Automatic proportioning method and system for ketogenic coffee solid beverage

Abstract

The invention belongs to the technical field of data processing, and provides an automatic proportioning method and system for ketogenic coffee solid drinks, and the method specifically comprises the steps: firstly, initializing an automatic proportioning scene of a high-pressure homogenizer, recognizing an environment collection module in the automatic proportioning scene of the high-pressure homogenizer, obtaining temperature and pressure information from the environment collection module, and carrying out the automatic proportioning of the ketogenic coffee solid drinks; the method comprises the following steps: constructing a temperature and pressure actual measurement array, then performing mixing chamber temperature and pressure abnormal analysis on the temperature and pressure actual measurement array to judge whether a temperature and pressure accumulation factor appears, and finally dynamically controlling the ingredient input speed of the high-pressure homogenizer in combination with the temperature and pressure accumulation factor. The temperature and pressure accumulation factor obtained through quantification can quantify the occurrence degree of the phenomenon of instantaneous temperature rise or instantaneous air pressure rise in the emulsification process of the high-pressure homogenizer in real time, so that the stability of ketogenic coffee solid beverage products in the emulsification process and the consistency of taste and flavor are guaranteed; therefore, the working efficiency and the product quality of the automatic production line are dynamically maintained.

Description

Technical Field

[0001] The present invention belongs to the technical field of data collection and automatic batching of ketogenic coffee, and in particular relates to an automatic batching method and system for a ketogenic coffee solid beverage. Background Art

[0002] Ketogenic coffee has the characteristic of high fat content. Usually, solid ketogenic coffee drinks use medium-chain triglyceride (MCT) oil, coconut oil or grass-fed butter as the main added ingredients, without the need for additional sugar or sweeteners, so it has the advantages of high energy and low carbon water. At the same time, unlike the refreshing taste of ordinary coffee, the lipid substances in ketogenic coffee bring a rich and creamy taste that is more in line with market demand.

[0003] In the current preparation process of ketogenic coffee solid beverage, the initially emulsified mixed liquid is continuously sent to the high-pressure homogenizer for emulsification treatment in the form of an assembly line. This high-pressure homogenizer process uses high-pressure impact and shearing to refine the fat particles to nanometer level. The fat particles are fully refined, but the temperature and pressure in the high-pressure homogenizer are often not constant. On the one hand, this is because the core principle of the high-pressure homogenizer is to pressurize the fluid through a high-pressure pump, and the plunger pump is used as the high-pressure pump. During work, the high-frequency reciprocating motion occurs, resulting in periodic fluctuations in the pressure output. On the other hand, the homogenization valve of the high-pressure homogenizer uses a narrow gap to pressurize the fluid. The gap realizes the purpose of high-speed shearing, collision and cavitation of the fluid, while the opening of the homogenizing valve shows dynamic changes and is linearly affected by the fluid pressure and flow rate. At the same time, the fluid in the homogenizing valve undergoes rapid compression and expansion, and the kinetic energy increases instantly and then quickly converts into heat energy, causing continuous and periodic accumulation of heat energy. Therefore, the temperature rises instantaneously or the air pressure rises instantaneously frequently. This sudden rise in temperature and pressure can lead to lipid oxygen degradation problems, that is, the mixed liquid cannot match the temperature and pressure environment actually provided by the high-pressure homogenizer, causing the fat particles to degrade or oxidize, thereby affecting the taste and flavor of ketogenic coffee solid beverages. Therefore, it is urgent to monitor the temperature and pressure status of the high-pressure homogenizer in real time to reduce the risk of coffee taste deterioration caused by lipid oxygen degradation problems. Summary of the invention

[0004] The purpose of the present invention is to propose an automatic dosing method and system for ketogenic coffee solid beverages to solve one or more technical problems existing in the prior art and at least provide a beneficial choice or create conditions.

[0005] In order to achieve the above object, according to one aspect of the present invention, there is provided an automatic batching method for a ketogenic coffee solid beverage, the method comprising the following steps:

[0006] S100, initializing the high-pressure homogenizer automatic batching scene, and identifying the environment acquisition module in the high-pressure homogenizer automatic batching scene;

[0007] S200, acquiring temperature and pressure information from the environment acquisition module to form a temperature and pressure measurement array;

[0008] S300, determining whether a temperature and pressure accumulation factor occurs by analyzing the temperature and pressure anomaly of the mixing chamber room and pressure on the temperature and pressure measurement array;

[0009] S400 dynamically controls the input speed of high-pressure homogenizer ingredients by combining the temperature and pressure accumulation factors.

[0010] Further, in step S100, the high-pressure homogenizer automatic batching scene is initialized, and the method for identifying the environment acquisition module in the high-pressure homogenizer automatic batching scene is: the high-pressure homogenizer automatic batching scene includes an environment acquisition module, and the environment acquisition module is arranged on the inner wall of the mixing chamber of the high-pressure homogenizer; the environment acquisition module is composed of a pressure sensor and a temperature sensor;

[0011] The pressure sensor is any one of a piezoelectric pressure sensor, an optical fiber pressure sensor or a ceramic pressure sensor, and the temperature sensor is any one of a thermocouple, an infrared temperature sensor or a semiconductor temperature sensor.

[0012] The environment acquisition module communicates via LoRa communication technology, zigbee or 5G network; the environment acquisition module sends the collected data to the server, and the server stores or applies the environment data to remotely control the input speed of the high-pressure homogenizer ingredients.

[0013] Through the networking function, the environmental acquisition module and the cloud server form a distributed collaborative architecture. By enhancing the computing power and data reading and writing capabilities, the real-time response capability and quantitative accuracy of the high-pressure homogenizer in a dynamic environment are greatly enhanced, while achieving high-precision controllability of the production process and convenient and intelligent software function iteration or update.

[0014] Further, in step S200, the temperature and pressure information are obtained from the environment acquisition module, and the method for forming a temperature and pressure measurement array is: the pressure and temperature of the high-pressure homogenizer are collected in real time by a pressure sensor and a temperature sensor, and recorded as a real-time pressure value and a real-time temperature value, respectively; a time period is set as an information feedback segment IRZ, IRZ∈[1,10] minutes; a temperature and pressure transient variable array is obtained once every IRZ, and the temperature and pressure transient variable array is a tuple consisting of a temperature peak number and a pressure peak number; the pressure peak number is the maximum value of each real-time pressure value measured in the information feedback segment IRZ, and the temperature peak number is the maximum value of each real-time temperature value measured in the information feedback segment IRZ.

[0015] Further, in step S300, by analyzing the temperature and pressure anomaly of the mixing chamber room and the pressure measurement array, a method for determining whether a temperature and pressure accumulation factor occurs is as follows: a time period is set as a dynamic monitoring period RMTZ, RMTZ∈[1,5] hours, and the default value is 1 hour;

[0016] When the number of pressure peaks at a moment is greater than that of the previous moment, the moment is defined as a pressure surge point; when the number of temperature peaks at a moment is greater than that of the previous moment, the moment is defined as a temperature surge point; from each pressure surge point, search the corresponding moment of the first temperature surge point in reverse time direction, record it as the feedback delay point of the pressure surge point, record the number of moments between the pressure surge point and its feedback delay point as the delay degree, calculate the average value of each delay degree in the RMTZ and round it up as the average delay degree EXTN, and take the average value of the number of pressure peaks at a moment and the number of EXTN moments before it as the delayed pressure peak at that moment;

[0017] If the pressure peak number at a moment is greater than the delayed pressure peak, the moment is defined as the first peak point, otherwise it is the second peak point; when the previous moment of a moment is the second peak point and the moment is the first peak point, the moment is defined as an instance point; the current moment is the instance point; the instance interval is divided in reverse time direction from the current moment: the set of moments between any two consecutive instance points is an instance interval; if the number of moments in the instance interval is less than the average delay, it is not considered as an instance interval;

[0018] The average value of the number of temperature peaks and the average value of the number of pressure peaks in an instance interval are formed into a two-tuple and recorded as a temperature and pressure instance array; the proportion of pressure sudden increase points and the proportion of temperature sudden increase points in the instance interval are recorded as PVRT and TPRT respectively;

[0019] Any two instance points that are continuous in time sequence refer to any instance point and the first instance point obtained by searching in the reverse time direction, or any instance point and the first instance point obtained by searching in the forward time direction, both of which are considered as instance points that are continuous in time sequence with the any instance point;

[0020] If the number of moments between the instance point corresponding to the current moment and its instance endpoint is less than the average delay, continue to search for the instance endpoint in the reverse time direction until the number of moments between the instance point corresponding to the current moment and its instance endpoint is greater than or equal to the average delay; the instance endpoint refers to the instance point farthest from the current moment in the instance interval;

[0021] The instance anomaly INS_OL at the current moment is:

[0022] Where exp is an exponential function with the natural constant e as the base, i1 is an accumulated variable, DEPV is the maximum value of the delayed pressure peaks in the current instance interval, FPV is the maximum value of the pressure peaks in the current instance interval; the instance intervals other than the current instance interval in the current RMTZ period are control instance intervals, NK is the number of control instance intervals, INSS(i1) and INSS_C represent the temperature and pressure instance arrays of the i1th control instance interval and the current instance interval respectively, ds<> is the Euclidean distance function, and the Euclidean distance function returns the Euclidean distance between two called tuples; max<> is the maximum value function;

[0023] If the difference between the anomaly of a moment and the anomaly of the previous moment is the anomaly step difference, and if the anomaly step difference of the current moment is greater than the upper quartile of the anomaly step difference of the current RMTZ period, a high step difference is defined.

[0024] The median value of the instance anomaly obtained at each moment in the current RMTZ period is MOL. If the instance anomaly at the current moment is greater than MOL and a high step difference occurs, the current moment belongs to a temperature and pressure accumulation risk point; the preset risk interval Rsz, Rsz∈[20%, 50%] If the proportion of temperature and pressure accumulation in the current instance interval exceeds Rsz, the temperature and pressure accumulation factor is defined to appear, otherwise the temperature and pressure accumulation factor does not appear.

[0025] The current instance interval refers to the instance interval corresponding to the current moment; the number of temperature peaks and pressure peaks are read from the temperature and pressure variable array; the previous moment refers to a moment in the reverse time direction; if this method is used to determine whether a temperature and pressure accumulation factor appears, the preset value of the information feedback segment IRZ in step S200 must be less than 5 minutes.

[0026] The current RMTZ period refers to the time period of the RMTZ in the reverse time direction of the current moment.

[0027] Since there is a phenomenon of excessive pursuit of timeliness in the process of judging the occurrence of the temperature and pressure accumulation factor through instance anomalies, that is, preference for risk identification in short-cycle changes, it will lead to the problem of random noise misleading and causing false fault alarms, especially when the environmental acquisition module works for a long time, random noise occurs more frequently. However, the existing technology cannot solve the problem of overfitting or over-sensitivity of the temperature and pressure accumulation factor caused by such random noise. In order to better distinguish the effect and solve the problem, and eliminate the phenomenon of over-sensitivity of the temperature and pressure accumulation factor, the present invention proposes a more preferred solution as follows:

[0028] Preferably, in step S300, by analyzing the temperature and pressure anomaly of the mixing chamber room and room temperature, a method for determining whether a temperature and pressure accumulation factor occurs is as follows: reading a 24-48 hour temperature and pressure measurement array to form a historical data set;

[0029] The number of temperature peaks and pressure peaks in the historical data set are normalized separately;

[0030] The normalization method is MinMax normalization. In the default state, the historical data set uses the most recently acquired temperature and pressure measurement array. The closer it is to the current moment, the higher the accuracy. Alternatively, the historical data set is obtained periodically, for example, once a month or once a week.

[0031] Preset an integer as the cluster quantity NCT, NCT∈[20,40], divide the historical data set into NCT clusters by K-Medoids clustering algorithm, obtain the number of temperature peaks of the cluster center of each cluster respectively, and calculate the average value of the number of temperature peaks of each cluster center as the median thermal amplitude, define the absolute value of the difference between the number of temperature peaks of the cluster center of any cluster and the median thermal amplitude as the cluster thermal deviation;

[0032] Define a cluster as the cluster thermal deviation level CLDG after each cluster is sorted from large to small according to the cluster thermal deviation. The percentage of the number of elements in the cluster to all elements is defined as the cluster point ratio. The first cluster anomaly is e -CLDG The ratio of the cluster point ratio; where e is a natural constant;

[0033] Calculate the Euclidean distance between a cluster and the cluster centers of the remaining clusters, and record the maximum value of the obtained Euclidean distances as the cluster boundary distance of the cluster; the ratio of any cluster boundary distance to the minimum value of the cluster boundary distances of all clusters is the cluster outlier degree;

[0034] The product of the cluster outlier degree and the first cluster heterogeneity is the second cluster heterogeneity; the average value of the second cluster heterogeneity of each cluster is the stable cluster threshold STTH. If the second cluster heterogeneity of a cluster is greater than (1+PSRt)STTH, the cluster is defined as a high-bias cluster; if the second cluster heterogeneity of a cluster is less than (1-PSRt)STTH, the cluster is defined as a low-bias cluster; PSRt is the preset heterogeneity screening rate, the value is PSRt∈[0.25,0.5], and the default value is 0.25;

[0035] The temperature and pressure transient array obtained in real time is used to select the cluster to which it belongs at the current moment through the nearest neighbor method. If the cluster to which a moment belongs is a high-bias cluster or a low-bias cluster, it is defined that a high deviation or a low deviation occurs at this moment; a period is defined as the occurrence condition interval OPRZ, and the value range is OPRZ∈[40,120] minutes; the total amount of time, the number of low deviations and the number of high deviations in the current OPRZ period are recorded as TOTt, TOL and TOH respectively. If TOL+TOH>0.5TOTt, it is defined that the temperature and pressure accumulation factor appears; otherwise, if TOL+TOH>0.1TOTt and TOH>0.5TOL, it is defined that the temperature and pressure accumulation factor appears, otherwise the temperature and pressure accumulation factor does not appear.

[0036] The current OPRZ period refers to the period whose time length in the reverse time direction is OPRZ at the current moment.

[0037] Beneficial effects: By analyzing the temperature and pressure anomalies in the mixing chamber room in a unit time period, the calculated temperature and pressure accumulation factor can quantify in real time the degree of instantaneous temperature rise or instantaneous pressure rise during the emulsification process of the high-pressure homogenizer, which is equivalent to dynamic identification of temperature and pressure adaptability, thereby indirectly reflecting the risk of inducing lipid oxygen degradation problems, providing mathematical support for dynamic adjustment of equipment operating parameters, and achieving the purpose of reducing the risk of temperature and pressure accumulation by maintaining a low incidence rate of the temperature and pressure accumulation factor.

[0038] Further, in step S400, the method of dynamically controlling the batching input speed of the high-pressure homogenizer in combination with the temperature-pressure accumulation factor is: if the temperature-pressure accumulation factor appears at the current moment, the batching delivery rate is reduced by 0.1%-5%, and if the temperature-pressure accumulation factor does not appear at the current moment, and the batching delivery rate does not reach 100% or does not reach a preset threshold, the batching delivery rate is increased by 0.1%-5%;

[0039] The ingredient delivery rate refers to the flow rate of the initially emulsified mixed liquid delivered to the high-pressure homogenizer per unit time.

[0040] The adjustment of the ingredient delivery rate is achieved by changing the power of the feed pump, ensuring that the operating parameters of the high-pressure homogenizer dynamically match the occurrence rate of the temperature and pressure accumulation factor during the emulsification process, improving the emulsification uniformity of the high-pressure homogenizer and reducing the risk of temperature and pressure accumulation.

[0041] Preferably, all undefined variables in the present invention, if not clearly defined, can be manually set thresholds.

[0042] The present invention also provides an automatic batching system for ketogenic coffee solid beverages, the automatic batching system for ketogenic coffee solid beverages comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, the processor implementing the steps in the automatic batching method for ketogenic coffee solid beverages when executing the computer program, the automatic batching system for ketogenic coffee solid beverages can be run in computing devices such as desktop computers, laptop computers, PDAs, and cloud data centers, the executable system may include, but is not limited to, a processor, a memory, and a server cluster, the processor executing the computer program runs in the following system units:

[0043] The environment acquisition module scene layout unit is used to initialize the high-pressure homogenizer automatic batching scene and identify the environment acquisition module in the high-pressure homogenizer automatic batching scene;

[0044] An environmental information acquisition unit is used to obtain temperature and pressure information from the environmental acquisition module to form a temperature and pressure measurement array;

[0045] A mixing chamber room and pressure anomaly analysis unit is used to analyze the mixing chamber room and pressure anomaly on the temperature and pressure measurement array to determine whether a temperature and pressure accumulation factor occurs;

[0046] The ingredient input control unit is used to dynamically control the ingredient input speed of the high-pressure homogenizer in combination with the temperature and pressure accumulation factor.

[0047] The beneficial effects of the present invention are as follows: the present invention provides an automatic batching method and system for ketogenic coffee solid beverages. By analyzing the abnormal temperature and pressure of the mixing chamber room in a unit time period, the calculated temperature and pressure accumulation factor can quantify in real time the degree of instantaneous temperature rise or instantaneous pressure rise during the emulsification process of the high-pressure homogenizer, which is equivalent to dynamic identification of temperature and pressure adaptability, thereby indirectly reflecting the risk of inducing lipid oxygen degradation problems, providing mathematical support for dynamic adjustment of equipment operating parameters, and achieving the purpose of reducing the risk of temperature and pressure accumulation by maintaining a low incidence rate of the temperature and pressure accumulation factor, thereby reducing the degree of lipid degradation or oxidation of fat particles, ensuring the stability of the ketogenic coffee solid beverage product in the emulsification process and the consistency of taste and flavor, thereby dynamically maintaining the working efficiency and product quality of the automated production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and other features of the present invention will become more obvious by describing in detail the embodiments shown in the accompanying drawings. The same reference numerals in the accompanying drawings of the present invention represent the same or similar elements. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other accompanying drawings can be obtained based on these accompanying drawings without creative work. In the accompanying drawings:

[0049] Figure 1 Shown is a flow chart of an automatic batching method for a ketogenic coffee solid beverage;

[0050] Figure 2 Shown is a structural diagram of an automatic batching system for a ketogenic coffee solid beverage. DETAILED DESCRIPTION

[0051] The following will be combined with the embodiments and drawings to clearly and completely describe the concept, specific structure and technical effects of the present invention, so as to fully understand the purpose, scheme and effect of the present invention. It should be noted that the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0052] like Figure 1 The flowchart of the automatic batching method of a ketogenic coffee solid beverage is shown below. Figure 1 To illustrate an automatic batching method for a ketogenic coffee solid beverage according to an embodiment of the present invention, the method comprises the following steps:

[0053] S100, initializing the high-pressure homogenizer automatic batching scene, and identifying the environment acquisition module in the high-pressure homogenizer automatic batching scene;

[0054] S200, acquiring temperature and pressure information from the environment acquisition module to form a temperature and pressure measurement array;

[0055] S300, determining whether a temperature and pressure accumulation factor occurs by analyzing the temperature and pressure anomaly of the mixing chamber room and pressure on the temperature and pressure measurement array;

[0056] S400 dynamically controls the input speed of high-pressure homogenizer ingredients by combining the temperature and pressure accumulation factors.

[0057] Further, in step S100, the high-pressure homogenizer automatic batching scene is initialized, and the method for identifying the environment acquisition module in the high-pressure homogenizer automatic batching scene is: the high-pressure homogenizer automatic batching scene includes an environment acquisition module, and the environment acquisition module is arranged on the inner wall of the mixing chamber of the high-pressure homogenizer; the environment acquisition module is composed of a pressure sensor and a temperature sensor;

[0058] The ingredient list of the ketogenic coffee solid beverage is as follows: powdered butter, including oligosaccharides, sodium caseinate, mono- and di-glycerol fatty acid esters, sodium ascorbate, cream powder, instant coffee powder, medium-chain triglyceride powder, resistant dextrin, inulin, virgin coconut oil powder, conjugated linoleic acid glyceride microcapsule powder, white kidney bean extract, tea theanine, green coffee powder, potato extract, turmeric, citrus polyphenols, and steviol glycosides.

[0059] The pressure sensor is a piezoelectric pressure sensor, and the temperature sensor is a semiconductor temperature sensor.

[0060] Further, in step S200, the temperature and pressure information are obtained from the environment acquisition module, and the method for forming a temperature and pressure measurement array is: the pressure and temperature of the high-pressure homogenizer are collected in real time by means of a pressure sensor and a temperature sensor, and are recorded as a real-time pressure value and a real-time temperature value, respectively; a time period is set as the information feedback segment IRZ, and the IRZ takes a value of 2 minutes; a temperature and pressure transient variable array is obtained once every IRZ, and the temperature and pressure transient variable array is a tuple consisting of the number of temperature peaks and the number of pressure peaks; the number of pressure peaks is the maximum value of each real-time pressure value measured in the information feedback segment IRZ, and the number of temperature peaks is the maximum value of each real-time temperature value measured in the information feedback segment IRZ.

[0061] Further, in step S300, by analyzing the abnormal temperature and pressure of the mixing chamber room temperature on the temperature and pressure measurement array, a method for determining whether a temperature and pressure accumulation factor occurs is as follows: a time period is set as a dynamic monitoring period RMTZ, with a value of 1 hour;

[0062] When the number of pressure peaks at a moment is greater than that of the previous moment, the moment is defined as a pressure surge point; when the number of temperature peaks at a moment is greater than that of the previous moment, the moment is defined as a temperature surge point; from each pressure surge point, search the corresponding moment of the first temperature surge point in reverse time direction, record it as the feedback delay point of the pressure surge point, record the number of moments between the pressure surge point and its feedback delay point as the delay degree, calculate the average value of each delay degree in the RMTZ and round it up as the average delay degree EXTN, and take the average value of the number of pressure peaks at a moment and the number of EXTN moments before it as the delayed pressure peak at that moment;

[0063] If the pressure peak number at a moment is greater than the delayed pressure peak, the moment is defined as the first peak point, otherwise it is the second peak point; when the previous moment of a moment is the second peak point and the moment is the first peak point, the moment is defined as an instance point; the current moment is the instance point; the instance interval is divided in reverse time direction from the current moment: the set of moments between any two consecutive instance points is an instance interval; if the number of moments in the instance interval is less than the average delay, it is not considered as an instance interval;

[0064] The average value of the number of temperature peaks and the average value of the number of pressure peaks in an instance interval are combined into a two-tuple and recorded as the temperature and pressure instance array; the proportion of the pressure surge points and the temperature surge points in the instance interval are recorded as PVRT and TPRT respectively; the instance abnormal state INS_OL at the current moment is: Where exp is an exponential function with the natural constant e as the base, i1 is an accumulated variable, DEPV is the maximum value of the delayed pressure peaks in the current instance interval, FPV is the maximum value of the pressure peaks in the current instance interval; the instance intervals other than the current instance interval in the current RMTZ period are control instance intervals, NK is the number of control instance intervals, INSS(i1) and INSS_C represent the temperature and pressure instance arrays of the i1th control instance interval and the current instance interval respectively, ds<> is the Euclidean distance function, and the Euclidean distance function returns the Euclidean distance between two called tuples; max<> is the maximum value function;

[0065] If the difference between the anomaly of a moment and the anomaly of the previous moment is the anomaly step difference, and if the anomaly step difference of the current moment is greater than the upper quartile of the anomaly step difference of the current RMTZ period, a high step difference is defined.

[0066] The median value of the instance anomaly obtained at each moment in the current RMTZ period is MOL. If the instance anomaly at the current moment is greater than MOL and a high step difference occurs, the current moment belongs to a temperature and pressure accumulation risk point; the preset risk interval Rsz is 25%; if the proportion of temperature and pressure accumulation in the current instance interval exceeds Rsz, a temperature and pressure accumulation factor is defined, otherwise no temperature and pressure accumulation factor appears.

[0067] Furthermore, in step S400, the method for dynamically controlling the input speed of the high-pressure homogenizer ingredients in combination with the temperature and pressure accumulation factor is: if the temperature and pressure accumulation factor appears at the current moment, the ingredient delivery rate is reduced by 2%; if the temperature and pressure accumulation factor does not appear at the current moment, and the ingredient delivery rate does not reach 100% or does not reach the preset threshold, the ingredient delivery rate is increased by 2%.

[0068] Example 2

[0069] Example 2 adopts the same automatic batching method for ketogenic coffee solid beverage as Example 1, the difference being that in step S300, the method for determining whether a temperature-pressure accumulation factor occurs is to perform an abnormal analysis of the temperature-pressure measured array for the mixing chamber room temperature and pressure by reading the temperature-pressure measured array for 24 hours to form a historical data set;

[0070] The number of temperature peaks and the number of pressure peaks in the historical data set are normalized respectively; the normalization method is MinMax normalization;

[0071] An integer is preset as the cluster quantity NCT, which is 20. The historical data set is divided into NCT clusters by the K-Medoids clustering algorithm. The number of temperature peaks of the cluster center of each cluster is obtained respectively, and the average value of the number of temperature peaks of each cluster center is calculated and recorded as the median thermal amplitude. The absolute value corresponding to the difference between the number of temperature peaks of the cluster center of any cluster and the median thermal amplitude is defined as the cluster thermal deviation.

[0072] Define a cluster as the cluster thermal deviation level CLDG after each cluster is sorted from large to small according to the cluster thermal deviation. The percentage of the number of elements in the cluster to all elements is defined as the cluster point ratio. The first cluster anomaly is e -CLDG The ratio of the cluster points;

[0073] Calculate the Euclidean distance between a cluster and the cluster centers of the remaining clusters, and record the maximum value of the obtained Euclidean distances as the cluster boundary distance of the cluster; the ratio of any cluster boundary distance to the minimum value of the cluster boundary distances of all clusters is the cluster outlier degree;

[0074] The product of the cluster outlier degree and the first cluster heterogeneity is the second cluster heterogeneity; the average value of the second cluster heterogeneity of each cluster is the stable cluster threshold STTH. If the second cluster heterogeneity of a cluster is greater than (1+PSRt)STTH, the cluster is defined as a high-bias cluster; if the second cluster heterogeneity of a cluster is less than (1-PSRt)STTH, the cluster is defined as a low-bias cluster; PSRt is the preset heterogeneity screening rate, which is set to 0.25;

[0075] The real-time temperature and pressure temporary variable array is used to select the cluster to which it belongs at the current moment through the nearest neighbor method. If the cluster to which a moment belongs is a high-bias cluster or a low-bias cluster, it is defined that a high deviation or a low deviation occurs at this moment; a time period is defined as the occurrence condition interval OPRZ, and the value of OPRZ is 100 minutes; the total amount of time, the number of low deviations and the number of high deviations in the current OPRZ time period are recorded as TOTt, TOL and TOH respectively. If TOL+TOH>0.5TOTt, it is defined that a temperature and pressure accumulation factor appears; otherwise, if TOL+TOH>0.1TOTt and TOH>0.5TOL, it is defined that a temperature and pressure accumulation factor appears, otherwise no temperature and pressure accumulation factor appears.

[0076] In the comparative example, during the operation of the high-pressure homogenizer, the speed of the input of ingredients to the high-pressure homogenizer is not controlled, that is, the speed is kept constant to maintain the input of ingredients.

[0077] Table 1

[0078] Comparative Example Example 1 Example 2 Average temperature(℃) 75.35 74.88 74.11 Temperature fluctuation range (%) 9.17 6.46 6.27 Average pressure(MPa) 82.96 81.57 81.46 Pressure fluctuation range (%) 3.62 2.54 2.9 Peroxide value (meq / kg) 9.14 7.45 7.43 Average particle size of fat particles (nm) 140 120 120

[0079] As shown in Table 1, the performance of the ability to solve the problem of lipid oxygen degradation is shown. When the working temperature and working pressure are maintained at the same target value, the stability of temperature and pressure obtained in the embodiment is obviously better than that in the embodiment. This is because the control of the material input speed can effectively reduce the degree of temperature and pressure surge or temperature and pressure accumulation, so that the internal workload is kept within the range of temperature and pressure adaptation. The peroxide value shows that the lipid oxygen degradation problem is effectively solved in the embodiment. The lower degree of lipid oxygen degradation means that the taste of ketogenic coffee has a more favorable guarantee. At the same time, the better particle size of the embodiment implies that this method has an improvement effect on the emulsification ability and emulsification effect. In Example 2, since it is necessary to overcome the problem of excessive pursuit of timeliness in Example 1, its reference scale is released. Under this premise, the pressure fluctuation amplitude is relatively reduced and the temperature amplitude fluctuation is relatively increased. This is because pressure measurement often has high sensitivity and temperature measurement usually has hysteresis, that is, the release of the reference scale reduces the control accuracy.

[0080] An automatic batching system for a ketogenic coffee solid beverage provided by an embodiment of the present invention is as follows: Figure 2Shown is a structural diagram of an automatic dosing system for a ketogenic coffee solid beverage of the present invention. The automatic dosing system for a ketogenic coffee solid beverage of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned embodiment of an automatic dosing method for a ketogenic coffee solid beverage are implemented.

[0081] The system comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to run in the following units of the system:

[0082] The environment acquisition module scene layout unit is used to initialize the high-pressure homogenizer automatic batching scene and identify the environment acquisition module in the high-pressure homogenizer automatic batching scene;

[0083] An environmental information acquisition unit is used to obtain temperature and pressure information from the environmental acquisition module to form a temperature and pressure measurement array;

[0084] A mixing chamber room and pressure anomaly analysis unit is used to analyze the mixing chamber room and pressure anomaly on the temperature and pressure measurement array to determine whether a temperature and pressure accumulation factor occurs;

[0085] The ingredient input control unit is used to dynamically control the ingredient input speed of the high-pressure homogenizer in combination with the temperature and pressure accumulation factor.

[0086] The automatic batching system for ketogenic coffee solid beverages can be run in computing devices such as desktop computers, laptops, PDAs, and cloud servers. The automatic batching system for ketogenic coffee solid beverages, the operating system may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that the example is only an example of an automatic batching method for a ketogenic coffee solid beverage, and does not constitute a limitation on an automatic batching system for a ketogenic coffee solid beverage, which may include more or fewer components than the example, or a combination of certain components, or different components. For example, the automatic batching system for ketogenic coffee solid beverages may also include input and output devices, network access devices, buses, etc.

[0087] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the automatic batching system for ketogenic coffee solid beverages, and various interfaces and lines are used to connect the various parts of the automatic batching system for ketogenic coffee solid beverages.

[0088] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the automatic batching system of the ketogenic coffee solid beverage by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0089] Although the description of the present invention has been quite detailed and has been described in particular with respect to several described embodiments, it is not intended to be limited to any of these details or embodiments or any particular embodiment, so as to effectively cover the intended scope of the present invention. In addition, the present invention is described above with the embodiments foreseeable by the inventors, and its purpose is to provide a useful description, and those non-substantial changes to the present invention that are not currently foreseen may still represent equivalent changes of the present invention.

Claims

1. An automatic batching method for ketogenic coffee solid beverage, characterized in that: The method comprises the following steps: S100, initializing the high-pressure homogenizer automatic batching scene, and identifying the environment acquisition module in the high-pressure homogenizer automatic batching scene; S200, acquiring temperature and pressure information from the environment acquisition module to form a temperature and pressure measurement array; S300, determining whether a temperature and pressure accumulation factor occurs by analyzing the temperature and pressure anomaly of the mixing chamber room and pressure on the temperature and pressure measurement array; S400, dynamically controls the input speed of high-pressure homogenizer ingredients by combining temperature and pressure accumulation factors; The method of determining whether a temperature and pressure accumulation factor occurs by analyzing the room and pressure anomalies of the mixed chamber through the temperature and pressure measured array is as follows: identifying the pressure surge point through the number of pressure peaks, identifying the temperature surge point through the number of temperature peaks, calculating the delay degree using the pressure surge point and the temperature surge point, and calculating the delayed pressure peak through the number of pressure peaks and the delay degree in a preset time period; identifying the first peak number point and the second peak number point according to the delayed pressure peak, and constructing an instance interval through the first peak number point and the second peak number point, calculating the instance anomaly through the temperature and pressure measured array under the instance interval, and determining whether a temperature and pressure accumulation factor occurs using the instance anomaly.

2. The automatic batching method for a ketogenic coffee solid beverage according to claim 1, characterized in that: In step S100, the high-pressure homogenizer automatic batching scene is initialized. The method for identifying the environment acquisition module in the high-pressure homogenizer automatic batching scene is as follows: the high-pressure homogenizer automatic batching scene includes an environment acquisition module, and the environment acquisition module is arranged on the inner wall of the mixing chamber of the high-pressure homogenizer; the environment acquisition module is composed of a pressure sensor and a temperature sensor; The pressure sensor is any one of a piezoelectric pressure sensor, an optical fiber pressure sensor or a ceramic pressure sensor, and the temperature sensor is any one of a thermocouple, an infrared temperature sensor or a semiconductor temperature sensor.

3. The automatic batching method for a ketogenic coffee solid beverage according to claim 1, characterized in that: In step S200, the temperature and pressure information are obtained from the environment acquisition module to form a temperature and pressure measurement array. The method is as follows: the pressure and temperature of the high-pressure homogenizer are collected in real time by a pressure sensor and a temperature sensor, and are recorded as a real-time pressure value and a real-time temperature value, respectively; a time period is set as an information feedback segment IRZ, IRZ∈[1,10] minutes; a temperature and pressure transient variable array is obtained every IRZ, and the temperature and pressure transient variable array is a tuple consisting of a temperature peak number and a pressure peak number; the pressure peak number is the maximum value of each real-time pressure value measured in the information feedback segment IRZ, and the temperature peak number is the maximum value of each real-time temperature value measured in the information feedback segment IRZ.

4. The automatic batching method for a ketogenic coffee solid beverage according to claim 1, characterized in that: In step S300, by analyzing the temperature and pressure anomaly of the mixing chamber room and the pressure measurement array, the method of judging whether the temperature and pressure accumulation factor occurs is as follows: setting a time period as the dynamic monitoring period RMTZ, RMTZ∈[1,5] hours, and the default value is 1 hour; When the number of pressure peaks at a moment is greater than that of the previous moment, the moment is defined as a pressure surge point; when the number of temperature peaks at a moment is greater than that of the previous moment, the moment is defined as a temperature surge point; from each pressure surge point, search the corresponding moment of the first temperature surge point in reverse time direction, record it as the feedback delay point of the pressure surge point, record the number of moments between the pressure surge point and its feedback delay point as the delay degree, calculate the average value of each delay degree in the RMTZ and round it up to the average delay degree EXTN, and take the average value of the number of pressure peaks at a moment and the number of EXTN moments before it as the delayed pressure peak at that moment; If the pressure peak number at a moment is greater than the delayed pressure peak, the moment is defined as the first peak point, otherwise it is the second peak point; when the previous moment of a moment is the second peak point and the moment is the first peak point, the moment is defined as an instance point; the current moment is the instance point; the instance interval is divided in reverse time direction from the current moment: the set of moments between any two consecutive instance points is an instance interval; if the number of moments in the instance interval is less than the average delay, it is not considered as an instance interval; The average value of the number of temperature peaks and the average value of the number of pressure peaks in an instance interval are formed into a two-tuple and recorded as a temperature and pressure instance array; the proportion of pressure surge points and temperature surge points in the instance interval are recorded as PVRT and TPRT respectively; the instance anomaly at the previous moment is calculated based on PVRT and TPRT; If the difference between the anomaly of a moment and the anomaly of the previous moment is the anomaly step difference, and if the anomaly step difference of the current moment is greater than the upper quartile of the anomaly step difference of the current RMTZ period, a high step difference is defined. The median value of the instance anomaly obtained at each moment in the current RMTZ period is MOL. If the instance anomaly at the current moment is greater than MOL and a high step difference occurs, the current moment is a temperature and pressure accumulation risk point; The preset risk interval Rsz, Rsz∈[20%, 50%], if the proportion of temperature and pressure accumulation in the current instance interval exceeds Rsz, then the temperature and pressure accumulation factor is defined to appear, otherwise the temperature and pressure accumulation factor does not appear.

5. The automatic batching method for a ketogenic coffee solid beverage according to claim 1, characterized in that: In step S300, by analyzing the temperature and pressure anomaly of the mixing chamber room and room temperature, a method for determining whether a temperature and pressure accumulation factor occurs is as follows: reading the temperature and pressure measurement array for 24-48 hours to form a historical data set; The number of temperature peaks and pressure peaks in the historical data set are normalized separately; Preset an integer as the cluster quantity NCT, NCT∈[20,40], divide the historical data set into NCT clusters by K-Medoids clustering algorithm, obtain the number of temperature peaks of the cluster center of each cluster respectively, and calculate the average value of the number of temperature peaks of each cluster center as the median thermal amplitude, define the absolute value of the difference between the number of temperature peaks of the cluster center of any cluster and the median thermal amplitude as the cluster thermal deviation; Define a cluster as the cluster thermal deviation level CLDG after each cluster is sorted from large to small according to the cluster thermal deviation. The percentage of the number of elements in the cluster to all elements is defined as the cluster point ratio. The first cluster anomaly is e -CLDG The ratio of the cluster points; Calculate the Euclidean distance between a cluster and the cluster centers of the remaining clusters, and record the maximum value of the obtained Euclidean distances as the cluster boundary distance of the cluster; the ratio of any cluster boundary distance to the minimum value of the cluster boundary distances of all clusters is the cluster outlier degree; The product of the cluster outlier degree and the first cluster heterogeneity is the second cluster heterogeneity; the average value of the second cluster heterogeneity of each cluster is the stable cluster threshold STTH. If the second cluster heterogeneity of a cluster is greater than (1+PSRt)STTH, the cluster is defined as a high-bias cluster; if the second cluster heterogeneity of a cluster is less than (1-PSRt)STTH, the cluster is defined as a low-bias cluster; PSRt is the preset heterogeneity screening rate; The temperature and pressure transient array obtained in real time is used to select the cluster to which it belongs at the current moment through the nearest neighbor method. If the cluster to which a moment belongs is a high-bias cluster or a low-bias cluster, it is defined that a high deviation or a low deviation occurs at this moment; a period is defined as the occurrence condition interval OPRZ, and the value range is OPRZ∈[40,120] minutes; the total amount of time, the number of low deviations and the number of high deviations in the current OPRZ period are recorded as TOTt, TOL and TOH respectively. If TOL+TOH>0.5TOTt, it is defined that the temperature and pressure accumulation factor appears; otherwise, if TOL+TOH>0.1TOTt and TOH>0.5TOL, it is defined that the temperature and pressure accumulation factor appears, otherwise the temperature and pressure accumulation factor does not appear.

6. The automatic batching method for a ketogenic coffee solid beverage according to claim 1, characterized in that: In step S400, the method for dynamically controlling the input speed of the high-pressure homogenizer ingredients in combination with the temperature and pressure accumulation factor is: if the temperature and pressure accumulation factor appears at the current moment, the ingredient delivery rate is reduced by 0.1%-5%; if the temperature and pressure accumulation factor does not appear at the current moment, and the ingredient delivery rate does not reach 100% or does not reach the preset threshold, the ingredient delivery rate is increased by 0.1%-5%.

7. An automatic batching system for ketogenic coffee solid beverage, characterized in that: The automatic batching system for ketogenic coffee solid beverages comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the automatic batching method for ketogenic coffee solid beverages described in any one of claims 1 to 6 are implemented. The automatic batching system for ketogenic coffee solid beverages runs on a desktop computer, a laptop computer, a PDA, and a computing device in a cloud data center.

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