Intelligent temperature regulation and control system for cold accumulation pipe

Abstract

The invention relates to the technical field of cold storage tubes, in particular to an intelligent temperature regulation and control system for cold storage tubes, which comprises a center console, a measurement module and a refrigeration module, temperature regulation and control software is installed in the center console, and the temperature regulation and control software comprises a parameter determination unit, a fault judgment unit and a control regulation unit. The problems that when an existing cold storage pipe is cooled, temperature control is simple, the intelligent degree is low, and the control effect is poor can be effectively solved.

Description

Technical Field

[0001] The invention relates to the technical field of cold storage pipes, in particular to an intelligent temperature regulation and control system for cold storage pipes. Background Art

[0002] The cold storage tube is a device component that absorbs heat by using the phase change of the coolant, but the existing cold storage tube still has shortcomings. Specifically, when cooling, the temperature control of the existing cold storage tube is relatively simple, the degree of intelligence is low, and the control effect is poor.

[0003] Therefore, a cold storage pipe intelligent temperature adjustment control system is needed to solve the problems raised in the above background technology. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent temperature regulation and control system for cold storage pipes to solve the problems raised in the above background technology.

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

[0006] A cold storage pipe intelligent temperature adjustment and control system comprises a central control console, a measuring module and a refrigeration module. The central control console is internally installed with temperature control software, which comprises a parameter determination unit, a fault judgment unit and a control adjustment unit.

[0007] As a preferred solution of the present invention, the measuring module includes a measuring box fixedly connected to the outer wall of the cold storage tube, the outer wall of the measuring box is provided with a temperature sensor, the interior of the measuring box is provided with a thermocouple, the outer wall of the thermocouple and the interior of the measuring box are fixedly connected with a connecting sleeve, the interior of the connecting sleeve and the measuring box is slidably connected with a measuring rod, the connecting sleeve is adhered to the measuring rod through thermal conductive silicone grease, the interior of the measuring box and the outer wall of the connecting sleeve are fixedly connected with a thermal insulation pad, the interior of the measuring box and the left side of the temperature sensor are fixedly connected with a GPS locator, the top of the measuring box and the right side of the temperature sensor are fixedly connected with a data transmitter, a controller is installed on the front of the measuring box, the outer wall of the measuring box is installed with a terminal, and the bottom of the measuring box is fixedly connected with a mounting clamp.

[0008] As a preferred solution of the present invention, the connection modes of the measuring module, the refrigeration module and the central console are all electrically connected, the refrigeration module includes various refrigeration modules with remote control function, and the measuring module is provided in multiple groups.

[0009] As a preferred solution of the present invention, the specific analysis steps of the parameter determination unit are: the parameter determination unit constructs a solidification degree model of the coolant in the cold storage tube, and establishes a real-time cooling capacity model of the cold storage tube based on the constructed solidification degree model of the coolant in the cold storage tube, the central control console collects the difference in cumulative cooling capacity at the same time point in the past to obtain the current cooling capacity for the whole day, and determines the optimal cold storage temperature of the cold storage tube based on the current cooling capacity for the whole day.

[0010] As a preferred solution of the present invention, the specific analysis steps of the fault judgment unit are: the fault judgment unit receives the measurement data input by the measurement module, and screens the measurement data to eliminate abnormal data, the fault judgment unit selects the abnormal detection measurement module according to the GPS data in the abnormal data, the fault judgment unit extracts multiple groups of data of other measurement modules located near the abnormal detection measurement module, and compares the data of other measurement modules with the data of the abnormal measurement module, if the difference between the data of other measurement modules and the data of the abnormal measurement module is lower than the threshold value, it indicates that the measurement module is operating normally and the abnormal data is caused by the failure of the cold storage tube, the fault judgment unit sends a maintenance signal to the maintenance personnel, and the maintenance personnel repair the cold storage tube at the position of the abnormal measurement module, if the difference between the data of other measurement modules and the data of the abnormal measurement module is higher than the threshold value, it indicates that the abnormal operation of the measurement module causes the data to be abnormal, the fault judgment unit sends a maintenance signal to the maintenance personnel, the maintenance personnel repair the abnormal measurement module, and the fault judgment unit inputs the remaining normal data into the control adjustment unit.

[0011] As a preferred solution of the present invention, the specific analysis steps of the control and adjustment unit are: the central console starts the refrigeration module, the refrigeration module starts to cool the coolant in the cold storage tube, the measurement module detects the temperature data inside and outside the cold storage tube, and inputs the temperature data into the central console, the control and adjustment unit in the central console inputs the temperature data into the real-time cooling capacity model, thereby obtaining the real-time cooling capacity data of the current cold storage tube, processing the real-time cooling capacity data, and adjusting the operating power of the refrigeration module according to the processing results.

[0012] As a preferred solution of the present invention, the measuring box and the thermal insulation pad are both made of thermal insulation materials, the measuring rod penetrates and extends into the cold storage tube, the data transmitter is connected to the central console via a wireless data network, the connecting sleeve and the measuring rod are both made of red copper, the thermocouple, temperature sensor, GPS locator, data transmitter and the connection method of the terminal to the controller are all electrical connections, the mounting clamp is made of aluminum alloy, and two groups of mounting clamps are provided.

[0013] As a preferred solution of the present invention, the expression of the solidification degree model of the coolant in the cold storage tube is: The real-time cooling model expression is Qs =|tt 0 |*ΔH*M*θ s , where θ s Indicates the solidification degree of the cold storage unit. T is the real-time temperature in the cold storage unit. T and T 0 is the temperature of the two end points of the phase change process; a1 is the temperature at which 50% phase change occurs during the solidification process; 1 / b1 is the solidification enthalpy of the coolant, which indicates the ability of the material to absorb / release heat during phase change; ΔH is the average phase change rate, which is the average mass fraction of the coolant material in the cold storage tube that undergoes phase change every time it rises / falls 0.1°C.

[0014] As a preferred solution of the present invention, the process for determining the optimal cold storage temperature is to obtain the current full-day cooling capacity by the difference between the accumulated cooling capacity at the same time point of the two days before and after, and take the arithmetic mean of the past cooling capacity as the predicted cooling capacity, and compare the predicted cooling capacity with the theoretical maximum cooling capacity of the cold storage pipe. If the predicted cooling capacity is ≥ r1*theoretical maximum cooling capacity, then it is determined that the optimal cold storage temperature is equal to the minimum cold storage temperature threshold; if r2*theoretical maximum cooling capacity<predicted cooling capacity<r1*theoretical maximum cooling capacity, then the optimal cold storage temperature is determined to be ... Optimal cold storage temperature = minimum cold storage temperature threshold + (3*predicted cooling capacity / theoretical maximum cold storage capacity); if the predicted cooling capacity ≤ r2*theoretical maximum cold storage capacity, then determine that the optimal cold storage temperature is equal to the maximum cold storage temperature threshold, wherein the theoretical maximum cold storage capacity = c*ρ*V*Δt, c is the specific heat capacity of cooling water, ρ is the density of water at the minimum cold storage temperature threshold, V is the cold storage volume, Δt is the temperature difference between the inlet and outlet, r1 and r2 are the first cold storage critical coefficient and the second cold storage critical coefficient, respectively, and 1>r1>r2>0.

[0015] As a preferred solution of the present invention, the specific steps of processing the real-time cooling data and adjusting the operating power of the refrigeration module according to the processing results are: The specific steps of processing the real-time cooling data and adjusting the operating power of the refrigeration module according to the processing results are: Constructing a cooling capacity expression model Qice = (Ti swr-Ti sws)*LPM*C ρw *60, where ΔTiswr is the return water temperature of the cold storage pipe coolant, Tisws is the supply water temperature of the cold storage pipe coolant, LPM is the water flow rate of the cold storage pipe coolant, Q ice The power consumption model P is constructed based on the cold load capacity expression model of the cold storage pipe. ice =a cp +b cp Q ice +C cp Q 2 ice +d cp Q 3 ice , where Pice is the cooling power, a cp 、b cp 、c cp d cp It's Q ice The regression coefficient is obtained, and then the least square method is used to fit the cooling load capacity expression of the ice storage tank with the power consumption expression to obtain the operation curve of the cooling capacity and output electric power of the ice storage tank. The current operation parameters of the refrigeration module are input into the standard load curve to obtain the theoretical cooling capacity data of the cold storage pipe. The theoretical cooling capacity data is compared with the real-time cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is lower than the threshold, it indicates that the operating power of the refrigerant is too high. The controller adjusts the operating power of the refrigeration module to the corresponding value of the theoretical cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is higher than the threshold, it indicates that the theoretical cooling capacity cannot be achieved under the operating power. The controller increases the operating power of the refrigeration module. After the refrigeration module runs stably for a period of time, the control adjustment unit compares the theoretical cooling capacity data with the real-time cooling capacity data again according to the data of the measurement module, and repeats the above process until the difference between the real-time cooling capacity data and the theoretical cooling capacity data is within the threshold range. When the cold storage pipe temperature data detected by the measurement module reaches the optimal cold storage temperature, the central console adjusts the operating power of the refrigeration module to the theoretical operating power corresponding to the optimal cold storage temperature.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] 1. In the present invention, a solidification degree model of the coolant in the cold storage pipe is constructed by a parameter determination unit, and a real-time cooling capacity model of the cold storage pipe is established according to the constructed solidification degree model of the coolant in the cold storage pipe. The central console collects the difference of the accumulated cooling capacity at the same time point in the past to obtain the current cooling capacity for the whole day, and determines the optimal cold storage temperature of the cold storage pipe according to the current cooling capacity for the whole day. The central console starts the refrigeration module, and the refrigeration module starts to cool the coolant in the cold storage pipe. The measurement module detects the temperature data inside and outside the cold storage pipe and inputs the temperature data into the central console. The control adjustment unit in the central console inputs the temperature data into the real-time cooling capacity model, thereby obtaining the real-time cooling capacity data of the current cold storage pipe, processing the real-time cooling capacity data, and adjusting the operating power of the refrigeration module according to the processing result. When the cold storage pipe is storing cold, the cooling capacity can be adjusted according to the processing result. The system uses previous operating data to determine the current cold storage parameters, and adjusts the operating status of the refrigerator according to the real-time cooling capacity of the cold storage pipe. It has a high degree of intelligence and can control the temperature of the cold storage pipe more accurately. At the same time, the fault judgment unit receives the measurement data input by the measurement module, and screens the measurement data to remove abnormal data. The fault judgment unit selects the abnormal detection measurement module according to the GPS data in the abnormal data. The fault judgment unit extracts data from multiple groups of other measurement modules located near the abnormal detection measurement module, and compares the data of other measurement modules with the data of the abnormal measurement module, so as to determine whether the measurement module or the cold storage pipe has a fault, which further improves the intelligence of the system and solves the problems of simple temperature control, low intelligence and poor control effect of the existing cold storage pipe during cooling.

[0018] 2. In the present invention, by arranging a thermocouple and a clamp in the measuring box, when inspecting the measuring module, the measuring module can be inspected without damaging the cold storage tube, which is convenient for inspection and solves the problem that the existing cold storage tube measuring module is generally fixedly installed and inconvenient for inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the overall hardware structure of the present invention;

[0020] Figure 2 It is a schematic diagram of the system block structure of the present invention;

[0021] Figure 3 This is a schematic diagram of the three-dimensional structure of the refrigeration module of the present invention;

[0022] Figure 4 This is a schematic diagram of the three-dimensional structure of the measurement module of the present invention;

[0023] Figure 5 It is a front cross-sectional view of the measurement module of the present invention;

[0024] Figure 6 For the present invention Figure 5 Enlarged view of point A in the middle.

[0025] In the figure: 1. Central console; 2. Measuring module; 3. Refrigeration module; 4. Temperature control software; 5. Parameter determination unit; 6. Fault judgment unit; 7. Control adjustment unit; 201. Measuring box; 202. Temperature sensor; 203. Thermocouple; 204. Connecting sleeve; 205. Measuring rod; 206. Thermal grease; 207. Thermal insulation pad; 208. GPS locator; 209. Data transmitter; 210. Controller; 211. Terminal block; 212. Mounting clamp. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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 work are within the scope of protection of the present invention.

[0027] To facilitate understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0028] It should be noted that when an element is referred to as being "fixed on" another element, it may be directly on the other element or there may also be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may also be a central element. The terms "vertical", "horizontal", "left", "right" and similar expressions used in this article are for illustrative purposes only.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which the present invention belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0030] For examples, see Figure 1-6 , the present invention provides a technical solution:

[0031] An intelligent temperature control system for a cold storage pipe includes a central console 1, a measuring module 2 and a refrigeration module 3. The central console 1 is internally installed with a temperature control software 4, and the temperature control software 4 includes a parameter determination unit 5, a fault judgment unit 6 and a control adjustment unit 7;

[0032] The connection modes of the measuring module 2, the cooling module 3 and the central console 1 are all electrically connected, the cooling module 3 includes various cooling modules 3 with remote control functions, and the measuring module 2 is provided with multiple groups;

[0033] Further, the measuring module 2 includes a measuring box 201 fixedly connected to the outer wall of the cold storage tube, the outer wall of the measuring box 201 is provided with a temperature sensor 202, the interior of the measuring box 201 is provided with a thermocouple 203, the outer wall of the thermocouple 203 and the interior of the measuring box 201 are fixedly connected with a connecting sleeve 204, the interior of the connecting sleeve 204 and the outside of the measuring box 201 are slidably connected with a measuring rod 205, the connecting sleeve 204 is adhered to the measuring rod 205 by a thermal conductive silicone grease 206, and the measuring rod 205 is connected to the measuring rod 205 by a thermal conductive silicone grease 206. A heat insulation pad 207 is fixedly connected inside the measuring box 201 and on the outer wall of the connecting sleeve 204, a GPS locator 208 is fixedly connected inside the measuring box 201 and on the left side of the temperature sensor 202, a data transmitter 209 is fixedly connected to the top of the measuring box 201 and on the right side of the temperature sensor 202, a controller 210 is installed on the front of the measuring box 201, a terminal 211 is installed on the outer wall of the measuring box 201, and a mounting clamp 212 is fixedly connected to the bottom of the measuring box 201;

[0034] The measuring box 201 and the thermal insulation pad 207 are both made of thermal insulation materials, the measuring rod 205 penetrates and extends into the cold storage tube, the data transmitter 209 is connected to the central console 1 through a wireless data network, the connecting sleeve 204 and the measuring rod 205 are both made of copper, the thermocouple 203, the temperature sensor 202, the GPS locator 208, the data transmitter 209 and the terminal 211 are all electrically connected to the controller 210, the mounting clamp 212 is made of aluminum alloy, and two sets of mounting clamps 212 are provided.

[0035] Furthermore, the specific analysis steps of the parameter determination unit 5 are: the parameter determination unit 5 constructs a solidification degree model of the coolant in the cold storage tube, and establishes a real-time cooling capacity model of the cold storage tube based on the constructed solidification degree model of the coolant in the cold storage tube, the central control console 1 collects the difference in cumulative cooling capacity at the same time point in the past to obtain the current cooling capacity for the whole day, and determines the optimal cold storage temperature of the cold storage tube based on the current cooling capacity for the whole day.

[0036] Furthermore, the specific analysis steps of the fault judgment unit 6 are as follows: the fault judgment unit 6 receives the measurement data input by the measurement module 2, and screens the measurement data to remove abnormal data therefrom; the fault judgment unit 6 selects the abnormal detection measurement module 2 according to the GPS data in the abnormal data; the fault judgment unit 6 extracts data of multiple groups of other measurement modules 2 located near the abnormal detection measurement module 2, and compares the data of other measurement modules 2 with the data of the abnormal measurement module 2; if the difference between the data of other measurement modules 2 and the data of the abnormal measurement module 2 is lower than the threshold value, it indicates that the operation of the measurement module 2 is normal and the abnormal data is caused by the failure of the cold storage pipe; the fault judgment unit 6 sends a maintenance signal to the maintenance personnel, and the maintenance personnel repair the cold storage pipe at the position of the abnormal measurement module 2; if the difference between the data of other measurement modules 2 and the data of the abnormal measurement module 2 is higher than the threshold value, it indicates that the abnormal operation of the measurement module 2 causes the data to be abnormal; the fault judgment unit 6 sends a maintenance signal to the maintenance personnel, and the maintenance personnel repair the abnormal measurement module 2; the fault judgment unit 6 inputs the remaining normal data into the control adjustment unit 7.

[0037] Furthermore, the specific analysis steps of the control and adjustment unit 7 are as follows: the central console 1 starts the refrigeration module 3, the refrigeration module 3 starts to cool the coolant in the cold storage tube, the measurement module 2 detects the temperature data inside and outside the cold storage tube, and inputs the temperature data into the central console 1, the control and adjustment unit 7 in the central console 1 inputs the temperature data into the real-time cooling capacity model, thereby obtaining the real-time cooling capacity data of the current cold storage tube, processing the real-time cooling capacity data, and adjusting the operating power of the refrigeration module 3 according to the processing results.

[0038] Furthermore, the expression of the solidification degree model of the coolant in the cold storage tube is: The real-time cooling model expression is Q s =|tt 0 |*ΔH*M*θ s , where θ s Indicates the solidification degree of the cold storage unit. T is the real-time temperature in the cold storage unit. T and T 0 is the temperature of the two end points of the phase change process; a1 is the temperature at which 50% phase change occurs during the solidification process; 1 / b1 is the solidification enthalpy of the coolant, which indicates the ability of the material to absorb / release heat during phase change; ΔH is the average phase change rate, which is the average mass fraction of the coolant material in the cold storage tube that undergoes phase change every time it rises / falls 0.1°C.

[0039] Furthermore, the process of determining the optimal cold storage temperature is to obtain the current full-day cooling capacity by the difference between the accumulated cooling capacity at the same time point of the previous and next two days, and take the arithmetic mean of the past cooling capacity as the predicted cooling capacity, and compare the predicted cooling capacity with the theoretical maximum cooling capacity of the cold storage pipe. If the predicted cooling capacity ≥ r1*theoretical maximum cooling capacity, then it is determined that the optimal cold storage temperature is equal to the minimum cold storage temperature threshold; if r2*theoretical maximum cooling capacity < predicted cooling capacity < r1*theoretical maximum cooling capacity, then the optimal cold storage temperature is degree = minimum cold storage temperature threshold + (3*predicted cooling capacity / theoretical maximum cold storage capacity); if the predicted cooling capacity ≤ r2*theoretical maximum cold storage capacity, then the optimal cold storage temperature is determined to be equal to the maximum cold storage temperature threshold, where the theoretical maximum cold storage capacity = c*ρ*V*Δt, c is the specific heat capacity of cooling water, ρ is the density of water at the minimum cold storage temperature threshold, V is the cold storage volume, Δt is the temperature difference between the inlet and outlet, r1 and r2 are the first cold storage critical coefficient and the second cold storage critical coefficient respectively, and 1>r1>r2>0.

[0040] Furthermore, the specific steps of processing the real-time cooling capacity data and adjusting the operating power of the refrigeration module 3 according to the processing results are as follows: comparing the theoretical cooling capacity data with the real-time cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is lower than the threshold value, it indicates that the operating power of the refrigerant is too high. The central console 1 adjusts the operating power of the refrigeration module 3 to the corresponding value of the theoretical cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is higher than the threshold value, it indicates that the theoretical cooling capacity cannot be achieved under the operating power. The central console 1 will increase the operating power of the refrigeration module 3. After waiting for the refrigeration module 3 to operate stably for a period of time, the control adjustment unit 7 will compare the theoretical cooling capacity data with the real-time cooling capacity data again according to the data of the measuring module 2, and repeat the above process until the difference between the real-time cooling capacity data and the theoretical cooling capacity data is within the threshold range. When the cold storage pipe temperature data detected by the measuring module 2 reaches the optimal cold storage temperature, the central console 1 adjusts the operating power of the refrigeration module 3 to the theoretical operating power corresponding to the optimal cold storage temperature.

[0041] The working process of the present invention is as follows: When the intelligent temperature control system for cold storage pipes designed by the present invention is in operation, the measuring module 2 is installed in the cold storage pipe, the terminal 211 is connected to the external power supply by a wire, and the parameter determination unit 5 constructs a solidification degree model of the coolant in the cold storage pipe. According to the solidification degree model of the coolant in the cold storage tube, the real-time cooling capacity model Q of the cold storage tube is established. s =|tt 0 |*ΔH*M*θ s , where θ s Indicates the solidification degree of the cold storage unit. T is the real-time temperature in the cold storage unit. T and T 0is the temperature of the two end points of the phase change process; a1 is the temperature at which 50% phase change occurs during the solidification process; 1 / b1 is the solidification enthalpy of the coolant, which indicates the ability of the material to absorb / release heat during phase change; ΔH is the average phase change rate, which is the average mass fraction of the coolant material in the cold storage tube that undergoes phase change when it rises / decreases by 0.1°C;

[0042] The central console 1 collects the difference of the accumulated cooling capacity at the same time point in the past to obtain the current cooling capacity for the whole day, and takes the arithmetic mean of the past cooling capacity as the predicted cooling capacity, and compares the predicted cooling capacity with the theoretical maximum cooling capacity of the cold storage pipe. If the predicted cooling capacity ≥ r1*theoretical maximum cooling capacity, it is determined that the optimal cooling temperature is equal to the minimum cooling temperature threshold;

[0043] If r2*theoretical maximum cooling capacity < predicted cooling capacity < r1*theoretical maximum cooling capacity, then the optimal cooling temperature = minimum cooling temperature threshold + (3*predicted cooling capacity / theoretical maximum cooling capacity);

[0044] If the predicted cooling capacity is ≤ r2*theoretical maximum cold storage capacity, then the optimal cold storage temperature is determined to be equal to the maximum cold storage temperature threshold, where the theoretical maximum cold storage capacity = c*ρ*V*Δt, c is the specific heat capacity of cooling water, ρ is the density of water at the minimum cold storage temperature threshold, V is the cold storage volume, Δt is the temperature difference between the inlet and outlet, r1 and r2 are the first cold storage critical coefficient and the second cold storage critical coefficient respectively, and 1>r1>r2>0;

[0045] The central console 1 inputs a start signal to the controller 210, and the controller 210 starts the thermocouple 203, the temperature sensor 202, the GPS locator 208 and the data transmitter 209. The thermocouple 203 detects the internal temperature of the cold storage tube through the connecting sleeve 204 and the measuring rod 205, and the temperature sensor 202 detects the external temperature of the cold storage tube. The GPS locator 208 locates the measuring box 201, and the controller 210 inputs the internal and external temperature data of the cold storage tube and the positioning data into the central console 1 through the data transmitter 209;

[0046] The fault judgment unit 6 receives the measurement data input by the measurement module 2, and screens the measurement data to remove abnormal data. The fault judgment unit 6 selects the abnormal detection measurement module 2 according to the GPS data in the abnormal data. The fault judgment unit 6 extracts multiple groups of data of other measurement modules 2 located near the abnormal detection measurement module 2, and compares the data of other measurement modules 2 with the data of the abnormal measurement module 2. If the difference between the data of other measurement modules 2 and the data of the abnormal measurement module 2 is lower than the threshold value, it indicates that the operation of the measurement module 2 is normal and the abnormal data is caused by the failure of the cold storage pipe. The fault judgment unit 6 sends a maintenance signal to the maintenance personnel, and the maintenance personnel repair the cold storage pipe at the position of the abnormal measurement module 2. If the difference between the data of other measurement modules 2 and the data of the abnormal measurement module 2 is higher than the threshold value, it indicates that the operation of the measurement module 2 is abnormal and the data is abnormal. The fault judgment unit 6 sends a maintenance signal to the maintenance personnel, and the maintenance personnel repair the abnormal measurement module 2. The fault judgment unit 6 inputs the remaining normal data into the control adjustment unit 7;

[0047] The central console 1 starts the refrigeration module 3, and the refrigeration module 3 starts to cool the coolant in the cold storage pipe. The measuring module 2 detects the temperature data inside and outside the cold storage pipe and inputs the temperature data into the central console 1. The control adjustment unit 7 in the central console 1 inputs the temperature data into the real-time cooling capacity model, thereby obtaining the real-time cooling capacity data of the current cold storage pipe;

[0048] The control and adjustment unit 7 constructs the cooling capacity expression model of the cold storage pipe Qice = Tiswr-Tisws*LPM*C ρw *60, where ΔTi swr is the return water temperature of the cold storage pipe coolant, Tisws is the supply water temperature of the cold storage pipe coolant, LPM is the water flow rate of the cold storage pipe coolant, Q ice The power consumption model P is constructed based on the cold load capacity expression model of the cold storage pipe. ice =a cp +b cp Q ice +C cp Q 2 ice +d cp Q 3 ice , where P ice is the cooling power, a cp , b cp 、c cp d cp It's Q ice The regression coefficient is then used to fit the cooling load capacity expression of the ice storage tank with the power consumption expression using the least squares method to obtain the standard load curve of the cooling capacity and output electric power of the ice storage tank.

[0049] Input the current operating parameters of the refrigeration module 3 into the standard load curve to obtain the theoretical cold storage pipe cooling capacity data, and compare the theoretical cooling capacity data with the real-time cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is lower than the threshold value, it indicates that the operating power of the refrigerant is too high, and the central console 1 adjusts the operating power of the refrigeration module 3 to the corresponding value of the theoretical cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is higher than the threshold value, it indicates that the theoretical cooling capacity cannot be achieved under the operating power. The central console 1 will increase the operating power of the refrigeration module 3. After waiting for the refrigeration module 3 to operate stably for a period of time, the control adjustment unit 7 will compare the theoretical cooling capacity data with the real-time cooling capacity data again according to the data of the measuring module 2, and repeat the above process until the difference between the real-time cooling capacity data and the theoretical cooling capacity data is within the threshold range. When the cold storage pipe temperature data detected by the measuring module 2 reaches the optimal cold storage temperature, the central console 1 adjusts the operating power of the refrigeration module 3 to the theoretical operating power corresponding to the optimal cold storage temperature.

[0050] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A cold storage pipe intelligent temperature adjustment control system, comprising a central control console (1), a measuring module (2) and a refrigeration module (3), characterized in that: The central control console (1) is internally installed with temperature control software (4), and the temperature control software (4) comprises a parameter determination unit (5), a fault judgment unit (6) and a control adjustment unit (7).

2. According to claim 1, the intelligent temperature regulation and control system for cold storage pipes is characterized in that: The measuring module (2) comprises a measuring box (201) fixedly connected to the outer wall of the cold storage tube, the outer wall of the measuring box (201) is provided with a temperature sensor (202), the interior of the measuring box (201) is provided with a thermocouple (203), the outer wall of the thermocouple (203) and the interior of the measuring box (201) are fixedly connected with a connecting sleeve (204), the interior of the connecting sleeve (204) and the exterior of the measuring box (201) are slidably connected with a measuring rod (205), the connecting sleeve (204) is adhered to the measuring rod (205) by means of thermal conductive silicone grease (206), and the measuring A heat insulation pad (207) is fixedly connected inside the box (201) and on the outer wall of the connecting sleeve (204); a GPS locator (208) is fixedly connected inside the measuring box (201) and on the left side of the temperature sensor (202); a data transmitter (209) is fixedly connected at the top of the measuring box (201) and on the right side of the temperature sensor (202); a controller (210) is installed on the front of the measuring box (201); a terminal (211) is installed on the outer wall of the measuring box (201); and a mounting clamp (212) is fixedly connected to the bottom of the measuring box (201).

3. The intelligent temperature regulation and control system for cold storage pipes according to claim 1 is characterized in that: The connection modes of the measuring module (2), the refrigeration module (3) and the central control console (1) are all electrical connections; the refrigeration module (3) includes various refrigeration modules (3) with remote control functions; and the measuring module (2) is provided with a plurality of groups.

4. The intelligent temperature regulation and control system for cold storage pipes according to claim 1 is characterized in that: The specific analysis steps of the parameter determination unit (5) are as follows: the parameter determination unit (5) constructs a solidification degree model of the coolant in the cold storage tube, and establishes a real-time cooling capacity model of the cold storage tube based on the constructed solidification degree model of the coolant in the cold storage tube; the central control console (1) collects the difference of the accumulated cooling capacity at the same time point in the past to obtain the current cooling capacity for the whole day, and determines the optimal cooling temperature of the cold storage tube based on the current cooling capacity for the whole day.

5. The intelligent temperature regulation and control system for cold storage pipes according to claim 1 is characterized in that: The specific analysis steps of the fault judgment unit (6) are as follows: the fault judgment unit (6) receives the measurement data input by the measurement module (2), and screens the measurement data to remove abnormal data; the fault judgment unit (6) selects the abnormal detection measurement module (2) according to the GPS data in the abnormal data; the fault judgment unit (6) extracts data of multiple groups of other measurement modules (2) located near the abnormal detection measurement module (2), and compares the data of the other measurement modules (2) with the data of the abnormal measurement module (2); if the difference between the data of the other measurement modules (2) and the data of the abnormal measurement module (2) is small, the fault judgment unit (6) selects the abnormal detection measurement module (2); If the value of the abnormal data is greater than the threshold, it indicates that the measurement module (2) is operating normally and the abnormal data is caused by the fault of the cold storage tube. The fault judgment unit (6) sends a maintenance signal to the maintenance personnel, who repair the cold storage tube at the location of the abnormal measurement module (2). If the difference between the data of other measurement modules (2) and the data of the abnormal measurement module (2) is greater than the threshold, it indicates that the abnormal data is caused by the abnormal operation of the measurement module (2). The fault judgment unit (6) sends a maintenance signal to the maintenance personnel, who repair the abnormal measurement module (2). The fault judgment unit (6) inputs the remaining normal data into the control adjustment unit (7).

6. The intelligent temperature regulation and control system for cold storage pipes according to claim 1 is characterized in that: The specific analysis steps of the control adjustment unit (7) are as follows: the central control console (1) starts the refrigeration module (3), the refrigeration module (3) starts to cool the coolant in the cold storage pipe, the measurement module (2) detects the temperature data inside and outside the cold storage pipe, and inputs the temperature data into the central control console (1), the control adjustment unit (7) in the central control console (1) inputs the temperature data into the real-time cooling capacity model, thereby obtaining the real-time cooling capacity data of the current cold storage pipe, processing the real-time cooling capacity data, and adjusting the operating power of the refrigeration module (3) according to the processing results.

7. The intelligent temperature regulation and control system for cold storage pipes according to claim 2 is characterized in that: The measuring box (201) and the heat insulation pad (207) are both made of heat-insulating materials. The measuring rod (205) penetrates and extends into the cold storage tube. The data transmitter (209) is connected to the central console (1) via a wireless data network. The connecting sleeve (204) and the measuring rod (205) are both made of red copper. The thermocouple (203), the temperature sensor (202), the GPS locator (208), the data transmitter (209) and the terminal (211) are all connected to the controller (210) in an electrical manner. The mounting clamp (212) is made of aluminum alloy. Two groups of the mounting clamp (212) are provided.

8. The intelligent temperature regulation and control system for cold storage pipes according to claim 5 is characterized in that: The expression of the solidification degree model of the coolant in the cold storage tube is: The real-time cooling model expression is Q s =|t-t0|*ΔH*M*θ s , where θ s It indicates the solidification degree of the cold storage unit, T is the real-time temperature in the cold storage unit, T and T0 are the temperatures at the two ends of the phase change process; a1 is the temperature when 50% phase change occurs during the solidification process, 1 / b1 is the solidification enthalpy of the coolant, which indicates the ability of the material to absorb / release heat during phase change, ΔH is the average phase change rate, which is the average mass fraction of the coolant material in the cold storage tube that undergoes phase change every time the temperature rises / falls by 0.1°C.

9. The intelligent temperature regulation and control system for cold storage pipes according to claim 5 is characterized in that: The process of determining the optimal cold storage temperature is to obtain the current full-day cooling capacity by the difference of the accumulated cooling capacity at the same time point of the two days before and after, and take the arithmetic mean of the past cooling capacity as the predicted cooling capacity, and compare the predicted cooling capacity with the theoretical maximum cooling capacity of the cold storage pipe. If the predicted cooling capacity ≥ r1*theoretical maximum cooling capacity, then it is determined that the optimal cold storage temperature is equal to the minimum cold storage temperature threshold; if r2*theoretical maximum cooling capacity < predicted cooling capacity < r1*theoretical maximum cooling capacity, then the optimal cold storage temperature = Minimum cold storage temperature threshold + (3*predicted cooling capacity / theoretical maximum cold storage capacity); if the predicted cooling capacity ≤ r2*theoretical maximum cold storage capacity, then determine that the optimal cold storage temperature is equal to the maximum cold storage temperature threshold, wherein the theoretical maximum cold storage capacity = c*ρ*V*Δt, c is the specific heat capacity of cooling water, ρ is the density of water at the minimum cold storage temperature threshold, V is the cold storage volume, Δt is the temperature difference between the inlet and outlet, r1 and r2 are the first cold storage critical coefficient and the second cold storage critical coefficient, respectively, and 1>r1>r2>0.

10. The intelligent temperature regulation and control system for cold storage pipes according to claim 6, characterized in that: The specific steps of processing the real-time cooling data and adjusting the operating power of the refrigeration module (3) according to the processing results are as follows: constructing a cooling capacity expression model Qice = (Tiswr-Tisws)*LPM*C ρw *60, where ΔTiswr is the return water temperature of the cold storage pipe coolant, Tisws is the supply water temperature of the cold storage pipe coolant, LPM is the water flow rate of the cold storage pipe coolant, Q ice The power consumption model P is constructed based on the cold load capacity expression model of the cold storage pipe. ice =a cp +b cp Q ice +C cp Q 2 ice +d cp Q 3 ice , where P ice is the cooling power, a cp 、b cp 、c cp d cp It's Q ice The regression coefficient is then used to fit the cooling load capacity expression of the ice storage tank with the power consumption expression using the least square method to obtain the operating curve of the cooling capacity and output electric power of the ice storage tank. The current operating parameters of the refrigeration module (3) are input into the standard load curve to obtain theoretical cooling capacity data of the cold storage pipe. The theoretical cooling capacity data is compared with the real-time cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is lower than the threshold value, it indicates that the operating power of the refrigerant is too high. The controller adjusts the operating power of the refrigeration module (3) to the corresponding value of the theoretical cooling capacity data. If the difference between the real-time cooling capacity data and the theoretical cooling capacity data is If the value is higher than the threshold, it indicates that the theoretical cooling capacity cannot be achieved under the operating power. The controller will increase the operating power of the refrigeration module (3). After the refrigeration module (3) has been running stably for a period of time, the control adjustment unit (7) will compare the theoretical cooling capacity data with the real-time cooling capacity data again based on the data of the measurement module (2). The above process is repeated until the difference between the real-time cooling capacity data and the theoretical cooling capacity data is within the threshold range. When the cold storage pipe temperature data detected by the measurement module (2) reaches the optimal cold storage temperature, the central control console (1) adjusts the operating power of the refrigeration module (3) to the theoretical operating power corresponding to the optimal cold storage temperature.

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