Multi-zone cold chain preservation and IoT temperature control system for fresh food transportation

Abstract

The present invention provides a multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation, which relates to the field of aviation logistics technology. The present invention can achieve more accurate temperature monitoring, faster fault response and more scientific emergency preservation strategy formulation through the coordinated work of a collection and marking module, a first temperature comparison coefficient generation module, a fault zone screening module, an emergency preservation strategy formulation module, a second temperature comparison coefficient generation module and a dynamic adjustment module; at the same time, the system can dynamically adjust the cold air delivery volume of adjacent zones according to historical temperature control data and the current temperature control status, ensuring that the preservation effect can be quickly and effectively restored when a temperature control failure occurs.

Description

Technical Field

[0001] The present invention relates to the field of aviation logistics technology, 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 for the transport of fresh food, medical supplies, vaccines, and other commodities requiring strict temperature control. These systems typically feature multiple independent temperature-controlled zones to ensure that goods with varying temperature requirements can be transported simultaneously, and the temperature in each zone can be independently controlled. The application of IoT temperature control systems enables cold chain logistics systems to independently control the temperature of multiple zones. This multi-zone cold chain system divides the transport vehicle into multiple independent temperature-controlled zones, setting different target temperatures based on the preservation requirements of different foods, thereby improving food preservation during transportation. Furthermore, IoT temperature control systems can also collect temperature data in real time, analyze temperature changes, identify temperature control failures, and develop emergency preservation strategies, thereby enhancing the intelligence of cold chain logistics systems.

[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 vehicles respectively use infrared cameras to capture a first image of the rear of the cold chain logistics vehicle; 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 existing multi-zone cold chain logistics systems have a high level of intelligence and automation, they still have 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 one zone, the temperature of adjacent zones cannot be adjusted quickly and effectively, resulting in the loss of freshness of some foods. For example, if the temperature control equipment in a certain area fails and the temperature rises, the existing system may not be able to detect 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 developing emergency preservation strategies. Most existing systems are limited to simple temperature monitoring and alarming. When a failure occurs, they lack effective emergency preservation strategies and are unable to dynamically adjust based on the severity of the failure and the temperature status of adjacent zones, compromising the overall stability and reliability of the cold chain system. Furthermore, existing technologies also have shortcomings in the collection and analysis of temperature data, failing to fully utilize historical temperature data for prediction and decision-making, resulting in a lack of scientific basis for developing emergency strategies.

[0006] The above information disclosed in this 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 a person 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 background technology.

[0008] To achieve the above objectives, 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:

[0009] Collection and marking module: used to mark the independently adjustable temperature zones of the multi-zone cold chain system, use the IoT temperature control system to determine the preservation temperature target value of each zone, and record the historical temperature control equipment status data of each zone;

[0010] A first temperature comparison coefficient generation module is used to extract temperature change data of each partition when temperature control failures of varying degrees occur based on historical temperature control device status data, and calculate a first temperature comparison coefficient between the temperature change data corresponding to the current time and the fresh-keeping temperature target value for each partition when temperature control failures of varying degrees occur;

[0011] 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 filter out the faulty partition at the current time from the temperature control fault degree judgment result;

[0012] Emergency fresh-keeping strategy formulation module: used to formulate a corresponding emergency fresh-keeping strategy for the faulty zone based on the output value range of the first temperature comparison coefficient of the faulty zone, the emergency fresh-keeping strategy including setting a cold air delivery component with adjustable cold air delivery volume in the normal zone adjacent to the faulty zone;

[0013] Second temperature comparison coefficient generation module: used to collect the fresh-keeping temperature values of 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;

[0014] Dynamic adjustment module: used to analyze the first temperature comparison coefficient and the second temperature comparison coefficient to generate a freshness preservation strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition.

[0015] Furthermore, the independently controllable temperature zones of the multi-zone cold chain system are divided and marked, and the target temperature for each zone is determined using the IoT temperature control system. The historical temperature control equipment status data for each zone is also recorded, including:

[0016] 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;

[0017] Determine the target value of the fresh-keeping temperature for each partition and form a target value sequence ,in is the target value of the fresh-keeping temperature of the i-th partition;

[0018] Historical temperature control device status data includes real-time temperature change data and corresponding operating status data of the temperature control device; operating status data includes the on / off status of the temperature control device, power consumption, compressor frequency, and refrigerant flow rate;

[0019] The temperature change data record sequence of each partition at the current time t is:

[0020] ;

[0021] in, is the temperature value of the i-th partition at the current time t;

[0022] Record the on / off state as , which represents the open or closed state of the temperature control device at the current time t;

[0023] The power consumption is recorded as P(t), which represents the power consumption of the temperature control device at the current time t;

[0024] The compressor frequency is recorded as , which represents the compressor operating frequency recorded at the current time t;

[0025] The refrigerant flow rate is recorded as , which represents the refrigerant flow recorded at the current time t.

[0026] Furthermore, historical temperature control equipment status data is extracted and standardized so that its output value is in the range of [0,1];

[0027] set up are the standardized output values of the power consumption, compressor operating frequency, and refrigerant flow of the temperature control device at the current time t;

[0028] For the judgment of different degrees of temperature control failure, a standardized fault threshold set is set to represent different degrees of temperature control failure;

[0029] Set the fault threshold set of power consumption to ;

[0030] when When , it means the temperature control device has a low level of fault or no fault;

[0031] when When , it means the temperature control device fault level is medium fault;

[0032] when When , it means the temperature control device fault level is high;

[0033] Set the fault threshold set of the compressor operating frequency to ;

[0034] when When , it means the temperature control device has a low level of fault or no fault;

[0035] when When , it means the temperature control device fault level is medium fault;

[0036] when When , it means the temperature control device fault level is high;

[0037] Set the refrigerant flow fault threshold set to ;

[0038] when When , it means the temperature control device has a low level of fault or no fault;

[0039] when When , it means the temperature control device fault level is medium fault;

[0040] when When , it indicates that the temperature control device fault level is high.

[0041] 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 ;

[0042] 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;

[0043] When the highest fault severity is judged as a low fault, the fault severity coefficient The calculation formula is as follows:

[0044] ;

[0045] When the highest fault severity is judged as a medium fault, the fault severity coefficient The calculation formula is as follows:

[0046] ;

[0047] When the highest fault severity is judged as a high fault, the fault severity coefficient The calculation formula is as follows:

[0048] ;

[0049] 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 of the corresponding fault levels.

[0050] 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 varying degrees occur, specifically including:

[0051] The first temperature comparison coefficient of the i-th partition at the current time t is recorded as , the calculation formula is as follows:

[0052] ;

[0053] in, The value range is [0,1]; is the actual temperature of the i-th 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;

[0054] 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 closed, The results of temperature control fault degree judgment are as follows:

[0055] 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 temperature control equipment failure is to no fault;

[0056] 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.

[0057] Furthermore, the temperature control fault degree of each marked partition is analyzed and determined in real time to obtain a temperature control fault degree determination result, and the current faulty partition is screened out from the temperature control fault degree determination result, specifically including:

[0058] 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;

[0059] will comply with The partitions 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 .

[0060] Furthermore, a corresponding emergency preservation strategy is formulated for the fault zone, including:

[0061] The cold air delivery assembly includes an air guide pipe, an exhaust distribution flow valve, an air pump and a controller end;

[0062] Determine the actual temperature value of the hth fault partition at the current time t and the target value of fresh-keeping temperature The missing difference between:

[0063] ;

[0064] in, is the missing difference, which represents the difference between the actual temperature value and the target value of the fresh-keeping temperature;

[0065] exist Under the premise of The value range of , formulate the following corresponding emergency preservation strategy;

[0066] 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. The emergency strategy is:

[0067] The IoT temperature control system controls the temperature control devices in the normal partition h-1 or h+1 adjacent to the h-th fault partition to generate the missing difference. quantity of supplementary temperature;

[0068] The supplementary temperature is delivered to the hth fault zone through the cold air delivery component;

[0069] 2.2) When When the value is between [0.4, 0.7], it means that the temperature control system is moderately abnormal. The emergency strategy is:

[0070] 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 to comprehensively generate the missing difference. quantity of supplementary temperature;

[0071] The supplementary temperature is delivered to the hth fault zone through the cold air delivery component;

[0072] 2.3) When When the value exceeds 0.7, it indicates that the temperature control system is highly abnormal. The emergency response strategy is:

[0073] 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;

[0074] The supplementary temperature is delivered to the hth fault zone through the cold air delivery component.

[0075] Furthermore, calculating a 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:

[0076] 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};

[0077] Calculate the real-time fresh-keeping temperature of each normal partition The corresponding fresh-keeping temperature target value The difference between , and further calculate the second temperature comparison coefficient The specific formula is as follows:

[0078] ;

[0079] ;

[0080] 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 temperature value of the fresh-keeping temperature; is the second temperature comparison coefficient of the jth normal partition.

[0081] Furthermore, a freshness preservation strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition specifically includes:

[0082] The analysis formula for defining the freshness preservation strategy adjustment model is as follows:

[0083] ;

[0084] in, is the freshness policy adjustment index of the h-th fault partition; is the adjustment factor to ensure The value range is (0,1);

[0085] when When the output value is in the range of (0, 0.4), it indicates that the IoT temperature control system of the entire system is in good condition, and the temperature difference between the faulty zone and the adjacent normal zone is within 16%. The emergency preservation strategy adjustment content is:

[0086] Increase the current missing difference Adjust the cooling air delivery components of the normal partition h-1 or h+1 on one side adjacent to the faulty partition, and finely control the cooling air delivery volume through the air duct and exhaust distribution flow valve;

[0087] ;

[0088] in, is the adjusted missing value of the h-th fault partition at the current time t;

[0089] when When the value is between [0.4, 0.7], it means that the IoT temperature control system is experiencing a moderate temperature control anomaly; the emergency preservation strategy adjustment content is:

[0090] Increase the current missing difference Adjust the cooling air delivery components of the normal partitions h-1 and h+1 on both sides of the faulty partition, and coordinate the cooling air delivery volume through the air duct and exhaust distribution flow valve;

[0091] ;

[0092] when When the value is greater than 0.7, it indicates that the system has a high degree of temperature control anomaly; the emergency preservation strategy adjustment content is as follows:

[0093] Increase the current missing difference 95% of the total cooling capacity is achieved by adjusting the cooling 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 coordinating the cooling air delivery volume through multiple air ducts and exhaust distribution flow valves;

[0094] .

[0095] Compared with the prior art, the present invention has the following beneficial effects:

[0096] 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 based on 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

[0097] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0098] Figure 1 It is a schematic diagram of the overall system module flow of the present invention.

[0099] Figure 2 Schematic diagram of the cold chain box of the multi-partition cold chain system of the present invention.

[0100] Among them, 1 is the air duct; 2 is the exhaust distribution flow valve; 3 is the cold chain box partition. DETAILED DESCRIPTION

[0101] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0102] Example 1

[0103] See also Figure 1 and Figure 2 , the present invention provides a technical solution:

[0104] A multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation, specifically comprising:

[0105] Collection and marking module: used to mark the independently adjustable temperature zones of the multi-zone cold chain system, use the IoT temperature control system to determine the preservation temperature target value of each zone, and record the historical temperature control equipment status data of each zone;

[0106] A first temperature comparison coefficient generation module is used to extract temperature change data of each partition when temperature control failures of varying degrees occur based on historical temperature control device status data, and calculate a first temperature comparison coefficient between the temperature change data corresponding to the current time and the fresh-keeping temperature target value for each partition when temperature control failures of varying degrees occur;

[0107] 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 filter out the faulty partition at the current time from the temperature control fault degree judgment result;

[0108] Emergency fresh-keeping strategy formulation module: used to formulate a corresponding emergency fresh-keeping strategy for the faulty zone based on the output value range of the first temperature comparison coefficient of the faulty zone, the emergency fresh-keeping strategy including setting a cold air delivery component with adjustable cold air delivery volume in the normal zone adjacent to the faulty zone;

[0109] Second temperature comparison coefficient generation module: used to collect the fresh-keeping temperature values of 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;

[0110] Dynamic adjustment module: used to analyze the first temperature comparison coefficient and the second temperature comparison coefficient to generate a freshness preservation strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition.

[0111] Further explanation: The independently controllable temperature zones of the multi-zone cold chain system are divided and marked, and the target temperature 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:

[0112] 1.1) Partition division and marking:

[0113] Physically partition the entire cold chain system of aviation logistics, and each partition can be independently temperature-controlled and marked;

[0114] Determine the physical boundaries of each zone and use insulation to separate the zones;

[0115] 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;

[0116] 1.2) Install IoT temperature control sensor:

[0117] Install IoT temperature control sensors in each partition, which can monitor the temperature in real time and transmit data to the centralized control system;

[0118] Select a high-precision temperature sensor to ensure that the temperature measurement error is within ±0.1°C;

[0119] 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;

[0120] 1.3) Determine the target value of the preservation temperature:

[0121] According to the type and storage requirements of fresh food, determine the target value of the fresh-keeping temperature for each partition and form a target value sequence ,in is the target temperature for freshness preservation of the i-th partition; the target temperature is based on scientific evidence and industry standards;

[0122] In this embodiment, if the first partition 1 stores fruits, the target value of the fresh-keeping temperature is The second partition 2 stores frozen meat, and the target temperature for freshness is 4°C. -18℃;

[0123] 1.4) Record historical temperature control equipment status data:

[0124] Historical temperature control device status data includes real-time temperature change data and corresponding operating status data of the temperature control device; operating status data includes the on / off status of the temperature control device, power consumption, compressor frequency, and refrigerant flow rate;

[0125] The temperature change data record sequence of each partition at the current time t is:

[0126] ;

[0127] in, is the temperature value of the i-th partition at the current time t;

[0128] Record the on / off state as , which represents the open or closed state of the temperature control device at the current time t;

[0129] 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);

[0130] The compressor frequency is recorded as , which represents the compressor operating frequency recorded at the current time t; the unit is Hertz (Hz);

[0131] The refrigerant flow rate is recorded as , which represents the refrigerant flow recorded at the current time t. The unit is liters per minute (L / min);

[0132] 1.5) Data Transmission and Storage:

[0133] 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;

[0134] Use MQTT protocol for data transmission to ensure the reliability and real-time performance of data transmission;

[0135] The data is stored in a cloud database for subsequent analysis and strategy formulation.

[0136] Further explanation: the historical temperature control device 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].

[0137] ;

[0138] ;

[0139] ;

[0140] in, are the minimum and maximum values of these parameters, respectively;

[0141] set up are the standardized output values of the power consumption, compressor operating frequency, and refrigerant flow of the temperature control device at the current time t;

[0142] For the judgment of different degrees of temperature control failure, a standardized fault threshold set is set to represent different degrees of temperature control failure;

[0143] Set the fault threshold set of power consumption to In this embodiment, 0.25 and 0.53 respectively;

[0144] when When , it means the temperature control device has a low level of fault or no fault;

[0145] when When , it means the temperature control device fault is medium fault;

[0146] when When , it means the temperature control device fault level is high;

[0147] Set the fault threshold set of the compressor operating frequency to In this embodiment, 0.26 and 0.57 respectively;

[0148] when When , it means the temperature control device has a low level of fault or no fault;

[0149] when When , it means the temperature control device fault is medium fault;

[0150] when When , it means the temperature control device fault level is high;

[0151] Set the refrigerant flow fault threshold set to In this embodiment, 0.31 and 0.61 respectively;

[0152] when When , it means the temperature control device has a low level of fault or no fault;

[0153] when When , it means the temperature control device fault is medium fault;

[0154] when When , it indicates that the temperature control device fault level is high.

[0155] 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 ;

[0156] 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;

[0157] When the highest fault severity is judged as a low fault, the fault severity coefficient The calculation formula is as follows:

[0158] ;

[0159] When the highest fault severity is judged as a medium fault, the fault severity coefficient The calculation formula is as follows:

[0160] ;

[0161] When the highest fault severity is judged as a high fault, the fault severity coefficient The calculation formula is as follows:

[0162] ;

[0163] 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 degree, and the adjustment coefficients are used to avoid the situation where the numerator of the fault degree coefficient is 0. 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;

[0164] To further illustrate, the calculation of 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 a temperature control failure of varying degrees occurs specifically includes:

[0165] The first temperature comparison coefficient of the i-th partition at the current time t is recorded as , the calculation formula is as follows:

[0166] ;

[0167] in, The value range is [0,1]; is the actual temperature of the i-th 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;

[0168] 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 closed, The results of temperature control fault degree judgment are as follows:

[0169] 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 temperature control equipment failure is to no fault;

[0170] 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.

[0171] To further illustrate, the temperature control fault degree of each marked partition is analyzed and determined in real time to obtain a temperature control fault degree determination result, and the current faulty partition is screened out from the temperature control fault degree determination result, specifically including:

[0172] 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;

[0173] will comply with The partitions 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 .

[0174] Further explanation: formulate corresponding emergency preservation strategies for fault zones, including:

[0175] The cold air delivery assembly includes an air guide pipe, an exhaust distribution flow valve, an air pump and a controller end;

[0176] Determine the actual temperature value of the hth fault partition at the current time t and the target value of fresh-keeping temperature The missing difference between:

[0177] ;

[0178] in, is the missing difference, which represents the difference between the actual temperature value and the target value of the fresh-keeping temperature;

[0179] exist Under the premise of The value range of , formulate the following corresponding emergency preservation strategy;

[0180] 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. The emergency strategy is:

[0181] The IoT temperature control system controls the temperature control devices in the normal partition h-1 or h+1 adjacent to the h-th fault partition to generate the missing difference. quantity of supplementary temperature;

[0182] The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; specifically including:

[0183] The controller receives the emergency preservation strategy signal and determines that it is necessary to provide supplementary temperature for the hth fault partition;

[0184] The controller starts the temperature control device of the adjacent normal partition h-1 or h+1, and also starts the air pump;

[0185] 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;

[0186] The exhaust distribution flow valve opens the air duct path to the fault zone h according to the instruction of the controller to ensure the missing difference The cooling air volume is delivered to the fault zone h;

[0187] 2.2) When When the value is between [0.4, 0.7], it means that the temperature control system is moderately abnormal. The emergency strategy is:

[0188] 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 to comprehensively generate the missing difference. quantity of supplementary temperature;

[0189] The supplementary temperature is delivered to the hth fault zone through the cold air delivery component; specifically including:

[0190] The controller receives the emergency preservation strategy signal and determines that it is necessary to provide supplementary temperature for the hth fault partition;

[0191] The controller simultaneously starts the temperature control devices of the normal partitions h-1 and h+1 on both sides of the adjacent area, and starts the air pump;

[0192] 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;

[0193] The exhaust distribution flow valve evenly distributes the cold air flow according to the instructions of the controller end, opens the air duct path to the fault zone h, and ensures the missing difference The cooling air volume is delivered to the fault zone h;

[0194] 2.3) When When the value exceeds 0.7, it indicates that the temperature control system is highly abnormal. The emergency response strategy is:

[0195] 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;

[0196] The supplementary temperature is delivered to the hth fault zone through the cold air delivery component. Specifically including:

[0197] The controller receives the emergency preservation strategy signal and determines that it is necessary to provide supplementary temperature for the hth fault partition;

[0198] The controller simultaneously starts the temperature control devices of the adjacent normal partitions h-1 and h+1, as well as the separated normal partitions h-2 and h+2, and starts the air pump;

[0199] 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;

[0200] 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.

[0201] 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:

[0202] 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};

[0203] Calculate the real-time fresh-keeping temperature of each normal partition The corresponding fresh-keeping temperature target value The difference between , and further calculate the second temperature comparison coefficient The specific formula is as follows:

[0204] ;

[0205] ;;

[0206] 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 temperature value of the fresh-keeping temperature; is the second temperature comparison coefficient of the jth normal partition.

[0207] Further description, the freshness preservation strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition specifically includes:

[0208] The analysis formula for defining the freshness preservation strategy adjustment model is as follows:

[0209] ;

[0210] in, is the freshness policy adjustment index of the h-th fault partition; is the adjustment factor to ensure The value range is (0,1); Determined by the expert group through experimental data, no further details will be given;

[0211] when When the output value is in the range of (0, 0.4), it indicates that the IoT temperature control system of the entire system is in good condition, and the temperature difference between the faulty zone and the adjacent normal zone is within 16%. The emergency preservation strategy adjustment content is:

[0212] Increase the current missing difference Adjust the cooling air delivery components of the normal partition h-1 or h+1 on one side adjacent to the faulty partition, and finely control the cooling air delivery volume through the air duct and exhaust distribution flow valve;

[0213] ;

[0214] in, is the adjusted missing value of the h-th fault partition at the current time t;

[0215] when When the value is between [0.4, 0.7], it means that the IoT temperature control system is experiencing a moderate temperature control anomaly; the emergency preservation strategy adjustment content is:

[0216] Increase the current missing difference Adjust the cooling air delivery components of the normal partitions h-1 and h+1 on both sides of the faulty partition, and coordinate the cooling air delivery volume through the air duct and exhaust distribution flow valve;

[0217] ;

[0218] when When the value is greater than 0.7, it indicates that the system has a high degree of temperature control anomaly; the emergency preservation strategy adjustment content is as follows:

[0219] Increase the current missing difference 95% of the total cooling capacity is achieved by adjusting the cooling 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 coordinating the cooling air delivery volume through multiple air ducts and exhaust distribution flow valves;

[0220] .

[0221] Implementation example:

[0222] The actual temperature value of the hth fault partition at present The target temperature for freshness preservation is 2℃ 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:

[0223] ;

[0224] Calculate the freshness preservation strategy adjustment index The index is 6.35, adjusted according to the calculated preservation strategy ,The emergency strategy is to adjust the air ,delivery components of the normal partitions on both adjacent sides, ,and coordinate the air delivery volume through the air duct and the exhaust distribution flow valve to ensure ,that the air is evenly delivered to the faulty partition h to ,make up for the 4.5℃ temperature loss.

[0225] Example 2

[0226] The purpose of this example is to verify the effectiveness of the invention, namely, a multi-zone cold chain preservation and IoT temperature control system for fresh food transportation. Five different fresh food categories were selected for the experiment: fish, meat, vegetables, fruit, and dairy products. These were placed in different zones of a cold chain transport vehicle. To ensure the authenticity and repeatability of the experimental results, the environmental conditions in each zone were carefully recorded and calibrated before the experiment began.

[0227] 1) Equipment preparation:

[0228] Cold chain transport vehicle: has multiple independent partitions, each equipped with independent temperature control system and sensors;

[0229] IoT temperature control system: collects temperature data of each partition in real time and calculates temperature deviation and comparison coefficient through algorithms;

[0230] Temperature sensors: distributed in each partition, used for real-time temperature monitoring;

[0231] Cold air delivery assembly: including air guide pipe and exhaust distribution valve, used to dynamically adjust the cold air delivery volume;

[0232] 2) Experimental samples:

[0233] Fish: 10 kg, target preservation temperature is 0°C;

[0234] Meat: 10 kg, target fresh-keeping temperature is 2°C;

[0235] Green vegetables: 10 kg, target preservation temperature is 4°C;

[0236] Fruit: 10 kg, target preservation temperature is 5°C;

[0237] Dairy products: 10 kg, target preservation temperature is 3°C;

[0238] 3) Experimental time and environmental conditions:

[0239] Experimental time: 24 hours;

[0240] Ambient temperature: 20℃;

[0241] The initial temperature of the internal partition of the cold chain transport vehicle is set to the target preservation temperature;

[0242] At the beginning of the experiment, the cold chain transport vehicle set the temperature of each zone to its respective target preservation temperature; the IoT temperature control system began to collect temperature data from each zone in real time and recorded it once every hour;

[0243] At the sixth hour, a simulated failure occurred: the temperature control system in the first zone where the fish were located malfunctioned, causing the temperature to rise to 4°C. At this point, the IoT temperature control system detected the temperature deviation and began to make adjustments.

[0244] The specific adjustment process is as follows:

[0245] Real-time collection of temperature data of the fault zone and adjacent zones:

[0246] Collect the temperature of the fault zone (fish zone, zone 1) ;

[0247] Collect the temperature of adjacent partitions (meat partition, partition 2) and (vegetable partition, partition 3) and ;

[0248] Calculate the first temperature comparison coefficient :

[0249] Target fresh-keeping temperature = 0℃;

[0250] Actual temperature = 4°C;

[0251] Maximum and minimum temperature changes = 5℃, = -5℃;

[0252] Failure severity coefficient = 0.5;

[0253] The first temperature comparison coefficient of the first partition Calculation formula:

[0254] ;

[0255] in, ,but:

[0256] ;

[0257] Calculate the second temperature comparison coefficient :

[0258] Target fresh-keeping temperature = 2℃, actual temperature = 3.5℃;

[0259] , ;

[0260] Target fresh-keeping temperature = 4℃, actual temperature = 4.5℃;

[0261] , ;

[0262] Calculate the freshness preservation strategy adjustment index :

[0263] Adjustment factor ;

[0264] ;

[0265] Analysis formula:

[0266] ;

[0267] Implement dynamic adjustments:

[0268] Due to the freshness preservation strategy adjustment index =0.67, in the interval (4, 7);

[0269] According to the setting, increase the current missing difference Adjust the cooling air delivery volume by 50%;

[0270] After adjustment ;

[0271] Over the next 24 hours, the IoT temperature control system continued to monitor the temperature of each zone in real time and made dynamic adjustments based on the condition of the faulty zone. The recorded data is shown in Table 1 below:

[0272]

[0273] Data Analysis and Conclusions:

[0274] As can be seen from the data table, after the failure occurred in the 6th hour, the invented multi-zone cold chain preservation and Internet of Things temperature control system dynamically adjusted 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 effect of fresh food.

[0275] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0276] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0277] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0278] The above embodiments are only intended to help understand the method and core concept of the present invention. It should be noted that, without departing from the principles of the present invention, a number of improvements and modifications may be made to the present invention by those skilled in the art, and such 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, use the IoT temperature control system to determine the preservation temperature target value of each zone, and record the historical temperature control equipment status data of each zone; A first temperature comparison coefficient generation module is used to extract temperature change data of each partition when temperature control failures of varying degrees occur based on historical temperature control device status data, and calculate a first temperature comparison coefficient between the temperature change data corresponding to the current time and the fresh-keeping temperature target value for each partition when temperature control failures of varying degrees occur; 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 filter out the faulty partition at the current time from the temperature control fault degree judgment result; Emergency fresh-keeping strategy formulation module: used to formulate a corresponding emergency fresh-keeping strategy for the faulty zone based on the output value range of the first temperature comparison coefficient of the faulty zone, the emergency fresh-keeping strategy including setting a cold air delivery component with adjustable cold air delivery volume in the normal zone adjacent to the faulty zone; Second temperature comparison coefficient generation module: used to collect the fresh-keeping temperature values of 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 the first temperature comparison coefficient and the second temperature comparison coefficient to generate a freshness preservation strategy adjustment model for dynamically adjusting the cold air delivery components of the normal partitions adjacent to the faulty partition.

2. The multi-zone cold chain preservation and Internet of Things temperature control system for fresh food transportation according to claim 1, characterized in that: The independently controllable temperature zones of the multi-zone cold chain system are divided and marked, and the target temperature for each zone is determined using the IoT temperature control system. The historical temperature control equipment status data for each zone is also 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 target value of the fresh-keeping temperature for each partition and form a target value sequence ,in is the target value of the fresh-keeping temperature of the i-th partition; Historical temperature control device status data includes real-time temperature change data and corresponding operating status data of the temperature control device; operating status data includes the on / off status of the temperature control device, power consumption, compressor frequency, and refrigerant flow rate; 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 represents 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 recorded as , 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. The 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 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 of the temperature control device at the current time t; For the judgment of different degrees of temperature control failure, a standardized fault threshold set is set to represent different degrees of temperature control failure; Set the fault threshold set of power consumption to ; when When , it means the temperature control device has a low level of fault or no fault; when When , it means the temperature control device fault level is medium fault; when When , it means the temperature control device fault level is high; Set the fault threshold set of the compressor operating frequency to ; when When , it means the temperature control device has a low level of fault or no fault; when When , it means the temperature control device fault level is medium fault; when When , it means the temperature control device fault level is high; Set the refrigerant flow fault threshold set to ; when When , it means the temperature control device has a low level of fault or no fault; when When , it means the temperature control device fault level is medium fault; when When , it indicates that the temperature control device fault level is high.

4. The 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 time period before the current time t. are the positive adjustment coefficients of the corresponding fault levels.

5. The 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 temperature control failures of varying 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 i-th 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 closed, The results of temperature control fault degree judgment 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 temperature control equipment failure 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. The 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 determine 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 faulty 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 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. The 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 the fault zone, including: The cold air delivery assembly includes an air guide pipe, an exhaust 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 target value of fresh-keeping temperature The missing difference between: ； in, is the missing difference, which represents the difference between the actual temperature value and the target value of the fresh-keeping temperature; exist Under the premise of The value range of , formulate the following corresponding emergency preservation strategy; 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. The emergency strategy is: The IoT temperature control system controls the temperature control devices in the normal partition 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 between [0.4, 0.7], it means that the temperature control system is moderately 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 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 indicates that the temperature control system is highly abnormal. The emergency response 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. The 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 temperature value of the fresh-keeping temperature; is the second temperature comparison coefficient of the jth normal partition.

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

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