A method for controlling a refrigeration device

Abstract

The invention discloses a method for controlling a refrigeration device, and relates to the technical field of refrigeration device control. The method for controlling a refrigeration device obtains the current internal temperature value of a cooling bin, the target cooling temperature value of a fish body of a marine fish school to be cooled, and the fish body state data of each marine fish in the marine fish school to be cooled, and performs preprocessing analysis to obtain the cooling energy demand value of the refrigeration device; after the marine fish school to be cooled is placed in the cooling bin, the initial state data of the coolant of the refrigeration device is obtained. The invention monitors the fish body temperature in real time during the cooling process, and dynamically adjusts the flow rate of the coolant in combination with the actual temperature deviation and the remaining time period, thereby effectively solving the drawbacks of fixed flow rate control in the traditional method, so that the cooling process can respond to the temperature change of the fish body in real time. Under the precise control of the coolant flow rate and temperature, the cooling process becomes more flexible, which helps to maintain the freshness of the fish and prevent over-cooling or under-cooling.

Description

Technical Field

[0001] The present invention relates to the technical field of refrigeration equipment control, and in particular to a method for controlling refrigeration equipment. Background Art

[0002] With the rapid development of cold chain logistics and food preservation technology, refrigeration equipment plays a vital role in the transportation and storage of perishable foods such as aquatic products and meat. In particular, high-value aquatic products such as marine fish have very strict requirements on refrigeration temperature and cooling rate. Improper temperature control will not only affect its freshness, but also lead to quality degradation, nutrient loss, and even economic losses. Traditional refrigeration equipment usually relies on ambient temperature monitoring and manual adjustment to achieve temperature control, and lacks the ability to dynamically respond to cooling needs.

[0003] Existing cooling systems generally use a fixed cooling flow rate and a simple temperature control mechanism. It is difficult to adjust the coolant flow rate according to the actual state of the object to be cooled and the real-time temperature changes, resulting in low cooling efficiency and limited refrigeration effect. This extensive cooling mode often causes increased cooling energy consumption and increased equipment wear. In addition, overcooling or insufficient cooling is prone to occur during the cooling process, affecting the preservation effect of food.

[0004] The limitations of the existing technologies include at least the following problems. First, in traditional refrigeration equipment control, preliminary cooling planning is usually only carried out through ambient temperature or preset temperature targets, which is limited to rough energy demand estimation and fails to fully consider the specific physical properties of the object to be cooled and the dynamic changes in the cooling process, which can easily lead to low cooling efficiency, increased energy consumption, and often insufficient cooling or overcooling. Secondly, most of the existing technologies lack dynamic monitoring and feedback adjustment mechanisms for the real-time cooling process. Usually, the refrigeration equipment is operated according to fixed parameters after it is started, and it is difficult to adjust the flow rate and cooling power in real time according to temperature changes in the cooling process. In addition, traditional cooling control methods are difficult to achieve dynamic optimization management of the coolant flow rate. The setting of the refrigerant flow rate is usually based on empirical values ​​or simple set values, lacking a scientific calculation basis, which can easily lead to unreasonable use of the coolant, which not only wastes energy, but also increases cooling costs and affects cooling efficiency. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method for controlling refrigeration equipment, which solves the problem that in traditional refrigeration equipment control, preliminary cooling planning is usually only carried out through ambient temperature or preset temperature targets, which is limited to rough energy demand estimation and fails to fully consider the specific physical properties of the object to be cooled itself and the dynamic changes in the cooling process, which easily leads to low cooling efficiency, increased energy consumption, and often insufficient cooling or overcooling. Secondly, most of the prior art lacks a dynamic monitoring and feedback adjustment mechanism for the real-time cooling process. Usually, the refrigeration equipment is operated according to fixed parameters after it is started, and it is difficult to adjust the flow rate and cooling power in real time according to the temperature changes in the cooling process. In addition, traditional cooling control methods are difficult to achieve dynamic optimization management of the coolant flow rate. The setting of the refrigerant flow rate is usually based on empirical values ​​or simple set values, lacks scientific calculation basis, and easily leads to unreasonable use of coolant, which not only wastes energy, but also increases cooling costs and affects cooling efficiency.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for controlling refrigeration equipment, comprising the following steps: obtaining the current internal temperature value of a cooling bin, the target cooling temperature value of the fish bodies of the marine fish school to be cooled, and the fish body status data of each marine fish in the marine fish school to be cooled, and preprocessing the fish body status data, wherein the fish body status data includes the fish body weight value and the fish body specific heat capacity value; comprehensively analyzing the preprocessed current internal temperature value of the cooling bin, the target cooling temperature value of the fish bodies of the marine fish school to be cooled, and the fish body status data of each marine fish in the marine fish school to be cooled to obtain the cooling energy demand value of the refrigeration equipment in the cooling bin; After the marine fish school is placed in the cooling bin, the initial state data of the coolant of the refrigeration equipment in the cooling bin is obtained, and a comprehensive analysis is performed in combination with the current internal temperature value of the cooling bin, the cooling energy demand value of the refrigeration equipment, and the preset cooling time to obtain the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin; the marine fish school to be cooled is refrigerated in the cooling bin based on the cooling energy demand value of the refrigeration equipment and the cooling flow rate value of the coolant in the refrigeration equipment, and real-time monitoring is performed, and the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin is adjusted based on the real-time monitoring results; wherein, the specific formula for calculating the cooling energy demand value of the refrigeration equipment of the cooling bin is as follows: ;in, is the cooling energy demand value of the refrigeration equipment of the cooling warehouse, For the first The weight of marine fish, For the first The specific heat capacity of the fish body of a marine fish, is the current internal temperature of the cooling chamber, is the target cooling temperature value of the fish body of the marine fish to be cooled, , The number of marine fish in the marine fish school to be cooled.

[0007] Furthermore, the initial state data of the coolant in the refrigeration equipment in the cooling bin specifically include a specific heat capacity value, an initial temperature value, and a density value of the coolant in the refrigeration equipment in the cooling bin.

[0008] Furthermore, the specific steps for obtaining the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin are as follows: perform temperature difference analysis on the current internal temperature value of the cooling bin and the initial temperature value of the coolant in the refrigeration equipment in the cooling bin to obtain the temperature difference value of the coolant between the cooling bin and the refrigeration equipment; perform a comprehensive analysis on the temperature difference value of the coolant in the cooling bin and the refrigeration equipment, the cooling energy demand value of the refrigeration equipment in the cooling bin, the preset cooling time, and the specific heat capacity value, initial temperature value, and density value of the coolant in the refrigeration equipment in the cooling bin to obtain the cooling flow rate value of the coolant in the refrigeration equipment in the cooling bin.

[0009] Furthermore, the specific formula for calculating the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin is as follows: ;in, is the cooling flow rate of the coolant in the refrigeration equipment of the cooling bin, is the cooling energy demand value of the refrigeration equipment, is the specific heat capacity of the coolant in the refrigeration equipment of the cooling bin, is the initial temperature value of the coolant in the refrigeration equipment of the cooling bin, The current internal temperature of the cooling chamber. is the density of the coolant in the refrigeration equipment of the cooling bin, The preset cooling time.

[0010] Furthermore, the specific steps for adjusting the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the real-time monitoring results are as follows: divide the preset cooling time into several time periods, and predict the predicted temperature value of the fish body cooling period in each future time period of the marine fish school to be cooled in the cooling bin; when the marine fish school to be cooled is refrigerated in the cooling bin, obtain the real-time temperature value of the fish body of the marine fish school to be cooled in each future time period in the cooling bin in real time, and perform real-time temperature judgment and analysis in combination with the predicted temperature value of the fish body cooling period in the corresponding time period, and adjust the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the judgment and analysis results.

[0011] Furthermore, the specific steps for predicting the predicted temperature value of the cooling period of the marine fish to be cooled in each future period in the cooling bin are as follows: obtaining the initial temperature value of the fish body of the marine fish to be cooled; inputting the initial temperature value of the fish body of the marine fish to be cooled and the current internal temperature value of the cooling bin into the cooling temperature analysis model for predictive analysis, and obtaining the predicted temperature value of the cooling period of the fish body of the marine fish to be cooled in each future period in the cooling bin.

[0012] Furthermore, the cooling temperature analysis model is as follows: ;in, For the future of cooling marine fish in the cooling chamber The predicted value of the fish cooling temperature during each period, is the current internal temperature of the cooling chamber, is the initial temperature of the fish body to be cooled, is a natural constant, is the cooling coefficient stored in the database, , The number of time periods.

[0013] Furthermore, the specific steps of adjusting the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the judgment and analysis results are as follows: compare and analyze in real time the real-time temperature value of the fish body of the marine fish school to be cooled in each future period in the cooling bin with the predicted value of the fish body cooling period temperature in the corresponding period; if there is a period when the real-time temperature value of the fish body of the marine fish school to be cooled in the cooling bin does not meet the predicted value of the fish body cooling period temperature, analyze the real-time temperature deviation value of the fish body; analyze the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin in the remaining period based on the real-time temperature deviation value of the fish body; in the remaining period, take speed adjustment measures for the coolant in the refrigeration equipment of the cooling bin based on the cooling flow rate adjustment value.

[0014] Furthermore, the specific formula for calculating the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin in the remaining period is as follows: ;in, is the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin during the remaining period, is the cooling flow rate of the coolant in the refrigeration equipment of the cooling bin, is the cooling adjustment factor, It is the real-time temperature deviation value of the fish body.

[0015] Furthermore, the specific steps of calculating the cooling adjustment coefficient are as follows: counting the number of remaining time periods when the real-time temperature value of the fish body of the marine fish to be cooled in the cooling chamber does not meet the temperature prediction value of the fish body cooling period; inputting the real-time temperature deviation value of the fish body and the number of remaining time periods into the adjustment analysis model for comprehensive analysis to obtain the cooling adjustment coefficient; wherein the adjustment analysis model is as follows: ;in, is the cooling adjustment factor, is the basic adjustment constant stored in the database, is a natural constant, is the sensitivity coefficient stored in the database, is the real-time temperature deviation value of the fish body, The number of remaining time periods.

[0016] The present invention has the following beneficial effects:

[0017] (1) The method for controlling the refrigeration equipment monitors the temperature of the fish body in real time during the cooling process, and dynamically adjusts the flow rate of the coolant in combination with the actual temperature deviation and the remaining time period, thereby effectively solving the drawbacks of the fixed flow rate control in the traditional method, so that the cooling process can respond to the temperature changes of the fish body in real time. Under the precise control of the coolant flow rate and temperature, the cooling process becomes more flexible, which helps to maintain the freshness of the fish and prevent over-cooling or under-cooling. In addition, dynamic adjustment can also optimize the operating state of the refrigeration equipment, reduce unnecessary start-up and shutdown, and extend the life of the equipment.

[0018] (2) The method for controlling the refrigeration equipment can accurately calculate the required cooling energy demand value by obtaining the state data of the fish body and combining it with the internal temperature of the cooling bin and the initial state parameters of the coolant, so that the refrigeration equipment can accurately match the cooling demand, avoiding the phenomenon of insufficient cooling or excessive cooling, and improving the cooling efficiency. Compared with the traditional simple temperature control method, it pays more attention to the energy consumption management in the cooling process, effectively reduces the energy consumption while meeting the cooling demand, and achieves a higher energy-saving effect.

[0019] (3) The method for controlling the refrigeration equipment introduces a cooling temperature analysis model and an adjustment analysis model, and realizes precise control of the cooling flow rate through the predicted value of the fish body temperature and the cooling adjustment coefficient. By inputting the initial temperature of the fish body, the temperature of the cooling chamber and the coolant state data into the prediction model, the temperature change in each period of the cooling process can be accurately predicted, so that the temperature change trend can be predicted in advance and the flow rate can be adjusted, avoiding the lag of passive regulation, thereby greatly improving the intelligence of the cooling process and the accuracy of control, and ensuring the safety and efficiency of the operation of the refrigeration equipment.

[0020] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The present invention is a flow chart of a method for controlling a refrigeration device.

[0022] Figure 2 The present invention is a flowchart of the steps in a method for controlling a refrigeration device.

[0023] Figure 3 The present invention is a flowchart of the steps in a method for controlling a refrigeration device. DETAILED DESCRIPTION

[0024] The embodiment of the present application solves the problem that in traditional refrigeration equipment control, only preliminary cooling planning is usually carried out through ambient temperature or preset temperature targets, which is limited to rough energy demand estimation and fails to fully consider the specific physical properties of the object to be cooled and the dynamic changes in the cooling process, which easily leads to low cooling efficiency, increased energy consumption, and often insufficient cooling or overcooling. Secondly, most of the existing technologies lack dynamic monitoring and feedback adjustment mechanisms for real-time cooling processes. Usually, the refrigeration equipment is operated according to fixed parameters after startup, and it is difficult to adjust the flow rate and cooling power in real time according to temperature changes in the cooling process. In addition, traditional cooling control methods are difficult to achieve dynamic optimization management of coolant flow rate. The setting of the refrigerant flow rate is usually based on empirical values ​​or simple set values, lacks scientific calculation basis, and easily leads to unreasonable use of coolant, which not only wastes energy, but also increases cooling costs and affects cooling efficiency.

[0025] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0026] First, the current internal temperature of the cooling chamber, the target cooling temperature of the marine fish to be cooled, and the state data of the fish (such as the weight and specific heat capacity of each fish) are obtained, and these data are preprocessed. This step is to lay the foundation for the subsequent calculation of cooling energy demand and determination of cooling flow rate. Next, the preprocessed temperature and fish state data are comprehensively analyzed to calculate the cooling energy demand value. Then, after the fish are placed in the cooling chamber, the initial state data of the coolant (specific heat capacity, initial temperature, density) is obtained, and the initial cooling flow rate value of the coolant is calculated in combination with the cooling energy demand, temperature difference and preset cooling time. During the cooling process, the fish body temperature is monitored in real time and compared with the predicted temperature. If there is a deviation between the actual temperature and the predicted temperature, the flow rate of the coolant is dynamically adjusted based on the deviation value and the remaining cooling period to ensure that the cooling process is more accurate and efficient.

[0027] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for controlling a refrigeration device, comprising the following steps: obtaining a current internal temperature value of a cooling bin (measured in real time by a temperature sensor installed inside the cooling bin), a target cooling temperature value of a fish body of a school of marine fish to be cooled (obtained from cold chain transportation or food safety regulations), and fish body status data of each marine fish in the school of marine fish to be cooled, and preprocessing the fish body status data, wherein the fish body status data includes a fish body weight value (automatically measured by a weighing sensor on a conveyor belt), a fish body specific heat capacity value (specific heat capacity value is searched and retrieved from a database according to the fish species); the current internal temperature value of the cooling bin after preprocessing, the target cooling temperature value of the fish body of the school of marine fish to be cooled, and the fish body status data of each marine fish in the school of marine fish to be cooled; A comprehensive analysis is performed on the body status data of each marine fish in the cooled marine fish school to obtain the cooling energy demand value of the refrigeration equipment in the cooling bin; after the marine fish school to be cooled is placed in the cooling bin, the initial status data of the coolant in the refrigeration equipment in the cooling bin is obtained, and a comprehensive analysis is performed in combination with the current internal temperature value of the cooling bin, the cooling energy demand value of the refrigeration equipment, and the preset cooling time to obtain the cooling flow rate value of the coolant in the refrigeration equipment in the cooling bin; in the cooling bin, the marine fish school to be cooled is refrigerated based on the cooling energy demand value of the refrigeration equipment and the cooling flow rate value of the coolant in the refrigeration equipment, and real-time monitoring is performed, and the cooling flow rate value of the coolant in the refrigeration equipment in the cooling bin is adjusted based on the real-time monitoring result.

[0028] The specific formula for calculating the cooling energy demand value of the refrigeration equipment of the cooling bin is as follows: ;in, is the cooling energy demand value of the refrigeration equipment of the cooling warehouse, For the first The weight of marine fish, For the first The specific heat capacity of the fish body of a marine fish, is the current internal temperature of the cooling chamber, is the target cooling temperature value of the fish body of the marine fish to be cooled, , The number of marine fish in the marine fish school to be cooled.

[0029] The initial state data of the coolant in the refrigeration equipment in the cooling bin specifically include the specific heat capacity value of the coolant in the refrigeration equipment in the cooling bin (obtained by searching in the material database or engineering manual), the initial temperature value (measured by the temperature sensor in the coolant pipeline or cooling equipment), and the density value (obtained by searching in the material manual or database).

[0030] Specifically, Figure 2As shown, the specific steps for obtaining the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin are as follows: perform temperature difference analysis on the current internal temperature value of the cooling bin and the initial temperature value of the coolant in the refrigeration equipment in the cooling bin (this value is the temperature value of the refrigerant added after the marine fish to be cooled enters the cooling bin, so the temperature is different from the current internal temperature value of the cooling bin) to obtain the temperature difference value of the coolant in the cooling bin and the refrigeration equipment; perform a comprehensive analysis on the temperature difference value of the coolant in the cooling bin and the refrigeration equipment, the cooling energy demand value of the refrigeration equipment in the cooling bin, the preset cooling time, and the specific heat capacity value, initial temperature value, and density value of the coolant in the refrigeration equipment in the cooling bin to obtain the cooling flow rate value of the coolant in the refrigeration equipment in the cooling bin.

[0031] The specific formula for calculating the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin is as follows: ;in, is the cooling flow rate of the coolant in the refrigeration equipment of the cooling bin, is the cooling energy demand value of the refrigeration equipment, is the specific heat capacity of the coolant in the refrigeration equipment of the cooling bin, is the initial temperature value of the coolant in the refrigeration equipment of the cooling bin, The current internal temperature of the cooling chamber. is the density of the coolant in the refrigeration equipment of the cooling bin, The preset cooling time.

[0032] In this embodiment, by obtaining the temperature difference between the current internal temperature of the cooling bin and the initial temperature of the coolant, the required temperature adjustment range can be accurately calculated, rather than just roughly adjusting according to the preset temperature range. Taking into account that the initial temperature of the coolant may be inconsistent with the current temperature of the cooling bin, the introduction of this difference makes the calculation more in line with actual operating conditions, which helps to reduce unnecessary energy consumption. After comprehensively analyzing parameters such as temperature difference, cooling energy demand, specific heat capacity and density of the coolant, a suitable cooling flow rate value can be obtained to ensure that the coolant flow and temperature can accurately meet the cooling needs, thereby improving the efficiency of the cooling process and avoiding excessive or insufficient cooling. Compared with the traditional single temperature control method, this method is more suitable for situations with high requirements on energy demand and cooling intensity. Through accurate pre-setting and control of the cooling time, the coolant flow rate can be dynamically adjusted during the cooling process. The preset cooling time enables the refrigeration equipment to be adjusted according to the needs of different stages during the cooling process, avoiding long-term operation at a fixed flow rate, which not only saves energy but also extends the service life of the equipment. The design not only improves the cooling efficiency, but also avoids the waste of coolant, reduces energy consumption, and improves the energy saving of refrigeration equipment. By accurately calculating the flow rate value of the coolant, the refrigeration equipment can maintain stable operation while reaching the target temperature, avoiding the problem of overcooling or insufficient temperature. In the case of too low flow rate, the cooling efficiency may not be enough; in the case of too high flow rate, it may cause overcooling and affect the quality of fish. This scheme ensures the precise control of flow rate by comprehensively considering factors such as temperature difference, energy demand and coolant characteristics, thereby ensuring the safety and stability of the cooling process. This method is also conducive to avoiding equipment wear or failure caused by improper coolant flow rate, reducing maintenance costs. Accurate flow rate control not only helps to achieve efficient cooling, but also maintains the smooth operation of refrigeration equipment throughout the cooling cycle, reduces the load of refrigeration equipment, and prevents the instability of refrigeration equipment caused by temperature fluctuations.

[0033] Specifically, Figure 3 As shown, the specific steps of adjusting the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the real-time monitoring results are as follows: dividing the preset cooling time into several time periods, and predicting the predicted value of the cooling period temperature of the marine fish to be cooled in each future time period in the cooling bin; when the marine fish to be cooled is refrigerated in the cooling bin, obtaining the real-time temperature value of the fish body of the marine fish to be cooled in each future time period in the cooling bin in real time, and performing real-time temperature judgment and analysis in combination with the predicted value of the cooling period temperature of the fish body in the corresponding time period, and adjusting the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the judgment and analysis results.

[0034] In this implementation, the preset cooling time is divided into several time periods, and the temperature of each time period is predicted, so that the refrigeration equipment can accurately grasp the temperature change trend of the fish body in each time period. This time-divided cooling control method can help the refrigeration equipment maintain optimal temperature control at each time node, ensuring that the fish body temperature gradually decreases according to the expected cooling curve. Real-time temperature judgment and analysis can enable the refrigeration equipment to make instant flow rate adjustments based on the difference between the real-time temperature value of the fish body and the predicted temperature value, ensuring more accurate temperature control. Compared with the traditional overall temperature control method, this time-divided, real-time monitoring method can more finely manage the cooling process and help avoid problems such as excessive or insufficient cooling. The real-time monitoring and dynamic adjustment mechanism can quickly respond to actual changes in fish body temperature, especially when the external environment or internal conditions of the cooling bin change. The refrigeration equipment can immediately adjust the coolant flow rate to adapt to new cooling needs. This rapid response mechanism not only helps to ensure the continued high efficiency of the cooling process, but also can adapt to complex The complex and changeable cooling needs improve the adaptability of refrigeration equipment to environmental changes. By dynamically adjusting the flow rate, the coolant flow rate can be gradually reduced during the cooling process to avoid overcooling when approaching the target temperature. This dynamic control method based on actual temperature deviation ensures the precise adjustment of the flow rate in each cooling period, making the cooling process more intelligent and flexible. The real-time monitoring and time-sharing control method makes the energy consumption of the cooling process more reasonable. By dynamically adjusting the coolant flow rate at different temperature stages, the refrigeration equipment can be prevented from continuously running at unnecessary high flow rates, saving energy consumption. This dynamic flow rate control based on temperature feedback can greatly reduce energy consumption during the cooling process and improve the overall energy efficiency of the refrigeration equipment. Dynamic flow rate adjustment can not only prevent the equipment from running for a long time under high load and reduce equipment wear, but also help reduce the maintenance and replacement costs caused by frequent start-stop or excessive operation of the refrigeration equipment. In the long run, the service life of the refrigeration equipment can be extended, and the reliability and stability of the equipment are also effectively guaranteed.

[0035] Specifically, the specific steps for predicting the temperature prediction value of the fish body cooling period of the marine fish school to be cooled in each future time period in the cooling bin are as follows: obtain the initial temperature value of the fish body of the marine fish school to be cooled (obtained by contact temperature measurement, non-contact temperature measurement, i.e., infrared thermometer measurement, or the seawater temperature value at the place where the marine fish school is captured); input the initial temperature value of the fish body of the marine fish school to be cooled and the current internal temperature value of the cooling bin into the cooling temperature analysis model for predictive analysis, so as to obtain the temperature prediction value of the fish body cooling period of the marine fish school to be cooled in each future time period in the cooling bin.

[0036] The cooling temperature analysis model is as follows: ;in, For the future of cooling marine fish in the cooling chamber The predicted value of the fish cooling temperature during each period, is the current internal temperature value of the cooling chamber, is the initial temperature of the fish body to be cooled, is a natural constant, is the cooling coefficient stored in the database, , The number of time periods.

[0037] It needs to be explained that the specific calculation process of the cooling coefficient is: put the marine fish to be cooled in the cooling chamber, record the initial internal temperature of the cooling chamber and the initial temperature of the fish body, record the change of the fish body temperature at a predetermined time interval, and obtain data for multiple time periods. In this way, the temperature change curve over time can be captured, which is used to fit the cooling model. The exponential decay model is used to fit the experimental data, because the cooling process usually exhibits an exponential decay trend of temperature over time. The collected time and temperature data are brought into the above-mentioned exponential decay model, and the cooling coefficient is fitted using regression analysis or least squares method. Through data fitting, an optimal cooling coefficient value is found so that the predicted temperature change curve is as close as possible to the actual measured temperature data. The fitted cooling coefficient value is applied to the new cooling process, and the error between the predicted temperature and the actual temperature is tested. If the error is within the allowable range, the cooling coefficient value is stored in the database as the cooling coefficient. If the error is large, it is necessary to further adjust the experimental conditions or use more data for refitting.

[0038] In this implementation example, the number of minutes in each period is 10 minutes, and an implementation example of calculating the predicted value of the cooling period temperature of the fish body of the marine fish to be cooled in the next two periods is as follows, and the following parameters are available:

[0039] The current internal temperature value of the cooling chamber is: 1°C.

[0040] The initial body temperature of the marine fish to be cooled is: 15°C.

[0041] The cooling factor stored in the database is: 0.2.

[0042] Substituting the above data into the cooling temperature analysis model, we get:

[0043] The predicted temperature of the first cooling period of the marine fish to be cooled in the future = 1 + (15-1) * e -0.2 =1+14*0.819=12.466°C.

[0044] The predicted value of the second cooling period temperature of the fish body of the marine fish to be cooled = 1 + (15-1) * e -0.4 =1+14*0.670=10.38°C.

[0045] In this implementation scheme, the cooling temperature analysis model is used to input the initial temperature of the fish body and the current internal temperature of the cooling bin, so as to accurately predict the temperature changes of the fish body in each future time period. This prediction method based on a mathematical model makes up for the shortcomings of the temperature curve set by experience in the traditional cooling process, making the temperature control of the cooling process more scientific. Through the fitting and optimization of the cooling coefficient, the model can fully adapt to the exponential decay trend of the temperature in the cooling process, ensuring that the predicted temperature curve is as close to the actual change as possible. In this way, the refrigeration equipment can control the temperature more accurately during the cooling process, avoid overcooling or insufficient cooling, and ensure the freshness and refrigeration quality of the fish. The temperature prediction by time period enables the refrigeration equipment to know the temperature trend of each future time period in advance, forming a temperature control "roadmap". On this basis, the refrigeration equipment can dynamically adjust the coolant flow rate according to the predicted temperature of each time period to improve the cooling efficiency. This method of advance prediction and dynamic adjustment enables the refrigeration equipment to be more It can respond to cooling needs more flexibly and intelligently. By accurately setting the time period length (for example, 10 minutes per period), the refrigeration equipment can dynamically update the temperature prediction data in a shorter time interval to ensure that the cooling process is more agile and efficient. Such a dynamic control mechanism can not only improve the adaptability of the refrigeration equipment, but also balance the relationship between energy consumption and effect in the cooling process to achieve more intelligent temperature regulation. The cooling temperature analysis model obtains the cooling coefficient through fitting to ensure that the refrigeration equipment maintains energy consumption at the lowest level while meeting the cooling demand. By accurately predicting the temperature changes in each period, the refrigeration equipment can reduce the coolant flow rate during periods when high-intensity cooling is not required, thereby saving energy consumption. Accurate temperature prediction and flow rate adjustment can avoid excessive use of coolant and frequent start and stop of equipment, reduce wear of refrigeration equipment, and reduce maintenance costs. This energy-saving control not only reduces the direct operating cost of the cooling process, but also extends the service life of the refrigeration equipment, making the refrigeration equipment more economical and efficient.

[0046] Specifically, the specific steps for adjusting the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the judgment and analysis results are as follows: compare and analyze in real time the real-time temperature value of the fish body of the marine fish to be cooled in each future period in the cooling bin with the predicted value of the fish body cooling period temperature in the corresponding period; if there is a period when the real-time temperature value of the fish body of the marine fish to be cooled in the cooling bin does not meet (i.e. is not equal to) the predicted value of the fish body cooling period temperature, analyze the real-time temperature deviation value of the fish body; analyze the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin in the remaining period based on the real-time temperature deviation value of the fish body; in the remaining period, take speed adjustment measures for the coolant in the refrigeration equipment of the cooling bin based on the cooling flow rate adjustment value.

[0047] The specific formula for calculating the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin during the remaining period is as follows: ;in, is the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin during the remaining period, is the cooling flow rate of the coolant in the refrigeration equipment of the cooling bin, is the cooling adjustment factor, It is the real-time temperature deviation value of the fish body.

[0048] In this implementation scheme, by comparing and analyzing the real-time temperature of each time period with the predicted temperature, the refrigeration equipment can find deviations in temperature control during the cooling process. If the real-time temperature does not match the predicted value, the refrigeration equipment can immediately analyze the deviation value to ensure that the temperature control is accurate and correct. Compared with the traditional fixed flow rate cooling method, this method is more adaptable to actual cooling needs and can respond to temperature changes in a timely manner to ensure that the temperature of the fish body always remains on the expected cooling track. Real-time temperature deviation analysis can prevent insufficient cooling or overcooling from occurring, and ensure the optimal refrigeration temperature range for fish. This not only improves the cooling effect, but also ensures the freshness and product quality of the fish. By adjusting the cooling flow rate based on the temperature deviation value, the refrigeration equipment can more flexibly adapt to temperature changes during the cooling process. Whenever the real-time temperature deviation exceeds the expected range, the refrigeration equipment can immediately adjust the coolant flow rate to prevent the temperature from continuing to deviate from the target. This dynamic adjustment mechanism improves the response speed of the refrigeration equipment, enabling the refrigeration equipment to quickly respond to changes in ambient temperature or fluctuations in cooling demand. Based on real-time adjustments in the remaining time period, the refrigeration equipment can flexibly adjust the cooling intensity according to the current temperature change trend. Compared with fixed parameters, The cooling mode of the number of operations is selected. This adjustment method effectively improves the flexibility of the refrigeration equipment without affecting the cooling efficiency. Dynamic adjustment of the coolant flow rate can prevent the refrigeration equipment from running at a high flow rate for a long time. When the temperature deviation is small, the refrigeration equipment can reduce the flow rate of the coolant and reduce energy consumption. Conversely, the flow rate is increased only when the temperature deviation is large. This on-demand control method realizes the optimal utilization of energy. Optimizing the flow rate of the coolant in the remaining period reduces the frequent start and stop and high-load operation of the equipment, extends the service life of the equipment, and reduces maintenance and operation costs. This on-demand dynamic adjustment not only saves energy, but also reduces equipment wear and tear, which helps to achieve long-term cooling cost control. Through real-time analysis and regulation, the refrigeration equipment can make independent judgments and adjustments, and has a certain level of intelligence. The adjustment strategy based on real-time temperature deviation enables the refrigeration equipment to automatically optimize the flow rate under different cooling requirements and achieve more intelligent temperature control. The introduction of this mechanism also improves the stability of the refrigeration equipment and avoids the problem of cooling out of control caused by excessive temperature deviation. The refrigeration equipment maintains a stable temperature control effect throughout the cooling cycle, effectively improving the safety and reliability of the cooling process.

[0049] Specifically, the specific steps for calculating the cooling adjustment coefficient are as follows: count the number of remaining time periods when the real-time temperature values ​​of the marine fish to be cooled in the cooling bin do not meet (i.e. are not equal to) the temperature prediction values ​​of the fish cooling period; input the real-time temperature deviation values ​​of the fish and the number of remaining time periods into the adjustment analysis model for comprehensive analysis to obtain the cooling adjustment coefficient.

[0050] The specific adjustment analysis model is as follows: ;in, is the cooling adjustment factor, is the basic adjustment constant stored in the database, is a natural constant, is the sensitivity coefficient stored in the database, is the real-time temperature deviation value of the fish body, The number of remaining time periods.

[0051] It needs to be explained that It determines the basic level of the cooling regulation coefficient when there are no other influencing factors. It sets the basic strength of the regulation action and reflects the design requirements of the refrigeration equipment, such as the maximum or minimum flow rate or energy output. This value is selected based on the design specifications of the refrigeration equipment, previous test results, and the requirements for the dynamic response of the refrigeration equipment. The specific calculation process is as follows: First, it is necessary to clarify the basic requirements that need to be met for regulating the refrigeration equipment, such as the maximum and minimum regulation range, the expected response time of the refrigeration equipment, and the stability requirements. These requirements determine the basic magnitude of the basic regulation constant, that is, the basic output level of the refrigeration equipment when there is no temperature difference. Check the values ​​of the basic regulation constants in similar refrigeration equipment or previous designs. This can provide a starting point to analyze the performance of previous refrigeration equipment under different basic regulation constant values, such as regulation speed, control accuracy, energy consumption, etc. Adjust the basic regulation constant in the experimental environment, observe the reaction of the refrigeration equipment to the setting changes, adjust the basic regulation constant to the optimal value found in the experiment, so that the refrigeration equipment can achieve a fast and smooth response, while avoiding over-regulation or oscillation. According to the feedback information collected in actual operation, continue to fine-tune the value of the basic regulation constant, and apply adaptive control theory or intelligent algorithms such as machine learning to dynamically adjust the basic regulation constant according to the performance of the refrigeration equipment.

[0052] The calculation logic of the regulation analysis model adopts the logistic function, so, To control the slope of the logistic function, that is, this parameter determines the sensitivity and reaction speed of the refrigeration equipment to temperature difference. The specific calculation process is as follows: determine the theoretical sensitivity coefficient range to provide a fast but smooth response of the refrigeration equipment, use a calculation model or simulation tool to simulate the impact of different sensitivity coefficient values ​​on the behavior of the refrigeration equipment, analyze the control effects under different sensitivity coefficients, such as response time, overshoot and steady-state error, implement different sensitivity coefficient values ​​in the control of the refrigeration equipment, conduct tests, observe the performance of the refrigeration equipment in actual operation, especially how the refrigeration equipment responds to rapidly changing temperature conditions, and adjust the sensitivity coefficient to the optimal value according to the test results and the needs of the refrigeration equipment.

[0053] The specific implementation example of calculating the cooling adjustment coefficient is as follows, with the following parameters:

[0054] The real-time temperature of the fish bodies of the marine fish to be cooled in the cooling chamber during a certain period is 11.45°C, and the predicted temperature of the fish bodies during the corresponding cooling period is 10.80°C, so the real-time temperature deviation of the fish bodies is 0.65°C.

[0055] The base adjustment constant stored in the database is 0.5.

[0056] The sensitivity factor stored in the database is 5.

[0057] The number of remaining time periods is 4.

[0058] Input the above data into the adjustment analysis model and obtain:

[0059] Cooling adjustment factor = 0.5 / ((1+e -0.5*0.65 )*4)≈0.1203.

[0060] In this implementation scheme, by analyzing the real-time temperature deviation value of the fish body and the remaining time period, the refrigeration equipment can adjust the cooling regulation coefficient in time to ensure that the cooling equipment responds quickly to the current temperature difference. The cooling regulation coefficient enables the refrigeration equipment to make flexible cooling adjustments according to different temperature differences and time conditions, effectively ensuring the real-time nature of the cooling process. Compared with traditional static refrigeration equipment, this dynamic adjustment based on the deviation value ensures that the temperature control is more real-time and accurate, and can respond quickly to temperature changes to ensure a more stable cooling effect. The cooling regulation coefficient is automatically adjusted based on real-time data and the historical operation of the refrigeration equipment, making the cooling process adaptive. Whether the temperature difference increases or the remaining time period decreases, the cooling regulation coefficient can be flexibly changed according to actual conditions, so that the refrigeration equipment always maintains the optimal flow rate or cooling intensity. The adjustment mechanism effectively reduces energy consumption through adaptive control, because the cooling intensity is increased only when needed. When the temperature difference is small, the refrigeration equipment will automatically reduce the flow rate, avoiding unnecessary energy consumption, and further improving the energy efficiency of the cooling process. The adjustment analysis model The basic adjustment constant and sensitivity coefficient in the model make the adjustment of the cooling adjustment coefficient have a scientific basis. The basic adjustment constant ensures the basic output level of the refrigeration equipment, while the sensitivity coefficient controls the sensitivity of the refrigeration equipment to temperature difference changes. This design ensures that the refrigeration equipment will not overreact when dealing with small temperature differences, and can respond quickly under large temperature differences to avoid over-adjustment or under-adjustment. This not only improves the stability of the cooling process, but also effectively prevents the influence of excessive temperature fluctuations on the refrigeration effect, making the fish cooling process more stable and reliable, thereby ensuring the freshness and quality of the fish. Through the adjustment of the cooling adjustment coefficient by the logistic function, the refrigeration equipment can automatically calculate the optimal flow rate of the coolant according to the real-time temperature deviation of the fish and the number of remaining time periods. This intelligent calculation process enables the refrigeration equipment to automatically optimize the operating parameters under various temperature requirements, and has a higher level of adaptability and intelligence. Especially when dealing with complex cooling requirements, the refrigeration equipment can make efficient cooling decisions without human intervention, laying the foundation for the automation and intelligent operation of the cooling warehouse.

[0061] In summary, this application has at least the following effects:

[0062] By real-time monitoring of the fish temperature during the cooling process and dynamically adjusting the coolant flow rate based on the actual temperature deviation and the remaining time period, the drawback of fixed flow rate control in the traditional method is effectively solved, so that the cooling process can respond to the temperature changes of the fish body in real time. Under the precise control of the coolant flow rate and temperature, the cooling process becomes more flexible, which helps to maintain the freshness of the fish and prevent over- or under-cooling. In addition, dynamic adjustment can also optimize the operating status of the refrigeration equipment, reduce unnecessary start-up and shutdown, and extend the life of the equipment.

[0063] By obtaining the status data of the fish body and combining it with the internal temperature of the cooling bin and the initial state parameters of the coolant, the required cooling energy demand value can be accurately calculated, so that the refrigeration equipment can accurately match the cooling demand, avoiding insufficient or excessive cooling, and improving the cooling efficiency. Compared with the traditional simple temperature control method, it pays more attention to energy consumption management in the cooling process, effectively reduces energy consumption while meeting cooling needs, and achieves higher energy-saving effects.

[0064] A cooling temperature analysis model and an adjustment analysis model were introduced. The cooling flow rate was accurately controlled through the predicted value of fish body temperature and the cooling adjustment coefficient. The temperature changes in each period of the cooling process could be accurately predicted by inputting the initial temperature of the fish body, the temperature of the cooling bin and the coolant status data into the prediction model. This allows the temperature change trend to be predicted in advance and the flow rate to be adjusted, avoiding the lag of passive regulation. This greatly improves the intelligence of the cooling process and the accuracy of control, ensuring the safety and efficiency of the refrigeration equipment operation.

[0065] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0066] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling a refrigeration device, characterized in that: The following steps are involved: Obtaining the current internal temperature value of the cooling bin, the target cooling temperature value of the fish body of the marine fish school to be cooled, and the fish body status data of each marine fish in the marine fish school to be cooled, and performing preprocessing, wherein the fish body status data includes the fish body weight value and the fish body specific heat capacity value; Comprehensively analyzing the current internal temperature value of the pre-treated cooling bin, the target cooling temperature value of the fish body of the marine fish school to be cooled, and the fish body status data of each marine fish in the marine fish school to be cooled, to obtain the cooling energy demand value of the refrigeration equipment in the cooling bin; After the marine fish to be cooled are placed in the cooling bin, the initial state data of the coolant of the refrigeration equipment in the cooling bin is obtained, and a comprehensive analysis is performed in combination with the current internal temperature value of the cooling bin, the cooling energy demand value of the refrigeration equipment, and the preset cooling time to obtain the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin; In the cooling bin, the marine fish to be cooled are refrigerated based on the cooling energy demand value of the refrigeration equipment and the cooling flow rate value of the coolant in the refrigeration equipment, and real-time monitoring is performed, and the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin is adjusted based on the real-time monitoring result; The specific formula for calculating the cooling energy demand value of the refrigeration equipment of the cooling bin is as follows: ； in, is the cooling energy demand value of the refrigeration equipment of the cooling warehouse, For the first The weight of marine fish, For the first The specific heat capacity of the fish body of a marine fish, is the current internal temperature of the cooling chamber, is the target cooling temperature value of the fish body of the marine fish to be cooled, , The number of marine fish in the marine fish school to be cooled.

2. The method for controlling a refrigeration device according to claim 1, characterized in that: The initial state data of the coolant in the refrigeration equipment in the cooling bin specifically include the specific heat capacity value, initial temperature value, and density value of the coolant in the refrigeration equipment in the cooling bin.

3. The method for controlling a refrigeration device according to claim 2, characterized in that: The specific steps for obtaining the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin are as follows: Performing temperature difference analysis on the current internal temperature value of the cooling bin and the initial temperature value of the coolant in the refrigeration equipment in the cooling bin to obtain the temperature difference between the cooling bin and the coolant in the refrigeration equipment; A comprehensive analysis is performed on the temperature difference between the coolant in the cooling bin and the refrigeration equipment, the cooling energy demand value of the refrigeration equipment in the cooling bin, the preset cooling time, and the specific heat capacity value, initial temperature value, and density value of the coolant in the refrigeration equipment in the cooling bin to obtain the cooling flow rate value of the coolant in the refrigeration equipment in the cooling bin.

4. The method for controlling a refrigeration device according to claim 3, characterized in that: The specific formula for calculating the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin is as follows: ； in, is the cooling flow rate of the coolant in the refrigeration equipment of the cooling bin, is the cooling energy demand value of the refrigeration equipment, is the specific heat capacity of the coolant in the refrigeration equipment of the cooling bin, is the initial temperature value of the coolant in the refrigeration equipment of the cooling bin, The current internal temperature of the cooling chamber. is the density of the coolant in the refrigeration equipment of the cooling bin, The preset cooling time.

5. The method for controlling a refrigeration device according to claim 1, characterized in that: The specific steps for adjusting the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the real-time monitoring results are as follows: Divide the preset cooling time into several time periods, and predict the predicted value of the cooling time period temperature of the marine fish to be cooled in each future time period in the cooling chamber; When the marine fish to be cooled are refrigerated in the cooling bin, the real-time temperature value of the fish bodies of the marine fish to be cooled in each future period in the cooling bin is obtained in real time, and the real-time temperature judgment and analysis is performed in combination with the temperature prediction value of the fish body cooling period in the corresponding period, and the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin is adjusted based on the judgment and analysis results.

6. The method for controlling a refrigeration device according to claim 5, characterized in that: The specific steps for predicting the predicted value of the cooling period temperature of the fish body of the marine fish to be cooled in the cooling chamber at each future period are as follows: Obtaining the initial body temperature of the marine fish to be cooled; The initial temperature value of the fish body of the marine fish to be cooled and the current internal temperature value of the cooling bin are input into the cooling temperature analysis model for prediction and analysis, so as to obtain the predicted value of the fish body temperature of each future period in the cooling bin.

7. The method for controlling a refrigeration device according to claim 6, characterized in that: The cooling temperature analysis model is as follows: ； in, For the future of cooling marine fish in the cooling chamber The predicted value of the fish cooling temperature during each period, is the current internal temperature of the cooling chamber, is the initial temperature of the fish body to be cooled, is a natural constant, is the cooling coefficient stored in the database, , The number of time periods.

8. The method for controlling a refrigeration device according to claim 5, characterized in that: The specific steps for adjusting the cooling flow rate value of the coolant in the refrigeration equipment of the cooling bin based on the judgment and analysis results are as follows: Compare and analyze the real-time temperature of the fish bodies of the marine fish to be cooled in the cooling chamber at each future period with the predicted temperature of the fish bodies during the corresponding period; If there is a period in which the real-time temperature value of the fish body of the marine fish to be cooled in the cooling chamber does not meet the temperature prediction value of the fish body cooling period, the real-time temperature deviation value of the fish body is analyzed; Analyze the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin in the remaining period based on the real-time temperature deviation value of the fish body; During the remaining period, speed adjustment measures are taken on the coolant in the refrigeration equipment of the cooling bin based on the cooling flow rate adjustment value.

9. The method for controlling a refrigeration device according to claim 8, characterized in that: The specific formula for calculating the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin during the remaining period is as follows: ； in, is the cooling flow rate adjustment value of the coolant in the refrigeration equipment of the cooling bin during the remaining period, is the cooling flow rate of the coolant in the refrigeration equipment of the cooling bin, is the cooling adjustment factor, It is the real-time temperature deviation value of the fish body.

10. The method for controlling a refrigeration device according to claim 9, characterized in that: The specific steps to calculate the cooling adjustment factor are as follows: Count the number of remaining time periods when the real-time temperature value of the fish body of the marine fish to be cooled in the cooling chamber does not meet the predicted value of the temperature during the cooling period of the fish body; The real-time temperature deviation value of the fish body and the number of remaining time periods are input into the regulation analysis model for comprehensive analysis to obtain the cooling regulation coefficient; The specific adjustment analysis model is as follows: ； in, is the cooling adjustment factor, is the basic adjustment constant stored in the database, is a natural constant, is the sensitivity coefficient stored in the database, is the real-time temperature deviation value of the fish body, The number of remaining time periods.

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