Sea-buckthorn concentrated juice evaporation temperature optimization control system

Abstract

The invention relates to the technical field of industrial data control, in particular to a hippophae rhamnoides concentrated juice evaporation temperature optimization control system, which comprises a memory and a processor, and is characterized in that the processor executes a computer program stored in the memory; the method comprises the following steps: acquiring environment temperature data, vacuum degree data and an infrared image in a sea-buckthorn concentration and evaporation process; the material influence degree is obtained according to the difference between the environment temperature data and the critical temperature value at each moment; a vacuum fluctuation index is obtained according to the difference between the vacuum degree data at each moment and the standard vacuum degree and the volatility of the vacuum degree data with abnormal conditions; performing region division according to the infrared image at each moment to obtain a coking influence degree; and regulating and controlling the temperature of the evaporator at the current moment according to the material influence degree, the coking influence degree and the vacuum fluctuation index. The device has a good temperature adjusting effect, damage to thermosensitive substances is reduced as much as possible, and the situation of local coking is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial data control, and particularly to an optimized control system for the evaporation temperature of seabuckthorn concentrated juice. Background Art

[0002] Seabuckthorn is a plant that grows in arid and cold regions. In recent years, it has gradually attracted attention in the healthy drink and health food markets due to its rich nutritional components such as vitamin C, antioxidant components, and fatty acids. In the production process of seabuckthorn concentrated juice, evaporation is a crucial technological process, which concentrates the seabuckthorn juice by evaporating water, reduces the transportation and storage costs, and at the same time enhances the flavor and nutritional value of the product.

[0003] During the evaporation process of seabuckthorn concentrated juice processing, temperature is an important parameter affecting the quality of seabuckthorn concentrated juice. Too high or too low temperature will have an adverse impact on the concentration effect and product quality. For example, too high temperature may lead to loss of nutritional components and damage of heat-sensitive components. In the actual processing process, there is often a situation where too much seabuckthorn is put in, resulting in uneven heating of the seabuckthorn in the evaporator, and even coking on the inner wall of the evaporator due to local overheating. And due to the lack of relevant targeted temperature optimization control, it will greatly affect the product quality of the final seabuckthorn concentrated juice. The existing method is to achieve temperature control by setting a fixed temperature value, which cannot fully consider the changes in the actual processing process, resulting in poor temperature control effect. Summary of the Invention

[0004] In order to solve the technical problem that the existing solution has a poor control effect in realizing temperature control by setting a fixed temperature value, the purpose of the present invention is to provide an optimized control system for the evaporation temperature of seabuckthorn concentrated juice, and the specific technical solution adopted is as follows: An optimized control system for the evaporation temperature of seabuckthorn concentrated juice includes a memory and a processor. The processor executes the computer program stored in the memory to implement the following steps: Obtain the ambient temperature data, vacuum degree data of the evaporator, and the infrared image inside the evaporator within a preset acquisition period before the current moment during the seabuckthorn concentration evaporation process; Analyze the temperature anomaly situation at each moment according to the difference between the ambient temperature data at each moment within a preset acquisition period before the current moment and the critical temperature value of the heat-sensitive substance, and obtain the degree of influence of the material at the current moment; Obtain the vacuum fluctuation index at the current moment according to the difference between the vacuum degree data at each moment within a preset acquisition period before the current moment and the standard vacuum degree, and the volatility of the vacuum degree data with abnormal situations; Based on the coincidence of the regional division results and the regional temperature distribution of the infrared images at each moment within a preset acquisition period before the current moment, the coking influence degree at the current moment is obtained; Based on the material influence degree and the coking influence degree at the current moment, combined with the vacuum fluctuation index, the temperature of the evaporator at the current moment is regulated.

[0005] Preferably, the method for analyzing the temperature anomaly situation at each moment based on the difference between the ambient temperature data and the critical temperature value of the heat-sensitive material at each moment within a preset acquisition period before the current moment to obtain the material influence degree at the current moment specifically includes: When the ambient temperature data at each moment within a preset acquisition period before the current moment is greater than the preset temperature threshold, the heat-sensitive abnormal moment is determined; Based on the continuous duration length of each heat-sensitive abnormal moment within the preset acquisition period, the continuous influence factor of each heat-sensitive abnormal moment is determined; According to the deviation value between the ambient temperature data at each heat-sensitive abnormal moment within the preset acquisition period and the preset critical temperature value of the heat-sensitive material, the temperature anomaly factor of each heat-sensitive abnormal moment is obtained; Based on the cumulative result of the product of the continuous influence factor and the temperature anomaly factor of each heat-sensitive abnormal moment, the material influence degree at the current moment is determined.

[0006] Preferably, the method for obtaining the temperature anomaly factor of each heat-sensitive abnormal moment according to the deviation value between the ambient temperature data at each heat-sensitive abnormal moment within the preset acquisition period and the critical temperature value of the heat-sensitive material specifically includes: The ambient temperature data includes the top temperature data and the bottom temperature data of the evaporator; Based on the difference between the top temperature data at each heat-sensitive abnormal moment and the preset critical temperature value of the heat-sensitive material, the first heat-sensitive temperature difference of each heat-sensitive abnormal moment is determined; based on the difference between the bottom temperature data at each heat-sensitive abnormal moment and the preset critical temperature value of the heat-sensitive material, the second heat-sensitive temperature difference of each heat-sensitive abnormal moment is determined; Based on the sum of the first heat-sensitive temperature difference and the second heat-sensitive temperature difference of each heat-sensitive abnormal moment, the temperature anomaly factor of each heat-sensitive abnormal moment is determined.

[0007] Preferably, the method for obtaining the vacuum fluctuation index at the current moment according to the difference between the vacuum degree data at each moment within a preset acquisition period before the current moment and the standard vacuum degree, and the volatility of the vacuum degree data with abnormal conditions specifically includes: Based on the comparison result between the vacuum degree data at each moment within a preset acquisition period before the current moment and the preset standard vacuum range, the vacuum abnormal moment is determined; Determine the deviation performance factor at the current moment based on the proportion of the number of vacuum abnormal moments within a preset acquisition period before the current moment; Determine the data dispersion factor at the current moment based on the degree of dispersion of the vacuum degree data of the vacuum abnormal moments within a preset acquisition period before the current moment; Determine the vacuum fluctuation index at the current moment based on the product of the deviation performance factor and the data dispersion factor at the current moment.

[0008] Preferably, obtaining the coking influence degree at the current moment according to the coincidence situation of the region division results and the region temperature distribution situation of the infrared images at each moment within a preset acquisition period before the current moment specifically includes: Perform threshold segmentation on the infrared images at each moment and perform screening to obtain suspected coking pixel points and normal evaporation pixel points; Determine the coking temperature anomaly factor at the current moment based on the ratio between the average temperature value of all suspected coking pixel points and the average temperature value of all normal evaporation pixel points in the infrared image at the current moment; Obtain the coking overlap factor at the current moment according to the overlap situation between the suspected coking pixel points in the infrared images at each moment within a preset acquisition period before the current moment; Determine the coking influence degree at the current moment based on the product of the coking temperature anomaly factor and the coking overlap factor at the current moment.

[0009] Preferably, obtaining the coking overlap factor at the current moment according to the overlap situation between the suspected coking pixel points in the infrared images at each moment within a preset acquisition period before the current moment specifically includes: Obtain the pixel point sets of each moment composed of the suspected coking pixel points in the infrared images at each moment, and use the proportion of the number of pixel points in the intersection between all the pixel point sets as the coking overlap factor at the current moment.

[0010] Preferably, performing threshold segmentation on the infrared images at each moment and performing screening to obtain suspected coking pixel points and normal evaporation pixel points specifically includes: Use the Otsu threshold segmentation method to segment the infrared images at each moment, and regard the pixel points in the infrared image that are greater than or equal to the threshold as suspected coking pixel points, and regard the pixel points in the infrared image that are less than the threshold as normal evaporation pixel points.

[0011] Preferably, performing temperature regulation on the evaporator at the current moment according to the material influence degree and the coking influence degree at the current moment, in combination with the vacuum fluctuation index, specifically includes: Obtain the temperature adjustment coefficient at the current moment according to the material influence degree and the coking influence degree at the current moment, in combination with the vacuum fluctuation index; Obtain the highest temperature value and the normal temperature range during the seabuckthorn concentration evaporation process; use the temperature adjustment coefficient and the normal temperature range, and combine the highest temperature value to control the temperature of the evaporator at the current moment.

[0012] Preferably, obtaining the temperature adjustment coefficient at the current moment according to the degree of influence of the material and the degree of coking influence at the current moment, and combining the vacuum fluctuation index specifically includes: Take the vacuum fluctuation index at the current moment as the first weight corresponding to the degree of coking influence, take the negative correlation coefficient of the vacuum fluctuation index at the current moment as the second weight corresponding to the degree of influence of the material, and use the first weight and the second weight to perform weighted summation and normalization processing on the degree of coking influence and the degree of influence of the material to obtain the temperature adjustment coefficient at the current moment.

[0013] Preferably, using the temperature adjustment coefficient and the normal temperature range, and combining the highest temperature value to control the temperature of the evaporator at the current moment specifically includes: Calculate the integer result of the product of the temperature adjustment coefficient at the current moment and the temperature difference in the normal temperature range to obtain the temperature adjustment degree at the current moment, and use the difference between the highest temperature value in the seabuckthorn concentration evaporation process and the temperature adjustment degree as the adjusted temperature value of the evaporator at the current moment.

[0014] The embodiments of the present invention have at least the following beneficial effects: The present invention first performs data collection including ambient temperature data, vacuum degree data, and infrared images, providing a data basis for subsequent feature analysis processes in multiple aspects. First, in terms of the seabuckthorn substance itself, it is necessary to consider the destructive effect of high temperature on the thermosensitive substances contained in seabuckthorn, that is, by analyzing the difference between the ambient temperature data and the critical value, analyzing the temperature anomaly at each moment, and quantifying the degree of influence of the material of the thermosensitive substances. Second, in terms of the feeding amount during the evaporation process, it is necessary to consider that when the feeding amount is excessive, it may cause pressure fluctuations in the vacuum system, analyze the difference between the vacuum degree data and the standard vacuum degree, and the fluctuation situation of the collected vacuum degree data, and quantify the vacuum fluctuation index. Third, considering that the pressure fluctuation in the vacuum system will also cause a temperature gradient, resulting in the precipitation or coking of solids, it is necessary to analyze the coking influence degree of the coking in the evaporator. Finally, through the deviation vacuum fluctuation degree, the real-time influence degree of the thermosensitive substances and the local coking influence degree at the current moment are weighed, and the temperature of the evaporator at the current moment is controlled, which can comprehensively consider the objective feature performances in multiple aspects such as the environment, has a good temperature adjustment effect, and minimizes the damage of thermosensitive substances and avoids the occurrence of local coking. Description of the Drawings

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0016] Figure 1 is a flowchart of the steps of a method for optimizing the evaporation temperature of seabuckthorn concentrated juice provided by the present invention; Figure 2 is a flowchart of the steps of a method for obtaining the degree of influence of materials at the current moment provided by the present invention; Figure 3 is a flowchart of the steps of a method for obtaining the vacuum fluctuation index at the current moment provided by the present invention; Figure 4 is a flowchart of the steps of a method for obtaining the degree of influence of coking at the current moment provided by the present invention; Figure 5 is a flowchart of the steps of a method for controlling the temperature of the evaporator at the current moment provided by the present invention. Detailed Embodiments

[0017] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, elaborate in detail on a seabuckthorn concentrated juice evaporation temperature optimization control system proposed according to the present invention, its specific implementation manner, structure, features, and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0019] The following will specifically describe the specific solution of a seabuckthorn concentrated juice evaporation temperature optimization control system provided by the present invention in conjunction with the accompanying drawings. Specifically, a seabuckthorn concentrated juice evaporation temperature optimization control system includes a memory and a processor. The processor executes the computer program stored in the memory to implement the steps of a method for optimizing the evaporation temperature of seabuckthorn concentrated juice.

[0020] Please refer to Figure 1 , which shows a flowchart of the steps of a method for optimizing the evaporation temperature of seabuckthorn concentrated juice provided by an embodiment of the present invention. The method includes the following steps: Step S100: Obtain the environmental temperature data, vacuum degree data of the evaporator, and the infrared images inside the evaporator within a preset acquisition period before the current moment during the sea buckthorn concentration evaporation process.

[0021] In the production process flow of sea buckthorn concentrated juice, it includes links such as raw material treatment, crushing and juicing, filtration, preheating, vacuum concentration, ingredient blending, sterilization, and filling. Among them, the evaporation link mainly adopts vacuum concentration and centrifugal thin-film evaporation technologies.

[0022] The evaporation process of sea buckthorn concentrated juice usually consists of an evaporator, a heater, a condenser, a variable-frequency vacuum pump, a control system, etc. The evaporator is the core component, which is used to heat the sea buckthorn concentrated juice to the evaporation temperature to evaporate its moisture; the heater provides heat energy; the condenser recovers the steam generated by evaporation and condenses it into a liquid; the variable-frequency vacuum pump maintains the negative pressure environment of the system to promote the evaporation process.

[0023] In this embodiment, real-time temperature data is obtained through intelligent temperature sensors at the bottom and top of the evaporator, the vacuum degree inside the evaporator is obtained in real time through the variable-frequency vacuum pump, and the thermal image of the inner wall of the evaporator is obtained through an infrared imager. Further, when implementing the monitoring of the current concentration evaporation process of sea buckthorn juice, real-time monitoring is carried out through a cycle with a fixed time length, that is, the preset acquisition period is set to 3 minutes, data is collected at each moment within the preset acquisition period, the time intervals between adjacent moments are equal, and each moment corresponds to two environmental temperature data, including the top temperature data and the bottom temperature data, one vacuum degree data, and one infrared image.

[0024] When optimizing the temperature of the evaporation process of sea buckthorn concentrated juice, multiple factors need to be fully considered. On the first hand, from the perspective of the sea buckthorn substance itself, the destructive effect of high temperature on the heat-sensitive substances contained in sea buckthorn needs to be considered. On the second hand, from the perspective of the feeding amount during the evaporation process, when the feeding amount is excessive, it may cause pressure fluctuations in the vacuum system, and the fluctuation of the vacuum degree data needs to be analyzed. On the third hand, considering that the pressure fluctuation of the vacuum system will also cause a temperature gradient, making the temperature at the bottom of the evaporator higher than that at the top, resulting in the precipitation or coking of solids, the coking effect inside the evaporator needs to be analyzed. Based on this feature analysis, in this embodiment, the characteristic performance of these three aspects is analyzed in sequence from step S200 to step S400.

[0025] Step S200: Analyze the temperature anomaly situation at each moment according to the difference between the environmental temperature data at each moment within the preset acquisition period before the current moment and the critical temperature value of the heat-sensitive substances, and obtain the degree of influence of the material at the current moment.

[0026] During the evaporation process of seabuckthorn concentrated juice, heat-sensitive components such as vitamin C and flavonoids in seabuckthorn are sensitive to high temperatures. Due to factors such as changes in the viscosity of the material and temperature fluctuations in the evaporation equipment, the temperature during the evaporation process deviates from the appropriate temperature range of the heat-sensitive materials in seabuckthorn, resulting in the destruction of the heat-sensitive materials in seabuckthorn and affecting the evaporation result of seabuckthorn concentrated juice. Among them, the increase in viscosity may lead to a decrease in heat exchange efficiency, resulting in local overheating and affecting temperature stability.

[0027] Under normal circumstances, for heat-sensitive substances, rapid degradation occurs above 60°C. For example, vitamin C begins to degrade at temperatures above 60°C, and the higher the temperature, the faster the degradation rate. Based on the high-temperature sensitivity characteristics of heat-sensitive substances, the evaporation process of seabuckthorn concentrated juice can be monitored in real time by using the highest temperature that the heat-sensitive substances can withstand as the critical temperature value.

[0028] It should be noted that this embodiment is for real-time monitoring of the evaporation process of seabuckthorn concentrated juice. Temperature is a key factor affecting the evaporation process of seabuckthorn concentrated juice. Therefore, when monitoring each acquisition cycle separately, if the temperature data at each moment within the preset acquisition cycle before the current moment do not exceed the critical temperature value of the heat-sensitive substance, it indicates that the temperature is relatively stable during this data acquisition cycle, and there will be no excessive temperature to damage the heat-sensitive substances in seabuckthorn for evaporation. At this time, there is no need to adjust the temperature at the current moment. Furthermore, this embodiment conducts multi-faceted feature analysis on the phenomenon of abnormal temperature that must exist within a preset acquisition cycle before the current moment.

[0029] In some embodiments, as Figure 2 shown, it shows the specific steps of the first aspect feature analysis, that is, the method for obtaining the degree of influence of the material at the current moment can be realized by steps S201 to S204.

[0030] Step S201, when the ambient temperature data at each moment within the preset acquisition cycle before the current moment is greater than the preset temperature threshold, determine the heat-sensitive abnormal moment.

[0031] The ambient temperature data at each moment within a preset acquisition cycle before the current moment includes the bottom temperature data of an evaporator and the top temperature data of an evaporator.

[0032] When the ambient temperature data at a certain moment is greater than the preset temperature threshold, it indicates that there is a temperature anomaly at the corresponding moment, and this moment is the heat-sensitive abnormal moment.

[0033] More specifically, when either the top temperature data or the bottom temperature data at a certain moment is greater than the preset temperature threshold, it indicates that there is a temperature anomaly inside the evaporator, and this moment is marked to obtain the thermosensitive anomaly moment. Among them, the preset temperature threshold can be the critical temperature value of the thermosensitive substance, that is, 60 °C, which means that when the ambient temperature data exceeds the critical temperature value of the thermosensitive substance, the temperature anomaly at the corresponding moment will affect the thermosensitive substance, and further affect the evaporation process of sea buckthorn concentrate.

[0034] For each thermosensitive anomaly moment, in order to comprehensively analyze the influence degree of temperature anomalies during the characteristic observation period, it is necessary to fully consider the horizontal and vertical influence situations. The horizontal analysis is to consider the damage to the thermosensitive substances in sea buckthorn caused by continuously staying at the temperature anomaly moment in terms of time, and the vertical analysis is to consider the situation of being in the thermosensitive anomaly at the same moment inside the evaporator at the same time, so as to comprehensively reflect the overall thermosensitive anomaly performance inside the evaporator. Specifically, step S202 is specifically the quantification process of horizontal analysis, step S203 is specifically the quantification process of vertical analysis, and step S204 is specifically the quantification process of comprehensive analysis.

[0035] Step S202: Based on the continuous duration length of each thermosensitive anomaly moment within the preset acquisition period, determine the continuous influence factor of each thermosensitive anomaly moment.

[0036] For any thermosensitive anomaly moment within the preset acquisition period before the current moment, normalize the number of consecutive thermosensitive anomaly moments to obtain the continuous influence factor of the any thermosensitive anomaly moment. It can be understood that the consecutive thermosensitive anomaly moments within the preset acquisition period can form a thermosensitive anomaly time period, which characterizes the duration length of the thermosensitive anomaly phenomenon. Within this time period, the continuous influence factor corresponding to each thermosensitive anomaly moment is the same.

[0037] Step S203: Obtain the temperature anomaly factor of each thermosensitive anomaly moment according to the deviation value between the ambient temperature data of each thermosensitive anomaly moment within the preset acquisition period and the preset critical temperature value of the thermosensitive substance.

[0038] Specifically, based on the difference between the top temperature data of each thermosensitive anomaly moment and the preset critical temperature value of the thermosensitive substance, determine the first thermosensitive temperature difference of each thermosensitive anomaly moment; based on the difference between the bottom temperature data of each thermosensitive anomaly moment and the preset critical temperature value of the thermosensitive substance, determine the second thermosensitive temperature difference of each thermosensitive anomaly moment; based on the sum of the first thermosensitive temperature difference and the second thermosensitive temperature difference of each thermosensitive anomaly moment, determine the temperature anomaly factor of each thermosensitive anomaly moment.

[0039] More specifically, in this embodiment, the preset critical temperature value of the heat-sensitive substance is 60 °C. The first thermosensitive temperature difference at each thermosensitive abnormal moment is the difference between the top temperature data at the corresponding moment and the critical temperature value, indicating the degree of difference in which the top of the evaporator exceeds the critical temperature value at the corresponding moment. The second thermosensitive temperature value at each thermosensitive abnormal moment is the difference between the bottom temperature data at the corresponding moment and the critical temperature value, indicating the degree of difference in which the bottom of the evaporator exceeds the critical temperature value at the corresponding moment.

[0040] Finally, by synthesizing the temperature difference degrees at the top and bottom of the evaporator at the same thermosensitive abnormal moment respectively, calculate the cumulative sum of the first thermosensitive temperature difference and the second thermosensitive temperature difference at the same thermosensitive abnormal moment, and perform normalization processing to obtain the temperature anomaly factor at the same thermosensitive abnormal moment, which characterizes the overall temperature anomaly degree at a thermosensitive abnormal moment. Among them, the method of normalization processing is a well-known technology and will not be introduced in detail here.

[0041] Step S204: Determine the degree of influence on the material at the current moment based on the cumulative result of the product between the continuous influence factor and the temperature anomaly factor at each thermosensitive abnormal moment.

[0042] First, calculate the product between the continuous influence factor and the temperature anomaly factor at each thermosensitive abnormal moment, and then sum up the products corresponding to all thermosensitive abnormal moments within the preset acquisition period before the current moment to obtain the degree of influence on the material at the current moment.

[0043] The degree of influence on the material comprehensively characterizes the abnormal situation in which the heat-sensitive substances in sea buckthorn are affected by temperature due to the existence of temperature anomalies before the current moment.

[0044] Step S300: Obtain the vacuum fluctuation index at the current moment based on the difference between the vacuum degree data at each moment within the preset acquisition period before the current moment and the standard vacuum degree, and the volatility of the vacuum degree data with abnormal conditions.

[0045] In terms of the evaporation process of sea buckthorn concentrated juice, affected by excessive feeding during charging, a large amount of water evaporates instantaneously, causing pressure fluctuations in the vacuum system, which in turn leads to an increase in boiling point and a temperature gradient, resulting in the bottom temperature of the evaporator being higher than the top temperature, causing solid precipitation or coking. Based on this characteristic, first analyze the influence of vacuum degree fluctuations caused by excessive material input.

[0046] In some embodiments, as Figure 3 shown, which shows the specific steps of the second aspect feature analysis, that is, the method for obtaining the vacuum fluctuation index at the current moment can be realized by steps S301 to S304.

[0047] Step S301: Determine the vacuum anomaly moment based on the comparison results between the vacuum degree data at each moment within a preset acquisition period before the current moment and the preset standard vacuum range.

[0048] It should be noted that the preset standard vacuum range refers to the normal vacuum degree range that needs to be maintained in the evaporator during the evaporation process of seabuckthorn concentrated juice. The implementer needs to set it according to the specific implementation scenario. In this embodiment, the standard vacuum range is that the value of the vacuum degree data is within the interval of 2.98 to 3.21 kPa. When the vacuum degree data is within this reasonable vacuum interval, it indicates that the vacuum degree data is normal and meets the requirements of the current seabuckthorn concentrated juice evaporation process. When the vacuum degree data in the evaporator fluctuates outside the reasonable vacuum interval, it may indicate that the vacuum fluctuates due to excessive feeding, which may affect the evaporation process of seabuckthorn concentrated juice.

[0049] Specifically, for each moment within the preset acquisition period before the current moment, determine the moment corresponding to the value of the vacuum degree data not within the standard vacuum range as the vacuum anomaly moment, which characterizes that the vacuum deviates from the reasonable range and generates a certain fluctuation phenomenon.

[0050] Step S302: Determine the deviation performance factor at the current moment based on the proportion of the number of vacuum anomaly moments within the preset acquisition period before the current moment.

[0051] Take the ratio of the number of all vacuum anomaly moments within the preset acquisition period before the current moment to the number of all moments within the preset acquisition period as the deviation performance factor at the current moment, which reflects the abnormal performance degree of the vacuum degree data deviating from the reasonable range within the preset acquisition period. The larger the value of the deviation performance factor, the more moments with abnormal vacuum fluctuations exist before the current moment, and thus the greater the impact of the feed rate on the current evaporation process.

[0052] Step S303: Determine the data dispersion factor at the current moment based on the dispersion degree of the vacuum degree data of the vacuum anomaly moments within the preset acquisition period before the current moment.

[0053] Specifically, take the standard deviation of the vacuum degree data of all vacuum anomaly moments within the preset acquisition period before the current moment as the data dispersion factor at the current moment. The data dispersion factor reflects the dispersion degree of the vacuum degree data of the vacuum anomaly moments within this period. The larger the value of the data dispersion factor, the greater the data fluctuation within the preset acquisition period before the current moment.

[0054] Step S304: Determine the vacuum fluctuation index at the current moment based on the product of the deviation performance factor and the data dispersion factor at the current moment.

[0055] Specifically, the normalized value of the product of the deviation performance factor and the data dispersion factor at the current moment is used as the vacuum fluctuation index at the current moment. The vacuum fluctuation index comprehensively reflects the abnormal fluctuation of the current data volatility from two aspects: the moment distribution data with vacuum deviation phenomenon and the data fluctuation degree with vacuum deviation phenomenon.

[0056] Step S400: Obtain the coking influence degree at the current moment according to the coincidence of the region division results and the regional temperature distribution of the infrared images at each moment within the preset acquisition period before the current moment.

[0057] The input of excessive materials will not only cause the fluctuation of the vacuum, resulting in too high bottom temperature and the occurrence of coking, but also prevent the formation of a uniform thin liquid film in the evaporator, leading to a liquid film thickness higher than the ideal value. Due to the too thick liquid film, the heat transfer coefficient is significantly reduced, the internal materials are heated with a lag due to the increase in thermal resistance, and local overheating may cause coking on the outside. Based on this feature, by analyzing the characteristic distribution of the infrared images in the evaporator, the coking situation caused by possible local overheating in the evaporator is quantitatively measured.

[0058] In some embodiments, as Figure 4 shown, it shows the specific process of the feature analysis of the third aspect, that is, the method for obtaining the coking influence degree at the current moment can be implemented by steps S401 to S404.

[0059] Step S401: Perform threshold segmentation on the infrared images at each moment and screen to obtain suspected coking pixel points and normal evaporation pixel points.

[0060] Use the Otsu threshold segmentation method to segment the infrared images at each moment. The pixel points in the infrared image that are greater than or equal to the threshold are regarded as suspected coking pixel points, and the pixel points in the infrared image that are less than the threshold are regarded as normal evaporation pixel points. The closed area composed of the suspected coking pixel points can be regarded as a local area where coking is suspected to exist.

[0061] When there is local coking in the evaporator, the temperature value at the corresponding position is relatively high, and the temperature values of other normal parts are relatively low and within the normal temperature range. Therefore, when performing threshold segmentation on the infrared image corresponding to each moment, the part exceeding the threshold belongs to the suspected coking pixel points where coking may exist, and the part less than the threshold belongs to the normal evaporation pixel points under normal conditions. It should be noted that the Otsu threshold segmentation method is a well-known technology and will not be introduced in detail here. The threshold for division is also obtained through this segmentation method.

[0062] Step S402 : determining a coking temperature anomaly factor at the current moment based on a ratio between an average temperature value of all suspected coking pixels and an average temperature value of all normal evaporation pixels in the infrared image at the current moment.

[0063] The first step is to calculate the average temperature value of all suspected coking pixels in the infrared image at the current moment as the first mean value corresponding to the current moment, reflecting the temperature performance of suspected coking in the infrared image at the current moment.

[0064] The second step is to calculate the average temperature value of all normal evaporation pixels in the infrared image at the current moment as the second mean value corresponding to the current moment, which reflects the temperature performance of the normal phenomenon in the infrared image at the current moment.

[0065] The third step is to calculate the ratio of the first mean and the second mean at the current moment to obtain the coking temperature anomaly factor at the current moment, which represents the comparison result between the abnormal temperature distribution and the normal temperature distribution in the evaporator at the current moment. The larger the value of the coking temperature anomaly factor is, the higher the local temperature of the local area where coking may occur in the evaporator at the current moment, which further indicates that the existing temperature anomaly has a greater impact on the evaporation process of the sea buckthorn concentrated juice.

[0066] Step S403 : obtaining a focus overlap factor at the current moment according to the overlap between suspected focus pixels in the infrared image at each moment in a preset acquisition period before the current moment.

[0067] Based on the characteristics that the focused area will be relatively persistent in a certain area, or even gradually expand, the overlap between the local areas suspected of having the focusing phenomenon in the preset acquisition cycle at the current moment is analyzed. Specifically, the suspected focused pixels in the infrared image at each moment are obtained to form a pixel set at each moment, and the proportion of the number of pixels in the intersection between the pixel sets at all moments is used as the focus overlap factor at the current moment. The proportion can be the ratio of the number of pixels contained in the intersection between the pixel sets at all moments to the total number of pixels in the infrared image.

[0068] It can be understood that a corresponding set of pixel points is obtained at each moment in the preset acquisition period before the current moment, representing the area of the local region where coking may exist at each moment, and then analyzing the overlap of all possible coking phenomena in the current period to reflect the abnormal impact of the suspected coking phenomenon at the moment.

[0069] When the value of the coking overlap factor is larger, it indicates that the overlapping area is larger at this time, which means that the coking phenomenon in the current cycle covers a larger area and is more serious. Furthermore, it indicates that the starting time of the coking phenomenon is earlier and the coking phenomenon lasts for a longer time. When the value of the coking overlap factor is smaller, it indicates that the overlapping area is smaller at this time, and further indicates that the coking phenomenon in the current cycle covers a smaller area and is less serious.

[0070] Step S404: Determine the coking influence degree at the current moment based on the product of the coking temperature anomaly factor and the coking overlap factor at the current moment.

[0071] By comprehensively considering the characteristic distribution of the suspected coking phenomenon at the current moment and the persistence characteristics of the suspected coking phenomenon at multiple consecutive moments, the influence degree is quantitatively measured. Specifically, the product of the coking temperature anomaly factor and the coking overlap factor at the current moment is used as the coking influence degree at the current moment. The coking influence degree characterizes the current temperature distribution situation and the influence degree of the possible coking phenomenon in the evaporator on the evaporation process of sea buckthorn concentrated juice.

[0072] Step S500: According to the material influence degree and the coking influence degree at the current moment, and in combination with the vacuum fluctuation index, perform temperature regulation on the evaporator at the current moment.

[0073] Overfeeding of materials will change the material flow balance in the evaporator. Especially, the high-fiber or oil components in sea buckthorn will form a non-uniform distribution during the evaporation process, which may cause a sudden increase in local resistance, resulting in abnormal fluctuations in the vacuum degree and an increase in the temperature difference inside and outside the material. Furthermore, it will trigger the occurrence of local coking, affecting the output quality of the final sea buckthorn concentrated juice. At the same time, it is also necessary to consider the damage to heat-sensitive substances caused by uneven temperature during the whole process.

[0074] Based on this characteristic, when determining the degree of temperature adjustment, the larger the value of the vacuum fluctuation index at the current moment, the more likely it indicates that the material input amount is excessive, resulting in excessive evaporation of water in the material, causing vacuum fluctuations and generating an obvious temperature gradient, that is, the temperature distribution is uneven. At this time, more attention should be paid to the magnitude of the coking influence degree at the current moment, that is, the temperature gradient phenomenon caused by vacuum fluctuations may produce solid matter coking, which has a relatively large impact on the evaporation process of sea buckthorn concentrated juice. Further, at this time, compared with the local coking phenomenon, the attention to the material influence degree is relatively small.

[0075] When the vacuum fluctuation index value is smaller, it means that the influence of excess material is smaller, that is, there may not be a large temperature gradient. In this case, attention should be paid to the real-time influence of the thermosensitive substances at the current moment. That is, although there may be no influence caused by excessive material input, even if the material input is normal, there may be other objective factors such as excessive temperature that affect the thermosensitive substances in sea buckthorn.

[0076] In some embodiments, as Figure 5 As shown, the method for controlling the temperature of the evaporator at the current moment can be implemented by steps S501 to S502.

[0077] Step S501 : obtaining the temperature adjustment coefficient at the current moment according to the degree of material influence and coking influence at the current moment and in combination with the vacuum fluctuation index.

[0078] The vacuum fluctuation index at the current moment is used as the first weight corresponding to the degree of coking influence, and the negative correlation coefficient of the vacuum fluctuation index at the current moment is used as the second weight corresponding to the degree of material influence. The coking influence degree and the material influence degree are weightedly summed and normalized using the first weight and the second weight to obtain the temperature regulation coefficient at the current moment.

[0079] As a specific example, the temperature adjustment coefficient at the current moment can be expressed as: in, Indicates the temperature adjustment coefficient at the current moment, Indicates the vacuum fluctuation index at the current moment, Indicates the degree of coking influence at the current moment, Indicates the degree of influence of the material at the current moment, and norm represents the normalization function.

[0080] Further, That is, the degree of coking impact The corresponding first weight, The degree of material impact The corresponding second weight is that the larger the first weight, the smaller the second weight. This reflects that when the vacuum fluctuation phenomenon is more severe, more attention should be paid to the impact of coking in the evaporator on the evaporation process. The smaller the first weight, the larger the second weight. This reflects that when the vacuum fluctuation phenomenon is less severe, the possibility of coking is less likely, and more attention should be paid to the impact of temperature changes.

[0081] Step S502, obtaining the maximum temperature value and normal temperature range during the sea buckthorn concentrated evaporation process; using the temperature adjustment coefficient and the normal temperature range, combined with the maximum temperature value, to control the temperature of the evaporator at the current moment.

[0082] In this embodiment, the corresponding temperature set value is dynamically adjusted in combination with the temperature control range during the evaporation process of seabuckthorn concentrated juice, so as to avoid the destruction of heat-sensitive substances and local coking during the evaporation process of different seabuckthorn concentrated juices.

[0083] The integer result of the product of the temperature adjustment coefficient at the current moment and the temperature difference in the normal temperature range is calculated to obtain the temperature adjustment degree at the current moment, and the difference between the highest temperature value during the seabuckthorn concentration evaporation process and the temperature adjustment degree is used as the temperature value of the evaporator after adjustment at the current moment.

[0084] As a specific example, the adjusted temperature value can be expressed as , represents the highest temperature value in the normal temperature range, that is, 60 °C, represents the temperature adjustment coefficient at the current moment, represents the temperature difference in the normal temperature range, that is, 10 °C.

[0085] It should be noted that according to the data of the seabuckthorn concentrated juice evaporation process, the normal temperature range of the evaporation process is usually between 50 °C and 60 °C, that is, this temperature region is the normal temperature range set in this embodiment, and the implementer needs to set it according to the specific implementation scenario.

[0086] In this embodiment, the degree of temperature adjustment required is determined by the degree of characteristic manifestation of various aspects during the evaporation process at the current moment, and the highest temperature value is adjusted. When the temperature adjustment coefficient at the current moment is larger, it indicates that the temperature non-uniformity situation presented by the influence of multi-directional factors during the current evaporation process is more serious. In this way, rapid heating will cause internal thermal expansion differences in the material, resulting in local coking or the destruction of the heat-sensitive substance components therein. Here, the heating rate can be slowed down to reduce the internal and external temperature difference and the accumulation of thermal stress, and avoid local coking or the destruction of heat-sensitive components.

[0087] In some embodiments, if the value of the temperature adjustment coefficient at the current moment is relatively large, it indicates that the data abnormality situation of the evaporation process at the current moment is relatively large. In necessary moments, an alarm can also be set to remind relevant staff to conduct an abnormality investigation on the current evaporation process. For example, when the value of the current temperature adjustment coefficient is greater than the preset temperature threshold, an alarm is issued, and the value of the temperature threshold can be 0.9. It should be noted that the larger the value of the temperature adjustment coefficient, the greater the possibility of temperature abnormality at present. If the current temperature abnormality situation exceeds a certain degree, relevant staff need to be reminded to investigate the current evaporation process and other operations.

[0088] In summary, the present invention can determine the real-time influence degree of heat-sensitive substances at the current moment by analyzing the influence degree of heat-sensitive substances at the abnormal heat-sensitive moments during the evaporation process of historical sea buckthorn concentrated juice; and consider the influence caused by excessive input of materials, and then determine the real-time deviation vacuum fluctuation degree and the local coking influence degree at the current moment; based on the deviation vacuum fluctuation degree, weigh the real-time influence degree of heat-sensitive substances and the local coking influence degree at the current moment, and determine the adjustment coefficient of the temperature setting at the current moment; thus, from the perspective of slowing down the heating rate and reducing the accumulation of thermal stress, determine the optimal temperature setting value at the current moment, and act on the current system to achieve the purpose of controlling the temperature of the evaporation process; dynamically adjust the evaporation temperature according to the comprehensive influence during the evaporation process of sea buckthorn juice, so as to minimize the damage of heat-sensitive substances and avoid the occurrence of local coking.

[0089] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An optimized control system for the evaporation temperature of sea buckthorn concentrated juice, comprising a memory and a processor, characterized in that, The processor executes the computer program stored in the memory to implement the following steps: Obtain the ambient temperature data, vacuum degree data of the evaporator, and infrared images inside the evaporator within a preset acquisition period before the current moment during the seabuckthorn concentrate evaporation process; Analyze the temperature anomaly situation at each moment based on the difference between the ambient temperature data at each moment within the preset acquisition period before the current moment and the critical temperature value of the heat-sensitive substance, and obtain the degree of influence on the material at the current moment; Obtain the vacuum fluctuation index at the current moment based on the difference between the vacuum degree data at each moment within the preset acquisition period before the current moment and the standard vacuum degree, and the volatility of the vacuum degree data with abnormal situations; Obtain the degree of influence of coking at the current moment based on the coincidence of the regional division results and the regional temperature distribution of the infrared images at each moment within the preset acquisition period before the current moment; Perform temperature regulation on the evaporator at the current moment according to the degree of influence on the material and the degree of influence of coking at the current moment, in combination with the vacuum fluctuation index.

2. The optimized control system for the evaporation temperature of sea buckthorn concentrated juice according to claim 1, wherein The step of analyzing the temperature anomaly situation at each moment based on the difference between the ambient temperature data at each moment within the preset acquisition period before the current moment and the critical temperature value of the heat-sensitive substance, and obtaining the degree of influence on the material at the current moment specifically includes: Based on the ambient temperature data at each moment within the preset acquisition period before the current moment being greater than the preset temperature threshold, determine the heat-sensitive anomaly moment; Based on the continuous duration length of each heat-sensitive anomaly moment within the preset acquisition period, determine the continuous influence factor of each heat-sensitive anomaly moment; Obtain the temperature anomaly factor of each heat-sensitive anomaly moment according to the deviation value between the ambient temperature data at each heat-sensitive anomaly moment within the preset acquisition period and the preset critical temperature value of the heat-sensitive substance; Based on the cumulative result of the product of the continuous influence factor and the temperature anomaly factor of each heat-sensitive anomaly moment, determine the degree of influence on the material at the current moment.

3. An optimized control system for the evaporation temperature of sea buckthorn concentrated juice according to claim 2, characterized in that, The step of obtaining the temperature anomaly factor of each heat-sensitive anomaly moment according to the deviation value between the ambient temperature data at each heat-sensitive anomaly moment within the preset acquisition period and the critical temperature value of the heat-sensitive substance specifically includes: The ambient temperature data includes the top temperature data and the bottom temperature data of the evaporator; Based on the difference between the top temperature data at each heat-sensitive anomaly moment and the preset critical temperature value of the heat-sensitive substance, determine the first heat-sensitive temperature difference of each heat-sensitive anomaly moment; based on the difference between the bottom temperature data at each heat-sensitive anomaly moment and the preset critical temperature value of the heat-sensitive substance, determine the second heat-sensitive temperature difference of each heat-sensitive anomaly moment; Based on the sum of the first heat-sensitive temperature difference and the second heat-sensitive temperature difference of each heat-sensitive anomaly moment, determine the temperature anomaly factor of each heat-sensitive anomaly moment.

4. The optimized control system for the evaporation temperature of seabuckthorn concentrated juice according to claim 1, wherein The step of obtaining the vacuum fluctuation index at the current moment based on the difference between the vacuum degree data at each moment within the preset acquisition period before the current moment and the standard vacuum degree, and the volatility of the vacuum degree data with abnormal situations specifically includes: Determine the vacuum anomaly moment based on the comparison result between the vacuum degree data at each moment within a preset acquisition period before the current moment and the preset standard vacuum range; Determine the deviation performance factor at the current moment based on the proportion of the number of vacuum anomaly moments within a preset acquisition period before the current moment; Determine the data dispersion factor at the current moment based on the degree of dispersion of the vacuum degree data of the vacuum anomaly moments within a preset acquisition period before the current moment; Determine the vacuum fluctuation index at the current moment based on the product of the deviation performance factor and the data dispersion factor at the current moment.

5. The optimized control system for the evaporation temperature of seabuckthorn concentrated juice according to claim 1, wherein Obtain the coking influence degree at the current moment according to the coincidence of the region division results and the region temperature distribution of the infrared images at each moment within a preset acquisition period before the current moment, specifically including: Perform threshold segmentation on the infrared images at each moment and screen to obtain suspected coking pixel points and normal evaporation pixel points; Determine the coking temperature anomaly factor at the current moment based on the ratio between the average temperature value of all suspected coking pixel points and the average temperature value of all normal evaporation pixel points in the infrared image at the current moment; Obtain the coking overlap factor at the current moment according to the overlap situation between the suspected coking pixel points in the infrared images at each moment within a preset acquisition period before the current moment; Determine the coking influence degree at the current moment based on the product of the coking temperature anomaly factor and the coking overlap factor at the current moment.

6. The optimized control system for the evaporation temperature of seabuckthorn concentrated juice according to claim 5, wherein The obtaining of the coking overlap factor at the current moment according to the overlap situation between the suspected coking pixel points in the infrared images at each moment within a preset acquisition period before the current moment specifically includes: Obtain the pixel point sets at each moment formed by the suspected coking pixel points in the infrared images at each moment, and use the proportion of the number of pixel points in the intersection between all the pixel point sets as the coking overlap factor at the current moment.

7. An optimized control system for the evaporation temperature of seabuckthorn concentrated juice according to claim 5, characterized in that, The performing of threshold segmentation on the infrared images at each moment and screening to obtain suspected coking pixel points and normal evaporation pixel points specifically includes: Use the Otsu threshold segmentation method to segment the infrared images at each moment, and regard the pixel points greater than or equal to the threshold in the infrared image as suspected coking pixel points, and regard the pixel points less than the threshold in the infrared image as normal evaporation pixel points.

8. An optimized control system for the evaporation temperature of seabuckthorn concentrated juice according to claim 1, characterized in that, Perform temperature regulation on the evaporator at the current moment according to the material influence degree and the coking influence degree at the current moment, in combination with the vacuum fluctuation index, specifically including: Obtain the temperature adjustment coefficient at the current moment according to the material influence degree and the coking influence degree at the current moment, in combination with the vacuum fluctuation index; Obtain the highest temperature value and the normal temperature range during the seabuckthorn concentration evaporation process; use the temperature adjustment coefficient and the normal temperature range, in combination with the highest temperature value, to perform temperature regulation on the evaporator at the current moment.

9. The optimized control system for the evaporation temperature of seabuckthorn concentrated juice according to claim 8, characterized in that The obtaining of the temperature adjustment coefficient at the current moment according to the material influence degree and the coking influence degree at the current moment, in combination with the vacuum fluctuation index specifically includes: Taking the vacuum fluctuation index at the current moment as the first weight corresponding to the coking influence degree, taking the negative correlation coefficient of the vacuum fluctuation index at the current moment as the second weight corresponding to the material influence degree, and using the first weight and the second weight to perform weighted summation and normalization processing on the coking influence degree and the material influence degree to obtain the temperature adjustment coefficient at the current moment.

10. A sea buckthorn concentrated juice evaporation temperature optimization control system according to claim 8, characterized in that, The temperature control of the evaporator at the current moment by using the temperature adjustment coefficient and the normal temperature range in combination with the highest temperature value specifically includes: Calculating the integer result of the product of the temperature adjustment coefficient at the current moment and the temperature difference in the normal temperature range to obtain the temperature adjustment degree at the current moment, and taking the difference between the highest temperature value in the seabuckthorn concentration evaporation process and the temperature adjustment degree as the adjusted temperature value of the evaporator at the current moment.

Images