A sea buckthorn concentrated juice evaporation temperature optimization control system

Abstract

The present application relates to the technical field of industrial data control, and particularly relates to a seabuckthorn concentrated juice evaporation temperature optimization control system, which comprises a memory and a processor, the processor executes the computer program stored in the memory to realize the following steps: obtaining environmental temperature data, vacuum degree data and infrared images in the seabuckthorn concentrated evaporation process; obtaining the material affected degree according to the difference between the environmental temperature data at each moment and the critical temperature value; obtaining the vacuum fluctuation index according to the difference between the vacuum degree data at each moment and the standard vacuum degree range and the volatility of the vacuum degree data in abnormal conditions; obtaining the coking affected degree according to the regional division result of the infrared images at each moment; and performing temperature regulation on the current moment evaporator according to the material affected degree, the coking affected degree and the vacuum fluctuation index. The present application has good temperature regulation effect, can minimize the damage of heat-sensitive substances and avoid the occurrence of local coking.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial data control, and in particular to a sea buckthorn concentrated juice evaporation temperature optimization control system. BACKGROUND

[0002] Sea buckthorn is a plant that grows in arid and cold regions. In recent years, it has gradually attracted attention in the health drink and health food market due to its rich vitamin C, antioxidant components, and fatty acid nutrients. In the production process of sea buckthorn concentrated juice, evaporation is a crucial process step. It concentrates sea buckthorn juice by evaporating water, reduces transportation and storage costs, and improves product flavor and nutritional value.

[0003] In the evaporation process of sea buckthorn concentrated juice processing, temperature is an important parameter affecting the quality of sea buckthorn concentrated juice. Too high or too low temperature will adversely affect the concentration effect and product quality. For example, too high temperature can cause loss of nutrients and damage to heat-sensitive components. In actual processing, there is often a situation of excessive sea buckthorn feeding, resulting in uneven heating of sea buckthorn in the evaporator, and even local overheating leading to evaporator inner wall coking. Due to the lack of relevant targeted temperature optimization control, the final product quality of sea buckthorn concentrated juice will be greatly affected. 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

[0004] In order to solve the technical problem of poor control effect of the existing scheme technology by setting a fixed temperature value to achieve temperature control, the purpose of the present application is to provide a sea buckthorn concentrated juice evaporation temperature optimization control system, and the technical solution adopted is as follows:

[0005] A sea buckthorn concentrated juice evaporation temperature optimization control system, comprising a storage and a processor, the processor executes the computer program stored in the storage to realize the following steps:

[0006] Obtain the environmental temperature data, vacuum degree data of the evaporator, and infrared image in the evaporator within a preset collection period before the current time in the sea buckthorn concentrated evaporation process;

[0007] According to the difference between the environmental temperature data at each time and the critical temperature value of the heat-sensitive substance within the preset collection period before the current time, analyze the temperature abnormality at each time, and obtain the material affected degree at the current time;

[0008] According to the difference between the vacuum degree data at each time and the standard vacuum degree range within the preset collection period before the current time, and the volatility of the vacuum degree data with abnormal conditions, obtain the vacuum fluctuation index at the current time;

[0009] According to the coincidence of the region division result and the temperature distribution of the region according to the infrared image of each time within the preset collection period before the current time, the coking influence degree of the current time is obtained;

[0010] According to the material affected degree and the coking influence degree of the current time, combined with the vacuum fluctuation index, the temperature of the evaporator of the current time is regulated.

[0011] Preferably, the difference between the environmental temperature data of each time within the preset collection period before the current time and the preset critical temperature value of the heat-sensitive material is analyzed to obtain the material affected degree of the current time, specifically including:

[0012] Based on the environmental temperature data of each time within the preset collection period before the current time being greater than the preset temperature threshold value, the heat-sensitive abnormal time is determined;

[0013] Based on the continuous duration length of each heat-sensitive abnormal time within the preset collection period, the continuous influence factor of each heat-sensitive abnormal time is determined;

[0014] According to the deviation value between the environmental temperature data of each heat-sensitive abnormal time within the preset collection period and the preset critical temperature value of the heat-sensitive material, the temperature abnormal factor of each heat-sensitive abnormal time is obtained;

[0015] Based on the product of the continuous influence factor and the temperature abnormal factor of each heat-sensitive abnormal time, the material affected degree of the current time is determined.

[0016] Preferably, the deviation value between the environmental temperature data of each heat-sensitive abnormal time within the preset collection period and the preset critical temperature value of the heat-sensitive material is obtained to obtain the temperature abnormal factor of each heat-sensitive abnormal time, specifically including:

[0017] The environmental temperature data includes the top temperature data and the bottom temperature data of the evaporator;

[0018] Based on the difference between the top temperature data of each heat-sensitive abnormal time and the preset critical temperature value of the heat-sensitive material, the first heat-sensitive temperature difference value of each heat-sensitive abnormal time is determined; based on the difference between the bottom temperature data of each heat-sensitive abnormal time and the preset critical temperature value of the heat-sensitive material, the second heat-sensitive temperature difference value of each heat-sensitive abnormal time is determined;

[0019] Based on the sum of the first heat-sensitive temperature difference value and the second heat-sensitive temperature difference value of each heat-sensitive abnormal time, the temperature abnormal factor of each heat-sensitive abnormal time is determined.

[0020] Preferably, the vacuum fluctuation index of the current moment is obtained according to the difference between the vacuum degree data of each moment in the preset collection period before the current moment and the standard vacuum range, and the volatility of the vacuum degree data of the abnormal situation, and specifically includes:

[0021] Determine the vacuum abnormal moment based on the comparison result of the vacuum degree data of each moment in the preset collection period before the current moment and the preset standard vacuum range.

[0022] Determine the deviation performance factor of the current moment based on the proportion of the number of vacuum abnormal moments in the preset collection period before the current moment.

[0023] Determine the data dispersion factor of the current moment based on the dispersion degree of the vacuum degree data of the vacuum abnormal moment in the preset collection period before the current moment.

[0024] Determine the vacuum fluctuation index of the current moment based on the product of the deviation performance factor and the data dispersion factor of the current moment.

[0025] Preferably, the coking influence degree of the current moment is obtained according to the coincidence of the region division result of the infrared image of each moment in the preset collection period before the current moment and the region temperature distribution, and specifically includes:

[0026] Threshold segmentation and screening are performed on the infrared image of each moment to obtain suspected coking pixel points and normal evaporation pixel points.

[0027] Determine the coking temperature abnormal factor of the current moment based on the ratio between the mean value of the temperature values of all suspected coking pixel points in the infrared image of the current moment and the mean value of the temperature values of all normal evaporation pixel points.

[0028] Obtain the coking overlap factor of the current moment according to the overlap between the suspected coking pixel points in the infrared image of each moment in the preset collection period before the current moment.

[0029] Determine the coking influence degree of the current moment based on the product of the coking temperature abnormal factor and the coking overlap factor of the current moment.

[0030] Preferably, the coking overlap factor of the current moment is obtained according to the overlap between the suspected coking pixel points in the infrared image of each moment in the preset collection period before the current moment, and specifically includes:

[0031] Obtain the pixel point set of each moment composed of suspected coking pixel points in the infrared image of each moment, and take the proportion of the number of pixel points in the intersection between all moment pixel point sets as the coking overlap factor of the current moment.

[0032] Preferably, the infrared image at each time is threshold segmented and screened to obtain suspected coking pixel points and normal evaporation pixel points, and specifically includes the following steps:

[0033] The infrared image at each time is segmented by using the Otsu threshold segmentation method, the pixel points in the infrared image greater than or equal to the threshold are regarded as suspected coking pixel points, and the pixel points in the infrared image less than the threshold are regarded as normal evaporation pixel points.

[0034] Preferably, the temperature of the evaporator at the current time is regulated according to the material affected degree and the coking affected degree at the current time, and in combination with the vacuum fluctuation index, and specifically includes the following steps:

[0035] The temperature regulation coefficient at the current time is obtained according to the material affected degree and the coking affected degree at the current time, and in combination with the vacuum fluctuation index.

[0036] The highest temperature value and the normal temperature interval in the sea buckthorn concentration evaporation process are obtained, the temperature of the evaporator at the current time is regulated by using the temperature regulation coefficient and the normal temperature interval, and in combination with the highest temperature value.

[0037] Preferably, the temperature regulation coefficient at the current time is obtained according to the material affected degree and the coking affected degree at the current time, and in combination with the vacuum fluctuation index, and specifically includes the following steps:

[0038] The vacuum fluctuation index at the current time is taken as a first weight corresponding to the coking affected degree, a negative correlation coefficient of the vacuum fluctuation index at the current time is taken as a second weight corresponding to the material affected degree, the coking affected degree and the material affected degree are weighted and summed by using the first weight and the second weight, and normalized processing is performed to obtain the temperature regulation coefficient at the current time.

[0039] Preferably, the temperature of the evaporator at the current time is regulated by using the temperature regulation coefficient and the normal temperature interval, and in combination with the highest temperature value, and specifically includes the following steps:

[0040] The integral result of the product of the temperature regulation coefficient at the current time and the temperature difference between the normal temperature interval is calculated to obtain the temperature adjustment degree at the current time, and the difference between the highest temperature value in the sea buckthorn concentration evaporation process and the temperature adjustment degree is taken as the adjusted temperature value of the evaporator at the current time.

[0041] The embodiment of the present application has at least the following beneficial effects:

[0042] The present application firstly carries out data collection including environmental temperature data, vacuum degree data and infrared image, to provide data basis for subsequent characteristic analysis process in multiple aspects. Firstly, from the sea buckthorn material itself, the damage influence of high temperature on the heat-sensitive substances contained in the sea buckthorn needs to be considered, that is, by analyzing the difference between the environmental temperature data and the critical value, the temperature abnormality at each moment is analyzed, and the influence degree of the heat-sensitive material is quantified. Secondly, from the feeding amount of the evaporation process, when the feeding amount is too large, it may cause pressure fluctuation of the vacuum system, and the difference between the vacuum degree data and the standard vacuum degree range is analyzed, and the fluctuation of the collected vacuum degree data is analyzed, and the vacuum fluctuation index is quantified. Thirdly, considering that the pressure fluctuation of the vacuum system will also cause temperature gradient, so that solid precipitation or coking phenomenon occurs, the coking influence degree of the coking influence of the evaporator inside needs to be analyzed. Finally, by weighing the real-time influence degree of the heat-sensitive material and the local coking influence degree at the moment through the deviation vacuum fluctuation degree, the temperature of the evaporator at the moment is regulated, which can comprehensively reflect the objective characteristics of the environment and other aspects, has good temperature regulation effect, and can minimize the damage of heat-sensitive substances and avoid the occurrence of local coking. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, a brief introduction will be given to the drawings needed in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0044] Figure 1 is a step flow chart of the sea buckthorn concentrated juice evaporation temperature optimization control method provided by the present application;

[0045] Figure 2 is a step flow chart of the method for obtaining the influence degree of the material at the moment provided by the present application;

[0046] Figure 3 is a step flow chart of the method for obtaining the vacuum fluctuation index at the moment provided by the present application;

[0047] Figure 4 is a step flow chart of the method for obtaining the coking influence degree at the moment provided by the present application;

[0048] Figure 5 is a step flow chart of the method for regulating the temperature of the evaporator at the moment provided by the present application. DETAILED DESCRIPTION

[0049] In order to further clarify the technical means and effects taken by the present application to achieve the predetermined inventive purpose, the specific implementation, structure, features and effects of a sea buckthorn concentrated juice evaporation temperature optimization control system according to the present application are described in detail below in combination with the drawings and preferred embodiments. 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.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0051] The specific scheme of a sea buckthorn concentrated juice evaporation temperature optimization control system provided by the present application is described below in combination with the drawings. Specifically, a sea buckthorn concentrated juice evaporation temperature optimization control system includes a memory and a processor, and the processor executes a computer program stored in the memory to realize the steps of a sea buckthorn concentrated juice evaporation temperature optimization control method.

[0052] Please refer to Figure 1 , which shows a step flowchart of a sea buckthorn concentrated juice evaporation temperature optimization control method provided by an embodiment of the present application, which includes the following steps:

[0053] Step S100, obtaining the environmental temperature data of the evaporator, the vacuum degree data and the infrared image in the evaporator within a preset collection period before the current time in the sea buckthorn concentrated evaporation process.

[0054] The production process of sea buckthorn concentrated juice includes raw material processing, crushing and juicing, filtering, preheating, vacuum concentration, batching, sterilization and filling, etc. The evaporation link mainly adopts vacuum concentration and centrifugal thin film evaporation technology.

[0055] The sea buckthorn concentrated juice evaporation process is usually composed 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 the water; the heater provides heat energy; the condenser recovers the steam generated by evaporation and condenses it into liquid; the variable frequency vacuum pump maintains the negative pressure environment of the system to promote the evaporation process.

[0056] In the present embodiment, real-time temperature data is obtained by intelligent temperature sensors at the bottom and top of the evaporator, real-time vacuum degree in the evaporator is obtained by a variable frequency vacuum pump, and thermal image of the inner wall of the evaporator is obtained by an infrared imager. Further, in the implementation of monitoring the evaporation process of the current sea buckthorn juice, real-time monitoring is performed in a fixed time length period, that is, the preset collection period is set to 3 minutes, data is collected at each time in the preset collection period, the time interval between adjacent times is equal, two environmental temperature data are obtained at each time, including top temperature data and bottom temperature data, one vacuum degree data and one infrared image.

[0057] In the optimization of the temperature of the evaporation process of the sea buckthorn concentrated juice, various factors need to be fully considered. First, from the sea buckthorn material itself, the damage of high temperature to the heat-sensitive substances contained in the sea buckthorn needs to be considered. Second, from the feeding amount of the evaporation process, it needs to be considered that excessive feeding may cause pressure fluctuation of the vacuum system, and the fluctuation of the vacuum degree data needs to be analyzed. Third, considering that the pressure fluctuation of the vacuum system will also cause temperature gradient, so that the bottom temperature of the evaporator is higher than the top temperature, causing solid precipitation or coking phenomenon, the coking influence in the evaporator needs to be analyzed. Based on this feature analysis, the present embodiment analyzes the feature performance of these three aspects from step S200 to step S400.

[0058] In step S200, the temperature abnormality at each time is analyzed according to the difference between the environmental temperature data at each time in the preset collection period before the current time and the critical temperature value of the heat-sensitive substance, and the affected degree of the material at the current time is obtained.

[0059] In the evaporation process of sea buckthorn concentrated juice, the heat-sensitive components such as vitamin C and flavonoids in sea buckthorn are sensitive to high temperature, which may cause the temperature to deviate from the suitable temperature range of heat-sensitive materials in sea buckthorn due to factors such as change of material viscosity and temperature fluctuation of evaporation equipment, and further cause the heat-sensitive materials in sea buckthorn to be destroyed, affecting the evaporation result of sea buckthorn concentrated juice. Among them, the increase of viscosity may reduce the heat exchange efficiency, thereby causing local overheating and affecting temperature stability.

[0060] Generally, for heat-sensitive substances, rapid degradation occurs above 60℃, for example, vitamin C begins to degrade at a high temperature above 60℃, and the higher the temperature, the faster the degradation rate. Based on the high-temperature sensitivity of heat-sensitive substances, the highest temperature that the heat-sensitive substances can withstand can be used as a critical temperature value to monitor the evaporation process of sea buckthorn concentrated juice in real time.

[0061] It should be noted that the embodiment is for real-time monitoring of the evaporation process of sea buckthorn concentrated juice, and temperature is a key factor affecting the evaporation process of sea buckthorn concentrated juice. Therefore, when monitoring each collection period, if the temperature data of each time in the preset collection period before the current time does not exceed the preset critical temperature value of the heat-sensitive substance, it indicates that the temperature in the data collection period is relatively stable, and there is no excessively high temperature to damage the heat-sensitive substance in the sea buckthorn for evaporation. At this time, the temperature at the current time does not need to be regulated. Further, the embodiment analyzes the characteristics of the phenomenon of abnormal temperature in a preset collection period before the current time in multiple aspects.

[0062] In some embodiments, as shown in FIG. 2, Figure 2 The specific steps of the first aspect feature analysis are shown in FIG. 2, that is, the method for obtaining the affected degree of the material at the current time can be realized by steps S201 to S204.

[0063] Step S201, determining a heat-sensitive abnormal time based on the fact that the environmental temperature data at each time in a preset collection period before the current time is greater than a preset temperature threshold.

[0064] The environmental temperature data at each time in a preset collection period before the current time includes bottom temperature data of an evaporator and top temperature data of an evaporator.

[0065] When the environmental temperature data at a certain time is greater than the preset temperature threshold, it indicates that there is a temperature abnormality at the corresponding time, and the time is the heat-sensitive abnormal time.

[0066] More specifically, when the top temperature data or the bottom temperature data at a certain time is greater than the preset temperature threshold, it indicates that there is a temperature abnormality inside the evaporator. The time is marked to obtain the heat-sensitive abnormal time. The preset temperature threshold can be the preset critical temperature value of the heat-sensitive substance, that is, 60°C. When the environmental temperature data exceeds the preset critical temperature value of the heat-sensitive substance, the temperature abnormality at the corresponding time will affect the heat-sensitive substance, and further affect the evaporation process of the sea buckthorn concentrated juice.

[0067] For each heat-sensitive abnormal time, in order to comprehensively analyze the influence degree of the temperature abnormality in the observation period, it is necessary to fully analyze the horizontal and vertical influence. The horizontal analysis means considering the damage to the heat-sensitive substance in the sea buckthorn caused by the temperature abnormality at the same time. The vertical analysis means considering the heat-sensitive abnormality in the evaporator at the same time. In this way, the overall heat-sensitive abnormality performance in the evaporator is comprehensively reflected. Specifically, step S202 is a quantitative process of horizontal analysis, step S203 is a quantitative process of vertical analysis, and step S204 is a quantitative process of comprehensive analysis.

[0068] Step S202, determining a continuous influence factor of each heat-sensitive abnormal time based on a continuous duration length of each heat-sensitive abnormal time within a preset collection period.

[0069] For any heat-sensitive abnormal time within the preset collection period before the current time, the number of continuous heat-sensitive abnormal times is normalized to obtain the continuous influence factor of the any heat-sensitive abnormal time. It can be understood that the heat-sensitive abnormal times that continuously occur within the preset collection period can constitute a heat-sensitive abnormal time period, and the heat-sensitive abnormal time period represents the duration length of the heat-sensitive abnormal phenomenon. Within the time period, the continuous influence factors corresponding to each heat-sensitive abnormal time are the same.

[0070] Step S203, obtaining a temperature abnormality factor of each heat-sensitive abnormal time according to a deviation value between the environmental temperature data of each heat-sensitive abnormal time within the preset collection period and the preset critical temperature value of the heat-sensitive substance.

[0071] Specifically, a first heat-sensitive temperature difference value of each heat-sensitive abnormal time is determined based on a difference value between the top temperature data of each heat-sensitive abnormal time and the preset critical temperature value of the heat-sensitive substance; a second heat-sensitive temperature difference value of each heat-sensitive abnormal time is determined based on a difference value between the bottom temperature data of each heat-sensitive abnormal time and the preset critical temperature value of the heat-sensitive substance; and a temperature abnormality factor of each heat-sensitive abnormal time is determined based on an accumulation sum of the first heat-sensitive temperature difference value and the second heat-sensitive temperature difference value of each heat-sensitive abnormal time.

[0072] More specifically, in the embodiment, the preset critical temperature value of the heat-sensitive substance is 60℃, the first heat-sensitive temperature difference value of each heat-sensitive abnormal time is a difference value between the top temperature data of the corresponding time and the critical temperature value, indicating a difference degree of the top of the evaporator exceeding the critical temperature value at the corresponding time. The second heat-sensitive temperature value of each heat-sensitive abnormal time is a difference value between the bottom temperature data of the corresponding time and the critical temperature value, indicating a difference degree of the bottom of the evaporator exceeding the critical temperature value at the corresponding time.

[0073] Finally, the accumulation sum of the first heat-sensitive temperature difference value and the second heat-sensitive temperature difference value of the same heat-sensitive abnormal time is calculated by comprehensively considering the temperature difference degrees of the same heat-sensitive abnormal time at the top and the bottom of the evaporator, and the temperature abnormality factor of the same heat-sensitive abnormal time is obtained by normalizing the accumulation sum, which represents the overall temperature abnormality degree of a heat-sensitive abnormal time. The normalization method is a known technology and will not be described in detail here.

[0074] Step S204, determining the material affected degree of the current time based on an accumulation result of the product of the continuous influence factor and the temperature abnormality factor of each heat-sensitive abnormal time.

[0075] Firstly, the product of the duration influence factor and the temperature anomaly factor of each thermal anomaly moment is calculated, and then the products corresponding to all thermal anomaly moments in the preset collection period before the current moment are accumulated and summed to obtain the material affected degree of the current moment.

[0076] The material affected degree comprehensively represents the abnormal situation of the thermal sensitive material in sea buckthorn being affected by temperature due to the temperature anomaly before the current moment.

[0077] Step S300, according to the difference between the vacuum degree data of each moment in the preset collection period before the current moment and the standard vacuum range, and the volatility of the vacuum degree data in the abnormal situation, the vacuum fluctuation index of the current moment is obtained.

[0078] From the aspect of the evaporation process of sea buckthorn concentrate, due to the excessive material input, a large amount of water is evaporated instantaneously, causing the pressure of the vacuum system to fluctuate, and then causing the boiling point to rise, triggering the temperature gradient, so that the temperature at the bottom of the evaporator is higher than that at the top, causing the solid to precipitate or coking. Based on this feature, first, the influence of the vacuum degree fluctuation caused by the excessive material input is analyzed.

[0079] In some embodiments, as shown in Figure 3 The specific steps of the second aspect feature analysis can be implemented by steps S301 to S304.

[0080] Step S301, based on the comparison result of the vacuum degree data of each moment in the preset collection period before the current moment and the preset standard vacuum range, the vacuum abnormal moment is determined.

[0081] It should be noted that the preset standard vacuum range refers to the normal vacuum degree range required to be maintained in the evaporator during the evaporation process of sea buckthorn concentrate. The implementer needs to set it according to the specific implementation scene. In this embodiment, the standard vacuum range is that the value of the vacuum degree data is located in the interval of 2.98 to 3.21 kilopascals. When the vacuum degree data is located in this reasonable vacuum interval, it indicates that the vacuum degree data is normal and meets the requirements of the current sea buckthorn concentrate evaporation process. When the vacuum degree data in the evaporator fluctuates outside the reasonable vacuum interval, it indicates that the vacuum fluctuation may be caused by excessive material input, which may affect the evaporation process of sea buckthorn concentrate.

[0082] Specifically, for each moment in the preset collection period before the current moment, the moment when the value of the vacuum degree data is not in the standard vacuum range is determined as the vacuum abnormal moment, which represents that the vacuum deviates from the reasonable range and produces a certain fluctuation phenomenon.

[0083] Step S302, based on the proportion of the number of vacuum abnormal moments in the preset collection period before the current moment, the deviation performance factor of the current moment is determined.

[0084] The ratio of the number of all vacuum abnormal time points in the preset collection period before the current time point and the number of all time points in the preset collection period is taken as the deviation performance factor of the current time point, which reflects the abnormal performance degree of the vacuum degree data deviating from the reasonable range in the preset collection period. The greater the value of the deviation performance factor, the more the time points with vacuum abnormal fluctuations before the current time point, and the greater the influence of the feed quantity on the current evaporation process.

[0085] In step S303, a data dispersion factor of the current time point is determined based on the dispersion degree of the vacuum degree data of the vacuum abnormal time points in the preset collection period before the current time point.

[0086] Specifically, the standard deviation of the vacuum degree data of all vacuum abnormal time points in the preset collection period before the current time point is taken as the data dispersion factor of the current time point. The data dispersion factor reflects the dispersion degree of the vacuum degree data of the time points with vacuum abnormality in the period, and the greater the value of the data dispersion factor, the greater the data fluctuation in the preset collection period before the current time point.

[0087] In step S304, a vacuum fluctuation index of the current time point is determined based on the product of the deviation performance factor and the data dispersion factor of the current time point.

[0088] Specifically, the normalized value of the product of the deviation performance factor and the data dispersion factor of the current time point is taken as the vacuum fluctuation index of the current time point. The vacuum fluctuation index reflects the abnormal fluctuation of the current data from two aspects: the time point distribution data with vacuum deviation and the data fluctuation degree with vacuum deviation.

[0089] In step S400, the coking influence degree of the current time point is obtained according to the coincidence of the region division results and the temperature distribution of the regions of the infrared images of each time point in the preset collection period before the current time point.

[0090] The input of excess material not only causes the fluctuation of vacuum to make the bottom temperature too high and form the occurrence of coking, but also causes the evaporation vessel to be unable to form a uniform thin liquid film, resulting in 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 material is heated and lags due to the increase of thermal resistance, and the outside may be overheated locally to cause coking. Based on this feature, the coking situation caused by the possible local temperature too high in the evaporation vessel is quantitatively measured by analyzing the characteristic distribution of the infrared image in the evaporation vessel.

[0091] In some embodiments, as shown in FIG. 4, Figure 4 The current coking influence degree can be obtained by steps S401 to S404.

[0092] Step S401, threshold segmentation is performed on the infrared image at each time point, and suspected coking pixel points and normal evaporation pixel points are obtained after screening.

[0093] The Otsu threshold segmentation method is used to segment the infrared image at each time point, and the pixel points in the infrared image greater than or equal to the threshold value are regarded as suspected coking pixel points, and the pixel points in the infrared image less than the threshold value are regarded as normal evaporation pixel points. The closed region formed by the suspected coking pixel points can be regarded as a local region where coking phenomenon is suspected to exist.

[0094] When there is a local coking phenomenon in the evaporator, the temperature value at the corresponding position is relatively high, and the temperature value of the other normal part is relatively low, which is within the normal temperature range. Therefore, when the threshold segmentation is performed on the infrared image corresponding to each time point, the part exceeding the threshold value is the suspected coking pixel point where coking phenomenon may exist, and the part less than the threshold value is the normal evaporation pixel point under normal phenomenon. It should be noted that the Otsu threshold segmentation method is a known technology, and will not be described in detail here. The threshold value for division is obtained by the segmentation method.

[0095] Step S402, 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 time, a coking temperature anomaly factor at the current time is determined.

[0096] Firstly, the average value of the temperature values of all suspected coking pixel points in the infrared image at the current time is calculated as the first average value corresponding to the current time, which reflects the temperature performance of the suspected coking phenomenon in the infrared image at the current time.

[0097] Secondly, the average value of the temperature values of all normal evaporation pixel points in the infrared image at the current time is calculated as the second average value corresponding to the current time, which reflects the temperature performance of the normal phenomenon in the infrared image at the current time.

[0098] Thirdly, the ratio of the first average value and the second average value at the current time is calculated to obtain the coking temperature anomaly factor at the current time, which represents the comparison result of the temperature abnormal distribution and the temperature normal distribution in the evaporator at the current time. The greater the value of the coking temperature anomaly factor, the higher the local temperature of the local area where coking phenomenon may exist in the evaporator at the current time, and the greater the influence of the existing temperature anomaly on the evaporation process of the sea buckthorn concentrate.

[0099] Step S403, according to the overlapping situation between the suspected coking pixel points in the infrared image at each time point within a preset collection period before the current time, a coking overlapping factor at the current time is obtained.

[0100] According to the characteristics of the coking area being relatively persistent in a certain area, even gradually expanding, the overlap between the local areas suspected of existing coking phenomenon in the preset collection period at the current time is analyzed. Specifically, the pixel point set at each time is obtained by the suspected coking pixel points in the infrared image at each time, and the number ratio of the intersection of the pixel point sets at all times is taken as the coking overlap factor at the current time. The number ratio can be the ratio of the number of pixel points contained in the intersection of all pixel point sets to the total number of pixel points in the infrared image.

[0101] It can be understood that obtaining a corresponding pixel point set at each time within the preset collection period before the current time represents the area performance of the local area that may exist coking phenomenon at each time, and then analyzing the overlap of all possible coking phenomena in the current period reflects the abnormal influence degree of the suspected coking phenomenon at the moment.

[0102] The greater the value of the coking overlap factor, the greater the overlap area at this time, indicating that the coking phenomenon in the current period covers a larger area and is more serious, and then indicating that the coking phenomenon starts earlier and lasts for a long time. The smaller the value of the coking overlap factor, the smaller the overlap area at this time, and then indicating that the coking phenomenon in the current period covers a smaller area and is less serious.

[0103] Step S404, determining the coking influence degree at the current time based on the product of the coking temperature anomaly factor and the coking overlap factor at the current time.

[0104] By comprehensively considering the characteristic distribution of the suspected coking phenomenon at the current time and the persistence characteristics of the suspected coking phenomenon at the continuous multiple times, the influence degree is quantitatively measured, and specifically, the product of the coking temperature anomaly factor and the coking overlap factor at the current time is taken as the coking influence degree at the current time. The coking influence degree represents the influence degree of the possible coking phenomenon in the evaporator caused by the current temperature distribution on the evaporation process of the sea buckthorn concentrate.

[0105] Step S500, according to the material affected degree and the coking influence degree at the current time, combining the vacuum fluctuation index, the temperature of the evaporator at the current time is regulated.

[0106] Excessive material input will change the material flow balance in the evaporator, especially the high fiber or oil components in sea buckthorn, which will form a non-uniform distribution in the evaporation process, which may cause a sudden increase in local resistance, cause abnormal fluctuations in vacuum degree, and increase the temperature difference between the inside and outside of the material, and then cause the occurrence of local coking, affecting the output quality of the final sea buckthorn concentrate. At the same time, the damage of the non-uniform temperature to the heat-sensitive substances in the whole process also needs to be considered.

[0107] Based on this characteristic, when determining the degree of temperature adjustment, a larger vacuum fluctuation index value at the current moment indicates that the material input may be excessive, leading to excessive evaporation of moisture in the material and causing vacuum fluctuations, resulting in a significant temperature gradient, i.e., uneven temperature distribution. In this case, more attention should be paid to the extent of coking at the current moment, i.e., the temperature gradient phenomenon caused by vacuum fluctuations may lead to solid coking, which has a relatively large impact on the evaporation process of sea buckthorn concentrate. Furthermore, compared to localized coking, the degree of impact on the material itself is relatively less important at this point.

[0108] When the value of the vacuum fluctuation index is smaller, it means that the influence of excessive material is smaller, which means that there may not be a large temperature gradient. In this case, we should pay attention to the real-time impact of the heat-sensitive substances. Even if there is no impact from excessive material input, there may still be other objective factors that cause excessive temperature and other situations that affect the heat-sensitive substances in sea buckthorn.

[0109] In some embodiments, such as Figure 5 As shown, the method for regulating the temperature of the evaporator at the current moment can be implemented by steps S501 to S502.

[0110] Step S501: Based on the degree of material impact and coking impact at the current moment, and combined with the vacuum fluctuation index, obtain the temperature adjustment coefficient at the current moment.

[0111] 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 impact. The degree of coking influence and the degree of material impact are weighted and summed using the first weight and the second weight and then normalized to obtain the temperature regulation coefficient at the current moment.

[0112] As a concrete example, the temperature regulation coefficient at the current moment can be expressed as:

[0113]

[0114] in, This represents the temperature regulation coefficient at the current moment. This indicates the vacuum fluctuation index at the current moment. This indicates the degree of coking effect at the current moment. This indicates the degree to which the material is affected at the current moment, and norm represents the normalization function.

[0115] Furthermore, That is, the degree of impact of coking. The corresponding first weight, the degree of influence of the material The greater the value of the first weight, the smaller the value of the second weight, which reflects that when the degree of vacuum fluctuation phenomenon is greater, more attention should be paid to the influence of the coking phenomenon in the current evaporator on the evaporation process. The smaller the value of the first weight, the greater the value of the second weight, which reflects that when the degree of vacuum fluctuation phenomenon is smaller, the possibility of coking phenomenon is smaller, and at this time more attention should be paid to the change of the temperature.

[0116] In step S502, the maximum temperature value and the normal temperature interval in the sea buckthorn concentrate evaporation process are obtained; and the temperature of the current evaporator is regulated by using the temperature regulation coefficient and the normal temperature interval in combination with the maximum temperature value.

[0117] In this embodiment, the corresponding temperature set value is dynamically adjusted in combination with the temperature regulation range in the sea buckthorn concentrate evaporation process, so as to avoid the destruction of heat-sensitive substances and the occurrence of local coking in different sea buckthorn concentrate evaporation processes.

[0118] The product of the temperature regulation coefficient at the current time and the temperature difference between the normal temperature interval is calculated, and the result of the rounding is the temperature adjustment degree at the current time. The difference between the maximum temperature value in the sea buckthorn concentrate evaporation process and the temperature adjustment degree is taken as the adjusted temperature value of the current evaporator.

[0119] As a specific example, the adjusted temperature value may be expressed as , , which represents the maximum temperature value of the normal temperature interval, that is, 60℃, , which represents the temperature regulation coefficient at the current time, , which represents the temperature difference of the normal temperature interval, that is, 10℃.

[0120] It should be noted that according to the data of the sea buckthorn concentrate evaporation process, the normal temperature interval of the evaporation process is usually between 50℃ and 60℃, that is, this temperature range is the normal temperature interval set by this embodiment, and the implementer needs to set it according to the specific implementation scene.

[0121] In this embodiment, the temperature adjustment degree determined by the degree of characteristic performance of each aspect in the current evaporation process is used to adjust the maximum temperature value. The greater the temperature regulation coefficient at the current time, the more serious the temperature unevenness caused by multiple directional factors in the current evaporation process, so the rapid temperature rise will cause internal thermal expansion difference of the material, and local coking or destruction of heat-sensitive components. At this time, the temperature rise rate can be slowed down to reduce the internal and external temperature difference, reduce the accumulation of thermal stress, and avoid local coking or destruction of heat-sensitive components.

[0122] In some embodiments, if the temperature adjustment coefficient at the current time is large, it indicates that the abnormal situation of the evaporation process data at the current time is large, and if necessary, a warning can be set to remind the relevant staff to investigate the abnormal evaporation process, for example, when the value of the current temperature adjustment coefficient is greater than the preset temperature threshold, a warning is given, wherein 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 the moment, and if the temperature abnormality at the moment is greater than a certain degree, the relevant staff need to be reminded to investigate the current evaporation process and the like.

[0123] In summary, the present application can determine the real-time influence degree of the heat-sensitive material at the current time by analyzing the influence degree of the heat-sensitive material at the moment of heat-sensitive abnormality in the historical sea-buckthorn concentrated juice evaporation process, and further determine the real-time deviation vacuum fluctuation degree and the local coking influence degree at the current time considering the influence caused by excessive material input. The adjustment coefficient of the temperature setting at the current time is determined based on the real-time influence degree of the heat-sensitive material and the local coking influence degree based on the deviation vacuum fluctuation degree. The optimal temperature setting value at the current time is determined from the perspective of slowing down the temperature rising rate and reducing the accumulation of thermal stress, which is used to the current system to achieve the purpose of controlling the temperature of the evaporation process. The evaporation temperature of the sea-buckthorn juice is dynamically adjusted according to the comprehensive influence in the evaporation process, so as to minimize the damage to the heat-sensitive material and avoid the occurrence of local coking.

[0124] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A temperature optimization control system for sea buckthorn concentrate evaporation, comprising a memory and a processor, characterized in that, The processor executes the computer program stored in the memory to perform the following steps: Acquire ambient temperature data, vacuum data, and infrared images of the evaporator within a preset acquisition period prior to the current moment during the sea buckthorn concentration and evaporation process; Based on the difference between the ambient temperature data at each moment within the preset collection period before the current moment and the preset critical temperature value of the heat-sensitive substance, analyze the temperature anomaly at each moment to obtain the degree of material impact at the current moment; Based on the difference between the vacuum level data and the standard vacuum level range at each moment within the preset acquisition period before the current moment, as well as the fluctuation of the vacuum level data in case of abnormal situations, the vacuum fluctuation index at the current moment is obtained. Based on the overlap of the region division results and the temperature distribution of the region in the infrared images of each time within the preset acquisition period before the current time, the degree of coking influence at the current time is obtained. Based on the current level of material impact and coking effect, and in conjunction with vacuum fluctuation indicators, the evaporator temperature is adjusted accordingly.

2. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 1, characterized in that, The method involves analyzing the temperature anomalies at each moment based on the difference between the ambient temperature data at each moment within a preset collection period prior to the current moment and the preset critical temperature value of the heat-sensitive substance, thereby determining the degree of material impact at the current moment. Specifically, this includes: The moment of thermal anomaly is determined when the ambient temperature data at each moment within the preset collection period before the current moment is greater than the preset temperature threshold. Based on the continuous duration of each thermal anomaly moment within the preset acquisition period, the continuous influence factor of each thermal anomaly moment is determined. The temperature anomaly factor for each thermosensitive anomaly is obtained based on the deviation between the ambient temperature data at each thermosensitive anomaly moment within the preset collection period and the preset critical temperature value of the thermosensitive substance. The degree of material impact at the current moment is determined by summing the products of the continuous impact factor and the temperature anomaly factor at each thermal anomaly moment.

3. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 2, characterized in that, The temperature anomaly factor for each thermosensitive anomaly moment is obtained based on the deviation between the ambient temperature data at each thermosensitive anomaly moment within a preset acquisition period and the preset critical temperature value of the thermosensitive substance. Specifically, this 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 thermal anomaly moment and the preset critical temperature value of the thermally sensitive material, a first thermal temperature difference is determined for each thermal anomaly moment; based on the difference between the bottom temperature data at each thermal anomaly moment and the preset critical temperature value of the thermally sensitive material, a second thermal temperature difference is determined for each thermal anomaly moment. The temperature anomaly factor for each thermosensitive anomaly is determined by summing the first and second thermosensitive temperature differences at each thermosensitive anomaly moment.

4. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 1, characterized in that, The process of obtaining the vacuum fluctuation index at the current moment based on the difference between the vacuum level data at each moment within the preset acquisition period prior to the current moment and the standard vacuum level range, as well as the fluctuation of the vacuum level data in cases of anomalies, specifically includes: Based on the comparison results of vacuum level data at each moment within the preset acquisition period before the current moment and the preset standard vacuum range, the moment of vacuum anomaly is determined; Based on the proportion of vacuum anomaly moments within the preset acquisition period prior to the current moment, the deviation performance factor at the current moment is determined. Based on the degree of dispersion of vacuum level data during vacuum anomaly times within a preset acquisition period prior to the current moment, the data dispersion factor at the current moment is determined. The vacuum fluctuation index at the current moment is determined by multiplying the deviation performance factor and the data dispersion factor at the current moment.

5. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 1, characterized in that, The determination of the degree of coking influence at the current moment, based on the overlap of region division results and the regional temperature distribution of infrared images from each moment within a preset acquisition period prior to the current moment, specifically includes: Threshold segmentation and filtering are performed on the infrared image at each time step to obtain suspected coking pixels and normal evaporation pixels; The coking temperature anomaly factor at the current moment is determined based on the ratio between the average temperature value of all suspected coking pixels and the average temperature value of all normal evaporation pixels in the infrared image at the current moment. Based on the overlap between suspected focal pixels in the infrared images at each time point within the preset acquisition period before the current time, the focal overlap factor at the current time is obtained. The degree of coking influence at the current moment is determined by the product of the coking temperature anomaly factor and the coking overlap factor.

6. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 5, characterized in that, The step of obtaining the focusing overlap factor at the current moment based on the overlap between suspected focal pixels in the infrared images at each moment within the preset acquisition period prior to the current moment specifically includes: The set of pixels at each moment is formed by obtaining the suspected focal pixels in the infrared image at each moment. The percentage of pixels in the intersection of the pixel sets at all moments is used as the focal overlap factor at the current moment.

7. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 5, characterized in that, The process of thresholding and filtering the infrared image at each time moment to obtain suspected focalized pixels and normal evaporation pixels specifically includes: The infrared image at each time step is segmented using the Otsu threshold segmentation method. Pixels in the infrared image that are greater than or equal to the threshold are considered as suspected focal pixels, while pixels in the infrared image that are less than the threshold are considered as normal evaporation pixels.

8. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 1, characterized in that, The method of adjusting the evaporator temperature based on the current material and coking impact levels, combined with vacuum fluctuation indicators, specifically includes: Based on the degree of material impact and coking impact at the current moment, and combined with the vacuum fluctuation index, the temperature adjustment coefficient at the current moment is obtained; Obtain the highest temperature value and normal temperature range during the sea buckthorn concentration and evaporation process; use the temperature adjustment coefficient and normal temperature range, combined with the highest temperature value, to regulate the temperature of the evaporator at the current moment.

9. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 8, characterized in that, The temperature adjustment coefficient for the current moment is obtained based on the degree of material impact and coking impact at the current moment, combined with the vacuum fluctuation index. Specifically, this includes: 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 impact. The degree of coking influence and the degree of material impact are weighted and summed using the first weight and the second weight and then normalized to obtain the temperature regulation coefficient at the current moment.

10. The sea buckthorn concentrate evaporation temperature optimization control system according to claim 8, characterized in that, The method of using a temperature regulation coefficient and a normal temperature range, combined with the highest temperature value, to regulate the temperature of the evaporator at the current moment specifically includes: The temperature adjustment level at the current moment is obtained by rounding down the product of the temperature adjustment coefficient at the current moment and the temperature difference in the normal temperature range. The difference between the highest temperature value during the sea buckthorn concentration and evaporation process and the temperature adjustment level is taken as the adjusted temperature value of the evaporator at the current moment.

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