Dynamic monitoring and adjusting system for cold-chain transportation of in-vitro diagnostic reagent

Abstract

The invention relates to the technical field of reagent cold-chain transportation monitoring, and particularly discloses a dynamic monitoring and adjusting system for cold-chain transportation of in-vitro diagnostic reagents, which is used for solving the problem that the temperatures of some regions cannot reach or keep a set value in time because local hot spots or cold regions are formed due to non-uniform stacking of the existing in-vitro diagnostic reagents. According to the method, the global temperature data and the reference three-dimensional temperature data in the warehouse are acquired, the first temperature abnormal fluctuation value is calculated, the abnormal deviation between the local temperature data and the global data is automatically identified, the consistency of the temperature data is ensured, the temperature gradient is quantitatively calculated from the global and local angles, and the accuracy of the temperature gradient is improved. Temperature distribution characteristics in the warehouse can be captured in detail, temperature gradient difference values are calculated by comparing different data sources, a reasonable threshold value is set, and automatic early warning is achieved, so that the stability of a temperature control environment is guaranteed, and the quality of an in-vitro diagnostic reagent is protected.

Description

Technical Field

[0001] The present invention relates to the technical field of reagent cold chain transportation monitoring, and more specifically, to a dynamic monitoring and regulation system for the cold chain transportation of in vitro diagnostic reagents. Background Art

[0002] In vitro diagnostic reagents are highly specialized and have strict requirements for transportation conditions. Therefore, their transportation methods and temperature monitoring during transit are one of the key points in the entire cold chain management of in vitro diagnostic reagents. Currently, some existing literature (Shi Hong, Yu Ling, Xu Haiqing. Cold Chain Management of In Vitro Diagnostic Reagents [J]. Medical Equipment, 2020, 33(03): 65-68.) mentions that some large-scale supply enterprises use refrigerated trucks to transport reagents. The refrigerated trucks are equipped with cold chain transportation environment monitoring system software and are configured with multiple temperature detection probes, which can automatically monitor, record, and alarm abnormal situations of the temperature and humidity of the reagents during transportation, and transmit the data to the relevant management departments of the company through GPS. In addition, an embedded printer is configured on the vehicle. When the reagents reach the destination, the temperature data during transportation can be printed out. However, refrigerated trucks usually adopt a centralized refrigeration system, and cold air is sent into the carriage through a fan. After the cold air enters from the air outlet, affected by factors such as the carriage structure, air duct design, and cargo occlusion, a temperature gradient is often formed inside the carriage. The area near the air outlet has a lower temperature, while the area far from the air outlet or near the door may have a higher temperature. For temperature-sensitive in vitro diagnostic reagents, this temperature difference may cause the local temperature to exceed the ideal temperature control range.

[0003] Existing cold chain transport vehicles use a refrigeration unit with multiple evaporators (mostly dual evaporators) to divide the general refrigerated truck carriage into a multi-temperature zone structure through a physical partition. However, when performing similar modifications, it should be noted that the layout of the dual evaporators will have a very large impact on the temperature distribution inside the carriage. Some existing literature (Zhou Fei, Zhu Zheng. Experience in the Configuration and Verification of Refrigerated Trucks in the Pharmaceutical Cold Chain [J]. Shanghai Medical & Pharmaceutical Journal, 2017, 38(23): 64-66.) gives the temperature distribution inside the vehicle with the rear evaporator at the rear as shown in Figure 2 The figure shows that reducing the space at the rear of the carriage can reduce the occurrence of high-temperature areas, but the multi-temperature zone structure may cause an obvious temperature gradient during the refrigeration process. Especially when the space at the rear of the carriage is large, it is not easy for the cold air to cover evenly. This temperature difference not only increases the risk of in vitro diagnostic reagents being affected by temperature fluctuations, but also may cause insufficient temperature control effect in some areas, thereby affecting the long-term stability of in vitro diagnostic reagents. Since cold air is heavier, it usually shows a trend of gradually increasing temperature from bottom to top inside the carriage. In vitro diagnostic reagents are often stacked in boxes during transportation, and the stacking method will also affect the flow of cold air. If the stacking is dense or uneven, local hot spots or cold zones will be formed, resulting in the temperature in some areas not being able to reach or maintain the set value in time. To solve the above problems, a technical solution is provided below. Summary of the Invention

[0004] To overcome the above defects of the prior art, the present invention provides a dynamic monitoring and regulation system for the cold chain transportation of in vitro diagnostic reagents. By automatically identifying the abnormal deviation between the local temperature data and the global data, it solves the problem that uneven stacking of in vitro diagnostic reagents will form local hot spots or cold zones, resulting in the temperature in some areas not being able to reach or maintain the set value in time, thereby ensuring the stability of the temperature control environment and protecting the quality of in vitro diagnostic reagents to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A dynamic monitoring and regulation system for the cold chain transportation of in vitro diagnostic reagents includes a multi-source temperature monitoring module, a reference calibration unit, a first-level temperature difference analysis unit, a second-level temperature difference analysis unit, and a regional temperature difference verification unit; the multi-source temperature monitoring module is used to obtain the global temperature data and the reference three-dimensional temperature data in the cargo hold; the first-level temperature difference analysis unit is based on the global temperature data T q (x i ,y i ,z i ) respectively obtains the first temperature gradient difference in the vertical direction in the cargo hold and the second temperature gradient difference in the horizontal direction The second-level temperature difference analysis unit is used to obtain the reference three-dimensional temperature data sequence I1 = {T1,..., T i ,…,T N} of the cargo hold, evenly divides the inner wall of the cold chain vehicle cargo hold without loading into several cargo hold space blocks in the vertical and horizontal directions, obtains the three-dimensional position coordinates (x j ,y i ,z j ) of the center position of each cargo hold space block, generates a continuous temperature field inside the cargo hold through a three-dimensional difference algorithm based on the reference three-dimensional temperature data sequence to obtain the three-dimensional temperature data of each cargo hold space block, and constitutes the first-level three-dimensional temperature data sequence I2 = {T1,..., T q ,…,T Q}, T q is the three-dimensional temperature data of the qth cargo hold space block, and Q is the number of cargo hold space blocks; based on the first-level three-dimensional temperature data sequence I2, analyze and obtain the third temperature gradient difference in the vertical direction in the cargo hold and the fourth temperature gradient difference in the horizontal direction The regional temperature difference verification unit is used to extract the first temperature gradient difference the second temperature gradient difference the third temperature gradient difference and the fourth temperature gradient difference Determine whether the temperature in the bin area is balanced.

[0007] As a further solution of the present invention, the multi-source temperature monitoring module includes two infrared thermal imaging cameras and high-precision temperature sensors; the infrared thermal imaging cameras are installed at the diagonal of the top surface of the cold chain vehicle cargo hold; the high-precision temperature sensors obtain the cargo hold surface when the cold chain vehicle cargo hold is not loaded, and evenly divide the opposite cargo hold surfaces into several segmentation blocks in pairs, and install high-precision temperature sensors in each segmentation block to obtain the reference three-dimensional temperature data sequence I1 = {T1,…,T i ,…,T N}, where T i is the i-th reference three-dimensional temperature data, and N is the total number of reference three-dimensional temperature data; based on the infrared thermal imaging camera, obtain the global temperature data T q (x i ,y i ,z i ) in the cargo hold; based on the high-precision temperature sensor, obtain the reference three-dimensional temperature data in the cargo hold.

[0008] The infrared thermal imaging cameras are installed diagonally from the top surface of the cold chain vehicle cargo hold, which can cover the entire cargo hold and obtain a continuous and macroscopic global temperature field. The high-precision temperature sensors are evenly arranged on the cargo hold surface, and the reference three-dimensional temperature data sequence is obtained through the segmentation blocks, which can provide high-precision and detailed temperature information and provide a reference for global data correction and local anomaly detection.

[0009] Using the reference temperature data provided by the high-precision sensor, the global temperature field obtained by the infrared thermal imaging camera can be corrected to compensate for the errors caused by factors such as surface material and reflection in infrared temperature measurement. At the same time, the global perspective provided by the infrared data can help identify temperature anomaly areas, improve the utilization rate of local sensor data, and form a more accurate three-dimensional temperature field.

[0010] As a further solution of the present invention, the abnormal swallowing recognition unit draws the mean change curve of the red channel based on the R value of the facial color change feature, draws the mean brightness change curve based on the brightness distribution value, and calculates the facial color change rate D diff (i) = |D(i + 1) - D(i)|, where D(i) is the second facial color feature value of the i-th frame, and D(i + 1) is the facial color feature value of the (i + 1)-th frame, and calculate the mean value of the facial color change rate and the standard deviation σ Δd Determine the four-level swallowing recognition range of the user as α4 is the fourth threshold adjustment factor, and based on the four-level swallowing recognition range, the feeding flow rate of the user is regulated to obtain the real-time second facial color feature value D(i) of the user: when When the patient is in an abnormal swallowing state, an instruction to reduce the medication flow rate or to stop medication feeding is issued.

[0011] As a further solution of the present invention, the reference calibration unit is used to q (x i ,y i ,z i ) and the reference three-dimensional temperature data sequence I1 to calculate the first abnormal temperature fluctuation value ΔT at the same position in the warehouse i =|T i -T q (x i ,y i ,z i )], compare the first temperature abnormal fluctuation value with the preset temperature abnormal fluctuation threshold value. If the first temperature abnormal fluctuation value is greater than or equal to the preset temperature abnormal fluctuation threshold value, the benchmark three-dimensional temperature data of the position needs to be adjusted; if the first temperature abnormal fluctuation value is less than the preset temperature abnormal fluctuation threshold value, the benchmark three-dimensional temperature data of the position does not need to be adjusted.

[0012] The first-level temperature difference analysis unit is based on the global temperature data T q (x i ,y i ,z i ) respectively obtain the temperature gradient difference in the vertical direction and the horizontal direction in the cargo hold, combine the global temperature data with the depth information in the cargo hold, and obtain the first longitudinal temperature value And the first transverse temperature value

[0013] Get the midpoint of the warehouse height, divide the warehouse into upper and lower layers according to the midpoint of the warehouse height, and calculate the first average temperature gradient difference value of the upper area of ​​the warehouse And the first average temperature gradient difference value of the lower area of ​​the cargo hold The difference between

[0014] Get the midpoint of the cargo hold length, divide the cargo hold into two parts according to the midpoint of the cargo hold length, and calculate the first average temperature gradient difference value of the front area of ​​the cargo hold. And the first average temperature gradient difference value of the rear area of ​​the cargo hold The difference between

[0015] As a further solution of the present invention, the secondary temperature difference analysis unit is based on the primary three-dimensional temperature data sequence I2={T1,…,T q ,…,T Q} Calculate the second temperature gradient differences in the vertical and horizontal directions within the warehouse respectively. The second temperature gradient differences include the second longitudinal temperature value and the second transverse temperature value;

[0016] For adjacent divided blocks at the same horizontal plane but different heights, obtain the central coordinate positions of divided blocks q and q + 1 in the z direction as z q and z q+1 respectively, and the corresponding temperatures are T q and T q+1 respectively. Calculate the second longitudinal temperature value

[0017] For adjacent divided blocks at different horizontal planes on the same vertical plane, obtain the central coordinates of adjacent divided blocks p and p + 1 in the x direction as x p and x p+1 respectively, and the corresponding temperatures are T p and T p+1 respectively. The second transverse temperature value

[0018] As a further solution of the present invention, the secondary temperature difference analysis unit evenly divides the number of divided blocks in the vertical direction of the warehouse, and calculates the second average temperature longitudinal gradients of the upper and lower two regions respectively. If the number M of divided blocks in the vertical direction of the warehouse is an even number, then divide the warehouse into upper and lower two regions according to one-half of the number of divided blocks ; if the number of divided blocks in the vertical direction of the warehouse is an odd number, then divide the warehouse into upper and lower two regions according to one-half of the number of divided blocks , that is, the divided block in the middle in the vertical direction is both in the upper region and in the lower region;

[0019] The second average temperature longitudinal gradient of the upper layer of the warehouse is obtained by averaging the second longitudinal temperature values of each divided block in the upper region, where is the change rate of the second longitudinal temperature value with respect to the height z at divided block a in the upper region, that is, the local temperature gradient at divided block a, N 上层 is the number of divided blocks in the upper region, is the sum of the local temperature gradients of all divided blocks in the upper layer;

[0020] The second average temperature longitudinal gradient of the lower layer of the warehouse is obtained by averaging the second longitudinal temperature values of each divided block in the lower region, where is the change rate of the second longitudinal temperature value with respect to the height z at divided block b in the lower region, that is, the local temperature gradient at divided block b, N 下层 is the number of divided blocks in the lower region, To sum up the local temperature gradients of all the divided blocks in the lower layer;

[0021] By calculating the second average longitudinal temperature gradient of the upper layer of the cargo hold And the second average longitudinal temperature gradient of the lower layer of the cargo hold is To obtain the third temperature gradient difference by taking the difference

[0022] As a further solution of the present invention, the secondary temperature difference analysis unit obtains the number of divided blocks in the horizontal direction of the cargo hold for equal division, and calculates the second average lateral temperature gradients of the upper and lower layer regions respectively. If the number R of divided blocks in the horizontal direction of the cargo hold is even, then according to one-half of the number of divided blocks The cargo hold is divided into front and rear regions; if the number of divided blocks in the horizontal direction of the cargo hold is odd, then according to one-half of the number of divided blocks The cargo hold is divided into front and rear regions, that is, the divided block in the middle in the horizontal direction is both in the front region and in the rear region;

[0023] The second average lateral temperature gradient of the front part of the cargo hold is Obtained by averaging the second lateral temperature values of each divided block in the front region, where Is the change rate of the second lateral temperature value at the divided block c in the front region with respect to the height z, that is, the local temperature gradient at the divided block c, N 前部 Is the number of divided blocks in the front region, Is to sum up the local temperature gradients of all the divided blocks in the front part;

[0024] The second average lateral temperature gradient of the rear part of the cargo hold is Obtained by averaging the second lateral temperature values of each divided block in the rear region, where Is the change rate of the second lateral temperature value at the divided block d in the rear region with respect to the height z, that is, the local temperature gradient at the divided block d, N 后部 Is the number of divided blocks in the rear region, Is to sum up the local temperature gradients of all the divided blocks in the rear part;

[0025] By calculating the second average lateral temperature gradient of the front part of the cargo hold And the second average lateral temperature gradient of the rear part of the cargo hold is To obtain the fourth temperature gradient difference by taking the difference

[0026] As a further solution of the present invention, the regional temperature difference verification unit is used to extract the first temperature gradient difference The second temperature gradient difference The third temperature gradient difference and the fourth temperature gradient difference To determine whether the temperature in the bin area is balanced, specifically:

[0027] When and the temperature in the bin area is balanced and there is no need to trigger an alarm reminder; otherwise, the temperature in the bin area is unbalanced and an alarm reminder needs to be triggered; where ΔT1 is the preset vertical temperature gradient threshold and ΔT2 is the preset horizontal temperature gradient threshold.

[0028] The technical effects and advantages of a dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents according to the present invention: By obtaining the global temperature data and reference three-dimensional temperature data in the cargo hold, calculating the first temperature abnormal fluctuation value, automatically identifying the abnormal deviation between the local temperature data and the global data, ensuring the consistency of the temperature data, quantitatively calculating the temperature gradient from both the global and local perspectives, being able to capture the temperature distribution characteristics in the cargo hold in detail, comparing the temperature gradient differences calculated from different data sources, and setting reasonable thresholds to achieve automatic early warning, thereby ensuring the stability of the temperature control environment and protecting the quality of in vitro diagnostic reagents. Brief Description of the Drawings

[0029] Figure 1 It is a real-time temperature overview and thermal distribution display interface provided by the present invention;

[0030] Figure 2 It is the temperature distribution in the vehicle behind the existing rear evaporator provided by the present invention;

[0031] Figure 3 It is a 24-hour temperature index and trend chart provided by the present invention;

[0032] Figure 4 It is a bar chart of temperature range distribution provided by the present invention;

[0033] Figure 5 It is a temperature fluctuation scatter plot provided by the present invention;

[0034] Figure 6 It is a schematic structural diagram of a dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents provided by the present invention. Detailed Embodiments

[0035] Next, the technical solutions in the present invention will be clearly and completely described in conjunction with the drawings in the present invention. Obviously, the described technical solutions are only a part of the present invention, rather than all of it. Based on the technical solutions in the present invention, all other technical solutions obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present invention.

[0036] Example 1

[0037] Figure 6 The structural schematic diagram of a dynamic monitoring and regulating system for cold chain transportation of in vitro diagnostic reagents provided by the present invention is shown in the figure. A dynamic monitoring and regulating system for cold chain transportation of in vitro diagnostic reagents includes a multi-source temperature monitoring module, a reference calibration unit, a first-level temperature difference analysis unit, a second-level temperature difference analysis unit, and a regional temperature difference verification unit; the multi-source temperature monitoring module is respectively connected to the reference calibration unit, the first-level temperature difference analysis unit, and the second-level temperature difference analysis unit, and the first-level temperature difference analysis unit and the second-level temperature difference analysis unit are respectively connected to the regional temperature difference verification unit.

[0038] The multi-source temperature monitoring module is used to obtain the global temperature data and the reference three-dimensional temperature data in the cargo hold.

[0039] Specifically, the multi-source temperature monitoring module includes two infrared thermal imaging cameras and high-precision temperature sensors;

[0040] The infrared thermal imaging cameras are installed diagonally on the top surface of the cold chain vehicle cargo hold; the high-precision temperature sensors obtain the cargo hold surface when the cold chain vehicle cargo hold is not loaded, evenly divide the opposite cargo hold surfaces into several segmentation blocks in pairs, and install high-precision temperature sensors in each segmentation block to obtain the reference three-dimensional temperature data sequence I1 = {T1,…,T i ,…,T N} where, T i is the i-th reference three-dimensional temperature data, and N is the total number of reference three-dimensional temperature data.

[0041] Based on the infrared thermal imaging cameras, obtain the global temperature data T q (x i ,y i ,z i ) in the cargo hold.

[0042] Based on the high-precision temperature sensors, obtain the reference three-dimensional temperature data in the cargo hold.

[0043] Specifically, the reference calibration unit is used to calculate the first temperature abnormal fluctuation value ΔT q at the same position in the cargo hold according to the global temperature data T i (x i ,y i ) and the reference three-dimensional temperature data sequence I1, where ΔT i = |T i - T q (x i ,y i ,z i) Compare the first temperature abnormal fluctuation value with a preset temperature abnormal fluctuation threshold. If the first temperature abnormal fluctuation value is greater than or equal to the preset temperature abnormal fluctuation threshold, the reference three-dimensional temperature data at this position needs to be adjusted; if the first temperature abnormal fluctuation value is less than the preset temperature abnormal fluctuation threshold, the reference three-dimensional temperature data at this position does not need to be adjusted.

[0044] By calculating the first temperature abnormal fluctuation value at each position, it is possible to intuitively compare whether the local temperature data obtained by the high-precision temperature sensor and the global temperature data obtained by the infrared thermal imaging camera meet the judgment criteria, which helps to discover deviations caused by measurement errors or local environmental interference. The infrared thermal imaging camera has the ability of global scanning, but local data deviation may be caused by factors such as surface material and angle; while the high-precision temperature sensor provides local high-precision temperature information. By comparing the two, the reference calibration unit can use the locally highly accurate data to correct the global data, thereby constructing a more accurate three-dimensional temperature field.

[0045] Specifically, the first-level temperature difference analysis unit is based on the global temperature data T q (x i ,y i ,z i ) to obtain the temperature gradient difference values in the vertical and horizontal directions inside the warehouse respectively, combine the global temperature data with the depth information inside the warehouse to obtain the first longitudinal temperature value and the first transverse temperature value

[0046] Obtain the midpoint of the warehouse height, and divide the warehouse into upper and lower layers according to the midpoint of the warehouse height to calculate the first average temperature gradient difference value in the upper area of the warehouse and the first average temperature gradient difference value in the lower area of the warehouse The difference, that is, the first temperature gradient difference

[0047] Obtain the midpoint of the warehouse length, and divide the warehouse into front and back parts according to the midpoint of the warehouse length to calculate the first average temperature gradient difference value in the front area of the warehouse and the first average temperature gradient difference value in the back area of the warehouse The difference, that is, the second temperature gradient difference

[0048] By using global temperature data in combination with depth information and calculating the temperature gradient in the vertical direction and the temperature gradient in the horizontal direction using the central difference method, it is possible to accurately reflect the temperature change rate at different positions inside the cargo hold, capture local hot spots or cold areas, and thus provide a data basis for subsequent temperature control adjustment; by dividing the cargo hold into an upper layer and a lower layer at the midpoint of the cargo hold height, calculating the average temperature gradient difference of each layer separately, and taking the difference, it is possible to intuitively reflect the unevenness of the temperature distribution in the vertical direction; by dividing the cargo hold into a front part and a rear part at the midpoint of the cargo hold length and calculating the horizontal temperature gradient difference to compare the temperature changes between different regions, it is convenient to identify the temperature difference between the front and the rear. The infrared thermal imaging camera can provide the global temperature distribution of the cargo hold, and calculating the temperature gradient in combination with depth information can more accurately describe the spatial temperature change. Using global data ensures the continuity and consistency of the overall temperature field description, and thus provides an accurate reference for cold chain temperature control. By calculating the average temperature gradient difference in different directions (vertical and horizontal directions), the system can detect the uneven temperature distribution area. If the detected gradient difference exceeds the preset range, an alarm can be triggered in a timely manner, and the abnormality can be corrected by dynamically adjusting the cold chain equipment (such as adjusting the cold air distribution and the fan speed), so as to ensure the temperature balance inside the cargo hold and protect the quality of temperature-sensitive products such as in vitro diagnostic reagents.

[0049] Specifically, the secondary temperature difference analysis unit is used to obtain the reference three-dimensional temperature data sequence I1 = {T1,..., T i ,..., T N} of the cargo hold, evenly divide the inner wall of the cold chain vehicle cargo hold without loading into several cargo hold space blocks in the vertical direction and the horizontal direction, obtain the three-dimensional position coordinates (x j , y j , z j ) of the center position of each cargo hold space block, generate a continuous temperature field inside the cargo hold through a three-dimensional difference algorithm based on the reference three-dimensional temperature data sequence to obtain the three-dimensional temperature data of each cargo hold space block, and form the first-level three-dimensional temperature data sequence I2 = {T1,..., T q ,..., T Q}, where T q is the three-dimensional temperature data of the q-th cargo hold space block, and Q is the number of cargo hold space blocks.

[0050] Based on the first-level three-dimensional temperature data sequence I2 = {T1,..., T q ,..., T Q}, calculate the second temperature gradient differences in the vertical direction and the horizontal direction inside the cargo hold respectively. The second temperature gradient differences include the second longitudinal temperature value and the second transverse temperature value.

[0051] Specifically, for adjacent segmentation blocks at the same horizontal plane but different heights, obtain the central coordinate positions of the segmentation blocks q and q + 1 in the z direction as zq and z q+1 corresponding to the temperature T q and T q+1 calculate the second longitudinal temperature value

[0052] Obtain the number of partition blocks in the vertical direction of the cargo hold for equal division, and calculate the second average temperature longitudinal gradient of the upper and lower layer areas respectively. If the number M of partition blocks in the vertical direction of the cargo hold is even, then according to half of the number of partition blocks divide the cargo hold into upper and lower layer areas; if the number of partition blocks in the vertical direction of the cargo hold is odd, then according to half of the number of partition blocks divide the cargo hold into upper and lower layer areas, that is, the partition block in the middle in the vertical direction is both in the upper layer area and in the lower layer area.

[0053] The second average temperature longitudinal gradient of the upper layer of the cargo hold is obtained by averaging the second longitudinal temperature values of each partition block in the upper layer area, where is the change rate of the second longitudinal temperature value with height z at partition block a in the upper layer area, that is, the local temperature gradient at partition block a, N 上层 is the number of partition blocks in the upper layer area, is the sum of the local temperature gradients of all partition blocks in the upper layer.

[0054] The second average temperature longitudinal gradient of the lower layer of the cargo hold is obtained by averaging the second longitudinal temperature values of each partition block in the lower layer area, where is the change rate of the second longitudinal temperature value with height z at partition block b in the lower layer area, that is, the local temperature gradient at partition block b, N 下层 is the number of partition blocks in the lower layer area, is the sum of the local temperature gradients of all partition blocks in the lower layer.

[0055] By calculating the second average temperature longitudinal gradient of the upper layer of the cargo hold and the second average temperature longitudinal gradient of the lower layer of the cargo hold is obtain the third temperature gradient difference by taking the difference

[0056] The secondary temperature difference analysis unit uses the reference three-dimensional temperature data collected by high-precision temperature sensors to construct a continuous temperature field inside the cargo hold through three-dimensional interpolation, and evenly divides the space inside the cargo hold into several spatial blocks in the vertical and horizontal directions. Then, it calculates the local temperature gradients of each divided block. Through the reference three-dimensional temperature data and the three-dimensional interpolation algorithm, a continuous and detailed temperature field data can be generated inside the cargo hold. Compared with simply relying on boundary data, it can more truly reflect the internal temperature distribution, thus providing an accurate basis for subsequent temperature control.

[0057] By evenly dividing the cargo hold space blocks into upper and lower layers in the vertical direction (if the number of divided blocks is even, each layer contains M / 2 blocks; if it is odd, the middle block is included in both the upper and lower layers), calculate the second average longitudinal temperature gradients of the upper and lower layers respectively, and then by calculating the difference between the two, the balance of the temperature distribution in the vertical direction of the cargo hold can be quantified. This layered comparison can clearly show whether there are abnormal temperature gradients between the upper and lower layers, which helps to detect local hot spots or cold areas in a timely manner.

[0058] Divide the cargo hold into the front part and the rear part in the horizontal direction (if the number of divided blocks is even, each part contains R / 2 blocks; if it is odd, the middle block is included in both the front and rear parts). Calculate the average temperature gradients of the front and rear regions respectively, and find the difference between them, which can intuitively reflect the balance of the front and rear temperature distributions in the cargo hold and discover possible temperature control problems in the horizontal direction. Using the local temperature gradients of multiple divided blocks within the region for average calculation can effectively reduce the measurement noise and accidental errors that may occur at a single sampling point and obtain more stable and reliable temperature gradient data.

[0059] Specifically, for the divided blocks adjacent to different horizontal planes on the same vertical plane, obtain the central coordinates of adjacent divided blocks p and p + 1 in the x direction as x p and x p+1 , and the corresponding temperatures are T p and T p+1 , the second lateral temperature value

[0060] Obtain the number of divided blocks in the horizontal direction of the cargo hold for equal division, and calculate the second average lateral temperature gradients of the upper and lower layer regions respectively. If the number of divided blocks R in the horizontal direction of the cargo hold is even, then divide the cargo hold into the front and rear part regions according to one-half of the number of divided blocks If the number of divided blocks in the horizontal direction of the cargo hold is odd, then divide the cargo hold into the front and rear part regions according to one-half of the number of divided blocks Divide the cargo hold into the front and rear part regions, that is, the divided block in the middle of the horizontal direction is both in the front part region and in the rear part region.

[0061] The second average lateral temperature gradient of the front part of the cargo hold is Obtained by averaging the second lateral temperature values of each segmentation block in the front region, where is the change rate of the second lateral temperature value with height z at segmentation block c in the front region, that is, the local temperature gradient at segmentation block c, N 前部 is the number of segmentation blocks in the front region, is the sum of the local temperature gradients of all segmentation blocks in the front part.

[0062] The second average temperature lateral gradient at the rear of the cargo hold is Obtained by averaging the second lateral temperature values of each segmentation block in the rear region, where is the change rate of the second lateral temperature value with height z at segmentation block d in the rear region, that is, the local temperature gradient at segmentation block d, N 后部 is the number of segmentation blocks in the rear region, is the sum of the local temperature gradients of all segmentation blocks in the rear part.

[0063] By calculating the second average temperature lateral gradient at the front of the cargo hold and the second average temperature lateral gradient at the rear of the cargo hold is to obtain the fourth temperature gradient difference by taking the difference

[0064] Specifically, the regional temperature difference verification unit is used to extract the first temperature gradient difference the second temperature gradient difference the third temperature gradient difference and the fourth temperature gradient difference to determine whether the temperature in the warehouse area is balanced. Specifically:

[0065] When and the temperature in the warehouse area is balanced and there is no need to trigger an alarm reminder; otherwise, the temperature in the warehouse area is unbalanced and an alarm reminder needs to be triggered; where, ΔT1 is the preset vertical direction temperature gradient threshold, and ΔT2 is the preset horizontal direction temperature gradient threshold.

[0066] Figure 1This is the real-time temperature overview and thermal distribution display interface provided by the present invention, which marks the current average temperature (representing the average temperature value of all monitoring points in the cargo hold at this time), the temperature fluctuation range (referring to the maximum amplitude of the deviation of the highest and lowest temperatures detected at the current moment from the average temperature, reflecting the temperature difference between different regions in the cargo hold), the number of abnormal alarms (indicating that the system identified 2 temperature anomalies during the most recent detection cycle, which may be local temperatures deviating from the set threshold), and gives a thermal map of the temperature distribution, presenting the temperature distribution at each position in the cargo hold in the form of a grid. The darker the color (red or warm tone), the higher the temperature; the lighter the color (blue or cold tone), the lower the temperature, which is convenient for quickly locating hot spots or cold areas. And the temperature trend graph shows the change trends of the average temperature, the highest temperature, and the lowest temperature over a period of time (such as the past 1 hour, 4 hours, etc.) through a line graph, which is used to observe whether the temperature fluctuates within the set range.

[0067] Figure 3 This is the 24-hour temperature index and trend graph provided by the present invention, which marks the average temperature in the past 24 hours (the average temperature level calculated by integrating all monitoring point data in the recent 24 hours), the maximum temperature fluctuation (the maximum difference between the highest and lowest temperatures in the past 24 hours, reflecting the overall fluctuation amplitude), the temperature duration (referring to the time length of a certain temperature range or a certain abnormal state in the past 24 hours), the standard deviation (used to measure the dispersion degree of the temperature data in the past 24 hours, and the smaller the value, the more stable the temperature), and gives a 24-hour temperature change trend graph. The abscissa is the time scale from 0:00 to 24:00, the ordinate is the temperature value, and the line graph shows the change of the average temperature or the temperature of a specified monitoring point in the past 24 hours, which is convenient for viewing the temperature trend throughout the day and the peak and valley time points.

[0068] Figure 4 This is the bar graph of the temperature range distribution provided by the present invention. The abscissa is the temperature range, and the range from -19.0°C to -17.0°C is segmented at intervals of 0.5°C or 1.0°C. For example: -19.0~-18.5, -18.5~-18.0, -18.0~-17.5, -17.5~-17.0; the ordinate is the duration representing the number of hours sustained in the corresponding temperature range; each bar represents the cumulative duration in the temperature range, and the higher the bar, the longer the time sustained at this temperature range. Through this graph, it is possible to quickly understand the main temperature range distribution of the cold chain vehicle in a day and judge whether it is in the target temperature range for a long time.

[0069] Figure 5The temperature fluctuation scatter plot provided by the present invention has the time on the abscissa, for example, from 0:00 to 24:00 of the same day, or a span of multiple days; there is a mark "2024-01-18 14:00:00" in the figure; the ordinate is the temperature fluctuation, showing the deviation value of each time point relative to a certain reference temperature (such as the average temperature or the set temperature). Each point represents the temperature deviation measured at that time point. For example, "0.3" means that the temperature at this moment is 0.3°C higher than the reference temperature; if the point is in the negative value area, it means that the temperature is lower than the reference value. By observing the distribution of the scatter points, the situation of the temperature deviating from the reference value within one day or multiple days can be observed. If most of the points are concentrated within ±0.5°C, it indicates that the temperature is relatively stable; if there are multiple points with large deviations, potential temperature control abnormalities need to be alerted.

[0070] The first temperature gradient difference calculated using the global temperature data obtained by the infrared thermal imaging camera and the second temperature gradient difference interpolated from the reference three-dimensional temperature data generated by the high-precision temperature sensor. The two sets of data respectively reflect the global and local temperature distribution situations. By comparing the differences between these two sets of data (i.e., the in the vertical direction and the in the horizontal direction), temperature anomalies caused by sensor deviation, environmental interference, or measurement errors can be effectively identified, ensuring the accuracy and reliability of temperature monitoring; by calculating the average temperature gradient of the area in the vertical and horizontal directions respectively and obtaining the difference between the two sets of gradients, it can intuitively reflect whether the temperature distribution in the cargo hold is balanced. When the differences between the two sets of gradient differences are both lower than the preset thresholds (ΔT1 and ΔT2), it indicates that the temperature distribution in each area is basically balanced; otherwise, it is determined that there is an anomaly, providing a basis for subsequent temperature control adjustment.

[0071] Embodiment 2

[0072] The reference temperature data measured at a position in the cold chain vehicle cargo hold by the high-precision temperature sensor is T i = 6.5°C, and the global temperature data corresponding to this position obtained by the infrared thermal imaging camera is T q (x i , y i , z i ) = 8.0°C. The reference calibration unit calculates the first temperature abnormal fluctuation value ΔT i = |T i - T q (x i , y i , z i)| = 1.5 °C. At this time, the preset temperature abnormal fluctuation threshold is 1.0 °C. Since 1.5 °C > 1.0 °C, it is determined that the abnormal temperature fluctuation at this position exceeds the normal range. In this case, the reference calibration unit will determine that the reference three-dimensional temperature data at this position is abnormal and needs to be adjusted. Subsequently, a data correction algorithm (such as interpolation correction or weighted average correction) can be started to adjust the data at this position to make it more in line with the actual situation of the global temperature field and ensure the uniform temperature distribution of the entire cargo hold.

[0073] Embodiment 3

[0074] When the cold chain vehicle is in the unloaded state, data is collected through the multi-source temperature monitoring module to obtain the following information:

[0075] Through two infrared thermal imaging cameras installed at the diagonal of the cargo hold ceiling, the system obtains the global temperature field inside the cargo hold. Using the global data, the first-level temperature difference analysis unit calculates the first longitudinal temperature gradient difference and the first transverse temperature gradient difference according to the depth information: The cargo hold is evenly divided into the upper layer and the lower layer according to the height midpoint. After calculation, the average longitudinal gradients of the upper layer area and the lower layer area are 0.8 °C / m and 0.0 °C / m respectively (or the lower layer gradient is a relatively low value), and then the first temperature gradient difference is obtained. The cargo hold is divided into the front part and the rear part according to the horizontal center line. After calculation, the average transverse gradients of the front part area and the rear part area are 1.2 °C / m and 0.0 °C / m respectively, and the second temperature gradient difference is obtained.

[0076] The high-precision temperature sensor obtains the temperature of each segmentation block by evenly dividing several segmentation blocks (reference three-dimensional temperature data sequence) on the inner wall of the cargo hold. Then, the second-level temperature difference analysis unit uses the three-dimensional interpolation algorithm to generate a continuous temperature field inside the cargo hold from these discrete data and evenly divides the internal space into several space blocks in the vertical and horizontal directions. After calculation, the third temperature gradient difference and the fourth temperature gradient difference are obtained: After stratifying in the vertical direction, the average local longitudinal temperature gradient of the upper layer area is 0.9 °C / m, and that of the lower layer area is 0.0 °C / m, and then the third temperature gradient difference is obtained.

[0077] The regional temperature difference verification unit will separately extract these four gradient differences and calculate the difference between them: the vertical direction difference. The horizontal direction difference The preset vertical direction temperature gradient threshold ΔT1 = 0.2 °C / m, and the preset horizontal direction temperature gradient threshold ΔT2 = 0.3 °C / m.

[0078] According to the judgment rule: if the differences in both the vertical and horizontal directions are lower than the corresponding thresholds, it is considered that the temperature in the cargo hold area is balanced and there is no need to trigger an alarm; if the difference in any direction exceeds the threshold, it is considered that the regional temperature is unbalanced and an alarm reminder needs to be triggered. Therefore, based on 0.1℃ / m < 0.2℃ / m in the vertical direction and 0.2℃ / m < 0.3℃ / m in the horizontal direction, the system determines that the temperature in the cargo hold area is balanced and does not trigger a warning.

[0079] In the embodiment of the present invention, by obtaining the global temperature data and the reference three-dimensional temperature data in the cargo hold, and calculating the first temperature abnormal fluctuation value, the abnormal deviation between the local temperature data and the global data is automatically identified to ensure the consistency of the temperature data. The temperature gradient is quantitatively calculated from both the global and local perspectives, and the temperature distribution characteristics in the cargo hold can be detailedly captured. By comparing the temperature gradient differences calculated from different data sources and setting reasonable thresholds, automatic early warning is realized, thereby ensuring the stability of the temperature control environment and protecting the quality of in vitro diagnostic reagents.

[0080] As mentioned above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claimed rights.

[0081] Finally: The above is only the preferred solution of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should all be included within the protection scope of the present invention.

Claims

1. A dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents, comprising a multi-source temperature monitoring module, a reference calibration unit, a first-level temperature difference analysis unit, a second-level temperature difference analysis unit, and a regional temperature difference verification unit; characterized in that, The multi-source temperature monitoring module is used to obtain the global temperature data and the reference three-dimensional temperature data in the cargo hold; the first-level temperature difference analysis unit is based on the global temperature data T q (x i , y i , z i ) respectively obtains the first temperature gradient difference in the vertical direction in the cargo hold and the second temperature gradient difference in the horizontal direction The second-level temperature difference analysis unit is used to obtain the reference three-dimensional temperature data sequence I1 of the cargo hold, evenly divide the inner wall of the cargo hold of the cold chain vehicle without loading into several cargo hold space blocks in the vertical and horizontal directions, and obtain the three-dimensional position coordinates (x j , y j , z j ) of the center position of each cargo hold space block, generate a continuous temperature field inside the cargo hold through a three-dimensional difference algorithm based on the reference three-dimensional temperature data sequence to obtain the three-dimensional temperature data of each cargo hold space block, and form the first-level three-dimensional temperature data sequence I2; analyze and obtain the third temperature gradient difference in the vertical direction in the cargo hold based on the first-level three-dimensional temperature data sequence I2 and the fourth temperature gradient difference in the horizontal direction The regional temperature difference verification unit is used to extract the first temperature gradient difference, the second temperature gradient difference, the third temperature gradient difference, and the fourth temperature gradient difference to determine whether the regional temperature in the warehouse is balanced.

2. The dynamic monitoring and regulation system for cold chain transportation of in vitro diagnostic reagents according to claim 1, wherein The multi-source temperature monitoring module includes two infrared thermal imaging cameras and high-precision temperature sensors; the infrared thermal imaging cameras are installed at the diagonal positions on the top surface of the cold chain vehicle cargo hold; the high-precision temperature sensors obtain the cargo hold surface when the cold chain vehicle cargo hold is not loaded, evenly divide the opposite cargo hold surfaces into several equal segments in pairs, and install high-precision temperature sensors in each segment to obtain the reference three-dimensional temperature data sequence I1 = {T1,…,T i ,…,T N}, where T i is the i-th reference three-dimensional temperature data, and N is the total number of reference three-dimensional temperature data; based on the infrared thermal imaging cameras, the global temperature data T q (x i ,y i ,z i ) in the cargo hold is obtained; based on the high-precision temperature sensors, the reference three-dimensional temperature data in the cargo hold is obtained.

3. The dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents according to claim 1, wherein, The abnormal swallowing recognition unit draws a red channel mean change curve based on the R value of the facial color change feature, draws a brightness mean change curve based on the brightness distribution value, and calculates the facial color change rate D of adjacent frames diff (i), and calculates the mean value of the facial color change rate and the standard deviation σ Δd Determine the user's four-level swallowing recognition range as α4 is the fourth threshold adjustment factor, and based on the four-level swallowing recognition range, the user's medicine feeding flow rate is regulated to obtain the user's real-time second facial color feature value D(i): when At this time, it is in an abnormal swallowing state, and a command to reduce the medicine feeding flow rate or pause the medicine feeding is issued.

4. The dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents according to claim 1, wherein, The reference calibration unit is used to calculate the first temperature abnormal fluctuation value ΔT at the same position in the cargo hold according to the global temperature data T q (x i ,y i ,z i ) and the reference three-dimensional temperature data sequence I1 i =|T i -T q (x i ,y i ,z i )|. Compare the first temperature abnormal fluctuation value with the preset temperature abnormal fluctuation threshold. If the first temperature abnormal fluctuation value is greater than or equal to the preset temperature abnormal fluctuation threshold, the reference three-dimensional temperature data at this position needs to be adjusted; If the first temperature abnormal fluctuation value is less than the preset temperature abnormal fluctuation threshold, the reference three-dimensional temperature data at this position does not need to be adjusted.

5. The dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents according to claim 1, characterized in that, The first-level temperature difference analysis unit is based on the global temperature data T q (x i , y i , z i ) respectively obtains the temperature gradient differences in the vertical and horizontal directions inside the cargo hold, combines the global temperature data with the depth information inside the cargo hold, and obtains the first longitudinal temperature value and the first transverse temperature value Obtain the midpoint of the warehouse height, and divide the warehouse into upper and lower layers according to the midpoint of the warehouse height to calculate the first average temperature gradient difference value of the upper area of the warehouse and the first average temperature gradient difference value of the lower area of the warehouse Take the difference between them, that is, obtain the first temperature gradient difference Obtain the midpoint of the warehouse length, divide the warehouse into the front and rear parts according to the midpoint of the warehouse length, calculate the difference between the first average temperature gradient difference value of the front part of the warehouse and the first average temperature gradient difference value of the rear part of the warehouse, that is, obtain the second temperature gradient difference value 6. The dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents according to claim 1, characterized in that The secondary temperature difference analysis unit calculates the second temperature gradient differences in the vertical and horizontal directions within the cargo hold respectively based on the primary three-dimensional temperature data sequence I2 = {T1, …, T q , …, T Q}, where T q is the three-dimensional temperature data of the q-th cargo hold space block, and Q is the number of cargo hold space blocks; The second temperature gradient difference includes a second longitudinal temperature value and a second transverse temperature value 7. The dynamic monitoring and regulation system for cold chain transportation of in vitro diagnostic reagents according to claim 6, wherein, The secondary temperature difference analysis unit obtains the number of divided blocks in the vertical direction of the cargo hold for equal division, and calculates the second average temperature longitudinal gradient of the upper and lower layers respectively; the second average temperature longitudinal gradient of the upper layer of the cargo hold is Obtained by averaging the second longitudinal temperature values of each divided block in the upper layer area; the second average temperature longitudinal gradient of the lower layer of the cargo hold is Obtained by averaging the second longitudinal temperature values of each divided block in the lower layer area; Obtain the third temperature gradient difference by calculating the difference between the second average temperature longitudinal gradient in the upper layer of the cargo hold and the second average temperature longitudinal gradient in the lower layer of the cargo hold 8. The dynamic monitoring and regulation system for cold chain transportation of in vitro diagnostic reagents according to claim 6, characterized in that, The secondary temperature difference analysis unit obtains the central coordinates of adjacent segmentation blocks p and p + 1 in the x direction as x p and x p+1 for adjacent segmentation blocks on different horizontal planes in the same vertical plane, and the corresponding temperatures are T p and T p+1 , and calculates the second lateral temperature value Obtain the number of divided blocks in the horizontal direction of the warehouse for equal division, and calculate the second average horizontal temperature gradient of the upper and lower two-layer areas respectively; The second average lateral temperature gradient at the front of the cargo hold is obtained by averaging the second lateral temperature values of each segmentation block in the front area; the second average temperature lateral gradient at the rear of the cargo hold is obtained by averaging the second lateral temperature values of each segmentation block in the rear area; Obtain the fourth temperature gradient difference by calculating the difference between the second average temperature lateral gradient at the front of the cargo hold and the second average temperature lateral gradient at the rear of the cargo hold 9. The dynamic monitoring and adjustment system for cold chain transportation of in vitro diagnostic reagents according to claim 1, wherein The regional temperature difference checking unit is used to extract the first temperature gradient difference The second temperature gradient difference The third temperature gradient difference And the fourth temperature gradient difference To determine whether the temperature in the bin area is balanced. Specifically: when And The temperature in the bin area is balanced and there is no need to trigger an alarm reminder; Otherwise, the temperature in the warehouse area is uneven, and an alarm reminder needs to be triggered; among them, ΔT1 is the preset vertical direction temperature gradient threshold, and ΔT2 is the preset horizontal direction temperature gradient threshold.

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