CN112032924B - Method and system for detecting abnormity of air conditioner operation efficiency - Google Patents
Method and system for detecting abnormity of air conditioner operation efficiency Download PDFInfo
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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
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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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
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
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Abstract
The invention relates to the technical field of air conditioner detection, in particular to a method and a system for detecting the abnormal operation efficiency of an air conditioner, wherein the method comprises the following steps: acquiring an air conditioner starting message, and acquiring at least one starting parameter message from the air conditioner starting message; acquiring indoor environment information in real time, and extracting at least one environment feature from the indoor environment information; acquiring the incidence relation between the starting parameter information and the environmental characteristics, and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation; if a complete matching message is obtained according to the matching degree, corresponding matching time information is obtained; and calculating the air conditioner operation efficiency according to the matching time information, and if the air conditioner operation efficiency is lower than a preset efficiency threshold, triggering abnormal air conditioner operation information. This application has the effect that can detect the efficiency of air conditioner operation.
Description
Technical Field
The invention relates to the technical field of air conditioner detection, in particular to a method and a system for detecting the abnormal operation efficiency of an air conditioner.
Background
Currently, an Air Conditioner (Air Conditioner) is a device that manually adjusts and controls parameters such as temperature, humidity, and flow rate of ambient Air in a building or structure.
When the existing air conditioner is used, the temperature set by a user is used as the starting condition of the air conditioner, so that the indoor temperature, humidity and flow rate of the air conditioner can be adjusted to the parameters set by the user, and the comfort level of the user is improved.
With respect to the related art among the above, the inventors consider that the following drawbacks exist: in the process of long-time operation of the air conditioner, when the indoor temperature, humidity and the like need to be maintained to the parameters set by the user in the same environment, the operation efficiency is continuously reduced, and the energy consumption of the operation of the air conditioner is continuously increased.
Disclosure of Invention
The application aims to provide an air conditioner operation efficiency abnormity detection method and system capable of detecting the operation efficiency of an air conditioner.
The above object of the present invention is achieved by the following technical solutions:
an abnormal detection method for the operating efficiency of an air conditioner comprises the following steps:
acquiring an air conditioner starting message, and acquiring at least one starting parameter information from the air conditioner starting message;
acquiring indoor environment information in real time, and extracting at least one environmental feature from the indoor environment information;
acquiring the incidence relation between the starting parameter information and the environmental characteristics, and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation;
if a complete matching message is obtained according to the matching degree, corresponding matching time information is obtained;
and calculating the air conditioner operation efficiency according to the matching time information, and if the air conditioner operation efficiency is lower than a preset efficiency threshold, triggering abnormal air conditioner operation information.
By adopting the technical scheme, the starting parameter information is obtained after the air conditioner is started, whether the air conditioner can adjust the indoor environment to the starting parameter information or not can be judged according to the environmental characteristics of the indoor environment information, the condition that the air conditioner adjusts the indoor environment information to the starting parameter information is shown in a matching mode when the complete matching information is obtained, the time for the air conditioner to adjust the indoor environment information to the starting parameter information is obtained by obtaining the time for matching the time information, the operation efficiency of the air conditioner can be calculated, when the operation efficiency of the air conditioner is continuously reduced along with the use time of the air conditioner, the condition that the air conditioner is abnormal is shown when the operation efficiency of the air conditioner is reduced to be lower than the efficiency threshold value is shown, the abnormal operation information of the air conditioner is triggered, and the user can timely clean and maintain the air conditioner.
The present application may be further configured in a preferred example to: the acquiring the incidence relation between the starting parameter information and the environmental characteristics, and acquiring the matching degree between the starting parameter and the environmental characteristics according to the incidence relation specifically include:
respectively obtaining the parameter type of the starting parameter information and the feature type of the environment feature, and obtaining the association relation according to the parameter type and the feature type;
obtaining a numerical parameter of each environmental characteristic, calculating a numerical difference between the numerical parameter and the corresponding starting parameter information according to the incidence relation, and obtaining the matching degree according to the numerical difference.
By adopting the technical scheme, the matching efficiency can be improved by acquiring the incidence relation, and the efficiency of acquiring the matching degree can be improved by calculating the numerical difference.
The present application may be further configured in a preferred example to: calculating the air conditioner operation efficiency according to the matching time information, and after triggering the air conditioner operation abnormal information if the air conditioner operation efficiency is lower than a preset efficiency threshold, the air conditioner operation efficiency abnormal detection method further comprises the following steps:
acquiring starting equipment information according to the starting parameter information, and acquiring air conditioner operation parameters of each piece of starting equipment information;
and inputting the air conditioner operation parameters into a preset forward operation model for matching, and acquiring abnormal component information according to a matching result.
By adopting the technical scheme, the operating condition of the air conditioner component which is in operation can be acquired in a targeted manner by acquiring the air conditioner operating parameter corresponding to the starting equipment information, so that the problem of abnormal operating efficiency is analyzed; through inputting the air conditioner operation parameter to the forward operation model, can regard as the spare part that the matching failed as the spare part that appears unusually, need not to set up the unusual model of corresponding operation in advance, promote the efficiency of discernment.
The present application may be further configured in a preferred example to: before the air conditioner operation parameters are input into a preset forward operation model for matching and abnormal component information is obtained according to a matching result, the method for detecting the abnormal air conditioner operation efficiency further comprises the following steps:
acquiring historical operating data of an air conditioner, and extracting forward operating parameters from the historical operating data of the air conditioner;
and carrying out neural network training on the forward operation parameters to obtain the forward operation model.
By adopting the technical scheme, the forward operation parameters are obtained from the historical operation data of the air conditioner, the sample size of the forward operation parameters can be utilized, the quality of neural network training is improved, and the accuracy of the forward operation model is facilitated.
The present application may be further configured in a preferred example to: the method for matching the air conditioner operation parameters comprises the following steps of inputting the air conditioner operation parameters into a preset forward operation model for matching, and obtaining abnormal component information according to a matching result, wherein the method specifically comprises the following steps:
splitting the air conditioner operation parameters according to the starting equipment information to obtain starting equipment operation parameters;
acquiring a preset matching time interval, and inputting the equipment operation parameters to the forward operation model at each matching time interval;
if the matching fails, counting a corresponding equipment operation abnormal value according to the matching failure times, and if the equipment operation abnormal value reaches a preset equipment abnormal threshold, generating corresponding abnormal component information.
By adopting the technical scheme, the air conditioner operation parameters are split through the information of the starting equipment, the split starting equipment operation parameters are input into the forward operation model, the matching accuracy can be improved, the time and frequency of abnormal equipment can be counted beneficially by setting the matching time interval, and the accuracy of diagnosing the abnormal equipment is improved.
The second objective of the present invention is achieved by the following technical solutions:
an air conditioner operation efficiency abnormality detection system, the air conditioner operation efficiency abnormality detection system comprising:
the system comprises a parameter acquisition module, a parameter storage module and a parameter processing module, wherein the parameter acquisition module is used for acquiring an air conditioner starting message and acquiring at least one piece of starting parameter information from the air conditioner starting message;
the system comprises a characteristic extraction module, a characteristic analysis module and a characteristic analysis module, wherein the characteristic extraction module is used for acquiring indoor environment information in real time and extracting at least one environmental characteristic from the indoor environment information;
the matching module is used for acquiring the incidence relation between the starting parameter information and the environmental characteristics and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation;
the time acquisition module is used for acquiring corresponding matching time information if a complete matching message is acquired according to the matching degree;
and the abnormity judgment module is used for calculating the air conditioner operation efficiency according to the matching time information, and triggering the air conditioner operation abnormity information if the air conditioner operation efficiency is lower than a preset efficiency threshold value.
By adopting the technical scheme, the starting parameter information is obtained after the air conditioner is started, whether the air conditioner can adjust the indoor environment to the starting parameter information or not can be judged according to the environmental characteristics of the indoor environment information, the condition that the air conditioner adjusts the indoor environment information to the starting parameter information is shown in a matching mode when the complete matching information is obtained, the time for the air conditioner to adjust the indoor environment information to the starting parameter information is obtained by obtaining the time for matching the time information, the operation efficiency of the air conditioner can be calculated, when the operation efficiency of the air conditioner is continuously reduced along with the use time of the air conditioner, the condition that the air conditioner is abnormal is shown when the operation efficiency of the air conditioner is reduced to be lower than the efficiency threshold value is shown, the abnormal operation information of the air conditioner is triggered, and the user can timely clean and maintain the air conditioner.
The third purpose of the present application is achieved by the following technical solutions:
a computer device comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the computer program to realize the steps of the air conditioner running efficiency abnormity detection method.
The fourth purpose of the present application is achieved by the following technical solutions:
a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the above-described air conditioner operation efficiency abnormality detection method.
In summary, the present application includes at least one of the following beneficial technical effects:
1. after the air conditioner is started, starting parameter information is obtained, whether the air conditioner can adjust the indoor environment to the starting parameter information or not can be judged according to the environmental characteristics of the indoor environment information, when a complete matching message is obtained in a matching mode, the fact that the air conditioner adjusts the indoor environment information to the starting parameter information is indicated, the time that the air conditioner adjusts the indoor environment information to the starting parameter information is obtained through obtaining the time of matching time information, therefore, the operation efficiency of the air conditioner can be calculated, when the operation efficiency of the air conditioner is continuously reduced along with the use time of the air conditioner, when the operation efficiency of the air conditioner is reduced to be lower than the efficiency threshold value, the fact that the air conditioner is abnormal is triggered, and users can clean and maintain the air conditioner timely;
2. by acquiring the air conditioner operation parameters corresponding to the starting equipment information, the operation condition of the air conditioner component in operation can be acquired in a targeted manner, and the problem of abnormal operation efficiency is analyzed; by inputting the air conditioner operation parameters into the forward operation model, the parts which fail to be matched can be used as abnormal parts, a corresponding abnormal operation model does not need to be preset, and the identification efficiency is improved;
3. the air conditioner operation parameters are split according to the information of the starting equipment, the split starting equipment operation parameters are input into the forward operation model, matching accuracy can be improved, time and frequency of abnormal equipment can be counted beneficially by setting a matching time interval, and accuracy of diagnosing the abnormal equipment is improved.
Drawings
FIG. 1 is a flowchart illustrating a method for detecting an abnormal operating efficiency of an air conditioner according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating an implementation of step S30 in the method for detecting abnormal operating efficiency of an air conditioner according to an embodiment of the present invention;
fig. 3 is a flowchart of another implementation of the method for detecting an abnormal operating efficiency of an air conditioner according to an embodiment of the present invention;
fig. 4 is a flowchart of another implementation of the method for detecting an abnormal operating efficiency of an air conditioner according to an embodiment of the present invention;
fig. 5 is a flowchart illustrating an implementation of step S52 in the method for detecting abnormal operating efficiency of an air conditioner according to an embodiment of the present invention;
FIG. 6 is a schematic block diagram of an air conditioner operation efficiency anomaly detection system according to an embodiment of the present invention;
fig. 7 is a schematic diagram of an apparatus in an embodiment of the invention.
Detailed Description
The present application is described in further detail below with reference to the attached drawings.
In an embodiment, as shown in fig. 1, the present application discloses a method for detecting an abnormal operating efficiency of an air conditioner, which specifically includes the following steps:
s10: and acquiring an air conditioner starting message, and acquiring at least one starting parameter information from the air conditioner starting message.
In this embodiment, the air conditioner start message is an instruction message triggered by a user to control the start of the air conditioner and adjust parameters such as the indoor temperature and humidity. The start parameter information refers to specific values of the air conditioner which need to adjust the indoor temperature, humidity and the like.
Specifically, when a user needs to start the air conditioner and adjust the indoor environment, the air conditioner start message is triggered through an air conditioner remote controller or a terminal capable of controlling the start of the air conditioner, so as to control the start of the air conditioner. Further, the starting parameter information is acquired in the air conditioner starting message. The method for acquiring the starting parameter information may be that a user inputs parameters to be adjusted, such as indoor temperature, humidity, air flow rate and the like, in an air conditioner remote controller or a terminal capable of controlling the starting of an air conditioner, and uses the parameters as the starting parameter information, and triggers the air conditioner starting information according to the starting parameter information, so that the starting parameter information can be acquired from the air conditioner starting information; or, the intelligent terminal may be installed in the air conditioner, and after the air conditioner is started after the air conditioner start message is acquired, and the indoor and outdoor environments are acquired, the start parameter information may be calculated by combining a preset human thermal comfort model.
S20: the method includes the steps of acquiring indoor environment information in real time, and extracting at least one environment feature from the indoor environment information.
In the present embodiment, the indoor environment information refers to data such as temperature, humidity, and air flow rate in the indoor environment, which are associated with the types of indoor environments that the air conditioner can control and adjust, and the environmental characteristics refer to the magnitude of the numerical value of the indoor environment information for each type.
Specifically, a sensor for detecting the indoor environment temperature, humidity and wind speed is installed in the air conditioner or indoors, the indoor environment information is composed of data acquired by the sensor, and a value corresponding to each piece of start parameter information, such as specific temperature, humidity and wind speed, is acquired from the indoor environment information as the environment characteristic.
S30: and acquiring the incidence relation between the starting parameter information and the environmental characteristics, and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation.
Specifically, the corresponding relationship between each piece of start parameter information and the environmental characteristics is obtained as the association relationship. Further, according to the association relationship, the matching degree of each piece of starting parameter information and the environmental characteristics is obtained, that is, the degree of closeness between the indoor actual environment and the starting parameter information set by the user or obtained through calculation after the indoor environment is adjusted through the air conditioner.
S40: and if the complete matching message is acquired according to the matching degree, acquiring corresponding matching time information.
In this embodiment, the complete matching message refers to a message triggered when the actual indoor environment condition completely reaches the start parameter information. The matching time information refers to a time required from the start of the air conditioner to the acquisition of the perfect matching message.
Specifically, when the environmental characteristics are completely consistent with the start parameter information, the complete matching message is triggered, timing is started when the air conditioner is started, that is, when the air conditioner start message is acquired, and the time taken by acquiring the time distance from the complete matching message is used as the matching time information.
S50: and calculating the air conditioner operation efficiency according to the matching time information, and triggering the air conditioner operation abnormal information if the air conditioner operation efficiency is lower than a preset efficiency threshold value.
In the present embodiment, the air conditioner operation efficiency refers to an ability value of the air conditioner to adjust the indoor temperature per unit time. The air conditioner operation abnormality information is information that abnormality occurs in parts in the air conditioning equipment.
Specifically, the efficiency threshold is set in advance according to the output power of the air conditioner and the size of the space of the scene where the air conditioner needs to be installed, and the output power is the power output when the air conditioner is normally operated or at the best performance.
Further, according to the matching time information, the air conditioner operation efficiency is calculated by using the following formula:
the air conditioner operation efficiency = V/(P × T) × 100%, where V denotes a space size of a scene actually installed, P denotes power output when the air conditioner is normally operated or at the best performance, and T denotes matching time information.
Further, if the air conditioner operation efficiency is lower than a preset efficiency threshold, the air conditioner operation abnormal information is triggered.
In this embodiment, after the air conditioner is started, starting parameter information is acquired, whether the air conditioner can adjust the indoor environment to the starting parameter information or not can be judged according to the environmental characteristics of the indoor environment information, when a complete matching message is acquired in a matching mode, it is stated that the air conditioner adjusts the indoor environment information to the starting parameter information, and the time for the air conditioner to adjust the indoor environment information to the starting parameter information is obtained by acquiring the time for matching time information, so that the operation efficiency of the air conditioner can be calculated.
In an embodiment, as shown in fig. 2, in step S30, that is, acquiring an association relationship between the start parameter information and the environmental characteristic, and acquiring a matching degree between the start parameter and the environmental characteristic according to the association relationship, specifically include:
s31: and respectively acquiring the parameter type of the starting parameter information and the feature type of the environmental feature, and acquiring the association relation according to the parameter type and the feature type.
In this embodiment, the parameter type refers to a specific data type in the startup parameter information. The feature type corresponds to the parameter type, and refers to a type of the indoor environment specifically referred to in the environmental feature.
Specifically, the kind of data that requires specific adjustment to the environment in the room, such as adjusting the temperature, humidity, and air flow rate in the room to specific values, is acquired in the start parameter information, and is taken as the parameter type. Further, when the feature type is obtained, corresponding data may be obtained indoors according to the parameter type, so as to form the feature type.
Further, the parameter type and the feature type of the same type are associated, for example, the parameter type and the feature type indicating the indoor temperature at the same time, and the associated result is taken as the association relationship.
S32: and acquiring the numerical parameter of each environmental characteristic, calculating the numerical difference between the numerical parameter and the corresponding starting parameter information according to the incidence relation, and acquiring the matching degree according to the numerical difference.
In this embodiment, the numerical value of the environmental characteristic corresponding to each characteristic type, such as a specific temperature value, a specific humidity value, a specific air flow rate value, and the like, is used as the numerical parameter. Obtaining a value of a parameter type corresponding to the feature type from the starting parameter information through the correlation relationship, subtracting the value parameter of the environmental feature from the value corresponding to the starting parameter information to obtain the value difference, taking the meaning size of the value difference as the matching degree, namely, the value difference is closer to 0, the matching degree is higher, and when the value difference is equal to 0 or is within a preset range value, a complete matching message can be triggered.
In an embodiment, as shown in fig. 3, after step S50, the method for detecting abnormality in operating efficiency of air conditioner further includes:
s51: and acquiring starting equipment information according to the starting parameter information, and acquiring the air conditioner operation parameter of each piece of starting equipment information.
In this embodiment, the starting apparatus information is information of components related to the environment in the room, which is specifically adjusted when the air conditioner is started based on the starting apparatus information acquired this time. The air conditioner operation parameters refer to operation parameters of each starting device which participates in the air conditioner starting and regulates the indoor environment when the starting device operates.
Specifically, when the air conditioner is started, the equipment components which need to participate when the air conditioner operates according to the starting parameter information or the equipment components which can influence the air conditioner to adjust the indoor environment according to the starting parameter information are acquired according to the model of the air conditioner, for example, when the starting parameter information includes the adjustment of the indoor temperature, the equipment components which can influence the air conditioner to adjust the indoor temperature are acquired, the equipment components include electrical equipment and mechanical equipment such as an air conditioner filter screen, and the information of the equipment components is acquired as the starting equipment information.
Further, a sensor for detecting each equipment component, for example, a sensor for detecting the vibration condition of the equipment, may be installed in the air conditioner, wherein the detection of the air conditioner filter screen may be the detection of dust attached to the air conditioner filter screen, and a specific manner may be to add a device for detecting the wind speed and temperature at the air outlet end of the air conditioner filter screen, and the wind speed and temperature may be compared with the wind speed and temperature in the starting parameter information, and according to the comparison, it is determined whether the air conditioner filter screen needs to be cleaned. And acquiring air conditioner operation parameters corresponding to the starting equipment information through a sensor device which is arranged in the air conditioner and used for detecting equipment components.
S52: and inputting the air conditioner operation parameters into a preset forward operation model for matching, and acquiring abnormal component information according to a matching result.
In this embodiment, the forward operation model is a model for detecting whether the operation state of the air conditioner is normal or not when the air conditioner is operating. The abnormal component information is information in which a component in which an abnormality has occurred is recorded.
Specifically, each air conditioner operation parameter corresponding to the starting equipment information is input into the forward operation model for matching, if the matching fails in a preset time period or number, the equipment component is determined to be abnormal, and the information of the abnormal equipment component is recorded to obtain the abnormal component information. Because the abnormal conditions of the equipment components are more, the conditions are relatively complex, and the state of the equipment components in normal operation is relatively fixed, the equipment components are judged by judging the conditions of the component equipment and the equipment components in normal operation, if the equipment components do not operate according to a normal working mode, the equipment components are determined to be abnormal, whether the equipment components appear can be judged without acquiring the specific abnormal conditions of the equipment, and the efficiency of acquiring the abnormal components can be improved.
In an embodiment, as shown in fig. 4, before step S52, the method for detecting abnormality in operating efficiency of an air conditioner further includes:
s5201: and acquiring historical operating data of the air conditioner, and extracting forward operating parameters from the historical operating data of the air conditioner.
In this embodiment, the historical operating data of the air conditioner refers to data obtained by recording parameters of each device component when the air conditioner of the same model is operated. The forward operation parameters refer to the operation parameters of each equipment component when the air conditioner is in normal operation.
Specifically, when the air conditioner is started each time, the operation parameters of each equipment component during the operation of the air conditioner are recorded, and meanwhile, a network communication module can be added into the air conditioner, so that the parameters during the operation of each air conditioner can be recorded and installed through the network communication module, and classified storage is performed according to the brand and the model of the air conditioner, and the historical operation data of the air conditioner is obtained.
Further, acquiring corresponding operation parameters according to the brand and the model of the air conditioner, and splitting the parameters recorded when the air conditioner operates normally from the acquired parameters to serve as the forward operation parameters.
S5202: and carrying out neural network training on the forward operation parameters to obtain a forward operation model.
Specifically, the forward running parameters are trained by using a neural network training mode on forward running data of each brand and model to obtain the forward running model.
In an embodiment, as shown in fig. 5, in step S52, inputting the air conditioner operation parameters into a preset forward operation model for matching, and acquiring the abnormal component information according to the matching result specifically includes:
s521: and splitting the air conditioner operation parameters according to the starting equipment information to obtain the starting equipment operation parameters.
In this embodiment, the starting device operation parameter refers to an air conditioner operation parameter of each device participating in the adjustment of the indoor environment when the air conditioner operates according to the starting parameter data.
Specifically, according to the type of the starting device information, the air conditioner operation parameters are split, and the starting device operation parameters corresponding to each type of the starting device information are obtained.
S522: and acquiring a preset matching time interval, and inputting the equipment operation parameters to the forward operation model at each matching time interval.
In the present embodiment, the matching time interval refers to a time interval of each input of the device operation parameters to the forward operation model.
Specifically, by setting the matching time interval, for example, 5 seconds, 10 seconds, 1 minute, or the like, according to which the device operation parameters are input to the forward operation model for matching.
S523: if the matching fails, counting a corresponding equipment operation abnormal value according to the matching failure times, and if the equipment operation abnormal value reaches a preset equipment abnormal threshold, generating corresponding abnormal component information.
In the present embodiment, the device operation abnormal value refers to a probability value for determining that an abnormality has occurred in the operating device component.
Specifically, if matching of the equipment operation parameters in the forward operation model fails, it is determined that the equipment component corresponding to the equipment operation parameters with failed matching may be abnormal, a basic score may be marked for the equipment component, as the number of times of matching failure increases, the product of the basic score and the number of times of matching failure is used as the equipment operation abnormal value, and if the equipment operation abnormal value reaches a preset equipment abnormal threshold, corresponding abnormal component information is generated.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an 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.
In an embodiment, an air conditioner operation efficiency abnormality detection system is provided, and the air conditioner operation efficiency abnormality detection system corresponds to the air conditioner operation efficiency abnormality detection method in the above embodiments one to one. As shown in fig. 6, the system for detecting the abnormality of the operating efficiency of the air conditioner includes a parameter obtaining module 10, a feature extracting module 20, a matching module 30, a time obtaining module 40, and an abnormality determining module 50. The functional modules are explained in detail as follows:
the parameter acquiring module 10 is configured to acquire an air conditioner starting message and acquire at least one piece of starting parameter information from the air conditioner starting message;
the feature extraction module 20 is configured to obtain indoor environment information in real time and extract at least one environmental feature from the indoor environment information;
the matching module 30 is configured to obtain an incidence relation between the start parameter information and the environmental characteristics, and obtain a matching degree between the start parameter and the environmental characteristics according to the incidence relation;
the time obtaining module 40 is configured to obtain corresponding matching time information if a complete matching message is obtained according to the matching degree;
and the abnormality judgment module 50 is configured to calculate air conditioner operation efficiency according to the matching time information, and trigger the air conditioner operation abnormality information if the air conditioner operation efficiency is lower than a preset efficiency threshold.
Optionally, the matching module 30 includes:
the incidence relation obtaining submodule is used for respectively obtaining the parameter type of the starting parameter information and the feature type of the environment feature and obtaining the incidence relation according to the parameter type and the feature type;
and the matching submodule is used for acquiring the numerical parameter of each environment characteristic, calculating the numerical difference between the numerical parameter and the corresponding starting parameter information according to the incidence relation, and acquiring the matching degree according to the numerical difference.
Optionally, the system for detecting the abnormal operating efficiency of the air conditioner further includes:
the parameter acquisition module is used for acquiring starting equipment information according to the starting parameter information and acquiring the air conditioner operation parameter of each piece of starting equipment information;
and the abnormal component acquisition module is used for inputting the air conditioner operation parameters into a preset forward operation model for matching and acquiring the information of the abnormal component according to a matching result.
Optionally, the system for detecting the abnormal operating efficiency of the air conditioner further includes:
the parameter extraction module is used for acquiring historical operating data of the air conditioner and extracting forward operating parameters from the historical operating data of the air conditioner;
and the model training module is used for carrying out neural network training on the forward operation parameters to obtain a forward operation model.
Optionally, the abnormal component acquiring module includes:
the data splitting submodule is used for splitting the air conditioner operation parameters according to the starting equipment information to obtain the starting equipment operation parameters;
the period matching submodule is used for acquiring a preset matching time interval, and inputting the equipment operation parameters to the forward operation model at each matching time interval;
and the counting submodule is used for counting a corresponding equipment operation abnormal value according to the matching failure times if the matching fails, and generating corresponding abnormal component information if the equipment operation abnormal value reaches a preset equipment abnormal threshold.
For the specific limitation of the air conditioner operation efficiency abnormality detection system, reference may be made to the above limitation on the air conditioner operation efficiency abnormality detection method, and details thereof are not repeated herein. All modules in the air conditioner operation efficiency abnormity detection system can be completely or partially realized through software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing historical operating data of the air conditioner. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an air conditioner operation efficiency abnormality detection method.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring an air conditioner starting message, and acquiring at least one starting parameter information from the air conditioner starting message;
acquiring indoor environment information in real time, and extracting at least one environment characteristic from the indoor environment information;
acquiring an incidence relation between the starting parameter information and the environmental characteristics, and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation;
if a complete matching message is obtained according to the matching degree, corresponding matching time information is obtained;
and calculating the air conditioner operation efficiency according to the matching time information, and triggering the air conditioner operation abnormal information if the air conditioner operation efficiency is lower than a preset efficiency threshold value.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring an air conditioner starting message, and acquiring at least one starting parameter information from the air conditioner starting message;
acquiring indoor environment information in real time, and extracting at least one environment characteristic from the indoor environment information;
acquiring an incidence relation between the starting parameter information and the environmental characteristics, and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation;
if a complete matching message is obtained according to the matching degree, corresponding matching time information is obtained;
and calculating the air conditioner operation efficiency according to the matching time information, and triggering the air conditioner operation abnormal information if the air conditioner operation efficiency is lower than a preset efficiency threshold value.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (6)
1. An abnormal detection method for the operating efficiency of an air conditioner is characterized by comprising the following steps:
acquiring an air conditioner starting message, and acquiring at least one piece of starting parameter information from the air conditioner starting message, wherein the starting parameter information is obtained by calculating by combining a preset human body thermal comfort model after the air conditioner starting message is acquired and the air conditioner is started and an indoor and outdoor environment are acquired by installing an intelligent terminal in the air conditioner;
acquiring indoor environment information in real time, and extracting at least one environment feature from the indoor environment information;
acquiring the incidence relation between the starting parameter information and the environmental characteristics, and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation;
if a complete matching message is obtained according to the matching degree, corresponding matching time information is obtained;
calculating the air conditioner operation efficiency according to the matching time information, and triggering the air conditioner operation abnormal information if the air conditioner operation efficiency is lower than a preset efficiency threshold, wherein the air conditioner operation efficiency is calculated by using the following formula according to the matching time information:
the air conditioner operation efficiency = V/(P × T) × 100%, where V refers to a space size of a scene actually installed, P refers to power output when the air conditioner is normally operated or at an optimal performance, and T refers to matching time information;
acquiring historical operating data of an air conditioner, and extracting forward operating parameters from the historical operating data of the air conditioner;
carrying out neural network training on the forward operation parameters to obtain a forward operation model;
acquiring starting equipment information according to the starting parameter information, and acquiring air conditioner operation parameters of each piece of starting equipment information;
inputting the air conditioner operation parameters into a preset forward operation model for matching, and acquiring abnormal component information according to a matching result, wherein the method specifically comprises the following steps:
splitting the air conditioner operation parameters according to the starting equipment information to obtain starting equipment operation parameters;
acquiring a preset matching time interval, and inputting the operating parameters of the starting equipment to the forward operating model at each matching time interval;
if the matching fails, counting a corresponding equipment operation abnormal value according to the matching failure times, and if the equipment operation abnormal value reaches a preset equipment abnormal threshold, generating corresponding abnormal component information.
2. The method for detecting the abnormality in the operating efficiency of the air conditioner according to claim 1, wherein the obtaining of the association between the information on the start parameter and the environmental characteristic and the obtaining of the matching degree between the start parameter and the environmental characteristic according to the association specifically include:
respectively obtaining the parameter type of the starting parameter information and the feature type of the environment feature, and obtaining the association relation according to the parameter type and the feature type;
obtaining a numerical parameter of each environmental characteristic, calculating a numerical difference between the numerical parameter and the corresponding starting parameter information according to the incidence relation, and obtaining the matching degree according to the numerical difference.
3. An air conditioner operation efficiency abnormality detection system, characterized in that the air conditioner operation efficiency abnormality detection system includes:
the system comprises a parameter acquisition module (10) and a parameter setting module, wherein the parameter acquisition module is used for acquiring an air conditioner starting message and acquiring at least one piece of starting parameter information from the air conditioner starting message, and calculating to acquire the starting parameter information by installing an intelligent terminal in the air conditioner after acquiring the air conditioner starting message and starting the air conditioner and after acquiring indoor and outdoor environments and combining a preset human body thermal comfort model;
the characteristic extraction module (20) is used for acquiring indoor environment information in real time and extracting at least one environmental characteristic from the indoor environment information;
the matching module (30) is used for acquiring the incidence relation between the starting parameter information and the environmental characteristics and acquiring the matching degree between the starting parameters and the environmental characteristics according to the incidence relation;
the time obtaining module (40) is used for obtaining corresponding matching time information if a complete matching message is obtained according to the matching degree;
an anomaly judgment module (50) for calculating the air conditioner operation efficiency according to the matching time information, and triggering the air conditioner operation anomaly information if the air conditioner operation efficiency is lower than a preset efficiency threshold, wherein the air conditioner operation efficiency is calculated by using the following formula according to the matching time information:
the air conditioner operation efficiency = V/(P × T) × 100%, where V refers to a space size of a scene actually installed, P refers to power output when the air conditioner is normally operated or at an optimal performance, and T refers to matching time information;
the parameter extraction module is used for acquiring historical operating data of the air conditioner and extracting forward operating parameters from the historical operating data of the air conditioner;
the model training module is used for carrying out neural network training on the forward operation parameters to obtain a forward operation model;
the parameter acquisition module is used for acquiring starting equipment information according to the starting parameter information and acquiring the air conditioner operation parameter of each piece of starting equipment information;
the abnormal component acquisition module is used for inputting the air conditioner operation parameters into a preset forward operation model for matching and acquiring abnormal component information according to a matching result, and the abnormal component acquisition module comprises:
the data splitting submodule is used for splitting the air conditioner operation parameters according to the starting equipment information to obtain the starting equipment operation parameters;
the period matching submodule is used for acquiring a preset matching time interval, and inputting the operation parameters of the starting equipment to the forward operation model at each matching time interval;
and the counting submodule is used for counting a corresponding equipment operation abnormal value according to the matching failure times if the matching fails, and generating corresponding abnormal component information if the equipment operation abnormal value reaches a preset equipment abnormal threshold.
4. The system of claim 3, wherein the matching module comprises:
the incidence relation obtaining submodule is used for respectively obtaining the parameter type of the starting parameter information and the feature type of the environment feature and obtaining the incidence relation according to the parameter type and the feature type;
and the matching submodule is used for acquiring the numerical parameter of each environmental characteristic, calculating the numerical difference between the numerical parameter and the corresponding starting parameter information according to the incidence relation, and acquiring the matching degree according to the numerical difference.
5. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the air conditioner operation efficiency abnormality detection method according to any one of claims 1 to 2 when executing the computer program.
6. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for detecting abnormality in operating efficiency of an air conditioner according to any one of claims 1 to 2.
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