Multi-partition cold chain fresh-keeping and internet-of-things temperature control system for fresh food transportation

Abstract

The invention provides a multi-partition cold chain preservation and Internet of Things temperature control system for fresh food transportation, and relates to the technical field of aviation logistics. According to the invention, the collection marking module, the first temperature comparison coefficient generation module, the fault partition screening module, the emergency fresh-keeping strategy making module, the second temperature comparison coefficient generation module and the dynamic adjustment module work cooperatively; more accurate temperature monitoring, faster fault response and more scientific emergency fresh-keeping strategy making can be realized; meanwhile, the system can dynamically adjust the cold air conveying amount of the adjacent subareas according to historical temperature control data and the current temperature control state, and it is ensured that the fresh-keeping effect can be rapidly and effectively recovered when a temperature control fault occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of aviation logistics, and in particular to a multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation. Background Art

[0002] Air cold chain transportation is widely used in the transportation of fresh food, medical supplies, vaccines and other commodities that require strict temperature control. These systems usually have multiple independent temperature control areas to ensure that goods with different temperature requirements can be transported at the same time, and the temperature of each area can be independently controlled; the application of the Internet of Things temperature control system enables the cold chain logistics system to achieve independent temperature control of multiple zones. This multi-zone cold chain system divides the transport compartment into multiple independent temperature control zones and sets different target temperature values ​​according to the preservation requirements of different foods, thereby improving the preservation effect of food during transportation. At the same time, the Internet of Things temperature control system can also collect temperature data in real time, analyze temperature changes, judge temperature control failures, formulate emergency preservation strategies, etc., which improves the intelligence level of the cold chain logistics system.

[0003] In the prior art, the publication number is CN115063062A, and the name is a method and system for monitoring temperature of the Internet of Things for fresh food transportation. The method includes: obtaining the configuration of the unmanned vehicle formation; if the configuration is a straight line arrangement, when the pilot vehicle is located behind the cold chain logistics vehicle, the unmanned vehicle respectively takes a first image behind the cold chain logistics vehicle through an infrared camera; the first image, wind speed information and the speed of the cold chain logistics vehicle are input into the first neural network, and the first neural network outputs the second temperature information in the cargo box of the cold chain logistics vehicle; and the second temperature information is sent to the pilot vehicle, the cold chain logistics vehicle sends the first temperature information to the pilot vehicle, and the pilot vehicle fuses the first temperature information and the second temperature information and sends it to the remote control terminal. This method solves the technical problems of low reliability of temperature control of cold chain logistics vehicles and a single temperature control method.

[0004] Although the existing multi-zone cold chain logistics system has a high level of intelligence and automation, it still has some shortcomings. First, the accuracy and response speed of existing technologies in zone temperature control are still not ideal. When a temperature control failure occurs in a certain area, the temperature of the adjacent zones cannot be adjusted quickly and effectively, resulting in the loss of the preservation effect of some foods. For example, when the temperature control equipment in a certain area fails and causes the temperature to rise, the existing system may not be able to perceive it in time and take effective measures, thus affecting the quality of food in that area.

[0005] Existing technologies have limitations in diagnosing temperature control failures and formulating emergency preservation strategies. Most existing systems can only perform simple temperature monitoring and alarms. When a failure occurs, there is a lack of effective emergency preservation strategies, and they cannot be dynamically adjusted according to the degree of the failure and the temperature status of adjacent partitions, which affects the overall stability and reliability of the cold chain system. At the same time, existing technologies are also insufficient in the collection and analysis of temperature data, and cannot fully utilize historical temperature data for prediction and decision-making, resulting in a lack of scientific basis for the formulation of emergency strategies.

[0006] The above information disclosed in the above Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0007] The object of the present invention is to provide a multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation to solve the problems raised in the above-mentioned background technology.

[0008] To achieve the above object, the present invention provides the following technical solution: a multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation, specifically comprising: Collection and marking module: used to mark the independently adjustable temperature zones of the multi-zone cold chain system, determine the fresh-keeping temperature target value of each zone using the IoT temperature control system, and record the historical temperature control equipment status data of each zone; The first temperature comparison coefficient generation module is used to extract the temperature change data of each partition when the temperature control failure occurs to different degrees according to the historical temperature control device status data, and calculate the first temperature comparison coefficient between the temperature change data corresponding to the current time and the fresh-keeping temperature target value when the temperature control failure occurs to different degrees in each partition; Fault partition screening module: used to analyze and judge the temperature control fault degree of each marked partition in real time, obtain the temperature control fault degree judgment result, and screen out the fault partition at the current time from the temperature control fault degree judgment result; Emergency preservation strategy formulation module: used to formulate a corresponding emergency preservation strategy for the faulty partition according to the output value range of the first temperature comparison coefficient of the faulty partition, and the emergency preservation strategy includes setting a cold air delivery component with adjustable cold air delivery volume in a normal partition adjacent to the faulty partition; The second temperature comparison coefficient generation module is used to collect the fresh-keeping temperature values ​​of the normal partitions adjacent to the faulty partition in real time, and calculate the second temperature comparison coefficient between the real-time fresh-keeping temperature of each partition in the normal partition and the corresponding fresh-keeping temperature target value; Dynamic adjustment module: used to analyze in combination with the first temperature comparison coefficient and the second temperature comparison coefficient to generate a fresh-keeping strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition.

[0009] Furthermore, the independently controllable temperature zones of the multi-zone cold chain system are divided and marked, and the preservation temperature target value of each zone is determined by the IoT temperature control system, and the historical temperature control equipment status data of each zone is recorded, including: All partitions are represented by a sorted set as {1, 2, ..., i, ..., n}, where i represents the index of the i-th partition and n represents the total number of partitions; Determine the fresh-keeping temperature target value for each partition and form a target value sequence ,in is the target value of the fresh-keeping temperature of the i-th partition; The historical temperature control equipment status data includes real-time recorded temperature change data and the corresponding operating status data of the temperature control equipment; the operating status data includes the on / off status, power consumption, compressor frequency, and refrigerant flow of the temperature control equipment; The temperature change data record sequence of each partition at the current time t is: ; in, is the temperature value of the i-th partition at the current time t; Record the on / off state as , which indicates the open or closed state of the temperature control device at the current time t; The power consumption is recorded as P(t), which represents the power consumption of the temperature control device at the current time t; The compressor frequency is , which represents the compressor operating frequency recorded at the current time t; The refrigerant flow rate is recorded as , which represents the refrigerant flow recorded at the current time t.

[0010] Furthermore, the historical temperature control equipment status data is extracted and standardized so that its output value is in the interval [0,1]; set up are the standardized output values ​​of the power consumption, compressor operating frequency and refrigerant flow rate of the temperature control device at the current time t, respectively; For the judgment of different degrees of temperature control failure, a standardized failure threshold set is set to represent different degrees of temperature control failure; The fault threshold set for power consumption is set to ; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when When , it indicates that the temperature control device fault level is high; The fault threshold set for setting the compressor operating frequency is ; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when When , it indicates that the temperature control device fault level is high; Set the fault threshold set of refrigerant flow to ; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when , it indicates that the temperature control device fault level is high.

[0011] Furthermore, the failure degree coefficient used to describe the temperature control failure of different degrees in the i-th partition at the current time t is recorded as ; From power consumption , compressor operating frequency and refrigerant flow Among the judgment results of the corresponding fault threshold set, the highest fault degree judgment result is selected as the fault degree of the temperature control device at the current time; When the highest fault severity is judged as a low fault, the fault severity coefficient The calculation formula is as follows: ; When the highest fault severity is judged as a medium fault, the fault severity coefficient The calculation formula is as follows: ; When the highest fault severity is judged as a high fault, the fault severity coefficient The calculation formula is as follows: ; in, are the standardized average values ​​of power consumption, compressor operating frequency, and refrigerant flow rate collected U times in the current time period Td; the current time period Td is the time period before the current time t. are the positive adjustment coefficients corresponding to the fault degree.

[0012] Furthermore, the first temperature comparison coefficient between the temperature change data corresponding to the current time t and the fresh-keeping temperature target value is calculated for each partition when temperature control failures of different degrees occur, specifically including: The first temperature comparison coefficient of the i-th partition at the current time t is recorded as , the calculation formula is as follows: ; in, The value range is [0,1]; is the actual temperature of the ith partition at the current time t; is the target value of the fresh-keeping temperature of the i-th partition; are the maximum and minimum values ​​of the temperature change in the current time period Td; is the failure degree coefficient of the i-th partition at the current time t; is the on / off status of the temperature control device at the current time t. When the temperature control device is on, ; When the temperature control device is in the off state, ; The results of judging the degree of temperature control failure are as follows: exist Under the premise of The closer it is to 0, the closer the temperature control system is to the ideal state, the closer the actual temperature is to the target value of the fresh-keeping temperature; the closer the fault level of the temperature control equipment is to no fault; exist Under the premise of The closer it is to 1, the higher the abnormality of the temperature control system, the greater the difference between the actual temperature and the target temperature, and the higher the degree of failure of the temperature control equipment.

[0013] Furthermore, the temperature control fault degree of each marked partition is analyzed and judged in real time to obtain the temperature control fault degree judgment result, and the current fault partition is screened out from the temperature control fault degree judgment result, specifically including: Based on experimental demonstration or expert group system analysis, set the first temperature comparison coefficient of the i-th partition at the current time t The screening threshold is Q1=0.53; Will comply with The partitions of the hth fault partition are taken as fault partitions to form a fault partition set {1, 2, ..., h, ..., H}, where h represents the index of the hth fault partition, H is the total number of fault partitions, and H ≤ n; and the first temperature comparison coefficient of the hth fault partition at the current time t is recorded as .

[0014] Furthermore, a corresponding emergency preservation strategy is formulated for the fault partition, including: The cold air delivery assembly includes an air guide pipe, an exhaust gas distribution flow valve, an air pump and a controller end; Determine the actual temperature value of the hth fault partition at the current time t And the preservation temperature target value The missing difference between: ; in, is the missing difference, which represents the difference between the actual temperature value and the fresh-keeping temperature target value; exist Based on the premise of the first temperature comparison coefficient of the hth fault partition The value range of , formulate the following corresponding emergency preservation strategies; 2.1) When the first temperature comparison coefficient When the value is in the range of (0,0.4), it means that the abnormality of the temperature control system is low. At this time, the emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 or h+1 adjacent to the h-th fault partition to generate the missing difference. quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; 2.2) When When the value is [0.4, 0.7], it means that the abnormality of the temperature control system is moderate. The emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 and h+1 on both sides of the hth fault partition to comprehensively generate the missing difference quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; 2.3) When When the value exceeds 0.7, it means that the temperature control system is highly abnormal. The emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 and h+1 on both sides of the h-th fault partition, as well as the normal partitions h-2 and h+2 in the adjacent interval, to comprehensively generate the missing difference. quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component.

[0015] Further, calculating the second temperature comparison coefficient between the real-time fresh-keeping temperature of each partition in the normal partition and the corresponding fresh-keeping temperature target value specifically includes: The IoT temperature control system collects the actual temperature values ​​of the normal partitions h-1 and h+1 adjacent to the fault partition h and the normal partitions h-2 and h+2 adjacent to the fault partition h in real time through sensors, and marks them in turn. ; and the actual temperature value of each normal partition is Represents, where j∈{h-1, h+1, h-2, h+2}; Calculate the real-time fresh-keeping temperature of each normal partition The corresponding preservation temperature target value The difference between , and further calculate the second temperature comparison coefficient ; The specific formula is as follows: ; ; in, is the actual temperature value of the jth normal partition at the current time t; is the target value of the fresh-keeping temperature of the jth normal partition; is the difference between the actual temperature value of the jth normal partition and the target value of the fresh-keeping temperature; is the second temperature comparison coefficient of the jth normal partition.

[0016] Furthermore, a fresh-keeping strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition specifically includes: The analysis formula for defining the fresh-keeping strategy adjustment model is as follows: ; in, is the freshness adjustment index of the h-th fault partition; is the adjustment factor used to ensure The value range is (0,1); when When the output value is in the range of (0,0.4), it means that the IoT temperature control system of the entire system is in good condition, and the temperature difference between the faulty partition and the adjacent normal partition is within 16%; the emergency preservation strategy adjustment content is: Increase the current missing difference Adjust the cold air delivery components of the normal partition h-1 or h+1 on one side adjacent to the faulty partition, and finely control the cold air delivery volume through the air duct and exhaust distribution flow valve; ; in, is the adjusted missing difference of the h-th fault partition at the current time t; when When the value is [0.4,0.7], it means that the IoT temperature control system is in a moderate degree of temperature control abnormality; the emergency preservation strategy adjustment content is: Increase the current missing difference 50% of the total volume, adjust the cold air delivery components of the normal partitions h-1 and h+1 on both sides adjacent to the faulty partition, and coordinate the cold air delivery volume through the air duct and the exhaust distribution flow valve; ; when When the value is greater than 0.7, it means that the system has a high degree of temperature control abnormality; the emergency preservation strategy adjustment content is: Increase the current missing difference 95% of the total volume, adjust the cold air delivery components of the normal partitions h-1 and h+1 on both sides of the faulty partition and the normal partitions h-2 and h+2 adjacent to each other, and coordinate the cold air delivery volume through multiple air ducts and exhaust distribution flow valves; .

[0017] Compared with the prior art, the present invention has the following beneficial effects: Through the collaborative work of the collection and marking module, the first temperature comparison coefficient generation module, the fault partition screening module, the emergency preservation strategy formulation module, the second temperature comparison coefficient generation module and the dynamic adjustment module, more accurate temperature monitoring, faster fault response and more scientific emergency preservation strategy formulation can be achieved; at the same time, the system can dynamically adjust the cold air delivery volume of adjacent partitions according to historical temperature control data and current temperature control status, ensuring that the preservation effect can be quickly and effectively restored when a temperature control failure occurs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0019] Figure 1 It is a schematic diagram of the overall system module flow of the present invention.

[0020] Figure 2 It is a schematic diagram of a cold chain box of the multi-partition cold chain system of the present invention.

[0021] Among them, 1 is the air duct; 2 is the exhaust distribution flow valve; 3 is the cold chain box partition. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example 1

[0023] See also Figure 1 and Figure 2 , the present invention provides a technical solution: A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation, specifically comprising: Collection and marking module: used to mark the independently adjustable temperature zones of the multi-zone cold chain system, determine the fresh-keeping temperature target value of each zone using the IoT temperature control system, and record the historical temperature control equipment status data of each zone; The first temperature comparison coefficient generation module is used to extract the temperature change data of each partition when the temperature control failure occurs to different degrees according to the historical temperature control device status data, and calculate the first temperature comparison coefficient between the temperature change data corresponding to the current time and the fresh-keeping temperature target value when the temperature control failure occurs to different degrees in each partition; Fault partition screening module: used to analyze and judge the temperature control fault degree of each marked partition in real time, obtain the temperature control fault degree judgment result, and screen out the fault partition at the current time from the temperature control fault degree judgment result; Emergency preservation strategy formulation module: used to formulate a corresponding emergency preservation strategy for the faulty partition according to the output value range of the first temperature comparison coefficient of the faulty partition, and the emergency preservation strategy includes setting a cold air delivery component with adjustable cold air delivery volume in a normal partition adjacent to the faulty partition; The second temperature comparison coefficient generation module is used to collect the fresh-keeping temperature values ​​of the normal partitions adjacent to the faulty partition in real time, and calculate the second temperature comparison coefficient between the real-time fresh-keeping temperature of each partition in the normal partition and the corresponding fresh-keeping temperature target value; Dynamic adjustment module: used to analyze in combination with the first temperature comparison coefficient and the second temperature comparison coefficient to generate a fresh-keeping strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition.

[0024] Further explanation: the independently controllable temperature zones of the multi-zone cold chain system are divided and marked, the IoT temperature control system is used to determine the fresh-keeping temperature target value of each zone, and the historical temperature control equipment status data of each zone is recorded, including: 1.1) Partition division and marking: Physically partition the entire air logistics cold chain system, and each partition can be independently temperature-controlled and marked; Determine the physical boundaries of each zone and use insulation to separate the zones; All partitions are represented by a sorted set as {1, 2, ..., i, ..., n}, where i represents the index of the i-th partition and n represents the total number of partitions; 1.2) Install IoT temperature control sensor: Install IoT temperature control sensors in each partition, which can monitor the temperature in real time and transmit data to the centralized control system; Select a high-precision temperature sensor to ensure that the temperature measurement error is within ±0.1°C; Each temperature control sensor is connected to the central control server through a wireless communication module; the wireless communication module can be Wi-Fi or LoRa; 1.3) Determine the target value of the preservation temperature: According to the type and storage requirements of fresh food, determine the fresh-keeping temperature target value for each partition and form a target value sequence ,in is the fresh-keeping temperature target value of the i-th partition; the temperature target value is based on scientific evidence and industry standards; In this embodiment, if the first partition 1 stores fruits, the fresh-keeping temperature target value is The second partition 2 stores frozen meat, and the target temperature for freshness preservation is 4°C. is -18℃; 1.4) Record historical temperature control equipment status data: The historical temperature control equipment status data includes real-time recorded temperature change data and the corresponding operating status data of the temperature control equipment; the operating status data includes the on / off status, power consumption, compressor frequency, and refrigerant flow of the temperature control equipment; The temperature change data record sequence of each partition at the current time t is: ; in, is the temperature value of the i-th partition at the current time t; Record the on / off state as , which indicates the open or closed state of the temperature control device at the current time t; The power consumption is recorded as P(t), which represents the power consumption of the temperature control device at the current time t; the unit is watt (W); The compressor frequency is , which represents the compressor operating frequency recorded at the current time t; the unit is Hertz (Hz); The refrigerant flow rate is recorded as , which indicates the refrigerant flow recorded at the current time t. The unit is liter / minute (L / min); 1.5) Data transmission and storage: The collected temperature change data and the operating status data of the temperature control equipment are transmitted to the cloud server through the Internet of Things for storage and processing; Use MQTT protocol for data transmission to ensure the reliability and real-time performance of data transmission; The data is stored in a cloud database for subsequent analysis and strategy formulation.

[0025] Further explanation: the historical temperature control equipment status data is extracted and standardized so that its output value is in the interval [0,1]. The purpose of the standardization process is to map the value of each parameter to the interval [0,1]. ; ; ; in, are the minimum and maximum values ​​of these parameters, respectively; set up are the standardized output values ​​of the power consumption, compressor operating frequency and refrigerant flow rate of the temperature control device at the current time t, respectively; For the judgment of different degrees of temperature control failure, a standardized failure threshold set is set to represent different degrees of temperature control failure; The fault threshold set for power consumption is set to In this embodiment, They are 0.25 and 0.53 respectively; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when When , it indicates that the temperature control device fault level is high; The fault threshold set for setting the compressor operating frequency is In this embodiment, They are 0.26 and 0.57 respectively; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when When , it indicates that the temperature control device fault level is high; Set the fault threshold set of refrigerant flow to In this embodiment, They are 0.31 and 0.61 respectively; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when , it indicates that the temperature control device fault level is high.

[0026] To further illustrate, the failure degree coefficient used to describe the temperature control failure of different degrees in the i-th partition at the current time t is recorded as ; Based on the above judgment, from the power consumption , compressor operating frequency and refrigerant flow Among the judgment results of the corresponding fault threshold set, the highest fault degree judgment result is selected as the fault degree of the temperature control device at the current time; When the highest fault severity is judged as a low fault, the fault severity coefficient The calculation formula is as follows: ; When the highest fault severity is judged as a medium fault, the fault severity coefficient The calculation formula is as follows: ; When the highest fault severity is judged as a high fault, the fault severity coefficient The calculation formula is as follows: ; in, are the standardized average values ​​of power consumption, compressor operating frequency, and refrigerant flow rate collected U times in the current time period Td; the current time period Td is the time period before the current time t. are respectively the positive adjustment coefficients of the corresponding fault levels, and the adjustment coefficients are used to avoid the situation where the numerator of the fault level coefficient is 0. And The value range is 0.1 to 0.45. In this embodiment, Td is the value within the past hour. The values ​​are 0.1, 0.2, and 0.15 respectively; Further explanation: calculating the first temperature comparison coefficient between the temperature change data corresponding to the current time t and the fresh-keeping temperature target value when temperature control failures of different degrees occur in each partition specifically includes: The first temperature comparison coefficient of the i-th partition at the current time t is recorded as , the calculation formula is as follows: ; in, The value range is [0,1]; is the actual temperature of the ith partition at the current time t; is the target value of the fresh-keeping temperature of the i-th partition; are the maximum and minimum values ​​of the temperature change in the current time period Td; is the failure degree coefficient of the i-th partition at the current time t; is the on / off status of the temperature control device at the current time t. When the temperature control device is on, ; When the temperature control device is in the off state, ; The results of judging the degree of temperature control failure are as follows: exist Under the premise of The closer it is to 0, the closer the temperature control system is to the ideal state, the closer the actual temperature is to the target value of the fresh-keeping temperature; the closer the fault level of the temperature control equipment is to no fault; exist Under the premise of The closer it is to 1, the higher the abnormality of the temperature control system, the greater the difference between the actual temperature and the target temperature, and the higher the degree of failure of the temperature control equipment.

[0027] Further explanation: the temperature control fault degree of each marked partition is analyzed and judged in real time to obtain the temperature control fault degree judgment result, and the current fault partition is screened out from the temperature control fault degree judgment result, specifically including: Based on experimental demonstration or expert group system analysis, set the first temperature comparison coefficient of the i-th partition at the current time t The screening threshold is Q1=0.53; in this embodiment, the screening threshold value range is 0.22<Q1<0.78; Will comply with The partitions of the hth fault partition are taken as fault partitions to form a fault partition set {1, 2, ..., h, ..., H}, where h represents the index of the hth fault partition, H is the total number of fault partitions, and H ≤ n; and the first temperature comparison coefficient of the hth fault partition at the current time t is recorded as .

[0028] To further explain, formulate corresponding emergency preservation strategies for fault partitions, including: The cold air delivery assembly includes an air guide pipe, an exhaust gas distribution flow valve, an air pump and a controller end; Determine the actual temperature value of the hth fault partition at the current time t And the preservation temperature target value The missing difference between: ; in, is the missing difference, which represents the difference between the actual temperature value and the fresh-keeping temperature target value; exist Based on the premise of the first temperature comparison coefficient of the hth fault partition The value range of , formulate the following corresponding emergency preservation strategies; 2.1) When the first temperature comparison coefficient When the value is in the range of (0,0.4), it means that the abnormality of the temperature control system is low. At this time, the emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 or h+1 adjacent to the h-th fault partition to generate the missing difference. quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; specifically including: The controller receives the emergency preservation strategy signal and determines that it is necessary to provide supplementary temperature for the hth fault partition; The controller starts the temperature control equipment of the adjacent normal partition h-1 or h+1 on one side, and also starts the air pump; The air pump delivers the cold air generated by the normal partition h-1 or h+1 to the exhaust distribution flow valve through the air duct; The exhaust distribution flow valve opens the air duct path to the fault partition h according to the instruction of the controller to ensure the missing difference The amount of cold air is delivered to the faulty zone h; 2.2) When When the value is [0.4, 0.7], it means that the abnormality of the temperature control system is moderate. The emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 and h+1 on both sides of the hth fault partition to comprehensively generate the missing difference quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; specifically including: The controller receives the emergency preservation strategy signal and determines that it is necessary to provide supplementary temperature for the hth fault partition; The controller starts the temperature control equipment of normal partitions h-1 and h+1 on both sides simultaneously, and starts the air pump; The air pump delivers the cold air generated by normal partitions h-1 and h+1 to the exhaust distribution flow valve through the air duct; The exhaust distribution flow valve evenly distributes the cold air flow according to the instructions of the controller, opens the air duct path to the fault partition h, and ensures the missing difference The amount of cold air is delivered to the faulty zone h; 2.3) When When the value exceeds 0.7, it means that the temperature control system is highly abnormal. The emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 and h+1 on both sides of the h-th fault partition, as well as the normal partitions h-2 and h+2 in the adjacent interval, to comprehensively generate the missing difference. quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component. Specifically including: The controller receives the emergency preservation strategy signal and determines that it is necessary to provide supplementary temperature for the hth fault partition; The controller simultaneously starts the temperature control equipment of the adjacent normal partitions h-1 and h+1, as well as the normal partitions h-2 and h+2, and starts the air pump; The air pump delivers the cold air generated by the normal partitions h-1 and h+1, and the interval normal partitions h-2 and h+2 to the exhaust distribution flow valve through the air duct; The exhaust distribution flow valve adjusts the cold air flow of each air duct according to the instructions of the controller to ensure the missing difference The cooling air is evenly delivered to the fault zone h through multiple air ducts and exhaust distribution flow valves.

[0029] To further illustrate, calculating the second temperature comparison coefficient between the real-time fresh-keeping temperature of each partition in the normal partition and the corresponding fresh-keeping temperature target value specifically includes: The IoT temperature control system collects the actual temperature values ​​of the normal partitions h-1 and h+1 adjacent to the fault partition h, and the normal partitions h-2 and h+2 adjacent to the fault partition h in real time through sensors, and marks them in turn. ; and the actual temperature value of each normal partition is Represents, where j∈{h-1, h+1, h-2, h+2}; Calculate the real-time fresh-keeping temperature of each normal partition The corresponding preservation temperature target value The difference between , and further calculate the second temperature comparison coefficient ; The specific formula is as follows: ; ;; in, is the actual temperature value of the jth normal partition at the current time t; is the target value of the fresh-keeping temperature of the jth normal partition; is the difference between the actual temperature value of the jth normal partition and the target value of the fresh-keeping temperature; is the second temperature comparison coefficient of the jth normal partition.

[0030] Further description, the fresh-keeping strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition specifically includes: The analysis formula for defining the fresh-keeping strategy adjustment model is as follows: ; in, is the freshness adjustment index of the h-th fault partition; is the adjustment factor used to ensure The value range is (0,1); Determined by the expert group through experimental data, no further elaboration is given; when When the output value is in the range of (0,0.4), it means that the IoT temperature control system of the entire system is in good condition, and the temperature difference between the faulty partition and the adjacent normal partition is within 16%; the emergency preservation strategy adjustment content is: Increase the current missing difference Adjust the cold air delivery components of the normal partition h-1 or h+1 on one side adjacent to the faulty partition, and finely control the cold air delivery volume through the air duct and exhaust distribution flow valve; ; in, is the adjusted missing difference of the h-th fault partition at the current time t; when When the value is [0.4,0.7], it means that the IoT temperature control system is in a moderate degree of temperature control abnormality; the emergency preservation strategy adjustment content is: Increase the current missing difference 50% of the total volume, adjust the cold air delivery components of the normal partitions h-1 and h+1 on both sides adjacent to the faulty partition, and coordinate the cold air delivery volume through the air duct and the exhaust distribution flow valve; ; when When the value is greater than 0.7, it means that the system has a high degree of temperature control abnormality; the emergency preservation strategy adjustment content is: Increase the current missing difference 95% of the total volume, adjust the cold air delivery components of the normal partitions h-1 and h+1 on both sides of the faulty partition and the normal partitions h-2 and h+2 adjacent to each other, and coordinate the cold air delivery volume through multiple air ducts and exhaust distribution flow valves; .

[0031] Implementation example: The actual temperature value of the hth fault partition at present The target temperature for fresh-keeping is 2°C. 5℃, missing difference is 3°C, and the first temperature comparison coefficient The value is 5; the temperature comparison coefficients of adjacent normal partitions are: ; Calculate the freshness-keeping strategy adjustment index is 6.35, and the index is adjusted according to the calculated preservation strategy ,The emergency strategy is to adjust the cold air delivery components of the normal partitions on both adjacent sides, coordinate the cold air delivery volume through the air duct and the exhaust distribution flow valve, to ensure that the cold air is evenly delivered to the faulty partition h to make up the 4.5℃ temperature loss. Example 2

[0032] The purpose of this embodiment is to verify the actual effect of the invention, that is, a multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation; the experiment selected five different types of fresh food, namely fish, meat, vegetables, fruits and dairy products, which were placed in different zones of the cold chain transport vehicle; in order to ensure the authenticity and repeatability of the experimental results, the environmental conditions in each zone were recorded and calibrated in detail before the experiment began; 1) Equipment preparation: Cold chain transport vehicle: has multiple independent partitions, each equipped with independent temperature control system and sensors; IoT temperature control system: collects temperature data of each partition in real time, and calculates temperature deviation and comparison coefficient through algorithm; Temperature sensors: distributed in each partition, used to monitor temperature in real time; Cold air delivery assembly: including air guide pipe and exhaust distribution valve, used to dynamically adjust the cold air delivery volume; 2) Experimental samples: Fish: 10 kg, target preservation temperature is 0°C; Meat: 10 kg, target fresh-keeping temperature is 2°C; Green vegetables: 10 kg, target preservation temperature is 4°C; Fruit: 10 kg, target preservation temperature is 5°C; Dairy products: 10 kg, target fresh-keeping temperature is 3°C; 3) Experimental time and environmental conditions: Experimental time: 24 hours; Ambient temperature: 20℃; The initial temperature of the internal partition of the cold chain transport vehicle is set as the target preservation temperature; At the beginning of the experiment, the cold chain transport vehicle set the temperature of each zone as its own target preservation temperature; the IoT temperature control system began to collect temperature data of each zone in real time and recorded it once every hour; At the 6th hour, a simulated failure occurred, and the temperature control system of the first zone where the fish were located failed, causing the temperature to rise to 4°C. At this time, the IoT temperature control system detected the temperature deviation and began to make adjustments. The specific adjustment process is as follows: Real-time collection of temperature data of faulty partitions and adjacent partitions: Collect the temperature of the fault zone (fish zone, zone 1) ; Collect the temperature of adjacent partitions (meat partition, partition 2) and (vegetable partition, partition 3) and ; Calculate the first temperature comparison coefficient : Target fresh-keeping temperature = 0℃; Actual temperature = 4°C; Maximum and minimum temperature changes = 5°C, = -5℃; Failure severity coefficient = 0.5; The first temperature comparison coefficient of the first zone Calculation formula: ; in, ,but: ; Calculate the second temperature comparison coefficient : Target fresh-keeping temperature = 2℃, actual temperature = 3.5℃; , ; Target fresh-keeping temperature = 4℃, actual temperature = 4.5℃; , ; Calculate the freshness-keeping strategy adjustment index : Adjustment factor ; ; Analysis formula: ; Implement dynamic adjustments: Due to the freshness-keeping strategy adjustment index =0.67, in the interval (4, 7); According to the setting, increase the current missing difference 50% of the total, adjust the air conditioning delivery volume; After adjustment ; In the next 24 hours, the IoT temperature control system continued to monitor the temperature of each partition in real time and made dynamic adjustments based on the situation of the faulty partition; the recorded data is shown in Table 1 below:

[0033] Data Analysis and Conclusion: It can be seen from the data table that after the failure occurred in the 6th hour, the invented multi-zone cold chain preservation and Internet of Things temperature control system was used to dynamically adjust the faulty zone, and eventually the temperature of the faulty zone gradually recovered to the target preservation temperature and was fully recovered within 24 hours; this shows that the invented system can effectively monitor and adjust the temperature of each zone to ensure the preservation of fresh food.

[0034] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0035] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0036] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0037] The above embodiments are only used to help understand the method and core idea of ​​the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation, characterized in that: Specifically include: Collection and marking module: used to mark the independently adjustable temperature zones of the multi-zone cold chain system, determine the fresh-keeping temperature target value of each zone using the IoT temperature control system, and record the historical temperature control equipment status data of each zone; The first temperature comparison coefficient generation module is used to extract the temperature change data of each partition when the temperature control failure occurs to different degrees according to the historical temperature control device status data, and calculate the first temperature comparison coefficient between the temperature change data corresponding to the current time and the fresh-keeping temperature target value when the temperature control failure occurs to different degrees in each partition; Fault partition screening module: used to analyze and judge the temperature control fault degree of each marked partition in real time, obtain the temperature control fault degree judgment result, and screen out the fault partition at the current time from the temperature control fault degree judgment result; Emergency preservation strategy formulation module: used to formulate a corresponding emergency preservation strategy for the faulty partition according to the output value range of the first temperature comparison coefficient of the faulty partition, and the emergency preservation strategy includes setting a cold air delivery component with adjustable cold air delivery volume in a normal partition adjacent to the faulty partition; The second temperature comparison coefficient generation module is used to collect the fresh-keeping temperature values ​​of the normal partitions adjacent to the faulty partition in real time, and calculate the second temperature comparison coefficient between the real-time fresh-keeping temperature of each partition in the normal partition and the corresponding fresh-keeping temperature target value; Dynamic adjustment module: used to analyze in combination with the first temperature comparison coefficient and the second temperature comparison coefficient to generate a fresh-keeping strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition.

2. According to claim 1, a multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation is characterized in that: The independently controllable temperature zones of the multi-zone cold chain system are divided and marked, and the preservation temperature target value of each zone is determined by the IoT temperature control system, and the historical temperature control equipment status data of each zone is recorded, including: All partitions are represented by a sorted set as {1, 2, ..., i, ..., n}, where i represents the index of the i-th partition and n represents the total number of partitions; Determine the fresh-keeping temperature target value for each partition and form a target value sequence ,in is the target value of the fresh-keeping temperature of the i-th partition; The historical temperature control equipment status data includes real-time recorded temperature change data and the corresponding operating status data of the temperature control equipment; the operating status data includes the on / off status, power consumption, compressor frequency, and refrigerant flow of the temperature control equipment; The temperature change data record sequence of each partition at the current time t is: ; in, is the temperature value of the i-th partition at the current time t; Record the on / off state as , which indicates the open or closed state of the temperature control device at the current time t; The power consumption is recorded as P(t), which represents the power consumption of the temperature control device at the current time t; The compressor frequency is , which represents the compressor operating frequency recorded at the current time t; The refrigerant flow rate is recorded as , which represents the refrigerant flow recorded at the current time t.

3. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 2, characterized in that: Extract and standardize the historical temperature control equipment status data so that its output value is in the range of [0,1]; set up are the standardized output values ​​of the power consumption, compressor operating frequency and refrigerant flow rate of the temperature control device at the current time t, respectively; For the judgment of different degrees of temperature control failure, a standardized failure threshold set is set to represent different degrees of temperature control failure; The fault threshold set for power consumption is set to ; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when When , it indicates that the temperature control device fault level is high; The fault threshold set for setting the compressor operating frequency is ; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when When , it indicates that the temperature control device fault level is high; Set the fault threshold set of refrigerant flow to ; when When , it means that the temperature control equipment has a low level of fault or no fault; when When , it indicates that the temperature control device fault level is medium fault; when , it indicates that the temperature control device fault level is high.

4. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 3, characterized in that: The failure degree coefficient used to describe the temperature control failure of different degrees in the i-th partition at the current time t is recorded as ; From power consumption , compressor operating frequency and refrigerant flow Among the judgment results of the corresponding fault threshold set, the highest fault degree judgment result is selected as the fault degree of the temperature control device at the current time; When the highest fault severity is judged as a low fault, the fault severity coefficient The calculation formula is as follows: ； When the highest fault severity is judged as a medium fault, the fault severity coefficient The calculation formula is as follows: ； When the highest fault severity is judged as a high fault, the fault severity coefficient The calculation formula is as follows: ； in, are the standardized average values ​​of power consumption, compressor operating frequency, and refrigerant flow rate collected U times in the current time period Td; the current time period Td is the previous time period including the current time t, are the positive adjustment coefficients corresponding to the fault degree.

5. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 4, characterized in that: Calculate the first temperature comparison coefficient between the temperature change data corresponding to the current time t and the fresh-keeping temperature target value for each partition when different degrees of temperature control failure occur, specifically including: The first temperature comparison coefficient of the i-th partition at the current time t is recorded as , the calculation formula is as follows: ； in, The value range is [0,1]; is the actual temperature of the ith partition at the current time t; is the target value of the fresh-keeping temperature of the i-th partition; are the maximum and minimum values ​​of the temperature change in the current time period Td; is the failure degree coefficient of the i-th partition at the current time t; is the on / off status of the temperature control device at the current time t. When the temperature control device is on, ; When the temperature control device is in the off state, ; The results of judging the degree of temperature control failure are as follows: exist Under the premise of The closer it is to 0, the closer the temperature control system is to the ideal state, the closer the actual temperature is to the target value of the fresh-keeping temperature; the closer the fault level of the temperature control equipment is to no fault; exist Under the premise of The closer it is to 1, the higher the abnormality of the temperature control system, the greater the difference between the actual temperature and the target temperature, and the higher the degree of failure of the temperature control equipment.

6. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 5, characterized in that: Analyze and judge the temperature control fault degree of each marked partition in real time, obtain the temperature control fault degree judgment result, and filter out the current fault partition from the temperature control fault degree judgment result, including: Based on experimental demonstration or expert group system analysis, set the first temperature comparison coefficient of the i-th partition at the current time t The screening threshold is Q1=0.53; Will comply with The partitions of the hth fault partition are taken as fault partitions to form a fault partition set {1, 2, ..., h, ..., H}, where h represents the index of the hth fault partition, H is the total number of fault partitions, and H ≤ n; and the first temperature comparison coefficient of the hth fault partition at the current time t is recorded as .

7. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 6, characterized in that: Develop corresponding emergency preservation strategies for fault zones, including: The cold air delivery assembly includes an air guide pipe, an exhaust gas distribution flow valve, an air pump and a controller end; Determine the actual temperature value of the hth fault partition at the current time t And the preservation temperature target value The missing difference between: ； in, is the missing difference, which represents the difference between the actual temperature value and the fresh-keeping temperature target value; exist Based on the premise of the first temperature comparison coefficient of the hth fault partition The value range of , formulate the following corresponding emergency preservation strategies; 2.1) When the first temperature comparison coefficient When the value is in the range of (0,0.4), it means that the abnormality of the temperature control system is low. At this time, the emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 or h+1 adjacent to the h-th fault partition to generate the missing difference. quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; 2.2) When When the value is [0.4, 0.7], it means that the abnormality of the temperature control system is moderate. The emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 and h+1 on both sides of the hth fault partition to comprehensively generate the missing difference quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; 2.3) When When the value exceeds 0.7, it means that the temperature control system is highly abnormal. The emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partitions h-1 and h+1 on both sides of the h-th fault partition, as well as the normal partitions h-2 and h+2 in the adjacent interval, to comprehensively generate the missing difference. quantity of supplementary temperature; The supplementary temperature is delivered to the hth fault zone through the cold air delivery component.

8. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 7, characterized in that: Calculating the second temperature comparison coefficient between the real-time fresh-keeping temperature of each partition in the normal partition and the corresponding fresh-keeping temperature target value specifically includes: The IoT temperature control system collects the actual temperature values ​​of the normal partitions h-1 and h+1 adjacent to the fault partition h and the normal partitions h-2 and h+2 adjacent to the fault partition h in real time through sensors, and marks them in turn. ; and the actual temperature value of each normal partition is Represents, where j∈{h-1, h+1, h-2, h+2}; Calculate the real-time fresh-keeping temperature of each normal partition The corresponding preservation temperature target value The difference between , and further calculate the second temperature comparison coefficient ; The specific formula is as follows: ； ； in, is the actual temperature value of the jth normal partition at the current time t; is the target value of the fresh-keeping temperature of the jth normal partition; is the difference between the actual temperature value of the jth normal partition and the target value of the fresh-keeping temperature; is the second temperature comparison coefficient of the jth normal partition.

9. A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 8, characterized in that: A fresh-keeping strategy adjustment model for dynamically adjusting the cold air delivery components of normal partitions adjacent to the faulty partition specifically includes: The analysis formula for defining the fresh-keeping strategy adjustment model is as follows: ； in, is the freshness adjustment index of the h-th fault partition; is the adjustment factor used to ensure The value range is (0,1); when When the output value is in the range of (0,0.4), it means that the IoT temperature control system of the entire system is in good condition, and the temperature difference between the faulty partition and the adjacent normal partition is within 16%; the emergency preservation strategy adjustment content is: Increase the current missing difference Adjust the cold air delivery components of the normal partition h-1 or h+1 on one side adjacent to the faulty partition, and finely control the cold air delivery volume through the air duct and exhaust distribution flow valve; ； in, is the adjusted missing difference of the h-th fault partition at the current time t; when When the value is [0.4,0.7], it means that the IoT temperature control system is in a moderate degree of temperature control abnormality; the emergency preservation strategy adjustment content is: Increase the current missing difference 50% of the total volume, adjust the cold air delivery components of the normal partitions h-1 and h+1 on both sides adjacent to the faulty partition, and coordinate the cold air delivery volume through the air duct and the exhaust distribution flow valve; ； when When the value is greater than 0.7, it means that the system has a high degree of temperature control abnormality; the emergency preservation strategy adjustment content is: Increase the current missing difference 95% of the total volume, adjust the cold air delivery components of the normal partitions h-1 and h+1 on both sides of the faulty partition and the normal partitions h-2 and h+2 adjacent to each other, and coordinate the cold air delivery volume through multiple air ducts and exhaust distribution flow valves; 。

Images