A cold chain transportation preservation method and system based on spatial electric field

Abstract

This invention relates to the field of cold chain preservation technology, and discloses a method and system for cold chain transportation preservation based on a spatial electric field. The method collects environmental parameters such as temperature, humidity, oxygen concentration, and microbial concentration inside the vehicle compartment in real time, and screens key influencing factors that significantly affect the preservation of goods. Based on the distribution characteristics of the key influencing factors and combined with the three-dimensional structural dimensions of the vehicle compartment, the compartment is divided into multiple independent electric field action regions, each corresponding to preset initial spatial electric field parameters. The initial parameters are optimized in real time; based on the changing trends of key influencing factors in each region, the electric field strength and frequency are dynamically adjusted to generate an adaptive control strategy, and the control device forms a uniform spatial electric field in each region. The spatial electric field continuously acts on the goods, inhibiting microbial reproduction and oxidation reactions, and real-time monitoring of preservation status data such as the rate of change in item hardness and respiration intensity. Further optimization is performed based on the comparison results with preset thresholds, achieving dynamic maintenance of the preservation effect of goods during cold chain transportation.

Description

Technical Field

[0001] This invention relates to the field of cold chain preservation technology, specifically to a cold chain transportation preservation method and system based on a spatial electric field. Background Technology

[0002] During cold chain transportation, the preservation effect of goods is directly affected by environmental factors. Traditional cold chain preservation methods mainly rely on temperature control, slowing down the spoilage process by lowering the temperature inside the vehicle. However, relying solely on temperature regulation has significant limitations; when the temperature fluctuates or is unevenly distributed, localized areas of spoilage can be accelerated.

[0003] Humidity is also a crucial factor affecting preservation; excessively high or low humidity can lead to dehydration and mold growth. Current humidity control technologies often employ a holistic approach, which struggles to adapt to the humidity requirements of different areas within the vehicle, leaving some items in unsuitable humidity environments.

[0004] Oxygen concentration has a significant effect on the oxidation reaction of materials and the reproduction of microorganisms. Traditional oxygen regulation methods lack precision and cannot be dynamically adjusted according to the real-time status of materials. This can easily lead to excessively high oxygen concentrations that promote oxidation, or excessively low oxygen concentrations that cause the growth of anaerobic microorganisms.

[0005] Microbial growth is one of the key causes of spoilage. Currently used preservation measures, such as chemical treatment, may have adverse effects on the quality of goods and human health. Physical preservation methods, such as ultraviolet irradiation, have problems such as limited range of action and the potential for blind spots.

[0006] Different items have different requirements for preservation environments. When transporting multiple items in the same carriage, traditional uniform environmental control methods are insufficient to meet the individual needs of each item, resulting in poor preservation of some items. At the same time, existing preservation technologies lack real-time monitoring and dynamic adjustment mechanisms for the preservation status of items, making it impossible to respond promptly to changes in environmental parameters during transportation and maintain stable preservation results. Summary of the Invention

[0007] The purpose of this invention is to provide a cold chain transportation preservation method and system based on a spatial electric field to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides a cold chain transportation preservation method based on a spatial electric field, the method comprising:

[0009] Real-time collection of environmental parameters inside the cold chain transport compartment, including temperature, humidity, oxygen concentration, and microbial concentration, and screening of key influencing factors that significantly affect the preservation effect of goods from these environmental parameters;

[0010] Based on the distribution characteristics of the key influencing factors and combined with the three-dimensional structural dimensions of the cold chain transport vehicle, the cold chain transport vehicle is divided into multiple independent electric field action regions, and each electric field action region corresponds to a preset initial spatial electric field parameter.

[0011] The initial spatial electric field parameters of the multiple electric field action regions are optimized in real time. Based on the changing trends of key influencing factors in each electric field action region, the intensity and frequency of the spatial electric field are dynamically adjusted to generate an adaptive electric field control strategy. Based on the adaptive electric field control strategy, the spatial electric field generating device is controlled to form a uniformly distributed spatial electric field in each of the electric field action regions.

[0012] The space electric field continuously acts on the items within each electric field area, inhibiting the growth rate of microorganisms on the surface of the items and the oxidation reaction rate inside the items; the preservation status data of the items within each electric field area is monitored in real time, including the change rate of the item's hardness and respiration intensity; based on the comparison results of the preservation status data with preset thresholds, the adaptive electric field control strategy is further optimized to achieve dynamic maintenance of the preservation effect of items during cold chain transportation.

[0013] Preferably, the step of dividing the cold chain transport vehicle into multiple independent electric field action regions based on the distribution characteristics of the key influencing factors and the three-dimensional structural dimensions of the cold chain transport vehicle includes: performing a three-dimensional model of the internal space of the cold chain transport vehicle to obtain the structural parameters of the vehicle; dividing the internal space of the vehicle into grids along the height and horizontal directions according to the structural parameters to obtain multiple initial sub-regions; analyzing the distribution density of key influencing factors in each initial sub-region, merging adjacent initial sub-regions with a distribution density difference less than a preset threshold into one electric field action region; determining the center point location and boundary range of each electric field action region, and assigning a unique identifier number to each electric field action region.

[0014] Preferably, the real-time optimization of the initial spatial electric field parameters of the multiple electric field action regions, and the dynamic adjustment of the intensity and frequency of the spatial electric field based on the changing trends of key influencing factors in each electric field action region to generate an adaptive electric field control strategy, includes: setting up an independent parameter adjustment queue for each electric field action region, with each parameter adjustment queue corresponding to the spatial electric field parameters of one electric field action region; real-time acquisition of real-time data of key influencing factors in each electric field action region, and calculation of the deviation between real-time data and historical data; determining the adjustment amplitude of the spatial electric field intensity and the adjustment step size of the frequency based on the magnitude of the deviation; controlling each parameter adjustment queue to correct the initial spatial electric field parameters according to the adjustment amplitude and adjustment step size to obtain optimized spatial electric field parameters; and integrating the optimized spatial electric field parameters of all electric field action regions into a unified adaptive electric field control strategy.

[0015] Preferably, the real-time acquisition of environmental parameters inside the cold chain transport vehicle includes temperature, humidity, oxygen concentration, and microbial concentration. Screening key influencing factors that significantly affect the preservation effect of goods from these environmental parameters includes: preprocessing the environmental parameters to remove outliers and noise data to obtain purified environmental data; using principal component analysis to extract features from the purified environmental data to obtain multiple candidate influencing factors; calculating the correlation coefficient between each candidate influencing factor and the preservation effect of goods, and identifying candidate influencing factors with an absolute correlation coefficient greater than a preset threshold as key influencing factors; and sorting the key influencing factors from highest to lowest influence to form a key influencing factor sequence.

[0016] Preferably, the step of further optimizing the adaptive electric field control strategy based on the comparison results of the preservation status data and the preset threshold includes: extracting the coupling characteristics of the item's hardness change rate and respiration intensity from the preservation status data; when the value of the coupling characteristics exceeds the preset safety threshold, coupling adjustment is performed on the spatial electric field parameters in the adaptive electric field control strategy; the coupling adjustment includes simultaneously increasing the intensity of the spatial electric field and decreasing the frequency, or simultaneously decreasing the intensity and increasing the frequency; verifying the spatial electric field parameters after coupling adjustment to ensure that the adjusted parameters will not cause damage to the item, thereby obtaining the final optimized adaptive electric field control strategy.

[0017] Preferably, the cold chain transport vehicle is equipped with multiple electric field generating units inside. The step of controlling the spatial electric field generating device to form a uniformly distributed spatial electric field within each electric field action area based on the adaptive electric field control strategy includes: constructing a three-dimensional physical model of the cold chain transport vehicle, the three-dimensional physical model including the internal structure of the vehicle and the position information of each electric field generating unit; constructing an electric field generation model for each electric field generating unit, integrating all electric field generation models into the three-dimensional physical model to obtain a target simulation model; assigning corresponding control parameters to each electric field generating unit in the target simulation model based on the adaptive electric field control strategy; simulating the distribution of the spatial electric field within each electric field action area according to the control parameters and the target simulation model, ensuring that the uniformity error of the electric field intensity is within a preset range; and activating the actual spatial electric field generating device based on the simulation results to generate a spatial electric field consistent with the simulation results.

[0018] Preferably, the cold chain transportation preservation method based on spatial electric field further includes: responding to an anomaly detection command for the target electric field's area of ​​action, the anomaly detection command including detection accuracy requirements; extracting anomaly data segments corresponding to the target electric field's area of ​​action from the preservation status data according to the anomaly detection command; performing multi-scale analysis on the anomaly data segments according to the detection accuracy requirements to identify the cause of the anomaly; and automatically adjusting the spatial electric field parameters of the target electric field's area of ​​action according to the cause of the anomaly, or issuing an alarm signal to remind manual intervention.

[0019] Preferably, the present invention also includes a cold chain transportation preservation system based on a spatial electric field, used to implement the cold chain transportation preservation method based on a spatial electric field as described above. The system includes an environmental parameter acquisition module, an electric field region division module, a control strategy generation module, an electric field generation control module, and a preservation status monitoring module. The environmental parameter acquisition module is used to collect environmental parameters inside the cold chain transport vehicle in real time, and to screen out key influencing factors that significantly affect the preservation effect of the goods from these environmental parameters. The electric field region division module is used to divide the cold chain transport vehicle into multiple independent electric field action regions based on the distribution characteristics of the key influencing factors and the three-dimensional structural dimensions of the cold chain transport vehicle. Each electric field action region corresponds to a preset... The initial spatial electric field parameters are defined as follows: the control strategy generation module optimizes the initial spatial electric field parameters of the multiple electric field action regions in real time, dynamically adjusts the intensity and frequency of the spatial electric field according to the changing trends of key influencing factors in each electric field action region, and generates an adaptive electric field control strategy; the electric field generation control module controls the spatial electric field generating device to form a uniformly distributed spatial electric field in each electric field action region based on the adaptive electric field control strategy; the preservation status monitoring module monitors the preservation status data of the items in each electric field action region in real time, and further optimizes the adaptive electric field control strategy based on the comparison results of the preservation status data with a preset threshold, so as to realize the dynamic maintenance of the preservation effect of the items during cold chain transportation.

[0020] Preferably, the electric field region division module divides the cold chain transport vehicle into multiple independent electric field action regions based on the distribution characteristics of the key influencing factors and the three-dimensional structural dimensions of the cold chain transport vehicle. This includes: the electric field region division module performing a three-dimensional model of the internal space of the cold chain transport vehicle to obtain the vehicle's structural parameters; dividing the internal space of the vehicle into grids along the height and horizontal directions according to the structural parameters to obtain multiple initial sub-regions; analyzing the distribution density of key influencing factors within each initial sub-region, merging adjacent initial sub-regions with a distribution density difference less than a preset threshold into one electric field action region; determining the center point location and boundary range of each electric field action region, and assigning a unique identifier to each electric field action region.

[0021] Preferably, the control strategy generation module optimizes the initial spatial electric field parameters of the multiple electric field action regions in real time. Based on the changing trends of key influencing factors in each electric field action region, it dynamically adjusts the intensity and frequency of the spatial electric field to generate an adaptive electric field control strategy. This includes: setting up an independent parameter adjustment queue for each electric field action region, with each queue corresponding to the spatial electric field parameters of one region; collecting real-time data of key influencing factors within each region and calculating the deviation between the real-time data and historical data; determining the adjustment amplitude of the spatial electric field intensity and the adjustment step size of the frequency based on the magnitude of the deviation; controlling each parameter adjustment queue to correct the initial spatial electric field parameters according to the adjustment amplitude and step size to obtain optimized spatial electric field parameters; and integrating the optimized spatial electric field parameters of all electric field action regions into a unified adaptive electric field control strategy.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] By collecting environmental parameters inside the carriage in real time and identifying key influencing factors, the core elements affecting the preservation of goods can be grasped more accurately. Based on the distribution characteristics of key influencing factors and the three-dimensional structure of the carriage, independent electric field action areas are divided, with each area corresponding to preset initial parameters. This makes the electric field action more targeted and adaptable to the environmental differences in different areas of the carriage.

[0024] Real-time optimization of initial spatial electric field parameters, dynamically adjusting intensity and frequency based on the changing trends of key influencing factors, generates an adaptive electric field control strategy that ensures the spatial electric field always matches the environmental conditions of the object. Controlling the spatial electric field generator to form a uniformly distributed spatial electric field in all areas ensures the comprehensiveness of the electric field's effect and avoids uneven application.

[0025] By continuously applying a spatial electric field to the goods, microbial growth and oxidation reactions can be inhibited, addressing the key stages of spoilage and slowing down the decline in quality. Real-time monitoring of the goods' preservation status data, such as the rate of change in hardness and respiration rate, and further optimization of control strategies based on comparisons with preset thresholds, allows preservation measures to adjust according to changes in the goods' condition, adapting to dynamic changes during transportation.

[0026] This method eliminates the need for chemical agents, reducing adverse effects on product quality and the environment, while avoiding the limitations of traditional physical preservation methods. When transporting multiple items, by dividing the area into independent electric field zones, it can meet the personalized preservation needs of different items, ensuring that each item is in a suitable electric field environment.

[0027] By dynamically maintaining the freshness of goods, their shelf life can be extended, losses during transportation can be reduced, and the overall freshness level of cold chain transportation can be improved. The entire process involves real-time monitoring and dynamic adjustment to ensure the electric field remains in a reasonable state, adapting to complex and changing transportation environments. Attached Figure Description

[0028] Figure 1 This is a schematic diagram illustrating the working principle of the cold chain transportation and preservation method based on a spatial electric field as described in this invention.

[0029] Figure 2 A flowchart for dividing the region of influence of the electric field;

[0030] Figure 3 A flowchart for screening key impact factors;

[0031] Figure 4 A flowchart for generating a uniformly distributed electric field in space;

[0032] Figure 5 This is a flowchart of a cold chain transportation and preservation system. Detailed Implementation

[0033] 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Please see Figure 1 This invention provides a cold chain transportation preservation method and system based on a spatial electric field, the method comprising:

[0035] Real-time collection of environmental parameters inside the cold chain transport compartment, including temperature, humidity, oxygen concentration and microbial concentration, and screening of key influencing factors that significantly affect the preservation effect of goods from these environmental parameters;

[0036] Based on the distribution characteristics of the key influencing factors and combined with the three-dimensional structural dimensions of the cold chain transport vehicle, the cold chain transport vehicle is divided into multiple independent electric field action regions, and each electric field action region corresponds to a preset initial spatial electric field parameter.

[0037] The initial spatial electric field parameters of the multiple electric field action regions are optimized in real time. Based on the changing trends of key influencing factors in each electric field action region, the intensity and frequency of the spatial electric field are dynamically adjusted to generate an adaptive electric field control strategy. Based on the adaptive electric field control strategy, the spatial electric field generating device is controlled to form a uniformly distributed spatial electric field in each of the electric field action regions.

[0038] The space electric field continuously acts on the items within each electric field area, inhibiting the growth rate of microorganisms on the surface of the items and the oxidation reaction rate inside the items; the preservation status data of the items within each electric field area is monitored in real time, including the change rate of the item's hardness and respiration intensity; based on the comparison results of the preservation status data with preset thresholds, the adaptive electric field control strategy is further optimized to achieve dynamic maintenance of the preservation effect of items during cold chain transportation.

[0039] Example 1: See Figure 2 Based on the distribution characteristics of key influencing factors and combined with the three-dimensional structural dimensions of the cold chain transport vehicle, when dividing the cold chain transport vehicle into multiple independent electric field action regions, it is necessary to perform three-dimensional modeling of the internal space of the cold chain transport vehicle. Three-dimensional modeling can be performed by using laser scanning equipment to scan the interior of the vehicle from all directions, acquiring point cloud data. The data is then processed using modeling software to generate a three-dimensional model containing all structural details of the vehicle's interior. Structural parameters of the vehicle are extracted from the three-dimensional model. These parameters include the overall length, width, and height of the vehicle, as well as the position coordinates and specific dimensions of internal fixed supports, partitions, hooks, and other devices, including their length, width, height, and relative distances to the vehicle walls.

[0040] Based on the extracted structural parameters, the interior space of the carriage is divided into grids along the vertical and horizontal directions. The vertical division is determined by the actual height of the carriage; for example, if the carriage height is 3 meters, it can be divided into 0.3-meter intervals, starting from the bottom and working upwards. The horizontal division is based on the carriage's length and width, with intervals of 1.2 meters for the length and 0.8 meters for the width, forming multiple regular initial sub-regions. Each initial sub-region has a clearly defined spatial extent, its boundaries defined by the maximum and minimum values ​​of its three-dimensional coordinates.

[0041] The distribution density of key influencing factors within each initial sub-region is analyzed. Calculating the distribution density requires first obtaining the specific values ​​of the key influencing factors within that sub-region, and then combining this with the sub-region's volume to obtain the values ​​per unit volume. The distribution densities of adjacent initial sub-regions are compared, and the difference between them is calculated. When the difference is less than a preset threshold, the two initial sub-regions are merged into a larger region. This process is repeated for all adjacent initial sub-regions, ultimately forming multiple independent electric field influence regions.

[0042] The center point and boundary range of each electric field application area are determined. The center point is obtained by calculating the average coordinates of the area in three dimensions, specifically by calculating the average of the maximum and minimum coordinates in the length, width, and height directions. The boundary range is determined by recording the maximum and minimum coordinate values ​​in the length, width, and height directions; for example, the length direction is from x1 to x2, the width direction is from y1 to y2, and the height direction is from z1 to z2. Each electric field application area is assigned a unique identification number, which can be a combination of the area's approximate location within the carriage and a serial number, such as "front left 1," "rear right 3," etc., to facilitate subsequent identification and management of each area.

[0043] The initial spatial electric field parameters of multiple electric field application regions are optimized in real time. Based on the changing trends of key influencing factors in each region, the intensity and frequency of the spatial electric field are dynamically adjusted to generate an adaptive electric field control strategy. An independent parameter adjustment queue is set up for each electric field application region. The parameter adjustment queue is a data sequence containing the spatial electric field parameters of that region at different time points, with each parameter consisting of an intensity value and a frequency value. The length of the parameter adjustment queue can be set according to actual needs; for example, it could contain a set of parameters recorded every 5 minutes over the past hour. It is continuously updated over time, deleting expired data and adding new data.

[0044] Real-time data on key influencing factors within each electric field's influence area is collected. This data acquisition is accomplished using sensors installed in each area. These sensors detect key influencing factors such as temperature, humidity, oxygen concentration, and microbial concentration at set time intervals, such as every 30 seconds, and transmit the detected data to the data processing unit. The data processing unit then retrieves historical data for each area, which represents the key influencing factor data collected for that area during the same time period in the past. The deviation between the real-time and historical data is calculated; the deviation is the difference between the real-time and historical data.

[0045] Based on the magnitude of the deviation, the adjustment range of the space electric field intensity and the adjustment step size of the frequency are determined. When the deviation is positive and large, it indicates that the current value of the key influencing factor is higher than the historical average for the same period, requiring adjustment of the space electric field parameters. Conversely, if the deviation is negative and large, it indicates that the current value is lower than the historical average for the same period, also requiring adjustment. The adjustment range and step size can be set using preset correspondences. For example, when the deviation is in the range of 0-5, the intensity adjustment range is 0.1 kV / m, and the frequency adjustment step size is 0.5 kHz; when the deviation is in the range of 5-10, the intensity adjustment range is 0.3 kV / m, and the frequency adjustment step size is 1 kHz, and so on.

[0046] The control parameter adjustment queues correct the initial spatial electric field parameters according to the determined adjustment range and step size. The correction process involves calculating new intensity and frequency values ​​based on the current parameters, taking into account the sign of the deviation and the adjustment range and step size, and replacing the latest parameters in the parameter adjustment queue. After completing the parameter correction for all electric field application regions, the optimized spatial electric field parameters for each region are summarized and organized according to their identification numbers to form a unified file containing all region parameters. This file constitutes the adaptive electric field control strategy, used to guide the subsequent operation of the spatial electric field generator.

[0047] Example 2: See Figure 3 When collecting real-time environmental parameters inside a cold chain transport vehicle, multiple sensors need to be deployed at different locations within the vehicle. These sensors include temperature sensors, humidity sensors, oxygen concentration sensors, and microbial concentration sensors. Temperature sensors, which can be thermocouples or resistance temperature detectors (RTDs), are distributed at the front, middle, and rear of the vehicle, as well as at the top, middle, and bottom, ensuring they can capture temperature differences across different areas. Capacitive humidity sensors are used, installed near stacked goods to avoid direct contact with their surfaces and away from ventilation openings to minimize airflow interference. Oxygen concentration sensors, employing electrochemical methods, are fixed at mid-height on the side wall of the vehicle and connected to the interior space via a pipe for real-time monitoring of oxygen levels. Microbial concentration sensors collect airborne microbial samples and use optical detection to obtain concentration data; these sensors are installed in areas with relatively flat airflow within the vehicle. All sensors continuously collect data at set time intervals, which can be adjusted according to actual transport needs. The collected data is transmitted to a data processing terminal via wired or wireless transmission.

[0048] When screening key influencing factors from environmental parameters, the collected environmental parameters are first preprocessed. During preprocessing, outlier identification is achieved by setting reasonable value ranges. For example, the normal temperature range is set to -5℃ to 10℃; when a detected temperature value exceeds this range, it is considered an outlier. The normal humidity range is set to 30% to 90%; humidity values ​​exceeding this range are considered outliers. For identified outliers, a nearest neighbor interpolation method is used for replacement; that is, multiple normal data points adjacent to the outlier are selected, and their average value is calculated as the replacement value. Noise data is processed using a moving average method. A time window of a certain length is selected, and the data within the window is averaged to smooth the data curve and eliminate interference from high-frequency fluctuations. The length of the time window can be selected according to the severity of data fluctuations. After the above processing, purified environmental data is obtained.

[0049] Principal component analysis (PCA) was used to extract features from the purified environmental data. First, the environmental data was organized into a matrix, where each row represents all environmental parameter data at a given time point, and each column represents data for one environmental parameter at all time points. The matrix was then standardized to eliminate the influence of different dimensions among the parameters. The covariance matrix of the standardized matrix was calculated, and the principal components were obtained by solving for the eigenvalues ​​and eigenvectors of the covariance matrix. Each principal component corresponds to an eigenvalue, the magnitude of which reflects the amount of original data information contained within that principal component. Based on the magnitude of the eigenvalues, the first few principal components were selected; these principal components are the candidate influencing factors. Each candidate influencing factor is a linear combination of the original environmental parameters and contains the main information from the original data.

[0050] Calculate the correlation coefficient between each candidate influencing factor and the product preservation effect. The product preservation effect is quantified using pre-defined indicators. The correlation coefficient is calculated using the Pearson correlation coefficient method, which calculates the degree of correlation between each candidate influencing factor and the quantified preservation effect indicator. The correlation coefficient ranges from -1 to 1. A preset threshold is set, for example, 0.6. When the absolute value of the correlation coefficient of a candidate influencing factor is greater than this threshold, it is identified as a key influencing factor. The identified key influencing factors are sorted from largest to smallest influencing influence based on the magnitude of the correlation coefficient. The larger the absolute value of the correlation coefficient, the greater the influence of the factor on the preservation effect. The sorted sequence forms a key influencing factor sequence, which includes the name of each key influencing factor and its corresponding correlation coefficient value.

[0051] Example 3: When further optimizing the adaptive electric field control strategy based on the comparison results between the preservation status data and the preset threshold, it is necessary to extract the coupling characteristics of the item's hardness change rate and respiration intensity from the preservation status data. The hardness change rate is obtained through a specific detection device. This device applies constant pressure to the surface of the item and measures the degree of deformation of the item under pressure. The hardness change rate is calculated by combining the initial hardness value. For example, if the initial hardness is H0 and the hardness after a period of time is H1, the hardness change rate is (H1-H0) / H0×100%. The respiration intensity is detected by collecting the carbon dioxide concentration released by the item. A gas sensor is used to monitor the change of carbon dioxide concentration in the sealed space in real time. The amount of carbon dioxide released per unit mass of item per unit time is calculated by combining the space volume and time, which is used as a quantitative indicator of respiration intensity.

[0052] Extracting the coupling feature requires data fusion of the rate of change in stiffness and breathing intensity. During the fusion process, the values ​​of both are first standardized, mapping the rate of change in stiffness and breathing intensity to the range of 0-1 respectively. The standardized rate of change in stiffness is denoted as A, and the standardized breathing intensity as B. The coupling feature value C is calculated using the following formula:

[0053] in, and These are the weighting coefficients. The value range is 0.4-0.6. The value range is 0.4-0.6, and The specific value of the weighting coefficient is determined based on the type of item; for example, for leafy vegetables... The value can be slightly greater than For fruit-type items, The value can be slightly greater than .

[0054] When the value of the coupling characteristic exceeds a preset safety threshold, the spatial electric field parameters in the adaptive electric field control strategy need to be adjusted. The safety threshold is set according to the preservation requirements of the item; different types of items have different thresholds. For example, the safety threshold can be set to 0.6 for strawberries and 0.7 for apples. There are two ways to adjust the coupling: one is to simultaneously increase the intensity of the spatial electric field and decrease the frequency. The increase in intensity is determined by how much the coupling characteristic value exceeds the threshold; the greater the exceedance, the greater the increase. The decrease in frequency corresponds to the increase in intensity. The other is to simultaneously decrease the intensity and increase the frequency. The magnitude of the decrease in intensity and the increase in frequency are also adjusted according to how much the coupling characteristic value exceeds the threshold.

[0055] When validating the coupled and adjusted spatial electric field parameters, a damage assessment model for the object needs to be constructed. This model is based on physiological response data of the object under different electric field parameters, and includes the correspondence between electric field strength, frequency, and the degree of damage to the object's cellular structure. The adjusted electric field parameters are input into the model to obtain the corresponding damage assessment results. If the assessment results show that the damage level is within an acceptable range, it is considered that the parameter will not cause damage to the object; if the assessment results show that the damage level exceeds the acceptable range, the electric field parameters need to be readjusted and verified again until the parameters that meet the requirements are obtained. After verification, the final optimized adaptive electric field control strategy is determined. This strategy includes the optimal spatial electric field strength and frequency parameters for each electric field application region under the current conditions, and is used to guide the operation of the spatial electric field generator.

[0056] Throughout the process, it is necessary to continuously collect data on the preservation status of the items, constantly calculate the coupling characteristic value and compare it with the safety threshold. When the coupling characteristic value falls below the safety threshold, the electric field parameters can be adjusted in reverse according to the actual situation to keep the spatial electric field effect within a reasonable range.

[0057] Example 4: See Figure 4The cold chain transport vehicle is equipped with multiple electric field generating units inside. These units can use flat or needle-shaped electrodes, distributed on the top, bottom, and side walls of the vehicle. Some units can also be installed on the surface of the internal partitions. A certain distance is maintained between the electrodes to avoid mutual interference. Based on an adaptive electric field control strategy, to control the spatial electric field generating device to form a uniformly distributed spatial electric field within each electric field application area, a three-dimensional physical model of the cold chain transport vehicle is first constructed. During the construction process, a 3D scanning device is used to perform a comprehensive scan of the vehicle's interior, acquiring detailed information including the curved shape of the interior walls, the curvature of the corners, and the dimensions of protruding structures. Simultaneously, the installation position of each electric field generating unit is recorded and marked in the model using coordinate positioning, ensuring that the three-dimensional physical model accurately reflects the internal structure of the vehicle and the actual layout of each electric field generating unit.

[0058] An electric field generation model is constructed for each electric field generating unit. This model must consider factors such as the shape, size, material of the electrodes, and the applied voltage. Simulation calculations are used to determine the spatial distribution of the electric field generated by this unit under different parameters, including the variation of the magnitude and direction of the electric field intensity with spatial location. All electric field generation models are integrated into a three-dimensional physical model to form a target simulation model. This model can be run using simulation software to simulate the overall electric field distribution when multiple electric field generating units operate simultaneously.

[0059] Based on an adaptive electric field control strategy, corresponding control parameters are assigned to each electric field generating unit in the target simulation model. These control parameters include specific values ​​for electric field intensity and frequency. Different parameters are assigned to electric field generating units corresponding to different electric field application regions. The parameters of multiple electric field generating units within the same region are coordinated to ensure the consistency of the electric field distribution within that region. Based on the control parameters and the target simulation model, a simulation program is run in the simulation software to obtain the simulation results of the spatial electric field distribution within each electric field application region, including the electric field intensity values ​​at different locations within each region.

[0060] The uniformity of the electric field intensity in the simulation results is analyzed. The difference between the maximum and minimum electric field intensity within the region is calculated and compared with the average electric field intensity within the region to obtain the uniformity error. When the uniformity error is within the preset range, it indicates that the current parameter settings meet the requirements. If it exceeds the preset range, the control parameters of the corresponding electric field generating unit need to be adjusted, and the simulation needs to be repeated until the uniformity error meets the requirements. Based on the final simulation results, control commands are sent to the actual space electric field generating device to start the device and enable each electric field generating unit to operate according to the parameters determined in the simulation, generating a space electric field consistent with the simulation results.

[0061] The cold chain transportation and preservation method based on spatial electric fields also includes responding to anomaly detection commands in response to the target electric field's area of ​​influence. These anomaly detection commands can be automatically triggered by the system or manually entered by the operator. The commands include detection accuracy requirements; for example, high-precision detection requires a data sampling interval of once every 10 seconds, while low-precision detection can use a sampling interval of once every 60 seconds. Based on the anomaly detection commands, abnormal data segments corresponding to the target electric field's area of ​​influence are extracted from the preservation status data. These abnormal data segments typically exhibit significant fluctuations in values ​​within a short period or a sustained deviation from the normal range. For example, the rate of change in the item's hardness may suddenly increase by 20% within 5 minutes, or the respiration rate may be higher than normal for 10 consecutive minutes.

[0062] Based on the required detection accuracy, multi-scale analysis is performed on abnormal data segments. In high-precision detection mode, the data change trends are analyzed at time scales of 10 seconds, 30 seconds, and 60 seconds to observe the frequency and amplitude of fluctuations. In low-precision detection mode, analysis can be performed at time scales of 5 minutes, 10 minutes, and 30 minutes. Through multi-scale analysis, the causes of anomalies are identified. Possible causes include a decrease in the output power of a certain electric field generating unit, resulting in insufficient electric field strength; a decrease in the sealing performance of the area, allowing outside air to enter and causing changes in environmental parameters; or sensor malfunction leading to abnormal data acquisition.

[0063] Depending on the cause of the anomaly, corresponding measures will be taken. If the cause is a decrease in the output power of the electric field generating unit, the system will automatically adjust the spatial electric field parameters of the target electric field's area of ​​action, increasing the electric field strength or adjusting the frequency. If the cause is a decrease in sealing performance that the system cannot resolve through parameter adjustments, an alarm signal will be issued. The alarm signal can be presented in the form of sound and light to remind operators to intervene manually, check, and repair the sealing problem. If the problem is determined to be a sensor malfunction, an alarm signal will also be issued, prompting the replacement or repair of the sensor.

[0064] Example 5: See Figure 5 A cold chain transportation preservation system based on a spatial electric field is used to realize a cold chain transportation preservation method based on a spatial electric field. It includes an environmental parameter acquisition module, an electric field region division module, a control strategy generation module, an electric field generation control module, and a preservation status monitoring module.

[0065] The environmental parameter acquisition module consists of multiple sensors of different types. Temperature sensors, typically digital, are distributed at different heights and horizontal positions inside the compartment, such as the top of the front, the side of the middle, and the bottom of the rear, to monitor temperature data in real time. Humidity sensors, using capacitive methods, are installed near the storage shelves to avoid direct contact with the items, detecting humidity in the surrounding air. Oxygen concentration sensors are connected to the interior of the compartment via gas sampling tubes, with the inlet positioned in the gaps between stacked items to collect data reflecting the oxygen levels around them. Microbial concentration sensors collect airborne microbial samples and use optical detection principles to obtain microbial concentration information; these sensors are installed in areas with relatively stable airflow within the compartment. These sensors collect data at set time intervals, and the collected data is transmitted to the module's data processing unit via internal communication lines. The data processing unit performs preliminary processing of the received environmental parameters, filtering out key influencing factors that significantly affect the preservation effect of the items. The filtering process is based on the correlation between each parameter and the preservation effect.

[0066] When the electric field region segmentation module is working, it first performs a 3D model of the internal space of the cold chain transport vehicle. The modeling process uses laser scanning to acquire point cloud data of the vehicle's interior, which is then processed to generate a 3D model. Structural parameters of the vehicle are extracted from the model, including its length, width, and height, as well as the position and dimensions of internal beams, columns, partitions, and other structures. Based on these structural parameters, the internal space of the vehicle is divided into grids along the vertical and horizontal directions. The vertical grid is divided at 0.4-meter intervals, while the horizontal grid is divided at 1.5-meter and 0.6-meter intervals for length and width, respectively, forming multiple initial sub-regions. The distribution density of key influencing factors within each initial sub-region is analyzed. The distribution density is calculated using the numerical values ​​of key influencing factors per unit volume. Adjacent initial sub-regions with distribution density differences less than a preset threshold are merged to form multiple independent electric field action regions. The center point of each electric field action region is determined and represented using 3D coordinates. The boundary range of the region is defined, i.e., the coordinate extreme values ​​in each direction. A unique identifier is assigned to each region, which can be in the form of a numerical sequence.

[0067] The control strategy generation module sets up an independent parameter adjustment queue for each electric field region. Each queue records the sequence of changes in the spatial electric field parameters for that region, including intensity and frequency values ​​at different time points. The module collects real-time data of key influencing factors within each electric field region, compares it with historical data for that region, and calculates the deviation value, which is the difference between the real-time and historical data. Based on the magnitude of the deviation, the adjustment amplitude of the spatial electric field intensity and the adjustment step size of the frequency are determined; larger deviations result in larger adjustment amplitudes and step sizes, while smaller deviations result in smaller adjustments. The control module then corrects the initial spatial electric field parameters according to the determined adjustment amplitude and step size, obtaining optimized parameters. Finally, the optimized parameters for all regions are integrated to form a unified adaptive electric field control strategy.

[0068] The electric field generation control module receives the adaptive electric field control strategy output by the control strategy generation module, analyzes the spatial electric field parameters corresponding to each electric field application region, converts these parameters into control signals, and sends them to the spatial electric field generating device. Each electric field generating unit in the spatial electric field generating device operates according to the received control signals, forming a spatial electric field within its corresponding application region. The module monitors the device's operating status in real time to ensure that its output meets the requirements of the control strategy.

[0069] The preservation status monitoring module monitors the preservation status data of goods in real time through detection devices installed in each electric field area, including the rate of change in hardness and respiration intensity. The detection devices acquire data through contact or non-contact methods and transmit the data to the module's processing unit. The processing unit compares the preservation status data with preset thresholds, generates adjustment signals based on the comparison results, and feeds them back to the control strategy generation module to further optimize the adaptive electric field control strategy, thereby dynamically maintaining the preservation effect of goods during cold chain transportation.

[0070] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0071] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A cold chain transportation preservation method based on a spatial electric field, characterized in that, include: Real-time collection of environmental parameters inside the cold chain transport compartment, including temperature, humidity, oxygen concentration, and microbial concentration, and screening of key influencing factors that significantly affect the preservation effect of goods from these environmental parameters; Based on the distribution characteristics of the key influencing factors and combined with the three-dimensional structural dimensions of the cold chain transport vehicle, the cold chain transport vehicle is divided into multiple independent electric field action regions, and each electric field action region corresponds to a preset initial spatial electric field parameter. The initial spatial electric field parameters of the multiple electric field action regions are optimized in real time. Based on the changing trends of the key influencing factors of each electric field action region, the intensity and frequency of the spatial electric field are dynamically adjusted to generate an adaptive electric field control strategy. Based on the adaptive electric field control strategy, the space electric field generating device is controlled to form a uniformly distributed space electric field in each of the electric field action regions; The space electric field continuously acts on the items within each electric field area to inhibit the growth rate of microorganisms on the surface of the items and the oxidation reaction rate inside the items; the preservation status data of the items within each electric field area is monitored in real time, including the change rate of the item's hardness and respiration intensity; based on the comparison results of the preservation status data with preset thresholds, the adaptive electric field control strategy is further optimized to achieve dynamic maintenance of the preservation effect of items during cold chain transportation. The real-time acquisition of environmental parameters inside the cold chain transport vehicle, including temperature, humidity, oxygen concentration, and microbial concentration, involves screening key influencing factors that significantly affect the preservation effect of goods. This process includes: preprocessing the environmental parameters to remove outliers and noise data, obtaining purified environmental data; using principal component analysis to extract features from the purified environmental data, obtaining multiple candidate influencing factors; calculating the correlation coefficient between each candidate influencing factor and the preservation effect of goods, identifying candidate influencing factors with absolute correlation coefficients greater than a preset threshold as key influencing factors; and sorting the key influencing factors from highest to lowest degree of influence to form a key influencing factor sequence.

2. The cold chain transportation and preservation method based on a spatial electric field as described in claim 1, characterized in that, Based on the distribution characteristics of the key influencing factors and combined with the three-dimensional structural dimensions of the cold chain transport vehicle, the cold chain transport vehicle is divided into multiple independent electric field action regions. This includes: performing a three-dimensional model of the internal space of the cold chain transport vehicle to obtain the structural parameters of the vehicle; dividing the internal space of the vehicle into grids along the height and horizontal directions according to the structural parameters to obtain multiple initial sub-regions; analyzing the distribution density of key influencing factors in each initial sub-region, merging adjacent initial sub-regions with a distribution density difference less than a preset threshold into one electric field action region; determining the center point location and boundary range of each electric field action region, and assigning a unique identifier number to each electric field action region.

3. The cold chain transportation and preservation method based on a spatial electric field as described in claim 2, characterized in that, The process of real-time optimization of the initial spatial electric field parameters of the multiple electric field action regions, dynamically adjusting the intensity and frequency of the spatial electric field based on the changing trends of key influencing factors in each electric field action region, and generating an adaptive electric field control strategy includes: setting up an independent parameter adjustment queue for each electric field action region, with each parameter adjustment queue corresponding to the spatial electric field parameters of one electric field action region; real-time acquisition of real-time data of key influencing factors in each electric field action region, and calculating the deviation between real-time data and historical data; determining the adjustment amplitude of the spatial electric field intensity and the adjustment step size of the frequency based on the magnitude of the deviation; controlling each parameter adjustment queue to correct the initial spatial electric field parameters according to the adjustment amplitude and adjustment step size to obtain optimized spatial electric field parameters; and integrating the optimized spatial electric field parameters of all electric field action regions into a unified adaptive electric field control strategy.

4. The cold chain transportation and preservation method based on a spatial electric field as described in claim 1, characterized in that, The step of further optimizing the adaptive electric field control strategy based on the comparison results between the preservation status data and the preset threshold includes: extracting the coupling characteristics of the item's hardness change rate and respiration intensity from the preservation status data; when the value of the coupling characteristics exceeds the preset safety threshold, adjusting the spatial electric field parameters in the adaptive electric field control strategy; the coupling adjustment includes simultaneously increasing the intensity of the spatial electric field and decreasing the frequency, or simultaneously decreasing the intensity and increasing the frequency; verifying the spatial electric field parameters after coupling adjustment to ensure that the adjusted parameters will not damage the item, thus obtaining the final optimized adaptive electric field control strategy.

5. The cold chain transportation and preservation method based on a spatial electric field as described in claim 1, characterized in that, The cold chain transport vehicle is equipped with multiple electric field generating units inside. The process of controlling the spatial electric field generating device to form a uniformly distributed spatial electric field within each electric field action area, based on the adaptive electric field control strategy, includes: constructing a three-dimensional physical model of the cold chain transport vehicle, the three-dimensional physical model containing the internal structure of the vehicle and the position information of each electric field generating unit; constructing an electric field generation model for each electric field generating unit, integrating all electric field generation models into the three-dimensional physical model to obtain a target simulation model; assigning corresponding control parameters to each electric field generating unit in the target simulation model based on the adaptive electric field control strategy; simulating the distribution of the spatial electric field within each electric field action area according to the control parameters and the target simulation model, ensuring that the uniformity error of the electric field intensity is within a preset range; and, based on the simulation results, activating the actual spatial electric field generating device to generate a spatial electric field consistent with the simulation results.

6. The cold chain transportation and preservation method based on a spatial electric field as described in claim 1, characterized in that, The cold chain transportation preservation method based on spatial electric field further includes: responding to an anomaly detection command for the target electric field's area of ​​action, the anomaly detection command including detection accuracy requirements; extracting anomaly data segments corresponding to the target electric field's area of ​​action from the preservation status data according to the anomaly detection command; performing multi-scale analysis on the anomaly data segments according to the detection accuracy requirements to identify the cause of the anomaly; and automatically adjusting the spatial electric field parameters of the target electric field's area of ​​action according to the cause of the anomaly, or issuing an alarm signal to remind manual intervention.

7. A cold chain transportation and preservation system based on a spatial electric field, used to implement the cold chain transportation and preservation method based on a spatial electric field as described in any one of claims 1 to 6, characterized in that, The system includes an environmental parameter acquisition module, an electric field region division module, a control strategy generation module, an electric field generation control module, and a preservation status monitoring module. The environmental parameter acquisition module collects environmental parameters inside the cold chain transport vehicle in real time and filters out key influencing factors that significantly affect the preservation effect of goods from these parameters. The electric field region division module divides the cold chain transport vehicle into multiple independent electric field action regions based on the distribution characteristics of the key influencing factors and the three-dimensional structural dimensions of the cold chain transport vehicle. Each electric field action region corresponds to a preset initial spatial electric field parameter. The control strategy generation module controls the multiple electric fields. The initial spatial electric field parameters of the region are optimized in real time. Based on the changing trends of key influencing factors in each electric field's area of ​​action, the intensity and frequency of the spatial electric field are dynamically adjusted to generate an adaptive electric field control strategy. The electric field generation control module is used to control the spatial electric field generating device to form a uniformly distributed spatial electric field in each of the electric field's areas of action based on the adaptive electric field control strategy. The preservation status monitoring module is used to monitor the preservation status data of the items in each of the electric field's areas of action in real time. Based on the comparison results of the preservation status data with preset thresholds, the adaptive electric field control strategy is further optimized to achieve dynamic maintenance of the preservation effect of items during cold chain transportation.

8. A cold chain transportation and preservation system based on a spatial electric field as described in claim 7, characterized in that, The electric field region division module, based on the distribution characteristics of the key influencing factors and combined with the three-dimensional structural dimensions of the cold chain transport vehicle, divides the cold chain transport vehicle into multiple independent electric field action regions. This includes: the electric field region division module performing a three-dimensional model of the internal space of the cold chain transport vehicle to obtain the vehicle's structural parameters; dividing the internal space of the vehicle into grids along the height and horizontal directions according to the structural parameters to obtain multiple initial sub-regions; analyzing the distribution density of key influencing factors within each initial sub-region, merging adjacent initial sub-regions with a distribution density difference less than a preset threshold into one electric field action region; determining the center point location and boundary range of each electric field action region, and assigning a unique identifier to each electric field action region.

9. A cold chain transportation and preservation system based on a spatial electric field as described in claim 8, characterized in that, The control strategy generation module optimizes the initial spatial electric field parameters of the multiple electric field action regions in real time. Based on the changing trends of key influencing factors in each electric field action region, it dynamically adjusts the intensity and frequency of the spatial electric field to generate an adaptive electric field control strategy. This includes: setting up an independent parameter adjustment queue for each electric field action region, with each queue corresponding to the spatial electric field parameters of one region; collecting real-time data of key influencing factors within each region and calculating the deviation between the real-time data and historical data; determining the adjustment amplitude of the spatial electric field intensity and the adjustment step size of the frequency based on the magnitude of the deviation; controlling each parameter adjustment queue to correct the initial spatial electric field parameters according to the adjustment amplitude and step size to obtain optimized spatial electric field parameters; and integrating the optimized spatial electric field parameters of all electric field action regions into a unified adaptive electric field control strategy.

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