Intelligent air conditioner state judgment and analysis system and method based on Internet of Things

Abstract

The invention discloses an intelligent air conditioner state judgment and analysis system and method based on the Internet of Things, and relates to the technical field of air conditioner intelligent analysis. The method comprises the steps that S10, a temperature boundary layer existing in a target area is found; s20, determining a target temperature boundary layer, and performing preliminary analysis on the operation state of each air diffuser based on a determination result; s30, predicting the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; and S40, according to the predicted temperature influence coefficient, judging and analyzing the operation state of the air diffuser matched with each target temperature boundary layer. According to the method, through the operation indexes of the air diffuser, multiple operation states of the air diffuser can be accurately analyzed, and meanwhile, when the starting time or the closing time of the air conditioner is short, accurate analysis of the operation states can be achieved; and the influence of the installation position of the window in the target area, the size of the window, the orientation of the house and the like on the target object is eliminated in the analysis process.

Description

Technical Field

[0001] The present invention relates to the technical field of air-conditioning intelligent analysis, and in particular to an intelligent air-conditioning state judgment and analysis system and method based on the Internet of Things. Background Art

[0002] With the continuous improvement of living standards, air conditioners have become one of the indispensable household appliances in daily life. In the hot summer, the on / off status of air conditioners directly affects human comfort. At present, the on / off status of air conditioners is mainly determined by observing the information on the air conditioner control panel or the status of the air conditioner fan blades. However, in some environments with limited space, the air conditioner control panel cannot be installed normally. For example, in some factory areas, it is not allowed to set the air conditioner through the control panel. There are only fans, and the air conditioner status cannot be determined by checking the air conditioner control panel or the status of the fan blades.

[0003] In the prior art, the switch status of the air conditioner within a certain time period is judged by the temperature value within a time period. When the air conditioner start time is short or the set temperature is high, misjudgment is easy to occur. The prior art judges the air conditioner status by training models. This process requires the collection of a large amount of data, and different models need to be trained for different situations, which increases the difficulty of collecting data and requires a lot of time to train new models, reducing the intelligent control effect of the air conditioner and reducing the control accuracy of the air conditioner. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent air conditioning state judgment and analysis system and method based on the Internet of Things to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things, the method comprising: S10: acquiring the position information of each diffuser installed in the target area, and searching for the temperature boundary layer existing in the target area according to the inclination angle of the guide vane of each diffuser; S20: using the Internet of Things technology to sense the temperature change of each target object in each temperature boundary layer, determining the target temperature boundary layer based on the sensed result and the positional relationship between the target objects, and performing a preliminary analysis on the operating status of each diffuser based on the determination result; S30: predicting the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; S40: According to the predicted temperature influence coefficient, the operation state of the diffuser matching each target temperature boundary layer is judged and analyzed.

[0006] Further, the S10 includes: S101: randomly selecting a point in the target area as the coordinate origin to construct a three-dimensional space coordinate system, and obtaining the position coordinates of the center of each diffuser installed in the target area in the three-dimensional space coordinate system; S102: using an image acquisition device to acquire a side image of each diffuser, and determining an inclination angle of a guide vane of each diffuser based on the acquired side image; S103: When the inclination angle of the diffuser guide vane is located on the right side of the vertical line segment between the diffuser center and the ground, according to [γ i ,f] to determine the air supply angle range of the diffuser, and search for the temperature boundary layer matching the diffuser numbered i; When the inclination angle of the diffuser guide vane is located on the left side of the vertical line segment between the center of the diffuser and the ground, according to [-f,-γ i ] The air supply angle range of the diffuser is determined, and the temperature boundary layer matching the diffuser numbered i is searched; Among them, γ i represents the inclination angle of the diffuser guide vane numbered i, and f represents the angle between the upper air supply line of the diffuser and the vertical line segment of the diffuser center compared to the ground. Compared with the method of analyzing the diffuser operating status based on the average temperature in the target area, the method of judging and analyzing the operating status of the diffuser based on the temperature change of each target object in the temperature boundary layer has higher accuracy and is not easily affected by external environmental factors and the aging degree of the diffuser, and reduces the amount of data processing.

[0007] Further, the S20 includes: S201: According to the three-dimensional distance calculation formula, the distance value d between the center of the j-th target object and the center of the diffuser numbered i in the temperature boundary layer matching the diffuser numbered i is calculated. ij Calculation is performed, and the target objects include mobile terminals and smart appliances. The temperature values ​​of each target object are collected through the Internet of Things technology; S202: At time intervals t, using the Internet of Things technology, collect the temperature value of the j-th target object in the temperature boundary layer matching the diffuser numbered i, and randomly select a target object in the temperature boundary layer matching the diffuser numbered i; when hour: according to Predict the operation index of diffuser numbered i at time T+p*t; when hour: according to Predict the operation index of diffuser numbered i at time T+p*t; Wherein, j=1,2,…,m, represents the number corresponding to each target object in the temperature boundary layer, m represents the total number of target objects in the temperature boundary layer, u represents the number corresponding to the selected target object, u=1,2,…,m, p=0,1,2,…,q, represents the numbering of the temperature collection time of the control terminal in chronological order, q represents the total number, T represents the time when the control terminal first collects the temperature value of the target object, W ij(T+p*t) represents the temperature value of the jth target object in the temperature boundary layer matching the diffuser numbered i at the time T+p*t, U i(T+p*t) represents the operation index of diffuser numbered i at time T+p*t; S203: If U i(T+p*t) >0.1, the temperature boundary layer matching the diffuser numbered i is considered to be the target temperature boundary layer; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] <W ij(T+p*t) , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the open state at the time T+p*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] =W ij(T+p*t) <E T+(p+1)*t , then the temperature boundary layer matching the diffuser numbered i is considered to be a non-target temperature boundary layer. At time T+(p+1)*t, the diffuser numbered i is in the open state. E T+(p+1)*t Indicates the average outdoor temperature at time T+(p+1)*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] >W ij(T+p*t) , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the closed state at time T+(p+1)*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] =W ij(T+p*t) ≥E T+(p+1)*t , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the closed state at time T+(p+1)*t. Through the predicted operation index of the diffuser, it is possible to judge and analyze the initial state of the diffuser in the open state, the initial state in the disconnected state, and the stable state in the open state and the disconnected state.

[0008] Further, the S30 includes: In the target temperature boundary layer, according to hxj(T+p*t) =(E T+(p+1)*t -E T+p*t ) / (W xj[T+(p+1)*t] -W xj(T+p*t) ) predicting the temperature influence coefficient of the outdoor temperature on the j-th target object in the target temperature boundary layer numbered x; Where x=1,2,…,q, represents the number corresponding to each target temperature boundary layer, q represents the total number of target temperature boundary layers, W xj(T+p*t) Indicates the temperature value corresponding to the jth target object in the target temperature boundary layer numbered x at time T+p*t.

[0009] Further, the S40 includes: S401: If h xj(T+p*t) ≥0.6, the diffuser matching the target temperature boundary layer numbered x is considered to be in the closed state at time T+p*t; If h xj(T+p*t) ≥0.6 part is true, then at 0≤h xj(T+p*t) When <0.6, the number of the corresponding target object is put into the set M; At this time, according to , predict the operating index of the diffuser matching the target temperature boundary layer numbered x at time T+p*t, where d xj Indicates the distance between the center of the jth target object in the target temperature boundary layer numbered x and the center of the diffuser matching the target temperature boundary layer numbered x. When number j is stored in the set M, , when number j is not stored in set M, This process can eliminate the influence of the window installation position, window size, house orientation, etc. on the indoor temperature in the target area, ensuring that the operating status of the diffuser can be analyzed more accurately according to the calculated operating index; S402: If 0≤U x(T+p*t) ≤0.1 and when number j is stored in set M, W xj[T+(p+1)*t] <W xj(T+p*t) , then the diffuser matching the target temperature boundary layer numbered x at the time T+p*t is considered to be in the open state; If 0≤U x(T+p*t) ≤0.1 and when number j is stored in set M, W xj[T+(p+1)*t] >W xj(T+p*t) , it is considered that the diffuser matching the target temperature boundary layer numbered x is in the closed state at the time T+p*t; If 0≤U i(T+p*t) ≤0.1 and when number j is stored in set M, W ij[T+(p+1)*t] =W ij(T+p*t) <ET+(p+1)*t , then the diffuser matching the target temperature boundary layer numbered x at the time T+p*t is considered to be in the open state; If 0≤U i(T+p*t) ≤0.1 and when number j is stored in set M, W ij[T+(p+1)*t] =W ij(T+p*t) ≥E T+(p+1)*t , then the diffuser matching the target temperature boundary layer numbered x at time T+p*t is considered to be in the closed state.

[0010] An intelligent air-conditioning state judgment and analysis system based on the Internet of Things, the system comprising a temperature boundary layer search module, an operation state preliminary analysis module, a temperature influence coefficient prediction module and an operation state judgment and analysis module; The temperature boundary layer search module is used to search for the temperature boundary layer existing in the target area; The operating status preliminary analysis module is used to determine the target temperature boundary layer and perform preliminary analysis on the operating status driven by each diffuser based on the determination result; The temperature influence coefficient prediction module is used to predict the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; The operation status judgment and analysis module is used to judge and analyze the operation status of the diffuser matching each target temperature boundary layer.

[0011] Further, the temperature boundary layer finding module includes a position coordinate acquisition unit, a guide vane inclination angle determination unit and a temperature boundary layer finding unit; The position coordinate acquisition unit randomly selects a point in the target area as the coordinate origin to construct a three-dimensional space coordinate system, and acquires the position coordinates of the center of each diffuser installed in the target area in the three-dimensional space coordinate system; The guide vane inclination angle determination unit collects the side image of each diffuser by using an image acquisition device, and determines the inclination angle of the guide vane of each diffuser based on the collected side image; The temperature boundary layer searching unit searches for a temperature boundary layer matching each diffuser according to the positional relationship between the inclination angle of the diffuser guide vane and the vertical line segment between the diffuser center and the ground, and the air supply angle range of the diffuser.

[0012] Further, the operation status preliminary analysis module includes a temperature value acquisition unit, an operation index prediction unit and an operation status preliminary analysis unit; The temperature value acquisition unit acquires the temperature value of each target object through the Internet of Things technology; The operation index prediction unit predicts the operation index of each diffuser according to the real-time temperature change difference of each target object and the distance value of each target object from the corresponding diffuser, and determines the target temperature boundary layer based on the prediction result; The operation status preliminary analysis unit performs preliminary analysis on the operation status of each diffuser according to the prediction result of the operation index prediction unit, the real-time temperature change of each target object and the real-time outdoor temperature value.

[0013] Furthermore, the temperature influence coefficient prediction module predicts the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer using the constructed mathematical model.

[0014] Further, the operation status judgment and analysis module includes a temperature influence coefficient analysis unit and an operation status judgment and analysis unit; The temperature influence coefficient analysis unit compares the prediction result transmitted by the temperature influence coefficient prediction module with the set threshold value, and based on the comparison result, selects whether to put the number of the corresponding target object into the set, and analyzes the operating state of the diffuser matching the target temperature boundary layer; The operation status judgment and analysis unit constructs a mathematical formula to predict the operation index of the diffuser matching each target temperature boundary layer according to the number of the target object stored in the set and the temperature influence coefficient of the outdoor temperature on each target object, and judges and analyzes the operation status of the diffuser matching each target temperature boundary layer based on the prediction result.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention searches for the temperature boundary layer of each diffuser, and based on the temperature value change of each target object in the temperature boundary layer and the outdoor real-time temperature value, realizes the judgment and analysis of the operating status of the diffuser. Compared with the traditional method, this process reduces the amount of temperature data collection and processing. At the same time, it can accurately analyze the operating status of the air conditioner when the air conditioner is turned on or off for a short time, which is conducive to improving the intelligent control effect of the air conditioner.

[0016] 2. The present invention uses the operating index of the diffuser to judge and analyze the initial state of the diffuser in the open state, the initial state of the diffuser in the disconnected state, and the stable state in the open state and the disconnected state, thereby improving the use effect of the system.

[0017] 3. The present invention predicts the operating index of the diffuser matching each target temperature boundary layer by predicting the temperature influence coefficient of each target object in the target temperature boundary layer by the predicted outdoor temperature. During the prediction process, the influence of the installation position of the windows, the window size, the outdoor temperature, the house orientation, etc. in the target area on the target object is eliminated, thereby improving the prediction accuracy of the operating index and the analysis accuracy of the operating status of the diffuser. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a schematic diagram of the working process of an intelligent air-conditioning state judgment and analysis system and method based on the Internet of Things; Figure 2 The present invention is a schematic structural diagram of the working principle of an intelligent air-conditioning state judgment and analysis system and method based on the Internet of Things. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Example: Figure 1-Figure 2 As shown, the present invention provides a system and method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things, and a method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things, the method comprising: S10: acquiring the position information of each diffuser installed in the target area, and searching for the temperature boundary layer existing in the target area according to the inclination angle of the guide vane of each diffuser; S10 includes: S101: randomly selecting a point in the target area as the coordinate origin to construct a three-dimensional space coordinate system, and obtaining the position coordinates of the center of each diffuser installed in the target area in the three-dimensional space coordinate system, where the diffuser refers to the air outlet in the central air conditioning pipeline system; S102: using an image acquisition device (the image acquisition device includes a camera) to acquire a side image of each diffuser, and based on the acquired side image, determining an inclination angle of a guide vane of each diffuser, where the guide vane inclination angle refers to an angle between the guide vane and a vertical line segment between the center of the diffuser and the ground; S103: When the inclination angle of the diffuser guide vane is located on the right side of the vertical line segment between the diffuser center and the ground, according to [γ i ,f] to determine the air supply angle range of the diffuser, and search for the temperature boundary layer matching the diffuser numbered i; When the inclination angle of the diffuser guide vane is located on the left side of the vertical line segment between the center of the diffuser and the ground, according to [-f,-γ i ] The air supply angle range of the diffuser is determined, and the temperature boundary layer matching the diffuser numbered i is searched; Among them, γ i represents the inclination angle of the diffuser guide vane numbered i, f represents the angle between the upper air supply line of the diffuser and the vertical line segment of the diffuser center compared to the ground, the upper air supply line refers to the upper air supply boundary line of the two air supply boundary lines corresponding to the air supply area of ​​the diffuser air outlet, the position of the upper air supply boundary line is not affected by the inclination angle of the diffuser guide vane, and the position of the lower air supply boundary line is affected by the inclination angle of the diffuser guide vane; the temperature difference between two randomly selected positions on the inner side of the two boundary surfaces of the temperature boundary layer is within the error range, the temperature on the outer side of the two boundary surfaces of the temperature boundary layer presents a gradient change, the two boundary surfaces of the temperature boundary layer refer to the plane where the diffuser guide vane is located, and the plane where the upper air supply line of the diffuser is located, and the angle between the plane where the upper air supply line of the diffuser is located and the plane where the diffuser guide vane is located = |γ i -f|; S20: using the Internet of Things technology to sense the temperature change of each target object in each temperature boundary layer, determining the target temperature boundary layer based on the sensed result and the positional relationship between the target objects, and performing a preliminary analysis on the operating status of each diffuser based on the determination result; The S20 includes: S201: According to the three-dimensional distance calculation formula, the distance value d between the center of the j-th target object and the center of the diffuser numbered i in the temperature boundary layer matching the diffuser numbered i is calculated. ij Calculation is performed, and the target objects include mobile terminals and smart appliances. The temperature values ​​of each target object are collected through the Internet of Things technology (the specific method is: using the temperature sensors installed in the mobile terminals and smart appliances to sense the temperature values ​​at the locations of the mobile terminals and smart appliances, and the control terminal wirelessly connected to the smart appliances and the mobile terminals collects the temperature values ​​sensed by the mobile terminals and smart appliances); S202: At time intervals t, using the Internet of Things technology, collect the temperature value of the j-th target object in the temperature boundary layer matching the diffuser numbered i, and randomly select a target object in the temperature boundary layer matching the diffuser numbered i, where there are multiple target objects in the temperature boundary layer; when hour: according to Predict the operation index of diffuser numbered i at time T+p*t; when hour: according to Predict the operation index of diffuser numbered i at time T+p*t; Wherein, j=1,2,…,m, represents the number corresponding to each target object in the temperature boundary layer, m represents the total number of target objects in the temperature boundary layer, u represents the number corresponding to the selected target object, u=1,2,…,m, p=0,1,2,…,q, represents the numbering of the temperature collection time of the control terminal in chronological order, q represents the total number, T represents the time when the control terminal first collects the temperature value of the target object, W ij(T+p*t) represents the temperature value of the jth target object in the temperature boundary layer matching the diffuser numbered i at the time T+p*t, U i(T+p*t) represents the operation index of diffuser numbered i at time T+p*t; S203: If U i(T+p*t) >0.1, the temperature boundary layer matching the diffuser numbered i is considered to be the target temperature boundary layer; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] <W ij(T+p*t) , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the open state at the time T+p*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] =W ij(T+p*t) <E T+(p+1)*t , then the temperature boundary layer matching the diffuser numbered i is considered to be a non-target temperature boundary layer. At time T+(p+1)*t, the diffuser numbered i is in the open state. E T+(p+1)*t Indicates the average outdoor temperature at time T+(p+1)*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] >W ij(T+p*t) , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the closed state at time T+(p+1)*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] =W ij(T+p*t) ≥E T+(p+1)*t , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the closed state at time T+(p+1)*t; S30: predicting the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; S30 includes: In the target temperature boundary layer, according to h xj(T+p*t) =(E T+(p+1)*t -E T+p*t ) / (W xj[T+(p+1)*t] -W xj(T+p*t) ) predicting the temperature influence coefficient of the outdoor temperature on the j-th target object in the target temperature boundary layer numbered x; Where x=1,2,…,q, represents the number corresponding to each target temperature boundary layer, q represents the total number of target temperature boundary layers, W xj(T+p*t) Indicates the temperature value corresponding to the jth target object in the target temperature boundary layer numbered x at time T+p*t; S40: judging and analyzing the operating state of the diffuser matching each target temperature boundary layer according to the predicted temperature influence coefficient; S40 includes: S401: If h xj(T+p*t) ≥0.6, the diffuser matching the target temperature boundary layer numbered x is considered to be in the closed state at time T+p*t; If h xj(T+p*t) ≥0.6 part is true, then at 0≤h xj(T+p*t) When <0.6, the number of the corresponding target object is put into the set M; according to , predict the operating index of the diffuser matching the target temperature boundary layer numbered x at time T+p*t, where d xj Indicates the distance between the center of the jth target object in the target temperature boundary layer numbered x and the center of the diffuser matching the target temperature boundary layer numbered x. When number j is stored in the set M, , when number j is not stored in set M, , when number u is stored in set M, , when number u is not stored in the set M, ; S402: If 0≤U x(T+p*t) ≤0.1 and when number j is stored in set M, W xj[T+(p+1)*t] <W xj(T+p*t) , then the diffuser matching the target temperature boundary layer numbered x at the time T+p*t is considered to be in the open state; If 0≤U x(T+p*t) ≤0.1 and when number j is stored in set M, W xj[T+(p+1)*t] >W xj(T+p*t) , it is considered that the diffuser matching the target temperature boundary layer numbered x is in the closed state at the time T+p*t; If 0≤U i(T+p*t) ≤0.1 and when number j is stored in set M, Wij[T+(p+1)*t] =W ij(T+p*t) <E T+(p+1)*t , then the diffuser matching the target temperature boundary layer numbered x at the time T+p*t is considered to be in the open state; If 0≤U i(T+p*t) ≤0.1 and when number j is stored in set M, W ij[T+(p+1)*t] =W ij(T+p*t) ≥E T+(p+1)*t , then the diffuser matching the target temperature boundary layer numbered x at time T+p*t is considered to be in the closed state.

[0021] An intelligent air-conditioning state judgment and analysis system based on the Internet of Things, the system includes a temperature boundary layer search module, an operation state preliminary analysis module, a temperature influence coefficient prediction module and an operation state judgment and analysis module; The temperature boundary layer search module is used to search for the temperature boundary layer existing in the target area; The temperature boundary layer search module includes a position coordinate acquisition unit, a guide vane inclination angle determination unit and a temperature boundary layer search unit; The position coordinate acquisition unit randomly selects a point in the target area as the coordinate origin to construct a three-dimensional space coordinate system, and acquires the position coordinates of the center of each diffuser installed in the target area in the three-dimensional space coordinate system; The guide vane inclination angle determination unit collects the side image of each diffuser by using the image acquisition device, and determines the inclination angle of the guide vane of each diffuser based on the collected side image; The temperature boundary layer search unit searches for the temperature boundary layer matching each diffuser according to the positional relationship between the inclination angle of the diffuser guide vane and the vertical line segment between the diffuser center and the ground, and the air supply angle range of the diffuser; The operation status preliminary analysis module is used to determine the target temperature boundary layer and perform preliminary analysis on the operation status driven by each diffuser based on the determination result; The operation status preliminary analysis module includes a temperature value acquisition unit, an operation index prediction unit and an operation status preliminary analysis unit; The temperature value collection unit collects the temperature value of each target object through the Internet of Things technology; The operation index prediction unit predicts the operation index of each diffuser according to the real-time temperature change difference of each target object and the distance value of each target object from the corresponding diffuser, and determines the target temperature boundary layer based on the prediction result; The operation status preliminary analysis unit performs preliminary analysis on the operation status of each diffuser according to the prediction result of the operation index prediction unit, the real-time temperature change of each target object and the real-time outdoor temperature value; The temperature influence coefficient prediction module is used to predict the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; The temperature influence coefficient prediction module uses the constructed mathematical model to predict the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; The operation status judgment and analysis module is used to judge and analyze the operation status of the diffuser matching each target temperature boundary layer; The operation status judgment and analysis module includes a temperature influence coefficient analysis unit and an operation status judgment and analysis unit; The temperature influence coefficient analysis unit compares the prediction result transmitted by the temperature influence coefficient prediction module with the set threshold value, and based on the comparison result, selects whether to put the number of the corresponding target object into the set, and analyzes the operating state of the diffuser matching the target temperature boundary layer; The operation status judgment and analysis unit constructs a mathematical formula to predict the operation index of the diffuser matching each target temperature boundary layer according to the number of the target object stored in the set and the temperature influence coefficient of the outdoor temperature on each target object, and judges and analyzes the operation status of the diffuser matching each target temperature boundary layer based on the prediction result.

[0022] Example 1: Assume that there are two target objects in the temperature boundary layer matching the diffuser numbered 1. At time T+t, the temperature values ​​of the first and second target objects collected by the control terminal are 30°C and 32°C respectively. At time T+2*t, the temperature values ​​of the first and second target objects collected by the control terminal are 28°C and 31°C respectively. The distance d between the center of the first target object in the temperature boundary layer matching the diffuser numbered 1 and the center of the diffuser numbered 1 is 11 = 2 meters, the distance d between the center of the second target object in the temperature boundary layer matched by diffuser number 1 and the center of diffuser number 1 11 =3.8 meters, assuming u=1, then the operating index of diffuser No. 1 at time T*t is: ; Since 0≤U 1(T+t) =0.01≤0.1 and W 1j[T+2*t] <W 1j(T+t) , it is considered that the temperature boundary layer matching the diffuser numbered 1 is not the target temperature boundary layer, and the diffuser numbered 1 is in the open state at time T+t.

[0023] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things, characterized in that: The method comprises: S10: acquiring the position information of each diffuser installed in the target area, and searching for the temperature boundary layer existing in the target area according to the inclination angle of the guide vane of each diffuser; S20: using the Internet of Things technology to sense the temperature change of each target object in each temperature boundary layer, determining the target temperature boundary layer based on the sensed result and the positional relationship between the target objects, and performing a preliminary analysis on the operating status of each diffuser based on the determination result; S30: predicting the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; S40: According to the predicted temperature influence coefficient, the operation state of the diffuser matching each target temperature boundary layer is judged and analyzed.

2. According to claim 1, a method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things is characterized in that: The S10 includes: S101: randomly selecting a point in the target area as the coordinate origin to construct a three-dimensional space coordinate system, and obtaining the position coordinates of the center of each diffuser installed in the target area in the three-dimensional space coordinate system; S102: using an image acquisition device to acquire a side image of each diffuser, and determining an inclination angle of a guide vane of each diffuser based on the acquired side image; S103: When the inclination angle of the diffuser guide vane is located on the right side of the vertical line segment between the diffuser center and the ground, according to [γ i ,f] to determine the air supply angle range of the diffuser, and search for the temperature boundary layer matching the diffuser numbered i; When the inclination angle of the diffuser guide vane is located on the left side of the vertical line segment between the center of the diffuser and the ground, according to [-f,-γ i ] The air supply angle range of the diffuser is determined, and the temperature boundary layer matching the diffuser numbered i is searched; Among them, γ i represents the inclination angle of the diffuser guide vane numbered i, and f represents the angle between the upper air supply line of the diffuser and the vertical line segment of the diffuser center compared to the ground.

3. According to claim 2, a method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things is characterized in that: The S20 includes: S201: Calculate the distance value dij between the center of the jth target object and the center of the diffuser numbered i in the temperature boundary layer matching the diffuser numbered i according to the three-dimensional distance calculation formula, the target objects include mobile terminals and smart appliances, and collect the temperature value of each target object through the Internet of Things technology; S202: At time intervals t, using the Internet of Things technology, collect the temperature value of the j-th target object in the temperature boundary layer matching the diffuser numbered i, and randomly select a target object in the temperature boundary layer matching the diffuser numbered i; when hour: according to Predict the operation index of diffuser numbered i at time T+p*t; when hour: according to Predict the operation index of diffuser numbered i at time T+p*t; Wherein, j=1,2,…,m, represents the number corresponding to each target object in the temperature boundary layer, m represents the total number of target objects in the temperature boundary layer, u represents the number corresponding to the selected target object, u=1,2,…,m, p=0,1,2,…,q, represents the numbering of the temperature collection time of the control terminal in chronological order, q represents the total number, T represents the time when the control terminal first collects the temperature value of the target object, W ij(T+p*t) represents the temperature value of the jth target object in the temperature boundary layer matching the diffuser numbered i at the time T+p*t, U i(T+p*t) represents the operation index of diffuser numbered i at time T+p*t; S203: If U i(T+p*t) >0.1, the temperature boundary layer matching the diffuser numbered i is considered to be the target temperature boundary layer; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] <W ij(T+p*t) , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the open state at the time T+p*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] =W ij(T+p*t) <E T+(p+1)*t , then the temperature boundary layer matching the diffuser numbered i is considered to be a non-target temperature boundary layer. At time T+(p+1)*t, the diffuser numbered i is in the open state. E T+(p+1)*t Indicates the average outdoor temperature at time T+(p+1)*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] >W ij(T+p*t) , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the closed state at time T+(p+1)*t; If 0≤U i(T+p*t) ≤0.1 and W ij[T+(p+1)*t] =W ij(T+p*t) ≥E T+(p+1)*t , it is considered that the temperature boundary layer matching the diffuser numbered i is not the target temperature boundary layer, and the diffuser numbered i is in the closed state at time T+(p+1)*t.

4. The method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things according to claim 3 is characterized in that: The S30 includes: In the target temperature boundary layer, according to h xj(T+p*t) =(E T+(p+1)*t -E T+p*t ) / (W xj[T+(p+1)*t] -W xj(T+p*t) ) predicting the temperature influence coefficient of the outdoor temperature on the j-th target object in the target temperature boundary layer numbered x; Where x=1,2,…,q, represents the number corresponding to each target temperature boundary layer, q represents the total number of target temperature boundary layers, W xj(T+p*t) Indicates the temperature value corresponding to the jth target object in the target temperature boundary layer numbered x at time T+p*t.

5. The method for judging and analyzing the state of an intelligent air conditioner based on the Internet of Things according to claim 4 is characterized in that: The S40 includes: S401: If h xj(T+p*t) ≥0.6, the diffuser matching the target temperature boundary layer numbered x is considered to be in the closed state at time T+p*t; If h xj(T+p*t) ≥0.6 part is true, then at 0≤h xj(T+p*t) When <0.6, the number of the corresponding target object is put into the set M; At this time, according to , predict the operating index of the diffuser matching the target temperature boundary layer numbered x at time T+p*t, where d xj Indicates the distance between the center of the jth target object in the target temperature boundary layer numbered x and the center of the diffuser matching the target temperature boundary layer numbered x. When number j is stored in the set M, , when number j is not stored in set M, ; S402: If 0≤U x(T+p*t) ≤0.1 and when number j is stored in set M, W xj[T+(p+1)*t] <W xj(T+p*t) , then the diffuser matching the target temperature boundary layer numbered x at the time T+p*t is considered to be in the open state; If 0≤U x(T+p*t) ≤0.1 and when number j is stored in set M, W xj[T+(p+1)*t] >W xj(T+p*t) , it is considered that the diffuser matching the target temperature boundary layer numbered x is in the closed state at the time T+p*t; If 0≤U i(T+p*t) ≤0.1 and when number j is stored in set M, W ij[T+(p+1)*t] =W ij(T+p*t) <E T+(p+1)*t , then the diffuser matching the target temperature boundary layer numbered x at the time T+p*t is considered to be in the open state; If 0≤U i(T+p*t) ≤0.1 and when number j is stored in set M, W ij[T+(p+1)*t] =W ij(T+p*t) ≥E T+(p+1)*t , then the diffuser matching the target temperature boundary layer numbered x at time T+p*t is considered to be in the closed state.

6. An intelligent air conditioner status judgment and analysis system based on the Internet of Things applied to the intelligent air conditioner status judgment and analysis method based on the Internet of Things according to any one of claims 1 to 5, characterized in that: The system includes a temperature boundary layer search module, an operation status preliminary analysis module, a temperature influence coefficient prediction module and an operation status judgment analysis module; The temperature boundary layer search module is used to search for the temperature boundary layer existing in the target area; The operating status preliminary analysis module is used to determine the target temperature boundary layer and perform preliminary analysis on the operating status driven by each diffuser based on the determination result; The temperature influence coefficient prediction module is used to predict the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer; The operation status judgment and analysis module is used to judge and analyze the operation status of the diffuser matching each target temperature boundary layer.

7. The intelligent air-conditioning state judgment and analysis system based on the Internet of Things according to claim 6 is characterized in that: The temperature boundary layer search module includes a position coordinate acquisition unit, a guide vane inclination angle determination unit and a temperature boundary layer search unit; The position coordinate acquisition unit randomly selects a point in the target area as the coordinate origin to construct a three-dimensional space coordinate system, and acquires the position coordinates of the center of each diffuser installed in the target area in the three-dimensional space coordinate system; The guide vane inclination angle determination unit collects the side image of each diffuser by using an image acquisition device, and determines the inclination angle of the guide vane of each diffuser based on the collected side image; The temperature boundary layer searching unit searches for a temperature boundary layer matching each diffuser according to the positional relationship between the inclination angle of the diffuser guide vane and the vertical line segment between the diffuser center and the ground, and the air supply angle range of the diffuser.

8. The intelligent air-conditioning status judgment and analysis system based on the Internet of Things according to claim 7 is characterized in that: The operation status preliminary analysis module includes a temperature value acquisition unit, an operation index prediction unit and an operation status preliminary analysis unit; The temperature value acquisition unit acquires the temperature value of each target object through the Internet of Things technology; The operation index prediction unit predicts the operation index of each diffuser according to the real-time temperature change difference of each target object and the distance value of each target object from the corresponding diffuser, and determines the target temperature boundary layer based on the prediction result; The operation status preliminary analysis unit performs preliminary analysis on the operation status of each diffuser according to the prediction result of the operation index prediction unit, the real-time temperature change of each target object and the real-time outdoor temperature value.

9. The intelligent air-conditioning status judgment and analysis system based on the Internet of Things according to claim 8 is characterized in that: The temperature influence coefficient prediction module predicts the temperature influence coefficient of the outdoor temperature on each target object in the target temperature boundary layer by using the constructed mathematical model.

10. The intelligent air-conditioning state judgment and analysis system based on the Internet of Things according to claim 9, characterized in that: The operation status judgment and analysis module includes a temperature influence coefficient analysis unit and an operation status judgment and analysis unit; The temperature influence coefficient analysis unit compares the prediction result transmitted by the temperature influence coefficient prediction module with the set threshold value, and based on the comparison result, selects whether to put the number of the corresponding target object into the set, and analyzes the operating state of the diffuser matching the target temperature boundary layer; The operation status judgment and analysis unit constructs a mathematical formula to predict the operation index of the diffuser matching each target temperature boundary layer according to the number of the target object stored in the set and the temperature influence coefficient of the outdoor temperature on each target object, and judges and analyzes the operation status of the diffuser matching each target temperature boundary layer based on the prediction result.

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