CN116857854A - Intelligent oil return control method, device, equipment, storage medium and intelligent equipment - Google Patents
Intelligent oil return control method, device, equipment, storage medium and intelligent equipment Download PDFInfo
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- CN116857854A CN116857854A CN202310757935.3A CN202310757935A CN116857854A CN 116857854 A CN116857854 A CN 116857854A CN 202310757935 A CN202310757935 A CN 202310757935A CN 116857854 A CN116857854 A CN 116857854A
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- 238000000034 method Methods 0.000 title claims abstract description 67
- 238000012545 processing Methods 0.000 claims abstract description 46
- 238000013528 artificial neural network Methods 0.000 claims abstract description 17
- 238000012549 training Methods 0.000 claims abstract description 15
- 230000002159 abnormal effect Effects 0.000 claims description 70
- 230000007613 environmental effect Effects 0.000 claims description 24
- 230000008439 repair process Effects 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 13
- 230000005856 abnormality Effects 0.000 claims description 8
- 238000012216 screening Methods 0.000 claims description 5
- 239000003921 oil Substances 0.000 description 370
- 238000004891 communication Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 238000010801 machine learning Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 238000005457 optimization Methods 0.000 description 4
- 238000005057 refrigeration Methods 0.000 description 4
- 238000004378 air conditioning Methods 0.000 description 3
- 238000013500 data storage Methods 0.000 description 3
- 239000010725 compressor oil Substances 0.000 description 2
- 238000003066 decision tree Methods 0.000 description 2
- 238000012417 linear regression Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012706 support-vector machine Methods 0.000 description 2
- 108010053481 Antifreeze Proteins Proteins 0.000 description 1
- 208000033999 Device damage Diseases 0.000 description 1
- 230000002528 anti-freeze Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003507 refrigerant Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000004148 unit process Methods 0.000 description 1
Classifications
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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
- F25B31/00—Compressor arrangements
- F25B31/002—Lubrication
- F25B31/004—Lubrication oil recirculating arrangements
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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
- F25B49/02—Arrangement or mounting of control or safety devices for compression type machines, plants or systems
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- Mechanical Engineering (AREA)
- Thermal Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The application provides an intelligent oil return control method, device, equipment, storage medium and intelligent equipment, and relates to the technical field of oil return. The method comprises the following steps: receiving the equipment data of the intelligent equipment acquired by the sensor group in real time; under the condition of equipment data updating, inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting equipment data samples and oil return frequency samples into a preset neural network for training; and controlling the intelligent equipment to execute oil return operation at the oil return frequency. According to the embodiment of the application, the oil return frequency is predicted through the oil return prediction model, the intelligent equipment is controlled to execute the oil return operation at the oil return frequency, the normal oil return of the compressor can be ensured, the operation efficiency and the reliability of the intelligent equipment are improved, and the experience of a user is further improved.
Description
Technical Field
The present application relates to the field of oil return technologies, and in particular, to an intelligent oil return control method, device, equipment, storage medium, and intelligent equipment.
Background
The air conditioner outdoor unit or the refrigeration equipment is provided with oil which can ensure the normal operation of the compressor when leaving the factory. However, when the unit is operated, compressor oil flows in the pipeline along with the refrigerant, and the compressor is starved due to daily loss, poor system control scheme and the like, so that the compressor is damaged finally.
For most air conditioning or refrigeration equipment, it is common practice in the industry to accumulate the operating time of the unit and to periodically force oil return according to the operating parameters of the unit. The disadvantage of this approach is that each manufacturer is typically provided with a sufficient amount of oil to ensure that the amount of oil in the compressor must be sufficient during the present period to ensure compliance with various market conditions. The existing oil return frequency is a fixed period, the compressor oil quantity is enough in normal use, oil return operation is not needed, but the oil return condition is reached, the unit executes the forced oil return operation logic, the operation efficiency and the reliability of the equipment are affected, and the user experience is also affected.
Disclosure of Invention
The application provides an intelligent oil return control method, an intelligent oil return control device, intelligent oil return control equipment, storage media and intelligent equipment, wherein oil return frequency is predicted through an oil return prediction model, the intelligent equipment is controlled to execute oil return operation at the oil return frequency, normal oil return of a compressor can be ensured, and the operation efficiency and reliability of the intelligent equipment are improved.
In a first aspect, the present application provides an intelligent oil return control method, applied to a controller, where the controller is connected to a sensor group through an electrical signal, and the sensor group is connected to an intelligent device through an electrical signal, and the intelligent oil return control method includes:
receiving the equipment data of the intelligent equipment acquired by the sensor group in real time;
inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting an equipment data sample and an oil return frequency sample into a preset neural network for training;
and controlling the intelligent equipment to execute oil return operation at the oil return frequency.
Preferably, according to the intelligent oil return control method provided by the application,
and inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the method comprises the following steps of:
performing exception analysis processing on the equipment data;
under the condition that no abnormal data exists in the equipment data, analyzing the equipment data to obtain the equipment state data and the environmental condition data of the intelligent equipment;
judging whether an oil return operation needs to be executed according to the equipment state data and the environmental condition data;
and under the condition that the oil return operation is required to be executed, inputting the equipment state data and the environmental condition data into the oil return prediction model for processing, and outputting the oil return frequency.
Preferably, according to the intelligent oil return control method provided by the application,
after the step of performing exception analysis processing on the device data, the method further includes:
under the condition that the abnormal data exists in the equipment data, carrying out identification processing on the abnormal data to obtain abnormal identification data;
screening the abnormal identification data from the equipment data, analyzing and processing the abnormal identification data, and determining an abnormal reason corresponding to the abnormal identification data;
acquiring a corresponding abnormality repair strategy according to the abnormality cause;
and adjusting the equipment parameters of the intelligent equipment according to the abnormal repair strategy so as to repair the abnormal data into normal data.
Preferably, according to the intelligent oil return control method provided by the application,
after the step of controlling the smart device to perform an oil return operation at the oil return frequency, the method further includes:
acquiring the current oil return frequency of the intelligent equipment through the sensor group;
comparing the current oil return frequency with the oil return frequency;
generating abnormal information of abnormal oil return of the intelligent equipment under the condition that the current oil return frequency is smaller than the oil return frequency, and displaying the abnormal information of abnormal oil return of the intelligent equipment on a preset display interface;
and under the condition that the current oil return frequency is greater than or equal to the oil return frequency, generating normal information of normal oil return of the intelligent equipment, and displaying the normal information of normal oil return of the intelligent equipment on the display interface.
Preferably, according to the intelligent oil return control method provided by the application,
after the step of controlling the smart device to perform an oil return operation at the oil return frequency, the method further includes:
acquiring oil return quantity of the intelligent equipment for executing oil return operation at the oil return frequency;
and stopping oil return operation and displaying the oil return amount on the display interface under the condition that the oil return amount is larger than or equal to a preset oil return threshold value.
Preferably, according to the intelligent oil return control method provided by the application,
after the step of obtaining the oil return amount of the oil return operation performed by the intelligent device at the oil return frequency, the method further includes:
counting the oil return time length of the intelligent equipment for executing the oil return operation at the oil return frequency;
comparing the oil return time with a preset time threshold;
suspending oil return operation when the oil return time reaches the time threshold and the oil return quantity is smaller than the oil return threshold;
and under the condition that the pause duration of the oil return operation reaches a preset pause threshold value, controlling the intelligent equipment to execute the oil return operation at the oil return frequency again until the oil return amount reaches the oil return threshold value, and stopping the oil return operation.
In a second aspect, the present application further provides an intelligent oil return control device, applied to a controller, where the controller is connected to a sensor group through an electrical signal, and the sensor group is connected to an intelligent device through an electrical signal, and the intelligent oil return control device includes:
the receiving module is used for receiving the equipment data of the intelligent equipment acquired by the sensor group in real time;
the prediction module is used for inputting the updated equipment data to an oil return prediction model for processing under the condition of equipment data updating, wherein the oil return prediction model is obtained by inputting an equipment data sample and an oil return frequency sample into a preset neural network for training;
and the control module is used for controlling the intelligent equipment to execute oil return operation at the oil return frequency.
In a third aspect, the present application also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the steps of any one of the above-mentioned intelligent oil return control methods are implemented when the processor executes the program.
In a fourth aspect, the present application also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the intelligent oil return control method as described in any of the above.
In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the intelligent oil return control method as described in any one of the above.
In a sixth aspect, the present application further provides an intelligent device, where the intelligent device at least includes a controller, where the controller is connected to the sensor group through an electrical signal, and the controller implements the steps of the intelligent oil return control method according to any one of the above.
According to the intelligent oil return control method, the device, the equipment, the storage medium and the intelligent equipment, equipment data of the intelligent equipment are collected in real time through the sensor group; inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting an equipment data sample and an oil return frequency sample into a preset neural network for training; and controlling the intelligent equipment to execute oil return operation at the oil return frequency. The oil return frequency is predicted through the oil return prediction model, the intelligent equipment is controlled to execute oil return operation at the oil return frequency, normal oil return of the compressor can be ensured, and the operation efficiency and reliability of the intelligent equipment are improved.
Drawings
In order to more clearly illustrate the application or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an intelligent oil return control method provided by the application;
FIG. 2 is a second flow chart of the intelligent oil return control method according to the present application;
FIG. 3 is a schematic diagram of the structure of the intelligent oil return control device provided by the application;
fig. 4 is a schematic structural diagram of an electronic device provided by the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The following describes an intelligent oil return control method, an intelligent oil return control device, intelligent oil return control equipment, storage media and intelligent equipment with reference to fig. 1-4.
As shown in fig. 1, which is one of implementation flow diagrams of an intelligent oil return control method according to an embodiment of the present application, the intelligent oil return control method may include, but is not limited to, steps S100 to S300.
S100, receiving device data of the intelligent device acquired by the sensor group in real time;
s200, under the condition that the equipment data is updated, inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting an equipment data sample and an oil return frequency sample into a preset neural network for training;
s300, controlling the intelligent equipment to execute oil return operation at the oil return frequency.
It should be noted that, an execution body of an intelligent oil return control method according to an embodiment of the present application may be a hardware device with data information processing capability and/or necessary software for driving the hardware device to work.
Alternatively, the execution body may include, but is not limited to, workstations, servers, computers, user terminals, and other intelligent devices. The user terminal comprises, but is not limited to, a mobile phone, a computer, intelligent voice interaction equipment, intelligent household appliances, vehicle-mounted terminals and the like.
The intelligent oil return control method provided by the application is applied to a controller, wherein the controller is connected with a sensor group through an electric signal, and the sensor group is connected with intelligent equipment through the electric signal.
In step S100 of some embodiments, device data of the smart device acquired in real time by the sensor group is received.
It is understood that the sensor group may include at least, but is not limited to, a temperature sensor, a pressure sensor, a load sensor, and the like.
The temperature sensor is used for detecting the temperature of the intelligent equipment, the pressure sensor is used for detecting the pressure of the intelligent equipment, and the load sensor is used for detecting the load of the intelligent equipment.
The sensor group is used for monitoring and collecting equipment data of the intelligent equipment in real time.
It should be noted that the intelligent device may be an air conditioner, or may be other devices that need to perform an oil return operation.
In step S200 of some embodiments, in the case of updating the device data, the updated device data is input to the oil return prediction model process, and the oil return frequency of the oil return operation is output.
It should be noted that, the oil return prediction model is obtained by inputting the equipment data sample and the oil return frequency sample into a preset neural network for training.
It may be appreciated that, after the step of receiving the device data of the intelligent device acquired in real time by the sensor group in step S100 is performed, the specific performing steps may be: under the condition of updating the collected equipment data, the updated equipment data is input into a trained oil return prediction model for prediction processing, so that the oil return frequency of the intelligent equipment for executing oil return operation is dynamically predicted.
It should be further noted that, once the device data is updated, the new oil return frequency is predicted again, and the oil return frequency of the intelligent device for executing the oil return operation is adjusted in time.
The oil return prediction model is obtained by inputting a large number of equipment data samples and oil return frequency samples into a preset neural network for training.
The neural network may include, but is not limited to, a machine learning model constructed based on a meta-linear regression model, a decision tree model, a support vector machine model, etc., which may be selectively determined according to actual conditions and requirements.
Further, in some embodiments of the present application, the inputting the updated device data to the oil return prediction model process, outputting the oil return frequency of the oil return operation includes:
performing exception analysis processing on the equipment data;
under the condition that no abnormal data exists in the equipment data, analyzing the equipment data to obtain the equipment state data and the environmental condition data of the intelligent equipment;
judging whether an oil return operation needs to be executed according to the equipment state data and the environmental condition data;
and under the condition that the oil return operation is required to be executed, inputting the equipment state data and the environmental condition data into the oil return prediction model for processing, and outputting the oil return frequency.
It can be understood that the device data collected by the sensor group is subjected to anomaly analysis processing, and the device data is analyzed and processed to obtain the device state data and the environmental condition data of the intelligent device under the condition that no anomaly data exists in the device data.
Judging whether the oil return operation needs to be executed according to the equipment state data and the environmental condition data, and judging that the oil return operation needs to be executed when the equipment state data and the environmental condition data meet the condition of executing the oil return operation. And under the condition that the oil return operation is required to be executed, inputting the equipment state data and the environmental condition data into the oil return prediction model for processing, and outputting the oil return frequency.
Further, after the step of performing the anomaly analysis processing on the device data, the method further includes:
under the condition that the abnormal data exists in the equipment data, carrying out identification processing on the abnormal data to obtain abnormal identification data;
screening the abnormal identification data from the equipment data, analyzing and processing the abnormal identification data, and determining an abnormal reason corresponding to the abnormal identification data;
acquiring a corresponding abnormality repair strategy according to the abnormality cause;
and adjusting the equipment parameters of the intelligent equipment according to the abnormal repair strategy so as to repair the abnormal data into normal data.
It can be understood that after the device data collected by the sensor group is subjected to the anomaly analysis processing, it is determined that the collected device data has anomaly data, and then the anomaly data is subjected to the identification processing so as to conveniently and quickly screen out the anomaly identification data.
And screening the abnormal identification data from the equipment data based on the annotated identification, analyzing and processing the abnormal identification data, and analyzing an abnormal reason corresponding to the abnormal identification data.
And searching a corresponding abnormal repair strategy from a solution library according to the abnormal cause, so as to adjust relevant equipment parameters of the intelligent equipment according to the abnormal repair strategy, and repairing the abnormal data into normal data according to the adjustment of the equipment parameters.
In step S300 of some embodiments, the smart device is controlled to perform an oil return operation at the oil return frequency.
It may be understood that after the step of inputting the updated device data to the oil return prediction model process and outputting the oil return frequency of the oil return operation in step S200 is performed, the specific implementation steps may be: and controlling the intelligent equipment to execute oil return operation at the predicted oil return frequency.
The oil return frequency is dynamically adjusted, namely, once equipment data acquired by utilizing the sensor group is changed, the oil return frequency is changed, so that the running efficiency and the reliability of the intelligent equipment can be improved by executing oil return operation at the dynamic oil return frequency.
In some embodiments of the present application, after the step of controlling the smart device to perform an oil return operation at the oil return frequency, the method further includes:
acquiring the current oil return frequency of the intelligent equipment through the sensor group;
comparing the current oil return frequency with the oil return frequency;
generating abnormal information of abnormal oil return of the intelligent equipment under the condition that the current oil return frequency is smaller than the oil return frequency, and displaying the abnormal information of abnormal oil return of the intelligent equipment on a preset display interface;
and under the condition that the current oil return frequency is greater than or equal to the oil return frequency, generating normal information of normal oil return of the intelligent equipment, and displaying the normal information of normal oil return of the intelligent equipment on the display interface.
It can be understood that the sensor group is utilized to acquire the current oil return frequency of the intelligent device for executing the oil return operation, the current oil return frequency is compared with the oil return frequency predicted by the oil return prediction model, and under the condition that the current oil return frequency is smaller than the oil return frequency, the intelligent device is determined to not execute the oil return operation according to the predicted oil return frequency, so that the intelligent device is determined to be abnormal oil return, abnormal information of abnormal oil return of the intelligent device is generated, the abnormal information of abnormal oil return of the intelligent device is displayed on a preset display interface, and the intelligent device damage caused by less oil return quantity of the intelligent device due to abnormal oil return can be avoided.
And under the condition that the current oil return frequency is greater than or equal to the oil return frequency, generating normal information of normal oil return of the intelligent equipment, and displaying the normal information of normal oil return of the intelligent equipment on the display interface, so that a user is directly informed of the normal oil return operation of the intelligent equipment, and the user can know the oil return condition of the intelligent equipment conveniently.
In some embodiments of the present application, after the step of controlling the smart device to perform an oil return operation at the oil return frequency, the method further includes:
acquiring oil return quantity of the intelligent equipment for executing oil return operation at the oil return frequency;
and stopping oil return operation and displaying the oil return amount on the display interface under the condition that the oil return amount is larger than or equal to a preset oil return threshold value.
It is understood that a flow detection assembly is arranged at the oil return pipeline of the intelligent device and is used for detecting the oil return quantity flowing through the oil return pipeline. And detecting the oil return quantity generated by the oil return operation executed by the intelligent equipment at the predicted oil return frequency by utilizing the flow detection assembly, and comparing the detected oil return quantity with a preset oil return threshold value.
And stopping oil return operation under the condition that the oil return amount is larger than or equal to a preset oil return threshold value, so as to avoid excessive oil return. And displaying the oil return quantity detected by the flow detection assembly on the display interface.
In some embodiments of the present application, after the step of obtaining the oil return amount of the oil return operation performed by the smart device at the oil return frequency, the method further includes:
counting the oil return time length of the intelligent equipment for executing the oil return operation at the oil return frequency;
comparing the oil return time with a preset time threshold;
suspending oil return operation when the oil return time reaches the time threshold and the oil return quantity is smaller than the oil return threshold;
and under the condition that the pause duration of the oil return operation reaches a preset pause threshold value, controlling the intelligent equipment to execute the oil return operation at the oil return frequency again until the oil return amount reaches the oil return threshold value, and stopping the oil return operation.
It can be understood that after the oil return amount is compared with the oil return threshold, counting the oil return time length of the intelligent device for executing the oil return operation at the oil return frequency, comparing the oil return time length with a preset time length threshold, and if the oil return time length reaches the set time length threshold and the oil return amount is smaller than the oil return threshold, suspending the oil return operation. And under the condition that the pause duration of the oil return operation reaches a preset pause threshold value, controlling the intelligent equipment to execute the oil return operation at the oil return frequency again until the oil return amount reaches the oil return threshold value, and stopping the oil return operation.
As shown in fig. 2, which is a second schematic diagram provided in the present application, when the intelligent device starts to operate, the sensor group starts to monitor the operation state and the environmental condition of the intelligent device, collects device data, that is, operation state data and environmental condition data, and then sends the operation state data and the environmental condition data to the control unit.
Data processing and decision: after receiving the running state data and the environmental condition data, the control unit processes and analyzes the data by utilizing a machine learning optimization algorithm, and then decides whether oil return operation is needed or not and predicts the oil return frequency for executing the oil return operation.
And (3) performing oil return operation: if the control unit decides that an oil return operation is required, it will perform the oil return operation by controlling other components of the device.
Fault detection and handling: if the control unit detects a device failure during data processing and analysis, it will activate an automatic failure detection and handling module to resolve the anomaly.
Prediction and reminding: the control unit predicts according to the historical data and the current data, and then reminds a user or maintainer of upcoming oil return operation through a display panel or a network interface.
And (3) data storage: the control unit will store all operational data and decision results in the data storage and processing unit for subsequent analysis and optimization.
And a control unit: the control unit is responsible for the operation and control of the whole system. It dynamically adjusts the oil return frequency of the oil return operation based on data received from various sensors and optimization algorithms based on machine learning.
A sensor group: the sensor group comprises a temperature sensor, a pressure sensor, a load sensor and the like and is used for monitoring the running state and the environmental condition of the equipment in real time. The data of the sensor group is sent to the control unit for decision making and control.
Display panel or network interface: the display panel or the network interface is used for displaying the running state information of the equipment and the scheduling and executing conditions of the oil return operation. In addition, the control unit can also remind the user or maintenance personnel of the impending oil return operation through the interface.
Automatic fault detection and processing module: this module may automatically process when the control unit receives anomaly data from the sensor group, for example, when an anti-freeze or low pressure, etc. failure of the device is detected, the control unit may adjust the oil return frequency or other device parameters to account for the anomaly.
Data storage and processing unit: the unit is responsible for storing the data collected from the sensor group and the various decisions and control instructions generated by the control unit. It also includes a processor for implementing a machine learning optimization algorithm.
The following is an example to illustrate this process: let us assume that we have intelligent devices and environmental parameters: the equipment load was 80%, the compressor temperature was 70 ℃, the pressure was 200psi, the indoor temperature was 22 ℃, and the outdoor temperature was 30 ℃. All of these data are monitored in real time by the sensor group and sent to the control unit. After the control unit receives the data, it uses a pre-trained machine learning model for processing and analysis. This model may be a multiple linear regression model or may be a more complex model of decision tree, support vector machine, neural network, etc. The specific machine learning model used can be selected according to actual conditions and requirements. This model predicts the optimal scavenge frequency for the scavenge operation based on the input equipment and environmental parameters. It is assumed that the predicted result is an optimal frequency threshold for the oil return operation of 20 minutes once. The control unit will then adjust the oil return operating frequency of the device to this new threshold. This process is dynamic, that is, it is re-predicted and adjusted each time a new data is received by the control unit. Therefore, the frequency threshold value of the oil return operation can be optimized according to the real-time running state and the environmental condition of the equipment, so that the running efficiency and the reliability of the equipment are improved.
The system may be implemented as a stand-alone hardware device or as a built-in function of a device. For example, it may be integrated into the control panel of an air conditioning or refrigeration appliance or may be a stand-alone appliance that interacts with the air conditioning or refrigeration appliance via a network or other communication means.
According to the intelligent oil return control method, the device, the equipment, the storage medium and the intelligent equipment, equipment data of the intelligent equipment are collected in real time through the sensor group; inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting an equipment data sample and an oil return frequency sample into a preset neural network for training; and controlling the intelligent equipment to execute oil return operation at the oil return frequency. The oil return frequency is predicted through the oil return prediction model, the intelligent equipment is controlled to execute oil return operation at the oil return frequency, normal oil return of the compressor can be ensured, the operation efficiency and reliability of the intelligent equipment are improved, and the experience of a user is further improved.
The following describes an intelligent oil return control device provided by the application, and the intelligent oil return control device and the intelligent oil return control method described below can be correspondingly referred to each other.
As shown in fig. 3, which is a schematic structural diagram of an intelligent oil return control device provided by the application, the intelligent oil return control device provided by the application is applied to a controller, the controller is connected with a sensor group through an electric signal, the sensor group is connected with an intelligent device through an electric signal, and the intelligent oil return control device comprises:
a receiving module 310, configured to receive device data of the intelligent device collected in real time by the sensor group;
the prediction module 320 is configured to input the updated device data to an oil return prediction model for processing and output an oil return frequency of an oil return operation under the condition that the device data is updated, where the oil return prediction model is obtained by inputting a device data sample and an oil return frequency sample into a preset neural network for training;
and the control module 330 is configured to control the intelligent device to perform an oil return operation at the oil return frequency.
Preferably, the prediction module 320 is specifically configured to perform exception analysis processing on the device data;
under the condition that no abnormal data exists in the equipment data, analyzing the equipment data to obtain the equipment state data and the environmental condition data of the intelligent equipment;
judging whether an oil return operation needs to be executed according to the equipment state data and the environmental condition data;
and under the condition that the oil return operation is required to be executed, inputting the equipment state data and the environmental condition data into the oil return prediction model for processing, and outputting the oil return frequency.
Preferably, in the intelligent oil return control device provided by the application, the prediction module 320 is specifically configured to perform identification processing on the abnormal data to obtain abnormal identification data when it is determined that the abnormal data exists in the device data;
screening the abnormal identification data from the equipment data, analyzing and processing the abnormal identification data, and determining an abnormal reason corresponding to the abnormal identification data;
acquiring a corresponding abnormality repair strategy according to the abnormality cause;
and adjusting the equipment parameters of the intelligent equipment according to the abnormal repair strategy so as to repair the abnormal data into normal data.
Preferably, after the step of controlling the intelligent device to perform the oil return operation at the oil return frequency, the intelligent oil return control device is specifically configured to obtain the current oil return frequency of the intelligent device through the sensor group;
comparing the current oil return frequency with the oil return frequency;
generating abnormal information of abnormal oil return of the intelligent equipment under the condition that the current oil return frequency is smaller than the oil return frequency, and displaying the abnormal information of abnormal oil return of the intelligent equipment on a preset display interface;
and under the condition that the current oil return frequency is greater than or equal to the oil return frequency, generating normal information of normal oil return of the intelligent equipment, and displaying the normal information of normal oil return of the intelligent equipment on the display interface.
Preferably, after the step of controlling the intelligent device to perform the oil return operation at the oil return frequency, the intelligent device is specifically configured to obtain an oil return amount of the intelligent device to perform the oil return operation at the oil return frequency;
and stopping oil return operation and displaying the oil return amount on the display interface under the condition that the oil return amount is larger than or equal to a preset oil return threshold value.
Preferably, after the step of obtaining the oil return amount of the oil return operation performed by the intelligent device at the oil return frequency, the intelligent oil return control device is specifically configured to count the oil return duration of the oil return operation performed by the intelligent device at the oil return frequency;
comparing the oil return time with a preset time threshold;
suspending oil return operation when the oil return time reaches the time threshold and the oil return quantity is smaller than the oil return threshold;
and under the condition that the pause duration of the oil return operation reaches a preset pause threshold value, controlling the intelligent equipment to execute the oil return operation at the oil return frequency again until the oil return amount reaches the oil return threshold value, and stopping the oil return operation.
According to the intelligent oil return control method, the device, the equipment, the storage medium and the intelligent equipment, equipment data of the intelligent equipment are collected in real time through the sensor group; inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting an equipment data sample and an oil return frequency sample into a preset neural network for training; and controlling the intelligent equipment to execute oil return operation at the oil return frequency. The oil return frequency is predicted through the oil return prediction model, the intelligent equipment is controlled to execute oil return operation at the oil return frequency, normal oil return of the compressor can be ensured, the operation efficiency and reliability of the intelligent equipment are improved, and the experience of a user is further improved.
Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include: processor 410, communication interface (Communications Interface) 420, memory 430 and communication bus 440, wherein processor 410, communication interface 420 and memory 430 communicate with each other via communication bus 440. Processor 410 may invoke logic instructions in memory 430 to perform an intelligent oil return control method comprising: receiving the equipment data of the intelligent equipment acquired by the sensor group in real time; under the condition of equipment data updating, inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting equipment data samples and oil return frequency samples into a preset neural network for training; and controlling the intelligent equipment to execute oil return operation at the oil return frequency.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present application also provides a computer program product, where the computer program product includes a computer program, where the computer program can be stored on a non-transitory computer readable storage medium, and when the computer program is executed by a processor, the computer can execute an intelligent oil return control method provided by the above methods, and the method includes: receiving the equipment data of the intelligent equipment acquired by the sensor group in real time; under the condition of equipment data updating, inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting equipment data samples and oil return frequency samples into a preset neural network for training; and controlling the intelligent equipment to execute oil return operation at the oil return frequency.
In yet another aspect, the present application further provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform an intelligent oil return control method provided by the above methods, the method comprising: receiving the equipment data of the intelligent equipment acquired by the sensor group in real time; under the condition of equipment data updating, inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting equipment data samples and oil return frequency samples into a preset neural network for training; and controlling the intelligent equipment to execute oil return operation at the oil return frequency.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present application without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. The utility model provides an intelligent oil return control method which characterized in that is applied to the controller, the controller passes through the electrical signal and is connected with the sensor group, the sensor group passes through the electrical signal and is connected with intelligent device, intelligent oil return control method includes:
receiving the equipment data of the intelligent equipment acquired by the sensor group in real time;
under the condition of equipment data updating, inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting equipment data samples and oil return frequency samples into a preset neural network for training;
and controlling the intelligent equipment to execute oil return operation at the oil return frequency.
2. The intelligent oil return control method according to claim 1, wherein,
and inputting the updated equipment data to an oil return prediction model for processing, and outputting the oil return frequency of oil return operation, wherein the method comprises the following steps of:
performing exception analysis processing on the equipment data;
under the condition that no abnormal data exists in the equipment data, analyzing the equipment data to obtain the equipment state data and the environmental condition data of the intelligent equipment;
judging whether an oil return operation needs to be executed according to the equipment state data and the environmental condition data;
and under the condition that the oil return operation is required to be executed, inputting the equipment state data and the environmental condition data into the oil return prediction model for processing, and outputting the oil return frequency.
3. The intelligent oil return control method according to claim 2, wherein,
after the step of performing exception analysis processing on the device data, the method further includes:
under the condition that the abnormal data exists in the equipment data, carrying out identification processing on the abnormal data to obtain abnormal identification data;
screening the abnormal identification data from the equipment data, analyzing and processing the abnormal identification data, and determining an abnormal reason corresponding to the abnormal identification data;
acquiring a corresponding abnormality repair strategy according to the abnormality cause;
and adjusting the equipment parameters of the intelligent equipment according to the abnormal repair strategy so as to repair the abnormal data into normal data.
4. The intelligent oil return control method according to claim 1, wherein,
after the step of controlling the smart device to perform an oil return operation at the oil return frequency, the method further includes:
acquiring the current oil return frequency of the intelligent equipment through the sensor group;
comparing the current oil return frequency with the oil return frequency;
generating abnormal information of abnormal oil return of the intelligent equipment under the condition that the current oil return frequency is smaller than the oil return frequency, and displaying the abnormal information of abnormal oil return of the intelligent equipment on a preset display interface;
and under the condition that the current oil return frequency is greater than or equal to the oil return frequency, generating normal information of normal oil return of the intelligent equipment, and displaying the normal information of normal oil return of the intelligent equipment on the display interface.
5. The intelligent oil return control method according to claim 4, wherein,
after the step of controlling the smart device to perform an oil return operation at the oil return frequency, the method further includes:
acquiring oil return quantity of the intelligent equipment for executing oil return operation at the oil return frequency;
and stopping oil return operation and displaying the oil return amount on the display interface under the condition that the oil return amount is larger than or equal to a preset oil return threshold value.
6. The intelligent oil return control method according to claim 5, characterized in that,
after the step of obtaining the oil return amount of the oil return operation performed by the intelligent device at the oil return frequency, the method further includes:
counting the oil return time length of the intelligent equipment for executing the oil return operation at the oil return frequency;
comparing the oil return time with a preset time threshold;
suspending oil return operation when the oil return time reaches the time threshold and the oil return quantity is smaller than the oil return threshold;
and under the condition that the pause duration of the oil return operation reaches a preset pause threshold value, controlling the intelligent equipment to execute the oil return operation at the oil return frequency again until the oil return amount reaches the oil return threshold value, and stopping the oil return operation.
7. The utility model provides an intelligence oil return controlling means, its characterized in that is applied to the controller, the controller passes through the electrical signal and is connected with the sensor group, the sensor group passes through the electrical signal and is connected with intelligent device, intelligence oil return controlling means includes:
the receiving module is used for receiving the equipment data of the intelligent equipment acquired by the sensor group in real time;
the prediction module is used for inputting the updated equipment data to an oil return prediction model for processing under the condition of equipment data updating, and outputting the oil return frequency of oil return operation, wherein the oil return prediction model is obtained by inputting equipment data samples and oil return frequency samples into a preset neural network for training;
and the control module is used for controlling the intelligent equipment to execute oil return operation at the oil return frequency.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the intelligent oil return control method according to any one of claims 1 to 6 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the intelligent oil return control method according to any one of claims 1 to 6.
10. An intelligent device comprising at least a controller connected to a sensor group by an electrical signal, wherein the controller implements the steps of the intelligent oil return control method according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310757935.3A CN116857854A (en) | 2023-06-25 | 2023-06-25 | Intelligent oil return control method, device, equipment, storage medium and intelligent equipment |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310757935.3A CN116857854A (en) | 2023-06-25 | 2023-06-25 | Intelligent oil return control method, device, equipment, storage medium and intelligent equipment |
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