Method for processing data of operating parameters of an air conditioning unit

Abstract

The application provides a processing method of data of operation parameters of an air conditioning unit, which comprises the following steps: for each air conditioning operation parameter, a plurality of continuous data is acquired within a period of time, the plurality of continuous data constitutes a data sequence, and each data in the data sequence corresponds to a time point; it is determined whether the air conditioning operation parameter is an internal parameter or an external parameter; the stability of data of at least some time points of the air conditioning operation parameter is calculated; and data that needs to be removed in the plurality of continuous data is screened based on the stability of data of the internal parameter and / or the stability of data of the external parameter. The processing method of the application can remove data of the air conditioning unit in a mutation state, so as to calculate the performance of the air conditioning unit based on operation parameters of the air conditioning unit in a steady state, thereby making the calculation result more accurate.

Description

Technical Field

[0001] This application relates to data processing methods, and more particularly to data processing methods for operating parameters of air conditioning units. Background Technology

[0002] The development of air conditioning units requires extensive experimentation to confirm performance and determine areas for improvement. Air conditioning units operate under different conditions in response to environmental changes and shifts in target parameters, with each condition having different data for multiple operating parameters. When the environment or target parameters change, the air conditioning unit adjusts its operating conditions accordingly. Specifically, before the environmental or target parameter changes, the air conditioning unit operates in condition one with the first set of operating parameters. After the environmental or target parameter changes, the air conditioning unit operates in condition two with the second set of operating parameters. However, after each change in environment or target parameter, the air conditioning unit does not immediately adjust to condition two; instead, it changes from condition one and then stabilizes back in condition two. During this process, the operating parameters fluctuate significantly, which can affect various indicators used to assess the performance of the air conditioning unit.

[0003] Therefore, a data processing method for the operating parameters of air conditioning units is needed to process the data of the operating parameters of air conditioning units. Summary of the Invention

[0004] To achieve the above objectives, this application provides a method for processing data of operating parameters of an air conditioning unit, comprising the following steps: for each air conditioning operating parameter, acquiring several consecutive data points over a period of time, the several consecutive data points constituting a data sequence, each data point in the data sequence corresponding to a time point; determining whether the air conditioning operating parameter is an internal parameter or an external parameter; calculating the stability of the data at at least some time points of the air conditioning operating parameter; and filtering the data that needs to be removed from the several consecutive data points based on the stability of the data of the internal parameter and / or the stability of the data of the external parameter.

[0005] According to the above-mentioned method for processing the operating parameters of the air conditioning unit, the data to be removed from the several consecutive data based on the stability of the external parameter data includes: comparing the stability of each data of the external parameter at the same time point with the external stability limit; and removing the data of the various external parameters at the same time point when the stability of at least one of the external parameter data is less than the external stability limit.

[0006] According to the above-mentioned method for processing the operating parameters of the air conditioning unit, before the step of filtering the data that needs to be removed from the several consecutive data based on the stability of the internal parameter data and / or the stability of the external parameter data, the processing method further includes: when the air conditioning operating parameters are internal parameters, calculating the stability of the unit based on the stability of the internal parameter data.

[0007] According to the data processing method of the operating parameters of the air conditioning unit, the data to be removed from the several consecutive data based on the stability of the internal parameter data includes: comparing the internal stability of the unit with the internal stability limit; when the internal stability of the unit is less than the internal stability limit, the data is removed.

[0008] According to the data processing method of the operating parameters of the air conditioning unit, the stability of the unit is calculated based on the stability of the data of various internal operating parameters at the corresponding time point and the weighting coefficients of various internal operating parameters.

[0009] According to the above-mentioned data processing method for the operating parameters of the air conditioning unit, calculating the stability of the data at at least a portion of the time points of the air conditioning operating parameters includes: selecting a data sequence corresponding to at least one operating parameter from several data sequences, wherein the data sequence includes m consecutive data; selecting n consecutive data as a window in chronological order, starting from several consecutive data, thereby forming several sliding windows, wherein n < m, and n is a positive odd number; for each air conditioning operating parameter in each sliding window, calculating the stability of the data located in the middle of the data in the sliding window, wherein the stability of the data located in the middle of the data is related to the other data in its sliding window.

[0010] Based on the data processing method of the operating parameters of the air conditioning unit mentioned above, n consecutive data points are selected as a window, including: the length of the n consecutive data points is determined based on the time length of COP data change under the data change of compressor frequency.

[0011] Based on the data processing method for the operating parameters of the air conditioning unit mentioned above, the stability of the data located in the middle of the sliding window is calculated as follows: data stability ;

[0012] Where the range of values ​​for k is: k=0,1,2,…,n-1;

[0013] i The range of values ​​for is: .

[0014] According to the data processing method of the above-mentioned air conditioning unit operating parameters, the internal parameters include at least one of compressor frequency data, fan speed data, and expansion valve opening data, and the external parameters include at least one of ambient temperature data, outlet water temperature data, cooling capacity data, water flow rate data, and COP data.

[0015] According to the data processing method of the above-mentioned air conditioning unit operating parameters, the stability of the unit is calculated based on the weight of each data in the compressor frequency data, fan speed data, and expansion valve opening data.

[0016] The processing method of this application can remove data of the air conditioning unit in a sudden state, thereby calculating the performance of the air conditioning unit based on the operating parameters of the air conditioning unit in a steady state, so as to make the calculation results more accurate.

[0017] Other features, advantages, and embodiments of this application may be set forth or become apparent from the following detailed description, accompanying drawings, and claims. Furthermore, it should be understood that the above description and the following detailed description are exemplary and intended to provide further explanation, without limiting the scope of the claimed application. However, the detailed description and specific examples only indicate preferred embodiments of this application. Various changes and modifications within the spirit and scope of this application will become apparent to those skilled in the art through these detailed descriptions. Attached Figure Description

[0018] The features and advantages of this application can be better understood by reading the following detailed description with reference to the accompanying drawings, in which the same reference numerals denote the same parts, wherein:

[0019] Figure 1 This is a schematic diagram of the air conditioning unit and control device of this application;

[0020] Figure 2 yes Figure 1 Internal structure diagram of the central control device;

[0021] Figure 3 yes Figure 1 A flowchart of the data processing method for the operating parameters of the air conditioning unit in the control device;

[0022] Figure 4 This is a more detailed flowchart in step 306 when the air conditioner's operating parameters are external operating parameters;

[0023] Figure 5 This is a more detailed flowchart of step 310 when the air conditioner's operating parameters are external operating parameters;

[0024] Figure 6This is a more detailed flowchart in step 306 when the air conditioner's operating parameters are internal operating parameters;

[0025] Figure 7 This is a more detailed flowchart of step 310 when the air conditioner's operating parameters are internal operating parameters;

[0026] Figure 8 and Figure 9 This is an example diagram showing the operating parameters of an air conditioning unit.

[0027] Figure 10 This is a parameter diagram of compressor frequency and COP when the air conditioning operating parameters of an exemplary air conditioning unit undergo the first sudden change.

[0028] Figure 11 and Figure 12 Based on Figure 8 and Figure 9 The data, based on the processing of external and internal parameters of the air conditioning unit's operating parameters, is presented in the form of an air conditioning operating parameter diagram.

[0029] Figure 13 and Figure 14 Based on Figure 8 and Figure 9 The data is a diagram of the air conditioning operating parameters after processing the data of the air conditioning unit's operating parameters based on external parameters. Detailed Implementation

[0030] Various specific embodiments of the invention will now be described with reference to the accompanying drawings, which form part of this specification.

[0031] Figure 1 This is a schematic diagram of the air conditioning unit 102 and control device 104 of this application. Figure 1 As shown, the air conditioning unit 102 includes a compressor 112, a throttling device 114, a condenser 116, and an evaporator 118, which are connected by pipes to form a refrigerant system. The air conditioning unit 102 can provide cooling or heating to users. The air conditioning unit 102 also includes a fan 120 for delivering the cooling or heating energy from the evaporator 118 to the users.

[0032] The control device 104 is communicatively connected to the air conditioning unit 102 and can acquire specific data on various operating parameters of the air conditioning unit 102. The operating parameters that the control device 104 can acquire include: the frequency of the compressor 112, the speed of the fan 120, the opening degree of the throttling device 114, the outlet water temperature of the condenser 116, the cooling capacity of the air conditioning unit 102, the water flow rate of the condenser 116, the COP (i.e., energy efficiency ratio) of the air conditioning unit 102, and the ambient temperature where the air conditioning unit 102 is located.

[0033] Figure 2 yes Figure 1 Internal structure diagram of the central control device 104. (See diagram below.) Figure 2 As shown, the control device 104 includes a bus 202, a processor 204, an input interface 208, an output interface 212, and a memory 214 containing a control program. The various components of the control device 104, including the bus 202, processor 204, input interface 208, output interface 212, and memory 214, are communicatively connected to the bus 202, enabling the processor 204 to control the operation of the input interface 208, output interface 212, and memory 214. Specifically, the memory 214 stores programs, instructions, and data, while the processor 204 reads programs, instructions, and data from the memory 214 and can write data to the memory 214. By executing the program and instruction read from the memory 214, the processor 204 controls the operation of the input interface 208 and output interface 212. Figure 2 As shown, input interface 208 is communicatively connected to air conditioning unit 102 via communication connection 209. Input interface 208 receives operating parameters from air conditioning unit 102 via communication connection 209. After processing by program 216 in memory 214, each operating parameter is displayed on an output device (e.g., a computer screen) via output interface 212. As an example, output interface 212 is communicatively connected to an output device via communication connection 211. Figures 3-9 The flowcharts shown are all stored in program 216.

[0034] Figure 3 yes Figure 1 A flowchart illustrating the data processing method for the operating parameters of the air conditioning unit 102 in the control device 104. (See attached flowchart.) Figure 3 As shown, in step 302, processor 204 acquires m consecutive data points within a certain time period for each type of air conditioner operating parameter, forming a data sequence. Each data point in the data sequence corresponds to a specific time point. Processor 204 then proceeds to step 304.

[0035] In step 304, the processor 204 determines whether each air conditioning operating parameter is an external or internal parameter. As an example, in this application, the compressor frequency, fan speed, and expansion valve opening are considered internal parameters, while the ambient temperature, outlet water temperature, cooling capacity, water flow rate, and COP are considered external parameters. The processor 204 then proceeds to step 306.

[0036] In step 306, processor 204 calculates the stability of the data at at least a portion of the time points for each parameter. Processor 204 then proceeds to step 310.

[0037] In step 310, processor 204 filters data that needs to be removed based on the calculated data stability of external parameters and / or internal parameters. Then, processor 204 proceeds to step 312, and the program ends.

[0038] Figure 4 This is a more detailed flowchart for step 306, where the air conditioner's operating parameters are external operating parameters. For example... Figure 4 As shown, when the processor 204 determines that the air conditioner operating parameters are external operating parameters, step 306 includes steps 402, 404 and 406.

[0039] In step 402, processor 204 selects a data sequence of external operating parameters from several data sequences. Then, processor 204 proceeds to step 404.

[0040] In step 404, the processor 204, following a chronological order, sequentially selects n consecutive data points as a window, starting with m consecutive data points, thus forming m-n+1 sliding windows. Here, n is a positive odd number. <m。

[0041] In the process of selecting the window, as a first example, n can be determined based on the time length of the COP data change under the data change of the compressor frequency. Specifically, the processor 204 records the latest sequence number of the compressor frequency in the first stable state as t1, and records the earliest sequence number of the compressor frequency in the second stable state as t2. The processor 204 queries the COP data with sequence number t2 in the COP data, and calculates the ratio A of the COP mean of three adjacent points starting from the j-th sequence number thereafter:

[0042]

[0043] Where j = 0, 1, 2, ..., m-t2.

[0044] When A is greater than or equal to At that time, processor 204 records j. Then, processor 204 compares multiple recorded j values ​​and obtains the smallest one. .

[0045] if If it is an odd number, then the window length ;

[0046] if If it is an even number, then the window length .

[0047] As a second example, .

[0048] In the process of selecting the window, as a second example, the processor 204 can obtain the duration of the COP change when the air conditioning operating parameters undergo the first abrupt change, and then obtain the number of data acquisitions Z during the duration of the change.

[0049] If Z is odd, then the window length n = Z;

[0050] If Z is even, then the window length n = Z + 1.

[0051] Subsequently, processor 204 transfers the operation to step 406.

[0052] In step 406, the processor 204 calculates the stability of the middle data point among the various data points of the external parameter for each sliding window. The stability of the middle data point is correlated with the other data points in its respective sliding window. For example, in this application, a parameter includes m data points, i.e. , , ,…, .

[0053] The i-th data Stability: ;

[0054] in, i The range of values ​​for is: ;

[0055] The value of k ranges from 0, 1, 2, ..., n-1.

[0056] For example, in this application, the stability of the ambient temperature is... The stability of the cooling capacity is The stability of COP is The stability of the outlet water temperature is .

[0057] Figure 5 This is a more detailed flowchart in step 310 when the air conditioner's operating parameters are the external operating parameters. For example... Figure 5 As shown, when processor 204 determines that the air conditioner operating parameters are external operating parameters, step 310 includes steps 502, 504, and 506. In step 502, processor 204 determines whether the stability of the data located in the middle of each window is less than the external stability limit. When processor 204 determines that the stability is less than the external stability limit, processor 204 transfers the operation to step 504.

[0058] In step 504, processor 204 removes the data for each external operating parameter corresponding to that time point. Then, processor 204 proceeds to step 312.

[0059] In step 502, when the processor 204 determines that the stability is not less than the external stability limit, the processor 204 will transfer the operation to step 506.

[0060] In step 506, the processor 204 will retain the data of the external operating parameters corresponding to that point in time.

[0061] For example, in this application, the external stability limit is... .when If the data for each external operating parameter at time i does not meet the external stability requirements, it needs to be removed. As an example, .

[0062] Figure 6 This is a more detailed flowchart for step 206, where the air conditioner's operating parameters are internal operating parameters. For example... Figure 6 As shown, when the processor 204 determines that the air conditioner operating parameters are internal operating parameters, step 306 includes steps 602, 604 and 606.

[0063] In step 602, processor 204 selects a data sequence of an internal operating parameter from several data sequences. For example, in this application, a parameter includes m data points, namely X1, X2, X3, ..., Xm. Then, processor 204 proceeds to step 604.

[0064] In step 604, the processor 204 sequentially selects n consecutive data points as windows, starting with m consecutive data points, to form m-n+1 sliding windows. Here, n is a positive odd number, and n < m. The method for determining n is similar to that described in step 404, and will not be repeated here. Subsequently, the processor 204 proceeds to step 606.

[0065] In step 606, the processor 204 calculates the stability of the middle data among the various data of the internal parameter for each sliding window. The stability of the middle data is correlated with the other data in its respective sliding window.

[0066] Stability of the i-th data point: ;

[0067] Where the range of values ​​for i is: i = (n+1) / 2, (n+1) / 2+1, ..., m-(n-1) / 2;

[0068] The value of k ranges from 0, 1, 2, ..., n-1.

[0069] Figure 7 This is a more detailed flowchart in step 310 when the air conditioner's operating parameters are the internal operating parameters. For example... Figure 7 As shown, when the processor 204 determines that the air conditioner operating parameters are internal operating parameters, step 310 includes steps 702, 712, 714 and 716.

[0070] Specifically, in step 702, for each time point, the unit-internal stability corresponding to that time point is calculated. The unit-internal stability is calculated based on the stability of the data of various internal operating parameters corresponding to that time point and the weighting coefficients of these internal operating parameters. For example, in this application, Indicates the stability of the compressor frequency. This indicates the stability of the fan speed. This indicates the stability of the expansion valve opening.

[0071] No. The unit stability r corresponding to each time point satisfies:

[0072] .

[0073] in, The weighting coefficient representing the compressor frequency. The weighting coefficient representing the fan speed. The weighting coefficient represents the expansion valve opening degree, and .

[0074] As an example, , The values ​​range for each value are: 0.5-0.9, 0.1-0.4, and 0.05-0.3.

[0075] As an example, =0.61, , .

[0076] In step 712, processor 204 determines whether the unit's internal stability is less than the internal stability limit at each time point. When processor 204 determines that the unit's internal stability is less than the internal stability limit, processor 204 proceeds to step 714.

[0077] In step 714, processor 204 removes the data for each internal operating parameter corresponding to that time point. Then, processor 204 proceeds to step 312.

[0078] In step 712, when the processor 204 determines that the unit’s internal stability is not less than the internal stability limit, the processor 204 will transfer the operation to step 906.

[0079] In step 716, the processor 204 will retain the data of each internal operating parameter corresponding to that point in time.

[0080] For example, in this application, the internal stability limit is... .when If the data for each internal operating parameter at time point i does not meet the internal stability requirement, it needs to be removed. As an example, .

[0081] Figure 8 and 9 These are the air conditioning operating parameters of the air conditioning unit 102 obtained by the exemplary control device 104. For example... Figure 8 and 9 As shown, the test time (i.e., the operating time of the air conditioning unit 102) was approximately from 9:14 AM to 10:24 AM. The control device 104 acquired parameters of the air conditioning unit 102, namely: Figure 8 The compressor frequency, represented by a triangle, in Figure 8 The fan speed is represented by a square in the middle. Figure 8 The expansion valve opening is represented by a circle in the middle. Figure 9 The ambient temperature is represented by a square (roughly located in the second row from the right). Figure 9 The outlet water temperature is represented by a diamond (roughly located in the first row on the right). Figure 9 The cooling capacity is represented by a triangle (roughly located in the fourth row from the right), and in... Figure 9 The COP is represented by a circle (it is roughly located in the third row from the right). Figure 8 and 9 As can be seen, there were three distinct periods of significant state change during the test. These changes occurred as the air conditioning unit 102 adapted to changes in the environment or target parameters. Data acquired under these unstable states (i.e., the state between two stable states) can affect the assessment of the overall performance of the air conditioning unit 102; therefore, it is necessary to remove the data acquired under these unstable states.

[0082] The following is based on Figure 8 and 9 Taking the data in the example, here is a detailed explanation of how to process the data for the running parameters:

[0083] like Figure 8 and 9As shown, the air conditioning unit 102 can collect all parameters, including compressor frequency, fan speed, expansion valve opening, ambient temperature, outlet water temperature, cooling capacity, and COP. For each parameter, it collects data once every 8 seconds, thus obtaining approximately 525 data points for each parameter (i.e., m=525). The processor 204 uses compressor frequency, fan speed, and expansion valve opening as internal parameters, and ambient temperature, outlet water temperature, cooling capacity, and COP as external parameters.

[0084] The processor 204 arranges the 525 data points in the order of their acquisition time and selects a window length n.

[0085] Figure 10 This is a parameter graph showing the compressor frequency and COP of an exemplary air conditioning unit when the air conditioning operating parameters undergo their first abrupt change (i.e., from the first stable state to the second stable state). According to the algorithm in the first example, the processor 204 obtains data from the air conditioning unit 102 for approximately 4 minutes, collecting data every 8 seconds. The last data point where the air conditioning compressor frequency stabilizes at 100% is numbered t1=82, and the first data point where the frequency stabilizes at 75% is numbered t2=85. Then, the mean COP ratio of adjacent three points at j=0, 1, 2… is calculated sequentially until A≥98%.

[0086]

[0087] When j=27, A = 0.982 > 0.98. At this time... Since it is an even number, the window length n should be an odd number, i.e., n=31.

[0088] According to the algorithm in the second example, the processor 204 obtains data from the air conditioning unit 102 for approximately 4 minutes, and it collects data every 8 seconds. Therefore, the corresponding sliding window n = (4 × 60) / 8 + 1 = 31.

[0089] Thus, 495 sliding windows can be formed from the 525 data points. Specifically, the first sliding window includes data points 1-31, the second sliding window includes data points 2-32, and so on. The processor 204 will calculate the stability of the data points located in the middle of the 495 sliding windows.

[0090] First, for external parameters, the stability of ambient temperature is calculated according to the following formula: The stability of the cooling capacity is The stability of COP is The stability of the outlet water temperature is :

[0091]

[0092]

[0093]

[0094]

[0095] Where n=31;

[0096] The range of values ​​for i is: i = 16, 17, ..., 510;

[0097] The range of values ​​for k is: k = 0, 1, 2, ..., 30.

[0098] Therefore, we can obtain , , as well as .

[0099] Subsequently, processor 204 removes the parameters based on the stability of the four external parameters. The stability of the four parameters at any given time satisfies:

[0100] , , and .

[0101] Then, the i-th data point is retained. When at least one of the four parameters has a stability of less than 99% at any given time, the processor 204 will remove the data of each external operating parameter at the time point corresponding to that stability.

[0102] Secondly, for the internal parameters, the stability of the compressor frequency is calculated according to the following formula. Stability of fan speed Stability of expansion valve opening :

[0103]

[0104]

[0105]

[0106] Where n=31;

[0107] The range of values ​​for i is: i = 16, 17, ..., 510;

[0108] The range of values ​​for k is: k = 0, 1, 2, ..., 30.

[0109] Therefore, we can obtain , as well as .

[0110] Subsequently, processor 204 calculates the intra-unit stability according to the intra-unit stability formula. When the unit's internal stability r is less than 98% at any given time, processor 204 will remove the data for each internal operating parameter at the time point corresponding to that unit's internal stability. After processing the operating parameter data of the air conditioning unit as described above, processor 204 removes... Figure 8 and 9 This is part of the data, and this data was collected when the air conditioning unit 102 was in a sudden change. Figure 11 and 12 The diagrams show the air conditioning operating parameters after processing the data of the air conditioning unit's operating parameters based on external and internal parameters.

[0111] It should be noted that although this application focuses on describing the processing of air conditioning unit operating parameter data based on both external and internal parameters, it is also possible to process the air conditioning unit operating parameter data based on either external or internal parameters alone. For example, Figure 13 and 14 They respectively show the basis Figure 8 and Figure 9 The data, processed based on external parameters, shows the air conditioning unit's operating parameters. From... Figure 13 and 14 As can be seen, the air conditioning operating parameters can be processed based solely on the stability of external parameters, thereby removing data from the air conditioning unit 102 that is in a state of sudden change.

[0112] Therefore, the data processing method for the operating parameters of the air conditioning unit in this application can remove data of the air conditioning unit in a sudden state, and thus calculate the performance of the air conditioning unit based on the operating parameters of the air conditioning unit in a steady state, thereby making the calculation results more accurate.

[0113] It should be noted that although this application uses compressor frequency data, fan speed data, and expansion valve opening data as internal parameters, and ambient temperature data, outlet water temperature data, cooling capacity data, water flow rate data, and COP data as external parameters, in other embodiments, the internal parameters are not limited to compressor frequency, fan speed, and expansion valve opening, and the external parameters are not limited to ambient temperature, outlet water temperature, cooling capacity, water flow rate, and COP. Furthermore, the control device 104 can collect at least one internal parameter or at least one external parameter to perform data processing of the operating parameters of the air conditioning unit 102.

[0114] Although only some features of this application have been illustrated and described herein, many modifications and variations will be apparent to those skilled in the art. Therefore, it should be understood that the appended claims are intended to cover all such modifications and variations that fall within the essential spirit and scope of this application.

Claims

1. A method for processing data of operating parameters of an air conditioning unit, characterized in that, The processing method includes the following steps: For each air conditioner operating parameter, several consecutive data points are acquired over a period of time. These consecutive data points constitute a data sequence, and each data point in the data sequence corresponds to a point in time. The air conditioner operating parameters are determined to be internal or external parameters; Calculate the stability of the air conditioner operating parameters at least at a portion of the time points; Based on the stability of the data according to the internal parameters and / or the stability of the data according to the external parameters, data that needs to be removed from the several consecutive data sets is selected. The process of filtering the data to be removed from the several consecutive data sets based on the stability of the data according to the external parameters includes: Compare the stability of various external parameters and their external stability limits at the same time point; and When the stability of at least one of the external parameters is less than the external stability limit, the data of each external parameter at the same time point are removed. The process of filtering data to be removed from a set of consecutive data based on the stability of the internal parameters includes: The stability of the computer group is determined by the stability of the data of various internal parameters at the same point in time and the weighting coefficients of various internal parameters. Compare the unit's internal stability with its internal stability limit; and When the internal stability of the unit is less than the internal stability limit, the data of various internal parameters at the same time point are removed. The internal parameters include at least one of compressor frequency data, fan speed data, and expansion valve opening data, while the external parameters include at least one of ambient temperature data, outlet water temperature data, cooling capacity data, water flow rate data, and COP data.

2. The method for processing data of operating parameters of an air conditioning unit as described in claim 1, characterized in that, The stability of the data for at least a portion of the time points of the air conditioner operating parameters is calculated, including: Select a data sequence corresponding to at least one air conditioning operating parameter from several data sequences; Following the chronological order, starting with several consecutive data points, n consecutive data points are selected as a window to form several sliding windows, where n < m, n is a positive odd number, and the several consecutive data points are m consecutive data points; For each air conditioning operating parameter in each sliding window, calculate the stability of the data located in the middle of the data in that sliding window, where the stability of the data located in the middle of the data is correlated with the other data in its sliding window.

3. The method for processing data of operating parameters of an air conditioning unit as described in claim 2, characterized in that, Selecting n consecutive data points as a window includes: The length of n consecutive data points is determined based on the time length of COP data changes under the data changes of compressor frequency.

4. The method for processing data of operating parameters of an air conditioning unit as described in claim 2, characterized in that, Calculating the stability of the data located in the middle of the sliding window includes: data stability ; Where the range of values ​​for k is: k=0,1,2,…,n-1; i The range of values ​​for is: .

5. The method for processing data of operating parameters of an air conditioning unit as described in claim 1, characterized in that: The stability of the unit is calculated based on the weights of each data point among the compressor frequency data, fan speed data, and expansion valve opening data.

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