Remote monitoring method and system for intelligent variable-frequency refrigeration and fresh-keeping equipment

Abstract

The invention provides a remote monitoring method and system for intelligent frequency conversion refrigeration and preservation equipment, and relates to the technical field of intelligent refrigeration and preservation control, and the system comprises an equipment state monitoring module, an energy consumption analysis module, an intelligent frequency conversion control module, a remote communication module, a user interaction interface module and an AI prediction optimization module. The equipment state monitoring module monitors temperature, humidity, gas concentration and equipment operation state in real time, the energy consumption analysis module evaluates energy consumption efficiency, the intelligent frequency conversion control module automatically adjusts working frequency and mode to save energy, the remote communication module realizes data transmission, and the user interaction interface module displays equipment state and energy consumption information and provides remote control. The AI prediction optimization module predicts an energy consumption trend and a fresh-keeping effect based on historical data and generates a parameter adjustment strategy, and the system can realize delicacy management of equipment, optimize energy consumption, improve fresh-keeping quality, realize predictive maintenance through a deep learning model, reduce human intervention, and improve management efficiency and equipment performance.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent refrigeration and fresh-keeping control, and in particular to a remote monitoring method and system for intelligent variable frequency refrigeration and fresh-keeping equipment. Background Art

[0002] With the rapid development of cold chain logistics and food storage industries, the demand for refrigeration and preservation equipment is growing. Most traditional refrigeration equipment operates at a fixed frequency and lacks adaptability to environmental changes, resulting in high energy consumption and unsatisfactory preservation effects. In addition, traditional equipment lacks remote monitoring functions, making it difficult to grasp the equipment operating status and refrigeration environment parameters in real time, which is not conducive to timely detection of problems and taking measures. In recent years, the rapid development of Internet of Things technology has made it possible for the intelligent management of refrigeration and preservation equipment. Through Internet of Things technology, remote monitoring, data collection and analysis, and data-based intelligent control of refrigeration equipment can be achieved.

[0003] However, the existing technology lacks frequency conversion control, has weak monitoring functions, and insufficient data processing. Summary of the invention

[0004] In order to overcome the problems of the prior art such as lack of frequency conversion control, weak monitoring function, insufficient data processing, etc., the present invention designs a remote monitoring method and system for intelligent frequency conversion refrigeration and preservation equipment, which can effectively solve the above technical problems.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows: A remote monitoring system for intelligent variable frequency refrigeration and fresh-keeping equipment, comprising: Equipment status monitoring module, used to monitor the temperature, humidity, gas concentration and equipment operation status in the refrigeration and fresh-keeping equipment in real time; Energy consumption analysis module, used to analyze the energy consumption of refrigeration and fresh-keeping equipment and calculate the current energy consumption efficiency; Intelligent frequency conversion control module, used to automatically adjust the working frequency and working mode of refrigeration and fresh-keeping equipment to achieve energy-saving and fresh-keeping effects; A remote communication module, used to realize remote data transmission between the refrigeration and fresh-keeping equipment and the user interaction interface module; User interaction interface module: used to display the status of refrigeration and fresh-keeping equipment, energy consumption information and remote control operations; The AI ​​prediction and optimization module is used to predict the future energy consumption trend and refrigeration and preservation effect of refrigeration and preservation equipment based on historical data, and adjust the parameters of refrigeration and preservation equipment in advance according to the prediction results to optimize energy consumption and preservation effects.

[0006] Preferably, the equipment status monitoring module includes: Temperature monitoring unit, used to monitor the temperature data in the refrigeration and fresh-keeping equipment in real time; Humidity monitoring unit, used to monitor humidity data in refrigeration and fresh-keeping equipment in real time; Gas concentration monitoring unit, used to monitor the gas concentration data in the refrigeration and fresh-keeping equipment in real time; The equipment operation status monitoring unit is used to monitor the operation status of the refrigeration and preservation equipment in real time.

[0007] Preferably, the energy consumption analysis module includes: Energy consumption data collection unit, used to collect energy consumption data of various components of refrigeration and fresh-keeping equipment; An energy consumption efficiency calculation unit, used to calculate the current energy consumption efficiency according to the energy consumption data provided by the energy consumption data collection unit, wherein the energy consumption efficiency calculation method includes the ratio of energy consumption to refrigeration and preservation effect; The energy consumption analysis report generating unit is used to generate an energy consumption analysis report according to the calculation result of the energy consumption efficiency calculating unit, and the report content includes energy consumption trend, energy consumption anomaly detection and energy saving suggestions.

[0008] Preferably, the intelligent frequency conversion control module includes: A frequency adjustment unit, used to automatically adjust the operating frequency of the refrigeration and fresh-keeping equipment according to the energy consumption efficiency provided by the energy consumption analysis module; The working mode adjustment unit is used to automatically adjust the working mode of the equipment according to the energy consumption efficiency and the current load condition of the refrigeration and fresh-keeping equipment.

[0009] Preferably, the remote communication module comprises: A data transmission unit, used to realize real-time data transmission between the refrigeration and fresh-keeping equipment and the user interaction interface module; Data encryption unit, used to encrypt the transmitted data to ensure data security; The data verification unit is used to verify the transmitted data to ensure data integrity.

[0010] Preferably, the user interaction interface module includes: Equipment status display unit, used to display the current status information of refrigeration and fresh-keeping equipment, including temperature, humidity, gas concentration and equipment operation status; Energy consumption information display unit, used to display energy consumption information and energy consumption analysis report of refrigeration and fresh-keeping equipment; The remote control operation unit is used to enable users to remotely control the operation of refrigeration and fresh-keeping equipment.

[0011] Preferably, the AI ​​prediction and optimization module includes: Data preprocessing unit, used to clean and normalize the historical data of refrigeration and fresh-keeping equipment, and construct feature engineering; A model training unit, used to train a deep learning model based on the data processed by the data preprocessing unit to obtain an energy consumption prediction model and a preservation effect prediction model; A prediction and analysis unit, used to input real-time data into the energy consumption prediction model and the preservation effect prediction model to obtain future energy consumption trends and refrigeration preservation effect prediction results; The optimization strategy generation unit is used to generate a parameter adjustment strategy for the refrigeration and fresh-keeping equipment according to the prediction results of the prediction and analysis unit, and send it to the equipment status monitoring module, energy consumption analysis module and intelligent frequency conversion control module to achieve intelligent optimization of the refrigeration and fresh-keeping equipment.

[0012] A remote monitoring method for intelligent variable frequency refrigeration and fresh-keeping equipment comprises the following steps: Monitor the temperature, humidity, gas concentration and equipment operation status in the refrigeration equipment in real time, and transmit the monitoring data to the remote monitoring center; The remote monitoring center receives the monitoring data, analyzes the energy consumption of the refrigeration and fresh-keeping equipment, and calculates the current energy consumption efficiency; According to the calculation results of energy consumption analysis, the working frequency and working mode of refrigeration and fresh-keeping equipment are automatically adjusted to achieve energy-saving and fresh-keeping effects; Through remote communication, the real-time status, energy consumption information and control instructions of the refrigeration and fresh-keeping equipment are transmitted between the refrigeration and fresh-keeping equipment and the remote user end; Display the status and energy consumption information of refrigeration and fresh-keeping equipment on the remote user side, and provide a remote control operation interface; Collect historical data of refrigeration and fresh-keeping equipment, and predict the future energy consumption trend and refrigeration and fresh-keeping effect of refrigeration and fresh-keeping equipment based on data preprocessing and model training; According to the prediction results, a parameter adjustment strategy for the refrigeration and fresh-keeping equipment is generated and sent to the refrigeration and fresh-keeping equipment terminal via remote communication; The refrigeration and preservation equipment side adjusts the refrigeration and preservation equipment parameters in advance according to the received adjustment strategy to optimize energy consumption and preservation effect.

[0013] An electronic device, comprising: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the remote monitoring method of the intelligent variable frequency refrigeration and fresh-keeping equipment as described above.

[0014] A computer storage medium stores computer instructions, which, when called, are used to execute the remote monitoring method of the intelligent variable frequency refrigeration and fresh-keeping equipment as described above.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: through the intelligent frequency conversion control module, the present invention can monitor the energy efficiency of the refrigeration and preservation equipment in real time, and automatically adjust the working frequency and working mode of the equipment according to the energy consumption analysis results. This dynamic adjustment mechanism not only ensures that the equipment operates under high energy consumption, but also realizes precise control of the refrigeration and preservation effect, and effectively solves the problems of high energy consumption and poor preservation effect caused by the fixed frequency operation of traditional refrigeration equipment. The coordinated work of the equipment status monitoring module and the remote communication module enables key information such as temperature, humidity, gas concentration and operating status of the refrigeration and preservation equipment to be transmitted to the remote monitoring center in real time. , realizing comprehensive monitoring of the equipment. Users can intuitively view the equipment status, energy consumption information and analysis reports through the user interaction interface module, which greatly improves the practicality and convenience of the monitoring function. The introduction of the AI ​​prediction and optimization module enables the present invention to accurately predict the future energy consumption trend and preservation effect of the refrigeration and preservation equipment based on historical data. Through data preprocessing, model training and predictive analysis, the system can generate equipment parameter adjustment strategies and intelligently optimize the equipment in advance. This data-based intelligent decision-making mechanism not only improves the stability and reliability of equipment operation, but also provides users with a more personalized refrigeration and preservation solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without paying any creative work.

[0017] Figure 1 This is a structure diagram of a remote monitoring system for intelligent variable frequency refrigeration and fresh-keeping equipment; Figure 2 The present invention is a step diagram of a remote monitoring method for intelligent variable frequency refrigeration and preservation equipment. DETAILED DESCRIPTION

[0018] The drawings are for illustrative purposes only and should not be construed as limiting the present patent; In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product; It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0019] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0020] Example 1

[0021] A remote monitoring system for intelligent variable frequency refrigeration and fresh-keeping equipment, such as Figure 1 As shown, including: Equipment status monitoring module, used to monitor the temperature, humidity, gas concentration and equipment operation status in the refrigeration and fresh-keeping equipment in real time; Energy consumption analysis module, used to analyze the energy consumption of refrigeration and fresh-keeping equipment and calculate the current energy consumption efficiency; Intelligent frequency conversion control module, used to automatically adjust the working frequency and working mode of refrigeration and fresh-keeping equipment to achieve energy-saving and fresh-keeping effects; A remote communication module, used to realize remote data transmission between the refrigeration and fresh-keeping equipment and the user interaction interface module; User interaction interface module: used to display the status of refrigeration and fresh-keeping equipment, energy consumption information and remote control operations; The AI ​​prediction and optimization module is used to predict the future energy consumption trend and refrigeration and preservation effect of refrigeration and preservation equipment based on historical data, and adjust the parameters of refrigeration and preservation equipment in advance according to the prediction results to optimize energy consumption and preservation effects.

[0022] The equipment status monitoring module comprises: Temperature monitoring unit, used to monitor the temperature data in the refrigeration and fresh-keeping equipment in real time; Humidity monitoring unit, used to monitor humidity data in refrigeration and fresh-keeping equipment in real time; The gas concentration monitoring unit is used to monitor the gas concentration data in the refrigeration and fresh-keeping equipment in real time, including oxygen concentration, carbon dioxide concentration, etc.

[0023] The equipment operation status monitoring unit is used to monitor the operation status of the refrigeration and fresh-keeping equipment in real time, including the compressor operation status, fan operation status, etc.

[0024] The energy consumption analysis module comprises: Energy consumption data collection unit, used to collect energy consumption data of various components of refrigeration and fresh-keeping equipment; An energy consumption efficiency calculation unit, used to calculate the current energy consumption efficiency according to the energy consumption data provided by the energy consumption data collection unit, wherein the energy consumption efficiency calculation method includes the ratio of energy consumption to refrigeration and preservation effect; The energy consumption analysis report generating unit is used to generate an energy consumption analysis report according to the calculation result of the energy consumption efficiency calculating unit, and the report content includes energy consumption trend, energy consumption anomaly detection and energy saving suggestions.

[0025] The intelligent frequency conversion control module comprises: A frequency adjustment unit, used to automatically adjust the operating frequency of the refrigeration and fresh-keeping equipment according to the energy consumption efficiency provided by the energy consumption analysis module; The working mode adjustment unit is used to automatically adjust the working mode of the equipment according to the energy consumption efficiency and the current load of the refrigeration and fresh-keeping equipment. The working modes include energy-saving mode, rapid cooling mode, etc.

[0026] The remote communication module comprises: A data transmission unit, used to realize real-time data transmission between the refrigeration and fresh-keeping equipment and the user interaction interface module; Data encryption unit, used to encrypt the transmitted data to ensure data security; The data verification unit is used to verify the transmitted data to ensure data integrity.

[0027] The user interaction interface module comprises: Equipment status display unit, used to display the current status information of refrigeration and fresh-keeping equipment, including temperature, humidity, gas concentration and equipment operation status; Energy consumption information display unit, used to display energy consumption information and energy consumption analysis report of refrigeration and fresh-keeping equipment; The remote control operation unit is used to enable users to remotely control the operation of refrigeration and preservation equipment, including adjusting temperature, humidity, gas concentration and equipment working mode.

[0028] The AI ​​prediction and optimization module includes: Data preprocessing unit, used to clean and normalize the historical data of refrigeration and fresh-keeping equipment, and construct feature engineering; A model training unit, used to train a deep learning model based on the data processed by the data preprocessing unit to obtain an energy consumption prediction model and a preservation effect prediction model; A prediction and analysis unit, used to input real-time data into the energy consumption prediction model and the preservation effect prediction model to obtain future energy consumption trends and refrigeration preservation effect prediction results; The optimization strategy generation unit is used to generate a parameter adjustment strategy for the refrigeration and fresh-keeping equipment according to the prediction results of the prediction and analysis unit, and send it to the equipment status monitoring module, energy consumption analysis module and intelligent frequency conversion control module to achieve intelligent optimization of the refrigeration and fresh-keeping equipment.

[0029] Equipment status monitoring module, various sensors are installed on the refrigeration and preservation equipment, including temperature sensors, humidity sensors, gas concentration sensors, such as oxygen and carbon dioxide concentrations, and sensors for monitoring the equipment operation status, such as compressor and fan status. The temperature monitoring unit uses a high-precision temperature sensor to monitor the temperature data inside the refrigeration and preservation equipment in real time to ensure that the food is stored in a suitable temperature environment. The temperature data is transmitted to the system center via wired or wireless methods for analysis and processing. The humidity monitoring unit uses a humidity sensor to monitor the humidity level inside the equipment in real time to maintain the optimal humidity environment required for the food. Similarly, the humidity data is also transmitted to the system center in real time. The gas concentration monitoring unit uses gas sensors such as oxygen sensors and carbon dioxide sensors to monitor the gas concentration data inside the equipment in real time to ensure that the food is stored in the best gas environment. The gas concentration data is also transmitted to the system center in real time. The equipment operation status monitoring unit uses vibration sensors, temperature sensors, etc. to monitor the operation status of key components such as compressors and fans in real time, and promptly discover and handle potential faults. The operation status data is also transmitted to the system center in real time.

[0030] Energy consumption analysis module, energy consumption data collection unit, through smart meters, sensors and other equipment, collects energy consumption data of various components of refrigeration and preservation equipment, including power consumption, refrigeration capacity, etc. The energy efficiency calculation unit calculates the current energy efficiency based on the ratio of the collected energy consumption data and refrigeration and preservation effects, such as food freshness, storage time, etc. The energy efficiency calculation method can be customized according to actual needs. The energy consumption analysis report generation unit automatically generates an energy consumption analysis report, including energy consumption trend chart, energy consumption anomaly detection, such as abnormally high energy consumption time period and energy-saving suggestions, such as adjusting the working mode to reduce energy consumption. The report is displayed in charts and texts to facilitate user understanding and operation.

[0031] Intelligent frequency conversion control module, the frequency adjustment unit automatically adjusts the working frequency of the refrigeration and preservation equipment according to the energy efficiency data provided by the energy consumption analysis module to achieve energy-saving effects. Frequency adjustment can be achieved through equipment such as frequency converters. The working mode adjustment unit automatically switches to energy-saving mode, rapid cooling mode, etc. according to the energy efficiency and current load of the equipment to adapt to different refrigeration and preservation needs. The working mode adjustment can be achieved through the control system.

[0032] Remote communication module, the data transmission unit uses Wi-Fi, 4G / 5G and other communication technologies to realize real-time data transmission between the refrigeration and preservation equipment and the user interaction interface module. The data transmission unit is responsible for receiving, sending and storing data. The data encryption unit uses advanced encryption algorithms, such as AES, RSA, etc., to encrypt the transmitted data to ensure data security. The encryption unit encrypts the data before data transmission and decrypts the data at the receiving end. The data verification unit verifies the transmitted data through verification codes, hash values, etc. to ensure data integrity. The data verification unit verifies the data during the data transmission process and promptly notifies the user or management personnel for processing when errors are found.

[0033] User interaction interface module, the equipment status display unit uses a graphical interface to display the current status information of the refrigeration and preservation equipment, including temperature, humidity, gas concentration and equipment operation status, etc. The user can intuitively understand the equipment status through the interface. The energy consumption information display unit displays the energy consumption information and energy consumption analysis report of the refrigeration and preservation equipment to help users understand the energy consumption of the equipment. The energy consumption information is displayed in the form of charts and texts to facilitate user understanding and operation. The remote control operation unit provides a remote control function, allowing the user to adjust the equipment's parameters such as temperature, humidity, gas concentration and working mode by clicking buttons or sliders on the interface. The remote control operation unit communicates with the equipment through the remote communication module to achieve remote control and adjustment.

[0034] AI prediction and optimization module, the data preprocessing unit cleans and normalizes the historical data of the refrigeration and preservation equipment, and constructs feature engineering. The data preprocessing unit is responsible for data preprocessing and feature extraction to provide high-quality data sets for subsequent model training. The model training unit uses deep learning algorithms, such as LSTM, GRU, etc., to train the energy consumption prediction model and the preservation effect prediction model according to the preprocessed data. The model training unit is responsible for model training and optimization to improve the prediction accuracy of the model. The prediction and analysis unit inputs real-time data into the energy consumption prediction model and the preservation effect prediction model to obtain the energy consumption trend and refrigeration preservation effect prediction results in the future. The prediction and analysis unit is responsible for the input of real-time data and the output of prediction results. The optimization strategy generation unit generates the parameter adjustment strategy of the refrigeration and preservation equipment according to the prediction results of the prediction and analysis unit, and sends it to the equipment status monitoring module, the energy consumption analysis module and the intelligent frequency conversion control module to realize the intelligent optimization of the equipment. The optimization strategy generation unit is responsible for the generation and sending of strategies to ensure that the equipment runs in the best state.

[0035] Example 2

[0036] A remote monitoring method for intelligent variable frequency refrigeration and fresh-keeping equipment, such as Figure 2 As shown, the following steps are included: Monitor the temperature, humidity, gas concentration and equipment operation status in the refrigeration equipment in real time, and transmit the monitoring data to the remote monitoring center; The remote monitoring center receives the monitoring data, analyzes the energy consumption of the refrigeration and fresh-keeping equipment, and calculates the current energy consumption efficiency; According to the calculation results of energy consumption analysis, the working frequency and working mode of refrigeration and fresh-keeping equipment are automatically adjusted to achieve energy-saving and fresh-keeping effects; Through remote communication, the real-time status, energy consumption information and control instructions of the refrigeration and fresh-keeping equipment are transmitted between the refrigeration and fresh-keeping equipment and the remote user end; Display the status and energy consumption information of refrigeration and fresh-keeping equipment on the remote user side, and provide a remote control operation interface; Collect historical data of refrigeration and fresh-keeping equipment, and predict the future energy consumption trend and refrigeration and fresh-keeping effect of refrigeration and fresh-keeping equipment based on data preprocessing and model training; According to the prediction results, a parameter adjustment strategy for the refrigeration and fresh-keeping equipment is generated and sent to the refrigeration and fresh-keeping equipment terminal via remote communication; The refrigeration and preservation equipment side adjusts the refrigeration and preservation equipment parameters in advance according to the received adjustment strategy to optimize energy consumption and preservation effect.

[0037] An electronic device, comprising: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the remote monitoring method of the intelligent variable frequency refrigeration and fresh-keeping equipment as described above.

[0038] A computer storage medium stores computer instructions, which, when called, are used to execute the remote monitoring method of the intelligent variable frequency refrigeration and fresh-keeping equipment as described above.

[0039] In the specific implementation, for real-time monitoring and data transmission, sensors are installed inside the refrigeration and preservation equipment to monitor the temperature, humidity, gas concentration, such as oxygen and carbon dioxide concentration, and equipment operating status, such as compressor operating status, fan speed, etc. These sensors are connected to the microprocessor or controller inside the equipment. The microprocessor or controller transmits the monitoring data to the remote monitoring center through wireless communication methods such as Wi-Fi, 4G / 5G, LoRa, etc. or wired communication methods such as Ethernet, RS485, etc.

[0040] After receiving the monitoring data, the remote monitoring center first stores and backs up the data. Then, it uses the energy consumption analysis algorithm to analyze the monitoring data and calculate the energy efficiency of the current refrigeration and fresh-keeping equipment, such as the fresh-keeping effect per unit energy consumption and the overall energy consumption level of the equipment.

[0041] Based on the calculation results of energy consumption analysis, the remote monitoring center automatically calculates and determines the working frequency and working mode adjustment plan of the refrigeration and preservation equipment through a preset algorithm or model. These adjustment plans are aimed at achieving energy saving and consumption reduction while ensuring the preservation effect.

[0042] The remote monitoring center transmits the real-time status, energy consumption information and control instructions of the refrigeration and preservation equipment to the remote user end, such as mobile phone APP, computer web page, etc. through wireless or wired communication. At the same time, the remote user end can also send remote control instructions to the remote monitoring center, such as adjusting the temperature and humidity setting values, viewing historical data, etc.

[0043] At the remote user end, users can view the status information of the refrigeration and preservation equipment in real time, such as temperature, humidity, gas concentration, etc., energy consumption information, such as total energy consumption, energy efficiency, etc., and equipment operation status, such as whether it is online, whether it is alarming, etc. In addition, the remote user end also provides a remote control operation interface, through which users can remotely control the refrigeration and preservation equipment.

[0044] The remote monitoring center is also responsible for collecting historical data of refrigeration and preservation equipment, including temperature, humidity, gas concentration, energy consumption information, etc. These data are used to train machine learning models or deep learning models after data preprocessing, such as cleaning, normalization, feature engineering, etc. The trained model can be used to predict the future energy consumption trend and refrigeration and preservation effect of refrigeration and preservation equipment. The prediction results can provide an important basis for the parameter adjustment of refrigeration and preservation equipment. According to the prediction results, the remote monitoring center generates parameter adjustment strategies for refrigeration and preservation equipment. These strategies include adjusting temperature and humidity set values, optimizing working frequency and working mode, etc. Then, the remote monitoring center sends the adjustment strategy to the refrigeration and preservation equipment through wireless or wired communication.

[0045] After receiving the adjustment strategy, the refrigerated preservation equipment automatically adjusts the equipment parameters according to the strategy content. These adjustments are aimed at optimizing energy consumption and preservation effects and improving the overall operating efficiency of the equipment.

[0046] The electronic device includes a memory storing executable program code and a processor coupled to the memory. The processor calls the executable program code stored in the memory to execute the remote monitoring method of the above-mentioned intelligent variable frequency refrigeration and preservation equipment. Specifically, the electronic device can be a server or workstation of a remote monitoring center, or it can be an application on a remote user terminal, such as a smart phone, tablet computer, laptop computer, etc. On these devices, by installing and executing the corresponding program code, the various functions of the above-mentioned remote monitoring method can be realized.

[0047] The computer storage medium stores computer instructions. When these computer instructions are called, they are used to execute the remote monitoring method of the above-mentioned intelligent variable frequency refrigeration and preservation equipment. Specifically, the computer storage medium can be a storage device such as a hard disk, a solid state drive (SSD), a flash memory (Flash Memory) on a remote monitoring center server, or a storage device such as a memory or a storage card on a remote user terminal device. On these storage media, program codes or instruction sets for implementing the above-mentioned remote monitoring method are stored. When these program codes or instruction sets are called by the processor, the various functions of the above-mentioned remote monitoring method can be executed.

[0048] The same or similar reference numerals correspond to the same or similar components; The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent; Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A remote monitoring system for intelligent variable frequency refrigeration and fresh-keeping equipment, characterized in that: include: Equipment status monitoring module, used to monitor the temperature, humidity, gas concentration and equipment operation status in the refrigeration and fresh-keeping equipment in real time; Energy consumption analysis module, used to analyze the energy consumption of refrigeration and fresh-keeping equipment and calculate the current energy consumption efficiency; Intelligent frequency conversion control module, used to automatically adjust the working frequency and working mode of refrigeration and fresh-keeping equipment to achieve energy-saving and fresh-keeping effects; A remote communication module, used to realize remote data transmission between the refrigeration and fresh-keeping equipment and the user interaction interface module; User interaction interface module: used to display the status of refrigeration and fresh-keeping equipment, energy consumption information and remote control operations; The AI ​​prediction and optimization module is used to predict the future energy consumption trend and refrigeration and preservation effect of refrigeration and preservation equipment based on historical data, and adjust the parameters of refrigeration and preservation equipment in advance according to the prediction results to optimize energy consumption and preservation effects.

2. A remote monitoring system for intelligent variable frequency refrigeration and fresh-keeping equipment according to claim 1, characterized in that: The equipment status monitoring module comprises: Temperature monitoring unit, used to monitor the temperature data in the refrigeration and fresh-keeping equipment in real time; Humidity monitoring unit, used to monitor humidity data in refrigeration and fresh-keeping equipment in real time; Gas concentration monitoring unit, used to monitor the gas concentration data in the refrigeration and fresh-keeping equipment in real time; The equipment operation status monitoring unit is used to monitor the operation status of the refrigeration and preservation equipment in real time.

3. The remote monitoring system of the intelligent variable frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: The energy consumption analysis module comprises: Energy consumption data collection unit, used to collect energy consumption data of various components of refrigeration and fresh-keeping equipment; An energy consumption efficiency calculation unit, used to calculate the current energy consumption efficiency according to the energy consumption data provided by the energy consumption data collection unit, wherein the energy consumption efficiency calculation method includes the ratio of energy consumption to refrigeration and preservation effect; The energy consumption analysis report generating unit is used to generate an energy consumption analysis report according to the calculation result of the energy consumption efficiency calculating unit, and the report content includes energy consumption trend, energy consumption anomaly detection and energy saving suggestions.

4. The remote monitoring system of the intelligent variable frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: The intelligent frequency conversion control module comprises: A frequency adjustment unit, used to automatically adjust the operating frequency of the refrigeration and fresh-keeping equipment according to the energy consumption efficiency provided by the energy consumption analysis module; The working mode adjustment unit is used to automatically adjust the working mode of the equipment according to the energy consumption efficiency and the current load condition of the refrigeration and fresh-keeping equipment.

5. The remote monitoring system of the intelligent variable frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: The remote communication module comprises: A data transmission unit, used to realize real-time data transmission between the refrigeration and fresh-keeping equipment and the user interaction interface module; Data encryption unit, used to encrypt the transmitted data to ensure data security; The data verification unit is used to verify the transmitted data to ensure data integrity.

6. The remote monitoring system for intelligent variable frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: The user interaction interface module comprises: Equipment status display unit, used to display the current status information of refrigeration and fresh-keeping equipment, including temperature, humidity, gas concentration and equipment operation status; Energy consumption information display unit, used to display energy consumption information and energy consumption analysis report of refrigeration and fresh-keeping equipment; The remote control operation unit is used to enable users to remotely control the operation of refrigeration and fresh-keeping equipment.

7. The remote monitoring system for intelligent variable frequency refrigeration and fresh-keeping equipment according to claim 1 is characterized in that: The AI ​​prediction optimization module includes: Data preprocessing unit, used to clean and normalize the historical data of refrigeration and fresh-keeping equipment, and construct feature engineering; A model training unit, used to train a deep learning model based on the data processed by the data preprocessing unit to obtain an energy consumption prediction model and a preservation effect prediction model; A prediction and analysis unit, used to input real-time data into the energy consumption prediction model and the preservation effect prediction model to obtain future energy consumption trends and refrigeration preservation effect prediction results; The optimization strategy generation unit is used to generate a parameter adjustment strategy for the refrigeration and fresh-keeping equipment according to the prediction results of the prediction and analysis unit, and send it to the equipment status monitoring module, energy consumption analysis module and intelligent frequency conversion control module to achieve intelligent optimization of the refrigeration and fresh-keeping equipment.

8. A remote monitoring method for intelligent variable frequency refrigeration and fresh-keeping equipment, characterized in that: The following steps are involved: Monitor the temperature, humidity, gas concentration and equipment operation status in the refrigeration equipment in real time, and transmit the monitoring data to the remote monitoring center; The remote monitoring center receives the monitoring data, analyzes the energy consumption of the refrigeration and fresh-keeping equipment, and calculates the current energy consumption efficiency; According to the calculation results of energy consumption analysis, the working frequency and working mode of refrigeration and fresh-keeping equipment are automatically adjusted to achieve energy-saving and fresh-keeping effects; Through remote communication, the real-time status, energy consumption information and control instructions of the refrigeration and fresh-keeping equipment are transmitted between the refrigeration and fresh-keeping equipment and the remote user end; Display the status and energy consumption information of refrigeration and fresh-keeping equipment on the remote user side, and provide a remote control operation interface; Collect historical data of refrigeration and fresh-keeping equipment, and predict the future energy consumption trend and refrigeration and fresh-keeping effect of refrigeration and fresh-keeping equipment based on data preprocessing and model training; According to the prediction results, a parameter adjustment strategy for the refrigeration and fresh-keeping equipment is generated and sent to the refrigeration and fresh-keeping equipment terminal via remote communication; The refrigeration and preservation equipment side adjusts the refrigeration and preservation equipment parameters in advance according to the received adjustment strategy to optimize energy consumption and preservation effect.

9. An electronic device, characterized in that: The electronic device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the remote monitoring method of the intelligent variable frequency refrigeration and fresh-keeping equipment as described in claim 8.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the remote monitoring method of the intelligent variable frequency refrigeration and preservation equipment as described in claim 8.

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