Intelligent regulation and control system and regulation and control method for storage environment of traditional Chinese medicinal materials

Abstract

The invention discloses an intelligent regulation and control system and regulation and control method for a traditional Chinese medicinal material storage environment, particularly relates to the technical field of storage regulation and control, and aims to solve the problem that quality is reduced due to the fact that existing storage environment control parameters are fixed and physicochemical property changes of traditional Chinese medicinal materials are difficult to respond in time. The method comprises the following steps: acquiring environmental parameters in a storage environment and physicochemical property data of traditional Chinese medicinal materials in real time, adding a timestamp, comparing an initial calibration model with stored reference data, and distinguishing deviations caused by moisture redistribution and active ingredient micro-degradation by using a neural network and wavelet transform combination algorithm; aiming at different deviations, a multi-parameter coupling control algorithm and an incremental calibration method optimized by a genetic algorithm are respectively adopted to carry out adaptive adjustment and correction, and finally, combined dynamic adjustment is carried out on the environmental parameters based on adjustment and correction results, so that accurate matching between the environmental parameters and actual requirements of the traditional Chinese medicinal materials is realized. Therefore, the storage life is prolonged and the quality is improved.

Description

Technical Field

[0001] The present invention relates to the field of storage control technology, and more specifically, to an intelligent control system and control method for a Chinese medicinal material storage environment. Background Art

[0002] As Chinese medicinal materials are stored for extended periods, their physical and chemical properties gradually change. These changes, such as moisture redistribution and micro-degradation of active ingredients, gradually become apparent. Traditionally, recommended environmental parameters are often developed based on the initial state of the materials, and these parameters may no longer be applicable during long-term storage. Currently, most warehouse management systems perform environmental control based solely on initial parameters, failing to fully account for the physical and chemical changes that occur during storage. This leads to a mismatch between environmental parameters like temperature and humidity and the actual state of the materials, impacting their quality preservation.

[0003] How to achieve dynamic matching between environmental parameters and the physical and chemical properties data of Chinese medicinal materials, and timely adjust environmental control parameters to ensure that environmental parameters always meet the actual needs of Chinese medicinal materials, is a technical problem that needs to be urgently solved by existing technologies. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide an intelligent control system and control method for a Chinese medicinal material storage environment to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for intelligently controlling a storage environment of Chinese medicinal materials comprises the following steps: Collect environmental parameters and physical and chemical properties of Chinese medicinal materials in the storage environment and attach timestamps; The initial calibration model is used to compare the environmental parameters and the physical and chemical properties of Chinese medicinal materials with the stored reference data. If the comparison results have a large deviation, the next step is entered. A neural network and wavelet transform algorithm were used to analyze environmental parameters and physical and chemical properties of Chinese medicinal materials, and to distinguish deviations caused by water redistribution and microdegradation of active ingredients. In response to the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded; To address deviations caused by micro-degradation of active ingredients, an incremental calibration method optimized by a genetic algorithm is used to correct environmental parameters and the physical and chemical properties of traditional Chinese medicines, update the initial calibration model, and generate sensor calibration update results. The environmental parameters are jointly and dynamically adjusted based on the environmental adjustment results and the sensor calibration update results to maintain a predetermined matching relationship between the environmental parameters and the physical and chemical properties data of Chinese medicinal materials.

[0006] In a preferred embodiment, the environmental parameters and physical and chemical properties of Chinese medicinal materials in the storage environment are collected and timestamped, including: Collect environmental parameters of the storage environment within the storage environment, including temperature data, relative humidity data, air pressure data, and carbon dioxide concentration data; Collecting data on the physical and chemical properties of Chinese medicinal materials in the Chinese medicinal materials storage area. The data on the physical and chemical properties of Chinese medicinal materials include water content data, active ingredient concentration data, and surface color data of the Chinese medicinal materials; In the process of collecting environmental parameters and physical and chemical properties data of Chinese medicinal materials, a timestamp that clearly identifies the moment of data collection is added to the environmental parameters and physical and chemical properties data of Chinese medicinal materials by synchronously recording the collection time.

[0007] In a preferred embodiment, the environmental parameters and the physical and chemical properties of the Chinese medicinal materials are compared with the stored reference data using the initial calibration model. If the comparison result deviates greatly, the next step is entered, including: Acquire reference data, the reference data including environmental parameter reference data corresponding to environmental parameters in the storage environment and Chinese medicinal material physical and chemical property reference data corresponding to Chinese medicinal material physical and chemical property data; The initial calibration model is used to compare the environmental parameters with the corresponding environmental parameter reference data, and the physical and chemical properties data of Chinese herbal medicines with the corresponding physical and chemical properties reference data of Chinese herbal medicines. The comparison process adopts the calculation method of data numerical difference; A preset deviation threshold is set. When the numerical difference between the environmental parameters or the physical and chemical properties data of Chinese medicinal materials and their corresponding reference data exceeds the preset deviation threshold, it is determined that there is a large deviation in the comparison result.

[0008] In a preferred embodiment, a neural network combined with a wavelet transform algorithm is used to analyze environmental parameters and physical and chemical properties of Chinese medicinal materials, and to distinguish deviations caused by water redistribution and micro-degradation of active ingredients, including: Environmental parameters and physical and chemical properties of Chinese medicinal materials are used as input data. Wavelet transform is used to perform multi-scale decomposition on the input data, and local features and spectral characteristics of each data item are extracted through time-frequency analysis. The local features and spectral characteristics obtained after wavelet transform are passed as input to a pre-established feedforward neural network, which is used to perform nonlinear mapping and data fitting on the input data to obtain output results reflecting the environmental status and changes in the physical and chemical properties of Chinese medicinal materials. Wherein, the feedforward neural network includes an input layer, at least one hidden layer and an output layer; The output results are analyzed using pre-set data comparison rules. By comparing the predetermined judgment parameters involved in the output results with the pre-recorded characteristic parameters generated by water redistribution and the characteristic parameters generated by micro-degradation of active ingredients, deviations in environmental parameters and physical and chemical properties data of Chinese medicinal materials caused by water redistribution and micro-degradation of active ingredients are distinguished.

[0009] In a preferred embodiment, in response to the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded, including: Extract temperature data and relative humidity data from environmental parameters, ensuring consistency in data format, collection time, and data item order during collection; The extracted temperature data and relative humidity data are jointly analyzed using a multi-parameter coupling control algorithm to determine the coupling relationship between the temperature data and the relative humidity data. This coupling relationship quantitatively reflects the dynamic characteristics of the mutual influence of temperature and relative humidity in the storage environment. Adaptively adjust the temperature data and relative humidity data based on the coupling relationship and the pre-set adjustment target. The adaptive adjustment process includes adjusting the temperature set value and the relative humidity set value in real time so that the adjusted temperature data and relative humidity data tend to the target values ​​specified by the pre-stored environmental parameter reference data. During the implementation of the adaptive adjustment process, the adjustment process of the temperature setting value and the relative humidity setting value is continuously recorded. The recorded content includes the start time of the adjustment, the value change during the adjustment process, and the final value at the end of the adjustment, thereby forming the environmental adjustment result.

[0010] In a preferred embodiment, the extracted temperature data and relative humidity data are jointly analyzed using a multi-parameter coupling control algorithm to determine the coupling relationship between the temperature data and the relative humidity data, specifically: The multi-parameter coupling control algorithm adopts a joint data analysis method, taking temperature data and relative humidity data as the overall input, and performs real-time data statistics and dynamic trend analysis. The quantitative description of the coupling relationship is expressed as: ;in, Represents the coupling relationship function between temperature data and relative humidity data, Indicates temperature data at time The function expression below is Represents the function corresponding to the relative humidity data, represents a position variable in time or a data series, represents the translation parameter of temperature data, Represents the scaling parameter for relative humidity data.

[0011] In a preferred embodiment, to address the deviation caused by micro-degradation of active ingredients, an incremental calibration method optimized by a genetic algorithm is used to correct environmental parameters and the physical and chemical properties of Chinese medicinal materials, update the initial calibration model, and generate a sensor calibration update result, including: Extract deviation information reflecting micro-degradation of active ingredients from environmental parameters and physical and chemical properties of Chinese medicinal materials; Adopting the incremental calibration method optimized by genetic algorithm, the extracted deviation information is dynamically corrected and the correction increment data is calculated; According to the calculated correction increment data, the environmental parameters and the physical and chemical properties of Chinese medicinal materials are corrected item by item, and the initial calibration model is updated; Record the changes of each data item before and after the correction during the correction process, generate and output the sensor calibration update result data.

[0012] In a preferred embodiment, the environmental parameters are jointly and dynamically adjusted based on the environmental adjustment results and the sensor calibration update results to maintain a predetermined matching relationship between the environmental parameters and the physical and chemical property data of the Chinese medicinal materials, including: Extract data information from environmental adjustment results and sensor calibration update results, and integrate them to generate joint adjustment input data; Calculate the numerical deviation between the current environmental parameters and the predetermined matching target based on the joint adjustment input data to obtain a quantitative deviation value; According to the quantitative deviation value, a dynamic adjustment strategy is used to adjust the set values ​​of temperature and relative humidity in real time, so that they gradually tend to the predetermined targets; Continuously monitor the adjusted environmental parameters, and record and archive the adjustment process and final results to form complete joint dynamic adjustment feedback data.

[0013] On the other hand, the present invention provides an intelligent control system for the storage environment of traditional Chinese medicine, including a storage data acquisition module, an initial calibration and comparison module, a neural wavelet analysis module, a temperature and humidity coupling adjustment module, a genetic calibration update module and a joint dynamic adjustment module; Warehouse data collection module: collects environmental parameters and physical and chemical properties of Chinese medicinal materials in the storage environment and adds time stamps; Initial calibration and comparison module: uses the initial calibration model to compare environmental parameters and Chinese medicinal material physical and chemical properties data with the stored reference data, and proceeds to the next step if the comparison result has a large deviation; Neural Wavelet Analysis Module: This module uses a combination of neural networks and wavelet transform algorithms to analyze environmental parameters and the physical and chemical properties of Chinese medicinal materials, and distinguish deviations caused by water redistribution and micro-degradation of active ingredients. Temperature and humidity coupling adjustment module: To address the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded; Genetic calibration update module: To address deviations caused by micro-degradation of active ingredients, an incremental calibration method optimized by genetic algorithms is used to correct environmental parameters and physical and chemical properties of Chinese medicinal materials, update the initial calibration model, and generate sensor calibration update results; Joint dynamic adjustment module: Based on the environmental adjustment results and sensor calibration update results, the environmental parameters are jointly and dynamically adjusted to maintain the predetermined matching relationship between the environmental parameters and the physical and chemical properties data of Chinese medicinal materials.

[0014] The technical effects and advantages of the intelligent control system and control method for the storage environment of traditional Chinese medicines of the present invention are as follows: 1. The present invention's intelligent storage environment control method collects environmental parameters and Chinese medicinal material physical and chemical property data in real time, and dynamically analyzes this data using an initial calibration model and intelligent algorithms. This method accurately identifies deviations in Chinese medicinal materials during storage due to moisture redistribution and micro-degradation of active ingredients, thereby enabling adaptive adjustment of key environmental parameters such as temperature and humidity. Using a combined neural network and wavelet transform algorithm, along with an incremental calibration method optimized by a genetic algorithm, the method ensures that environmental parameters consistently match the Chinese medicinal material physical and chemical property data, effectively preventing the degradation of Chinese medicinal material quality caused by environmental parameter mismatches.

[0015] 2. The present invention dynamically adjusts storage environment parameters based on the combined results of environmental adjustments and sensor calibration updates, enabling continuous tracking and automatic correction of storage environment parameters. This ensures closed-loop feedback during the adjustment process, consistent data, and high control accuracy. This overcomes the drawbacks of existing technologies, which often involve fixed environmental control parameters and an inability to respond promptly to changes in the state of Chinese medicinal materials. Furthermore, it achieves real-time matching between environmental parameters and the actual needs of Chinese medicinal materials, effectively extending the storage period of Chinese medicinal materials and improving their storage quality. The system offers significant advantages, including rapid response, accurate control, and strong adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of an intelligent control method for a Chinese medicinal material storage environment according to the present invention; Figure 2 This is a structural schematic diagram of an intelligent control system for a Chinese medicinal material storage environment according to the present invention. DETAILED DESCRIPTION

[0017] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] Example 1: Figure 1 The present invention provides an intelligent control method for a Chinese medicinal material storage environment, which comprises the following steps: Collect environmental parameters and physical and chemical properties data of Chinese medicinal materials in the storage environment and attach timestamps.

[0019] The initial calibration model is used to compare the environmental parameters and the physical and chemical properties of Chinese medicinal materials with the stored reference data, and the next step is entered when the comparison results have a large deviation.

[0020] A neural network and wavelet transform combined algorithm was used to analyze environmental parameters and physicochemical properties of Chinese medicinal materials, and to distinguish deviations caused by water redistribution and microdegradation of active ingredients.

[0021] Aiming at the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded.

[0022] To address the deviation caused by micro-degradation of active ingredients, an incremental calibration method optimized by genetic algorithm is used to correct environmental parameters and physical and chemical properties data of traditional Chinese medicine, update the initial calibration model and generate sensor calibration update results.

[0023] The environmental parameters are jointly and dynamically adjusted based on the environmental adjustment results and the sensor calibration update results to maintain a predetermined matching relationship between the environmental parameters and the physical and chemical properties data of traditional Chinese medicine.

[0024] Collect environmental parameters and physical and chemical properties of Chinese medicinal materials in the storage environment and add time stamps, including: Environmental parameters of the storage environment are collected in the storage environment, including temperature data, relative humidity data, air pressure data and carbon dioxide concentration data.

[0025] To achieve real-time monitoring of the storage environment and the status of Chinese medicinal materials, sensors are first installed within the storage environment to continuously collect environmental parameters. Specifically, a temperature sensor collects temperature data, a relative humidity sensor collects relative humidity data, an air pressure sensor collects air pressure data, and a carbon dioxide concentration sensor collects carbon dioxide concentration data. The temperature, relative humidity, air pressure, and carbon dioxide concentration data together constitute the environmental parameters.

[0026] The physical and chemical property data of Chinese medicinal materials are collected in the Chinese medicinal materials storage area. The physical and chemical property data of Chinese medicinal materials include the moisture content data of Chinese medicinal materials, the active ingredient concentration data and the surface color data of Chinese medicinal materials.

[0027] Sensors are installed in the Chinese medicinal material storage area to continuously collect data on the physical and chemical properties of the Chinese medicinal materials. Specifically, the moisture sensor collects moisture content data, the active ingredient concentration sensor collects active ingredient concentration data, and the color detection sensor collects surface color data. The moisture content data, active ingredient concentration data, and surface color data of the Chinese medicinal materials together constitute the physical and chemical property data of the Chinese medicinal materials.

[0028] In the process of collecting environmental parameters and physical and chemical properties data of Chinese medicinal materials, a timestamp that clearly identifies the moment of data collection is added to the environmental parameters and physical and chemical properties data of Chinese medicinal materials by synchronously recording the collection time.

[0029] During the collection of these environmental parameters and TCM material physiochemical properties, a data collection time recording device was established. This device, synchronized with the sensor's acquisition process, records each data collection moment in real time. The recorded collection moment is digitally converted to a standard time format and recorded alongside the environmental parameters and TCM material physiochemical properties data as the data is generated. This provides each data point with a timestamp clearly identifying the collection moment.

[0030] The initial calibration model is used to compare the environmental parameters and the physical and chemical properties of Chinese medicinal materials with the stored reference data. If the comparison results deviate significantly, the next step is taken, including: Reference data are obtained, including environmental parameter reference data corresponding to environmental parameters in the storage environment and physical and chemical property reference data of Chinese medicinal materials corresponding to physical and chemical property data of Chinese medicinal materials.

[0031] To ensure the accuracy of data comparison, environmental parameter reference data corresponding one-to-one to environmental parameters, as well as Chinese medicinal material physical and chemical property reference data corresponding one-to-one to Chinese medicinal material physical and chemical property data are pre-stored. The reference data and the collected data are consistent in terms of items, sequence and data format.

[0032] Reference data refers to standard benchmarks derived from historical measurements or experimental data before the storage environment is operational. For example, environmental parameter reference data might be the average of multiple measurements taken under standard conditions (e.g., temperature of 25°C, relative humidity of 50%, air pressure of 101.3 kPa, and carbon dioxide concentration of 400 ppm). Reference data for the physical and chemical properties of traditional Chinese medicines might be, for example, a moisture content of 10%, an active ingredient concentration of 2 mg / g, and surface color indicators meeting predetermined standards under ideal storage conditions.

[0033] The initial calibration model is used to compare the environmental parameters with the corresponding environmental parameter reference data, and the physical and chemical properties data of Chinese medicinal materials with the corresponding physical and chemical properties reference data of Chinese medicinal materials. The comparison process adopts the calculation method of data numerical difference.

[0034] Using the initial calibration model, the environmental parameters and the physical and chemical properties data of Chinese medicinal materials are compared one by one with their corresponding reference data. Specifically, the initial calibration model compares the temperature data with the reference value of the corresponding temperature in the environmental parameter reference data, and compares the relative humidity data, air pressure data, and carbon dioxide concentration data with their corresponding reference values. For the physical and chemical properties data of Chinese medicinal materials, the initial calibration model compares the moisture content data, active ingredient concentration data, and the surface color data of Chinese medicinal materials with the corresponding physical and chemical properties reference data of Chinese medicinal materials in storage. The comparison process adopts the method of calculating the numerical difference of data, that is, the numerical difference between each collected data and its corresponding reference data is calculated. The numerical difference can be determined by calculating the absolute value or relative percentage of the two, thereby quantifying the gap between each data item.

[0035] The initial calibration model refers to a set of pre-set calibration rules, which compares the environmental parameters and physical and chemical properties of Chinese medicinal materials collected in real time with the above-mentioned reference data one by one, and uses a difference calculation method (such as calculating the absolute difference or relative percentage difference between each data item) to determine the degree of deviation between the data, and sets a predetermined allowable error range; when the difference between the measured value of any data item and its corresponding reference data exceeds the allowable error, it is determined that there is a large deviation in the data, and a deviation signal is output to trigger subsequent processing steps.

[0036] A preset deviation threshold is set. When the numerical difference between the environmental parameters or the physical and chemical properties data of Chinese medicinal materials and their corresponding reference data exceeds the preset deviation threshold, it is determined that there is a large deviation in the comparison result.

[0037] The preset deviation threshold is the maximum allowable numerical difference between each data item. When the numerical difference between any environmental parameter or TCM material physical and chemical property data and its corresponding reference data exceeds this preset deviation threshold, the initial calibration model determines that the data has a significant deviation. To this end, the initial calibration model outputs a corresponding deviation signal, instructing the overall system to proceed to the next step for further processing.

[0038] The initial calibration model uses the same item order and data format as the collected data during one-to-one comparisons, ensuring accurate alignment between environmental parameters, parameters in the TCM physicochemical properties data, and their corresponding reference data. After the comparisons are complete, the initial calibration model records and saves the differences between the data. This data provides the necessary basis for further analysis and dynamic adjustments in subsequent steps.

[0039] A neural network combined with a wavelet transform algorithm is used to analyze environmental parameters and the physical and chemical properties of Chinese medicinal materials, and to distinguish deviations caused by water redistribution and micro-degradation of active ingredients, including: Environmental parameters and physical and chemical properties of Chinese medicinal materials are used as input data. The input data are decomposed at multiple scales using wavelet transform method, and the local features and spectral characteristics of each data item are extracted through time-frequency analysis.

[0040] Preprocess the input data to form a unified data set to ensure the consistency of the format, order and dimension of each data item in the subsequent processing process, and ensure the coherence and consistency of the data throughout the analysis process.

[0041] The above input data is subjected to multi-scale decomposition using the wavelet transform method. Specifically, the wavelet transform method decomposes each input data item into components of different scales through time-frequency analysis, thereby extracting the local characteristics and spectral characteristics of each data item at different time scales. The continuous wavelet transform is used, and its mathematical expression is as follows: ;in, Represents the transformation coefficient under the translation parameter and scale parameter, which is used to reflect the characteristics of the input signal in the local area; represents an input signal function, which in this embodiment corresponds to a numerical sequence of a single environmental parameter or physical and chemical property data of a Chinese herbal medicine; Represents the selected wavelet function, and its complex conjugate is ; represents the integration variable, which represents the position or time in the input data sequence; is the translation parameter, which is used to determine the position of the local feature in the input data; is a scale parameter used to control the degree of expansion and contraction of the wavelet function, thereby capturing different frequency components.

[0042] Through the above-mentioned continuous wavelet transform processing, each input data can obtain multi-scale local feature information and spectral distribution information. This information provides a detailed description for the subsequent nonlinear mapping and ensures the capture and quantification of subtle changes in the input data.

[0043] The local features and spectral characteristics obtained after wavelet transform processing are passed as input to a pre-established feedforward neural network, which is used to perform nonlinear mapping and data fitting on the input data to obtain output results reflecting the environmental status and changes in the physical and chemical properties of Chinese medicinal materials.

[0044] The feedforward neural network includes an input layer, at least one hidden layer and an output layer.

[0045] The local features and spectral characteristics obtained after wavelet transform processing are passed as input to a pre-established feedforward neural network. The feedforward neural network consists of an input layer, at least one hidden layer and an output layer. Its structure is determined through training based on historical collected data and corresponding reference data in this embodiment. The input layer receives multi-scale data after wavelet transform processing, the hidden layer performs nonlinear operations on the input data, and the output layer outputs results reflecting the environmental status and changes in the physical and chemical properties of Chinese medicinal materials. During the training process, the feedforward neural network continuously adjusts the network weights and biases to accurately map the complex nonlinear relationship between input data and output results, and forms a mathematical model that can be used for real-time data fitting.

[0046] The output results are analyzed using pre-set data comparison rules. By comparing the predetermined judgment parameters involved in the output results with the pre-recorded characteristic parameters generated by water redistribution and the characteristic parameters generated by micro-degradation of active ingredients, deviations in environmental parameters and physical and chemical properties data of Chinese medicinal materials caused by water redistribution and micro-degradation of active ingredients are distinguished.

[0047] Specifically, two types of characteristic parameters are pre-recorded in this embodiment: characteristic parameters caused by water redistribution, which are used to describe the characteristics produced when the local and overall distribution of water content data in Chinese medicinal materials changes; characteristic parameters caused by micro-degradation of active ingredients, which are used to describe the characteristics of active ingredient concentration data in Chinese medicinal materials during the micro-degradation process.

[0048] Among them, the data comparison rule adopts a quantitative comparison method to compare the judgment indicators in the output results of the neural network with the above-mentioned pre-recorded water redistribution characteristic parameters and active ingredient micro-degradation characteristic parameters item by item. To clarify the comparison rules, the following judgment steps are set in this embodiment: first, a judgment indicator reflecting the overall environmental state and changes in the physical and chemical properties of the Chinese medicinal materials is extracted from the output results of the neural network; second, the judgment indicator is compared with the recorded water redistribution characteristic parameters. If the two are highly consistent in the numerical range or fluctuation characteristics, it is determined that the input data mainly has deviations caused by water redistribution; otherwise, the judgment indicator is compared with the recorded active ingredient micro-degradation characteristic parameters. If the judgment indicator matches, it is determined that the input data mainly has deviations caused by active ingredient micro-degradation. The numerical calculations in the entire comparison process can use absolute error, relative error or other quantitative evaluation methods to ensure the accuracy of the output results.

[0049] Throughout the entire process, the multi-scale local features and spectral characteristics extracted by wavelet transform processing provide rich input information for the feedforward neural network, while the neural network's nonlinear mapping and data fitting enable the output results to accurately reflect the storage environment status and changes in the physical and chemical properties of traditional Chinese medicines. Subsequently, using pre-set data comparison rules, the judgment indicators in the neural network output results are compared with two types of pre-recorded characteristic parameters, accurately distinguishing deviations in the environmental parameters and the physical and chemical properties of traditional Chinese medicines caused by water redistribution and micro-degradation of active ingredients, respectively.

[0050] To address the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded, including: Temperature data and relative humidity data are extracted from environmental parameters, and the consistency of data format, collection time and data item order is guaranteed during collection.

[0051] For example, in a storage environment, the pre-collected temperature data, relative humidity data, air pressure data, and carbon dioxide concentration data are pre-processed, and only the temperature data and relative humidity data are selected for subsequent adjustment; at this time, ensure that the structure, time stamp, and arrangement order of the data file remain unchanged with the original collected data to facilitate subsequent joint processing and comparison of the data.

[0052] The extracted temperature data and relative humidity data were jointly analyzed using a multi-parameter coupling control algorithm to determine the coupling relationship between the temperature data and the relative humidity data. This coupling relationship quantitatively reflects the dynamic characteristics of the mutual influence of temperature and relative humidity in the storage environment.

[0053] In this step, the multi-parameter coupling control algorithm uses a joint data analysis method, taking temperature data and relative humidity data as the overall input, and performs real-time data statistics and dynamic trend analysis. The quantitative description of this coupling relationship can be introduced into the following mathematical expression: ;in, A function that represents the coupling relationship between temperature data and relative humidity data. This function is used to quantitatively describe the dynamic characteristics of the mutual influence between temperature and relative humidity in a storage environment. Indicates temperature data at time The function expression below is used to describe the time series changes of temperature data; Represents the function corresponding to the relative humidity data, which is used to describe the change of relative humidity data after linear transformation; Represents the position variable in time or data sequence, and is used to characterize the temporal characteristics of data during the integral calculation process; Represents the translation parameter of the temperature data, which is used to adjust the position matching of the temperature data in the calculation to facilitate coupled calculation; Represents the scaling parameter for the relative humidity data, used to adjust the relative humidity data's scale during the coupled calculation to align it with the temperature data. This formula quantitatively describes the data coupling relationship. The actual calculation process is based on numerical integration, ensuring that the output accurately reflects the dynamic coupling characteristics between temperature and relative humidity data.

[0054] Based on the coupling relationship and the pre-set adjustment target, the temperature data and relative humidity data are adaptively adjusted. The adaptive adjustment process includes real-time adjustment of the temperature set value and the relative humidity set value so that the adjusted temperature data and relative humidity data tend to the target value specified by the pre-stored environmental parameter reference data.

[0055] Specifically, the pre-stored environmental parameter reference data clearly specifies the target values ​​for temperature and relative humidity, where the target value for temperature is a set fixed value, and the target value for relative humidity is a set fixed value. After obtaining the results of the coupling relationship analysis, a real-time feedback mechanism is used to calculate the deviation between the currently measured temperature data and the temperature target value, as well as the deviation between the currently measured relative humidity data and the relative humidity target value. Based on this deviation information, proportional, integral, and differential control methods or other known adaptive adjustment methods are used to dynamically adjust the temperature set value and the relative humidity set value. During this process, the adjustment system will correct the control parameters in real time according to the changing trend of the current deviation to ensure the continuous update of the adjustment instructions, so that the temperature data and relative humidity data gradually approach the preset target values ​​after multiple adjustments, and ultimately meet the set control requirements.

[0056] During the implementation of the adaptive adjustment process, the adjustment process of the temperature setting value and the relative humidity setting value is continuously recorded. The recorded content includes the start time of the adjustment, the value change during the adjustment process, and the final value at the end of the adjustment, thereby forming the environmental adjustment result.

[0057] In this step, a data table is created to automatically record the timestamp, real-time temperature setpoint, and relative humidity setpoint for each adjustment. The data format, recording interval, and data item sequence used during this recording process remain consistent with the previously described data collection steps, ensuring that the recorded results can be traced throughout the entire adjustment process. The recorded numerical data can be used for subsequent analysis of system performance or as a basis for further feedback adjustments to ensure that environmental parameters continue to meet target requirements.

[0058] To address deviations caused by micro-degradation of active ingredients, an incremental calibration method optimized by a genetic algorithm is used to correct environmental parameters and the physical and chemical properties of traditional Chinese medicines. This method updates the initial calibration model and generates updated sensor calibration results, including: Extract deviation information caused by microdegradation of active ingredients from environmental parameters and physical and chemical properties data of traditional Chinese medicine.

[0059] First, pre-processing is performed on pre-collected environmental parameters (including temperature, relative humidity, air pressure, and carbon dioxide concentration) and TCM physiochemical property data (including moisture content, active ingredient concentration, and surface color data). After pre-processing, specific data items that reflect the microdegradation effects of active ingredients are screened, ensuring consistent acquisition time and data item sequence. Deviation information is the difference between the actual measured value and pre-stored TCM physiochemical property reference data. This pre-stored reference data is the average value of multiple measurements under standard storage conditions, and its numerical standard is used to determine the microdegradation of active ingredient concentrations.

[0060] An incremental calibration method optimized by genetic algorithm is used to dynamically correct the extracted deviation information and calculate the correction increment data.

[0061] The extracted deviation information is used as input and dynamically corrected in real time using an incremental calibration method optimized by a genetic algorithm. This "incremental calibration method optimized by a genetic algorithm" is a numerical correction technique based on the principle of iterative optimization. Its core concept is to gradually adjust small deviations in the data by continuously searching for the optimal combination of correction parameters through a genetic algorithm. The calculation process for correcting incremental data can be expressed as follows: ;in, Indicates the calculated correction increment data, which is used to determine the correction amplitude of each data item; is a weight function, which is used to assign corresponding weights according to the importance of different data items; represents a function reflecting the actual measurement value, which corresponds to the actual value in the deviation information extracted after preprocessing; A function that reflects the reference data value, i.e., the standard value corresponding to the pre-stored reference data of the physical and chemical properties of Chinese medicinal materials; is an integral variable used to describe the distribution of a data item over time or in a data series. This formula integrates the deviations of each data item to produce an overall correction increment. This data fully reflects the magnitude of the deviation caused by microdegradation of the active ingredient and provides a quantitative basis for subsequent item-by-item corrections.

[0062] Based on the calculated correction increment data, the environmental parameters and the physical and chemical properties data of Chinese medicinal materials are calibrated item by item, and the initial calibration model is updated.

[0063] In this step, the calculated correction increment data is used to make corresponding adjustments to the pre-processed environmental parameters and each data item in the physical and chemical properties data of Chinese medicinal materials. Specifically, for each data item, its original measurement value is added with the corresponding correction increment to obtain the corrected data value. The corrected data value should be closer to the standard value specified in the pre-stored reference data. At the same time, the results of this correction are used to update the initial calibration model, that is, the newly corrected data is used as the new calibration benchmark for subsequent continuous monitoring and correction of data deviations. This update process ensures adaptation to slight changes in the physical and chemical properties of Chinese medicinal materials over time, and maintains consistency and continuity in data processing.

[0064] Record the changes of each data item before and after the correction during the correction process, generate and output the sensor calibration update result data.

[0065] In this step, each data item is continuously recorded: its original value before calibration, the intermediate value after each adjustment during the calibration process, and the final value after calibration. The record content includes the acquisition time of the data item, the start time of the calibration, the numerical changes at each stage of the calibration process, and the final value at the end of the calibration. By establishing a detailed record file, sensor calibration update result data is generated, which can be used for subsequent verification of the calibration effect and further dynamic adjustment and control. All numerical data during the recording process are stored in a format consistent with the previous steps to ensure data traceability and integrity, while providing sufficient historical basis for the long-term calibration of environmental parameters and the physical and chemical properties of traditional Chinese medicine data.

[0066] Based on the environmental adjustment results and sensor calibration update results, the environmental parameters are jointly and dynamically adjusted to maintain the predetermined matching relationship between the environmental parameters and the physical and chemical properties of the Chinese medicinal materials, including: Data information is extracted from the environmental adjustment results and the sensor calibration update results, and integrated to generate joint adjustment input data.

[0067] Based on previously acquired environmental adjustment results, which include the actual temperature and relative humidity measurements after adaptive adjustment, this process is combined with sensor calibration updates, which detail changes in various data items (such as temperature and relative humidity) before and after calibration. To ensure data consistency and accuracy, these two types of data are compared and integrated according to a predefined data format, a unified collection time, and a strict item sequence. This generates a set of joint adjustment input data. This joint input data includes both the latest actual environmental parameter values ​​and the data correction information after sensor calibration updates, providing a unified and accurate data foundation for subsequent dynamic adjustments.

[0068] All data are arranged in a pre-agreed format, and their collection time stamps and the order of data items remain consistent in each processing step, thus avoiding subsequent adjustment errors caused by data mismatch.

[0069] The numerical deviation between the current environmental parameters and the predetermined matching target is calculated based on the joint adjustment input data to obtain a quantitative deviation value.

[0070] Based on the aforementioned combined adjustment input data, the actual collected temperature and relative humidity data are compared with pre-stored environmental parameter reference targets. These pre-stored environmental parameter reference targets are standardized values ​​derived from extensive experimental statistics and based on the physical and chemical properties of Chinese medicinal materials. For example, these target temperature and relative humidity values ​​are highly repeatable and stable.

[0071] By using a quantitative comparison method, the numerical differences between the actual and target values ​​of temperature and relative humidity in the joint adjustment input data are calculated to derive a quantitative deviation value representing the overall deviation. The calculation process involves taking the difference between the actual and target values ​​for each data item, then combining the deviations of each data item according to pre-set weights to form an overall deviation index, which is the quantitative deviation value. This deviation index truly reflects the numerical difference between the current environmental parameter state and the predetermined target, providing a clear quantitative basis for subsequent adjustments.

[0072] According to the quantitative deviation value, a dynamic adjustment strategy is adopted to adjust the set values ​​of temperature and relative humidity in real time, so that they gradually tend to the predetermined targets.

[0073] Based on the quantitative deviation values ​​obtained, a dynamic adjustment strategy is used to adjust the temperature and relative humidity setpoints in real time, gradually bringing the adjusted environmental parameters closer to the pre-defined target values. The adjustment strategy requires that the temperature and relative humidity control settings be gradually revised over successive time intervals based on the quantitative deviation values ​​calculated each time. Each adjustment is based on the current deviation and combined with the previous adjustment results to provide closed-loop feedback.

[0074] The adjustment process requires data collection and deviation recalculation at each successive acquisition moment, and new adjustment instructions are issued accordingly. This closed-loop dynamic adjustment process ensures that temperature and relative humidity data, after multiple corrections, gradually converge toward pre-stored target values, thereby meeting the predetermined matching relationship required by the physical and chemical properties of traditional Chinese medicines. The adjustment method utilizes the common principle of real-time feedback control, with adjustment instructions continuously updated and the adjustment range controlled within pre-set parameter limits to avoid severe fluctuations and overshoot.

[0075] Continuously monitor the adjusted environmental parameters, and record and archive the adjustment process and final results to form complete joint dynamic adjustment feedback data.

[0076] The actual values ​​of temperature and relative humidity at each time point during the dynamic adjustment process are continuously monitored, and detailed records are made of the start time of adjustment, the real-time value changes in each adjustment stage, and the final stable value at the end of adjustment.

[0077] Recorded data must be saved in a predefined format. The recorded content must be consistent with the format, collection time, and data item order of the joint adjustment input data to ensure accuracy and traceability. The recorded data constitutes complete joint dynamic adjustment feedback data. This feedback data not only reflects the execution effect of each adjustment instruction but also provides a sufficient basis for subsequent evaluation of adjustment strategies, optimization of adjustment parameters, and long-term calibration.

[0078] Through detailed process records, it is possible to verify whether the temperature and relative humidity are gradually approaching the predetermined targets during the continuous adjustment process, and to analyze the deviation trend of each data item during the adjustment process to ensure that the entire joint dynamic adjustment process meets the set matching requirements.

[0079] Example 2: Example 2 of the present invention introduces an intelligent control system for the storage environment of Chinese medicinal materials.

[0080] Figure 2 A structural schematic diagram of an intelligent control system for a Chinese medicinal material storage environment is given in the present invention. The intelligent control system for a Chinese medicinal material storage environment includes a storage data acquisition module, an initial calibration and comparison module, a neural wavelet analysis module, a temperature and humidity coupling adjustment module, a genetic calibration update module, and a joint dynamic adjustment module.

[0081] Warehouse data collection module: collects environmental parameters and physical and chemical properties data of Chinese medicinal materials in the storage environment, and adds a timestamp.

[0082] Initial calibration and comparison module: Use the initial calibration model to compare the environmental parameters and the physical and chemical properties of Chinese medicinal materials with the stored reference data, and proceed to the next step when the comparison result deviates greatly.

[0083] Neural wavelet analysis module: Utilizes a combination of neural network and wavelet transform algorithms to analyze environmental parameters and physical and chemical properties of Chinese medicinal materials, and distinguish deviations caused by water redistribution and micro-degradation of active ingredients.

[0084] Temperature and humidity coupling adjustment module: In response to the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded.

[0085] Genetic calibration update module: To address the deviation caused by micro-degradation of active ingredients, an incremental calibration method optimized by genetic algorithms is used to correct environmental parameters and physical and chemical properties of Chinese medicinal materials, update the initial calibration model and generate sensor calibration update results.

[0086] Joint dynamic adjustment module: Based on the environmental adjustment results and sensor calibration update results, the environmental parameters are jointly and dynamically adjusted to maintain the predetermined matching relationship between the environmental parameters and the physical and chemical properties data of Chinese medicinal materials.

[0087] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0088] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0089] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0090] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0091] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0092] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0093] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0094] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

[0095] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for intelligently controlling the storage environment of Chinese medicinal materials, characterized in that: The steps include: Collect environmental parameters and physical and chemical properties of Chinese medicinal materials in the storage environment and attach timestamps; The initial calibration model is used to compare the environmental parameters and the physical and chemical properties of Chinese medicinal materials with the stored reference data. If the comparison results have a large deviation, the next step is entered. A neural network and wavelet transform algorithm were used to analyze environmental parameters and physical and chemical properties of Chinese medicinal materials, and to distinguish deviations caused by water redistribution and microdegradation of active ingredients. In response to the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded; To address deviations caused by micro-degradation of active ingredients, an incremental calibration method optimized by a genetic algorithm is used to correct environmental parameters and the physical and chemical properties of traditional Chinese medicines, update the initial calibration model, and generate sensor calibration update results. The environmental parameters are jointly and dynamically adjusted based on the environmental adjustment results and the sensor calibration update results to maintain a predetermined matching relationship between the environmental parameters and the physical and chemical properties data of traditional Chinese medicine.

2. The intelligent control method for the storage environment of Chinese medicinal materials according to claim 1, characterized in that: Collect environmental parameters and physical and chemical properties of Chinese medicinal materials in the storage environment and add time stamps, including: Collect environmental parameters of the storage environment within the storage environment, including temperature data, relative humidity data, air pressure data, and carbon dioxide concentration data; Collecting data on the physical and chemical properties of Chinese medicinal materials in the Chinese medicinal materials storage area. The data on the physical and chemical properties of Chinese medicinal materials include water content data, active ingredient concentration data, and surface color data of the Chinese medicinal materials; In the process of collecting environmental parameters and physical and chemical properties data of Chinese medicinal materials, a timestamp that clearly identifies the moment of data collection is added to the environmental parameters and physical and chemical properties data of Chinese medicinal materials by synchronously recording the collection time.

3. The intelligent control method for the storage environment of Chinese medicinal materials according to claim 1, characterized in that: The initial calibration model is used to compare the environmental parameters and the physical and chemical properties of Chinese medicinal materials with the stored reference data. If the comparison results deviate significantly, the next step is taken, including: Acquire reference data, the reference data including environmental parameter reference data corresponding to environmental parameters in the storage environment and Chinese medicinal material physical and chemical property reference data corresponding to Chinese medicinal material physical and chemical property data; The initial calibration model is used to compare the environmental parameters with the corresponding environmental parameter reference data, and the physical and chemical properties data of Chinese herbal medicines with the corresponding physical and chemical properties reference data of Chinese herbal medicines. The comparison process adopts the calculation method of data numerical difference; A preset deviation threshold is set. When the numerical difference between the environmental parameters or the physical and chemical properties data of Chinese medicinal materials and their corresponding reference data exceeds the preset deviation threshold, it is determined that there is a large deviation in the comparison result.

4. The intelligent control method for the storage environment of Chinese medicinal materials according to claim 1, characterized in that: A neural network combined with a wavelet transform algorithm is used to analyze environmental parameters and the physical and chemical properties of Chinese medicinal materials, and to distinguish deviations caused by water redistribution and micro-degradation of active ingredients, including: Environmental parameters and physical and chemical properties of Chinese medicinal materials are used as input data. Wavelet transform is used to perform multi-scale decomposition on the input data, and local features and spectral characteristics of each data item are extracted through time-frequency analysis. The local features and spectral characteristics obtained after wavelet transform are passed as input to a pre-established feedforward neural network, which is used to perform nonlinear mapping and data fitting on the input data to obtain output results reflecting the environmental status and changes in the physical and chemical properties of Chinese medicinal materials. Wherein, the feedforward neural network includes an input layer, at least one hidden layer and an output layer; The output results are analyzed using pre-set data comparison rules. By comparing the predetermined judgment parameters involved in the output results with the pre-recorded characteristic parameters generated by water redistribution and the characteristic parameters generated by micro-degradation of active ingredients, deviations in environmental parameters and physical and chemical properties data of Chinese medicinal materials caused by water redistribution and micro-degradation of active ingredients are distinguished.

5. The intelligent control method for the storage environment of Chinese medicinal materials according to claim 1, characterized in that: To address the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded, including: Extract temperature data and relative humidity data from environmental parameters, ensuring consistency in data format, collection time, and data item order during collection; The extracted temperature data and relative humidity data are jointly analyzed using a multi-parameter coupling control algorithm to determine the coupling relationship between the temperature data and the relative humidity data. This coupling relationship quantitatively reflects the dynamic characteristics of the mutual influence of temperature and relative humidity in the storage environment. Adaptively adjust the temperature data and relative humidity data based on the coupling relationship and the pre-set adjustment target. The adaptive adjustment process includes adjusting the temperature set value and the relative humidity set value in real time so that the adjusted temperature data and relative humidity data tend to the target values ​​specified by the pre-stored environmental parameter reference data. During the implementation of the adaptive adjustment process, the adjustment process of the temperature setting value and the relative humidity setting value is continuously recorded. The recorded content includes the start time of the adjustment, the value change during the adjustment process, and the final value at the end of the adjustment, thereby forming the environmental adjustment result.

6. The intelligent control method for the storage environment of Chinese medicinal materials according to claim 5, characterized in that: The extracted temperature data and relative humidity data are jointly analyzed using a multi-parameter coupling control algorithm to determine the coupling relationship between the temperature data and the relative humidity data, specifically: The multi-parameter coupling control algorithm adopts a joint data analysis method, taking temperature data and relative humidity data as the overall input, and performs real-time data statistics and dynamic trend analysis. The quantitative description of the coupling relationship is expressed as: ;in, Represents the coupling relationship function between temperature data and relative humidity data, Indicates temperature data at time The function expression below is Represents the function corresponding to the relative humidity data, represents a position variable in time or a data series, represents the translation parameter of temperature data, Represents the scaling parameter for relative humidity data.

7. The intelligent control method for the storage environment of Chinese medicinal materials according to claim 1, characterized in that: To address deviations caused by micro-degradation of active ingredients, an incremental calibration method optimized by a genetic algorithm is used to correct environmental parameters and the physical and chemical properties of traditional Chinese medicines. This method updates the initial calibration model and generates updated sensor calibration results, including: Extract deviation information reflecting micro-degradation of active ingredients from environmental parameters and physical and chemical properties of Chinese medicinal materials; Adopting the incremental calibration method optimized by genetic algorithm, the extracted deviation information is dynamically corrected and the correction increment data is calculated; According to the calculated correction increment data, the environmental parameters and the physical and chemical properties of Chinese medicinal materials are corrected item by item, and the initial calibration model is updated; Record the changes of each data item before and after the calibration process, generate and output the sensor calibration update result data.

8. The intelligent control method for the storage environment of Chinese medicinal materials according to claim 1, characterized in that: Based on the environmental adjustment results and sensor calibration update results, the environmental parameters are jointly and dynamically adjusted to maintain the predetermined matching relationship between the environmental parameters and the physical and chemical properties of the Chinese medicinal materials, including: Extract data information from environmental adjustment results and sensor calibration update results, and integrate them to generate joint adjustment input data; Calculate the numerical deviation between the current environmental parameters and the predetermined matching target based on the joint adjustment input data to obtain a quantitative deviation value; According to the quantitative deviation value, a dynamic adjustment strategy is used to adjust the set values ​​of temperature and relative humidity in real time, so that they gradually tend to the predetermined targets; Continuously monitor the adjusted environmental parameters, and record and archive the adjustment process and final results to form complete joint dynamic adjustment feedback data.

9. An intelligent control system for a Chinese medicinal material storage environment, used to implement the intelligent control method for a Chinese medicinal material storage environment according to any one of claims 1 to 8, characterized in that: It includes storage data acquisition module, initial calibration and comparison module, neural wavelet analysis module, temperature and humidity coupling adjustment module, genetic calibration update module and joint dynamic adjustment module; Warehouse data collection module: collects environmental parameters and physical and chemical properties of Chinese medicinal materials in the storage environment and adds time stamps; Initial calibration and comparison module: uses the initial calibration model to compare environmental parameters and Chinese medicinal material physical and chemical properties data with the stored reference data, and proceeds to the next step if the comparison result has a large deviation; Neural Wavelet Analysis Module: This module uses a combination of neural networks and wavelet transform algorithms to analyze environmental parameters and the physical and chemical properties of Chinese medicinal materials, and distinguish deviations caused by water redistribution and micro-degradation of active ingredients. Temperature and humidity coupling adjustment module: To address the deviation caused by moisture redistribution, a multi-parameter coupling control algorithm is used to adaptively adjust the temperature and humidity in the environmental parameters, and the environmental adjustment results are recorded; Genetic calibration update module: To address deviations caused by micro-degradation of active ingredients, an incremental calibration method optimized by genetic algorithms is used to correct environmental parameters and physical and chemical properties of Chinese medicinal materials, update the initial calibration model, and generate sensor calibration update results; Joint dynamic adjustment module: Based on the environmental adjustment results and sensor calibration update results, the environmental parameters are jointly and dynamically adjusted to maintain the predetermined matching relationship between the environmental parameters and the physical and chemical properties data of Chinese medicinal materials.

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