CN111339641A - Refrigeration system management method and device, cloud platform and storage medium - Google Patents
Refrigeration system management method and device, cloud platform and storage medium Download PDFInfo
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- CN111339641A CN111339641A CN202010090439.3A CN202010090439A CN111339641A CN 111339641 A CN111339641 A CN 111339641A CN 202010090439 A CN202010090439 A CN 202010090439A CN 111339641 A CN111339641 A CN 111339641A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F11/32—Responding to malfunctions or emergencies
- F24F11/38—Failure diagnosis
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/89—Arrangement or mounting of control or safety devices
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
- F25B49/00—Arrangement or mounting of control or safety devices
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Abstract
The embodiment of the application discloses a refrigeration system management method, a refrigeration system management device, a cloud platform and a readable storage medium, wherein the method comprises the following steps: acquiring target operation parameters from a target refrigeration system which is in communication connection with the target refrigeration system based on receiving an acquisition instruction aiming at the target operation parameters in a hierarchical structure model stored in the hierarchical structure model, wherein the hierarchical structure model comprises target refrigeration system options and operation parameter options; judging whether the variation range of the target operation parameter is within a prestored parameter variation threshold value; when the variation range of the target operation parameter is not within the pre-stored parameter variation threshold, determining a target adjustment parameter of the target operation parameter according to a pre-stored energy consumption model; generating a control instruction according to the target adjustment parameter; and sending the control instruction to the target refrigeration system so that the refrigeration system adjusts the self operating parameters according to the target adjustment parameters.
Description
Technical Field
The embodiment of the application relates to the technical field of refrigeration, and relates to but is not limited to a refrigeration system management method, a refrigeration system management device, a cloud platform and a storage medium.
Background
With the wide application of the refrigeration and air conditioning technology in modern production and life, professional refrigeration systems have large gaps among operation and maintenance personnel, the phenomena of unreasonable daily maintenance and untimely system fault maintenance occur occasionally, and advanced management and energy-saving management such as fault early warning and energy management cannot be guaranteed. Meanwhile, the refrigeration and air-conditioning industry is a traditional industry, and also faces huge challenges in the modern industrialization process, and as equipment guarantee of the temperature and humidity environment of each node on a cold-chain logistics chain and the air-conditioning environment of people in daily life and production activities, the application and development of a refrigeration system are greatly restricted by the traditional monitoring, controlling and managing modes. Each manager of the refrigeration system is faced with some of the same problems: manual recording, difficulty in technician application, unclear quality, overhigh energy consumption and low informatization.
With the industrial development, the era of 'industrial 4.0' and 'Chinese manufacturing 2025' is entered, resources are integrated through the internet, the internet of things and the logistics network, an intelligent production mode of 'internet + manufacturing industry' is achieved, industrial equipment is in internet of things and intelligent, information isolated islands are broken, and productivity is greatly improved. Modern internet technology and information technology break through the obstacles brought to human communication by regions. People can log in the internet at any time and any place, and the purpose of communication at any time is achieved by utilizing various mobile phone apps. In this case, the refrigeration energy industry must realize evolution by means of the internet to better serve production and living, and the method provided by the embodiment of the application is developed under the condition.
In the related technology, for example, a cold chain temperature monitoring alarm and tracing system based on the internet of things and a cloud computing platform carries out monitoring alarm and tracing on the temperature of articles in cold chain logistics, and other parameters of the system and equipment are not involved, and energy management is not involved. In another related art "a remotely controllable refrigeration control system", a remotely controllable refrigeration control system of a refrigeration system can be monitored in real time regardless of whether an operator is at a work site, but it does not use a deep learning algorithm for artificial intelligence control, so that efficient intelligent operation of the system cannot be ensured.
Disclosure of Invention
In view of this, embodiments of the present application provide a method and an apparatus for managing a refrigeration system, a cloud platform, and a storage medium.
The technical scheme of the embodiment of the application is realized as follows:
the embodiment of the application provides a refrigeration system management method, which comprises the following steps:
acquiring target operation parameters from a target refrigeration system which is in communication connection with the target refrigeration system based on receiving an acquisition instruction aiming at the target operation parameters in a hierarchical structure model stored in the hierarchical structure model, wherein the hierarchical structure model comprises target refrigeration system options and operation parameter options;
judging whether the variation range of the target operation parameter is within a prestored parameter variation threshold value;
when the variation range of the target operation parameter is not within the pre-stored parameter variation threshold, determining a target adjustment parameter of the target operation parameter according to a pre-stored energy consumption model;
generating a control instruction according to the target adjustment parameter;
and sending the control instruction to the target refrigeration system so that the refrigeration system adjusts the self operating parameters according to the target adjustment parameters.
The embodiment of the application provides a refrigerating system management device, the device includes:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring target operation parameters from a target refrigeration system which is in communication connection with the first acquisition module on the basis of receiving an acquisition instruction aiming at the target operation parameters in a hierarchical structure model, and the hierarchical structure model comprises target refrigeration system options and operation parameter options;
the judging module is used for judging whether the variation range of the target operation parameter is within a prestored parameter variation threshold value;
the adjusting module is used for determining a target adjusting parameter of the target operating parameter according to a prestored energy consumption model when the variation range of the target operating parameter is not within a prestored parameter variation threshold;
the first generation module is used for generating a control instruction according to the target adjustment parameter;
and the first sending module is used for sending the control instruction to the target refrigerating system so as to enable the refrigerating system to adjust the self operating parameters according to the target adjusting parameters.
An embodiment of the present application provides a refrigeration system management cloud platform, the cloud platform includes:
a processor; and
a memory for storing a computer program operable on the processor;
wherein the computer program when executed by a processor implements the steps of the refrigeration system management method.
Embodiments of the present application provide a readable storage medium having stored therein computer-executable instructions configured to perform the steps of the refrigeration system management method.
The embodiment of the application provides a refrigeration system management method, a refrigeration system management device, refrigeration system management equipment and a readable storage medium, wherein a hierarchical structure model is arranged, a receiving user can conveniently select a target refrigeration system and operation parameters, when the target operation parameters are received, the target operation parameters are compared with a parameter variation threshold value, and when the target operation parameters are not in a pre-stored parameter variation threshold value, the target operation parameters are adjusted through an energy consumption model to obtain target adjustment parameters, so that the target refrigeration system can efficiently and intelligently operate.
Drawings
In the drawings, which are not necessarily drawn to scale, like reference numerals may describe similar components in different views. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed herein.
Fig. 1 is a schematic connection diagram of a cloud platform according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating a method for managing a refrigeration system according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of establishing an energy consumption model according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a hierarchical structure model provided by an embodiment of the present application;
fig. 5 is a schematic structural diagram of a management device of a refrigeration system according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a cloud platform provided in an embodiment of the present application.
Detailed Description
In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the attached drawings, the described embodiments should not be considered as limiting the present application, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
The following description will be added if a similar description of "first \ second \ third" appears in the application file, where the terms "first \ second \ third" merely distinguish similar objects and do not represent a specific ordering with respect to the objects, and it should be understood that "first \ second \ third" may be interchanged with a specific order or sequence as permitted, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.
Based on the problems in the related art, the embodiment of the present application provides a refrigeration system management method, the method is applied to a cloud platform, fig. 1 is a schematic connection diagram of the cloud platform provided in the embodiment of the present application, as shown in fig. 1, a cloud platform 101 establishes communication with a refrigeration system 103 through a detector 102, and the cloud platform 101 may also be connected with an intelligent terminal 104. The method provided by this embodiment may be implemented by a computer program, and when the computer program is executed, each step in the method provided by this embodiment is completed. In some embodiments, the computer program may be executed by a processor in a cloud platform.
Fig. 2 is a schematic flow chart of a management method of a refrigeration system according to an embodiment of the present application, and as shown in fig. 2, the method includes:
step S201, the cloud platform acquires target operation parameters from a target refrigeration system which is in communication connection with the cloud platform on the basis of receiving an acquisition instruction aiming at the target operation parameters in the hierarchical structure model stored in the cloud platform.
In an embodiment of the present application, the hierarchical structure model includes target refrigeration system options and operational parameter options. Receiving an acquisition instruction for a target operation parameter in a hierarchical structure model stored in the hierarchical structure model is generally a checking operation performed by a user on a refrigeration system option and an operation parameter option in the hierarchical structure model, the checked refrigeration system is a target refrigeration system, and the checked operation parameter is a target operation parameter.
In the embodiment of the present application, a communication connection is established between the refrigeration system and the cloud platform, and in the embodiment of the present application, the communication connection is generally a GPRS network connection.
In an embodiment of the present application, a target refrigeration system includes: detection elements of the switching values of the running states such as a compressor, a fan, a pump, an electromagnetic valve and the like; the detection elements of analog quantities such as temperature, pressure, humidity, flow, liquid level and the like; a PLC module; a power sensing element. The detection elements of the switching values are respectively arranged at all refrigeration compressors, evaporator fans, cooling water tower fans, evaporative condenser fans, cooling water pumps, refrigerant pumps, liquid supply electromagnetic valves, air return electromagnetic valves, water flow electromagnetic valves and the like used by the refrigeration system and used for detecting the start-stop states of corresponding equipment. The detection and control elements of analog quantities such as temperature, pressure, humidity, flow, liquid level and the like are respectively arranged at typical positions of a cold room, equipment, a pipeline and the environment which need to be detected and controlled by the system and are used for detecting corresponding parameter values. The power detection element is arranged at power equipment such as a compressor, a water pump and a fan and used for detecting the power consumption of the power device. The detection parameters are converted into digital signals through analog-to-digital conversion, the switching values are collected by the PLC through a transmission channel in a centralized mode, the digital signals and the switching values are processed through a PLC program written in advance, and the processing results are converted through the digital-to-analog conversion and returned to a controller of the refrigerating system through the transmission channel, so that all parameters and all equipment in the refrigerating system are controlled. The PLC is configured through corresponding configuration software, and then data acquired by the PLC are transmitted to the monitor through a USB interface (485 bus, adopting a Modbus485 protocol).
In the embodiment of the application, when the cloud platform receives the target operation parameter obtaining instruction, the target operation parameter can be obtained from the target refrigeration system. Specifically, target operating parameters are obtained from the detector.
In the embodiment of the application, the refrigeration system in the hierarchical structure model comprises equipment types, equipment processes and equipment monitoring parameters. Illustratively, a refrigeration system A is included in the hierarchical structure model, a temperature option of a cold room is arranged under the refrigeration system A, and when a user selects the temperature option of the cold room in the refrigeration system A, the refrigeration system A checks the temperature of the cold room through a checking element and then sends the temperature of the cold room to the cloud platform.
Step S202, the cloud platform judges whether the variation range of the target operation parameter is within a pre-stored parameter variation threshold value.
In the embodiment of the present application, the variation threshold of the parameter may be determined according to historical data or historical experience. In the embodiment of the application, after the target operation parameter is obtained, the target operation parameter is compared with a parameter variation threshold value. When the target operating parameter is not within the parameter variation threshold, step S203 is executed, and when the target operating parameter is within the variation threshold, it indicates that the target operating parameter of the target refrigeration system is normal.
Step S203, the cloud platform determines target adjustment parameters of the target operation parameters according to the pre-stored energy consumption model.
In the embodiment of the application, the pre-stored energy consumption model can be obtained through historical operating parameters and historical energy consumption and based on a deep learning algorithm according to the historical operating parameters and the historical energy consumption. The method includes the steps of applying historical operating parameters and historical energy consumption data, processing the data by one or more deep learning algorithms such as an artificial intelligent simulated neural network, and the like, wherein fig. 3 is a schematic diagram for establishing an energy consumption model provided by the embodiment of the application, as shown in fig. 3, a plurality of parameters such as evaporation temperature, condensation temperature and the like are used as neurons for efficient operation and fault learning, a system refrigeration energy efficiency ratio coefficient is used as a target function, and a prediction relation based on the deep learning algorithm between the system refrigeration energy efficiency and the system energy efficiency is established according to collected parameters such as warehouse temperature, evaporation temperature, suction temperature, condensation temperature, high-low pressure ratio and refrigerant flow, so that the energy consumption model is obtained. And storing the obtained energy consumption model in the cloud platform, and determining target adjustment parameters through the energy consumption model when target operation parameters are obtained. In an embodiment of the application, the energy consumption model enables the refrigeration system to operate in an efficient and safe environment based on the operating parameters.
And step S204, the cloud platform generates a control instruction according to the target adjustment parameter.
Step S205, the cloud platform sends the control instruction to the target refrigeration system, so that the refrigeration system adjusts its own operating parameters according to the target adjustment parameters.
The embodiment of the application provides a refrigeration system management method, which can conveniently receive the selection of a target refrigeration system and operation parameters by a user through setting a hierarchical structure model, and when the target operation parameters are received, the target operation parameters are compared with a parameter change threshold value, and when the target operation parameters are not in the pre-stored parameter change threshold value, the target operation parameters are adjusted through an energy consumption model to obtain target adjustment parameters, so that the target refrigeration system can efficiently and intelligently operate.
In some embodiments, before step S201, the method further includes step S200 of building a hierarchical structure model, and in this embodiment, building the hierarchical structure model may be implemented by:
step S200A, the cloud platform determines the equipment type according to the equipment type, the refrigerant working medium and the number of evaporators;
step S200B, the cloud platform determines equipment and process according to the evaporation system, the compression system and the condensation system;
step S200C, the cloud platform determines equipment monitoring parameters according to the outdoor parameters and the indoor parameters;
and step S200D, the cloud platform establishes a hierarchical structure model according to the determined equipment type, equipment process and monitoring parameters.
A hierarchical structure model is built through the above method, fig. 4 is a schematic diagram of a hierarchical structure model provided in an embodiment of the present application, and as shown in fig. 4, in the hierarchical structure model, a target refrigeration system and a target operating parameter may be selected by clicking a corresponding option. In the embodiment of the application, when the detection scheme is configured, the model lists all the monitorable parameters for the user to select, and in the using process, the corresponding parameters can be selected according to specific detection and control contents without manual setting and addition.
In some embodiments, when the target operating parameter has a variation range that is not within a pre-stored parameter variation threshold, the method may further comprise:
and step S206, the cloud platform determines the fault reason of the target refrigeration system according to the target operation parameters and a prestored fault experience database.
In the embodiment of the application, possible fault reasons corresponding to abnormal parameters are stored in the fault experience database. The target operation parameters can be compared with the data in the fault experience database, and further the possible fault reasons can be determined.
And step S207, generating a fault analysis report and sending fault early warning prompt information according to the fault reason.
In the embodiment of the application, after the fault analysis report is generated, the fault analysis report can be stored in the cloud platform and also can be sent to a mobile phone, a tablet computer, a desktop computer or a notebook computer of a user. An administrator supervises the refrigeration system all over the world at any time through a mobile phone and a computer, and breaks the time and space limitation of management.
In some embodiments, when the target operating parameter has a variation range that is not within a pre-stored parameter variation threshold, the method may further comprise:
and step S208, the cloud platform determines the operation condition of the target refrigeration system according to the target operation parameters and a prestored operation experience database.
In an embodiment of the present application, the running the experience database may include: historical operating databases and expert databases, etc. When the target operating parameters are received, the target operating parameters can be compared and analyzed with data in the operating experience database to determine the operating condition of the target refrigeration system.
In some embodiments, future operating conditions may also be predicted.
And S209, generating an operation analysis report by the cloud platform according to the operation condition of the target refrigeration system.
In the embodiment of the application, after the operation analysis report is generated, the operation analysis report can be stored in the cloud platform, and also can be sent to a mobile phone, a tablet computer, a desktop computer or a notebook computer of a user. An administrator supervises the refrigeration system all over the world at any time through a mobile phone and a computer, and breaks the time and space limitation of management.
In some embodiments, a parameter change threshold, an operation experience database and a fault experience database may be preset in the cloud platform; in the embodiment of the application, a fault experience database records possible faults and solutions, and presets a fault early warning information template, a fault analysis report template, an operation analysis report template and an energy management report template; the detected parameter change is compared with a parameter change threshold value, then whether a fault or operation is in a problem is judged, and if the change exceeds the threshold value, the operation is judged to be in a problem or a fault according to the operation experience database and the fault experience database. And pushing a fault early warning signal, a fault analysis report, an operation analysis report or an energy management report according to the change condition of the detected parameter value and the user requirement.
The invention relates to a cloud management platform for a refrigeration system, wherein a hierarchical structure is adopted for modeling; all types of refrigeration systems can be expanded to a cloud platform by setting user information and checking and determining corresponding refrigerants and system modules; setting a sensor in a refrigeration system according to management needs or user needs, converting detection signals, and converting analog quantity or switching value into electric signals; capturing effective information by adopting an artificial intelligence deep learning algorithm, and adjusting and operating to a safe and efficient state in time by taking an energy efficiency ratio as a target function; the detection device transmits the electric signal to the cloud management platform through GPRS and platform data synchronization; the cloud management platform analyzes and generates files such as a fault analysis report, an energy management report, a use suggestion report and the like according to the detection signals according to the user requirements; the user carries out man-machine conversation through the user sides such as a mobile phone, a tablet computer, a desktop computer and a notebook computer and receives related files. The management platform creates a cloud-based refrigeration management mode, establishes a full-life-cycle operation file of the refrigeration system for a client, and realizes supervision of the refrigeration system by a manager in various regions and at any time all over the world through a mobile phone and a computer; the management is convenient and reliable, the cost is low, the time and space limitation of the management is broken, and the management system can meet the requirement of modern logistics management.
Based on the foregoing embodiments, the present application provides a refrigeration system management apparatus, where the apparatus includes modules and units included in the modules, and the modules may be implemented by a processor in a computer device; of course, the implementation can also be realized through a specific logic circuit; in the implementation process, the processor may be a Central Processing Unit (CPU), a Microprocessor Unit (MPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or the like.
An embodiment of the present application further provides a refrigeration system management device, fig. 5 is a schematic structural diagram of the refrigeration system management device provided in the embodiment of the present application, and as shown in fig. 5, the refrigeration system management device 500 includes:
a first obtaining module 501, configured to obtain a target operation parameter from a target refrigeration system that establishes a communication connection with a hierarchical structure model based on receiving an obtaining instruction for the target operation parameter in the hierarchical structure model, where the hierarchical structure model includes a target refrigeration system option and an operation parameter option;
a determining module 502, configured to determine whether a variation range of the target operating parameter is within a pre-stored parameter variation threshold;
an adjusting module 503, configured to determine a target adjusting parameter of the target operating parameter according to a pre-stored energy consumption model when a variation range of the target operating parameter is not within a pre-stored parameter variation threshold;
a first generating module 504, configured to generate a control instruction according to the target adjustment parameter;
a first sending module 505, configured to send the control instruction to the target refrigeration system, so that the refrigeration system adjusts its own operating parameter according to the target adjustment parameter.
In some embodiments, the refrigeration system management apparatus 500 further comprises:
the first acquisition module is used for acquiring historical operating parameters and historical energy consumption;
and the second determining module is used for determining a pre-stored energy consumption model based on a deep learning algorithm according to the historical operating parameters and the historical energy consumption.
In some embodiments, the refrigeration system management apparatus 500 further comprises:
the second determining module is used for determining the equipment type according to the equipment type, the refrigerant working medium and the number of the evaporation areas;
the third determining module is used for determining equipment and process according to the evaporation system, the compression system and the condensation system;
the fourth determining module is used for determining the equipment monitoring parameters according to the outdoor parameters and the indoor parameters;
and the establishing module is used for establishing a hierarchical structure model according to the determined equipment type, equipment process and monitoring parameters.
In some embodiments, the refrigeration system management apparatus 500 further comprises:
a sixth determining module, configured to determine a cause of a fault in the target refrigeration system according to the target operating parameter and a prestored fault experience database when a variation range of the target operating parameter is not within a prestored parameter variation threshold;
and the second generation module is used for generating a fault analysis report and sending out fault early warning prompt information according to the fault reason.
In some embodiments, the refrigeration system management apparatus 500 further comprises:
a seventh determining module, configured to determine, when the variation range of the target operation parameter is not within a pre-stored parameter variation threshold, an operation condition of the target refrigeration system according to the target operation parameter and a pre-stored operation experience database;
and the third production module is used for generating an operation analysis report according to the operation condition of the target refrigeration system.
In some embodiments, the refrigeration system management apparatus 500 further comprises:
the receiving module is used for receiving an analysis report acquisition instruction sent by the first terminal equipment;
and the second sending module is used for responding to and acquiring an analysis report instruction and sending the analysis report to the first terminal equipment.
The above description of the apparatus embodiments, similar to the above description of the method embodiments, has similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the apparatus of the present application, reference is made to the description of the embodiments of the method of the present application for understanding.
It should be noted that, in the embodiment of the present application, if the refrigeration system management method is implemented in the form of a software functional module and is sold or used as a standalone product, the method may also be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially implemented or portions thereof contributing to the prior art may be embodied in the form of a software product stored in a storage medium, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, or an optical disk. Thus, embodiments of the present application are not limited to any specific combination of hardware and software.
Accordingly, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, wherein the computer program is executed by a processor to implement the steps in the refrigeration system management method provided in the above embodiment.
An embodiment of the present application provides a cloud platform, fig. 6 is a schematic diagram of a composition structure of the cloud platform provided in the embodiment of the present application, and as shown in fig. 6, the refrigeration system management apparatus 600 includes: a processor 601, at least one communication bus 602, a user interface 603, at least one external communication interface 604, and memory 605. Wherein the communication bus 602 is configured to enable connective communication between these components. The user interface 603 may comprise a display screen, and the external communication interface 604 may comprise a standard wired interface and a wireless interface, among others. Wherein the processor 601 is configured to execute the program of the refrigeration system management method stored in the memory to realize the steps of the refrigeration system management method provided in the above embodiment
The above description of the refrigeration system management apparatus and storage medium embodiments is similar to the description of the method embodiments described above, with similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the refrigeration system management apparatus and storage medium of the present application, reference is made to the description of the embodiments of the method of the present application for understanding.
Here, it should be noted that: the above description of the storage medium and device embodiments is similar to the description of the method embodiments above, with similar advantageous effects as the method embodiments. For technical details not disclosed in the embodiments of the storage medium and apparatus of the present application, reference is made to the description of the embodiments of the method of the present application for understanding.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
Alternatively, the integrated units described above in the present application may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as independent products. Based on such understanding, the technical solutions of the embodiments of the present application may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a controller to execute all or part of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The above description is only for the embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. A method of refrigerant system management, the method comprising:
acquiring target operation parameters from a target refrigeration system which is in communication connection with the target refrigeration system based on receiving an acquisition instruction aiming at the target operation parameters in a hierarchical structure model stored in the hierarchical structure model, wherein the hierarchical structure model comprises target refrigeration system options and operation parameter options;
judging whether the variation range of the target operation parameter is within a prestored parameter variation threshold value;
when the variation range of the target operation parameter is not within the pre-stored parameter variation threshold, determining a target adjustment parameter of the target operation parameter according to a pre-stored energy consumption model;
generating a control instruction according to the target adjustment parameter;
and sending the control instruction to the target refrigeration system so that the refrigeration system adjusts the self operating parameters according to the target adjustment parameters.
2. The method of claim 1, further comprising:
acquiring historical operating parameters and historical energy consumption;
and obtaining a pre-stored energy consumption model based on a deep learning algorithm according to the historical operating parameters and the historical energy consumption.
3. The method of claim 1, further comprising:
determining the equipment type according to the equipment type, the refrigerant working medium and the number of the evaporators;
determining equipment and process according to the evaporation system, the compression system and the condensation system;
determining equipment monitoring parameters according to the outdoor parameters and the indoor parameters;
and establishing a hierarchical structure model according to the determined equipment type, equipment process and monitoring parameters.
4. The method of claim 1, further comprising:
when the variation range of the target operation parameter is not within the prestored parameter variation threshold value, determining the fault reason of the target refrigeration system according to the target operation parameter and a prestored fault experience database;
and generating a fault analysis report and sending fault early warning prompt information according to the fault reason.
5. The method of claim 1, further comprising:
when the variation range of the target operation parameter is not within the prestored parameter variation threshold value, determining the operation condition of the target refrigeration system according to the target operation parameter and a prestored operation experience database;
and generating an operation analysis report according to the operation condition of the target refrigeration system.
6. The method according to any one of claims 3 to 4, further comprising:
receiving an analysis report acquisition instruction sent by first terminal equipment;
and responding and acquiring an analysis report instruction, and sending the analysis report to the first terminal equipment.
7. A refrigeration system management apparatus, the apparatus comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring target operation parameters from a target refrigeration system which is in communication connection with the first acquisition module on the basis of receiving an acquisition instruction aiming at the target operation parameters in a hierarchical structure model, and the hierarchical structure model comprises target refrigeration system options and operation parameter options;
the judging module is used for judging whether the variation range of the target operation parameter is within a prestored parameter variation threshold value;
the adjusting module is used for determining a target adjusting parameter of the target operating parameter according to a prestored energy consumption model when the variation range of the target operating parameter is not within a prestored parameter variation threshold;
the first generation module is used for generating a control instruction according to the target adjustment parameter;
and the first sending module is used for sending the control instruction to the target refrigerating system so as to enable the refrigerating system to adjust the self operating parameters according to the target adjusting parameters.
8. A refrigeration system management cloud platform, the management cloud platform comprising:
a processor; and
a memory for storing a computer program operable on the processor;
wherein the computer program when executed by a processor performs the steps of the refrigeration system management method of any one of claims 1 to 6.
9. A storage medium having stored therein computer-executable instructions configured to perform the steps of the refrigeration system management method of any of claims 1 to 6.
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