CN112212477A - Intelligent control system and intelligent control method for air conditioner energy efficiency of AIoT data center - Google Patents
Intelligent control system and intelligent control method for air conditioner energy efficiency of AIoT data center 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
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
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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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- F24F11/54—Control or safety arrangements characterised by user interfaces or communication using one central controller connected to several sub-controllers
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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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- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
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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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- F24F11/67—Switching between heating and cooling modes
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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
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
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Abstract
The invention belongs to the technical field of air conditioner control, and discloses an intelligent control system and an intelligent control method for air conditioner energy efficiency of an AIoT data center, wherein the intelligent control system for the air conditioner energy efficiency of the AIoT data center comprises: the device comprises a temperature monitoring module, a temperature analysis module, a temperature regulation and control module, a central control module, an image acquisition module, an image analysis module, a three-dimensional model construction module, a user positioning module, a distance measurement module, a wind speed determination module, a path planning module, a wind direction adjusting module and a communication module. According to the invention, the image acquisition module is arranged for acquiring indoor images, the construction of an indoor three-dimensional model is realized through operations such as analysis and the like, the distribution condition of indoor furniture and household appliances is accurately and visually displayed, the transfer of the air outlet direction of an air conditioner can be realized by combining with the position information of a user, the comfort of the user is better, and the energy conservation is realized to a greater extent; the air conditioner and the mobile terminal are communicated in a wireless communication mode, the mobile terminal is controlled to operate the air conditioner, and the intelligent degree is higher.
Description
Technical Field
The invention belongs to the technical field of air conditioner control, and particularly relates to an intelligent control system and an intelligent control method for air conditioner energy efficiency of an AIoT data center.
Background
At present: AIoT (artificial intelligence internet of things) ═ AI (artificial intelligence) + IoT (internet of things). The AIoT is integrated with the AI technology and the IoT technology, mass data are generated and collected through the Internet of things and stored in a cloud end and an edge end, and then all-things datamation and all-things intelligent association are realized through big data analysis and artificial intelligence in a higher form, and the Internet of things technology and the artificial intelligence pursue an intelligent ecological system.
With the widespread use of household air conditioners and the rapid development of air conditioning technology, the performance requirements of people on air conditioners are gradually increased. The air conditioning energy efficiency is a general name of the household air conditioning refrigeration Energy Efficiency Ratio (EER), and is a ratio of rated refrigeration capacity to rated power consumption. In addition, the cooling and heating type home air conditioner further includes a heating energy efficiency ratio (COP), which refers to a ratio of a rated heating amount to a rated power. Simply, the air conditioning energy efficiency is how much cool air/warm air is generated by consuming the same amount of electricity, and the higher the energy efficiency, the more power the air conditioner is. Therefore, the air conditioner energy efficiency is an important parameter for measuring the performance of the air conditioner. The traditional air conditioner energy efficiency control system singly adopts chilled water supply water temperature regulation and single frequency converter regulation, and cannot reflect the real requirements of the terminal actual environment to the maximum extent, so that the accuracy of regulation and control parameters cannot be improved, and the real-time acquisition of signals cannot be realized, so that the requirements of the terminal environment on continuous change cannot be met by regulating and controlling the signals in real time. At present, AIoT is not used for an air conditioner energy efficiency intelligent control system, and the intelligent degree of a scheme for controlling the air conditioner energy efficiency is low.
Through the above analysis, the problems and defects of the prior art are as follows: at present, AIoT is not used for an air conditioner energy efficiency intelligent control system, and the intelligent degree of a scheme for controlling the air conditioner energy efficiency is low.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an intelligent control system and an intelligent control method for air conditioning energy efficiency of an AIoT data center.
The invention discloses an intelligent control method and system for air conditioning energy efficiency of an AIoT data center, wherein the intelligent control method for the air conditioning energy efficiency of the AIoT data center comprises the following steps:
monitoring outdoor temperature and indoor temperature by a temperature monitoring module by using a temperature monitoring program; analyzing the monitored temperature by a temperature analysis module by using a temperature analysis program;
acquiring the analysis result of the monitored temperature and the data of the monitored outdoor temperature and indoor temperature by using a temperature regulation program through a temperature regulation module, and judging whether the current season is summer, winter or spring and autumn; if the season decision result is summer, turning to the third step; if the season decision result is winter, turning to the step four, and if the season decision result is spring and autumn, turning to the step five;
step three, when the season is judged to be summer, setting and controlling an air-conditioning refrigerating or heating system to adjust the indoor temperature to a temperature 7-8 ℃ lower than the outdoor temperature;
step four, when the season is judged to be winter, the indoor temperature is adjusted to 18-20 ℃ by setting and controlling a refrigerating or heating system of an air conditioner;
step five, when the season is judged to be spring and autumn, setting and controlling an air-conditioning refrigeration or heating system to adjust the indoor temperature to 28 ℃;
collecting a plurality of indoor images by using image collection equipment through an image collection module; acquiring an indoor image acquired by an image acquisition module by using an image analysis program through an image analysis module;
step seven, acquiring the gray value of the pixel in the indoor image acquired in the step six; calculating the gray value gradient of the pixel according to the obtained gray value of the pixel, and obtaining a special point on the indoor image;
step eight, calculating a graph and a graph parameter formed by the special points according to the special points on the image obtained in the step seven, and outputting the graph and the graph parameter to obtain the distribution information of the indoor furniture and the household appliances;
step nine, acquiring feature points in the collected multiple indoor images by using a three-dimensional model building program according to the distribution information of the indoor furniture and household appliances through a three-dimensional model building module;
step ten, performing feature matching on a plurality of different indoor images, determining feature points of the plurality of different indoor images which meet feature matching conditions, and constructing a plurality of feature point pairs;
eleventh, determining a projection mapping relation basis matrix between the feature points in the feature point pairs for representing the feature points in the feature point pairs by using the plurality of feature point pairs;
step twelve, performing matrix decomposition on the basic matrix to obtain the relative displacement and posture change of the image acquisition equipment between different shooting points;
thirteen, determining the motion posture of the image acquisition equipment at each shooting point according to the relative displacement and the posture change; determining the relative positions of the different shooting points according to the motion postures;
fourteen, constructing an indoor three-dimensional model based on the motion attitude, the relative positions of the different shooting points and the plurality of characteristic point pairs;
fifteen, determining the position of the user by using a user positioning program through a user positioning module; the distance between the air conditioner and the human body is measured by a distance measuring module through a sensor; determining the wind outlet speed according to the distance between the user and the air conditioner by using a wind speed determining program through a wind speed determining module;
sixthly, planning the air conditioner air outlet path by using a path planning program through a path planning module based on the indoor three-dimensional model constructed in the fourteenth step, the user position determined in the fifteenth step and the distance between the user and the air conditioner;
seventhly, adjusting the wind direction of the air outlet of the air conditioner by a wind direction adjusting module based on the user position determined in the fifteenth step by using a wind direction adjusting program;
eighteen, the communication between the air conditioner and the mobile terminal is carried out through the communication module by utilizing a wireless network, and the air conditioner is regulated and controlled based on the air outlet speed determined in the fifteenth step, the air outlet path specified in the sixteenth step and the air outlet direction determined in the seventeenth step.
Further, in the first step, the analyzing the monitored temperature by the temperature analysis module using the temperature analysis program includes: and analyzing the temperature difference between the outdoor temperature and the indoor temperature.
Further, step seven, the acquiring the gray value of the pixel in the collected indoor image includes:
(1) acquiring a gray value of an initial pixel; taking an initial pixel as a base point, and acquiring the gray value of a second pixel at a certain distance in a plurality of directions from the periphery of the initial pixel;
(2) setting the second pixel as an initial pixel, repeating the step A, and obtaining the gray value of each pixel in the indoor image;
(3) setting the number requirement of pixels of which the gray values are to be acquired and judging whether the number of the pixels of which the gray values are acquired meets the set number requirement, if so, finishing the step of acquiring the gray values of the pixels, and if not, continuously acquiring the gray values of the next pixels.
Further, in step (1), the obtaining a gray value of the start pixel includes:
acquiring two-dimensional coordinates of the pixel;
determining an area near the pixel according to the two-dimensional coordinates of the pixel;
acquiring two-dimensional coordinates of each pixel of the area;
acquiring the gray value of each pixel corresponding to each coordinate according to the two-dimensional coordinates of each pixel;
and taking the intermediate value of the gray value of each pixel as the gray value of the pixel.
Further, in the seventh step, the acquiring a special point on the indoor image includes:
1) setting a gray value gradient limit; taking the difference value between the gray value of the pixel and the gray value of each pixel which is obtained from the pixel as a base point to the periphery of the initial pixel along a plurality of directions at a certain distance in the directions as the gray value gradient of the pixel along the directions;
2) judging whether the gray gradient value of the pixel along the direction exceeds the gray value limit, and if the gray gradient value exceeds the gray value limit, determining the pixel as a special point;
3) if the gradient value limit is not exceeded, continuously acquiring the gray value gradient of a certain pixel which is obtained from the pixel as a base point to the periphery of the starting pixel along a plurality of directions at a certain distance in the directions, and searching for a special point, namely a special point on the indoor image.
Further, in the ninth step, the construction of the indoor three-dimensional model by the three-dimensional model construction module according to the distribution information of the indoor furniture and household appliances by the three-dimensional model construction program further comprises the step of splicing a plurality of collected indoor images to obtain a complete indoor image.
Further, in a fourteenth step, the building an indoor three-dimensional model based on the motion posture, the relative positions of the different shooting points, and the plurality of feature point pairs includes:
determining a space transformation matrix of a space three-dimensional coordinate system and a camera coordinate system according to the motion attitude; for one or more characteristic point pairs in the plurality of characteristic point pairs, determining the spatial position relation of the characteristic point pairs under the same camera coordinate system according to the spatial transformation matrix; and determining the spatial position of the three-dimensional point corresponding to the distribution information of the indoor furniture household appliances and the characteristic point pair by utilizing the relative positions of the different shooting points and the spatial position relationship of the characteristic point pair so as to construct an indoor three-dimensional model.
Another object of the present invention is to provide an AIoT data center air conditioning energy efficiency intelligent control system implementing the AIoT data center air conditioning energy efficiency intelligent control method, the AIoT data center air conditioning energy efficiency intelligent control system including:
the system comprises a temperature monitoring module, a temperature analysis module, a temperature regulation and control module, a central control module, an image acquisition module, an image analysis module, a three-dimensional model construction module, a user positioning module, a distance measurement module, a wind speed determination module, a path planning module, a wind direction adjusting module and a communication module;
the temperature monitoring module is connected with the central control module and is used for monitoring the outdoor temperature and the indoor temperature through a temperature monitoring program;
the temperature analysis module is connected with the central control module and is used for analyzing the monitored temperature through a temperature analysis program;
the temperature regulation and control module is connected with the central control module and is used for regulating and controlling the air outlet temperature of the air conditioner according to the temperature analysis result through a temperature regulation and control program;
the central control module is connected with the temperature monitoring module, the temperature analysis module, the temperature regulation and control module, the image acquisition module, the image analysis module, the three-dimensional model construction module, the user positioning module, the distance measurement module, the wind speed determination module, the path planning module, the wind direction regulation module and the communication module and is used for controlling the normal operation of each module through the main control computer;
the image acquisition module is connected with the central control module and is used for acquiring indoor images through image acquisition equipment;
the image analysis module is connected with the central control module and used for analyzing the collected images through an image analysis program to obtain the distribution information of the indoor furniture and the household appliances;
the three-dimensional model building module is connected with the central control module and used for building an indoor three-dimensional model according to the distribution information of the indoor furniture and household appliances through a three-dimensional model building program;
the user positioning module is connected with the central control module and is used for determining the position of a user through a user positioning program;
the distance measuring module is connected with the central control module and is used for measuring the distance between the air conditioner and the human body through the sensor;
the wind speed determining module is connected with the central control module and used for determining the wind speed of the outlet wind according to the distance between the user and the air conditioner through a wind speed determining program;
the path planning module is connected with the central control module and used for planning the air conditioner air outlet path through a path planning program;
the wind direction adjusting module is connected with the central control module and is used for adjusting the wind direction of the air outlet of the air conditioner through a wind direction adjusting program;
and the communication module is connected with the central control module and is used for communicating the air conditioner with the mobile terminal through a wireless network and regulating and controlling the air conditioner.
By combining all the technical schemes, the invention has the advantages and positive effects that: the intelligent selection of refrigeration and heating is realized by monitoring indoor and outdoor temperatures; the temperature of the air conditioner is adjusted through the analysis of the indoor and outdoor temperature difference, and the energy-saving effect is achieved; the method comprises the steps that an image acquisition module is arranged for acquiring indoor images, an indoor three-dimensional model is constructed through analysis and other operations, the distribution condition of indoor furniture and household appliances is accurately and visually displayed, the transfer of the air outlet direction of the air conditioner can be realized by combining the acquired position information of a user, the comfort of the user is better, and the energy conservation is realized to a greater extent; the air conditioner and the mobile terminal are communicated in a wireless communication mode, the mobile terminal is controlled to operate the air conditioner, and the intelligent degree is higher.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a flowchart of an energy efficiency intelligent control method for an AIoT data center air conditioner according to an embodiment of the present invention.
Fig. 2 is a block diagram of a structure of an AIoT data center air conditioning energy efficiency intelligent control system according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a temperature regulation program utilized by the temperature regulation module to regulate the outlet air temperature of the air conditioner according to the temperature analysis result according to the embodiment of the present invention.
Fig. 4 is a flowchart for acquiring a gray scale value of a pixel in a two-dimensional image according to an embodiment of the present invention.
Fig. 5 is a flowchart for acquiring a special point on an indoor image according to an embodiment of the present invention.
In fig. 2: 1. a temperature monitoring module; 2. a temperature analysis module; 3. a temperature regulation module; 4. a central control module; 5. an image acquisition module; 6. an image analysis module; 7. a three-dimensional model building module; 8. a user positioning module; 9. a distance measuring module; 10. a wind speed determination module; 11. a path planning module; 12. a wind direction adjusting module; 13. and a communication module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides an intelligent control system and an intelligent control method for air conditioning energy efficiency of an AIoT data center, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the method for intelligently controlling the energy efficiency of the air conditioner in the AIoT data center according to the embodiment of the invention includes the following steps:
s101, monitoring outdoor temperature and indoor temperature by a temperature monitoring module by using a temperature monitoring program; analyzing the monitored temperature by a temperature analysis module by using a temperature analysis program;
s102, regulating and controlling the air outlet temperature of the air conditioner according to a temperature analysis result by using a temperature regulation and control program through a temperature regulation and control module;
s103, acquiring an indoor image by using an image acquisition device through an image acquisition module; analyzing the collected image by using an image analysis program through an image analysis module to obtain the distribution information of the indoor furniture and the household appliances;
s104, constructing an indoor three-dimensional model by using a three-dimensional model construction program through a three-dimensional model construction module according to indoor furniture and household appliance distribution information;
s105, determining the position of a user by using a user positioning program through a user positioning module; the distance between the air conditioner and the human body is measured by a distance measuring module through a sensor; determining the wind outlet speed according to the distance between the user and the air conditioner by using a wind speed determining program through a wind speed determining module;
s106, planning the air outlet path of the air conditioner by using a path planning program through a path planning module;
s107, adjusting the wind direction of the air outlet of the air conditioner by using a wind direction adjusting program through a wind direction adjusting module;
and S108, communicating the air conditioner with the mobile terminal through the communication module by using a wireless network, and regulating and controlling the air conditioner.
In step S101, the temperature analysis module according to the embodiment of the present invention analyzes the monitored temperature using a temperature analysis program, including analyzing the temperature difference between the outdoor temperature and the indoor temperature.
As shown in fig. 2, an AIoT data center air conditioning energy efficiency intelligent control system provided by an embodiment of the present invention includes:
the system comprises a temperature monitoring module 1, a temperature analysis module 2, a temperature regulation and control module 3, a central control module 4, an image acquisition module 5, an image analysis module 6, a three-dimensional model building module 7, a user positioning module 8, a distance measuring module 9, a wind speed determining module 10, a path planning module 11, a wind direction adjusting module 12 and a communication module 13;
the temperature monitoring module 1 is connected with the central control module 4 and is used for monitoring the outdoor temperature and the indoor temperature through a temperature monitoring program;
the temperature analysis module 2 is connected with the central control module 4 and is used for analyzing the monitored temperature through a temperature analysis program;
the temperature regulation and control module 3 is connected with the central control module 4 and is used for regulating and controlling the air outlet temperature of the air conditioner according to the temperature analysis result through a temperature regulation and control program;
the central control module 4 is connected with the temperature monitoring module 1, the temperature analysis module 2, the temperature regulation and control module 3, the image acquisition module 5, the image analysis module 6, the three-dimensional model construction module 7, the user positioning module 8, the distance measurement module 9, the wind speed determination module 10, the path planning module 11, the wind direction adjustment module 12 and the communication module 13, and is used for controlling the normal operation of each module through a main control computer;
the image acquisition module 5 is connected with the central control module 4 and is used for acquiring indoor images through image acquisition equipment;
the image analysis module 6 is connected with the central control module 4 and used for analyzing the collected images through an image analysis program to obtain the distribution information of the indoor furniture and household appliances;
the three-dimensional model building module 7 is connected with the central control module 4 and used for building an indoor three-dimensional model according to the distribution information of the indoor furniture and household appliances through a three-dimensional model building program;
the user positioning module 8 is connected with the central control module 4 and is used for determining the position of a user through a user positioning program;
the distance measuring module 9 is connected with the central control module 4 and is used for measuring the distance between the air conditioner and the human body through a sensor;
the wind speed determining module 10 is connected with the central control module 4 and used for determining the wind speed of the outlet wind according to the distance between the user and the air conditioner through a wind speed determining program;
the path planning module 11 is connected with the central control module 4 and used for planning the air conditioner air outlet path through a path planning program;
the wind direction adjusting module 12 is connected with the central control module 4 and is used for adjusting the wind direction of the air outlet of the air conditioner through a wind direction adjusting program;
and the communication module 13 is connected with the central control module 4 and is used for communicating the air conditioner with the mobile terminal through a wireless network and regulating and controlling the air conditioner.
The technical solution of the present invention is further illustrated by the following specific examples.
Example 1
As shown in fig. 1 and fig. 3, as a preferred embodiment, the method for intelligently controlling energy efficiency of an air conditioner in an AIoT data center according to an embodiment of the present invention for controlling an outlet air temperature of an air conditioner according to a temperature analysis result by using a temperature control program through a temperature control module includes:
s201, acquiring monitored outdoor temperature and indoor temperature data, and judging whether the current season is summer, winter or spring and autumn;
s202, if the current season is judged to be winter, the indoor temperature is adjusted to 18-20 ℃ by setting and controlling an air conditioner refrigerating or heating system;
s203, if the current season is summer, setting and controlling an air conditioner refrigerating or heating system to adjust the indoor temperature to a temperature 7-8 ℃ lower than the outdoor temperature;
and S204, if the current season is determined to be spring and autumn, setting and controlling an air-conditioning refrigerating or heating system to adjust the indoor temperature to 28 ℃.
Example 2
As shown in fig. 1, as a preferred embodiment, the method for intelligently controlling energy efficiency of an air conditioner in an AIoT data center according to an embodiment of the present invention analyzes an acquired image by using an image analysis program through an image analysis module to obtain distribution information of indoor furniture appliances, and includes:
acquiring a plurality of collected indoor images; acquiring a gray value of a pixel in a two-dimensional image; calculating the gray value gradient of the pixel according to the obtained gray value of the pixel, and obtaining a special point on the indoor image; and calculating a graph and a graph parameter formed by the special points according to the obtained special points on the image, and outputting the graph and the graph parameter.
As shown in fig. 4, acquiring a gray scale value of a pixel in a two-dimensional image according to an embodiment of the present invention includes:
s301, acquiring a gray value of an initial pixel; taking an initial pixel as a base point, and acquiring the gray value of a second pixel at a certain distance in a plurality of directions from the periphery of the initial pixel;
s302, setting the second pixel as an initial pixel, repeating the step S301, and obtaining the gray value of each pixel in the indoor image;
and S303, setting the number requirement of the pixels of which the gray values are to be acquired, judging whether the number of the pixels of which the gray values are acquired meets the set number requirement, if so, ending the step of acquiring the gray values of the pixels, and if not, continuously acquiring the gray values of the next pixels.
In step S301, the obtaining of the gray scale value of the start pixel provided by the embodiment of the present invention includes:
acquiring two-dimensional coordinates of the pixel;
determining an area near the pixel according to the two-dimensional coordinates of the pixel;
acquiring two-dimensional coordinates of each pixel of the area;
acquiring the gray value of each pixel corresponding to each coordinate according to the two-dimensional coordinates of each pixel;
and taking the intermediate value of the gray value of each pixel as the gray value of the pixel.
As shown in fig. 5, the acquiring of the special point on the indoor image according to the embodiment of the present invention includes:
s401, setting a gray value gradient limit; taking the difference value between the gray value of the pixel and the gray value of each pixel which is obtained from the pixel as a base point to the periphery of the initial pixel along a plurality of directions at a certain distance in the directions as the gray value gradient of the pixel along the directions;
s402, judging whether the gray gradient value of the pixel along the direction exceeds the gray value limit, and if the gray gradient value exceeds the gray value limit, determining the pixel as a special point;
and S403, if the gradient value limit is not exceeded, continuously acquiring the gray value gradient of a certain pixel which is obtained from the pixel as a base point to the periphery of the starting pixel along a plurality of directions at a certain distance in the directions, and searching for a special point, namely a special point on the indoor image.
Example 3
As shown in fig. 1, as a preferred embodiment, the method for intelligently controlling the energy efficiency of an air conditioner in an AIoT data center provided by the embodiment of the present invention includes splicing a plurality of collected indoor images to obtain a complete indoor image before constructing an indoor three-dimensional model according to indoor furniture and household appliance distribution information by using a three-dimensional model construction program through a three-dimensional model construction module.
Example 4
As shown in fig. 1, as a preferred embodiment, the method for intelligently controlling the energy efficiency of an air conditioner in an AIoT data center according to an embodiment of the present invention, where the method for building an indoor three-dimensional model by using a three-dimensional model building program through a three-dimensional model building module according to indoor furniture and household appliance distribution information includes:
acquiring feature points in a plurality of collected indoor images by a three-dimensional model building module according to indoor furniture and household appliance distribution information by using a three-dimensional model building program; performing feature matching on a plurality of different indoor images, determining feature points of the plurality of different indoor images which meet feature matching conditions, and constructing a plurality of feature point pairs; determining a projective mapping relation base matrix between the characteristic points in the characteristic point pairs for characterizing the characteristic points in the characteristic point pairs by using the plurality of characteristic point pairs; performing matrix decomposition on the basic matrix to obtain the relative displacement and the posture change of the image acquisition equipment among different shooting points; determining the motion posture of the image acquisition equipment at each shooting point according to the relative displacement and the posture change; determining the relative positions of the different shooting points according to the motion postures; and constructing an indoor three-dimensional model based on the motion posture, the relative positions of the different shooting points and the plurality of characteristic point pairs.
The method for constructing the indoor three-dimensional model based on the motion attitude, the relative positions of different shooting points and the plurality of characteristic point pairs comprises the following steps:
determining a space transformation matrix of a space three-dimensional coordinate system and a camera coordinate system according to the motion attitude; for one or more characteristic point pairs in the plurality of characteristic point pairs, determining the spatial position relation of the characteristic point pairs under the same camera coordinate system according to the spatial transformation matrix; and determining the spatial position of the three-dimensional point corresponding to the distribution information of the indoor furniture household appliances and the characteristic point pair by utilizing the relative positions of the different shooting points and the spatial position relationship of the characteristic point pair so as to construct an indoor three-dimensional model.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.
Claims (10)
1. The intelligent control method for the air conditioning energy efficiency of the AIoT data center is characterized by comprising the following steps of:
monitoring outdoor temperature and indoor temperature by a temperature monitoring module by using a temperature monitoring program; analyzing the monitored temperature by a temperature analysis module by using a temperature analysis program;
acquiring the analysis result of the monitored temperature and the data of the monitored outdoor temperature and indoor temperature by using a temperature regulation program through a temperature regulation module, and judging whether the current season is summer, winter or spring and autumn; if the season decision result is summer, turning to the third step; if the season decision result is winter, turning to the step four, and if the season decision result is spring and autumn, turning to the step five;
step three, when the season is judged to be summer, setting and controlling an air-conditioning refrigerating or heating system to adjust the indoor temperature to a temperature 7-8 ℃ lower than the outdoor temperature;
step four, when the season is judged to be winter, the indoor temperature is adjusted to 18-20 ℃ by setting and controlling a refrigerating or heating system of an air conditioner;
step five, when the season is judged to be spring and autumn, setting and controlling an air-conditioning refrigeration or heating system to adjust the indoor temperature to 28 ℃;
collecting a plurality of indoor images by using image collection equipment through an image collection module; acquiring an indoor image acquired by an image acquisition module by using an image analysis program through an image analysis module;
step seven, acquiring the gray value of the pixel in the indoor image acquired in the step six; calculating the gray value gradient of the pixel according to the obtained gray value of the pixel, and obtaining a special point on the indoor image;
step eight, calculating a graph and a graph parameter formed by the special points according to the special points on the image obtained in the step seven, and outputting the graph and the graph parameter to obtain the distribution information of the indoor furniture and the household appliances;
step nine, acquiring feature points in the collected multiple indoor images by using a three-dimensional model building program according to the distribution information of the indoor furniture and household appliances through a three-dimensional model building module;
step ten, performing feature matching on a plurality of different indoor images, determining feature points of the plurality of different indoor images which meet feature matching conditions, and constructing a plurality of feature point pairs;
eleventh, determining a projection mapping relation basis matrix between the feature points in the feature point pairs for representing the feature points in the feature point pairs by using the plurality of feature point pairs;
step twelve, performing matrix decomposition on the basic matrix to obtain the relative displacement and posture change of the image acquisition equipment between different shooting points;
thirteen, determining the motion posture of the image acquisition equipment at each shooting point according to the relative displacement and the posture change; determining the relative positions of the different shooting points according to the motion postures;
fourteen, constructing an indoor three-dimensional model based on the motion attitude, the relative positions of the different shooting points and the plurality of characteristic point pairs;
fifteen, determining the position of the user by using a user positioning program through a user positioning module; the distance between the air conditioner and the human body is measured by a distance measuring module through a sensor; determining the wind outlet speed according to the distance between the user and the air conditioner by using a wind speed determining program through a wind speed determining module;
sixthly, planning the air conditioner air outlet path by using a path planning program through a path planning module based on the indoor three-dimensional model constructed in the fourteenth step, the user position determined in the fifteenth step and the distance between the user and the air conditioner;
seventhly, adjusting the wind direction of the air outlet of the air conditioner by a wind direction adjusting module based on the user position determined in the fifteenth step by using a wind direction adjusting program;
eighteen, the communication between the air conditioner and the mobile terminal is carried out through the communication module by utilizing a wireless network, and the air conditioner is regulated and controlled based on the air outlet speed determined in the fifteenth step, the air outlet path specified in the sixteenth step and the air outlet direction determined in the seventeenth step.
2. The method for intelligently controlling air conditioning energy efficiency of an AIoT data center as claimed in claim 1, wherein in step one, the analyzing the monitored temperature by the temperature analysis module using the temperature analysis program comprises: and analyzing the temperature difference between the outdoor temperature and the indoor temperature.
3. The method for intelligently controlling air conditioning energy efficiency of the AIoT data center as claimed in claim 1, wherein in step seven, the obtaining gray scale values of pixels in the collected indoor image comprises:
(1) acquiring a gray value of an initial pixel; taking an initial pixel as a base point, and acquiring the gray value of a second pixel at a certain distance in a plurality of directions from the periphery of the initial pixel;
(2) setting the second pixel as an initial pixel, repeating the step A, and obtaining the gray value of each pixel in the indoor image;
(3) setting the number requirement of pixels of which the gray values are to be acquired and judging whether the number of the pixels of which the gray values are acquired meets the set number requirement, if so, finishing the step of acquiring the gray values of the pixels, and if not, continuously acquiring the gray values of the next pixels.
4. The method for intelligently controlling air conditioning energy efficiency of the AIoT data center as claimed in claim 3, wherein in step (1), the obtaining the gray scale value of the start pixel comprises:
acquiring two-dimensional coordinates of the pixel;
determining an area near the pixel according to the two-dimensional coordinates of the pixel;
acquiring two-dimensional coordinates of each pixel of the area;
acquiring the gray value of each pixel corresponding to each coordinate according to the two-dimensional coordinates of each pixel;
and taking the intermediate value of the gray value of each pixel as the gray value of the pixel.
5. The method for intelligently controlling air conditioning energy efficiency of the AIoT data center as claimed in claim 1, wherein in step seven, the obtaining of the special point on the indoor image comprises:
1) setting a gray value gradient limit; taking the difference value between the gray value of the pixel and the gray value of each pixel which is obtained from the pixel as a base point to the periphery of the initial pixel along a plurality of directions at a certain distance in the directions as the gray value gradient of the pixel along the directions;
2) judging whether the gray gradient value of the pixel along the direction exceeds the gray value limit, and if the gray gradient value exceeds the gray value limit, determining the pixel as a special point;
3) if the gradient value limit is not exceeded, continuously acquiring the gray value gradient of a certain pixel which is obtained from the pixel as a base point to the periphery of the starting pixel along a plurality of directions at a certain distance in the directions, and searching for a special point, namely a special point on the indoor image.
6. The method as claimed in claim 1, wherein in the ninth step, the splicing of the collected multiple indoor images is further included before the construction of the indoor three-dimensional model by the three-dimensional model construction module according to the indoor furniture and appliance distribution information by using the three-dimensional model construction program, so as to obtain a complete indoor image.
7. The method for intelligently controlling the energy efficiency of the air conditioner in the AIoT data center as claimed in claim 1, wherein in the fourteenth step, the building an indoor three-dimensional model based on the motion attitude, the relative positions of different shooting points and a plurality of characteristic point pairs comprises the following steps:
determining a space transformation matrix of a space three-dimensional coordinate system and a camera coordinate system according to the motion attitude; for one or more characteristic point pairs in the plurality of characteristic point pairs, determining the spatial position relation of the characteristic point pairs under the same camera coordinate system according to the spatial transformation matrix; and determining the spatial position of the three-dimensional point corresponding to the distribution information of the indoor furniture household appliances and the characteristic point pair by utilizing the relative positions of the different shooting points and the spatial position relationship of the characteristic point pair so as to construct an indoor three-dimensional model.
8. An AIoT data center air conditioning energy efficiency intelligent control system for implementing the AIoT data center air conditioning energy efficiency intelligent control method according to claims 1-7, wherein the AIoT data center air conditioning energy efficiency intelligent control system comprises:
the system comprises a temperature monitoring module, a temperature analysis module, a temperature regulation and control module, a central control module, an image acquisition module, an image analysis module, a three-dimensional model construction module, a user positioning module, a distance measurement module, a wind speed determination module, a path planning module, a wind direction adjusting module and a communication module;
the temperature monitoring module is connected with the central control module and is used for monitoring the outdoor temperature and the indoor temperature through a temperature monitoring program;
the temperature analysis module is connected with the central control module and is used for analyzing the monitored temperature through a temperature analysis program;
the temperature regulation and control module is connected with the central control module and is used for regulating and controlling the air outlet temperature of the air conditioner according to the temperature analysis result through a temperature regulation and control program;
the central control module is connected with the temperature monitoring module, the temperature analysis module, the temperature regulation and control module, the image acquisition module, the image analysis module, the three-dimensional model construction module, the user positioning module, the distance measurement module, the wind speed determination module, the path planning module, the wind direction regulation module and the communication module and is used for controlling the normal operation of each module through the main control computer;
the image acquisition module is connected with the central control module and is used for acquiring indoor images through image acquisition equipment;
the image analysis module is connected with the central control module and used for analyzing the collected images through an image analysis program to obtain the distribution information of the indoor furniture and the household appliances;
the three-dimensional model building module is connected with the central control module and used for building an indoor three-dimensional model according to the distribution information of the indoor furniture and household appliances through a three-dimensional model building program;
the user positioning module is connected with the central control module and is used for determining the position of a user through a user positioning program;
the distance measuring module is connected with the central control module and is used for measuring the distance between the air conditioner and the human body through the sensor;
the wind speed determining module is connected with the central control module and used for determining the wind speed of the outlet wind according to the distance between the user and the air conditioner through a wind speed determining program;
the path planning module is connected with the central control module and used for planning the air conditioner air outlet path through a path planning program;
the wind direction adjusting module is connected with the central control module and is used for adjusting the wind direction of the air outlet of the air conditioner through a wind direction adjusting program;
and the communication module is connected with the central control module and is used for communicating the air conditioner with the mobile terminal through a wireless network and regulating and controlling the air conditioner.
9. A computer program product stored on a computer readable medium, comprising a computer readable program that, when executed on an electronic device, provides a user input interface to implement the AIoT data center air conditioning energy efficiency intelligent control method of any one of claims 1-7.
10. A computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for intelligently controlling the energy efficiency of an AIoT data center air conditioner as claimed in any one of claims 1-7.
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