Intelligent cold-chain logistics temperature monitoring system for logistics field

Abstract

The invention relates to the field of temperature monitoring, in particular to an intelligent cold-chain logistics temperature monitoring system used in the logistics field. The data monitoring module monitors the temperature and the transportation speed of the truck regularly, calculates a temperature mean value and a standard deviation, then calculates a data value, and sends out a feedback sound after the comparison data value exceeds a preset threshold value; the positioning tracking module monitors latitude and longitude coordinates of the truck, calculates a plurality of distances, obtains the minimum distance according to a rapid sorting method, and displays the transfer station position information and the transportation speed corresponding to the minimum distance; the refrigeration power control module monitors the temperature outside the truck; a user measures the laser round-trip time by emitting laser beams from different angles, the carriage volume and the pre-measured carriage area are obtained through the round-trip time, the heat conduction value, the truck heat capacity, the temperature variation, the total cooling heat and the total refrigeration power are calculated, and then the output power of refrigeration equipment is controlled to be the total refrigeration power based on the total refrigeration power.

Description

Technical Field

[0001] The present invention belongs to the technical field of temperature monitoring, and particularly relates to an intelligent cold chain logistics temperature monitoring system for the logistics field. Background Art

[0002] Cold chain logistics refers to maintaining a specific low-temperature environment during transportation, storage, distribution, etc. to ensure the quality and safety of perishable goods. With the rapid development of global trade and e-commerce, the importance of cold chain logistics in the modern supply chain has become increasingly prominent. Especially after the epidemic, the transportation demand for biological products such as vaccines and drugs has surged, posing higher requirements for the reliability and accuracy of the cold chain. However, there are many challenges in the actual operation of cold chain logistics, especially in terms of temperature control, transportation timeliness, and energy efficiency. First of all, temperature stability is one of the most critical factors in cold chain logistics. Temperature deviation may lead to a decline in the quality of goods and even spoilage. For example, when transporting vaccines, even a temperature fluctuation of a few degrees may affect the effectiveness of the vaccines, causing huge economic losses and public health risks. Currently, many cold chain logistics systems mainly rely on traditional temperature control equipment and manual monitoring, but these systems often have problems such as slow response speed, low accuracy, and information lag. The traditional temperature monitoring method only relies on regular manual inspections and cannot detect temperature fluctuations or abnormal changes in a timely manner, possibly missing the best intervention opportunity. Secondly, the transportation route and timeliness are also a major challenge for the management of cold chain logistics. Cold chain transportation not only requires proper temperature control but also needs to ensure high efficiency and punctuality during the transportation process. The arrival time of goods and the optimization of the transportation route directly affect the overall efficiency of the cold chain, especially for high-value goods that need to be transported within a strict time limit. Factors such as traffic and weather during transportation may affect the scheduled arrival time, but the existing systems often lack real-time monitoring and prediction of transportation speed, route, traffic conditions, etc., resulting in the inability to synchronize dispatching and temperature control management, increasing the uncertainty and risk of cold chain transportation. In addition, the energy efficiency issue is also an important problem in cold chain logistics. In order to maintain a low-temperature environment, cold chain logistics usually requires a large number of refrigeration devices, which will bring huge energy consumption and costs. The traditional refrigeration method is often not fully optimized in terms of energy efficiency, and many systems will operate continuously without discrimination, resulting in energy waste. In the context of increasingly strict environmental protection requirements and rising energy costs, how to achieve precise refrigeration control and reduce energy consumption has become an urgent problem to be solved in the cold chain logistics industry. Therefore, an intelligent cold chain logistics temperature monitoring system for the logistics field is proposed. Summary of the Invention

[0003] The technical problem to be solved by the present invention is the lack of precise temperature control management, dynamic path and time monitoring, and reasonable refrigeration power adjustment, and provides an intelligent cold chain logistics temperature monitoring system for the logistics field.

[0004] The technical solution adopted by the present invention to solve its technical problems is: an intelligent cold chain logistics temperature monitoring system for the logistics field, including a data monitoring module, a positioning and tracking module, and a refrigeration power control module.

[0005] The data monitoring module is arranged inside the truck and is used for regularly monitoring the temperature of the truck.

[0006] The positioning and tracking module is arranged inside the truck compartment and is used for positioning and tracking the position of the truck.

[0007] The refrigeration power control module is arranged outside the truck and is used for refrigerating the compartment.

[0008] Furthermore, the data monitoring module includes a monitoring unit, a feedback unit, and an anomaly analysis unit.

[0009] The monitoring unit is arranged inside the truck and is used for regularly monitoring the temperature of the truck, and then transmitting the truck temperatures at different time points monitored regularly to the anomaly analysis unit according to the number of preset time points.

[0010] The anomaly analysis unit is connected to the monitoring unit and the refrigeration power control module. After receiving the truck temperature, it is used for calculating the temperature mean value according to the truck temperatures at different time points monitored regularly, calculating the temperature standard deviation based on the truck temperatures at different time points monitored regularly, calculating a data value based on the temperature standard deviation and the temperature mean value, and then comparing whether the data value exceeds a preset threshold. And it is used for generating an alarm prompt message and transmitting it to the feedback unit after the comparison shows that the data value exceeds the preset threshold.

[0011] The feedback unit is connected to the anomaly analysis unit and is arranged inside the truck cab. It is used for emitting a feedback sound after receiving the alarm prompt message.

[0012] Furthermore, the formula for the anomaly analysis unit to calculate the temperature mean value according to the temperatures at different time points monitored regularly is:

[0013] where μ is the temperature mean value, with the unit of °C, N is the number of preset time points, and x e is the truck temperature at the e-th time point, with the unit of °C.

[0014] Furthermore, the formula for the anomaly analysis unit to calculate the temperature standard deviation based on the temperatures at different time points monitored regularly is:

[0015]

[0016] where σ is the standard deviation.

[0017] Furthermore, the formula for the anomaly analysis unit to calculate the data value based on the standard deviation and the mean value is:

[0018]

[0019] Among them, Z e is the data value.

[0020] Furthermore, the positioning and tracking module includes a GPS positioning device, a cloud server, and a display module.

[0021] The monitoring unit is used to monitor the transportation speed of the truck and then transmit it to the cloud server.

[0022] The GPS positioning device is set inside the truck compartment and is used to monitor the longitude and latitude coordinates of the truck, and then transmit the longitude and latitude coordinates of the truck to the cloud server.

[0023] The cloud server is connected to the monitoring unit, the GPS positioning device, and the refrigeration power control module, and is used to provide managers with the location information of several cold chain transfer stations. And it is used to calculate several distances based on the location information of several cold chain transfer stations and the longitude and latitude coordinates of the truck after receiving the longitude and latitude coordinates of the truck, then sort the several distances according to the quicksort method to obtain the minimum distance, and then transmit the location information of the transfer station corresponding to the minimum distance to the display module. And it is used to calculate the arrival time based on the minimum distance and the transportation speed after receiving the transportation speed, and then transmit it to the display module.

[0024] The display module is connected to the cloud server and is used to display the location information of the transfer station corresponding to the minimum distance and the arrival time after receiving the location information of the transfer station corresponding to the minimum distance and the arrival time.

[0025] Furthermore, the formula for the cloud server to calculate several distances based on the location information of several cold chain transfer stations and the longitude and latitude coordinates of the truck is:

[0026]

[0027] Among them, d i is the i-th distance, with the unit of m, r is the radius of the earth, with the unit of km, is the longitude coordinate of the truck, with the unit of degree, is the longitude coordinate of the location information of the i-th cold chain transfer station, with the unit of degree, Δλ is the radian difference of the latitude difference between the latitude coordinate of the truck and the location information of the i-th cold chain transfer station, with the unit of degree, is the radian difference of the longitude conversion between the longitude coordinate of the truck and the location information of the i-th cold chain transfer station, with the unit of degree,

[0028] The formula for calculating the arrival time based on the minimum distance and the transportation speed is:

[0029]

[0030] where t remaining is the arrival time in hours, d min is the minimum distance in meters, and v is the transportation speed in m / s.

[0031] Furthermore, the refrigeration power control module includes an external temperature sensor, a calculation unit, and a control unit.

[0032] The anomaly analysis unit is used to transmit the calculated temperature mean to the calculation unit after obtaining it.

[0033] After calculating the arrival time based on the minimum distance and transportation speed, the cloud server transmits it to the calculation unit.

[0034] The external temperature sensor is installed outside the truck to monitor the temperature outside the truck and then transmit it to the calculation unit.

[0035] The calculation unit is connected to the external temperature sensor, the cloud server, and the anomaly analysis unit. It is used to calculate the heat conduction value based on the arrival time, the temperature outside the truck, the volume of the carriage, the pre-measured area of the carriage, and the temperature mean. Then, it calculates the heat capacity of the truck based on the volume of the carriage, the preset air-to-truck heat capacity ratio, and the preset air density. Next, it calculates the temperature change based on the temperature outside the truck and the temperature mean. Then, it calculates the total cooling heat based on the temperature change and the heat capacity of the truck-carriage. Finally, it calculates the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time, and the preset refrigeration efficiency, and then transmits it to the control unit.

[0036] The control unit is connected to the calculation unit and is used to control the output power of the refrigeration equipment to be the total refrigeration power after receiving the total refrigeration power.

[0037] Furthermore, the formula for the calculation unit to calculate the heat conduction value based on the pre-measured area of the carriage, the preset carriage heat transfer coefficient, the temperature outside the truck, and the temperature mean is: Q IN = A × U × (T OUT - μ),

[0038] where A is the pre-measured area of the carriage in m 2 , U is the preset carriage heat transfer coefficient in W / m 2 K, T OUT is the temperature outside the truck in °C, Q IN is the heat conduction value in J,

[0039] The formula for calculating the heat capacity of the truck based on the volume of the carriage, the preset air-to-truck heat capacity ratio, and the preset air density is:

[0040] C CAR= V × ρ AIR × c AIR

[0041] Wherein, V is the volume of the carriage, with the unit of m 3 , ρ AIR is the preset air density, with the unit of kg / m 3 , c AIR is the preset specific heat capacity of air to the truck, with the unit of J / kgK, C CAR is the heat capacity of the truck, with the unit of J / K,

[0042] The formula for calculating the temperature change based on the temperature outside the truck and the average temperature is: ΔT = T OUT - μ

[0043] Wherein, ΔT is the temperature change, with the unit of °C.

[0044] Furthermore, the formula for the calculation unit to calculate the total cooling heat based on the temperature variable and the heat capacity of the carriage and the truck is Q COOL = C CAR × ΔT,

[0045] Wherein, Q COOL is the total cooling heat, with the unit of J,

[0046] The formula for calculating the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time, and the preset refrigeration efficiency is:

[0047]

[0048] Wherein, t remaining is the arrival time, with the unit of h, P COOL is the total refrigeration power, with the unit of W / h, and δ is the preset refrigeration efficiency.

[0049] Advantages of the present invention:

[0050] 1. The data monitoring module monitors the temperature inside the truck in real time, processes the temperature data through timed measurement and calculation, and ensures the accuracy and stability of temperature control. By calculating the average temperature and standard deviation of each time period, it can effectively identify abnormal temperature fluctuations and determine whether they exceed the normal range through the set threshold. When the temperature exceeds the threshold, the module will trigger an audible feedback to alert the operator in a timely manner, thus avoiding temperature deviation from affecting the quality of the goods. In addition, the module also tracks and records the transportation speed of the truck and transmits this information to the positioning and tracking module to ensure the close coordination of temperature management and transportation progress.

[0051] 2. The present invention relates to temperature monitoring, and particularly to an intelligent cold chain logistics temperature monitoring system for the logistics field. The data monitoring module regularly monitors the temperature and transportation speed of the truck, calculates the temperature mean value and standard deviation, and then calculates the data value. After comparing that the data value exceeds the preset threshold, it emits a feedback sound; the positioning and tracking module is for the administrator to deploy the location information of several cold chain transfer stations; monitors the longitude and latitude coordinates of the truck, calculates several distances, and then obtains the minimum distance according to the quicksort method, and then displays the location information of the transfer station corresponding to the minimum distance and the transportation speed; the refrigeration power control module monitors the temperature outside the truck; allows the user to measure the laser round-trip time by emitting laser beams from different angles, obtains the carriage volume and the pre-measured carriage area through the round-trip time, calculates the heat conduction value, the heat capacity of the truck, the temperature change amount, the total cooling heat, and the total refrigeration power, and then controls the output power of the refrigeration equipment to be the total refrigeration power based on the total refrigeration power.

[0052] 3. The refrigeration power control module calculates the heat conduction and temperature change in real time by monitoring the external temperature and the physical characteristics of the carriage, and then determines the required refrigeration power. By using laser measurement technology to obtain the accurate dimensions of the carriage, calculates the heat capacity of the truck and the heat to be cooled in the carriage, providing accurate power requirements for the refrigeration equipment. When the arrival time and the external temperature information are transmitted to the module, the system can calculate the optimal refrigeration power output, thereby adjusting the working state of the refrigeration equipment in real time to ensure that the temperature inside the carriage is maintained within the preset range. This module not only improves the energy utilization efficiency but also dynamically responds to environmental changes, ensuring the stability and safety of cold chain transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a schematic diagram of the system modules of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] The following will clearly and completely describe the concept of the present invention and the technical effects produced in combination with the embodiments to fully understand the purpose, features, and effects of the present invention. Please refer to Figure 1 .

[0055] An intelligent cold chain logistics temperature monitoring system for the logistics field includes a data monitoring module, a positioning and tracking module, and a refrigeration power control module.

[0056] The data monitoring module is arranged inside the truck and is used to regularly monitor the temperature of the truck.

[0057] The positioning and tracking module is arranged inside the truck carriage and is used to position and track the location of the truck.

[0058] The refrigeration power control module is arranged outside the truck and is used to refrigerate the carriage.

[0059] In this embodiment, the data monitoring module includes a monitoring unit, a feedback unit, and an anomaly analysis unit.

[0060] The monitoring unit is arranged inside the truck and is used to regularly monitor the temperature of the truck, and then transmit the truck temperatures at different time points monitored regularly to the anomaly analysis unit according to the number of preset time points. The monitoring unit is a digital temperature sensor.

[0061] The anomaly analysis unit is connected to the monitoring unit and the refrigeration power control module. After receiving the truck temperature, it is used to calculate the temperature mean value based on the truck temperatures at different time points monitored regularly, then calculate the temperature standard deviation based on the truck temperatures at different time points monitored regularly, then calculate the data value based on the temperature standard deviation and the temperature mean value, and then compare whether the data value exceeds the preset threshold. And it is used to generate an alarm prompt message after comparing that the data value exceeds the preset threshold and transmit it to the feedback unit. The anomaly analysis unit can adopt a microcontroller based on the ARM architecture.

[0062] The feedback unit is connected to the anomaly analysis unit and is arranged inside the truck cab. It is used to emit a feedback sound after receiving the alarm prompt message. The feedback unit is a speaker. When receiving the alarm prompt message, the speaker emits a feedback sound to remind the truck driver.

[0063] In this embodiment, the monitoring unit regularly collects the temperature data inside the truck and transmits it to the anomaly analysis unit. By performing segmented processing on the temperature data, the accuracy of temperature change monitoring is effectively improved. In addition, the monitoring unit is also responsible for real-time tracking of the transportation speed of the truck and transmitting this information to the positioning and tracking module to ensure that the temperature monitoring is synchronized with the transportation progress. The anomaly analysis unit can accurately analyze the temperature fluctuations inside the truck by calculating the temperature mean value and the standard deviation, and identify anomalies in a timely manner. The data value calculated using the temperature standard deviation and the mean value is compared with the preset threshold. When the temperature fluctuation exceeds the threshold, the system can immediately detect and identify the abnormal situation. After receiving the alarm prompt message from the anomaly analysis unit, the feedback unit can quickly emit a feedback sound to remind the driver or operator to pay attention to the temperature change and take corresponding treatment measures. This alarm mechanism ensures the timely discovery and response to abnormal situations, thereby reducing the impact of temperature control problems on the safety of goods.

[0064] In this embodiment, the formula for the anomaly analysis unit to calculate the temperature mean value based on the temperatures at different time points monitored regularly is:

[0065]

[0066] where μ is the temperature mean value, with the unit of °C, N is the number of preset time points, and x e is the truck temperature at the e-th time point, with the unit of °C.

[0067] In this embodiment, the formula for the anomaly analysis unit to calculate the temperature standard deviation based on the temperatures at different time points monitored at regular intervals is as follows:

[0068]

[0069] where σ is the standard deviation.

[0070] In this embodiment, the formula for the anomaly analysis unit to calculate the data value based on the standard deviation and the mean is as follows:

[0071]

[0072] where Z e is the data value.

[0073] For example, assume that we have the temperature data of a truck at 5 time points monitored at regular intervals. If N is 5, then x 1 、x 2 、x 3 、x 4 、x 5 are 10°C, 12°C, 8°C, 11°C, 9°C respectively, μ is 10°C, σ is 1.41°C, and Z t is -1.42, then an anomaly occurs.

[0074] In this embodiment, the positioning and tracking module includes a GPS positioning device, a cloud server, and a display module.

[0075] The monitoring unit is used to monitor the transportation speed of the truck and then transmit it to the cloud server.

[0076] The GPS positioning device is set inside the truck compartment and is used to monitor the longitude and latitude coordinates of the truck, and then transmit the longitude and latitude coordinates of the truck to the cloud server. The GPS positioning device uses a GPS locator.

[0077] The cloud server is connected to the monitoring unit, the GPS positioning device, and the refrigeration power control module, and is used for the manager to deploy the location information of several cold chain transfer stations. And it is used to calculate several distances based on the location information of several cold chain transfer stations and the longitude and latitude coordinates of the truck after receiving the longitude and latitude coordinates of the truck, then sort the several distances according to the quicksort method to obtain the minimum distance, and then transmit the location information of the transfer station corresponding to the minimum distance to the display module. And it is used to calculate the arrival time based on the minimum distance and the transportation speed after receiving the transportation speed, and then transmit it to the display module.

[0078] The display module is connected to the cloud server and is used to display the location information of the transfer station corresponding to the minimum distance and the arrival time after receiving the location information of the transfer station corresponding to the minimum distance and the arrival time. The display module uses an OLED display screen.

[0079] In this embodiment, the GPS positioning device monitors the longitude and latitude coordinates of the truck in real time and transmits this information to the cloud server. This function ensures the accurate tracking of the truck's location, enabling managers to know the dynamic position of the truck at any time. The cloud server not only receives the truck location data but also allows managers to preset the location information of the cold chain transfer stations. Based on the calculation of the distance between the current location of the truck and the transfer stations, the system determines the nearest transfer station through the quicksort method, optimizing the selection of transfer stations to ensure that the goods can reach the appropriate transfer station as soon as possible. After receiving the transportation speed of the truck, the cloud server can calculate the expected time for the truck to reach the target transfer station in real time by combining the shortest distance and speed data. This information is transmitted to the refrigeration power control module for corresponding temperature adjustment and at the same time transmitted to the display module so that the management personnel can master the transportation progress. The display module receives the transfer station information corresponding to the shortest distance and the arrival time transmitted by the cloud server and intuitively displays them to the manager, facilitating the real-time monitoring of the transportation situation of the truck and the expected arrival time to ensure the timeliness and coordination during the transportation process.

[0080] In this embodiment, the formula for calculating several distances based on the location information of several cold chain transfer stations and the longitude and latitude coordinates of the truck is:

[0081]

[0082] where d i is the i-th distance, with the unit of m, r is the radius of the earth, with the unit of km, is the longitude coordinate of the truck, with the unit of degree, is the longitude coordinate of the location information of the i-th cold chain transfer station, with the unit of degree, Δλ is the radian difference of the latitude difference between the truck's latitude coordinate and the latitude coordinate of the location information of the i-th cold chain transfer station, with the unit of degree, is the radian difference of the longitude difference between the truck's longitude coordinate and the longitude coordinate of the location information of the i-th cold chain transfer station, with the unit of degree,

[0083] The formula for calculating the arrival time based on the minimum distance and transportation speed is:

[0084]

[0085] where t renaining is the arrival time, with the unit of h, d min is the minimum distance, with the unit of m, v is the transportation speed, with the unit of m / s,

[0086] For example, the longitude coordinate of the truck is 30°, the longitude coordinate of the location information of the i-th cold chain transfer station is 31°, the radius of the earth is 6,371 km, the difference in longitude coordinates between the truck and the location information of the i-th cold chain transfer station converted to the difference in radians is -0.000155 rad, and the difference in latitude between the user's location and the punctuation of the critical path converted to radians is 0.000079 rad. Then the distance of the i-th one is 10,000 m. Assuming that the distance of the i-th one is the minimum distance, the transportation speed is 2 m / s, and the arrival time is 1.4 h.

[0087] In this embodiment, the refrigeration power control module includes an external temperature sensor, a calculation unit, and a control unit.

[0088] The anomaly analysis unit is used to transmit the temperature mean value to the calculation unit after calculating it.

[0089] After calculating the arrival time based on the minimum distance and the transportation speed, the cloud server transmits it to the calculation unit.

[0090] The external temperature sensor is set outside the truck and is used to monitor the temperature outside the truck and then transmit it to the calculation unit.

[0091] The calculation unit is connected to the external temperature sensor, the cloud server, and the anomaly analysis unit. It is used to, after receiving the arrival time, the temperature outside the truck, the volume of the carriage, the pre-measured area of the carriage, and the temperature mean value, calculate the heat conduction value based on the pre-measured area of the carriage, the preset heat transfer coefficient of the carriage, the temperature outside the truck, and the temperature mean value. Then calculate the heat capacity of the truck based on the volume of the carriage, the preset air specific heat capacity of the truck, and the preset air density. Then calculate the temperature change amount based on the temperature outside the truck and the temperature mean value. Then calculate the total cooling heat based on the temperature change amount and the heat capacity of the truck. Then calculate the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time, and the preset refrigeration efficiency, and then transmit it to the control unit. The calculation unit can use an embedded computer.

[0092] The control unit is connected to the calculation unit and is used to control the output power of the refrigeration equipment to be the total refrigeration power after receiving the total refrigeration power. The control unit can use a PLC.

[0093] In this embodiment, the external temperature sensor monitors the external environmental temperature of the truck and transmits the temperature data to the calculation unit. This function provides real-time feedback on the external environment for calculating the internal temperature control of the carriage, ensuring that the temperature control system can respond promptly to external climate changes. The calculation unit combines the physical parameters of the carriage, the external temperature, the temperature inside the truck, and the preset heat transfer coefficient to calculate the heat transfer value. At the same time, the truck heat capacity of the truck is calculated using the carriage volume, the air specific heat capacity of the truck, and the air density to ensure an accurate estimation of heat changes. The calculation unit calculates the total cooling heat required based on the temperature change and the truck heat capacity of the carriage. This calculation helps predict the temperature change inside the truck, thereby determining the required refrigeration power and avoiding affecting the temperature control effect during transportation due to excessive or insufficient refrigeration. Based on the heat transfer value, the total cooling heat, the arrival time, and the refrigeration efficiency, the calculation unit can obtain the accurate total refrigeration power and transmit the result to the control unit. The control unit adjusts the output power of the refrigeration equipment according to this power, thereby achieving precise adjustment of the internal temperature of the carriage and ensuring temperature stability during transportation.

[0094] In this embodiment, the formula for calculating the heat transfer value by the calculation unit according to the pre-measured carriage area, the preset carriage heat transfer coefficient, the temperature outside the truck, and the temperature average value is: Q IN = A × U × (T OUT - μ),

[0095] where, A is the pre-measured carriage area, with the unit of m 2 , U is the preset carriage heat transfer coefficient, with the unit of W / m 2 K, T OUT is the temperature outside the truck, with the unit of °C, Q IN is the heat transfer value, with the unit of J,

[0096] The formula for calculating the truck heat capacity based on the carriage volume, the preset air specific heat capacity of the truck, and the preset air density is:

[0097] C CAR = V × ρ AIR × c AIR

[0098] where, V is the carriage volume, with the unit of m 3 , ρ AIR is the preset air density, with the unit of kg / m 3 , c AIR is the preset air specific heat capacity of the truck, with the unit of J / kgK, C CAR is the truck heat capacity, with the unit of J / K,

[0099] The formula for calculating the temperature change based on the temperature outside the truck and the temperature average value is: ΔT = T OUT - μ

[0100] Among them, ΔT is the temperature change amount, with the unit of °C.

[0101] In this embodiment, the formula for calculating the total cooling heat based on the temperature variable and the heat capacity of the freight car is Q COOL = C CAR ×ΔT,

[0102] Among them, Q COOL is the total cooling heat, with the unit of J,

[0103] The formula for calculating the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time, and the preset refrigeration efficiency is:

[0104]

[0105] Among them, t remaining is the arrival time, with the unit of h, P COOL is the total refrigeration power, with the unit of W / h, and δ is the preset refrigeration efficiency.

[0106] For example, assume that the pre-measured carriage area is 10 m 2 , the preset carriage heat conduction coefficient is 5 W / m 2 K, the outside temperature is 30 °C, the freight car temperature is 20 degrees Celsius, the heat conduction value is 500 J, the preset air density is 1.2 kg / m 3 , the preset specific heat capacity of air relative to the freight car is 1000 J / kgK, the heat capacity of the freight car is 6000 J / K, the temperature change rate is 10 °C, the total cooling heat is 6000 J / K, the preset refrigeration efficiency is 0.8, and the total refrigeration power is 5800 W / h.

[0107] The above embodiments are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without creative efforts shall fall within the scope of protection of the present invention.

Claims

1. An intelligent cold chain logistics temperature monitoring system used in the logistics field, characterized by: Including data monitoring module, positioning tracking module, cooling power control module, The data monitoring module is arranged in the truck and is used to monitor the temperature of the truck at regular intervals; The positioning and tracking module is arranged in the truck compartment and is used to locate and track the position of the truck; The refrigeration power control module is arranged outside the truck and is used for cooling the compartment.

2. According to claim 1, an intelligent cold chain logistics temperature monitoring system for logistics, characterized in that: The data monitoring module includes a monitoring unit, a feedback unit, and an abnormality analysis unit. The monitoring unit is arranged in the truck, and is used to regularly monitor the temperature of the truck, and then transmit the temperature of the truck at different time points of regular monitoring to the abnormality analysis unit according to the number of preset time points; The abnormal analysis unit is connected to the monitoring unit and the refrigeration power control module, and is used to calculate the temperature mean value according to the temperature of the truck at different time points of the regular monitoring after receiving the temperature of the truck, and then calculate the temperature standard deviation based on the temperature of the truck at different time points of the regular monitoring, and then calculate the data value based on the temperature standard deviation and the temperature mean, and then compare whether the data value exceeds the preset threshold value; and is used to generate an alarm prompt message after the comparison data value exceeds a preset threshold value, and transmit it to the feedback unit; The feedback unit is connected to the abnormality analysis unit, and is disposed in the truck cab, and is used to issue a feedback sound after receiving the alarm prompt information.

3. The intelligent cold chain logistics temperature monitoring system for the logistics field according to claim 2 is characterized in that: The formula for calculating the temperature mean value by the abnormal analysis unit according to the temperature at different time points monitored regularly is: Where μ is the mean temperature in °C, N is the number of preset time points, and x e is the temperature of the truck at the e-th time point, in °C.

4. The intelligent cold chain logistics temperature monitoring system for the logistics field according to claim 2 is characterized in that: The formula for calculating the temperature standard deviation by the abnormal analysis unit based on the temperature at different time points of the regular monitoring is: Here, σ is the standard deviation.

5. The intelligent cold chain logistics temperature monitoring system for the logistics field according to claim 2 is characterized in that: The formula for calculating the data value based on the standard deviation and mean value by the abnormal analysis unit is: Among them, Z e is the data value.

6. The intelligent cold chain logistics temperature monitoring system for the logistics field according to claim 2 is characterized in that: The positioning and tracking module includes a GPS positioning device, a cloud server, and a display module. The monitoring unit is used to monitor the transportation speed of the truck and then transmit it to the cloud server; The GPS positioning device is arranged in the truck compartment to monitor the longitude and latitude coordinates of the truck, and then transmit the longitude and latitude coordinates of the truck to the cloud server; The cloud server is connected to the monitoring unit, the GPS positioning device, and the refrigeration power control module, and is used for the administrator to deploy the location information of several cold chain transfer stations; And it is used to calculate a number of distances based on a number of cold chain transfer station location information and the longitude and latitude coordinates of the truck after receiving the longitude and latitude coordinates of the truck, sort the distances according to the quick sorting method to obtain the minimum distance, and then transmit the transfer station location information corresponding to the minimum distance to the display module; and is used to calculate the arrival time based on the minimum distance and the transportation speed after receiving the transportation speed, and then transmit it to the display module; The display module is connected to the cloud server and is used to display the transfer station location information and arrival time corresponding to the minimum distance after receiving the transfer station location information and arrival time corresponding to the minimum distance.

7. The intelligent cold chain logistics temperature monitoring system for logistics according to claim 6 is characterized in that: The cloud server calculates the distances based on the location information of the cold chain transfer stations and the longitude and latitude coordinates of the trucks as follows: Among them, d i is the ith distance in meters, r is the radius of the earth in kilometers, is the longitude coordinate of the truck in degrees, is the longitude coordinate of the location information of the i-th cold chain transfer station, in degrees, Δλ is the latitude difference between the latitude coordinate of the truck and the location information of the i-th cold chain transfer station, in degrees, is the difference in arc between the longitude coordinate of the truck and the location information of the i-th cold chain transfer station, in degrees. The formula for calculating the arrival time based on the minimum distance and transportation speed is: Among them, t remaining is the arrival time, in h, d min is the minimum distance in meters, and v is the transport speed in meters per second.

8. The intelligent cold chain logistics temperature monitoring system for logistics according to claim 6 is characterized in that: The cooling power control module includes an external temperature sensor, a calculation unit, and the control unit. The abnormality analysis unit is used to transmit the calculated temperature mean to the calculation unit after obtaining the calculated temperature mean; After the cloud server calculates the arrival time based on the minimum distance and the transportation speed, it transmits it to the calculation unit; The external temperature sensor is disposed outside the truck and is used to monitor the temperature outside the truck and transmit it to the computing unit; The calculation unit is connected to the external temperature sensor, the cloud server, and the abnormal analysis unit, and is used to calculate the heat conduction value according to the pre-measured compartment area, the preset compartment heat conduction coefficient, the temperature outside the truck, and the temperature average after receiving the arrival time, the temperature outside the truck, the compartment volume, the pre-measured compartment area, and the temperature average, and then calculate the truck heat capacity based on the compartment volume, the preset air-to-truck heat capacity, and the preset air density, and then calculate the temperature change based on the temperature outside the truck and the temperature average, and then calculate the total cooling heat based on the temperature change and the compartment truck heat capacity, and then calculate the total cooling power based on the heat conduction value, the total cooling heat, the arrival time, and the preset cooling efficiency, and then transmit it to the control unit; The control unit is connected to the calculation unit, and is used for controlling the output power of the refrigeration equipment to be the total refrigeration power based on the total refrigeration power after receiving the total refrigeration power.

9. The intelligent cold chain logistics temperature monitoring system for the logistics field according to claim 8 is characterized in that: The calculation unit calculates the heat transfer value according to the pre-measured compartment area, the preset compartment heat transfer coefficient, the temperature outside the truck, and the average temperature. The formula is: Q IN =A×U×(T OUT -μ), Where A is the pre-measured compartment area in m 2 , U is the preset cabin heat transfer coefficient, unit is W / m 2 K, T OUT is the temperature outside the truck, in °C, Q IN is the heat conduction value, the unit is J, The formula for calculating the heat capacity of a truck based on the volume of the car, the preset air-to-truck heat capacity, and the preset air density is: C CAR =V×ρ AIR ×c AIR Where V is the volume of the car, in m 3 , ρ AIR is the preset air density in kg / m 3 , c AIR is the preset air specific heat capacity of the truck, in J / kgK, C CAR is the heat capacity of the truck, in J / K, The formula for calculating the temperature change based on the temperature outside the truck and the temperature average is: ΔT = T OUT -μ Where ΔT is the temperature change in °C.

10. The intelligent cold chain logistics temperature monitoring system for logistics according to claim 8, characterized in that: The calculation unit calculates the total cooling heat based on the temperature variable and the heat capacity of the compartment and the truck as follows: COOL =C CAR × ΔT, Among them, Q COOL is the total cooling heat, in J, The formula for calculating the total cooling power based on the heat transfer value, total cooling heat, arrival time, and preset cooling efficiency is: Among them, t remaining is the arrival time in h, P COOL is the total cooling power in W / h, and δ is the preset cooling efficiency.

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