Energy-saving refrigerator management system based on block chain and energy-saving refrigerator

Abstract

The invention relates to the technical field of energy-saving refrigerator management, and particularly discloses an energy-saving refrigerator management system based on a block chain and an energy-saving refrigerator. The system is provided with a refrigerator threshold matching subsystem, a performance characteristic analysis subsystem, an overall operation analysis subsystem, a refrigerator adjustment scheme matching subsystem and a temperature and humidity control subsystem; the method solves the problems that a traditional energy-saving refrigerator is insufficient in management dynamic adjustment capacity and insufficient in adaptive capacity, a traditional energy-saving strategy is mainly based on a preset time table or a fixed rule to adjust the operation mode of the refrigerator, the optimal energy-saving effect cannot be achieved, a data island phenomenon exists, data integration and sharing become complex, and the efficiency is high. And multi-party cooperation efficiency is low. Personalized management of different refrigerators is facilitated, early warning can be carried out in the early stage of fault occurrence, and the utilization rate of resources is increased. Based on the block chain technology, the security, traceability and non-tampering property of the data are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of energy-saving refrigerator management, and specifically to an energy-saving refrigerator management system and an energy-saving refrigerator based on blockchain. Background Art

[0002] The global energy crisis is becoming increasingly serious, and the rate of energy consumption far exceeds its regeneration rate. In the cold chain industry, refrigerators are important equipment with considerable energy consumption. The power consumption of commercial refrigerators accounts for a large proportion of the total power consumption of commercial places. The refrigerators in supermarkets operate 24 hours a day, and their power consumption may account for 30%-50% of the total power consumption of supermarkets. Therefore, from the perspective of energy management, it is urgent to manage refrigerators for energy saving. During the operation of refrigerators, their operating status needs to be monitored and precisely controlled in real time to ensure the quality of stored goods. Traditional management methods are difficult to meet these requirements, and often temperature out of control, excessive energy consumption, and equipment failures cannot be discovered in time, resulting in cargo loss and energy waste. Blockchain technology, with its decentralized, tamper-proof, and traceable characteristics, has shown great application potential in many fields. In terms of data storage and sharing, blockchain can provide a safe and reliable platform. For refrigerator management, a large amount of data generated during its operation can be securely stored and shared through blockchain.

[0003] Nowadays, there are still some deficiencies in the research on energy-saving refrigerator management based on blockchain, which is specifically reflected in the lack of dynamic adjustment ability and adaptability of traditional energy-saving refrigerator management. Traditional energy-saving strategies are mainly based on preset schedules or fixed rules to adjust the operation mode of refrigerators. This fixed mode often cannot achieve the best energy-saving effect in practical applications. In the traditional mode, each subject may have its own data format and storage system, and there is a data island phenomenon, which makes data integration and sharing complicated and multi-party collaboration inefficient. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an energy-saving refrigerator management system and an energy-saving refrigerator based on blockchain, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: In a first aspect, the present invention provides an energy-saving refrigerator management system based on blockchain, including a refrigerator threshold matching subsystem, a performance characteristic analysis subsystem, an overall operation analysis subsystem, a refrigerator adjustment scheme matching subsystem and a temperature and humidity control subsystem, wherein: the refrigerator threshold matching subsystem is used to obtain basic characteristic data of the energy-saving refrigerator, and based on the obtained basic characteristic data of the energy-saving refrigerator, match the energy-saving refrigerator threshold data set, and the energy-saving refrigerator threshold data set specifically includes energy-saving refrigerator performance threshold and energy-saving refrigerator fault analysis threshold; the performance characteristic analysis subsystem is used to match the energy-saving refrigerator based on the blockchain distribution of the energy-saving refrigerator The system uses a typed account book to analyze the performance characteristics of the energy-saving refrigerator, and in combination with the performance threshold of the energy-saving refrigerator, determines whether the energy-saving refrigerator needs to be adjusted, and marks the energy-saving refrigerator that needs to be adjusted as the energy-saving refrigerator to be adjusted; the overall operation analysis subsystem is used to analyze the overall operation status of the energy-saving refrigerator to be adjusted and obtain an overall operation analysis signal; the refrigerator adjustment plan matching subsystem is used to analyze the status of the components of the energy-saving refrigerator to be adjusted, and match the energy-saving refrigerator adjustment plan in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold; the temperature and humidity control subsystem is used to analyze the operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted, and realize intelligent temperature and humidity control.

[0006] As a further solution, basic characteristic data of energy-saving refrigerators are obtained, and based on the obtained basic characteristic data of energy-saving refrigerators, a threshold data set of energy-saving refrigerators is matched. The specific analysis process is: basic characteristic data of energy-saving refrigerators are obtained, and the basic characteristic data of energy-saving refrigerators specifically include the rated power of energy-saving refrigerators, the total capacity of energy-saving refrigerators, the refrigeration speed of energy-saving refrigerators, and the operating environment temperature of energy-saving refrigerators; based on the obtained basic characteristic data of energy-saving refrigerators, basic characteristic signals of energy-saving refrigerators are obtained through comprehensive analysis, and the basic characteristic signals of energy-saving refrigerators are used as the analysis basis for matching the threshold data set of energy-saving refrigerators; the basic characteristic signals of energy-saving refrigerators are stored as designated tags, and the designated tags are compared with each set tag stored in a database to obtain a set tag corresponding to the designated tag, and the threshold data set of energy-saving refrigerators corresponding to the set tag stored in the database is obtained.

[0007] As a further solution, based on the distributed ledger of the energy-saving refrigerator blockchain, the performance characteristics of the energy-saving refrigerator are analyzed, and combined with the performance threshold of the energy-saving refrigerator, it is judged whether the energy-saving refrigerator needs to be adjusted, and the energy-saving refrigerator that needs to be adjusted is marked as the energy-saving refrigerator to be adjusted. The specific analysis process is: based on the distributed ledger of the energy-saving refrigerator blockchain, the performance characteristic data of the energy-saving refrigerator is obtained. The performance characteristic data of the energy-saving refrigerator specifically includes the heat exchange area of ​​the evaporator, the heat transfer coefficient, the logarithmic mean temperature difference between the evaporator and the refrigerated space, the exhaust pressure of the compressor, the suction pressure of the compressor, the refrigerant flow, the compressor efficiency, and the energy consumption deviation rate per unit time of the energy-saving refrigerator; Q c =Ue *A e *ΔT lm,e ; In the formula, Q c is the heat absorbed by the refrigerator evaporator from the refrigerated space, U e is the heat exchange area of ​​the evaporator, A e is the heat transfer coefficient, ΔT lm,e is the logarithmic mean temperature difference between the evaporator and the refrigerated space; Where W c is the compressor input power, m r is the refrigerant flow rate, h d is the exhaust pressure of the compressor, h s is the suction pressure of the compressor, η c is the compressor efficiency; In the formula, COP is the refrigeration coefficient of the energy-saving refrigerator refrigeration system;

[0008] Based on the refrigeration coefficient of the energy-saving refrigerator refrigeration system and the energy consumption deviation rate of the energy-saving refrigerator per unit time, a comprehensive analysis is performed to obtain the energy-saving refrigerator performance characteristic factor, which is used as an analysis basis for judging whether the energy-saving refrigerator needs to be adjusted; the energy-saving refrigerator performance characteristic factor is compared with the energy-saving refrigerator performance threshold; if the energy-saving refrigerator performance characteristic factor is not lower than the energy-saving refrigerator performance threshold, the energy-saving refrigerator corresponding to the energy-saving refrigerator performance characteristic factor does not need to be adjusted; if the energy-saving refrigerator performance characteristic factor is lower than the energy-saving refrigerator performance threshold, the energy-saving refrigerator corresponding to the energy-saving refrigerator performance characteristic factor needs to be adjusted, and the energy-saving refrigerator that needs to be adjusted is marked as an energy-saving refrigerator to be adjusted.

[0009] As a further solution, the energy-saving refrigerator performance characteristic factors, the specific analysis process is:

[0010]

[0011] In the formula, δ is the performance characteristic factor of the energy-saving refrigerator, hnp is the energy consumption deviation rate per unit time of the energy-saving refrigerator, and ε 1 is the compensation factor of the set COP, ε 2 is the compensation factor of the set hnp, and e is a natural constant.

[0012] As a further solution, the overall operating status of the energy-saving refrigerator to be adjusted is analyzed to obtain an overall operating analysis signal. The specific analysis process is: based on the energy-saving refrigerator blockchain distributed ledger, the overall operating status data of the energy-saving refrigerator to be adjusted is obtained, and the overall operating status data of the energy-saving refrigerator to be adjusted specifically includes the vibration frequency of the energy-saving refrigerator, the vibration amplitude of the energy-saving refrigerator, and the decibel value of the energy-saving refrigerator noise; based on the obtained overall operating status data of the energy-saving refrigerator to be adjusted, the overall operating analysis signal is obtained through comprehensive analysis, and the overall operating analysis signal is used as the analysis basis for matching the energy-saving refrigerator adjustment plan.

[0013] As a further solution, the status of the energy-saving refrigerator component to be adjusted is analyzed, and the energy-saving refrigerator adjustment plan is matched in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold. The specific analysis process is: based on the energy-saving refrigerator blockchain distributed ledger, the status data of the energy-saving refrigerator component to be adjusted is obtained, and the status data of the energy-saving refrigerator component to be adjusted specifically includes the compressor working current deviation rate, the evaporator frost layer thickness, and the refrigerant flow deviation rate; based on the obtained status data of the energy-saving refrigerator component to be adjusted, combined with the overall operation analysis signal, a comprehensive analysis is performed to obtain the energy-saving refrigerator fault analysis factor, and the energy-saving refrigerator fault analysis factor is used as the analysis basis for matching the energy-saving refrigerator adjustment plan; the difference between the energy-saving refrigerator fault analysis factor and the energy-saving refrigerator fault analysis threshold is recorded as the energy-saving refrigerator fault analysis deviation value; the energy-saving refrigerator fault analysis deviation value is stored as a designated label, and the designated label is compared with each set label stored in the database to obtain the set label corresponding to the designated label, and the energy-saving refrigerator adjustment plan corresponding to the set label stored in the database is obtained.

[0014] As a further solution, the energy-saving refrigerator failure analysis factor, the specific analysis process is:

[0015]

[0016] Where, β is the energy-saving refrigerator fault analysis factor, α is the overall operation analysis signal, ydp is the compressor working current deviation rate, sch is the evaporator frost layer thickness, l lp is the refrigerant flow deviation rate, τ 1 is the compensation factor of the set ydp, τ 2 is the compensation factor of the set sch, τ 3 is the compensation factor of the set l lp.

[0017] As a further solution, the operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted are analyzed. The specific analysis process is: based on the distributed ledger of the energy-saving refrigerator blockchain, the operating temperature and humidity characteristic data of the energy-saving refrigerator to be adjusted are obtained. The operating temperature and humidity characteristic data of the energy-saving refrigerator to be adjusted specifically include the actual temperature of the energy-saving refrigerator, the rated temperature of the energy-saving refrigerator, the actual humidity of the energy-saving refrigerator, and the rated humidity of the energy-saving refrigerator;

[0018] ep=|T a -T s |;

[0019] Where ep is the temperature deviation of the energy-saving refrigerator, T a is the actual temperature of the energy-saving refrigerator, T s Rated temperature for energy-saving freezers;

[0020] es=|S a -S s |;

[0021] Where es is the humidity deviation of the energy-saving refrigerator, S a is the actual humidity of the energy-saving refrigerator, S s is the rated humidity of the energy-saving refrigerator; based on the temperature deviation and humidity deviation of the energy-saving refrigerator, a comprehensive analysis is performed to obtain an intelligent temperature and humidity control signal, which is used as an analysis basis for realizing intelligent temperature and humidity control;

[0022]

[0023] Where, γ is the intelligent temperature and humidity control signal, θ 1 is the compensation factor of the set ep, θ 2 is the compensation factor of the set es, and e is a natural constant.

[0024] As a further solution, intelligent temperature and humidity control is realized. The specific analysis process is: the intelligent temperature and humidity control signal is stored as a specified tag, the specified tag is compared with each setting tag stored in the database, the setting tag corresponding to the specified tag is obtained, and the intelligent temperature and humidity control solution corresponding to the setting tag stored in the database is obtained.

[0025] The second aspect of the present invention provides an energy-saving refrigerator based on blockchain, which is used for the above-mentioned energy-saving refrigerator management system based on blockchain, including a cabinet, a cabinet door, an evaporator and a compressor, a temperature sensor and a humidity sensor are installed inside the cabinet, and a communication module is installed on the surface of the cabinet, and also includes:

[0026] Refrigerator threshold matching module, performance characteristic analysis module, overall operation analysis module, refrigerator adjustment scheme matching module and temperature and humidity control module, among which:

[0027] The refrigerator threshold matching module is used to obtain the basic characteristic data of the energy-saving refrigerator transmitted by the communication module, and match the energy-saving refrigerator threshold data set based on the obtained basic characteristic data of the energy-saving refrigerator, wherein the energy-saving refrigerator threshold data set specifically includes the energy-saving refrigerator performance threshold and the energy-saving refrigerator fault analysis threshold;

[0028] The performance characteristic analysis module is used to analyze the performance characteristics of the energy-saving refrigerator based on the distributed ledger of the energy-saving refrigerator blockchain, and determine whether the energy-saving refrigerator needs to be adjusted in combination with the performance threshold of the energy-saving refrigerator, and mark the energy-saving refrigerator that needs to be adjusted as the energy-saving refrigerator to be adjusted;

[0029] The overall operation analysis module is used to analyze the overall operation status of the energy-saving refrigerator to be adjusted and obtain an overall operation analysis signal;

[0030] The refrigerator adjustment scheme matching module is used to analyze the status of the energy-saving refrigerator components to be adjusted, and match the energy-saving refrigerator adjustment scheme in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold;

[0031] The temperature and humidity control module is used to analyze the operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted to achieve intelligent temperature and humidity control.

[0032] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0033] (1) The present invention provides an energy-saving refrigerator management system based on blockchain. By acquiring the basic characteristic data of energy-saving refrigerators to match the threshold data set, the personalized management of different refrigerators can be realized, and the setting of the energy-saving refrigerator fault analysis threshold helps to discover potential faults in advance. Based on the blockchain distributed ledger, the performance characteristics of the energy-saving refrigerator are analyzed, and combined with the performance threshold, it can be accurately determined whether the refrigerator needs to be adjusted.

[0034] (2) Since the account book records the detailed operating data of the refrigerator, by comparing the performance threshold, the decline or abnormality of the refrigerator performance can be discovered in time, and the refrigerator that needs to be adjusted can be marked as the energy-saving refrigerator to be adjusted, realizing an intelligent screening process. The status of the energy-saving refrigerator components to be adjusted is analyzed, and the adjustment plan is matched based on the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold. A customized solution can be provided for each refrigerator component with problems. The operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted are analyzed to realize intelligent temperature and humidity control, which can provide the best environment for the stored goods and help further save energy.

[0035] (3) The present invention obtains the basic characteristic data of the energy-saving refrigerator, and matches the threshold data set of the energy-saving refrigerator based on the obtained basic characteristic data of the energy-saving refrigerator. Since the basic characteristics of each refrigerator are different, matching the corresponding threshold data set can achieve personalized management, so that each refrigerator can operate in the most suitable state for itself, thereby improving the overall energy-saving effect and operating efficiency. Matching the threshold value of energy-saving refrigerator fault analysis can help discover potential faults in advance. Parameter changes in the basic characteristic data of the refrigerator may indicate the occurrence of a fault. The method based on data and threshold matching can provide early warning at the early stage of the fault, thereby improving resource utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0037] Figure 1This is a schematic diagram of the subsystem connections of the blockchain-based energy-saving refrigerator management system of the present invention.

[0038] Figure 2 This is a schematic diagram of the overall structure of the energy-saving refrigerator based on blockchain of the present invention.

[0039] Figure 3 This is a schematic diagram of the internal structure of the energy-saving refrigerator based on blockchain in the present invention.

[0040] In the figure, 1. cabinet body; 2. cabinet door; 3. temperature sensor; 4. humidity sensor; 5. communication module. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all 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.

[0042] Reference Figure 1 As shown, the first aspect of the present invention provides an energy-saving refrigerator management system based on blockchain, including a refrigerator threshold matching subsystem, a performance characteristic analysis subsystem, an overall operation analysis subsystem, a refrigerator adjustment scheme matching subsystem and a temperature and humidity control subsystem.

[0043] The refrigerator threshold matching subsystem is used to obtain basic characteristic data of energy-saving refrigerators, and match the energy-saving refrigerator threshold data set based on the obtained basic characteristic data of energy-saving refrigerators. The energy-saving refrigerator threshold data set specifically includes energy-saving refrigerator performance thresholds and energy-saving refrigerator fault analysis thresholds.

[0044] The specific analysis process is as follows: obtaining the basic characteristic data of the energy-saving refrigerator, which specifically includes the rated power of the energy-saving refrigerator, the total capacity of the energy-saving refrigerator, the refrigeration speed of the energy-saving refrigerator, and the ambient temperature of the energy-saving refrigerator; based on the obtained basic characteristic data of the energy-saving refrigerator, a comprehensive analysis is performed to obtain the basic characteristic signal of the energy-saving refrigerator, and the basic characteristic signal of the energy-saving refrigerator is used as the analysis basis for matching the threshold data set of the energy-saving refrigerator; the basic characteristic signal of the energy-saving refrigerator is stored as a designated label, and the designated label is compared with each set label stored in the database to obtain the set label corresponding to the designated label, and the threshold data set of the energy-saving refrigerator corresponding to the set label stored in the database is obtained.

[0045] The basic characteristic signal of energy-saving refrigerator, the specific analysis process is:

[0046]

[0047] Where, ω is the basic characteristic signal of the energy-saving refrigerator, edg is the rated power of the energy-saving refrigerator, zrl is the total capacity of the energy-saving refrigerator, zls is the refrigeration speed of the energy-saving refrigerator, hjw is the ambient temperature of the energy-saving refrigerator, μ 1 is the compensation factor of the set edg, μ 2 is the compensation factor of the set zr l, μ 3 is the compensation factor of the set zls, μ 4 is the compensation factor of the set hjw, and e is a natural constant.

[0048] Normalize edg, zr l, zls and hjw.

[0049] The basic characteristic data of energy-saving refrigerators, such as rated power, total capacity, cooling speed and ambient temperature, are crucial for the operation and management of refrigerators. Different rated power refrigerators require different strategies for energy consumption management. By comprehensively analyzing these data to obtain basic characteristic signals, and using them as the basis for matching threshold data sets, appropriate management and monitoring standards can be tailored for each refrigerator. The addition of ambient temperature as a characteristic data makes refrigerator management more flexible and practical. The performance and energy consumption of refrigerators will be different under different ambient temperatures.

[0050] The basic characteristic signals of energy-saving refrigerators are stored as specified tags and compared with the set tags in the database. This method can quickly and accurately find the corresponding threshold data set of energy-saving refrigerators. The threshold data set based on these basic characteristic data matching helps to detect potential failures of refrigerators in advance. Measures can be taken while the failure is still in its infancy to avoid further deterioration of the failure, reduce maintenance costs and energy waste caused by the failure. Reasonable refrigeration speed thresholds can prevent the refrigerator from over-cooling or under-cooling, thereby achieving the purpose of energy saving and extending the service life of the refrigerator.

[0051] It should be explained that the compensation factors of edg, zrl, zls and hjw set above are obtained from the database. According to the historical data, a mapping set of the historically measured energy-saving refrigerator rated power, energy-saving refrigerator total capacity, energy-saving refrigerator refrigeration speed, energy-saving refrigerator operating ambient temperature and the compensation factors of edg, zrl, zls and hjw is established to obtain the compensation factors of edg, zrl, zls and hjw corresponding to the current edg, zrl, zls and hjw.

[0052] It should be noted that the ε 1 , ε 2 , σ 1 , σ 2 , σ 3 , τ 1 , τ 2, τ 3 ,θ 1 ,θ 2 They are also obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained according to the current data.

[0053] The performance characteristic analysis subsystem is used to analyze the performance characteristics of energy-saving refrigerators based on the energy-saving refrigerator blockchain distributed ledger, and determine whether the energy-saving refrigerators need to be adjusted based on the performance threshold of the energy-saving refrigerators, and mark the energy-saving refrigerators that need to be adjusted as energy-saving refrigerators to be adjusted.

[0054] The specific analysis process is as follows: Based on the distributed ledger of the energy-saving refrigerator blockchain, the performance characteristic data of the energy-saving refrigerator is obtained. The performance characteristic data of the energy-saving refrigerator specifically includes the heat exchange area of ​​the evaporator, the heat transfer coefficient, the logarithmic mean temperature difference between the evaporator and the refrigerated space, the exhaust pressure of the compressor, the suction pressure of the compressor, the refrigerant flow, the compressor efficiency, and the energy consumption deviation rate per unit time of the energy-saving refrigerator; Q c =U e *A e *ΔT lm,e ; In the formula, Q c is the heat absorbed by the refrigerator evaporator from the refrigerated space, U e is the heat exchange area of ​​the evaporator, A e is the heat transfer coefficient, ΔT lm,e is the logarithmic mean temperature difference between the evaporator and the refrigerated space; Where W c is the compressor input power, m r is the refrigerant flow rate, h d is the exhaust pressure of the compressor, h s is the suction pressure of the compressor, η c is the compressor efficiency; In the formula, COP is the refrigeration coefficient of the energy-saving refrigerator refrigeration system;

[0055] Based on the refrigeration coefficient of the energy-saving refrigerator refrigeration system and the energy consumption deviation rate of the energy-saving refrigerator per unit time, the energy-saving refrigerator performance characteristic factor is obtained through comprehensive analysis. The energy-saving refrigerator performance characteristic factor is used as the analysis basis for judging whether the energy-saving refrigerator needs to be adjusted; the energy-saving refrigerator performance characteristic factor is compared with the energy-saving refrigerator performance threshold; if the energy-saving refrigerator performance characteristic factor is not lower than the energy-saving refrigerator performance threshold, the energy-saving refrigerator corresponding to the energy-saving refrigerator performance characteristic factor does not need to be adjusted; if the energy-saving refrigerator performance characteristic factor is lower than the energy-saving refrigerator performance threshold, the energy-saving refrigerator corresponding to the energy-saving refrigerator performance characteristic factor needs to be adjusted, and the energy-saving refrigerator that needs to be adjusted is marked as the energy-saving refrigerator to be adjusted, and the deviation rate is the ratio of the absolute value of the difference between the actual value and the reference value to the reference value.

[0056] Energy-saving refrigerator performance characteristic factors, the specific analysis process is:

[0057]

[0058] In the formula, δ is the performance characteristic factor of the energy-saving refrigerator, hnp is the energy consumption deviation rate per unit time of the energy-saving refrigerator, and ε 1 is the compensation factor of the set COP, ε 2 is the compensation factor of the set hnp, and e is a natural constant.

[0059] COP and hnp were normalized.

[0060] By obtaining detailed energy-saving refrigerator performance characteristic data including evaporator heat exchange area, heat transfer coefficient, etc., the refrigerator's refrigeration system can be comprehensively evaluated. The refrigeration coefficient is calculated by considering multiple factors such as compressor input power, refrigerant flow, exhaust pressure, suction pressure and compressor efficiency, and can accurately reflect the actual performance of the refrigerator refrigeration system. This analysis method based on physical principles and mathematical formulas avoids subjective assumptions and provides an objective and accurate basis for refrigerator performance evaluation. The performance characteristic factor is obtained by combining the refrigeration coefficient and the energy consumption per unit time deviation rate, and a large number of performance data are further integrated into a representative indicator. By comparing with the performance threshold, it is possible to quickly and accurately determine whether the refrigerator needs to be adjusted, thereby achieving effective monitoring of the refrigerator performance. By analyzing the energy consumption per unit time deviation rate of energy-saving refrigerators, the energy-saving potential of the refrigerator can be discovered. The deviation rate is the ratio of the absolute value of the difference between the actual value and the reference value to the reference value. This indicator can accurately reflect whether the energy consumption of the refrigerator exceeds the normal range.

[0061] The use of energy-saving refrigerator blockchain distributed ledgers to obtain performance characteristic data ensures data security, traceability and non-tamperability. This means that every performance data record of the refrigerator is saved truthfully and completely. Throughout the life cycle of the refrigerator, manufacturers, operators and maintenance personnel can trace the performance change history of the refrigerator.

[0062] The overall operation analysis subsystem is used to analyze the overall operation status of the energy-saving refrigerator to be adjusted and obtain an overall operation analysis signal.

[0063] The specific analysis process is as follows: based on the distributed ledger of the energy-saving refrigerator blockchain, the overall operating status data of the energy-saving refrigerator to be adjusted is obtained, and the overall operating status data of the energy-saving refrigerator to be adjusted specifically includes the vibration frequency of the energy-saving refrigerator, the vibration amplitude of the energy-saving refrigerator, and the decibel value of the noise of the energy-saving refrigerator; based on the obtained overall operating status data of the energy-saving refrigerator to be adjusted, the overall operation analysis signal is obtained through comprehensive analysis, and the overall operation analysis signal is used as the analysis basis for matching the energy-saving refrigerator adjustment plan.

[0064] The overall operation analysis signal, the specific analysis process is:

[0065]

[0066] Where α is the overall operation analysis signal, zdp is the vibration frequency of the energy-saving refrigerator, zdf is the vibration amplitude of the energy-saving refrigerator, fbz is the noise decibel value of the energy-saving refrigerator, σ 1 is the compensation factor of the set zdp, σ 2 is the compensation factor of the set zdf, σ 3 is the compensation factor of the set fbz.

[0067] Normalize zdp, zdf, and fbz.

[0068] By obtaining the overall operating status data of the energy-saving refrigerator, such as the vibration frequency, vibration amplitude and noise decibel value, the operation of the refrigerator can be observed from multiple angles. The vibration frequency and amplitude can reflect the operating stability of the mechanical components inside the refrigerator (such as compressors, fans, etc.). The vibration of a refrigerator that operates normally should be within a reasonable range. If the vibration frequency is too high or the amplitude is too large, it may mean that the internal components are loose, worn or unbalanced. The noise decibel value is another important indicator of the operating status of the refrigerator. Abnormal noise may indicate a failure in the refrigeration system, ventilation system, etc. This multi-dimensional data collection method helps to promptly discover hidden problems in the operation of the refrigerator. Based on the overall operating status data obtained, a comprehensive analysis is performed to obtain an overall operation analysis signal. This signal is used as the basis for matching the adjustment plan of the energy-saving refrigerator, making the adjustment plan more accurate.

[0069] The refrigerator adjustment plan matching subsystem is used to analyze the status of the energy-saving refrigerator components to be adjusted, and match the energy-saving refrigerator adjustment plan in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold.

[0070] The specific analysis process is as follows: based on the distributed ledger of the energy-saving refrigerator blockchain, the status data of the energy-saving refrigerator components to be adjusted are obtained, and the status data of the energy-saving refrigerator components to be adjusted specifically include the compressor working current deviation rate, the evaporator frost layer thickness, and the refrigerant flow deviation rate; based on the obtained status data of the energy-saving refrigerator components to be adjusted, combined with the overall operation analysis signal, a comprehensive analysis is performed to obtain the energy-saving refrigerator fault analysis factor, and the energy-saving refrigerator fault analysis factor is used as the analysis basis for matching the energy-saving refrigerator adjustment plan; the difference between the energy-saving refrigerator fault analysis factor and the energy-saving refrigerator fault analysis threshold is recorded as the energy-saving refrigerator fault analysis deviation value; the energy-saving refrigerator fault analysis deviation value is stored as a designated label, and the designated label is compared with each set label stored in the database to obtain the set label corresponding to the designated label, and the energy-saving refrigerator adjustment plan corresponding to the set label stored in the database is obtained.

[0071] Energy-saving refrigerator failure analysis factors, the specific analysis process is:

[0072]

[0073] Where, β is the energy-saving refrigerator fault analysis factor, α is the overall operation analysis signal, ydp is the compressor working current deviation rate, sch is the evaporator frost layer thickness, l lp is the refrigerant flow deviation rate, τ 1 is the compensation factor of the set ydp, τ 2 is the compensation factor of the set sch, τ 3 is the compensation factor of the set l lp.

[0074] Normalize ydp, sch, and l lp.

[0075] Obtaining the status data of the energy-saving refrigerator components to be adjusted, such as the compressor working current deviation rate, the evaporator frost layer thickness and the refrigerant flow deviation rate, can make a detailed evaluation of the working status of the key components of the refrigerator. For example, the compressor working current deviation rate can directly reflect whether the compressor is working properly. If the current deviation rate exceeds the normal range, it may indicate that the compressor has problems such as overload, short circuit or mechanical failure. Monitoring the thickness of the evaporator frost layer is also critical. Too thick frost will affect the heat exchange efficiency of the evaporator, and then affect the refrigeration effect of the refrigerator. Combined with the overall operation analysis signal, the energy-saving refrigerator fault analysis factor is obtained through comprehensive analysis, which makes the fault analysis more comprehensive and accurate. The overall operation analysis signal contains the overall operation status information of the refrigerator, such as vibration and noise. Combined with the component status data, the fault can be judged from the system level. It helps to accurately locate the cause of the fault. Different abnormal combinations of component status data may point to different causes of the fault.

[0076] The energy-saving refrigerator fault analysis deviation value is stored as a specified tag and compared with the set tag in the database. This method can quickly and accurately obtain the corresponding energy-saving refrigerator adjustment plan. Since the fault conditions of different refrigerators may vary due to factors such as model, usage environment, and operation history, this tag comparison method can provide a personalized adjustment plan for each refrigerator.

[0077] The temperature and humidity control subsystem is used to analyze the operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted and realize intelligent temperature and humidity control.

[0078] The specific analysis process is as follows: based on the distributed ledger of the energy-saving refrigerator blockchain, the operating temperature and humidity characteristic data of the energy-saving refrigerator to be adjusted are obtained. The operating temperature and humidity characteristic data of the energy-saving refrigerator to be adjusted specifically include the actual temperature of the energy-saving refrigerator, the rated temperature of the energy-saving refrigerator, the actual humidity of the energy-saving refrigerator, and the rated humidity of the energy-saving refrigerator; ep = |T a -Ts |;

[0079] Where ep is the temperature deviation of the energy-saving refrigerator, T a is the actual temperature of the energy-saving refrigerator, T s Rated temperature for energy-saving freezers;

[0080] es=|S a -S s |;

[0081] Where es is the humidity deviation of the energy-saving refrigerator, S a is the actual humidity of the energy-saving refrigerator, S s is the rated humidity of the energy-saving refrigerator; based on the temperature deviation and humidity deviation of the energy-saving refrigerator, a comprehensive analysis is performed to obtain an intelligent temperature and humidity control signal, which is used as an analysis basis for realizing intelligent temperature and humidity control;

[0082] Intelligent temperature and humidity control signal, the specific analysis process is:

[0083]

[0084] Where, γ is the intelligent temperature and humidity control signal, θ 1 is the compensation factor of the set ep, θ 2 is the compensation factor of the set es, and e is a natural constant.

[0085] Normalize ep and es.

[0086] By obtaining the actual temperature, rated temperature, actual humidity and rated humidity of the energy-saving refrigerator, the real state of the internal environment of the refrigerator can be fully understood. The temperature deviation and humidity deviation are calculated using formulas to make the evaluation of temperature and humidity more accurate. These deviation values ​​can intuitively reflect the accuracy of the temperature and humidity control of the refrigerator. The intelligent temperature and humidity control signal is obtained by combining the temperature deviation and humidity deviation. As the basis for realizing intelligent control, it can guide the refrigerator's refrigeration, dehumidification or humidification equipment to operate accurately according to the actual deviation, thereby realizing refined control of temperature and humidity. Adjustment based on the intelligent temperature and humidity control signal can avoid excessive cooling or dehumidification of the refrigerator, thereby achieving energy saving.

[0087] The intelligent temperature and humidity control signal is stored as a designated tag, the designated tag is compared with each setting tag stored in the database, the setting tag corresponding to the designated tag is obtained, and the intelligent temperature and humidity control scheme corresponding to the setting tag stored in the database is obtained.

[0088] The intelligent temperature and humidity control signal is stored as a specified tag and compared with the set tag in the database. This method can quickly and accurately obtain the corresponding intelligent temperature and humidity control solution. The database stores preset solutions for different temperature and humidity control signals. By comparing, the tediousness of manual screening solutions and possible errors can be avoided, ensuring that the most suitable control strategy for the current temperature and humidity conditions of the refrigerator is found at the first time. The obtained intelligent temperature and humidity control solution is based on the pre-set and optimized content in the database, and the solution has been tested in practice or verified in theory. Temperature and humidity control according to these solutions can improve the accuracy and stability of control.

[0089] In a specific embodiment, the rated power of an energy-saving refrigerator is 200W, the total capacity is 500L, the cooling speed is 10℃ / h, the operating ambient temperature is 25℃, the set compensation factors are 0.8, 1.2, 1.0, and 0.9 respectively, and the basic characteristic signal of the energy-saving refrigerator is calculated to be 23.54, which matches the energy-saving refrigerator threshold data set. The energy-saving refrigerator threshold data set specifically includes the energy-saving refrigerator performance threshold of 10 and the energy-saving refrigerator fault analysis threshold of 0.

[0090] The heat exchange area of ​​the evaporator is 10 square meters, the heat transfer coefficient is 20, the logarithmic mean temperature difference between the evaporator and the refrigerated space is 5K, the exhaust pressure of the compressor is 1.5 MPa, the suction pressure of the compressor is 0.5 MPa, the refrigerant flow rate is 0.5 kg / s, the compressor efficiency is 0.8, the calculated COP is 1.6, the set compensation factor is 1.5, the energy consumption deviation rate per unit time of the energy-saving refrigerator is 0.08, the set compensation factor is 1.2, and the performance characteristic factor of the energy-saving refrigerator is 9.27, which is lower than the performance threshold of 10 for the energy-saving refrigerator. The energy-saving refrigerator is marked as an energy-saving refrigerator to be adjusted.

[0091] The overall operating status data of the energy-saving refrigerator to be adjusted are as follows:

[0092] The vibration frequency of the energy-saving refrigerator is 15Hz, the vibration amplitude of the energy-saving refrigerator is 0.5mm, the noise decibel value of the energy-saving refrigerator is 40dB, the set compensation factors are 0.9, 1.1, and 1.0 respectively, and the overall operation analysis signal is 0.78.

[0093] The compressor working current deviation rate is 0.06, the evaporator frost layer thickness is 3mm, the refrigerant flow deviation rate is 0.09, the set compensation factors are 1.1, 1.0, and 0.9, respectively, the energy-saving refrigerator fault analysis factor is -0.05, and the difference between the energy-saving refrigerator fault analysis factor and the energy-saving refrigerator fault analysis threshold is recorded as the energy-saving refrigerator fault analysis deviation value of -0.05. After comparison, the corresponding energy-saving refrigerator adjustment plan is obtained, and the energy-saving refrigerator is manually re-inspected, defrosted, and the refrigerant flow is adjusted.

[0094] The acquired operating temperature and humidity characteristic data of the energy-saving refrigerator to be adjusted are as follows: the actual temperature of the energy-saving refrigerator is 5°C, the rated temperature of the energy-saving refrigerator is 4°C, the actual humidity of the energy-saving refrigerator is 70%, the rated humidity of the energy-saving refrigerator is 65%, the temperature deviation of the energy-saving refrigerator is 1°C, the humidity deviation of the energy-saving refrigerator is 5%, the set compensation factors are 1.0 and 1.2 respectively, the calculated intelligent temperature and humidity control signal is 0.63, and the corresponding intelligent temperature and humidity control scheme is obtained. The refrigeration power is appropriately reduced to fine-tune the temperature, and the dehumidification function is started to reduce the humidity.

[0095] Reference Figure 2-Figure 3 As shown, the second aspect of the present invention provides an energy-saving refrigerator based on blockchain, which is used for the above-mentioned energy-saving refrigerator management system based on blockchain, including a cabinet 1, a cabinet door 2, an evaporator and a compressor, a temperature sensor 3 and a humidity sensor 4 are installed inside the cabinet 1, and a communication module 5 is installed on the surface of the cabinet 1, and also includes:

[0096] Refrigerator threshold matching module, performance characteristic analysis module, overall operation analysis module, refrigerator adjustment scheme matching module and temperature and humidity control module, among which:

[0097] The refrigerator threshold matching module is used to obtain the basic characteristic data of the energy-saving refrigerator transmitted by the communication module 5, and match the energy-saving refrigerator threshold data set based on the obtained basic characteristic data of the energy-saving refrigerator, wherein the energy-saving refrigerator threshold data set specifically includes the energy-saving refrigerator performance threshold and the energy-saving refrigerator fault analysis threshold;

[0098] The performance characteristic analysis module is used to analyze the performance characteristics of the energy-saving refrigerator based on the distributed ledger of the energy-saving refrigerator blockchain, and determine whether the energy-saving refrigerator needs to be adjusted in combination with the performance threshold of the energy-saving refrigerator, and mark the energy-saving refrigerator that needs to be adjusted as the energy-saving refrigerator to be adjusted;

[0099] The overall operation analysis module is used to analyze the overall operation status of the energy-saving refrigerator to be adjusted and obtain an overall operation analysis signal;

[0100] The refrigerator adjustment scheme matching module is used to analyze the status of the energy-saving refrigerator components to be adjusted, and match the energy-saving refrigerator adjustment scheme in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold;

[0101] The temperature and humidity control module is used to analyze the operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted to achieve intelligent temperature and humidity control.

[0102] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An energy-saving refrigerator management system based on blockchain, characterized in that: It includes refrigerator threshold matching subsystem, performance characteristic analysis subsystem, overall operation analysis subsystem, refrigerator adjustment scheme matching subsystem and temperature and humidity control subsystem, among which: The refrigerator threshold matching subsystem is used to obtain basic characteristic data of the energy-saving refrigerator, and match the energy-saving refrigerator threshold data set based on the obtained basic characteristic data of the energy-saving refrigerator, wherein the energy-saving refrigerator threshold data set specifically includes the energy-saving refrigerator performance threshold and the energy-saving refrigerator fault analysis threshold; The performance characteristic analysis subsystem is used to analyze the performance characteristics of the energy-saving refrigerator based on the energy-saving refrigerator blockchain distributed ledger, and determine whether the energy-saving refrigerator needs to be adjusted in combination with the energy-saving refrigerator performance threshold, and mark the energy-saving refrigerator that needs to be adjusted as the energy-saving refrigerator to be adjusted; The overall operation analysis subsystem is used to analyze the overall operation status of the energy-saving refrigerator to be adjusted and obtain an overall operation analysis signal; The refrigerator adjustment scheme matching subsystem is used to analyze the status of the energy-saving refrigerator components to be adjusted, and match the energy-saving refrigerator adjustment scheme in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold; The temperature and humidity control subsystem is used to analyze the operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted, and realize intelligent temperature and humidity control.

2. According to claim 1, the energy-saving refrigerator management system based on blockchain is characterized in that: The basic characteristic data of the energy-saving refrigerator is obtained, and based on the obtained basic characteristic data of the energy-saving refrigerator, the threshold data set of the energy-saving refrigerator is matched. The specific analysis process is as follows: Obtaining basic characteristic data of the energy-saving refrigerator, the basic characteristic data of the energy-saving refrigerator specifically includes the rated power of the energy-saving refrigerator, the total capacity of the energy-saving refrigerator, the refrigeration speed of the energy-saving refrigerator, and the ambient temperature of the energy-saving refrigerator; Based on the acquired basic characteristic data of energy-saving refrigerators, a comprehensive analysis is performed to obtain basic characteristic signals of energy-saving refrigerators, and the basic characteristic signals of energy-saving refrigerators are used as the analysis basis for matching the threshold data set of energy-saving refrigerators; The basic characteristic signal of the energy-saving refrigerator is stored as a designated label, the designated label is compared with each set label stored in the database, the set label corresponding to the designated label is obtained, and the energy-saving refrigerator threshold data set corresponding to the set label stored in the database is obtained.

3. According to the blockchain-based energy-saving refrigerator management system of claim 1, it is characterized by: Based on the distributed ledger of the energy-saving refrigerator blockchain, the performance characteristics of the energy-saving refrigerator are analyzed, and combined with the performance threshold of the energy-saving refrigerator, it is determined whether the energy-saving refrigerator needs to be adjusted, and the energy-saving refrigerator that needs to be adjusted is marked as the energy-saving refrigerator to be adjusted. The specific analysis process is: Based on the distributed ledger of the energy-saving refrigerator blockchain, the performance characteristic data of the energy-saving refrigerator is obtained. The performance characteristic data of the energy-saving refrigerator specifically includes the heat exchange area of ​​the evaporator, the heat transfer coefficient, the logarithmic mean temperature difference between the evaporator and the refrigerated space, the exhaust pressure of the compressor, the suction pressure of the compressor, the refrigerant flow, the compressor efficiency, and the energy consumption deviation rate per unit time of the energy-saving refrigerator; Q c =U e *A e *ΔT lm,e ; In the formula, Q c is the heat absorbed by the refrigerator evaporator from the refrigerated space, U e is the heat exchange area of ​​the evaporator, A e is the heat transfer coefficient, ΔT lm,e is the logarithmic mean temperature difference between the evaporator and the refrigerated space; Where W c is the compressor input power, m r is the refrigerant flow rate, h d is the exhaust pressure of the compressor, h s is the suction pressure of the compressor, η c is the compressor efficiency; In the formula, COP is the refrigeration coefficient of the energy-saving refrigerator refrigeration system; Based on the refrigeration coefficient of the energy-saving refrigerator refrigeration system and the energy consumption deviation rate of the energy-saving refrigerator per unit time, the energy-saving refrigerator performance characteristic factor is obtained through comprehensive analysis. The energy-saving refrigerator performance characteristic factor is used as the analysis basis for judging whether the energy-saving refrigerator needs to be adjusted. comparing the energy-saving refrigerator performance characteristic factor with the energy-saving refrigerator performance threshold; If the energy-saving refrigerator performance characteristic factor is not lower than the energy-saving refrigerator performance threshold, the energy-saving refrigerator corresponding to the energy-saving refrigerator performance characteristic factor does not need to be adjusted; If the energy-saving refrigerator performance characteristic factor is lower than the energy-saving refrigerator performance threshold, the energy-saving refrigerator corresponding to the energy-saving refrigerator performance characteristic factor needs to be adjusted, and the energy-saving refrigerator that needs to be adjusted is marked as an energy-saving refrigerator to be adjusted.

4. According to claim 3, the energy-saving refrigerator management system based on blockchain is characterized in that: The specific analysis process of the energy-saving refrigerator performance characteristic factor is as follows: Wherein, δ is the performance characteristic factor of the energy-saving refrigerator, hnp is the energy consumption deviation rate per unit time of the energy-saving refrigerator, ε1 is the compensation factor of the set COP, ε2 is the compensation factor of the set hnp, and e is a natural constant.

5. According to the blockchain-based energy-saving refrigerator management system of claim 1, it is characterized by: The overall operation state of the energy-saving refrigerator to be adjusted is analyzed to obtain an overall operation analysis signal. The specific analysis process is as follows: Based on the distributed ledger of the energy-saving refrigerator blockchain, the overall operating status data of the energy-saving refrigerator to be adjusted is obtained, and the overall operating status data of the energy-saving refrigerator to be adjusted specifically includes the vibration frequency of the energy-saving refrigerator, the vibration amplitude of the energy-saving refrigerator, and the decibel value of the noise of the energy-saving refrigerator; Based on the acquired overall operating status data of the energy-saving refrigerator to be adjusted, an overall operating analysis signal is obtained through comprehensive analysis, and the overall operating analysis signal is used as an analysis basis for matching the energy-saving refrigerator adjustment plan.

6. The energy-saving refrigerator management system based on blockchain according to claim 1 is characterized in that: The energy-saving refrigerator component status to be adjusted is analyzed, and the energy-saving refrigerator adjustment plan is matched in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold. The specific analysis process is as follows: Based on the distributed ledger of the energy-saving refrigerator blockchain, the status data of the energy-saving refrigerator components to be adjusted are obtained. The status data of the energy-saving refrigerator components to be adjusted specifically include the compressor working current deviation rate, the evaporator frost layer thickness, and the refrigerant flow deviation rate; Based on the acquired status data of the energy-saving refrigerator components to be adjusted, combined with the overall operation analysis signal, a comprehensive analysis is performed to obtain the energy-saving refrigerator fault analysis factor, which is used as the analysis basis for matching the energy-saving refrigerator adjustment plan; The difference between the energy-saving refrigerator failure analysis factor and the energy-saving refrigerator failure analysis threshold is recorded as the energy-saving refrigerator failure analysis deviation value; The energy-saving refrigerator fault analysis deviation value is stored as a designated label, the designated label is compared with each setting label stored in the database, the setting label corresponding to the designated label is obtained, and the energy-saving refrigerator adjustment plan corresponding to the setting label stored in the database is obtained.

7. The energy-saving refrigerator management system based on blockchain according to claim 6 is characterized in that: The energy-saving refrigerator failure analysis factor, the specific analysis process is: Wherein, β is the energy-saving refrigerator fault analysis factor, α is the overall operation analysis signal, ydp is the compressor working current deviation rate, sch is the evaporator frost thickness, llp is the refrigerant flow deviation rate, τ1 is the compensation factor of the set ydp, τ2 is the compensation factor of the set sch, and τ3 is the compensation factor of the set llp.

8. The energy-saving refrigerator management system based on blockchain according to claim 1 is characterized in that: The operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted are analyzed, and the specific analysis process is as follows: Based on the distributed ledger of the energy-saving refrigerator blockchain, the operating temperature and humidity characteristic data of the energy-saving refrigerator to be adjusted are obtained, and the operating temperature and humidity characteristic data of the energy-saving refrigerator to be adjusted specifically include the actual temperature of the energy-saving refrigerator, the rated temperature of the energy-saving refrigerator, the actual humidity of the energy-saving refrigerator, and the rated humidity of the energy-saving refrigerator; ep=|T a -T s |; Where ep is the temperature deviation of the energy-saving refrigerator, T a is the actual temperature of the energy-saving refrigerator, T s Rated temperature for energy-saving freezers; is=|S a -S s |; Where es is the humidity deviation of the energy-saving refrigerator, S a is the actual humidity of the energy-saving refrigerator, S s Rated humidity for energy-saving freezers; Based on the temperature deviation and humidity deviation of the energy-saving refrigerator, the intelligent temperature and humidity control signal is obtained through comprehensive analysis. The intelligent temperature and humidity control signal is used as the analysis basis for realizing intelligent temperature and humidity control. Intelligent temperature and humidity control signal, the specific analysis process is: Wherein, γ is the intelligent temperature and humidity control signal, θ1 is the compensation factor of the set ep, θ2 is the compensation factor of the set es, and e is a natural constant.

9. The energy-saving refrigerator management system based on blockchain according to claim 8 is characterized in that: The specific analysis process of realizing intelligent temperature and humidity control is as follows: The intelligent temperature and humidity control signal is stored as a designated tag, the designated tag is compared with each setting tag stored in the database, the setting tag corresponding to the designated tag is obtained, and the intelligent temperature and humidity control scheme corresponding to the setting tag stored in the database is obtained.

10. An energy-saving refrigerator based on blockchain, used in an energy-saving refrigerator management system based on blockchain as claimed in any one of claims 1 to 9, comprising a cabinet body (1), a cabinet door (2), an evaporator and a compressor, characterized in that: The cabinet (1) is internally installed with a temperature sensor (3) and a humidity sensor (4), the surface of the cabinet (1) is installed with a communication module (5), and further comprises: Refrigerator threshold matching module, performance characteristic analysis module, overall operation analysis module, refrigerator adjustment scheme matching module and temperature and humidity control module, among which: The refrigerator threshold matching module is used to obtain the basic characteristic data of the energy-saving refrigerator transmitted by the communication module (5), and match the energy-saving refrigerator threshold data set based on the obtained basic characteristic data of the energy-saving refrigerator, wherein the energy-saving refrigerator threshold data set specifically includes the energy-saving refrigerator performance threshold and the energy-saving refrigerator fault analysis threshold; The performance characteristic analysis module is used to analyze the performance characteristics of the energy-saving refrigerator based on the distributed ledger of the energy-saving refrigerator blockchain, and determine whether the energy-saving refrigerator needs to be adjusted in combination with the performance threshold of the energy-saving refrigerator, and mark the energy-saving refrigerator that needs to be adjusted as the energy-saving refrigerator to be adjusted; The overall operation analysis module is used to analyze the overall operation status of the energy-saving refrigerator to be adjusted and obtain an overall operation analysis signal; The refrigerator adjustment scheme matching module is used to analyze the status of the energy-saving refrigerator components to be adjusted, and match the energy-saving refrigerator adjustment scheme in combination with the overall operation analysis signal and the energy-saving refrigerator fault analysis threshold; The temperature and humidity control module is used to analyze the operating temperature and humidity characteristics of the energy-saving refrigerator to be adjusted to achieve intelligent temperature and humidity control.

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