A method, system, and equipment for controlling the storage environment to preserve the quality of prickly pear.

Abstract

This invention discloses a storage environment control method, system, and equipment for preserving the quality of prickly pear, specifically relating to the field of preservation environment control technology. It addresses the problems of existing technologies, such as the inability to identify microporous damage to the prickly pear epidermis due to homogenization control and insufficient compensation precision leading to water loss and shrinkage. The method locates candidate damage areas based on dynamic fluctuations in contact pressure; simultaneously collects the hot spot diffusion rate and the dominant frequency of gas concentration oscillation; determines the water loss activity level through temporal correlation analysis; generates progressively increasing compensation control parameters; matches the coverage range of atomized water vapor with the area of ​​candidate areas; and adjusts the ventilation opening to create a negative pressure gradient driving reverse water vapor infiltration. This achieves precise perception and dynamic compensation of locally damaged areas of the prickly pear, balancing fruit preservation quality and energy consumption control in large-scale storage.

Description

Technical Field

[0001] This invention relates to the field of preservation environment control technology, and more specifically, to a method, system, and equipment for controlling the storage environment for the quality preservation of prickly pear. Background Technology

[0002] In the field of postharvest storage of fruits and vegetables, existing methods typically delay fruit moisture loss by regulating the temperature and humidity parameters of the storage environment and combining physical barriers. These technologies rely on environmental monitoring equipment and humidification and ventilation devices in enclosed spaces to maintain humidity uniformity, and reduce gas exchange between the fruit and the environment through sealed packaging or film covering. The core logic is to balance the interaction between fruit physiological activities and external conditions through homogenized environmental control strategies, assuming that the integrity of the fruit epidermal structure has a dominant influence on the rate of water loss.

[0003] However, the rigid, thorny structure of the prickly pear's skin is susceptible to mechanical damage during harvesting and storage stacking, leading to the exposure of local micropores and the formation of non-uniform water loss channels. Existing homogenization control methods cannot identify and compensate for the abnormal water loss paths caused by such microstructural damage, resulting in local water loss rates that deviate significantly from preset environmental parameters, causing fruit shrinkage and reduced marketability. This is especially pronounced in large-scale storage scenarios due to increased physical contact between fruits. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a storage environment control method, system and equipment for the preservation of prickly pear quality to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for controlling the storage environment to preserve the quality of prickly pear includes the following steps:

[0007] S1. Periodically collect the contact pressure distribution of the prickly pear stacking area in the storage space, and identify candidate areas based on the dynamic fluctuation characteristics of the contact pressure distribution;

[0008] S2. Capture the diffusion rate of hot spots caused by epidermal damage in the candidate area, and simultaneously monitor the periodic fluctuation characteristics of gas concentration in the candidate area to extract the dominant frequency of gas concentration oscillation.

[0009] S3. Analyze the temporal correlation between hot spot diffusion rate and gas concentration oscillation frequency. When the temporal changes of the two show synchronous acceleration characteristics, determine the water loss activity level of the candidate area.

[0010] S4. Generate compensation and control intensity parameters based on the water loss activity level. The compensation and control intensity increases stepwise as the water loss activity level increases.

[0011] S5. Adjust the atomization parameters corresponding to the candidate area according to the compensation control intensity parameters so that the water vapor coverage range matches the area of ​​the candidate area.

[0012] S6. Synchronously adjust the opening ratio of ventilation ducts in adjacent areas of the candidate area to force atomized water vapor to permeate into the candidate area in the opposite direction of gas diffusion.

[0013] In a preferred embodiment, the contact pressure distribution of the prickly pear stacking area is periodically collected within the storage space, and candidate areas are identified based on the dynamic fluctuation characteristics of the contact pressure distribution, including:

[0014] Data on the contact pressure distribution in the prickly pear stacking area within the storage space were collected, and the time-domain fluctuation frequency and peak pressure duration of the contact pressure distribution were analyzed.

[0015] The corresponding region will be marked as a candidate region if and only if the frequency of time fluctuation exceeds a preset frequency threshold and the duration of pressure peak exceeds a preset duration threshold.

[0016] The time-domain fluctuation frequency is calculated by extracting the main frequency component from the pressure time-series data output by the pressure sensor array after Fourier transform. The duration of the pressure peak is obtained by statistically analyzing the continuous time window when the pressure signal exceeds the dynamic pressure baseline threshold.

[0017] In a preferred embodiment, the diffusion rate of hot spots induced by epidermal damage in the candidate region is captured, while the periodic fluctuation characteristics of gas concentration in the candidate region are monitored to extract the dominant frequency of gas concentration oscillation, including:

[0018] An infrared thermal imager and a gas concentration sensor are deployed in the candidate area in a spatiotemporally synchronized manner. The infrared thermal imager dynamically adjusts the frame rate based on the infrared radiation characteristics of the damaged area of ​​the prickly pear epidermis, and acquires infrared thermal imaging video sequences of the candidate area. Cross-frame centroid displacement tracking is performed on the hot spot contour in the infrared thermal imaging video sequence, and the hot spot diffusion rate is calculated based on the mapping relationship between the centroid displacement distance and the damage propagation rate of the prickly pear epidermis.

[0019] The gas concentration sensor acquires time-series data of gas concentration in the candidate area at a sampling frequency that is strictly synchronized with the frame rate of the infrared thermal imager. The gas concentration time-series data is subjected to windowed Fourier transform based on the prickly pear respiratory metabolic cycle to extract the frequency components in the spectrum that simultaneously satisfy the energy proportion threshold and phase continuity as the gas concentration oscillation frequency.

[0020] In a preferred embodiment, the temporal correlation between the hot spot diffusion rate and the dominant frequency of gas concentration oscillation is analyzed. When the temporal changes of both exhibit synchronous acceleration characteristics, the water loss activity level of the candidate region is determined, including:

[0021] The time series data of hot spot diffusion rate and gas concentration oscillation frequency are dynamically aligned by time window. The length of the dynamic time window is adjusted in real time according to the gas concentration oscillation frequency. The Pearson correlation coefficient is used to calculate the synchronization index between the growth rate of hot spot diffusion rate and the growth rate of gas concentration oscillation frequency within the same time window.

[0022] At the same time, a comprehensive judgment is made by combining the analysis of the irregularity of the hot spot contour in the candidate area and the monitoring of the local humidity change rate in the candidate area.

[0023] When the synchronicity index exceeds the preset synchronicity threshold, the hot spot contour irregularity is lower than the preset irregularity threshold, and the local humidity change rate is lower than the preset humidity decrease threshold, the water loss activity level of the candidate area is determined to be high.

[0024] When the synchronicity index exceeds the preset synchronicity threshold, but does not simultaneously meet the hot spot contour irregularity threshold and the humidity change rate threshold, the water loss activity level is determined to be medium.

[0025] When the synchronization index is lower than the preset synchronization threshold, the water loss activity level is determined to be low.

[0026] In a preferred embodiment, when the temporal changes in hot spot diffusion rate and gas concentration oscillation frequency do not show synchronous acceleration characteristics, the water loss activity level is determined to be the default level.

[0027] In a preferred embodiment, a compensation regulation intensity parameter is generated based on the water loss activity level, and the compensation regulation intensity increases in a stepwise manner with increasing water loss activity level, including:

[0028] When the water loss activity level is high, the compensation control intensity parameters include the first preset spray volume gradient and the corresponding upper limit of the ventilation opening ratio.

[0029] When the water loss activity level is medium, the compensation control intensity parameters include the second preset spray volume gradient and the corresponding ventilation opening ratio medium limit.

[0030] When the water loss activity level is low, the compensation control intensity parameters include the third preset spray volume gradient and the corresponding lower limit of the ventilation opening ratio.

[0031] When the water loss activity level is the default level, the compensation control intensity parameters include the fixed baseline spray volume and the baseline ratio of ventilation opening.

[0032] In a preferred embodiment, the atomization parameters corresponding to the candidate region are adjusted according to the compensation control intensity parameter to match the water vapor coverage area with the candidate region area, including:

[0033] Based on the spray volume gradient in the compensation and control intensity parameters, the spray volume of the directional atomizing nozzle corresponding to the candidate area is adjusted. The spray volume is calculated based on the product of the candidate area area and the preset unit area benchmark spray volume. The unit area benchmark spray volume is calibrated by the mapping experiment between the water loss per unit time in the damaged area of ​​the prickly pear epidermis and the compensation efficiency.

[0034] The atomized particle size is adjusted synchronously, dynamically according to the inverse proportional relationship between the spray volume and the humidity of the candidate area.

[0035] The spray angle of the atomizing nozzle is matched according to the shape of the candidate area. The spray angle is calibrated by the relationship between the aspect ratio of the minimum bounding rectangle of the candidate area and the geometric distribution of the nozzle array.

[0036] In a preferred embodiment, the opening ratio of ventilation ducts in adjacent areas of the candidate area is simultaneously adjusted to force atomized water vapor to permeate into the candidate area in the opposite direction of gas diffusion, including:

[0037] By increasing the opening of the ventilation ducts on the outside of the candidate area and decreasing the opening of the ventilation ducts on the inside, a negative pressure gradient is formed around the candidate area from the outside to the inside, forcing the atomized water vapor to permeate into the candidate area in the opposite direction of gas diffusion.

[0038] On the other hand, the present invention provides a storage environment control system for preserving the quality of prickly pear, comprising:

[0039] Pressure recognition module: Periodically collects the contact pressure distribution of the prickly pear stacking area in the storage space, and identifies candidate areas based on the dynamic fluctuation characteristics of the contact pressure distribution;

[0040] Hot spot gas frequency module: captures the hot spot diffusion rate caused by epidermal damage in the candidate area, and monitors the periodic fluctuation characteristics of gas concentration in the candidate area to extract the main frequency of gas concentration oscillation;

[0041] The time-series classification module analyzes the temporal correlation between hot spot diffusion rate and gas concentration oscillation frequency. When the temporal changes of the two show synchronous acceleration characteristics, the water loss activity level of the candidate region is determined.

[0042] Stepped intensity modulation module: Generates compensation and control intensity parameters based on the water loss activity level. The compensation and control intensity increases stepwise as the water loss activity level increases.

[0043] Fog control matching module: Adjusts the atomization parameters corresponding to the candidate area according to the compensation and control intensity parameters to match the water vapor coverage range with the area of ​​the candidate area;

[0044] Ventilation and Reverse Osmosis Module: Synchronously adjusts the opening ratio of ventilation ducts in adjacent areas of the candidate zone to force atomized water vapor to permeate into the candidate zone in the reverse direction of gas diffusion.

[0045] On the other hand, the present invention provides a storage environment control device for preserving the quality of prickly pear, comprising: a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, a storage environment control method for preserving the quality of prickly pear is implemented.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. By capturing the dynamic fluctuations caused by epidermal damage based on contact pressure distribution characteristics, and combining the temporal correlation analysis of hot spot diffusion rate and gas concentration oscillation frequency, the micropore exposure area and its water loss activity level can be accurately identified, breaking through the blind spot of traditional methods in perceiving local abnormal water loss paths; by dynamically adapting the damage evolution trend with stepwise increasing compensation and control parameters, the spatial matching of atomized spray volume and candidate area area is achieved, and the water vapor infiltration path is reversed by using the ventilation negative pressure gradient, forming a synergistic regulation of local moisture compensation and storage environment stability, effectively inhibiting non-uniform water loss in the epidermal damage area of ​​prickly pear, and reducing the risk of fruit shrinkage and quality deterioration;

[0048] 2. By adjusting the ventilation opening of adjacent candidate areas in reverse, the pressure transmission effect between surrounding fruits is weakened while compensating for the target area, thus avoiding secondary damage; the dynamic calibration of the coverage area of ​​atomized water vapor and the boundary of the candidate area further reduces the environmental disturbance caused by ineffective humidification; it not only improves the self-repair efficiency of the micropores on the surface of the prickly pear, but also reduces the overall energy consumption through precise local control, providing a solution for high-density stacked storage that balances preservation quality and cost control. Attached Figure Description

[0049] Figure 1 This is a flowchart of a storage environment control method for preserving the quality of prickly pear according to the present invention.

[0050] Figure 2 This is a schematic diagram of a storage environment control system for preserving the quality of prickly pears according to the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0052] Example 1: Figure 1 This invention presents a method for controlling the storage environment to preserve the quality of prickly pear, comprising the following steps:

[0053] S1. Periodically collect the contact pressure distribution of the prickly pear stacking area in the storage space, and identify candidate areas based on the dynamic fluctuation characteristics of the contact pressure distribution;

[0054] S2. Capture the diffusion rate of hot spots caused by epidermal damage in the candidate area, and simultaneously monitor the periodic fluctuation characteristics of gas concentration in the candidate area to extract the dominant frequency of gas concentration oscillation.

[0055] S3. Analyze the temporal correlation between hot spot diffusion rate and gas concentration oscillation frequency. When the temporal changes of the two show synchronous acceleration characteristics, determine the water loss activity level of the candidate area.

[0056] S4. Generate compensation and control intensity parameters based on the water loss activity level. The compensation and control intensity increases stepwise as the water loss activity level increases.

[0057] S5. Adjust the atomization parameters corresponding to the candidate area according to the compensation control intensity parameters so that the water vapor coverage range matches the area of ​​the candidate area.

[0058] S6. Synchronously adjust the opening ratio of ventilation ducts in adjacent areas of the candidate area to force atomized water vapor to permeate into the candidate area in the opposite direction of gas diffusion.

[0059] S1. Periodically collect the contact pressure distribution of the prickly pear stacking area within the storage space, and identify candidate areas based on the dynamic fluctuation characteristics of the contact pressure distribution, including:

[0060] A pressure sensor array is deployed in the storage space. The pressure sensor array is evenly distributed in a matrix on the bearing plane below the prickly pear stack area. Each sensor node of the pressure sensor array periodically collects real-time pressure data at various locations in the prickly pear stack area at a fixed sampling frequency. The real-time pressure data is transmitted to the data storage medium via wired or wireless communication.

[0061] The real-time pressure data transmitted by the pressure sensor array is processed as follows: the pressure data of each sensor node is time-series aligned to form contact pressure distribution data of the prickly pear stacking area in the storage space. The contact pressure distribution data includes the pressure time-series change curve of each location point within a continuous time window.

[0062] Time-domain fluctuation frequency analysis is performed on the contact pressure distribution data. The specific method of time-domain fluctuation frequency analysis is as follows: perform fast Fourier transform calculation on the pressure time-series change curve of each sensor node, extract the dominant frequency component with the largest amplitude in the pressure time-series change curve, and take the frequency value of the dominant frequency component as the time-domain fluctuation frequency of the corresponding location point.

[0063] Simultaneously, pressure peak duration analysis is performed. The specific method for pressure peak duration analysis is as follows: First, based on historical data of the pressure time series change curve, the dynamic pressure baseline threshold is calculated using the sliding window mean method. The window length of the sliding window mean method is a preset time span, and the dynamic pressure baseline threshold is the arithmetic mean of the pressure time series change curve within the window length. Then, pressure signal segments in the pressure time series change curve that exceed the dynamic pressure baseline threshold are detected, and the duration of each pressure signal segment is counted. The longest duration is taken as the pressure peak duration at the corresponding location point.

[0064] The region where a certain location point is located is marked as a candidate region if and only if the time-domain fluctuation frequency of a certain location point exceeds a preset frequency threshold and the duration of the pressure peak exceeds a preset duration threshold. The preset frequency threshold is obtained by experimentally calibrating the range of pressure fluctuation frequency when the rigid thorns of the prickly pear epidermis are damaged. The preset duration threshold is obtained by experimentally calibrating the minimum continuous pressure time for thorn damage caused by stacking and squeezing of prickly pears.

[0065] In the matrix deployment of the pressure sensor array, the spacing between adjacent sensor nodes is determined based on the size of a single prickly pear fruit, and the spacing is no greater than half the average diameter of a single prickly pear fruit, so as to ensure that the spatial resolution of pressure data acquisition meets the requirements for locating the damaged area.

[0066] In the Fast Fourier Transform calculation, the radix-2 time-domain decimation method is used to perform Discrete Fourier Transform on the pressure time-series change curve. After calculating the spectrum, the dominant frequency component with the largest amplitude and frequency within the preset biomechanical damage frequency band is selected.

[0067] The window length of the sliding window mean method is set to an integer multiple of the prickly pear storage stacking operation cycle, specifically three times the single handling operation cycle of the prickly pear stacking robotic arm, to ensure that the dynamic pressure baseline threshold can reflect the background of periodic pressure fluctuations caused by stacking operations.

[0068] The experimental calibration method for the preset frequency threshold includes: in a mechanical experiment simulating damage to the prickly pear epidermis spikes, measuring the pressure signal spectrum at the instant the spikes break, statistically analyzing the frequency distribution range of the dominant frequency component in the spectrum, and using the lower limit of the frequency distribution range as the preset frequency threshold; the experimental calibration method for the preset duration threshold includes: in a simulated test of prickly pear stacking under pressure, gradually increasing the stacking pressure and recording the minimum duration of pressure when spike damage occurs, and using the average value of the minimum duration of pressure as the preset duration threshold.

[0069] During the candidate region marking process, regions that meet the dual thresholds of temporal fluctuation frequency and pressure peak duration are subjected to morphological dilation processing. The size of the structural element in the morphological dilation processing is matched with the size of a single prickly pear fruit to eliminate the candidate region positioning error caused by the gap between sensor nodes.

[0070] S2. Capture the diffusion rate of hot spots induced by epidermal damage in the candidate area, and simultaneously monitor the periodic fluctuation characteristics of gas concentration in the candidate area to extract the dominant frequency of gas concentration oscillation, including:

[0071] The infrared thermal imager and the gas concentration sensor are synchronized at the hardware level through a synchronization signal generator. The infrared thermal imager is installed directly above the candidate area, and the gas concentration sensor is installed at the side air inlet of the candidate area. The optical axis of the infrared thermal imager is vertically aligned with the center point of the epidermal damage area of ​​the candidate area, and the air inlet direction of the gas concentration sensor is consistent with the dominant gas flow direction in the storage space.

[0072] The infrared thermal imager dynamically adjusts the frame rate based on the infrared radiation intensity of the epidermal damage area in the candidate region. For example, when the rate of change of infrared radiation intensity exceeds the preset rate of change threshold, the frame rate is increased from 30 frames per second to 60 frames per second, and when the rate of change of infrared radiation intensity is lower than the threshold, it is restored to 30 frames per second. The preset rate of change threshold is calibrated through the epidermal damage expansion experiment of prickly pear.

[0073] After acquiring infrared thermal imaging video sequences of the candidate areas, cross-frame centroid displacement tracking was performed on the hot spot contours in the video sequences. The specific method for cross-frame centroid displacement tracking is as follows: hot spot contours of each frame image are extracted by grayscale thresholding, the geometric centroid coordinates of the hot spot contours are calculated, the displacement vectors of the centroid coordinates between adjacent frames are tracked based on the Lucas-Kanade optical flow method, and the hot spot diffusion rate is calculated based on the ratio of the magnitude of the displacement vector to the frame interval time. The mapping relationship between the centroid displacement distance and the damage propagation rate of the prickly pear epidermis is realized through experimentally calibrated quadratic polynomial fitting curves.

[0074] For example, the gas concentration sensor collects time-series data of gas concentration in the candidate area at a sampling frequency of 30 or 60 times per second, which is strictly synchronized with the infrared thermal imager. The gas concentration time-series data includes synchronous measurements of carbon dioxide and ethylene concentrations. The carbon dioxide concentration is detected by an electrochemical sensor, and the ethylene concentration is detected by a photoionization sensor.

[0075] An adaptive windowed Fourier transform based on the respiratory metabolic cycle of prickly pear was performed on the gas concentration time series data. The specific method of adaptive windowing is as follows: the respiratory metabolic cycle of prickly pear is calculated by the peak interval of the carbon dioxide concentration time series data, the window length of the Hanning window function is set to one-quarter of the respiratory metabolic cycle, the windowed data is subjected to fast Fourier transform to generate a spectrum, and the frequency components with energy proportions exceeding the preset energy threshold and phase continuity satisfying the preset phase tolerance threshold are extracted from the spectrum as the gas concentration oscillation frequency.

[0076] The working band of the infrared thermal imager is matched with the infrared transmittance mutation band after damage to the waxy layer of the prickly pear epidermis. The infrared transmittance mutation band is determined by measuring the transmittance curve of the damaged area using a Fourier transform infrared spectrometer. The measurement method includes: scanning the infrared transmittance of the damaged area and the undamaged area, and extracting the band with the transmittance difference exceeding the preset difference threshold as the characteristic band.

[0077] The dynamic concentration ratio of the mixed gas of carbon dioxide and ethylene is achieved by parallel detection of an electrochemical sensor and a photoionization sensor. The dynamic concentration ratio is calculated by multiplying the ratio of ethylene concentration to carbon dioxide concentration by the prickly pear maturity coefficient, which is calibrated by the linear relationship between storage environment temperature and storage days.

[0078] The synchronization accuracy of the synchronization signal generator is at the microsecond level, ensuring that the acquisition time deviation between the infrared thermal imager and the gas concentration sensor does not exceed one-thousandth of the frame interval time.

[0079] The threshold used in grayscale thresholding is adaptively determined based on the bimodal distribution of the grayscale histogram of the hot spot region in the first frame image. When the bimodal distribution does not exist, the threshold is calculated using the maximum inter-class variance method.

[0080] The search window size of the Lucas-Kanade optical flow method is set to twice the length of the diagonal of the rectangle circumscribed by the hot spot profile, and the iteration termination condition is that the optical flow residual is less than a preset residual threshold.

[0081] In the calculation of the respiratory metabolic cycle of prickly pear, the peak interval of carbon dioxide concentration is achieved by finding the time difference between adjacent maximum points in the time series data. The criteria for determining the maximum point are that the data value is greater than the value of the two sampling points before and after and exceeds the preset peak threshold.

[0082] The method for determining the phase continuity condition is as follows: perform first-order difference calculation on the phase sequence of the main frequency component of the gas concentration oscillation. If the absolute values ​​of three consecutive difference values ​​are all less than the preset phase tolerance threshold, then the phase continuity condition is satisfied.

[0083] The transmittance difference threshold of the Fourier transform infrared spectrometer was determined by statistically analyzing the range of infrared transmittance fluctuations of undamaged prickly pear epidermis, and the transmittance difference threshold was set to 3 times the standard deviation of the fluctuation range.

[0084] The calibration methods for electrochemical sensors and photoionization sensors include: fitting the linear relationship between the sensor output signal and the gas concentration using the least squares method under a standard mixed gas environment, and dynamically updating the sensitivity coefficient.

[0085] S3. Analyze the temporal correlation between hot spot diffusion rate and gas concentration oscillation frequency. When the temporal changes of both show synchronous acceleration characteristics, determine the water loss activity level of the candidate region, including:

[0086] The time-series data of hot spot diffusion rate and gas concentration oscillation frequency obtained in step S2 are dynamically aligned using a time window. The length of the dynamic time window is adjusted in real time according to the gas concentration oscillation frequency. Specifically, the time window length is set to an integer multiple (e.g., 2-5 times) of the corresponding period of the gas concentration oscillation frequency to cover several complete oscillation periods, thereby ensuring the stability of the time-series correlation analysis. The gas concentration oscillation frequency characterizes the forced oscillation frequency of the local microenvironment gas concentration in the candidate area caused by the intense water transpiration and increased respiration at the site of epidermal damage in the prickly pear. This frequency is much higher than the frequency of macroscopic respiration rate changes in the fruit as a whole. The gas concentration oscillation frequency is extracted through windowed Fourier transform in step S2, and its physical meaning is the most significant fluctuation frequency of microenvironment gas concentration under damage stimulation.

[0087] The specific method for dynamic time window alignment is as follows: Align the hot spot diffusion rate time series data with the gas concentration oscillation frequency time series data according to the acquisition timestamp, and extract data segments within the same time window. The sliding step size of the time window is set to a fixed value (e.g., 30 seconds) or a fixed proportion to the period corresponding to the gas concentration oscillation frequency (e.g., half), and the data overlap rate between adjacent windows is 75%.

[0088] The Pearson correlation coefficient is used to calculate the synchronicity index between the growth rate of hot spot diffusion rate and the growth rate of gas concentration oscillation frequency within the same time window. The growth rate is calculated by taking the absolute value after performing a first-order difference on the time series data. The first-order difference is calculated by the difference between the values ​​of adjacent sampling points. If the hot spot diffusion rate or gas concentration oscillation frequency data within a certain time window are all zero or there are consecutive missing values, the synchronicity index calculation for that window is skipped, and the judgment result of the previous valid window is directly inherited.

[0089] Simultaneously, the infrared thermal imaging video sequence acquired in step S2 is subjected to hot spot morphology analysis to extract the irregularity of the hot spot contour. The irregularity is obtained by calculating the ratio of the hot spot contour perimeter to the circumference of a circle with an equal area; and the local humidity change rate of the candidate area is monitored.

[0090] The preset synchronization threshold was calibrated through a coupling experiment of the damage propagation rate of the prickly pear epidermis and the gas diffusion rate. The coupling experiment method included: in a simulated storage environment, a pressure control device was used to apply three levels of mechanical damage to the prickly pear epidermis: low speed, medium speed, and high speed. For example, the low speed level corresponds to a pressure sensor measurement value of 0.5-1.0N, the medium speed level corresponds to 1.0-2.0N, and the high speed level corresponds to 2.0-3.5N. The hot spot diffusion rate and the oscillation frequency of the gas concentration were measured simultaneously. The Pearson correlation coefficient distribution of the growth rates of the two under each damage level was statistically analyzed, and the median of the distribution was used as the preset synchronization threshold for the corresponding level.

[0091] A candidate region is classified as having a high water loss activity level if and only if all of the following conditions are met:

[0092] Condition 1: The synchronization index exceeds the preset synchronization threshold and the synchronization index remains monotonically increasing within three consecutive time windows;

[0093] Condition 2: The irregularity of the hot spot contour is lower than the preset irregularity threshold;

[0094] Condition 3: The rate of change of local humidity in the candidate area is less than zero or lower than the preset humidity decrease threshold. (The criterion for three consecutive time windows is that the difference in the synchronicity index between adjacent windows is greater than or equal to 0.01 to eliminate the influence of data rounding errors.)

[0095] When the synchronicity index exceeds the preset synchronicity threshold but does not meet all the above conditions (i.e., conditions 2 and 3 are not met at the same time), the water loss activity level is determined to be medium.

[0096] When the synchronicity index is lower than the preset synchronicity threshold, the water loss activity level is determined to be low.

[0097] When the temporal changes in the hot spot diffusion rate and the dominant frequency of gas concentration oscillation do not show synchronous acceleration characteristics, the water loss activity level is determined to be the default level. The compensation control intensity corresponding to the default level is a fixed baseline value, which is determined by statistically analyzing the average humidity value in the storage environment when no damage to the prickly pear skin occurs, and calculating the historical average of the atomized spray volume required to maintain this humidity.

[0098] In the detection of peak carbon dioxide concentration, the preset peak threshold calibration method is as follows: collect time series data of carbon dioxide concentration of undamaged prickly pear in the storage environment, calculate the standard deviation of its fluctuation range, and take three times the standard deviation as the preset peak threshold.

[0099] The mechanical damage application rate of the pressure control device is achieved by adjusting the pressure application speed through a servo motor. For example, the low speed corresponds to a pressure head displacement speed of 0.1 mm per second, the medium speed corresponds to 0.3 mm per second, and the high speed corresponds to 0.5 mm per second.

[0100] The method for handling missing data values ​​is as follows: For example, if the number of missing data points in a certain window exceeds 10% of the total number of points, the window is marked as invalid; otherwise, linear interpolation is used to fill in the missing values ​​before they are included in the calculation.

[0101] The tolerance values ​​of 0.01 and 0.05 were determined through a tolerance experiment for judging epidermal damage in prickly pear. The experimental method included adjusting the tolerance value in samples with known damage levels until the judgment result was consistent with human observations by more than 95%.

[0102] The historical average of the fixed benchmark value is calculated over the most recent 30 days during which the storage environment has been operating stably. For example, the daily average is calculated by taking the spray volume data at 24 full hours each day, and then averaging the 30 daily averages.

[0103] It is worth noting that in the storage environment, the contact pressure distribution in the prickly pear stacking area was collected in real time by a high-density sensor array. The sensor node spacing was customized according to the fruit size to ensure sensitive capture of high-frequency pressure fluctuations caused by minor damage to the epidermal thorns. Dynamic fluctuation feature analysis combined with time-domain frequency and peak duration dual thresholds screened out pressure abnormal areas as candidate areas, avoiding the problem of missed detection of instantaneous mechanical damage by the traditional static threshold method. After the candidate areas were located, the infrared thermal imager tracked the centroid displacement of the hot spot contour at an adaptive frame rate, and the gas sensor simultaneously captured the main frequency of carbon dioxide concentration oscillation. The data of the two were time-series aligned and the correlation of growth rate were calculated to reveal the dynamic association between epidermal micropore exposure and abnormal respiratory metabolism. When the hot spot diffusion rate and the growth rate of the gas main frequency showed a continuous increasing positive synchronicity, and the hot spot morphology was regular and the local environment showed a drying trend, the system comprehensively determined that the water loss activity level of the area was high, providing a precise quantitative basis for subsequent compensation. This multi-source heterogeneous data fusion and cross-domain time-series correlation mechanism solved the problem of the perception lag of the dynamic evolution of local damage by traditional homogenized monitoring.

[0104] S4. Generate compensation control intensity parameters based on the water loss activity level. The compensation control intensity increases in a stepwise manner as the water loss activity level increases, including:

[0105] When the water loss activity level is high, the compensation control intensity parameter includes the first preset spray volume gradient and the corresponding upper limit of the ventilation opening ratio. The first preset spray volume gradient is calibrated by the mapping experiment between the damage expansion rate of the prickly pear skin and the water compensation efficiency. For example, in a simulated storage environment, high-speed mechanical damage (e.g., the pressure head displacement speed is 0.5 mm per second) is applied to the prickly pear skin, and the water evaporation is measured at different damage rates. The functional relationship between the damage rate and the water compensation amount (e.g., a quadratic function) is fitted, and a specific proportion of the maximum compensation amount (e.g., 80%) is used as the first preset spray volume gradient.

[0106] When the water loss activity level is medium, the compensation control intensity parameter includes the second preset spray volume gradient and the corresponding ventilation opening ratio medium limit. The second preset spray volume gradient is calibrated by medium speed mechanical damage test. For example, another ratio of the maximum compensation amount (e.g., 60%) is used as the second preset spray volume gradient.

[0107] When the water loss activity level is low, the compensation control intensity parameter includes the third preset spray volume gradient and the corresponding lower limit of the ventilation opening ratio. The third preset spray volume gradient is calibrated by a low-speed mechanical damage test. For example, another ratio of the maximum compensation value (e.g., 40%) is used as the third preset spray volume gradient.

[0108] When the water loss activity level is the default level, the compensation control intensity parameters include a fixed baseline spray volume and a ventilation opening baseline ratio. The fixed baseline spray volume is determined by statistically analyzing the average humidity of the undamaged prickly pear storage environment to maintain the spray volume, for example, the statistical period is a specific number of days (e.g., 30 days). The ventilation opening baseline ratio is set to a specific ratio of the standard ventilation parameters for storage (e.g., 50%).

[0109] The ventilation opening ratio adjustment coefficient is calibrated through a synergistic experiment of gas reverse osmosis efficiency and spray volume. For example, the penetration depth of atomized water vapor in the candidate area is measured under different spray volume gradients, and the linear relationship between spray volume and ventilation opening is fitted (for example, the upper limit of the ventilation opening ratio is 0.8 times the spray volume gradient).

[0110] In the high-speed mechanical damage test, the damage rate is applied at an example speed (e.g., 0.5 mm per second) by a pressure control device, and the amount of water evaporation is monitored in real time by a high-precision electronic scale. The maximum compensation amount is a specific multiple (e.g., 1.2 times) of the peak evaporation amount. In the medium-speed mechanical damage test, the damage rate is another example speed (e.g., 0.3 mm per second), and the proportion of the maximum water compensation amount (e.g., 60%) is calculated by the proportion of the integral area of ​​the evaporation curve. In the low-speed mechanical damage test, the damage rate is another example speed (e.g., 0.1 mm per second), and the proportion of the maximum compensation amount (e.g., 40%) is determined based on the steady-state value of evaporation.

[0111] The statistical period for the fixed baseline spray volume is the example number of days (e.g., 30 days). Spray volume data is collected a specific number of times (e.g., 24 times) each day, and the arithmetic mean is taken after removing outliers.

[0112] The method for measuring gas reverse osmosis efficiency is as follows: tracer gas is released at the center of the candidate area, and the mixing and permeation depth of the atomized water vapor and tracer gas is monitored by a gas concentration sensor. For example, when the permeation depth reaches the boundary of the candidate area, the corresponding ventilation opening ratio is recorded.

[0113] In the linear fitting of the collaborative experiment, if the spray volume gradient is an example value X and the ventilation opening ratio is another example value Y, then the fitting relationship is, for example, Y=0.8X (high level), and the goodness of fit is required to be greater than a specific value (e.g., 0.9).

[0114] S5. Adjust the atomization parameters corresponding to the candidate region according to the compensation control intensity parameters to match the water vapor coverage area with the candidate region area, including:

[0115] Based on the spray volume gradient in the compensation control intensity parameter, the spray volume of the directional atomizing nozzle corresponding to the candidate area is adjusted. The spray volume is calculated based on the product of the candidate area area and the preset unit area benchmark spray volume. The candidate area area is calculated through the candidate area marking range of the pressure sensor array in step S1. The preset unit area benchmark spray volume is calibrated through the mapping experiment of water loss per unit time and compensation efficiency in the damaged area of ​​the prickly pear skin. For example, mechanical damage at different rates is applied to the prickly pear skin in a simulated storage environment, the water loss per unit time is measured, the quadratic function relationship between water loss and compensation efficiency is fitted, and a specific proportion (e.g., 80%) of the maximum compensation efficiency is used as the unit area benchmark spray volume.

[0116] The atomized particle size is adjusted synchronously. The atomized particle size is dynamically adjusted according to the inverse relationship between the spray volume and the humidity of the candidate area. For example, when the spray volume is increased to the first gradient and the humidity of the candidate area is lower than the preset humidity threshold, the atomized particle size is reduced to a specific value (e.g., 50 micrometers). The humidity is monitored in real time by a humidity sensor arranged at the edge of the candidate area. The preset humidity threshold is determined by a calibration experiment of the water penetration rate in the damaged area of ​​the prickly pear skin.

[0117] The spray angle of the atomizing nozzle is matched according to the shape of the candidate area. The shape of the candidate area is determined by the minimum bounding rectangle of the candidate area marking range in step S1. The spray angle is calibrated by the aspect ratio of the rectangle and the geometric distribution relationship of the nozzle array. For example, when the aspect ratio is greater than a specific value (e.g., 2:1), the tilt angle of the nozzle array is adjusted to a specific angle (e.g., 30 degrees) to ensure that the boundary error between the water vapor coverage area and the candidate area shape is less than a preset tolerance threshold (e.g., 5%).

[0118] The compensation efficiency coefficient in the spray volume calculation formula is calibrated through a synergistic experiment of damage propagation rate and water penetration rate. For example, under high-speed damage propagation, the ratio of water penetration rate to damage rate is used as the compensation efficiency coefficient, and the compensation efficiency coefficient takes a value within a specific range (e.g., 0.5-1.2).

[0119] The atomized particle size adjustment rule is determined by fitting the curve of the residence time of atomized water vapor in the candidate area. For example, an exponential function is used to fit the residence time of water vapor with different particle sizes, and the optimal particle size value is deduced from the target residence time (e.g., 60 seconds).

[0120] The specific method for calculating the candidate area is as follows: project the coordinates of the candidate area pressure sensor nodes marked in step S1 onto a two-dimensional plane, calculate the area of ​​the polygon formed by the connection of the nodes, and extract the coordinates of the polygon vertices using the convex hull algorithm.

[0121] The humidity sensors are arranged at four points evenly spaced along the edge of the candidate area. The humidity monitoring value is the arithmetic mean of the four points. The preset humidity threshold is calibrated by an experiment on the water penetration rate of the damaged area. For example, when the damage rate is a specific value (e.g., 0.5 mm per second), the ratio of the penetration rate to the humidity decrease rate is used as the basis for setting the threshold.

[0122] In the calculation of the aspect ratio of the minimum bounding rectangle, the long side of the rectangle is aligned with the dominant airflow direction of the storage space, and the geometric distribution of the nozzle array is arranged at equal intervals according to the direction of the long side of the rectangle, with the interval being a specific proportion of the long side of the candidate area (e.g., 1 / 10).

[0123] The residence time fitting curve of atomized water vapor in the candidate area is described by an exponential function. The residence time decreases exponentially with the increase of the atomized particle size. For example, for every unit increase in particle size (e.g., 10 micrometers), the residence time decreases to a specific proportion of the original value (e.g., 1 / 2 of the original value). The decay coefficient and proportional coefficient of the exponential function are calibrated by the dissipation experiment of water vapor with different particle sizes. The dissipation experiment method is as follows: atomized water vapor of different particle sizes is released in the candidate area, the time from the water vapor spraying out to complete dissipation is recorded, the relationship curve between particle size and residence time is plotted, and the parameters of the exponential function are fitted by the least squares method to ensure that the error between the fitted curve and the actual data is less than the preset error threshold (e.g., 5%).

[0124] When the convex hull algorithm extracts polygon vertices, it removes outlier pressure sensor nodes. The criteria for determining outlier nodes is that the difference between the pressure value of a node and the pressure values ​​of its neighboring nodes exceeds a certain multiple (e.g., 3 times the standard deviation).

[0125] S6. Synchronously adjust the opening ratio of ventilation ducts in adjacent areas of the candidate area to force atomized water vapor to permeate into the candidate area in the opposite direction of gas diffusion, including:

[0126] When simultaneously adjusting the opening ratio of ventilation ducts in adjacent areas of the candidate area, the opening ratio of the ventilation ducts on the outside of the candidate area is first adjusted to a specific value (e.g., 80%), while the opening ratio of the ventilation ducts on the inside of the candidate area is adjusted to another specific value (e.g., 20%). The difference between the opening ratios on the outside and inside creates a negative pressure gradient from the outside to the inside around the candidate area. The magnitude of the negative pressure gradient is monitored in real time by the pressure difference between the edge of the candidate area and the outside area. The pressure difference is measured by pressure sensors arranged on the outside and inside of the candidate area.

[0127] The formation of a negative pressure gradient drives the gas flow direction in the storage space from the outside to the inside of the candidate area, forcing the atomized water vapor to penetrate into the candidate area in the opposite direction of gas diffusion. The penetration depth of the atomized water vapor is verified by the humidity difference between the center and the edge of the candidate area. For example, when the humidity at the center reaches a certain multiple (e.g., 1.5 times) of the humidity at the edge, the penetration is determined to be complete.

[0128] The opening ratio adjustment step of the ventilation duct outside the candidate area is dynamically set according to the target value of the negative pressure gradient. For example, when the target pressure difference is a specific value (e.g., 10 Pa), the opening ratio is adjusted by a specific percentage (e.g., 5%) each time until the real-time pressure difference reaches the target value.

[0129] The opening ratio adjustment rule of the ventilation duct inside the candidate area is synchronized with that of the outside but in the opposite direction. For example, when the opening of the outside is increased by 5%, the opening of the inside is reduced by 5% to keep the total ventilation volume constant and avoid pressure imbalance in the storage environment.

[0130] The negative pressure gradient is maintained through closed-loop control. For example, when the pressure difference decreases due to environmental disturbances, the outer opening ratio is automatically increased and the inner opening ratio is decreased. The adjustment range is calculated based on the percentage of pressure difference deviating from the target value.

[0131] The pressure sensor is positioned at a specific distance (e.g., 0.5 meters) beyond the outer boundary of the candidate area and at the same distance inward from the inner boundary. The pressure difference measurement is the difference between the average value of the outer sensor and the average value of the inner sensor.

[0132] In the humidity difference verification of the penetration depth of atomized water vapor, humidity sensors are placed at the center point and the midpoints of the four edges of the candidate area. When the humidity at the center reaches a certain multiple (e.g., 1.5 times) of the humidity at the edges, it is determined that the water vapor coverage area of ​​the candidate area exceeds a certain proportion (e.g., 90%).

[0133] The dynamic setting rules for adjusting the opening ratio step size are calibrated through gradient pressure experiments. For example, the opening ratio is gradually adjusted in a simulated storage environment and the pressure difference change curve is recorded. The step size corresponding to the interval with the largest slope of the curve is used as the default adjustment step size.

[0134] The total ventilation volume is kept constant by the conservation of the product of the cross-sectional area and the opening ratio of the ventilation duct. For example, when the cross-sectional area of ​​the outer duct is a certain multiple of the inner duct (e.g., 2 times), the adjustment range of the outer opening ratio is a certain ratio of the inner one (e.g., 1 / 2).

[0135] The adjustment range calculation in closed-loop control adopts the proportional-integral-derivative (PID) algorithm. The proportional coefficient, integral time, and derivative time are calibrated through pressure difference step response experiments. For example, when the target pressure difference is 10 Pa, the adjustment parameters are adjusted until the system stabilizes in the shortest time after applying a step disturbance.

[0136] Based on the step-wise compensation parameters generated by the water loss activity level, precise moisture compensation is achieved through dynamic matching of candidate area geometry features and atomization parameters. The spray angle of the atomizing nozzle is dynamically adjusted according to the aspect ratio of the minimum bounding rectangle of the candidate area to ensure that the water vapor coverage area is highly consistent with the shape of the damaged area, avoiding edge leakage or over-humidification in the traditional circular spray mode. The opening ratio of the ventilation ducts in adjacent areas is adjusted simultaneously, and the outer opening is greatly increased to form a negative pressure gradient, forcing the atomized water vapor to penetrate into the core of the candidate area against the natural diffusion direction of the gas. This reverse driving mechanism is controlled by a differential pressure sensor in a closed loop to maintain the directional accumulation of water vapor in the damaged area. The coordinated adjustment of ventilation opening and spray volume not only prevents local humidity oversaturation from causing mold growth, but also inhibits the diffusion of compensated water vapor to non-target areas, which would cause environmental fluctuations.

[0137] Example 2: Figure 2 A schematic diagram of a storage environment control system for preserving the quality of prickly pear is provided. The system includes:

[0138] Pressure recognition module: Periodically collects the contact pressure distribution of the prickly pear stacking area in the storage space, and identifies candidate areas based on the dynamic fluctuation characteristics of the contact pressure distribution;

[0139] Hot spot gas frequency module: captures the hot spot diffusion rate caused by epidermal damage in the candidate area, and monitors the periodic fluctuation characteristics of gas concentration in the candidate area to extract the main frequency of gas concentration oscillation;

[0140] The time-series classification module analyzes the temporal correlation between hot spot diffusion rate and gas concentration oscillation frequency. When the temporal changes of the two show synchronous acceleration characteristics, the water loss activity level of the candidate region is determined.

[0141] Stepped intensity modulation module: Generates compensation and control intensity parameters based on the water loss activity level. The compensation and control intensity increases stepwise as the water loss activity level increases.

[0142] Fog control matching module: Adjusts the atomization parameters corresponding to the candidate area according to the compensation and control intensity parameters to match the water vapor coverage range with the area of ​​the candidate area;

[0143] Ventilation and Reverse Osmosis Module: Synchronously adjusts the opening ratio of ventilation ducts in adjacent areas of the candidate zone to force atomized water vapor to permeate into the candidate zone in the reverse direction of gas diffusion.

[0144] Example 3: A storage environment control device for preserving the quality of prickly pear includes: a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, a storage environment control method for preserving the quality of prickly pear is implemented.

[0145] The above formulas are all dimensionless calculations. The formulas are derived from software simulations using a large amount of collected data, and are the closest to the real situation. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0146] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0147] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. 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 (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0148] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0149] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0150] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0151] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0152] If the aforementioned functions are implemented as software functional 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 this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0153] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0154] In conclusion, 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 within the protection scope of the present invention.

Claims

1. A warehouse environment regulation method for preserving the quality of Malus hallingsensis, characterized by, The method comprises the following steps: S1, periodically collecting the contact pressure distribution of the Malus baccata Borkh. stacking area in the storage space, and identifying the candidate area based on the dynamic fluctuation characteristics of the contact pressure distribution; S2, capturing the heat spot diffusion rate caused by the skin damage of the candidate area, and monitoring the periodic fluctuation characteristics of the gas concentration in the candidate area to extract the gas concentration oscillation main frequency, comprising: deploying an infrared thermal imager and a gas concentration sensor in the candidate area in a space-time synchronous manner, the infrared thermal imager dynamically adjusts the frame rate based on the infrared radiation characteristics of the Malus baccata Borkh. skin damage area, collects infrared thermal imaging video sequences of the candidate area, tracks the cross-frame centroid displacement of the heat spot profile in the infrared thermal imaging video sequences, and calculates the heat spot diffusion rate based on the mapping relationship between the centroid displacement distance and the Malus baccata Borkh. skin damage expansion rate; the gas concentration sensor collects time series data of the gas concentration in the candidate area at a sampling frequency strictly synchronized with the frame rate of the infrared thermal imager, performs windowed Fourier transform on the gas concentration time series data based on the respiratory metabolism cycle of Malus baccata Borkh., and extracts the frequency component in the frequency spectrum that simultaneously satisfies the energy proportion threshold and the phase continuity as the gas concentration oscillation main frequency; S3, analyzing the time sequence correlation of the heat spot diffusion rate and the gas concentration oscillation main frequency, when the time sequence changes of the two are synchronous acceleration characteristics, determining the dehydration activity level of the candidate area, comprising: performing dynamic time window alignment processing on the time sequence data of the heat spot diffusion rate and the gas concentration oscillation main frequency, the length of the dynamic time window is adjusted in real time according to the gas concentration oscillation main frequency, and the synchronism index of the heat spot diffusion rate and the gas concentration oscillation main frequency is calculated in the same time window by using the Pearson correlation coefficient; At the same time, combined with the analysis of the irregularity of the heat spot profile of the candidate area and the monitoring of the local humidity change rate of the candidate area, comprehensive judgment is made; when the synchronism index exceeds the preset synchronization threshold, the heat spot profile irregularity is lower than the preset irregularity threshold, and the local humidity change rate is lower than the preset humidity drop threshold, it is determined that the dehydration activity level of the candidate area is high; when the synchronism index exceeds the preset synchronization threshold, but does not simultaneously satisfy the heat spot profile irregularity threshold and the humidity change rate threshold, it is determined that the dehydration activity level is medium; when the synchronism index is lower than the preset synchronization threshold, it is determined that the dehydration activity level is low; S4, generating a compensation control intensity parameter according to the dehydration activity level, and the compensation control intensity increases in steps with the increase of the dehydration activity level; S5, adjusting the atomization parameter corresponding to the candidate area according to the compensation control intensity parameter, so that the water vapor coverage range matches the area of the candidate area; S6, synchronously adjusting the opening ratio of the ventilation pipeline of the adjacent area of the candidate area, so as to force the atomized water vapor to penetrate into the candidate area in the opposite direction of gas diffusion.

2. The warehouse environment regulation method for the Malus hallings care according to claim 1, characterized in that, Periodically collect the contact pressure distribution of the Malus baccata Borkh. stacking area in the storage space, and identify the candidate area based on the dynamic fluctuation characteristics of the contact pressure distribution, comprising: collecting the contact pressure distribution data of the Malus baccata Borkh. stacking area in the storage space, analyzing the time domain fluctuation frequency and pressure peak duration of the contact pressure distribution; The corresponding region is marked as a candidate area when and only when the time domain fluctuation frequency exceeds a preset frequency threshold and the pressure peak duration exceeds a preset time length threshold; The time domain fluctuation frequency is calculated by extracting the main frequency component through Fourier transform of the pressure time series data output by the pressure sensor array, and the pressure peak duration is obtained by counting the continuous time window in which the pressure signal exceeds the dynamic pressure baseline threshold.

3. The warehouse environment regulation method for Malus hallings care according to claim 1, characterized in that, When the time sequence change of the hot spot diffusion rate and the main frequency of the gas concentration oscillation does not show the characteristics of synchronous acceleration, it is determined that the water loss activity level is the default level.

4. The warehouse environment regulation method for Malus hallings care according to claim 1, characterized in that, The compensation control intensity parameter is generated according to the water loss activity level, and the compensation control intensity increases in steps with the increase of the water loss activity level, including: When the water loss activity level is high, the compensation control intensity parameter includes a first preset spraying amount gradient and a corresponding upper limit of the ventilation opening degree ratio; When the water loss activity level is medium, the compensation control intensity parameter includes a second preset spraying amount gradient and a corresponding medium limit of the ventilation opening degree ratio; When the water loss activity level is low, the compensation control intensity parameter includes a third preset spraying amount gradient and a corresponding lower limit of the ventilation opening degree ratio; When the water loss activity level is the default level, the compensation control intensity parameter includes a fixed reference spraying amount and a reference ratio of the ventilation opening degree.

5. The warehouse environment regulation method for the Malus hallings care according to claim 1, characterized in that, According to the compensation control intensity parameter, the atomization parameters of the candidate area are controlled to match the water vapor coverage range with the area of the candidate area, including: Based on the spraying amount gradient in the compensation control intensity parameter, the spraying amount of the directional atomization nozzle corresponding to the candidate area is adjusted, and the spraying amount is calculated according to the product of the area of the candidate area and the preset unit area reference spraying amount, and the unit area reference spraying amount is calibrated through the mapping experiment of the unit time water loss amount of the nopal skin damage area and the compensation efficiency; The atomized particle size is adjusted synchronously, and the atomized particle size is dynamically adjusted according to the inverse proportional relationship between the spraying amount and the space humidity of the candidate area; The spraying angle of the atomization nozzle is matched according to the shape of the candidate area, and the spraying angle is calibrated through the geometric distribution relationship between the aspect ratio of the minimum circumscribed rectangle of the candidate area and the nozzle array.

6. The warehouse environment regulation method for Malus hallings care according to claim 1, characterized in that, The opening ratio of the ventilation duct of the adjacent area of the candidate area is adjusted synchronously to force the atomized water vapor to penetrate into the candidate area in the opposite direction of the gas diffusion, including: By increasing the opening of the ventilation duct outside the candidate area and reducing the opening of the ventilation duct inside, a negative pressure gradient is formed from the outside to the inside around the candidate area, forcing the atomized water vapor to penetrate into the candidate area in the opposite direction of the gas diffusion.

7. A storage environment regulation system for fresh-keeping of Malus dasyclados quality, for implementing the storage environment regulation method for fresh-keeping of Malus dasyclados quality according to any one of claims 1-6, characterized in that, It includes: A pressure recognition module: periodically collects the contact pressure distribution of the nopal stacking area in the storage space, and recognizes the candidate area based on the dynamic fluctuation characteristics of the contact pressure distribution; A hot spot gas frequency module: captures the hot spot diffusion rate caused by the skin damage of the candidate area, and monitors the periodic fluctuation characteristics of the gas concentration in the candidate area to extract the main frequency of the gas concentration oscillation; A time sequence judgment module: analyzes the time sequence correlation of the hot spot diffusion rate and the main frequency of the gas concentration oscillation, and determines the water loss activity level of the candidate area when the time sequence change of the two shows the characteristics of synchronous acceleration; A stepwise intensity adjustment module: generates a compensation control intensity parameter according to the water loss activity level, and the compensation control intensity increases in steps with the increase of the water loss activity level. The fog control matching module: according to the compensation control intensity parameter, the atomization parameter corresponding to the candidate area is controlled, so that the water vapor coverage range is matched with the area of the candidate area; The ventilation pipe opening degree proportion of the adjacent area of the candidate area is synchronously adjusted to force the atomized water vapor to penetrate into the candidate area along the gas diffusion direction.

8. A storage environment regulation device for preserving the quality of Malus hallingsensis, characterized by, The application relates to a kind of warehousing environment control methods for Malus robusta quality preservation, comprising: A processor, a memory, and a program or instructions stored on the memory and executable on the processor, which, when executed by the processor, implement a warehousing environment control method for Malus robusta quality preservation as claimed in any one of claims 1-6.

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