A temperature control system and method for extracting raw materials of traditional Chinese medicine

Abstract

The present invention relates to the field of temperature control technology, specifically to a temperature control system and method for the extraction process of Chinese medicinal materials. The system includes a real-time environment monitoring module, a temperature prediction and adjustment module, an abnormal temperature analysis module, and a temperature control optimization response module. The real-time environment monitoring module collects temperature signals of Chinese medicinal materials extraction equipment based on real-time sensing technology and records humidity changes in the extraction environment. The present invention further improves the accuracy and reaction speed of temperature regulation by real-time collection and analysis of temperature and humidity data, so that even small temperature fluctuations can be detected and included in regulation. Through temperature prediction, the system can effectively foresee future temperature change trends. The combination of this prediction capability and immediate response keeps the temperature in the optimal state during the extraction process, greatly optimizing the extraction rate and quality of effective components. The timely identification and regulation of abnormal temperature points not only prevents potential quality problems, but also reduces energy consumption.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control, and in particular to a temperature control system and method for a Chinese medicinal material raw material extraction process. Background Art

[0002] Temperature control technology involves the technology of accurately regulating and controlling temperature in different industrial and experimental environments. This field is widely used in chemistry, food processing, drug production and other production and research processes that require temperature control. In these fields, temperature changes may affect the properties of substances, reaction rates and product quality. Therefore, temperature control is often designed as automated or semi-automated equipment with the ability to accurately monitor, adjust and maintain set temperatures. Temperature control technology requires not only high precision, but also system stability, efficiency and energy consumption optimization.

[0003] Among them, the temperature control system of the Chinese medicinal material raw material extraction process involves the technology of accurately regulating the temperature during the extraction process of Chinese medicinal materials. The system ensures that the temperature is maintained in an optimal range during the extraction process through automated control means to improve the extraction efficiency and the concentration of the effective ingredients of the medicinal materials, and prevent the extraction effect from being affected by excessively high or low temperatures. It mainly improves the stability, accuracy and production efficiency of Chinese medicinal material extraction. Especially in the traditional Chinese medicine manufacturing process, the temperature control requirements of the extraction process are very high to ensure the quality of Chinese medicinal materials.

[0004] The existing technology lacks a rapid response and prediction mechanism for subtle changes in the environment. In the process of chemical or medicinal material extraction that is highly sensitive to temperature, slight fluctuations in temperature will have an adverse effect on the quality of Chinese medicinal materials. Most of the temperature control systems in the existing technology rely on passive adjustment after the temperature deviates from the preset range. This reactive control strategy is difficult to adjust subtle fluctuations in real time, which can easily lead to low efficiency and unstable quality of Chinese medicinal material extraction. In addition, the traditional system fails to consider the important impact of the interaction between temperature and humidity on the extraction process, lacks the function of combined temperature and humidity control, and makes the adjustment effect unsatisfactory under certain circumstances, which in turn limits the overall production efficiency and quality of Chinese medicinal material extraction. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a temperature control system and method for the extraction process of Chinese medicinal materials.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a temperature control system for the extraction process of Chinese medicinal materials, the system comprising:

[0007] The real-time environmental monitoring module is based on real-time sensing technology. It collects temperature signals from Chinese medicinal material extraction equipment, records humidity changes in the extraction environment, analyzes the correlation between temperature and humidity data, determines the amplitude of temperature fluctuations, calculates the frequency and stability of temperature changes, evaluates deviations from the set values ​​of the extraction equipment, and obtains temperature and humidity monitoring data.

[0008] The temperature prediction and adjustment module analyzes the long-term trend changes of temperature and humidity based on the temperature and humidity monitoring data, calculates the difference between the predicted value and the current data, identifies the trend characteristics of data fluctuations, calibrates the temperature prediction value, matches the temperature control conditions of the extraction process, and evaluates the future temperature change range and trend fluctuations to obtain temperature trend prediction data;

[0009] The abnormal temperature analysis module compares the temperature trend prediction data with the standard temperature control index of the Chinese herbal medicine extraction process, identifies abnormal temperature points, analyzes whether the abnormal points exceed the temperature control setting standards, determines their potential impact on the extraction process, determines the frequency and duration of the abnormal points, and obtains abnormal temperature impact information;

[0010] The temperature control optimization response module optimizes the temperature control parameters of the extraction equipment based on the abnormal temperature impact information, performs temperature control, adjusts the heating power or cooling rate, and determines the stability of the temperature after adjustment according to the real-time monitoring data, evaluates whether it meets the temperature control requirements, and obtains the temperature control optimization result.

[0011] The present invention is improved in that the step of determining the temperature fluctuation amplitude is specifically as follows:

[0012] Based on real-time sensing technology, the temperature signal of the Chinese medicinal material extraction equipment is collected, combined with the humidity change data, the temperature and humidity data at each time point are recorded, and the preliminary temperature and humidity change values ​​are obtained;

[0013] Based on the preliminary temperature and humidity change values, the correlation between temperature and humidity data is analyzed and compared with the standard fluctuation range to determine whether the temperature fluctuation exceeds the set threshold, using the formula:

[0014] ;

[0015] Calculate the temperature fluctuation deviation value at each time point , and the temperature fluctuation amplitude is obtained, where Indicates the real-time temperature value. Indicates the set target temperature value. Indicates the real-time humidity value. Indicates the set target humidity value. It is the adjustment coefficient of humidity to temperature fluctuation deviation.

[0016] The present invention is improved in that the step of acquiring the temperature and humidity monitoring data is specifically as follows:

[0017] Based on the temperature fluctuation amplitude, the number of temperature fluctuations within the time period is counted, the periodicity of the temperature change is calculated, and the temperature stability of the extraction device is evaluated in combination with the time interval to obtain temperature change and stability data;

[0018] Based on the temperature change and stability data, the set temperature and humidity values ​​of the extraction equipment are compared, the deviation from the current temperature and humidity data is evaluated, and the temperature and humidity monitoring data are obtained.

[0019] The present invention is improved in that the step of identifying the trend characteristics of the data fluctuation is specifically as follows:

[0020] Based on the temperature and humidity monitoring data, the timestamp, temperature value and humidity value of each sampling point are marked to obtain a time series data set;

[0021] Based on the time series data set, the cumulative sum of temperature and humidity for each data point is calculated using the formula:

[0022] ;

[0023] Get long-term trend data, where Represents the average temperature value after time attenuation. Representative The temperature value of the data point, is the decay constant, Represents the period from data collection to The time interval between data points, is the number of data points;

[0024] Based on the long-term trend data, the difference between the predicted value at each time point and the current monitoring data is calculated, the data volatility and abnormal points are determined, and the trend characteristics of the data fluctuation are obtained.

[0025] The present invention is improved in that the step of acquiring the temperature trend prediction data is specifically as follows:

[0026] Based on the trend characteristics of the data fluctuations, according to the time series of the temperature data, the temperature fluctuation amplitude at each time point is calculated, the key fluctuation interval is screened, and the temperature value of the fluctuation time period is obtained;

[0027] Based on the temperature value of the fluctuation time period, the temperature control conditions of the extraction process are matched, and the predicted value is calibrated by comparing the difference between the current temperature and the predicted temperature to obtain a calibrated temperature predicted value;

[0028] Based on the calibrated temperature prediction value, the future temperature change range and trend fluctuation are evaluated using the formula:

[0029] ;

[0030] Get temperature trend forecast data ,in, represents the calibrated temperature prediction value, Represents the long-term trend change value, represents the trend adjustment coefficient, represents the fluctuation attenuation coefficient, Represents the exponential function, which is used to calculate the exponential part of the fluctuation decay.

[0031] The present invention is improved in that the step of obtaining the abnormal temperature impact information is specifically as follows:

[0032] Compare the temperature value of each abnormal temperature point with the temperature control standard, analyze whether the abnormal point exceeds the temperature control setting standard, and obtain the abnormal point exceeding standard information;

[0033] Based on the abnormal point exceeding standard information, the formula is adopted:

[0034] ;

[0035] Evaluate the potential impact of each outlier on the extraction process and obtain the impact evaluation result, where: It is The influence of abnormal temperature points, It is The temperature value of the abnormal temperature point, It is the temperature set by the standard temperature control. It is The frequency of abnormal temperature points occurring, It is The duration of abnormal temperature points, It is an adjustment factor used to balance the impact of frequency and duration;

[0036] Based on the impact evaluation result, the occurrence frequency and duration of the abnormal point are determined to obtain abnormal temperature impact information.

[0037] The present invention is improved in that the step of obtaining the temperature control optimization result is specifically as follows:

[0038] Based on the abnormal temperature impact information, according to the extraction equipment performance and target temperature control requirements, the range of change of the adjusted heating power or cooling rate is calculated to obtain a preliminary temperature control optimization configuration;

[0039] Based on the preliminary temperature control optimization configuration, the temperature control operation is performed, and the temperature change data output by the extraction device is monitored in real time, using the formula:

[0040] ;

[0041] The stability of the temperature adjustment process is evaluated to obtain a stability evaluation result, wherein: For the Stability score after temperature adjustment, is the adjusted temperature value, is the target temperature value, is the adjusted heating power or cooling rate, is the maximum power value, is the time required for temperature stabilization, is the target time, Indicates the influence coefficient of power on temperature stability, Indicates the influence coefficient of time on temperature stability;

[0042] Based on the stability evaluation result, it is determined whether the stability after the temperature adjustment meets the temperature control requirements, and a temperature control optimization result is obtained.

[0043] A method for controlling the temperature of a Chinese medicinal material raw material extraction process, the method for controlling the temperature of a Chinese medicinal material raw material extraction process is performed based on the above-mentioned temperature control system for the Chinese medicinal material raw material extraction process, and comprises the following steps:

[0044] S1: Based on real-time sensing technology, collect temperature signals from Chinese medicinal materials extraction equipment, record humidity changes in the extraction environment, analyze the correlation between temperature and humidity data, calculate the frequency and stability of temperature changes, and obtain temperature and humidity monitoring data;

[0045] S2: Based on the temperature and humidity monitoring data, analyze the long-term trend changes of temperature and humidity, calculate the difference between the predicted value and the current data, calibrate the temperature prediction value, and evaluate the future temperature change range and trend fluctuations to obtain temperature trend prediction data;

[0046] S3: Based on the temperature trend prediction data, compare the standard temperature control index of the Chinese herbal medicine extraction process, identify abnormal temperature points, analyze whether the abnormal points exceed the temperature control setting standards, determine their potential impact on the extraction process, and obtain abnormal temperature impact information;

[0047] S4: Based on the abnormal temperature impact information, optimize the temperature control parameters of the extraction equipment, perform temperature control, adjust the heating power or cooling rate, evaluate whether it meets the temperature control requirements, and obtain the temperature control optimization result.

[0048] Compared with the prior art, the advantages and positive effects of the present invention are:

[0049] In the present invention, by real-time collection and analysis of temperature and humidity data, the accuracy and reaction speed of temperature regulation are further improved, so that even tiny temperature fluctuations can be detected and included in the regulation. Through temperature prediction, the system can effectively foresee future temperature change trends. The combination of this prediction ability and instant response maintains the temperature at the optimal state during the extraction process, greatly optimizing the extraction rate of effective ingredients and their quality. The timely identification and regulation of abnormal temperature points not only prevents potential quality problems, but also reduces energy consumption, thereby improving the extraction quality of Chinese medicinal materials and equipment stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 The present invention proposes a temperature control system module diagram for the extraction process of Chinese medicinal materials;

[0051] Figure 2 This is a flow chart for determining the temperature fluctuation amplitude in the present invention;

[0052] Figure 3 It is a flow chart for obtaining temperature and humidity monitoring data in the present invention;

[0053] Figure 4 A flow chart for identifying trend characteristics of data fluctuations in the present invention;

[0054] Figure 5 This is a flow chart for obtaining temperature trend prediction data in the present invention;

[0055] Figure 6 It is a flow chart for obtaining abnormal temperature impact information in the present invention;

[0056] Figure 7 This is a flow chart for obtaining the temperature control optimization results in the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0059] Example: See Figure 1 The present invention provides a technical solution: a temperature control system for the extraction process of Chinese medicinal materials comprises:

[0060] The real-time environmental monitoring module is based on real-time sensing technology. It collects temperature signals from Chinese medicinal material extraction equipment, records humidity changes in the extraction environment, analyzes the correlation between temperature and humidity data, determines the amplitude of temperature fluctuations, calculates the frequency and stability of temperature changes, evaluates deviations from the set values ​​of the extraction equipment, and obtains temperature and humidity monitoring data.

[0061] The temperature prediction and adjustment module analyzes the long-term trend changes of temperature and humidity based on the temperature and humidity monitoring data, calculates the difference between the predicted value and the current data, identifies the trend characteristics of data fluctuations, calibrates the temperature prediction value, matches the temperature control conditions of the extraction process, and evaluates the future temperature change range and trend fluctuations to obtain temperature trend prediction data;

[0062] The abnormal temperature analysis module is based on the temperature trend prediction data, compares the standard temperature control indicators of the Chinese herbal medicine extraction process, identifies abnormal temperature points, analyzes whether the abnormal points exceed the temperature control setting standards, judges their potential impact on the extraction process, determines the frequency and duration of abnormal points, and obtains abnormal temperature impact information;

[0063] The temperature control optimization response module optimizes and extracts the temperature control parameters of the equipment based on the abnormal temperature impact information, performs temperature regulation, adjusts the heating power or cooling rate, and judges the stability of the temperature after adjustment based on real-time monitoring data, evaluates whether it meets the temperature control requirements, and obtains the temperature control optimization results.

[0064] The temperature and humidity monitoring data include temperature stability indicators, set value deviation analysis results, and fluctuation amplitude records. The temperature trend prediction data include predicted calibration values, temperature change ranges, and trend fluctuation characteristics. The abnormal temperature impact information includes exceeding temperature points, potential impact assessment results, and abnormal frequency data. The temperature control optimization results include optimized power settings, cooling rate adjustment results, and stability improvement conditions.

[0065] See also Figure 2 , the specific steps for determining the temperature fluctuation amplitude are:

[0066] Based on real-time sensing technology, the temperature signal of the Chinese medicinal material extraction equipment is collected, combined with the humidity change data, the temperature and humidity data at each time point are recorded, and the preliminary temperature and humidity change values ​​are obtained;

[0067] Real-time temperature and humidity signals are collected through temperature and humidity sensors. Temperature signals are generally obtained through sensors such as thermocouples, RTDs or thermistors, and humidity data are obtained through humidity sensors (such as capacitive, impedance, etc.). After preliminary filtering and denoising, the real-time collected data can obtain the temperature and humidity values ​​at each moment. The changes in temperature and humidity data reflect the fluctuations in the extraction environment. During the recording process, a reasonable collection interval needs to be set to ensure the continuity and integrity of the data and obtain preliminary temperature and humidity change values.

[0068] Based on the preliminary temperature and humidity change values, analyze the correlation between temperature and humidity data, compare with the standard fluctuation range, and determine whether the temperature fluctuation exceeds the set threshold. Use the formula:

[0069] ;

[0070] Calculate the temperature fluctuation deviation value at each time point , and the temperature fluctuation amplitude is obtained, where Indicates the real-time temperature value. Indicates the set target temperature value. Indicates the real-time humidity value. Indicates the set target humidity value. It is the adjustment coefficient of humidity on temperature fluctuation deviation, which is used to adjust the influence weight of humidity in temperature fluctuation calculation and reflect the influence of the interaction between temperature and humidity on the fluctuation amplitude;

[0071] Use the Pearson correlation coefficient, Spearman rank correlation coefficient or other statistical methods to evaluate the correlation between temperature and humidity changes. The value of the correlation coefficient determines the linear or nonlinear relationship between the two. If the correlation is strong, it can be concluded that the changes in temperature and humidity affect each other. Through this correlation analysis result, it can be further determined whether the temperature and humidity fluctuations exceed the set standard range. The standard fluctuation range is generally set by analyzing historical collection data and equipment working requirements. The tolerance range of temperature and humidity changes must be considered when setting. If the real-time collected temperature and humidity changes exceed the preset fluctuation range, it is judged as an abnormal fluctuation, which is used to judge the subsequent temperature fluctuation amplitude. If the current actual temperature of the device is 45°C, the set temperature is 40°C, the actual humidity is 60%, and the humidity is set to 50%, the humidity adjustment coefficient is 0.1, substitute the value into the formula for calculation:

[0072] ;

[0073] ;

[0074] The result shows that the fluctuation deviation value after the combined effects of humidity and temperature is 0.494, indicating that the temperature fluctuation deviation of the equipment is close to the standard within the set range and does not exceed the set normal fluctuation range.

[0075] See also Figure 3 ,The specific steps for obtaining temperature and humidity monitoring data are as follows:

[0076] Based on the temperature fluctuation amplitude, the number of temperature fluctuations within the time period is counted, the periodicity of temperature change is calculated, and combined with the time interval, the temperature stability of the extraction equipment is evaluated to obtain temperature change and stability data;

[0077] The temperature change signal of the equipment is collected in real time through the temperature sensor, the temperature value at each time point is recorded, and the data is used to calculate the number of temperature fluctuations in the time period. The periodicity of the fluctuation is calculated to measure the regularity of the temperature change. The periodicity of temperature change is obtained by analyzing the frequency and amplitude of the temperature change data. Usually, the difference between the maximum and minimum values ​​of the temperature fluctuation in each cycle is calculated, combined with the cycle length, to obtain the periodicity index of temperature change. At the same time, considering the temperature stability of the equipment operating environment and combining the time interval, the standard deviation and mean value of the temperature data are calculated using statistical methods to evaluate the temperature stability, and finally the temperature change and stability data are obtained.

[0078] Based on the temperature change and stability data, compare and extract the set temperature and humidity values ​​of the equipment, evaluate the deviation from the current temperature and humidity data, and obtain the temperature and humidity monitoring data;

[0079] The temperature and humidity data of the equipment are collected and compared to obtain the actual temperature and humidity values, and the deviation is calculated with the preset target temperature and humidity values ​​of the equipment. According to the difference in real-time data, the temperature and humidity deviation between the current state of the equipment and the set value is evaluated, and the operating status and stability of the equipment are further evaluated. This process combines the actual collected data, calculates the difference between the temperature and humidity and the target set value, and obtains the temperature and humidity deviation data of the equipment, so as to evaluate whether the equipment is in normal operation and provide a basis for subsequent equipment regulation.

[0080] See also Figure 4 , the specific steps for identifying the trend characteristics of data fluctuations are:

[0081] Based on the temperature and humidity monitoring data, the timestamp, temperature value and humidity value of each sampling point are marked to obtain a time series data set;

[0082] The timestamp, temperature and humidity values ​​of each sampling point are collected, and data points that do not conform to the reasonable range are eliminated, such as data points with temperature values ​​lower than -50℃ or higher than 70℃, and humidity values ​​lower than 0% or higher than 100%. Then the data are sorted in ascending order according to the timestamp to ensure the consistency of the data time sequence. Next, the temperature and humidity values ​​corresponding to each time point are extracted with the timestamp as the index to construct a time series data set. The time series data set contains the temperature value, humidity value and its corresponding timestamp information at each time point. The data format is stored in the form of a triple (timestamp, temperature, humidity). The data set is then verified for integrity to check whether there are missing values ​​or repeated timestamps. If there are missing values, linear interpolation is used to fill in the missing data. If there are repeated timestamps, the average value is taken.

[0083] Based on the time series data set, calculate the cumulative sum of temperature and humidity for each data point using the formula:

[0084] ;

[0085] Get long-term trend data, where Represents the average temperature value after time attenuation. Representative The temperature value of the data point, is the decay constant used to adjust the impact of time effects on the data, Represents the period from data collection to The time interval between data points, is the number of data points;

[0086] If you have the following data, is the attenuation constant, and its specific value is determined according to the time interval of the data and the trend analysis requirements, and is set to 0.2. is the total number of data points. There are 2 data points. The collected temperature data is: ℃, time interval , substitute into the formula to calculate:

[0087] Calculate the weight of each data point :

[0088] ;

[0089] ;

[0090] calculate :

[0091] ;

[0092] ;

[0093] The numerator is calculated as:

[0094] ;

[0095] The denominator is calculated as:

[0096] ;

[0097] calculate :

[0098] ;

[0099] The results show that the weighted average temperature value after time attenuation is 23.8°C, which represents the long-term trend of temperature data and provides a reference for subsequent volatility analysis and outlier detection.

[0100] Based on long-term trend data, calculate the difference between the predicted value at each time point and the current monitoring data, determine data volatility and abnormal points, and obtain the trend characteristics of data fluctuations;

[0101] The long-term trend value of each time point is extracted from the trend analysis results, and the actual temperature data of the current time point is obtained. The trend value and the actual data are aligned with the timestamp as the index to ensure that the long-term trend value of each time point corresponds to the real-time data one by one. Then the difference value of each time point is calculated. The difference value is defined as the absolute difference between the two sets of data. For all calculated difference values, they are compared with the preset fluctuation threshold one by one. The threshold can be determined according to the fluctuation range of historical monitoring data or a fixed value set manually. If the difference value of a certain time point exceeds the set threshold, the data at that time point is marked as an abnormal point, and the timestamp and difference value of the time point are recorded and saved in the abnormal point record table. Finally, the difference data of all time points are summarized and analyzed to obtain a record table of timestamps and difference values, thereby identifying volatility and abnormal points in the data.

[0102] See also Figure 5 ,The specific steps for obtaining temperature trend prediction data are as follows:

[0103] Based on the trend characteristics of data fluctuations and the time series of temperature data, the temperature fluctuation amplitude at each time point is calculated, the key fluctuation interval is screened, and the temperature value of the fluctuation time period is obtained;

[0104] The temperature fluctuation amplitude at each time point is calculated by comparing the temperature changes between adjacent data points. Specifically, for each pair of adjacent temperature data, the temperature difference between them is calculated to obtain the temperature fluctuation amplitude. In order to identify the key fluctuation interval, a fluctuation amplitude threshold can be set. When the fluctuation amplitude exceeds the threshold, the time period is considered to be the key fluctuation interval. In this way, the time period with large fluctuations can be screened out from the temperature data sequence. For the fluctuation interval, the temperature data within the interval can be further extracted, and the average temperature within the interval or other related statistical values ​​can be calculated. The data will be used for the subsequent temperature control condition matching and temperature calibration process.

[0105] Based on the temperature value of the fluctuation time period, the temperature control conditions of the extraction process are matched, and the predicted value is calibrated by comparing the difference between the current temperature and the predicted temperature to obtain the calibrated temperature predicted value;

[0106] A temperature prediction model is established based on the temperature data extracted from the fluctuation time period. The model generates corresponding temperature prediction values ​​based on historical data and process temperature control requirements. In actual operation, the model needs to be constantly compared with real-time temperature data to calculate the difference between the predicted temperature and the actual temperature. In order to optimize the accuracy of the prediction, the error between the predicted temperature and the actual temperature can be reduced by adjusting the parameters of the model. In practical applications, the parameters of the prediction model are adjusted by minimizing the temperature prediction error. Through this process, the difference between the predicted temperature and the actual temperature can be minimized, thereby obtaining a more accurate temperature prediction value, ensuring that the temperature prediction value is more in line with actual needs.

[0107] Based on the calibrated temperature forecast value, the future temperature change range and trend fluctuation are evaluated using the formula:

[0108] ;

[0109] Get temperature trend forecast data ,in, represents the calibrated temperature prediction value, Represents the long-term trend change value, Represents the trend adjustment coefficient, which is used to adjust the impact of long-term trends on the forecast value. Represents the fluctuation attenuation coefficient, which is used to control the attenuation effect of temperature fluctuation on the predicted value. represents the exponential function, which is used to calculate the exponential part of the fluctuation decay;

[0110] With the following parameters, the calibrated temperature prediction value is , long-term trend change value , trend adjustment coefficient , fluctuation attenuation coefficient ,calculate :

[0111] ;

[0112] Calculate the absolute value:

[0113] ;

[0114] Calculate the exponential part:

[0115] ;

[0116] Then, calculate the fluctuation decay part:

[0117] ;

[0118] ;

[0119] Finally, calculate the temperature trend forecast data:

[0120] ;

[0121] The results show that the temperature trend forecast data is about 25°C. After fluctuation attenuation and trend adjustment, the temperature trend forecast data is very close to the calibrated temperature forecast value, indicating that the current temperature fluctuation has little impact on the long-term trend.

[0122] The specific steps for identifying abnormal temperature points are as follows:

[0123] The temperature data is collected in real time by the temperature sensor installed on the extraction equipment. The temperature value is recorded every 10 seconds, and the collected temperature data is smoothed. The sliding average method is used to calculate the average temperature value every 5 minutes to obtain the temperature change trend curve. The real-time collected temperature value is compared with the temperature change trend curve, and the temperature difference value at each time point is calculated. The difference value is the real-time temperature minus the predicted temperature. The calculated difference value is stored in the difference value array, and the temperature upper limit value and the temperature lower limit value are read. Each difference value in the difference value array is compared with the temperature upper limit value and the temperature lower limit value. If the difference value is greater than the temperature upper limit value or less than the temperature lower limit value, the temperature at that time point is marked as an abnormal temperature point, and the timestamp and corresponding temperature value of the abnormal temperature point are recorded to obtain a list of abnormal temperature points for subsequent temperature control adjustments.

[0124] See also Figure 6 ,The specific steps for obtaining abnormal temperature impact information are:

[0125] Compare the temperature value of each abnormal temperature point with the temperature control standard, analyze whether the abnormal point exceeds the temperature control setting standard, and obtain the abnormal point exceeding standard information;

[0126] First, collect the temperature data monitored in real time during the extraction process, compare the temperature value of each measuring point with the preset standard temperature control temperature (for example, 80°C), calculate the degree of deviation of each temperature point, and mark the points that exceed the standard setting range as abnormal, and obtain the exceeding standard information of the abnormal points. Specifically, the temperature values ​​of all abnormal points will be compared with the standard temperature control temperature. When the temperature deviation exceeds a certain set threshold, the point is considered to be an abnormal temperature point. The threshold can be set according to the actual situation to determine whether the temperature fluctuation exceeds the normal range of the equipment. All temperature points that exceed the range will be recorded to ensure that each abnormal point is accurately identified and marked.

[0127] Based on the abnormal point exceeding standard information, the formula is adopted:

[0128] ;

[0129] Evaluate the potential impact of each outlier on the extraction process and obtain the impact evaluation result, where: It is The influence degree of an abnormal temperature point indicates the potential influence of the abnormal temperature point on the extraction process of Chinese medicinal materials. It is The temperature value of the abnormal temperature point, It is the temperature set by the standard temperature control, which refers to the predetermined temperature control target during the extraction process. It is The frequency of abnormal temperature points occurring during the extraction process. It is The duration of abnormal temperature points, It is an adjustment factor used to balance the impact of frequency and duration;

[0130] If an abnormal temperature point ℃ (monitoring value), standard temperature setting ℃, its occurrence frequency (frequency is 0.4), duration Hours, adjustment factor , substitute into the formula to calculate the influence:

[0131] ;

[0132] ;

[0133] ;

[0134] The results show that the combined influence of temperature deviation, occurrence frequency and duration is 0.0441, indicating that the potential impact of this abnormal temperature point on the extraction process is relatively small.

[0135] Based on the impact assessment results, determine the frequency and duration of abnormal points, and obtain abnormal temperature impact information;

[0136] By calculating the frequency and duration of each abnormal temperature point, combined with the temperature exceeding the standard information, the potential impact is further evaluated. The evaluation process is carried out in a weighted manner. First, a corresponding impact weight is assigned to each abnormal point. This weight is determined based on the frequency and duration of each abnormal point. The higher the frequency and duration, the greater the impact of the abnormal temperature on the extraction process. The weight is adjusted by the set adjustment coefficient to obtain the impact of each abnormal point. The evaluation results are used to analyze the impact of all abnormal points, and finally obtain the potential impact information of abnormal temperature on the extraction process.

[0137] See also Figure 7 , the specific steps for obtaining the temperature control optimization results are:

[0138] Based on the abnormal temperature impact information, according to the extraction equipment performance and target temperature control requirements, the range of changes in the adjusted heating power or cooling rate is calculated to obtain a preliminary temperature control optimization configuration;

[0139] First, the existing heating power or cooling rate of the equipment is obtained, and the variation range of the heating power or cooling rate is calculated by comparing the temperature control standard and the working status of the equipment. The temperature data and the power output of the equipment are fed back for verification. Based on the data, the power adjustment range is evaluated to obtain a preliminary temperature control optimization configuration. This configuration includes the set minimum and maximum heating power or cooling rate and the corresponding time requirements. The adjusted temperature control parameters will serve as the basis for the next adjustment process. The heating power or cooling rate range of the equipment is actually monitored and adjusted.

[0140] Based on the preliminary temperature control optimization configuration, perform temperature control operations, and monitor the temperature change data output by the extraction equipment in real time, using the formula:

[0141] ;

[0142] The stability of the temperature adjustment process is evaluated to obtain a stability evaluation result, wherein: For the Stability score after temperature adjustment, is the adjusted temperature value, is the target temperature value, which is set according to the extraction process requirements. is the adjusted heating power or cooling rate, The maximum power value is the maximum allowed heating or cooling power value, which is used to limit the temperature control range. is the time required for temperature stabilization, The target time is the time required by the process to reach a stable temperature. Indicates the influence coefficient of power on temperature stability, Indicates the influence coefficient of time on temperature stability;

[0143] The following data were collected. The temperature after the hth adjustment is ℃, the target temperature is ℃, the adjusted power is W, the maximum power is W, the stabilization time is min, the target time is min, adjustment factor and , substitute into the formula to calculate the stability score:

[0144] ;

[0145] ;

[0146] The result shows that the stability score of the temperature control system in this adjustment is 0.078, indicating that the stability of the temperature control system after adjustment is good and close to the target temperature requirement.

[0147] Based on the stability evaluation results, determine whether the stability after temperature adjustment meets the temperature control requirements and obtain the temperature control optimization results;

[0148] By monitoring the temperature data output by the equipment in real time and comparing it with the target temperature value, it is determined whether the temperature change of the equipment is within the specified range, the rate of temperature change is calculated, and the temperature stability is determined using the rate. Through the monitoring data collected in actual operation, it is gradually verified whether the temperature adjustment meets the requirements. In the judgment process, the influence of power adjustment and temperature control time on stability is evaluated to obtain the stability evaluation result. Finally, the evaluation result is compared with the predetermined temperature control requirement to confirm whether the temperature control meets the requirements, thereby obtaining the temperature control optimization result.

[0149] A method for controlling temperature during the extraction process of Chinese medicinal materials, comprising the following steps:

[0150] S1: Based on real-time sensing technology, collect temperature signals from Chinese medicinal materials extraction equipment, record humidity changes in the extraction environment, analyze the correlation between temperature and humidity data, calculate the frequency and stability of temperature changes, and obtain temperature and humidity monitoring data;

[0151] S2: Based on the temperature and humidity monitoring data, analyze the long-term trend changes of temperature and humidity, calculate the difference between the predicted value and the current data, calibrate the temperature prediction value, and evaluate the future temperature change range and trend fluctuations to obtain temperature trend prediction data;

[0152] S3: Based on the temperature trend prediction data, compare the standard temperature control indicators of the Chinese herbal medicine extraction process, identify abnormal temperature points, analyze whether the abnormal points exceed the temperature control setting standards, determine their potential impact on the extraction process, and obtain abnormal temperature impact information;

[0153] S4: Based on the abnormal temperature impact information, optimize the temperature control parameters of the extraction equipment, perform temperature control, adjust the heating power or cooling rate, evaluate whether it meets the temperature control requirements, and obtain the temperature control optimization results.

[0154] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A temperature control system for the extraction process of Chinese medicinal materials, characterized in that: The system comprises: The real-time environmental monitoring module is based on real-time sensing technology. It collects temperature signals from Chinese medicinal material extraction equipment, records humidity changes in the extraction environment, analyzes the correlation between temperature and humidity data, determines the amplitude of temperature fluctuations, calculates the frequency and stability of temperature changes, evaluates deviations from the set values ​​of the extraction equipment, and obtains temperature and humidity monitoring data. The temperature prediction and adjustment module analyzes the long-term trend changes of temperature and humidity based on the temperature and humidity monitoring data, calculates the difference between the predicted value and the current data, identifies the trend characteristics of data fluctuations, calibrates the temperature prediction value, matches the temperature control conditions of the extraction process, and evaluates the future temperature change range and trend fluctuations to obtain temperature trend prediction data; The abnormal temperature analysis module compares the temperature trend prediction data with the standard temperature control index of the Chinese herbal medicine extraction process, identifies abnormal temperature points, analyzes whether the abnormal points exceed the temperature control setting standards, determines their potential impact on the extraction process, determines the frequency and duration of the abnormal points, and obtains abnormal temperature impact information; The specific steps of identifying the abnormal temperature point are: The temperature sensor installed on the extraction equipment collects temperature data in real time, records the temperature value every 10 seconds, and smoothes the collected temperature data. The average temperature value within 5 minutes is calculated to obtain the temperature change trend curve. The temperature difference at each time point is obtained by subtracting the predicted temperature from the real-time temperature value. Based on the temperature difference, the standard temperature control index is compared to identify abnormal temperature points that exceed the standard range. The temperature control optimization response module optimizes the temperature control parameters of the extraction equipment based on the abnormal temperature impact information, performs temperature control, adjusts the heating power or cooling rate, and determines the stability of the temperature after adjustment according to the real-time monitoring data, evaluates whether it meets the temperature control requirements, and obtains the temperature control optimization result.

2. The temperature control system for the extraction process of Chinese medicinal materials according to claim 1, characterized in that: The steps for determining the temperature fluctuation amplitude are specifically as follows: Based on real-time sensing technology, the temperature signal of the Chinese medicinal material extraction equipment is collected, combined with the humidity change data, the temperature and humidity data at each time point are recorded, and the preliminary temperature and humidity change values ​​are obtained; Based on the preliminary temperature and humidity change values, the correlation between temperature and humidity data is analyzed and compared with the standard fluctuation range to determine whether the temperature fluctuation exceeds the set threshold, using the formula: ； Calculate the temperature fluctuation deviation value at each time point , and the temperature fluctuation amplitude is obtained, where Indicates the real-time temperature value. Indicates the set target temperature value. Indicates the real-time humidity value. Indicates the set target humidity value. It is the adjustment coefficient of humidity to temperature fluctuation deviation.

3. The temperature control system for the extraction process of Chinese medicinal materials according to claim 1, characterized in that: The steps for obtaining the temperature and humidity monitoring data are specifically as follows: Based on the temperature fluctuation amplitude, the number of temperature fluctuations within the time period is counted, the periodicity of the temperature change is calculated, and the temperature stability of the extraction device is evaluated in combination with the time interval to obtain temperature change and stability data; Based on the temperature change and stability data, the set temperature and humidity values ​​of the extraction equipment are compared, the deviation from the current temperature and humidity data is evaluated, and the temperature and humidity monitoring data are obtained.

4. The temperature control system for the extraction process of Chinese medicinal materials according to claim 1, characterized in that: The steps for identifying the trend characteristics of the data fluctuation are specifically as follows: Based on the temperature and humidity monitoring data, the timestamp, temperature value and humidity value of each sampling point are marked to obtain a time series data set; Based on the time series data set, the cumulative sum of temperature and humidity for each data point is calculated using the formula: ； Get long-term trend data, where Represents the average temperature value after time attenuation. Representative The temperature value of the data point, is the decay constant, Represents the period from data collection to The time interval between data points, is the number of data points; Based on the long-term trend data, the difference between the predicted value at each time point and the current monitoring data is calculated, the data volatility and abnormal points are determined, and the trend characteristics of the data fluctuation are obtained.

5. The temperature control system for the extraction process of Chinese medicinal materials according to claim 1, characterized in that: The steps for obtaining the temperature trend prediction data are specifically as follows: Based on the trend characteristics of the data fluctuations, according to the time series of the temperature data, the temperature fluctuation amplitude at each time point is calculated, the key fluctuation interval is screened, and the temperature value of the fluctuation time period is obtained; Based on the temperature value of the fluctuation time period, the temperature control conditions of the extraction process are matched, and the predicted value is calibrated by comparing the difference between the current temperature and the predicted temperature to obtain a calibrated temperature predicted value; Based on the calibrated temperature prediction value, the future temperature change range and trend fluctuation are evaluated using the formula: ； Get temperature trend forecast data ,in, represents the calibrated temperature prediction value, Represents the long-term trend change value, represents the trend adjustment coefficient, represents the fluctuation attenuation coefficient, Represents the exponential function, which is used to calculate the exponential part of the fluctuation decay.

6. The temperature control system for the extraction process of Chinese medicinal materials according to claim 1, characterized in that: The steps for obtaining the abnormal temperature impact information are specifically as follows: Compare the temperature value of each abnormal temperature point with the temperature control standard, analyze whether the abnormal point exceeds the temperature control setting standard, and obtain the abnormal point exceeding standard information; Based on the abnormal point exceeding standard information, the formula is adopted: ； Evaluate the potential impact of each outlier on the extraction process and obtain the impact evaluation result, where: It is The influence of abnormal temperature points, It is The temperature value of the abnormal temperature point, It is the temperature set by the standard temperature control. It is The frequency of abnormal temperature points occurring, It is The duration of abnormal temperature points, It is an adjustment factor used to balance the impact of frequency and duration; Based on the impact evaluation result, the occurrence frequency and duration of the abnormal point are determined to obtain abnormal temperature impact information.

7. The temperature control system for the extraction process of Chinese medicinal materials according to claim 1, characterized in that: The steps for obtaining the temperature control optimization result are specifically as follows: Based on the abnormal temperature impact information, according to the extraction equipment performance and target temperature control requirements, the range of change of the adjusted heating power or cooling rate is calculated to obtain a preliminary temperature control optimization configuration; Based on the preliminary temperature control optimization configuration, the temperature control operation is performed, and the temperature change data output by the extraction device is monitored in real time, using the formula: ； The stability of the temperature adjustment process is evaluated to obtain a stability evaluation result, wherein: For the Stability score after temperature adjustment, is the adjusted temperature value, is the target temperature value, is the adjusted heating power or cooling rate, is the maximum power value, is the time required for temperature stabilization, is the target time, Indicates the influence coefficient of power on temperature stability, Indicates the influence coefficient of time on temperature stability; Based on the stability evaluation result, it is determined whether the stability after the temperature adjustment meets the temperature control requirements, and a temperature control optimization result is obtained.

8. A method for controlling temperature during the extraction process of Chinese medicinal materials, characterized in that: The temperature control system for the extraction process of Chinese medicinal materials according to any one of claims 1 to 7 comprises the following steps: S1: Based on real-time sensing technology, collect temperature signals from Chinese medicinal materials extraction equipment, record humidity changes in the extraction environment, analyze the correlation between temperature and humidity data, calculate the frequency and stability of temperature changes, and obtain temperature and humidity monitoring data; S2: Based on the temperature and humidity monitoring data, analyze the long-term trend changes of temperature and humidity, calculate the difference between the predicted value and the current data, calibrate the temperature prediction value, and evaluate the future temperature change range and trend fluctuations to obtain temperature trend prediction data; S3: Based on the temperature trend prediction data, compare the standard temperature control index of the Chinese herbal medicine extraction process, identify abnormal temperature points, analyze whether the abnormal points exceed the temperature control setting standards, determine their potential impact on the extraction process, and obtain abnormal temperature impact information; S4: Based on the abnormal temperature impact information, optimize the temperature control parameters of the extraction equipment, perform temperature control, adjust the heating power or cooling rate, evaluate whether it meets the temperature control requirements, and obtain the temperature control optimization result.

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