined together so that the two can cooperate with each other to complete the work, and the purpose of automatically purifying the air in the cleaning area while cleaning the cleaning area can be achieved.

[0006] For example, the invention patent with announcement number CN114895719A discloses a large-capacity ozone water preparation device and an intelligent ozone concentration adjustment method thereof, which includes three parts: an ozone water tank, a new water tank, and a used water tank, and is equipped with corresponding ozone concentration sensors, water quality sensors, ozone generators, air replenishment devices, circulating water pumps and other components, and at the same time, three types of algorithms, PID control, BP neural network, and support vector machine SVR, are applied to the three stages of ozone water storage, new water injection, and ozone water use. The present invention realizes that no matter whether new water is injected or ozone water is discharged, and no matter how the water temperature, water quality, pH value, set ozone concentration, etc. in the ozone water change, the ozone concentration in the ozone water tank can be adaptively maintained unchanged without manual intervention, and a large-capacity ozone water of a specified concentration can be provided at any time. The present invention can be widely used for sterilization and disinfection in the fields of water treatment, air purification, food processing, medical disease control, biopharmaceuticals, aquaculture, etc.

[0007] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0008] In the existing technology, the raw materials of canned livestock, poultry and aquatic products may be contaminated by various types of pollution, such as microorganisms and chemical pollutants. Ozone purification technology can be used to purify the raw materials of canned livestock, poultry and aquatic products. The ozone utilization rate refers to the proportion of the amount of ozone actually used for oxidation or disinfection of the raw materials of canned livestock, poultry and aquatic products in the ozone purification technology to the total amount of ozone input. The existing technology has the problem of low ozone utilization rate in the food purification process. Summary of the invention

[0009] The embodiments of the present application provide a control method and system for food purification, thereby solving the problem of low ozone utilization rate in the food purification process in the prior art and improving the control accuracy of food purification.

[0010] The embodiment of the present application provides a control method for food purification, comprising the following steps: S1, collecting initial ozone purification data of an ozone reaction experiment through a sensor, and preprocessing the initial ozone purification data to obtain ozone purification data; S1, collecting initial ozone purification data of an ozone reaction experiment through a sensor, and preprocessing the initial ozone purification data to obtain ozone purification data; S2, performing data analysis on the ozone purification data to obtain an ozone correlation coefficient, wherein the ozone correlation coefficient includes an ozone temperature coefficient and an ozone pH coefficient, wherein the ozone temperature coefficient is used to quantify the correlation between ozone utilization rate and temperature, and the ozone pH coefficient is used to quantify the correlation between ozone utilization rate and pH data; S3, performing a comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index, and at the same time obtaining a control strategy based on the comprehensive ozone evaluation index, and sending the control strategy to a preset person for processing.

[0011] Furthermore, the specific method for collecting the initial ozone purification data is as follows: the initial ozone purification data is collected by a sensor installed in the food purification room, the initial ozone purification data includes initial temperature data, initial pH data and initial ozone data, the initial ozone data includes a first initial ozone concentration and a second initial ozone concentration, the first initial ozone concentration represents the initial ozone concentration before the start of the ozone reaction experiment, and the second initial ozone concentration represents the initial ozone concentration after the end of the ozone reaction experiment.

[0012] Furthermore, the specific process of the preprocessing is as follows: the first ozone purification data is obtained by performing noise filtering on the initial ozone purification data; the second ozone purification data is obtained by removing outliers from the first ozone purification data; the ozone purification data is obtained by performing deduplication processing on the second ozone purification data; the ozone purification data includes temperature data, pH data and ozone data, and the ozone data includes a first ozone concentration and a second ozone concentration.

[0013] Furthermore, the specific steps of the comprehensive ozone assessment are as follows: obtaining a weight distribution factor corresponding to the ozone temperature coefficient and the ozone pH coefficient from a preset database, wherein the weight distribution factor includes an ozone temperature weight and an ozone pH weight; obtaining a comprehensive ozone assessment index according to the weight distribution factor, the ozone temperature coefficient and the ozone pH coefficient, wherein the comprehensive ozone assessment index is used to assess the correlation between temperature and pH value and ozone utilization rate; the comprehensive ozone assessment index is calculated using the following formula:

[0014]

[0015] In the formula, I U is the comprehensive ozone evaluation index of the ozone reaction experiment in the food purification room, R T is the ozone temperature coefficient, ω T is the ozone temperature weight, R PH is the ozone pH coefficient, ω PH is the pH weight of ozone.

[0016] Furthermore, the steps for formulating the control strategy are as follows: obtaining a preset comprehensive ozone assessment threshold and a preset ozone utilization rate from a preset database; judging the comprehensive ozone assessment index and the preset comprehensive ozone assessment threshold; if the comprehensive ozone assessment index is greater than the preset comprehensive ozone assessment threshold, generating a control strategy based on the ozone correlation coefficient and the preset ozone utilization rate, the control strategy including a temperature control strategy and a pH value control strategy, the control strategy is used to improve the ozone utilization rate by adjusting the temperature data or the pH data; if the comprehensive ozone assessment index is not greater than the preset comprehensive ozone assessment threshold, no processing is performed.

[0017] Furthermore, the specific method of the temperature control strategy is: if the ozone temperature coefficient is positive, the ozone utilization rate is improved by increasing the temperature of the ozone reaction experiment to the temperature control parameter; if the ozone temperature coefficient is negative, the ozone utilization rate is improved by reducing the temperature of the ozone reaction experiment to the temperature control parameter; if the ozone temperature coefficient is zero, the temperature of the ozone reaction experiment is not controlled; the temperature control parameter is calculated using the following formula:

[0018]

[0019] Where, T new is the temperature control parameter, T cur is the temperature data before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, ε1 is the temperature correction factor;

[0020] The specific method of the pH value control strategy is: if the ozone pH coefficient is positive, the ozone utilization rate is improved by increasing the pH value of the ozone reaction experiment to the pH control parameter; if the ozone pH coefficient is negative, the ozone utilization rate is improved by reducing the pH value of the ozone reaction experiment to the pH control parameter; if the ozone pH coefficient is zero, the pH value of the ozone reaction experiment is not controlled; the pH control parameter is calculated using the following formula:

[0021]

[0022] Where, pH new is the pH control parameter, pH cur is the pH value before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, and ε2 is the pH correction factor.

[0023] Furthermore, the data analysis includes a first data analysis and a second data analysis; the first data analysis represents obtaining an ozone temperature coefficient by acquiring temperature data and ozone data in ozone purification data to evaluate the correlation between temperature and ozone utilization rate in an ozone reaction experiment; the second data analysis represents obtaining an ozone pH coefficient by acquiring pH data and ozone data in ozone purification data to evaluate the correlation between pH value and ozone utilization rate in an ozone reaction experiment.

[0024] Furthermore, the specific method of the first data analysis is as follows: obtaining temperature data and ozone data from ozone purification data, and obtaining ozone utilization rate according to the ozone data; calculating the covariance and standard deviation of the temperature data and the ozone utilization rate according to the temperature data and the ozone utilization rate, and obtaining the ozone temperature coefficient accordingly, and the ozone temperature coefficient is calculated using the following formula:

[0025]

[0026] In the formula, R T is the ozone temperature coefficient of the ozone reaction experiment in the food purification room, T is the temperature data, U is the ozone utilization rate, CovT,U is the covariance between temperature and ozone utilization rate, σ T is the standard deviation of the temperature data, σ U is the standard deviation of ozone utilization efficiency.

[0027] Furthermore, the specific method of the second data analysis is as follows: obtaining pH data and ozone data from ozone purification data, and calculating ozone utilization rate according to the ozone data; calculating the covariance and standard deviation of pH data and ozone utilization rate according to pH data and ozone utilization rate, and obtaining ozone pH coefficient accordingly, and the ozone pH coefficient is calculated using the following formula:

[0028]

[0029] In the formula, R ph is the ozone pH coefficient of the ozone reaction experiment in the food purification room, P is the pH data, U is the ozone utilization rate, CovP,U is the covariance between the pH data and the ozone utilization rate, σ P is the standard deviation of pH data, σ U is the standard deviation of ozone utilization efficiency.

[0030] An embodiment of the present application provides a control system for food purification, comprising: a data collection module, a data analysis module and a data control module; wherein the data collection module is used to collect initial ozone purification data of an ozone reaction experiment through a sensor, and pre-process the initial ozone purification data to obtain ozone purification data; the data analysis module is used to perform data analysis on the ozone purification data to obtain an ozone correlation coefficient, wherein the ozone correlation coefficient comprises an ozone temperature coefficient and an ozone pH coefficient, wherein the ozone temperature coefficient is used to quantify the correlation between ozone utilization rate and temperature, and the ozone pH coefficient is used to quantify the correlation between ozone utilization rate and pH data; the data control module is used to perform a comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index, and at the same time obtain a control strategy based on the comprehensive ozone evaluation index, and send the control strategy to a preset person for processing.

[0031] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0032] 1. The initial ozone purification data of the ozone reaction experiment is collected by sensors and pre-processed to obtain ozone purification data. Then, the ozone purification data is analyzed to obtain the ozone correlation coefficient. Then, the ozone correlation coefficient is comprehensively evaluated to obtain the comprehensive ozone evaluation index. Finally, the control strategy is obtained according to the comprehensive ozone evaluation index, and the control strategy is sent to the preset personnel for processing, thereby realizing the efficient formulation of the control strategy of ozone-related data, and then realizing the improvement of the control accuracy of food purification, and effectively solving the problem of low ozone utilization rate in the food purification process in the prior art.

[0033] 2. By obtaining the preset comprehensive ozone assessment threshold and the preset ozone utilization rate from the preset database, and then judging the comprehensive ozone assessment index and the preset comprehensive ozone assessment threshold, if the comprehensive ozone assessment index is greater than the preset comprehensive ozone assessment threshold, a control strategy is formulated according to the ozone correlation coefficient and the preset ozone utilization rate; if the comprehensive ozone assessment index is not greater than the preset comprehensive ozone assessment threshold, no processing is performed, thereby realizing the specific numericalization of the control strategy in the ozone reaction experiment, and then realizing a more accurate formulation of the control strategy in the ozone reaction experiment.

[0034] 3. By obtaining the ozone temperature weight and ozone pH weight corresponding to the ozone temperature coefficient and the ozone pH coefficient from the preset database, and then obtaining the comprehensive ozone evaluation index according to the ozone temperature weight, the ozone pH weight, the ozone temperature coefficient and the ozone pH coefficient to evaluate the correlation between temperature and pH value and ozone utilization rate, the correlation between temperature and pH value and ozone utilization rate in the ozone reaction experiment is quantified, thereby achieving a more accurate evaluation of the correlation between temperature and pH value and ozone utilization rate in the ozone reaction experiment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A flow chart of a control method for food purification provided in an embodiment of the present application;

[0036] Figure 2 A flow chart of formulating a control strategy provided in an embodiment of the present application;

[0037] Figure 3 A schematic diagram of changes in the comprehensive ozone assessment index provided in an embodiment of the present application;

[0038] Figure 4 A schematic diagram of the structure of a control system for food purification provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The embodiments of the present application solve the problem of low ozone utilization rate in existing ozone purification technologies by providing a control method and system for food purification. Initial ozone purification data of ozone reaction experiments are collected by sensors, and the initial ozone purification data are preprocessed to obtain ozone purification data. The ozone purification data are then analyzed to obtain an ozone correlation coefficient. The ozone correlation coefficient is then subjected to a comprehensive ozone evaluation to obtain a comprehensive ozone evaluation index. Finally, a control strategy is obtained based on the comprehensive ozone evaluation index, and the control strategy is sent to a preset person for processing, thereby improving the control accuracy of food purification.

[0040] The technical solution in the embodiment of the present application is to solve the problem of low ozone utilization rate in the above-mentioned food purification process, and the overall idea is as follows:

[0041] The ozone correlation coefficient is obtained by analyzing the ozone purification data, and then a comprehensive ozone evaluation is performed on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index. Finally, a control strategy is obtained based on the comprehensive ozone evaluation index, thereby achieving the effect of improving the control accuracy of food purification.

[0042] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0043] like Figure 1 As shown, it is a flow chart of a control method for food purification provided in an embodiment of the present application, and the method includes the following steps: S1, collecting initial ozone purification data of an ozone reaction experiment through a sensor, and preprocessing the initial ozone purification data to obtain ozone purification data; S2, performing data analysis on the ozone purification data to obtain an ozone correlation coefficient, the ozone correlation coefficient includes an ozone temperature coefficient and an ozone pH coefficient, the ozone temperature coefficient is used to quantify the correlation between ozone utilization rate and temperature, and the ozone pH coefficient is used to quantify the correlation between ozone utilization rate and pH data; S3, performing a comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index, and at the same time obtaining a control strategy based on the comprehensive ozone evaluation index, and sending the control strategy to a preset person for processing.

[0044] In this embodiment, the ozone reaction experiment means that the pollutants on the surface of food are oxidized and decomposed by ozone to achieve the purpose of food purification; the ozone reaction experiment is applied to the field of food purification, and the pollutants on the surface of the raw materials of livestock, poultry and aquatic canned products are oxidized and decomposed by the strong oxidizing property of ozone, thereby achieving the cleaning and disinfection of the raw materials of livestock, poultry and aquatic canned products. The steps of the ozone reaction experiment include preparing experimental equipment and samples, starting the ozone generator to generate ozone and supplying it to the reactor, so that the ozone reacts with the pollutants in the sample to produce an oxidation reaction, during which the data is recorded and analyzed to evaluate the reaction effect, and finally shutting down the equipment and cleaning the existing field; preprocessing means filtering out noise, removing outliers and de-duplication of initial ozone purification data; the control strategy aims to improve the utilization rate of ozone by adjusting the temperature or pH value of the ozone reaction experiment. For example, if the ozone utilization rate is low at the current temperature, it is recommended to lower the temperature to the temperature control parameter to promote the dissolution and reaction of ozone to achieve the purpose of improving the utilization rate of ozone; if the pH value deviates from the optimal range, it is recommended to adjust the pH value to the pH control parameter to improve the ozone reaction environment to achieve the purpose of improving the utilization rate of ozone; the control accuracy of food purification is improved.

[0045] Furthermore, the specific method for collecting initial ozone purification data is as follows: initial ozone purification data is collected through sensors installed in the food purification room, the initial ozone purification data includes initial temperature data, initial pH data and initial ozone data, the initial ozone data includes a first initial ozone concentration and a second initial ozone concentration, the first initial ozone concentration represents the initial ozone concentration before the start of the ozone reaction experiment, and the second initial ozone concentration represents the initial ozone concentration after the end of the ozone reaction experiment.

[0046] In this embodiment, the sensor is used to monitor and collect data related to the food purification process in real time, and these data are of great significance for evaluating the purification effect, adjusting the purification strategy, and ensuring the safety of raw materials for canned livestock, poultry and aquatic products; the sensor includes a temperature sensor, a pH sensor and an ozone concentration sensor; the temperature sensor is used to monitor the temperature conditions in the food purification room. Temperature is one of the important factors affecting microbial growth and ozone decomposition efficiency. By real-time monitoring the temperature in the food purification room, it can be ensured that the temperature in the purification room is maintained within an appropriate range to optimize the sterilization effect of ozone purification and inhibit the reproduction of harmful microorganisms. The pH sensor is used to measure the pH value of the purification room environment. In the food purification process, the pH value is crucial to controlling the growth of microorganisms and the activity of enzymes. Understanding the pH value in the food purification room helps to determine whether the pH value needs to be adjusted to achieve a better ozone purification effect; the ozone concentration sensor is used to monitor the ozone concentration in the purification room in real time, and the ozone utilization rate is obtained by monitoring the ozone concentration before and after the ozone reaction experiment in the food purification room to facilitate the formulation of subsequent control strategies; accurate collection of data related to the ozone reaction experiment in the food purification room is achieved.

[0047] Furthermore, the specific process of preprocessing is as follows: the first ozone purification data is obtained by performing noise filtering on the initial ozone purification data; the second ozone purification data is obtained by removing outliers from the first ozone purification data; the ozone purification data is obtained by performing deduplication processing on the second ozone purification data; the ozone purification data includes temperature data, pH data and ozone data, and the ozone data includes a first ozone concentration and a second ozone concentration.

[0048] In this embodiment, noise filtering is used to reduce random fluctuations and noise introduced in the data due to measurement errors and environmental interference factors. When conducting ozone reaction experiments, the temperature sensor has high-frequency fluctuation noise in the collected temperature data due to slight temperature changes in the environment or slight drift of the sensor itself. This noise will affect the accuracy of subsequent data analysis. A low-pass filter is used to perform noise filtering on the initial ozone purification data. A window size (such as 5 data points) is set, and the average value of the data in each window is calculated as the filtered value of the center point of the window to achieve the effect of averaging high-frequency noise and retaining low-frequency signals (i.e., the true temperature change trend); outlier removal is used to exclude outliers caused by equipment failure, extreme conditions or human errors. Strong electromagnetic interference or momentary failure of the data transmission line may cause the ozone concentration data at a certain moment to be higher or different from the previous and subsequent data points. A threshold range based on the standard deviation of normal ozone concentration data can be set to traverse the initial ozone data. Data points that exceed the threshold range are considered as outliers and are eliminated. Deduplication is used to ensure the uniqueness and accuracy of the data. Duplicate data may be caused by problems with the data acquisition system or improper settings. A hash table can be used for deduplication. First, each row of data in the ozone purification data (including temperature data, pH data, and ozone data) is converted into a unique hash value, and then the hash value is stored in the hash table. It is checked whether there are duplicate hash values. If there are duplicates, only one row of data is retained and the remaining duplicate rows are deleted.

[0049] Specifically, the first ozone concentration represents the first initial ozone concentration after pretreatment, and the second ozone concentration represents the second initial ozone concentration after pretreatment. The ozone utilization rate is calculated according to the first ozone concentration and the second ozone concentration. The ozone utilization rate is calculated using the following formula:

[0050]

[0051] Where U is the ozone utilization rate, M a is the ozone concentration before reaction, M b is the ozone concentration after the reaction.

[0052] Ozone purification data is obtained by filtering out noise, removing outliers and deduplicating the initial ozone purification data, which provides strong support for the precise implementation of food purification regulation and effectively improves the data quality of ozone purification data.

[0053] Furthermore, the specific steps of the comprehensive ozone assessment are as follows: obtain the weight distribution factors corresponding to the ozone temperature coefficient and the ozone pH coefficient from the preset database, the weight distribution factors including the ozone temperature weight and the ozone pH weight; obtain the comprehensive ozone assessment index according to the weight distribution factor, the ozone temperature coefficient and the ozone pH coefficient, and the comprehensive ozone assessment index is used to evaluate the correlation between temperature and pH value and ozone utilization rate; the comprehensive ozone assessment index is calculated using the following formula:

[0054]

[0055] In the formula, I U is the comprehensive ozone evaluation index of the ozone reaction experiment in the food purification room, R T is the ozone temperature coefficient, ω T is the ozone temperature weight, R PH is the ozone pH coefficient, ω PH is the pH weight of ozone.

[0056] In this embodiment, the formula combines the ozone temperature coefficient, the ozone pH coefficient, the ozone temperature weight and the ozone pH weight to obtain a comprehensive ozone assessment index. In this formula, the ozone temperature coefficient and the ozone pH coefficient are positively correlated with the comprehensive ozone assessment index. The value range of the comprehensive ozone assessment index is 0 to 1. The closer the value of the comprehensive ozone assessment index is to 1, the stronger the correlation between temperature and pH value and ozone utilization rate. The closer the value of the comprehensive ozone assessment index is to 0, the weaker the correlation between temperature and pH value and ozone utilization rate. It shows that the accuracy of the ozone correlation coefficient will significantly affect the value of the comprehensive ozone assessment index, among which the ozone temperature coefficient and the ozone pH coefficient independently affect the ozone utilization rate within their respective ranges of action. In practical applications, changes in temperature and pH value may interact with each other to produce synergistic or antagonistic effects. For example, under certain conditions, changes in temperature and pH value may promote each other, so that the utilization rate of ozone is significantly improved; while under other conditions, their changes may offset each other and even lead to a decrease in ozone utilization rate.

[0057] Specifically, the weight distribution factor is a quantitative expression of the role of temperature and pH value in ozone utilization. The ozone temperature weight represents the influence of temperature factors on ozone utilization in ozone reaction experiments. Under different temperature conditions, the decomposition rate of ozone and the reaction rate with other substances will change, thereby affecting the ozone utilization rate. The ozone pH weight represents the influence of pH factors on ozone utilization in ozone reaction experiments. Changes in pH value may change the reaction path and rate of ozone with other substances in the solution, thereby affecting the ozone utilization rate. The sum of the ozone temperature weight and the ozone pH weight is 1, which represents the different effects of different factors on the comprehensive ozone assessment index. Adjusting the distribution of weights can reflect the different effects of different factors on the comprehensive ozone assessment index.

[0058] According to the relationship between the historical ozone temperature coefficient and the comprehensive ozone assessment index, a mapping set of the ozone temperature coefficient and its corresponding weight factor is constructed, and the real-time ozone temperature coefficient is input into the mapping set to obtain the corresponding ozone temperature weight.

[0059] According to the relationship between the historical ozone pH coefficient and the comprehensive ozone assessment index, a mapping set of the ozone pH coefficient and its corresponding weight factor is constructed, and the real-time ozone temperature coefficient is input into the mapping set to obtain the corresponding ozone pH weight.

[0060] It should be understood that, taking the ozone temperature weight as 0.6 and the ozone pH weight as 0.4 as an example, the statistical table of changes in the comprehensive ozone assessment index is shown in Table 1:

[0061] Table 1 Statistics of changes in the comprehensive ozone assessment index

[0062] <![CDATA[Ozone temperature coefficient R T > <![CDATA[Ozone pH coefficient R PH > <![CDATA[Comprehensive Ozone Assessment Index I U > 0.5 0.3 0.61 -0.2 0 0.19 0 -0.8 0.48 0.8 0.8 0.95 ... ...

[0063] As can be seen from Table 1, these four sets of data show the changes in the comprehensive ozone evaluation index under different ozone temperature coefficients and ozone pH coefficients. In the first set of data, both temperature and pH value are positively correlated with ozone utilization rate, and the comprehensive ozone evaluation index is 0.67, indicating that there is a strong correlation between temperature and pH value and ozone utilization rate. In the second set of data, temperature is negatively correlated with ozone utilization rate, but pH value has no correlation with ozone utilization rate. In addition, due to the small influence of temperature (the absolute value of the ozone temperature coefficient is small and the ozone temperature weight is not high), the value of the comprehensive ozone evaluation index is relatively high. Low, indicating that the correlation between temperature and pH value and ozone utilization rate is weak. In the third set of data, there is no correlation between temperature and ozone utilization rate, but pH value is negatively correlated with ozone utilization rate. Although the influence of pH value is large (the absolute value of ozone pH coefficient is large but the weight of ozone pH coefficient is low), and because temperature has no effect, the value of comprehensive ozone evaluation index is at a medium level, indicating that there is a certain correlation between temperature and pH value and ozone utilization rate, but not as strong as when it is completely positively correlated. In the fourth set of data, both temperature and pH value are positively correlated with ozone utilization rate, and the influence is large. Therefore, the value of comprehensive ozone evaluation index reaches 0.95, indicating that there is a strong correlation between temperature and pH value and ozone utilization rate.

[0064] like Figure 3 As shown, it is a schematic diagram of the change of the comprehensive ozone evaluation index provided in the embodiment of the present application, and the relationship between the comprehensive ozone evaluation index and the ozone temperature coefficient and the ozone pH coefficient is shown in the figure. It is assumed that the value range of the ozone temperature coefficient is 0 to 1, the ozone temperature weight is 0.5, the value range of the ozone pH coefficient is 0 to 1, and the ozone pH weight is 0.5. It can be seen from the figure that the larger the values ​​of the ozone temperature coefficient and the ozone pH coefficient, the larger the comprehensive ozone evaluation index, indicating that the correlation between the temperature and pH value and the ozone utilization rate is stronger, and the smaller the values ​​of the ozone temperature coefficient and the ozone pH coefficient, the smaller the comprehensive ozone evaluation index, indicating that the correlation between the temperature and pH value and the ozone utilization rate is weaker, showing the degree of correlation between the temperature and pH value and the ozone utilization rate, and providing support for the subsequent formulation of control strategies; a more accurate numericalization of the comprehensive ozone evaluation index of the ozone reaction experiment in the food purification room is achieved.

[0065] Further, such as Figure 2As shown, it is a flow chart for formulating a control strategy provided in an embodiment of the present application, and the steps for formulating the control strategy are as follows: obtaining a preset comprehensive ozone assessment threshold and a preset ozone utilization rate from a preset database; judging the comprehensive ozone assessment index and the preset comprehensive ozone assessment threshold; if the comprehensive ozone assessment index is greater than the preset comprehensive ozone assessment threshold, generating a control strategy based on the ozone correlation coefficient and the preset ozone utilization rate, the control strategy includes a temperature control strategy and a pH value control strategy, and the control strategy is used to achieve the purpose of improving the ozone utilization rate by adjusting the temperature data or the pH data; if the comprehensive ozone assessment index is not greater than the preset comprehensive ozone assessment threshold, no processing is performed.

[0066] In this embodiment, the preset comprehensive ozone evaluation threshold is a preset limit value obtained from a preset database, and the value range of the preset comprehensive ozone evaluation threshold is 0.5 to 1; when the comprehensive ozone evaluation index is greater than the preset comprehensive ozone evaluation threshold, it means that the temperature and pH value are strongly correlated with the ozone utilization rate, and the temperature and pH value of the ozone reaction experiment in the food purification room can be adjusted through a control strategy to achieve the purpose of improving the ozone utilization rate in the food purification process; the preset ozone utilization rate is an ozone utilization rate lower limit value obtained from a preset database, and the value range of the preset ozone utilization rate is 60% to 100%. The preset ozone utilization rate is used to determine whether it is necessary to control the ozone reaction experiment. When the ozone utilization rate is lower than the preset ozone utilization rate, it is considered that the temperature and pH value of the ozone reaction experiment need to be regulated, and when the ozone utilization rate is higher than the preset ozone utilization rate, it is considered that the temperature and pH value of the ozone reaction experiment do not need to be regulated; the purpose of generating a control strategy for the ozone purification process based on the comprehensive ozone evaluation index is achieved.

[0067] Furthermore, the specific method of the temperature control strategy is: if the ozone temperature coefficient is positive, the ozone utilization rate is improved by increasing the temperature of the ozone reaction experiment to the temperature control parameter; if the ozone temperature coefficient is negative, the ozone utilization rate is improved by reducing the temperature of the ozone reaction experiment to the temperature control parameter; if the ozone temperature coefficient is zero, the temperature of the ozone reaction experiment is not controlled; the temperature control parameter is calculated using the following formula:

[0068]

[0069] Where, T new is the temperature control parameter, T cur is the temperature data before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, ε1 is the temperature correction factor;

[0070] The specific method of the pH value control strategy is: if the ozone pH coefficient is positive, the ozone utilization rate is improved by increasing the pH value of the ozone reaction experiment to the pH control parameter; if the ozone pH coefficient is negative, the ozone utilization rate is improved by reducing the pH value of the ozone reaction experiment to the pH control parameter; if the ozone pH coefficient is zero, the pH value of the ozone reaction experiment is not controlled; the pH control parameter is calculated using the following formula:

[0071]

[0072] Where, pH new is the pH control parameter, pH cur is the pH value before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, and ε2 is the pH correction factor.

[0073] In this embodiment, a temperature correction factor and a pH correction factor are obtained from a preset database for correcting the formula unit, and the value range is between 0 and 1. The temperature correction factor indicates that the temperature needs to be adjusted by ε1°C for every 1% increase in ozone utilization, and the unit of the pH correction factor indicates that the pH value needs to be adjusted by ε2 for every 1% increase in ozone utilization. When the comprehensive ozone evaluation index is greater than the preset comprehensive ozone evaluation threshold and the ozone utilization rate is lower than the preset ozone utilization rate, it means that the temperature and pH value in the food purification room can be adjusted to improve the ozone utilization rate.

[0074] Specifically, a mapping set of the temperature data before adjustment and its corresponding correction factor is constructed according to the relationship between the historical temperature data before adjustment and the temperature control parameters, and the real-time temperature data before adjustment is input into the mapping set to obtain the corresponding temperature correction factor.

[0075] According to the relationship between the historical pH value before adjustment and the pH control parameter, a mapping set of the pH value before adjustment and its corresponding correction factor is constructed, and the real-time pH value before adjustment is input into the mapping set to obtain the corresponding pH value correction factor; thus, the digitization of the control strategy in the food purification process is realized.

[0076] Furthermore, the specific method of the first data analysis is as follows: temperature data and ozone data are obtained from ozone purification data, and ozone utilization rate is obtained according to the ozone data; covariance and standard deviation of temperature data and ozone utilization rate are calculated according to temperature data and ozone utilization rate, and ozone temperature coefficient is obtained accordingly. The ozone temperature coefficient is calculated using the following formula:

[0077]

[0078] In the formula, R Tis the ozone temperature coefficient of the ozone reaction experiment in the food purification room, T is the temperature data, U is the ozone utilization rate, CovT,U is the covariance between temperature and ozone utilization rate, σ T is the standard deviation of the temperature data, σ U is the standard deviation of ozone utilization efficiency.

[0079] In this embodiment, the value range of the ozone temperature coefficient is from -1 to 1. If the ozone temperature coefficient is positive, it indicates that there is a positive correlation between temperature and ozone utilization rate, that is, the ozone utilization rate increases when the temperature increases; if the ozone temperature coefficient is negative, it indicates that there is a negative correlation, that is, the ozone utilization rate decreases when the temperature increases; if the ozone coefficient is 0, it indicates that there is no linear correlation between temperature and ozone utilization rate; the closer the absolute value of the ozone temperature coefficient is to 1, the stronger the correlation between temperature and ozone utilization rate is, and the closer the absolute value of the ozone temperature coefficient is to 0, the weaker the correlation between temperature and ozone utilization rate is.

[0080] Specifically, the standard deviation of temperature data is calculated using the following formula: In the formula, σ T is the standard deviation of the temperature data, i represents the temperature of the i-th observation, i=1,2,...,n, n is the total number of temperature observations, T i is the temperature of the ith observation, is the observed average temperature; the standard deviation of ozone utilization efficiency is calculated using the following formula: In the formula, σ U is the standard deviation of ozone utilization rate, j represents the ozone utilization rate of the jth observation, j=1,2,...,m, m is the total number of observations, U j is the ozone utilization rate corresponding to the j-th observed ozone data, is the average value of ozone utilization rate corresponding to the observed ozone data; the covariance between temperature and ozone utilization rate is calculated using the following formula: Where CovT,U is the covariance between temperature and ozone utilization rate, a represents the ath observation, a=1,2,...,x, x is the total number of observations, T a is the temperature of the a-th observation, is the observed average temperature, U a is the ozone utilization rate corresponding to the a-th observed ozone data, It is the average value of ozone utilization rate corresponding to the observed ozone data; it realizes the correlation between temperature data and ozone utilization rate in the quantitative food purification process.

[0081] Furthermore, the specific method of the second data analysis is as follows: pH data and ozone data are obtained from the ozone purification data, and the ozone utilization rate is calculated according to the ozone data; the covariance and standard deviation of the pH data and the ozone utilization rate are calculated according to the pH data and the ozone utilization rate, and the ozone pH coefficient is obtained accordingly. The ozone pH coefficient is calculated using the following formula:

[0082]

[0083] In the formula, R ph is the ozone pH coefficient of the ozone reaction experiment in the food purification room, P is the pH data, U is the ozone utilization rate, CovP,U is the covariance between the pH data and the ozone utilization rate, σ P is the standard deviation of pH data, σ U is the standard deviation of ozone utilization efficiency.

[0084] In this embodiment, the value range of the ozone pH coefficient is from -1 to 1. If the ozone pH coefficient is positive, it indicates that there is a positive correlation between the pH value and the ozone utilization rate, that is, the ozone utilization rate increases when the pH value increases; if the ozone pH coefficient is negative, it indicates that there is a negative correlation, that is, the ozone utilization rate decreases when the pH value increases; if the ozone pH coefficient is 0, it indicates that there is no linear correlation between the pH value and the ozone utilization rate; the closer the absolute value of the ozone pH coefficient is to 1, the stronger the correlation between the pH value and the ozone utilization rate, and the closer the absolute value of the ozone pH coefficient is to 0, the weaker the correlation between the pH value and the ozone utilization rate;

[0085] Specifically, the standard deviation of pH data is calculated using the following formula: In the formula, σ P is the standard deviation of the pH data, k represents the pH value of the kth observation, k = 1, 2, ..., l, l is the total number of pH value observations, P k is the pH value of the kth observation, is the average value of the observed pH value; the covariance between pH data and ozone utilization rate is calculated using the following formula: Where CovP,U is the covariance between pH data and ozone utilization rate, b represents the bth observation, b=1,2,...,y, y is the total number of observations, P b is the pH value of the bth observation, is the observed average pH value, U b is the ozone utilization rate corresponding to the b-th observed ozone data, It is the average value of ozone utilization rate corresponding to the observed ozone data; it realizes the correlation between pH data and ozone utilization rate in the quantitative food purification process.

[0086] Furthermore, the data analysis includes a first data analysis and a second data analysis; the first data analysis represents obtaining the ozone temperature coefficient by acquiring the temperature data and ozone data in the ozone purification data to evaluate the correlation between temperature and ozone utilization rate in the ozone reaction experiment; the second data analysis represents obtaining the ozone pH coefficient by acquiring the pH data and ozone data in the ozone purification data to evaluate the correlation between pH value and ozone utilization rate in the ozone reaction experiment.

[0087] In this embodiment, the correlation between temperature and ozone utilization rate in the ozone reaction experiment includes a first correlation direction and a first correlation strength, and the first correlation direction between temperature and ozone utilization rate is determined according to the positive and negative values ​​of the ozone temperature coefficient; the absolute value of the ozone temperature coefficient reflects the first correlation strength; the correlation between pH value and ozone utilization rate in the ozone reaction experiment includes a second correlation direction and a second correlation strength, and the second correlation direction between pH value and ozone utilization rate is determined according to the positive and negative values ​​of the ozone pH coefficient; the absolute value of the ozone pH coefficient reflects the second correlation strength; a more accurate evaluation of the ozone correlation coefficient in the food purification process is achieved.

[0088] like Figure 4 As shown, it is a structural schematic diagram of a control system for food purification provided in an embodiment of the present application. A control system for food purification provided in an embodiment of the present application includes: a data collection module, a data analysis module and a data control module; wherein the data collection module is used to collect initial ozone purification data of the ozone reaction experiment through a sensor, and pre-process the initial ozone purification data to obtain ozone purification data; the data analysis module is used to perform data analysis on the ozone purification data to obtain an ozone correlation coefficient, the ozone correlation coefficient includes an ozone temperature coefficient and an ozone pH coefficient, the ozone temperature coefficient is used to quantify the correlation between ozone utilization rate and temperature, and the ozone pH coefficient is used to quantify the correlation between ozone utilization rate and pH data; the data control module is used to perform a comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index, and at the same time obtain a control strategy based on the comprehensive ozone evaluation index, and send the control strategy to a preset person for processing.

[0089] In this embodiment, the ozone correlation coefficient and the comprehensive ozone evaluation index are obtained by the data processing of the above steps according to the data collected during the ozone reaction experiment, and the corresponding control strategy can be formulated to solve the problem of low ozone utilization rate. For example, if the comprehensive ozone evaluation index is 0.8, the preset comprehensive ozone evaluation threshold is 0.5, the ozone utilization rate is 70%, the preset ozone utilization rate is 85%, the ozone temperature weight is 0.5, the ozone pH weight is 0.5, the temperature data before adjustment is 25°C, the pH value before adjustment is 7.0, the temperature correction factor and the pH correction factor are both 0.1, the ozone correlation coefficient is 0.5, and the ozone pH coefficient is -0.3, then the temperature control parameter T can be calculated according to the temperature control strategy. new =T cur +U tar -U cur *ε1=25℃+85%-75%*0.1℃ / %=26.5℃; pH control parameter pH can be calculated according to pH control strategy new =pH cur -U tar -U cur *ε2=7.0-85%-75%*0.11 / %=6.85, and the obtained control strategy is sent to the preset personnel for processing, thereby realizing the accurate formulation of the control strategy in the food purification process.

[0090] To summarize, the embodiment of the present application obtains the ozone correlation coefficient by performing data analysis on the ozone purification data, then performs a comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index, and finally obtains a control strategy based on the comprehensive ozone evaluation index, and sends the control strategy to a preset person for processing, thereby achieving efficient formulation of a control strategy for ozone-related data, and further achieving improved control accuracy of food purification, effectively solving the problem of low ozone utilization in the food purification process in the prior art.

[0091] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0092] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0093] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0095] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0096] 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.

Claims

1. A control method for food purification, characterized in that: The following steps are involved: S1, collecting initial ozone purification data of the ozone reaction experiment through a sensor, and preprocessing the initial ozone purification data to obtain ozone purification data; S2, performing data analysis on the ozone purification data to obtain an ozone correlation coefficient, wherein the ozone correlation coefficient includes an ozone temperature coefficient and an ozone pH coefficient, wherein the ozone temperature coefficient is used to quantify the correlation between ozone utilization rate and temperature, and the ozone pH coefficient is used to quantify the correlation between ozone utilization rate and pH data; S3, performing a comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index, and obtaining a control strategy based on the comprehensive ozone evaluation index, and sending the control strategy to a preset person for processing; The specific steps of the comprehensive ozone assessment are as follows: Obtaining a weight distribution factor corresponding to an ozone temperature coefficient and an ozone pH coefficient from a preset database, wherein the weight distribution factor includes an ozone temperature weight and an ozone pH weight; Obtaining a comprehensive ozone evaluation index according to the weight distribution factor, the ozone temperature coefficient and the ozone pH coefficient, wherein the comprehensive ozone evaluation index is used to evaluate the correlation between temperature and pH value and ozone utilization rate; The comprehensive ozone assessment index is calculated using the following formula: In the formula, I U is the comprehensive ozone evaluation index of the ozone reaction experiment in the food purification room, R T is the ozone temperature coefficient, ω T is the ozone temperature weight, R PH is the ozone pH coefficient, ω PH is the ozone pH weight; The steps for formulating the control strategy are as follows: Obtaining a preset comprehensive ozone assessment threshold and a preset ozone utilization rate from a preset database; The comprehensive ozone assessment index is compared with the preset comprehensive ozone assessment threshold; If the comprehensive ozone assessment index is greater than the preset comprehensive ozone assessment threshold, a control strategy is generated according to the ozone correlation coefficient and the preset ozone utilization rate, wherein the control strategy includes a temperature control strategy and a pH value control strategy, and the control strategy is used to achieve the purpose of improving the ozone utilization rate by adjusting the temperature data or the pH data; If the comprehensive ozone assessment index is not greater than the preset comprehensive ozone assessment threshold, no processing is performed; The specific method of the temperature control strategy is: If the ozone temperature coefficient is positive, the ozone utilization rate is increased by increasing the temperature of the ozone reaction experiment to the temperature control parameter; If the ozone temperature coefficient is negative, the ozone utilization rate is increased by lowering the temperature of the ozone reaction experiment to the temperature control parameter; If the ozone temperature coefficient is zero, the temperature of the ozone reaction experiment will not be regulated; The temperature control parameters are calculated using the following formula: Where, T new is the temperature control parameter, T cur is the temperature data before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, and ε1 is the temperature correction factor.

2. A control method for food purification as claimed in claim 1, characterized in that: The specific method of the pH value control strategy is: If the ozone pH coefficient is positive, the ozone utilization rate is increased by increasing the pH value of the ozone reaction experiment to the pH control parameter; If the ozone pH coefficient is negative, the ozone utilization rate is increased by lowering the pH value of the ozone reaction experiment to the pH control parameter; If the ozone pH coefficient is zero, the pH value of the ozone reaction experiment will not be regulated; The pH control parameter is calculated using the following formula: Where, pH new is the pH control parameter, pH cur is the pH value before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, and ε2 is the pH correction factor.

3. A control method for food purification as claimed in claim 1, characterized in that: The specific method for collecting the initial ozone purification data is as follows: Initial ozone purification data is collected by sensors installed in the food purification room, the initial ozone purification data includes initial temperature data, initial pH data and initial ozone data, the initial ozone data includes a first initial ozone concentration and a second initial ozone concentration, the first initial ozone concentration represents the initial ozone concentration before the start of the ozone reaction experiment, and the second initial ozone concentration represents the initial ozone concentration after the end of the ozone reaction experiment.

4. A control method for food purification as claimed in claim 1, characterized in that: The specific process of the pretreatment is as follows: The first ozone purification data is obtained by performing noise filtering on the initial ozone purification data; The second ozone purification data is obtained by removing outliers from the first ozone purification data; Obtaining ozone purification data by performing deduplication processing on the second ozone purification data; The ozone purification data includes temperature data, pH data and ozone data, and the ozone data includes a first ozone concentration and a second ozone concentration.

5. A control method for food purification as claimed in claim 1, characterized in that: The data analysis includes a first data analysis and a second data analysis; The first data analysis means obtaining the temperature data and ozone data in the ozone purification data to obtain the ozone temperature coefficient to evaluate the correlation between the temperature and the ozone utilization rate in the ozone reaction experiment; The second data analysis means obtaining the pH data and ozone data in the ozone purification data to obtain the ozone pH coefficient so as to evaluate the correlation between the pH value and the ozone utilization rate in the ozone reaction experiment.

6. A control method for food purification as claimed in claim 5, characterized in that: The specific method of the first data analysis is as follows: Acquire temperature data and ozone data from ozone purification data, and obtain ozone utilization rate based on the ozone data; The covariance and standard deviation of the temperature data and the ozone utilization rate are calculated according to the temperature data and the ozone utilization rate, and the ozone temperature coefficient is obtained based on this. The ozone temperature coefficient is calculated using the following formula: In the formula, R T is the ozone temperature coefficient of the ozone reaction experiment in the food purification room, T is the temperature data, U is the ozone utilization rate, Cov(T,U) is the covariance between temperature and ozone utilization rate, σ T is the standard deviation of the temperature data, σ U is the standard deviation of ozone utilization efficiency.

7. A control method for food purification as claimed in claim 6, characterized in that: The specific method of the second data analysis is as follows: Obtain pH data and ozone data from ozone purification data, and calculate ozone utilization rate based on the ozone data; The covariance and standard deviation of the pH data and the ozone utilization rate are calculated according to the pH data and the ozone utilization rate, and the ozone pH coefficient is obtained based on this. The ozone pH coefficient is calculated using the following formula: In the formula, R ph is the ozone pH coefficient of the ozone reaction experiment in the food purification room, P is the pH data, U is the ozone utilization rate, Cov(P,U) is the covariance between the pH data and the ozone utilization rate, σ P is the standard deviation of pH data, σ U is the standard deviation of ozone utilization efficiency.

8. A control system for food purification, characterized in that: include: Data collection module, data analysis module and data control module; Wherein, the data collection module is used to collect initial ozone purification data of the ozone reaction experiment through a sensor, and pre-process the initial ozone purification data to obtain ozone purification data; The data analysis module is used to perform data analysis on the ozone purification data to obtain an ozone correlation coefficient, wherein the ozone correlation coefficient includes an ozone temperature coefficient and an ozone pH coefficient, wherein the ozone temperature coefficient is used to quantify the correlation between ozone utilization rate and temperature, and the ozone pH coefficient is used to quantify the correlation between ozone utilization rate and pH data; The data control module is used to perform a comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index, and at the same time obtain a control strategy based on the comprehensive ozone evaluation index, and send the control strategy to a preset person for processing.

9. A control system for food purification as claimed in claim 8, characterized in that: The specific steps of the comprehensive ozone assessment are as follows: Obtaining a weight distribution factor corresponding to an ozone temperature coefficient and an ozone pH coefficient from a preset database, wherein the weight distribution factor includes an ozone temperature weight and an ozone pH weight; Obtaining a comprehensive ozone evaluation index according to the weight distribution factor, the ozone temperature coefficient and the ozone pH coefficient, wherein the comprehensive ozone evaluation index is used to evaluate the correlation between temperature and pH value and ozone utilization rate; The comprehensive ozone assessment index is calculated using the following formula: In the formula, I U is the comprehensive ozone evaluation index of the ozone reaction experiment in the food purification room, R T is the ozone temperature coefficient, ω T is the ozone temperature weight, R PH is the ozone pH coefficient, ω PH is the ozone pH weight; The steps for formulating the control strategy are as follows: Obtaining a preset comprehensive ozone assessment threshold and a preset ozone utilization rate from a preset database; The comprehensive ozone assessment index is compared with the preset comprehensive ozone assessment threshold; If the comprehensive ozone assessment index is greater than the preset comprehensive ozone assessment threshold, a control strategy is generated according to the ozone correlation coefficient and the preset ozone utilization rate, wherein the control strategy includes a temperature control strategy and a pH value control strategy, and the control strategy is used to achieve the purpose of improving the ozone utilization rate by adjusting the temperature data or the pH data; If the comprehensive ozone assessment index is not greater than the preset comprehensive ozone assessment threshold, no processing is performed; The specific method of the temperature control strategy is: If the ozone temperature coefficient is positive, the ozone utilization rate is increased by increasing the temperature of the ozone reaction experiment to the temperature control parameter; If the ozone temperature coefficient is negative, the ozone utilization rate is increased by lowering the temperature of the ozone reaction experiment to the temperature control parameter; If the ozone temperature coefficient is zero, the temperature of the ozone reaction experiment will not be regulated; The temperature control parameters are calculated using the following formula: Where, T new is the temperature control parameter, T cur is the temperature data before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, ε1 is the temperature correction factor; The specific method of the pH value control strategy is: If the ozone pH coefficient is positive, the ozone utilization rate is increased by increasing the pH value of the ozone reaction experiment to the pH control parameter; If the ozone pH coefficient is negative, the ozone utilization rate is increased by lowering the pH value of the ozone reaction experiment to the pH control parameter; If the ozone pH coefficient is zero, the pH value of the ozone reaction experiment will not be regulated; The pH control parameter is calculated using the following formula: Where, pH new is the pH control parameter, pH cur is the pH value before adjustment, U tar is the preset ozone utilization rate threshold, U cur is the ozone utilization rate, and ε2 is the pH correction factor.

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