An air conditioner ventilation state diagnosis method, device, air conditioner, equipment, medium and program

Abstract

The present disclosure relates to an air conditioner ventilation state diagnosis method and device, an air conditioner, equipment, a medium and a program, and relates to the technical field of model prediction. The method comprises: collecting air conditioner operating parameters; predicting the air conditioner operating parameters through an air conditioner ventilation state prediction model to determine an air conditioner ventilation state diagnosis result. The air conditioner ventilation state diagnosis result is determined based on indoor pipe temperature prediction information and / or indoor unit overheating degree prediction information. According to the present disclosure, the air conditioner operating parameters are predicted through the air conditioner ventilation state prediction model to determine the air conditioner ventilation state diagnosis result, which realizes timely detection, prediction or diagnosis of the air conditioner ventilation state, improves the reliability and response rate of air conditioner ventilation state recognition, and enhances the overall reliability and operation stability of the equipment.

Description

Technical Field

[0001] This disclosure relates to the field of model prediction technology, and more specifically, to a method, apparatus, air conditioner, equipment, medium, and procedure for diagnosing the condition of air conditioning ventilation. Background Technology

[0002] In related technologies, residential multi-split air conditioners adopt a pre-installation model. The process covers construction preparation, indoor and outdoor unit positioning (ensuring adequate ventilation space for the indoor units), piping / electrical installation, and system commissioning. Furthermore, it requires coordination with civil engineering / plumbing and electrical work. Therefore, the installation quality of residential multi-split air conditioners is affected by two factors: firstly, the compliance of air conditioning construction standards (including indoor unit airflow organization design); and secondly, the potential for subsequent work to damage pipes or obstruct indoor unit ventilation openings. If the indoor unit ventilation is obstructed after installation, it will lead to reduced cooling and heating capacity, abnormal noise, or even system malfunctions. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides a method, apparatus, air conditioner, equipment, medium, and procedure for diagnosing the air conditioning ventilation status.

[0004] According to a first aspect of the present disclosure, a method for diagnosing the air conditioning ventilation status is provided, comprising: Collect air conditioner operating parameters; The air conditioning operating parameters are predicted using an air conditioning ventilation status prediction model to determine the air conditioning ventilation status diagnosis result. The air conditioning ventilation status diagnosis result is determined based on the predicted information of the inner pipe temperature and / or the predicted information of the indoor unit superheat.

[0005] In one exemplary embodiment of this disclosure, the method for training the air conditioning ventilation state prediction model includes: Construct a test environment for the air conditioning ventilation status prediction model; In the test environment, the historical operating data sample is input into the air conditioning ventilation status prediction model, and the prediction information output by the air conditioning ventilation status prediction model is obtained; The predicted information is compared with the corresponding air conditioning ventilation status label to adjust the parameters of the air conditioning ventilation status prediction model.

[0006] In one exemplary embodiment of this disclosure, the method for obtaining the historical operational data sample includes: Collect at least one set of sample data corresponding to the air conditioner operating parameters; Determine the actual air conditioning and ventilation status corresponding to the sample data; Based on the actual air conditioning and ventilation status, each group of sample data is labeled to obtain historical operating data samples labeled with air conditioning and ventilation status tags, which include good ventilation and / or poor ventilation.

[0007] In an exemplary embodiment of this disclosure, the air conditioning ventilation status prediction model includes an inner pipe temperature prediction model, and the prediction information includes inner pipe temperature prediction information. The method of prediction using the inner pipe temperature prediction model includes: A first operating parameter is determined from the air conditioning operating parameters, and the first operating parameter is related to the inner pipe temperature prediction information; The first operating parameter is predicted using the inner tube temperature prediction model to obtain inner tube temperature prediction information.

[0008] In one exemplary embodiment of this disclosure, the first operating parameter includes at least one of the following: compressor operating frequency, exhaust temperature, exhaust superheat, outdoor ambient temperature, outer pipe midpoint temperature, average evaporator inlet temperature, and average evaporator outlet temperature.

[0009] In an exemplary embodiment of this disclosure, the air conditioning ventilation status prediction model includes an indoor unit overheat prediction model, the prediction information includes indoor unit overheat prediction information, and the prediction using the indoor unit overheat prediction model further includes: Determine a second operating parameter among the air conditioning operating parameters, the second operating parameter being related to the indoor unit superheat prediction information; The second operating parameter is predicted using the indoor unit overheating prediction model to obtain indoor unit overheating prediction information.

[0010] In one exemplary embodiment of this disclosure, the second operating parameter includes at least one of the following: average indoor ambient temperature, average evaporator inlet temperature, average evaporator intermediate temperature, and average evaporator outlet temperature.

[0011] In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status includes: The measured information and preset tolerance value of the air conditioner are obtained. The measured information includes the measured information of the inner pipe temperature and / or the measured information of the indoor unit superheat. The preset tolerance value is the preset difference between the predicted information and the measured information. The predicted information includes the predicted information of the inner pipe temperature and / or the predicted information of the indoor unit superheat. Based on the predicted information, the measured information, and the preset tolerance value, the diagnostic result of the air conditioning ventilation status is obtained.

[0012] In an exemplary embodiment of this disclosure, the determination result of the ventilation state is either a first ventilation state or a second ventilation state, wherein the wind speed in the first ventilation state is lower than the wind speed in the second ventilation state, and the method for determining the diagnostic result of the air conditioning ventilation state includes: Determine the proportion of the air conditioning operating parameters under the first ventilation state in the target operating parameters, wherein the target operating parameters include the air conditioning operating parameters under the first ventilation state and the air conditioning operating parameters under the second ventilation state; The diagnostic result of the air conditioning ventilation status is determined based on the relationship between the stated proportion and the preset proportion.

[0013] In one exemplary embodiment of this disclosure, the method for determining the proportion includes: Determine the proportion of the first operating parameter under the first ventilation state in the target first operating parameter, wherein the target first operating parameter includes the first operating parameter under the first ventilation state and the first operating parameter under the second ventilation state; And / or, determine the proportion of the second operating parameter in the first ventilation state in the target second operating parameter, wherein the target second operating parameter includes the second operating parameter in the first ventilation state and the second operating parameter in the second ventilation state.

[0014] In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status includes: The diagnostic result of the air conditioning ventilation status is determined based on the proportion of the first operating parameter under the first ventilation state and / or the proportion of the second operating parameter under the first ventilation state.

[0015] In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status includes: In response to the acquired prediction information, the prediction information is corrected based on the indoor unit vent installation information; Based on the correction results of the predicted information, the diagnostic result of the air conditioning ventilation status is determined.

[0016] In one exemplary embodiment of this disclosure, the modification is performed in the following ways: Determine the correction factor corresponding to the indoor unit air vent installation information; The prediction information is corrected based on the correction coefficient.

[0017] In an exemplary embodiment of this disclosure, correcting the prediction information according to the correction coefficient specifically includes: At least one of the correction coefficients is weighted and summed according to preset weights; The prediction information is corrected based on the weighted summation result.

[0018] In an exemplary embodiment of this disclosure, the indoor unit air vent installation information includes at least one of the following: return air method, return air vent extension pipe installation information, and louver installation information, wherein the return air method includes bottom return air and / or rear return air.

[0019] In an exemplary embodiment of this disclosure, the correction coefficient includes at least one of the following: the correction coefficient corresponding to the return air method, the correction coefficient corresponding to the extension pipe installation information of the return air vent, and the correction coefficient corresponding to the louver installation information of the return air vent.

[0020] In one exemplary embodiment of this disclosure, before obtaining the prediction information, the method further includes: Obtain the basic parameters of the air conditioner, including indoor unit platform parameter information and / or indoor unit return air vent installation information; In response to the fact that the basic parameters fall within the preset parameter range, a running command is sent to the outdoor unit. And / or, in response to the basic parameter not being within the preset parameter range, or the basic parameter being incorrect, or the basic parameter being missing, send an input prompt for the basic parameter, and / or switch to the input interface corresponding to the basic parameter.

[0021] In one exemplary embodiment of this disclosure, the indoor unit platform parameter information includes at least one of the following: indoor unit model parameters, indoor unit fan model parameters, and indoor unit driver version.

[0022] In one exemplary embodiment of this disclosure, before obtaining the basic parameters of the air conditioner, the method further includes: The air conditioner unit components are reset, including the components of the indoor unit and / or the components of the outdoor unit.

[0023] In one exemplary embodiment of this disclosure, the reset operation includes the following methods: Perform a power-off operation on the air conditioner and time the duration of the power-off. In response to the power outage duration reaching the preset power outage duration, the air conditioner is powered on; In response to the air conditioner being powered on, the standby status parameters of the air conditioner are detected to determine whether they fall within the preset standby parameter range. In response to the standby state parameter falling within the preset standby parameter range, the reset operation is determined to be completed.

[0024] In an exemplary embodiment of this disclosure, the standby state parameters include at least one of the following: outer tube outlet temperature, outdoor ambient temperature, outer tube correction temperature, average inner tube temperature, average indoor ambient temperature, and inner tube correction temperature.

[0025] In one exemplary embodiment of this disclosure, the method for collecting the air conditioner operating parameters includes: Determine the cumulative operating time of the air conditioner; In response to the cumulative working time reaching a first preset time, the air conditioner operating parameters are collected.

[0026] In an exemplary embodiment of this disclosure, collecting the air conditioner operating parameters specifically includes: At least one set of the air conditioner operating parameters is collected at preset time intervals until the number of sets of air conditioner operating parameters reaches the preset number.

[0027] In one exemplary embodiment of this disclosure, the method of stopping the collection of the air conditioner operating parameters includes: The cumulative collection time for the air conditioner operating parameters; In response to the cumulative collection time reaching a second preset time, the collection of the air conditioner operating parameters is stopped.

[0028] In one exemplary embodiment of this disclosure, before collecting the air conditioner operating parameters, the method further includes: Send an operating command to the outdoor unit of the air conditioner; In response to the operation of the outdoor unit, a start-up command is sent to the indoor unit of the air conditioner; In response to the indoor unit being turned on, a target operating parameter command is sent to the indoor unit, the target operating parameter command including the target indoor ambient temperature and / or the target fan speed setting.

[0029] In one exemplary embodiment of this disclosure, after obtaining the air conditioning ventilation status diagnostic result, the method further includes: The diagnostic results of the air conditioning ventilation status are fed back to the client and / or server, and / or a shutdown command is executed on the air conditioner.

[0030] According to a second aspect of the present disclosure, an air conditioning ventilation status diagnostic device is provided, the air conditioning ventilation status diagnostic device being used to perform the method described in any of the above technical solutions, the air conditioning ventilation status diagnostic device comprising: The data acquisition module is configured to collect air conditioner operating parameters; The status diagnosis module is configured to predict the air conditioning operating parameters through an air conditioning ventilation status prediction model to determine the air conditioning ventilation status diagnosis result. The air conditioning ventilation status diagnosis result is determined based on the indoor pipe temperature prediction information and / or the indoor unit superheat prediction information.

[0031] According to a third aspect of the present disclosure, an air conditioner is provided, comprising: The processor is configured to perform the air conditioning ventilation status diagnosis method as described in any of the above technical solutions.

[0032] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to: implement the air conditioning ventilation status diagnosis method as described in any of the foregoing technical solutions.

[0033] According to a fifth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, which, when the instructions in the storage medium are executed by a processor of a mobile terminal, enables the mobile terminal to perform the air conditioning ventilation status diagnosis method as described in any of the above technical solutions.

[0034] According to a sixth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the air conditioning ventilation status diagnosis method as described in any of the above technical solutions.

[0035] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects: The embodiments of this disclosure predict the air conditioning operating parameters using an air conditioning ventilation status prediction model to determine the air conditioning ventilation status diagnosis results. Based on the air conditioning ventilation status diagnosis results, it is determined whether there is ventilation obstruction or poor ventilation, especially in the initial operation phase after installation, to determine whether there is ventilation obstruction or poor ventilation in all indoor units. This enables timely detection, prediction, or diagnosis of the air conditioning ventilation status, improves the reliability and response rate of air conditioning ventilation status identification, and enhances the overall reliability and operational stability of the equipment.

[0036] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0038] Figure 1 This is a schematic diagram illustrating an air conditioning ventilation status diagnosis method according to an exemplary embodiment of the present disclosure.

[0039] Figure 2 This is a schematic diagram illustrating an air conditioning ventilation status diagnosis scheme according to an exemplary embodiment of the present disclosure.

[0040] Figure 3 This is a schematic diagram illustrating an air conditioning ventilation status diagnosis scheme according to another exemplary embodiment of the present disclosure.

[0041] Figure 4 This is a schematic diagram illustrating predicted, measured, and average information of the inner tube temperature according to an exemplary embodiment of the present disclosure.

[0042] Figure 5 This is a schematic diagram illustrating predicted, measured, and average information of indoor unit overheating according to an exemplary embodiment of this disclosure.

[0043] Figure 6 This is a block diagram illustrating an air conditioning ventilation status diagnostic device according to an exemplary embodiment of the present disclosure.

[0044] Figure 7 This is a block diagram illustrating an air conditioner according to an exemplary embodiment of the present disclosure.

[0045] Figure 8 This is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0046] Exemplary embodiments of this disclosure will be described in detail herein, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. Various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but can be changed as will become apparent upon understanding this disclosure, except for operations that must be performed in a particular order. Furthermore, for clarity and brevity, descriptions of features known in the art may be omitted.

[0047] The embodiments described below, which are some of the embodiments of this disclosure, do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0048] In related technologies, the installation process of air conditioners involves steps such as construction preparation, indoor unit installation, outdoor unit installation, piping installation, electrical installation, and system debugging. If the air conditioner is installed during the interior decoration phase, it also involves civil engineering, water and electricity, and piping engineering. The complex installation steps and engineering processes may cause some construction debris to fall into the air conditioner's indoor unit, leading to obstructed ventilation or fan malfunction. This can result in poor cooling / heating performance, abnormal noise, vibration, and machine malfunctions, among other adverse effects. Therefore, there is an urgent need for a highly accurate method for identifying the ventilation status of air conditioners.

[0049] The steps of the method in the exemplary embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings and examples.

[0050] Figure 1 This is a schematic diagram illustrating an air conditioning ventilation status diagnosis method according to an exemplary embodiment of the present disclosure.

[0051] like Figure 1 As shown, in some embodiments, an air conditioning ventilation status diagnosis method is provided, including: Step S102: Collect air conditioner operating parameters.

[0052] In an exemplary embodiment of this disclosure, the object of data collection can be a wall-mounted air conditioner, a floor-standing air conditioner, or a residential multi-split air conditioner. The residential multi-split air conditioner includes multiple indoor units and one outdoor unit. Air conditioner operating parameters are collected for each indoor unit and outdoor unit. The collected air conditioner operating parameters can be stored separately according to the identifiers of the indoor and outdoor units. Based on the air conditioner operating parameters, it is possible to accurately determine which indoor unit has obstructed ventilation, poor ventilation, or fan failure. This helps improve the reliability and accuracy of the air conditioner ventilation status diagnosis scheme and facilitates after-sales maintenance personnel to quickly identify the faulty indoor unit for troubleshooting and repair.

[0053] In an exemplary embodiment of this disclosure, the time period for data collection may be the initial operation phase after the air conditioner is installed, or a preset equipment maintenance phase, fault detection phase, or periodic detection phase. Alternatively, the air conditioner operating parameters may be collected in real time according to the user's instructions.

[0054] In an exemplary embodiment of this disclosure, the collected air conditioning operating parameters can be stored locally or uploaded to a cloud server. They can be used not only for predicting the air conditioning ventilation status but also as a training model for the training phase of the air conditioning ventilation status prediction model.

[0055] Step S104: The air conditioning operating parameters are predicted using the air conditioning ventilation status prediction model to determine the air conditioning ventilation status diagnosis result. The air conditioning ventilation status diagnosis result is determined based on the indoor pipe temperature prediction information and / or the indoor unit superheat prediction information.

[0056] In an exemplary embodiment of this disclosure, before applying the air conditioning ventilation status prediction model, the model is trained using samples of air conditioning operating parameters. This allows the model to learn the correspondence between air conditioning operating parameters and air conditioning ventilation status diagnostic results. By inputting the air conditioning operating parameters into the air conditioning ventilation status prediction model, the model can predict and process the air conditioning ventilation status diagnostic results. This enables timely detection and prediction of whether the air conditioning ventilation status is abnormal, especially during the initial operation phase after air conditioning installation. Based on the indoor unit overheating prediction information and / or indoor pipe temperature prediction information output by the air conditioning ventilation status prediction model, it is possible to accurately detect whether any indoor unit of the air conditioner has poor ventilation or ventilation issues. This helps reduce adverse effects such as poor cooling / heating performance, abnormal noise, vibration, and operational malfunctions of the air conditioner, and can significantly improve the stability, reliability, energy efficiency, and temperature control effect of the air conditioner.

[0057] In one exemplary embodiment of this disclosure, the prediction information output by the air conditioning ventilation state prediction model may only include the prediction information of the inner pipe temperature, or only the prediction information of the indoor unit superheat, or may include both the prediction information of the inner pipe temperature and the prediction information of the indoor unit superheat, but is not limited thereto.

[0058] In an exemplary embodiment of this disclosure, after the air conditioning ventilation status prediction model outputs the predicted information of the inner pipe temperature and / or the predicted information of the indoor unit overheating, the air conditioning ventilation status diagnosis result is further determined comprehensively based on the predicted information of the inner pipe temperature and / or the predicted information of the indoor unit overheating.

[0059] In one exemplary embodiment of this disclosure, the method for training the air conditioning ventilation state prediction model includes: Construct a test environment for the air conditioning ventilation status prediction model; In the test environment, the historical operating data sample is input into the air conditioning ventilation status prediction model, and the prediction information output by the air conditioning ventilation status prediction model is obtained; The predicted information is compared with the corresponding air conditioning ventilation status label to adjust the parameters of the air conditioning ventilation status prediction model.

[0060] In an exemplary embodiment of this disclosure, the air conditioning ventilation status prediction model is trained using historical operating data samples, and the parameters of the air conditioning ventilation status prediction model are optimized, which greatly improves the accuracy and reliability of air conditioning ventilation status prediction. Through continuous data-driven optimization, the model can more sensitively capture subtle abnormal features of system operation, thereby effectively avoiding serious failures such as compressor damage, significantly reducing operation and maintenance costs, and ensuring the continuous, efficient and stable operation of the system.

[0061] In one exemplary embodiment of this disclosure, the method for obtaining the historical operational data sample includes: Collect at least one set of sample data corresponding to the air conditioner operating parameters; Determine the actual air conditioning and ventilation status corresponding to the sample data; Based on the actual air conditioning and ventilation status, each group of sample data is labeled to obtain historical operating data samples labeled with air conditioning and ventilation status tags, which include good ventilation and / or poor ventilation.

[0062] In an exemplary embodiment of this disclosure, historical operating data samples are labeled with air conditioning ventilation status tags, that is, the air conditioning ventilation status corresponding to any historical operating data sample is preset. The actual air conditioning ventilation status may include normal air volume, slightly reduced air volume, moderately reduced air volume, and severely insufficient air volume, but is not limited to these. Finally, the accuracy of the prediction information is verified by the air conditioning ventilation status tags.

[0063] In an exemplary embodiment of this disclosure, the air conditioning ventilation status prediction model includes an inner pipe temperature prediction model, and the prediction information includes inner pipe temperature prediction information. The prediction method includes: A first operating parameter is determined from the air conditioning operating parameters, and the first operating parameter is related to the predicted temperature of the inner pipe.

[0064] In an exemplary embodiment of this disclosure, when the indoor unit's ventilation volume decreases, the evaporator temperature will change accordingly, and in severe cases, frost will form. Based on this, by acquiring a first operating parameter related to the indoor pipe temperature prediction information, the indoor pipe temperature prediction information is predicted based on the first operating parameter. That is, the indoor pipe temperature prediction information is used to indirectly determine whether any indoor unit has poor ventilation or an indoor unit malfunction.

[0065] In one exemplary embodiment of this disclosure, the prediction method further includes: The first operating parameter is predicted using the inner tube temperature prediction model to obtain inner tube temperature prediction information.

[0066] In one exemplary embodiment of this disclosure, the inner tube temperature prediction information includes predicting and evaluating the intermediate tube temperature of the evaporator. T 预测评价蒸发器中间管温 For the specific calculation process, please refer to formula (1): , formula (1) In an exemplary embodiment of this disclosure, the first operating parameter involved in formula (1) specifically includes the compressor operating frequency. f 压缩机频率 Exhaust temperature T 排气 Exhaust superheat T 排气过热度 Outdoor ambient temperature T 外环 Temperature at the midpoint of the outer tube T 外管中点温 Average evaporator inlet temperature T 平均蒸发器进口管温 and average evaporator outlet temperature T 平均蒸发器出口管温 .

[0067] In an exemplary embodiment of this disclosure, the definitions and value ranges of the first operating parameter and the preset coefficient involved in formula (1) are as follows: T 预测评价蒸发器中间管温 : Using γ min as the time interval, from the cumulative duration twork (twork = β min) of the air conditioner's ventilation status diagnostic mode to the cumulative duration toff (toff = α min) of the air conditioner's ventilation status diagnostic mode, the predicted value of the evaporator intermediate pipe temperature of the air conditioner is tested, with the unit being ℃.

[0068] a: T 预测评价蒸发器中间管温 The constant term.

[0069] In one exemplary embodiment of this disclosure, the preferred value of a is in the range of 0.2 to 0.7.

[0070] b: Diagnostic model for ventilation status of residential multi-split air conditioning systems f 压缩机频率 The correction factor.

[0071] In an exemplary embodiment of this disclosure, the preferred value range of b is -0.001 to -0.010.

[0072] c: Prediction model for the average intermediate pipe temperature of the indoor unit evaporator of a residential multi-split air conditioner. T 排气 The correction factor.

[0073] In one exemplary embodiment of this disclosure, the preferred value of c is in the range of 0.10 to 0.5.

[0074] d: Predictive model for the average intermediate pipe temperature of the indoor unit evaporator of a residential multi-split air conditioner. T 排气过热度 The correction factor.

[0075] In an exemplary embodiment of this disclosure, the preferred value range of d is -0.01 to -0.10.

[0076] e: Predictive model for the average intermediate pipe temperature of the indoor unit evaporator of a residential multi-split air conditioner. T 外环 The correction factor.

[0077] In one exemplary embodiment of this disclosure, the preferred value range of e is -0.05 to -0.20.

[0078] g: Prediction model for the average intermediate pipe temperature of the indoor unit evaporator of a residential multi-split air conditioner. T 外管中点温 The correction factor.

[0079] In one exemplary embodiment of this disclosure, the preferred value of g is in the range of -0.05 to -0.15.

[0080] h: Predictive model for the average intermediate pipe temperature of the indoor unit evaporator of a residential multi-split air conditioner. T 平均蒸发器进口管温 The correction factor.

[0081] In one exemplary embodiment of this disclosure, the preferred value of h is in the range of 0.05 to 0.20.

[0082] j: A predictive model for the average intermediate pipe temperature of the indoor unit evaporator in a residential multi-split air conditioner. T 平均蒸发器出口管温 The correction factor.

[0083] In one exemplary embodiment of this disclosure, the preferred value of j is in the range of 0.50 to 1.50.

[0084] In an exemplary embodiment of this disclosure, the air conditioning ventilation status prediction model includes an indoor unit overheat prediction model, the prediction information includes indoor unit overheat prediction information, and the prediction further includes: A second operating parameter is determined from the air conditioning operating parameters, and the second operating parameter is related to the indoor unit superheat prediction information.

[0085] In an exemplary embodiment of this disclosure, the superheat of the indoor unit also changes accordingly. When the indoor unit's ventilation volume decreases, the reduced ventilation volume (decreased airflow) leads to weakened heat exchange, meaning less air flows through the evaporator (indoor unit), resulting in less heat being carried away and less heat absorption by the refrigerant within the evaporator. Furthermore, this causes an increase in evaporation pressure / temperature, leading to insufficient refrigerant heat absorption, increased refrigerant temperature within the evaporator, and consequently, increased evaporation pressure and corresponding saturation temperature. In extreme cases (severely insufficient airflow), if the indoor unit's airflow is too small, the refrigerant cannot fully absorb heat for evaporation, and the outlet may still be in a liquid or gas-liquid mixture. In this case, the superheat becomes very low (close to 0 or even negative), which can lead to a risk of compressor liquid slugging and severe damage to the compressor. Based on this, by acquiring a second operating parameter related to the indoor unit's superheat prediction information, the indoor unit's superheat prediction information is predicted based on the second operating parameter. That is, the indoor unit's superheat prediction information is used to indirectly determine whether any indoor unit has poor ventilation or a malfunction.

[0086] In one exemplary embodiment of this disclosure, the prediction process further includes: The second operating parameter is predicted using the indoor unit overheating prediction model to obtain indoor unit overheating prediction information.

[0087] In one exemplary embodiment of this disclosure, the indoor unit superheat prediction information includes predicting and evaluating the evaporator superheat. T 预测平均蒸发器过热度 For the specific calculation process, please refer to formula (2): , formula (2) In one exemplary embodiment of this disclosure, the second operating parameter includes at least one of the following: average indoor ambient temperature, average evaporator inlet temperature, average evaporator intermediate temperature, and average evaporator outlet temperature.

[0088] In an exemplary embodiment of this disclosure, the second operating parameter involved in formula (2) specifically includes the average indoor ambient temperature. T 平均内环温 Average evaporator intermediate temperature T 平均蒸发器中间管温 Average evaporator inlet temperature T 平均蒸发器进口管温 and average evaporator outlet temperature T 平均蒸发器出口管温 .

[0089] In an exemplary embodiment of this disclosure, the definition and value range of the second operating parameter involved in formula (2) are as follows: T 预测平均蒸发器过热度The data set of the predicted average superheat of the evaporator of the air conditioner is calculated based on the air conditioning operating parameters collected at time intervals of γ min. It starts from the cumulative duration twork (twork = β min) of the air conditioner operating in the air conditioning ventilation state test mode, and ends at the cumulative duration tooff (toff = α min) of the air conditioner operating in the residential multi-split air conditioning ventilation state diagnosis mode. The unit of the data set is ℃.

[0090] k: T 预测平均蒸发器过热度 The constant term.

[0091] In one exemplary embodiment of this disclosure, the preferred value of k is in the range of 0.05 to 0.15.

[0092] n: A predictive model for the average superheat of the indoor unit evaporator in a residential multi-split air conditioner. T 平均内环温 The correction factor.

[0093] In one exemplary embodiment of this disclosure, the preferred value of n is in the range of 0.005 to -0.020.

[0094] m: A predictive model for the average superheat of the indoor unit evaporator in a residential multi-split air conditioner. T 平均蒸发器进口管温 The correction factor.

[0095] In one exemplary embodiment of this disclosure, the preferred value of m is in the range of -0.05 to -1.5.

[0096] p: A predictive model for the average superheat of the indoor unit evaporator in a residential multi-split air conditioner. T 平均蒸发器中间管温 The correction factor.

[0097] In one exemplary embodiment of this disclosure, the preferred value of p is in the range of -0.08 to -0.20.

[0098] Q: A predictive model for the average superheat of the indoor unit evaporator in a residential multi-split air conditioner. T 平均蒸发器出口管温 The correction factor.

[0099] In an exemplary embodiment of this disclosure, the preferred value of q is in the range of 0.50 to 1.50.

[0100] In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status includes: The measured information and preset tolerance value of the air conditioner are obtained. The measured information includes the measured information of the inner pipe temperature and / or the measured information of the indoor unit superheat. The preset tolerance value is the preset difference between the predicted information and the measured information. The predicted information includes the predicted information of the inner pipe temperature and / or the predicted information of the indoor unit superheat.

[0101] In one exemplary embodiment of this disclosure, the preset tolerance value includes a preset difference in the inner tube temperature and / or a preset difference in the indoor unit superheat.

[0102] In one exemplary embodiment of this disclosure, calculating the difference between predicted information and measured information includes calculating the difference between measured information of the inner tube temperature and predicted information of the inner tube temperature, and / or calculating the difference between measured information of the indoor unit superheat and predicted information of the indoor unit superheat.

[0103] In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status includes: Based on the predicted information, the measured information, and the preset tolerance value, the diagnostic result of the air conditioning ventilation status is obtained.

[0104] In one exemplary embodiment of this disclosure, such as Figure 4 As shown in Figure 400, the error analysis of the inner pipe temperature prediction model shows that the range of the preset tolerance value is determined based on the upper limit curve and the lower limit curve of the prediction curve error. The average evaporator intermediate pipe temperature prediction curve is determined based on the predicted average evaporator intermediate pipe temperature value. Then, the air conditioning ventilation status diagnosis result is obtained based on whether the average evaporator intermediate pipe temperature prediction curve belongs to the range of the preset tolerance value.

[0105] In one exemplary embodiment of this disclosure, such as Figure 5 As shown in the figure, the error analysis of the indoor unit overheating prediction model 500 shows that the range of the preset tolerance value is determined based on the upper limit curve of the prediction curve error and the lower limit curve of the prediction curve error. The average indoor unit overheating prediction curve is determined based on the predicted average indoor unit overheating value. Then, the air conditioning ventilation status diagnosis result is obtained according to whether the average indoor unit overheating prediction curve belongs to the range of the preset tolerance value.

[0106] In an exemplary embodiment of this disclosure, the measured information and preset tolerance value of the air conditioner are obtained, and the difference between the measured information and the predicted information is calculated. Then, the difference is compared with the corresponding preset tolerance value. If the difference exceeds the preset tolerance value, it can be determined that the ventilation is poor (poor ventilation of the indoor unit or obstructed ventilation). Otherwise, it can be determined that the ventilation is good. The air conditioner ventilation status corresponding to the predicted information is determined based on the comparison result.

[0107] In an exemplary embodiment of this disclosure, the indoor unit ventilation is determined based on the predicted information, measured information and preset tolerance value corresponding to the intermediate pipe temperature of the evaporator, as detailed in Table 1 below.

[0108] In an exemplary embodiment of this disclosure, the indoor unit ventilation is determined based on the predicted information, measured information and preset tolerance value corresponding to the evaporator superheat, as detailed in Table 2 below.

[0109] Table 1

[0110] In one exemplary embodiment of this disclosure, T 平均蒸发器中间管温对应的预设容差值 The preferred value range is -3℃ to -8℃.

[0111] Table 2

[0112] In one exemplary embodiment of this disclosure, T 平均蒸发器过热度对应的预设容差值 The preferred value range is -2℃ to -6℃.

[0113] In an exemplary embodiment of this disclosure, the determination result of the ventilation state is either a first ventilation state or a second ventilation state, wherein the wind speed in the first ventilation state is lower than the wind speed in the second ventilation state, and the method for determining the diagnostic result of the air conditioning ventilation state includes: Determine the proportion of the air conditioning operating parameters under the first ventilation state in the target operating parameters, wherein the target operating parameters include the air conditioning operating parameters under the first ventilation state and the air conditioning operating parameters under the second ventilation state.

[0114] In an exemplary embodiment of this disclosure, the wind speed in the second ventilation state is the wind speed in the normal ventilation state of the air conditioner indoor unit, and the wind speed in the first ventilation state is the wind speed in the state of poor ventilation or obstructed ventilation of the air conditioner indoor unit. The air conditioner ventilation state diagnosis result is determined according to the relationship between the ratio and the preset ratio. That is, based on the ratio statistics and ratio comparison, the unreliability of single or one-time prediction information is reduced, which reduces the adverse impact on the reliability of the air conditioner ventilation state diagnosis result.

[0115] In one exemplary embodiment of this disclosure, M groups are collected under the second ventilation state. T 预测平均蒸发器中间管温 and T 预测平均蒸发器过热度 To determine the air conditioning ventilation status, we need to perform percentage statistics and comparisons. The value of M can be 10, 20, 30, 40, 50, etc., but is not limited to these.

[0116] In one exemplary embodiment of this disclosure, the method for determining the proportion includes: Determine the proportion of the first operating parameter under the first ventilation state in the target first operating parameter, wherein the target first operating parameter includes the first operating parameter under the first ventilation state and the first operating parameter under the second ventilation state.

[0117] In an exemplary embodiment of this disclosure, by determining the proportion of the first operating parameter under the first ventilation state in the target first operating parameter, that is, determining the proportion of the first operating parameter corresponding to poor indoor unit ventilation or obstructed indoor unit ventilation in the target first operating parameter, the target first operating parameter may be the original dataset of the first operating parameter, or may only include the first operating parameter under the first ventilation state and the first operating parameter under the second ventilation state. The proportion of effective parameters in the target first operating parameter is significantly higher than that in the original dataset, which is beneficial to further improve the reliability and accuracy of the proportion.

[0118] In one exemplary embodiment of this disclosure, the method for determining the proportion further includes: Determine the proportion of the second operating parameter under the first ventilation state in the target second operating parameter, wherein the target second operating parameter includes the second operating parameter under the first ventilation state and the second operating parameter under the second ventilation state.

[0119] In an exemplary embodiment of this disclosure, the percentage determination result corresponding to the average intermediate pipe temperature of the indoor unit evaporator is calculated using formula (3): , formula (3) In an exemplary embodiment of this disclosure, the percentage of the average superheat of the indoor unit evaporator is determined by calculation process as shown in formula (4): , formula (4) In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status includes: The diagnostic result of the air conditioning ventilation status is determined based on the proportion of the first operating parameter under the first ventilation state and / or the proportion of the second operating parameter under the first ventilation state.

[0120] In one exemplary embodiment of this disclosure, when θ 内机蒸发器平均中间管温预测模型_通风不佳占比 ≥ θ 内机蒸发器平均中间管温预测模型_通风不佳占比阈值 When the average intermediate pipe temperature of the indoor unit evaporator is determined, the diagnostic result is "poor ventilation"; otherwise, it is "good ventilation".

[0121] In one exemplary embodiment of this disclosure, when θ 内机蒸发器平均过热度预测模型_通风不佳占比 ≥ θ 内机蒸发器平均过热度预测模型_通风不佳占比阈值 When the average superheat of the indoor unit evaporator is determined, the diagnostic result is "poor ventilation"; otherwise, it is "good ventilation".

[0122] In one exemplary embodiment of this disclosure, for θ 内机蒸发器平均中间管温预测模型_通风不佳占比阈值 The preferred value range is 0.75 ~ 0.85.

[0123] In one exemplary embodiment of this disclosure, for θ 内机蒸发器平均过热度预测模型_通风不佳占比阈值 The preferred value range is 0.60 ~ 0.80.

[0124] In an exemplary embodiment of this disclosure, the method for determining the diagnostic results of the air conditioning ventilation status is shown in Table 3 below.

[0125] Table 3

[0126] In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status includes: In response to the acquired prediction information, the prediction information is corrected based on the indoor unit vent installation information.

[0127] In an exemplary embodiment of this disclosure, the indoor unit air vent installation information is directly related to the ventilation volume under normal air conditioning operation. Based on this, the predicted information is corrected by combining the indoor unit air vent installation information, so that the air conditioning ventilation status diagnosis scheme of this disclosure is applicable to air conditioners under various indoor unit air vent installation information. This not only expands the robustness, accuracy and reliability of the scheme of this disclosure, but also broadens the applicable scenarios of the scheme.

[0128] In one exemplary embodiment of this disclosure, the method for determining the diagnostic result of the air conditioning ventilation status further includes: Based on the correction results of the predicted information, the diagnostic result of the air conditioning ventilation status is determined.

[0129] In an exemplary embodiment of this disclosure, the correction result of the prediction information may be the correction result of the inner pipe temperature prediction information, and the air conditioning ventilation status diagnosis result is determined based on the correction result of the inner pipe temperature prediction information.

[0130] In an exemplary embodiment of this disclosure, the correction result of the prediction information may be the correction result of the indoor unit overheat prediction information, and the air conditioning ventilation status diagnosis result is determined based on the correction result of the indoor unit overheat prediction information.

[0131] In an exemplary embodiment of this disclosure, the correction result of the prediction information may be the correction result of the indoor pipe temperature prediction information and the correction result of the indoor unit overheating prediction information. The air conditioning ventilation status diagnosis result is determined based on the correction result of the indoor pipe temperature prediction information and the correction result of the indoor unit overheating prediction information.

[0132] In one exemplary embodiment of this disclosure, the modification is performed in the following ways: Determine the correction coefficient corresponding to the indoor unit air vent installation information; correct the predicted information according to the correction coefficient. Specifically, correct the calculation results by inputting parameters such as return air method (bottom return air, rear return air), whether there is a return air vent extension pipe, and whether the return air vent is equipped with louvers.

[0133] In an exemplary embodiment of this disclosure, the corresponding correction coefficient is determined by inputting parameters such as the return air method (bottom return air, rear return air), whether there is a return air outlet extension pipe, and whether the return air outlet is equipped with louvers. The prediction information is then corrected based on the correction coefficient to improve the accuracy and reliability of the prediction information in various air conditioning installation scenarios.

[0134] In an exemplary embodiment of this disclosure, correcting the prediction information according to the correction coefficient specifically includes: At least one of the correction coefficients is weighted and summed according to preset weights.

[0135] The prediction information is corrected based on the weighted summation result.

[0136] In one exemplary embodiment of this disclosure, the correction for the average intermediate tube temperature of the indoor unit evaporator, T 预测评价蒸发器中间管温 The corrected value. T 预测评价蒸发器中间管温 For the value before correction, refer to the following formula (5): , formula (5) In one exemplary embodiment of this disclosure, the correction for the average superheat of the indoor unit evaporator, T 预测评价蒸发器过热度 The corrected value. T 预测评价蒸发器过热度 For the value before correction, refer to the following formula (6): , formula (6) In an exemplary embodiment of this disclosure, the indoor unit air vent installation information includes at least one of the following: return air method, return air vent extension pipe installation information, and louver installation information, wherein the return air method includes bottom return air and / or rear return air.

[0137] In an exemplary embodiment of this disclosure, by obtaining the above-mentioned indoor unit air vent installation information, on the one hand, it is possible to check whether the air conditioner installation is reliable and complete; on the other hand, it is possible to make targeted corrections to the prediction information based on the indoor unit air vent installation information, so that the air conditioning ventilation status diagnosis scheme of this disclosure is applicable to air conditioners in various installation scenarios, thus expanding the application scenarios and reliability of this scheme.

[0138] In an exemplary embodiment of this disclosure, the correction coefficient includes at least one of the correction coefficient corresponding to the return air method, the correction coefficient corresponding to the extension pipe installation information of the return air vent, and the correction coefficient corresponding to the louver installation information of the return air vent. Specific correction coefficients are shown in Tables 4, 5, and 6.

[0139] Table 4

[0140] Table 5

[0141] Table 6

[0142] In one exemplary embodiment of this disclosure, before obtaining the prediction information, the method further includes: Obtain the basic parameters of the air conditioner, including indoor unit platform parameter information and / or indoor unit return air vent installation information. In response to the basic parameters falling within a preset parameter range, determine to send an operation command to the outdoor unit.

[0143] In an exemplary embodiment of this disclosure, after inputting basic parameters, it is verified whether the basic parameters fall within the preset parameter range. If it is determined that the basic parameters fall within the preset parameter range, the outdoor unit is controlled to start running, thereby improving the stability and reliability of the air conditioner operation.

[0144] In one exemplary embodiment of this disclosure, before obtaining the prediction information, the method further includes: In response to the basic parameter not being within the preset parameter range, or the basic parameter being incorrect, or the basic parameter being missing, an input prompt for the basic parameter is sent, and / or the input interface corresponding to the basic parameter is switched.

[0145] In an exemplary embodiment of this disclosure, if the basic information is not within the preset parameter range, or if the basic parameters are incorrect or missing, the air conditioner may become unstable or report an error. In such cases, prompts and / or switching to the input interface are required to instruct the user to re-enter the basic information, thereby improving the efficiency and reliability of basic information entry.

[0146] In one exemplary embodiment of this disclosure, the indoor unit platform parameter information includes, but is not limited to: indoor unit model parameters, indoor unit fan model parameters, indoor unit driver version, etc.

[0147] In one exemplary embodiment of this disclosure, such as Figure 2 As shown, the ventilation status diagnosis solution applied to residential multi-split air conditioning systems includes: Step S202: Execute the main control program for ventilation diagnosis of the indoor unit of the residential multi-split air conditioner.

[0148] Step S204: Execute the ventilation diagnostic mode for the indoor unit of the residential multi-split air conditioner. In this mode, wait for the collection of air conditioner operating parameters and module prediction processing.

[0149] Step S206: Residential multi-split air conditioning ventilation status diagnosis module, which is used to perform the air conditioning ventilation status diagnosis steps defined in any of the above technical solutions.

[0150] Step S208: Analyze the ventilation status of the residential multi-split air conditioning system and output the ventilation status diagnosis results to a designated terminal, user interface, or server.

[0151] Specifically, after detecting the outdoor unit platform information parameters input / selected by the after-sales technician for testing, step S202 above verifies whether the indoor unit platform information read through the software backend and the outdoor unit platform parameter information input / selected by the after-sales technician are consistent by executing the indoor unit ventilation diagnosis main control program of the residential multi-split air conditioner. If the information is consistent, the information is confirmed to be correct; if the information is inconsistent, the after-sales technician needs to perform a second confirmation.

[0152] In one exemplary embodiment of this disclosure, the indoor unit return air vent installation information includes, but is not limited to: return air method (bottom return air, rear return air), whether there is a return air vent extension pipe, and whether the return air vent is equipped with louvers, etc.

[0153] In one exemplary embodiment of this disclosure, after detecting that the after-sales technician has entered / selected the installation information of the return air vents of each indoor unit of the test air conditioner, it is also necessary to verify the installation information of the return air vents of the indoor unit.

[0154] In an exemplary embodiment of this disclosure, the air conditioner's determination center confirms the input parameter information. When the determination center confirms that the input parameters of the basic parameters of the air conditioner are correct, the determination center feeds back to the preprocessing module, which then sends a "can be turned on and run" prompt.

[0155] In an exemplary embodiment of this disclosure, if the determination center determines that the input parameters of the test air conditioner basic parameter preset module and the test air conditioner installation parameter preset module are missing or incorrect, it issues an input prompt of "Input of test air conditioner basic parameter information not completed" or "Input of test air conditioner installation parameter information not completed" and switches back to the input interface of the corresponding parameter.

[0156] In one exemplary embodiment of this disclosure, the indoor unit platform parameter information includes at least one of the following: indoor unit model parameters, indoor unit fan model parameters, and indoor unit driver version.

[0157] In one exemplary embodiment of this disclosure, by inputting indoor unit platform parameter information, including but not limited to indoor unit model parameters, indoor unit fan model parameters, and indoor unit driver version, an air conditioning ventilation status diagnostic solution for the entire platform is implemented. It is even possible to specify a corresponding air conditioning ventilation status diagnostic solution for each type of air conditioner and / or adjust the preset values ​​and thresholds in the air conditioning ventilation status diagnostic parameters, thereby further improving the reliability, accuracy, and applicability of the air conditioning ventilation status diagnostic solution.

[0158] In one exemplary embodiment of this disclosure, in Figure 2 Based on what is shown, as Figure 3 As shown, the ventilation status diagnosis solution applied to residential multi-split air conditioning systems also includes: Step S302: The main control program for ventilation diagnosis of the indoor unit of the residential multi-split air conditioner is started.

[0159] Step S304: Power on and run.

[0160] Step S306: Enter the residential multi-split air conditioning ventilation status diagnosis mode, and wait for the collection of air conditioning operating parameters and module prediction processing in this mode.

[0161] Step S308: The ventilation status diagnosis module for residential multi-split air conditioning systems is activated.

[0162] Step S310: Control the data processing module to work. The data processing module includes a timing module (including a diagnostic runtime control module and a diagnostic data parameter acquisition control module) and a data acquisition module. The data acquisition module acquires... f 压缩机频率 、 T 外环温 、T 排气 、T 排气过热度 、T 外管温 、T 平均内环温 、T 平均蒸发器进口温度、T 平均蒸发器中间温度 、T 平均蒸发器出口温度 And so on, but not limited to these.

[0163] Step S310: Control the diagnostic module to work. The diagnostic module includes an indoor pipe temperature diagnostic module and an indoor unit overheating diagnostic module. After the two diagnostic modules output their diagnostic results, determine the air conditioning ventilation status diagnostic results, including but not limited to the following: ① When both the pipe temperature diagnostic module and the indoor unit overheat diagnostic module return "YES", the diagnosis is "abnormal indoor unit ventilation". ② If the pipe temperature diagnostic module returns "YES" and the indoor unit overheat diagnostic module returns "NO", the diagnosis is "Unable to diagnose". ③ If the pipe temperature diagnostic module returns "NO" and the indoor unit overheat diagnostic module returns "YES", the diagnosis is "Unable to diagnose". ④ When both the pipe temperature diagnosis module and the indoor unit overheat diagnosis module return "NO", the diagnosis is "the indoor unit ventilation is normal".

[0164] In one exemplary embodiment of this disclosure, before obtaining the basic parameters of the air conditioner, the method further includes: The air conditioner unit components are reset, including the components of the indoor unit and / or the components of the outdoor unit.

[0165] In an exemplary embodiment of this disclosure, the air conditioner unit components are reset, i.e., the air conditioner is turned off and then restarted, to avoid affecting the detection accuracy of the subsequent air conditioning ventilation status diagnostic scheme due to the misalignment of some components.

[0166] In one exemplary embodiment of this disclosure, the reset operation includes the following methods: A power-off operation is performed on the air conditioner, and the power-off duration is timed. In response to the power-off duration reaching the preset power-off duration, the air conditioner is powered on. In response to the air conditioner being powered on, the standby status parameters of the air conditioner are detected to see if they fall within the preset standby parameter range. In response to the standby status parameters falling within the preset standby parameter range, the reset operation is determined to be completed.

[0167] In one exemplary embodiment of this disclosure, a power-off operation is performed on all indoor and outdoor units of the air conditioner. The power-off state needs to be maintained in a power-off standby state to allow the indoor pipes of the air conditioner to cool completely and the components to reset before the air conditioner is powered on again. After power-on, the standby state is detected, and the relevant parameters of the standby state include the outdoor pipe temperature. T 外管 Outer ring temperature T外环 、 External tube correction temperature T 外管修正 Average inner tube temperature T 平均内管 Average inner ring temperature T 平均内环 and inner ring correction temperature T 内管修正 Furthermore, the relevant parameters for standby mode must meet the following requirements. T 外管 ≤ T 外环 +T 外管修正 and T 平均内管 ≤ T 平均内环 +T 内管修正 The above constraints are used to ensure that the air conditioner operates in a stable state, so as to avoid affecting the detection accuracy of the subsequent indoor unit ventilation diagnostic algorithm due to the misalignment of some components.

[0168] In one exemplary embodiment of this disclosure, t 断电待机 The value range is 1~10min.

[0169] In one exemplary embodiment of this disclosure, if the air conditioner compressor has maintained a standby or off state for ≥30 minutes before executing the indoor unit ventilation diagnostic procedure, then... t 断电待机 The value can be 3min, otherwise... t 断电待机 The value can be 5min.

[0170] In one exemplary embodiment of this disclosure, T 外管修正 The value range is 0℃~10℃. T 内管修正 The value can be 5℃.

[0171] In one exemplary embodiment of this disclosure, T 内管修正 The value range is 0℃ to -10℃. T 外管修正 The value can be -5℃.

[0172] In one exemplary embodiment of this disclosure, the standby state parameter includes the outer tube outlet temperature. T 外管 Outdoor ambient temperature T 外环 External tube correction temperature T 外管修正 Average inner tube temperatureT 平均内管 Average indoor ambient temperature T 平均内环 Inner tube correction temperature T 内管修正 At least one of them.

[0173] In one exemplary embodiment of this disclosure, the method for collecting the air conditioner operating parameters includes: The cumulative operating time of the air conditioner is determined, and in response to the cumulative operating time reaching a first preset time, the operating parameters of the air conditioner are collected.

[0174] In an exemplary embodiment of this disclosure, when the cumulative working time twork reaches the first preset time βmin, a "start data acquisition" instruction is sent to the data acquisition module so that the data acquisition module can collect the air conditioner operating parameters.

[0175] In an exemplary embodiment of this disclosure, the value of β ranges from 1 to 30 min, and can be 10 min.

[0176] In an exemplary embodiment of this disclosure, collecting the air conditioner operating parameters specifically includes: At least one set of the air conditioner operating parameters is collected at preset time intervals until the number of sets of air conditioner operating parameters reaches the preset number.

[0177] In an exemplary embodiment of this disclosure, a set of operating parameters of the test air conditioner are collected at a preset time interval of γs (seconds). The value of γ can be 1, 2, 3, 4, ..., 120, etc., but is not limited to this. The preset time interval can be adjusted or set according to user needs.

[0178] In one exemplary embodiment of this disclosure, the value of γ ranges from 1s to 60s (seconds), and can be 30s (seconds).

[0179] In one exemplary embodiment of this disclosure, the air conditioning operating parameters may include, but are not limited to, the following: f 压缩机频率 : The real-time operating frequency of the air conditioner compressor, in Hz.

[0180] T 外环温 The real-time ambient temperature detected by the outdoor unit of the air conditioner is in °C.

[0181] T 排气 The real-time exhaust temperature of the air conditioner compressor is measured in °C.

[0182] T 排气过热度: The real-time exhaust superheat temperature of the air conditioner compressor. For the specific calculation process, please refer to formula (7), and the unit is ℃.

[0183] , formula (7)

[0184] The parameters defined in formula (7) include, but are not limited to, the following: To obtain T 外管中点温 and T 外管出口温 The minimum value among them.

[0185] In one exemplary embodiment of this disclosure, T 外管中点温 The real-time temperature of the heat exchanger midpoint pipe of the outdoor unit of an air conditioner, taking the refrigeration flow path as an example. T 外管温 Specifically, it refers to the temperature of the heat exchanger tubes collected by a temperature acquisition device located in the middle of the pipe along the flow path of the outdoor unit heat exchanger, with the unit being °C.

[0186] In one exemplary embodiment of this disclosure, T 外管出口温 The real-time temperature of the heat exchanger outlet pipe of the outdoor unit of an air conditioner, taking the refrigeration flow path as an example. T 外管温 Specifically, it refers to the temperature of the heat exchanger tubes collected by the temperature acquisition device at the outlet of the pipe along the flow path of the outdoor unit heat exchanger, with the unit being °C.

[0187] In one exemplary embodiment of this disclosure, T 平均内环温 The real-time average inner loop temperature collected from all indoor units of the air conditioner. T 平均内环温 Specifically, it refers to the average real-time indoor ambient temperature of the room collected by all indoor units of the air conditioner, as shown in formula (8), with the unit being ℃.

[0188] , formula (8)

[0189] The parameters defined in formula (8) include, but are not limited to, the following: T 平均内环温 The average real-time indoor ambient temperature of the room collected by all indoor units of the air conditioner is expressed in °C.

[0190] T 内环温_n The real-time indoor ambient temperature of the room collected by the nth air conditioner indoor unit is in °C.

[0191] T 平均蒸发器进口温度The average real-time evaporator inlet pipe temperature collected by all indoor units of the air conditioner is in °C, as shown in formula (9).

[0192] , formula (9)

[0193] The parameters defined in formula (9) include, but are not limited to, the following: T 平均蒸发器进口温度 The average real-time evaporator inlet pipe temperature collected from all indoor units of the air conditioner is expressed in °C.

[0194] T 平均蒸发器进口温度_n The real-time evaporator inlet pipe temperature collected by the nth indoor air conditioner unit is in °C.

[0195] In one exemplary embodiment of this disclosure, T 平均蒸发器中间温度 : The average real-time evaporator intermediate pipe temperature collected by all indoor units of the air conditioner. T Evaporator intermediate temperature specifically refers to the heat exchanger pipe temperature collected by the temperature acquisition device at the middle position of the pipe along the flow path of the heat exchanger in the indoor unit, in °C, as shown in formula (10).

[0196] (10)

[0197] The parameters defined in formula (10) include, but are not limited to, the following: T 平均蒸发器中间温度 The average real-time evaporator intermediate pipe temperature collected from all indoor units of the air conditioner, in °C.

[0198] T 平均蒸发器中间温度_n : Real-time evaporator intermediate pipe temperature collected by the nth indoor unit of the air conditioner, in °C.

[0199] T 平均蒸发器出口温度 : The average real-time evaporator outlet pipe temperature collected from all indoor units of the air conditioner, in °C, as shown in formula (11).

[0200] , formula (11)

[0201] The parameters in formula (11) are defined including, but not limited to, the following: T 平均蒸发器出口温度 The average real-time evaporator outlet pipe temperature collected from all indoor units of the air conditioner, in °C.

[0202] T 平均蒸发器出口温度_n : Real-time evaporator outlet pipe temperature collected by the nth indoor unit of the air conditioner, in °C.

[0203] In one exemplary embodiment of this disclosure, the method of stopping the collection of the air conditioner operating parameters includes: The cumulative collection time for the air conditioner operating parameters is recorded, and the collection of the air conditioner operating parameters is stopped when the cumulative collection time reaches a second preset time.

[0204] In an exemplary embodiment of this disclosure, the timing begins when the test air conditioner is turned on and enters the residential multi-split air conditioning ventilation status diagnosis mode, which is recorded as ton=0min. The cumulative duration of the air conditioner running the residential multi-split air conditioning ventilation status diagnosis mode is recorded as tof. When tof satisfies tof=αmin, a "stop data acquisition" instruction is fed back to the data acquisition module.

[0205] In an exemplary embodiment of this disclosure, the value of α ranges from 1 to 60 min, and can be 20 min.

[0206] In one exemplary embodiment of this disclosure, before collecting the air conditioner operating parameters, the method further includes: The system sends an operation command to the outdoor unit of the air conditioner, and in response to the operation of the outdoor unit, sends a start command to the indoor unit of the air conditioner. In response to the start of the indoor unit, the system sends a target operation parameter command to the indoor unit, the target operation parameter command including the target indoor ambient temperature and / or the target fan speed setting.

[0207] In one exemplary embodiment of this disclosure, in cooling mode, a "run cooling mode" command is sent to the outdoor unit.

[0208] In one exemplary embodiment of this disclosure, a "power on" command is sent to all indoor units in the powered-on state.

[0209] In one exemplary embodiment of this disclosure, a "set target ambient temperature T setting" command is sent to all indoor units in the power-on state.

[0210] In one exemplary embodiment of this disclosure, a "Set target fan speed F setting" command is sent to all indoor units in the powered-on state.

[0211] In one exemplary embodiment of this disclosure, the target inner ambient temperature T 设定 The value range is 16℃~31℃, and the value can be... T 设定 = T 内环 - 10℃ or T 设定 =16℃.

[0212] In one exemplary embodiment of this disclosure, the value of the target wind speed F can be the highest wind speed or the highest speed.

[0213] In an exemplary embodiment of this disclosure, the purpose of setting the temperature and setting the fan speed is to allow the air conditioner to output at its maximum capacity as much as possible. On the one hand, this makes the system operating parameters more obvious, amplifies some abnormal values, and facilitates the extraction of characteristic parameters; on the other hand, it can shorten the diagnostic time.

[0214] In one exemplary embodiment of this disclosure, existing diagnostic technologies mostly adopt a fixed compressor frequency. The limitation of this approach is that the compressor can only operate in a fixed mode under any operating conditions. This is feasible in the scenario of a technician coming to install the air conditioner, but it cannot be diagnosed when the air conditioner is actually running in the user's home, or a specific diagnostic mode must be executed.

[0215] In one exemplary embodiment of this disclosure, by setting a target temperature, the compressor can operate freely (not limited to a fixed frequency). The technical effect achieved is that, during operation, the algorithm can extract the operating temperature of the air conditioner to meet the "target indoor ambient temperature". T 设定 "and" Target windshield F 设定 In the context of the "running scenario", the diagnostic model machine can perform seamless diagnosis based on the background data. That is, compared with conventional diagnostic methods, the use of this diagnostic algorithm does not require the machine to execute a specific mode, and its application range is wider.

[0216] In one exemplary embodiment of this disclosure, T 内环 This refers to the ambient temperature detected by the indoor unit of the system at the moment it enters the diagnostic mode for the ventilation status of the residential multi-split air conditioning system. For example, the ambient temperature detected by indoor unit i is denoted as "". T 内环_i ".

[0217] In one exemplary embodiment of this disclosure, T 设定 The target ambient temperature for the indoor unit in the system, for example, the target ambient temperature for indoor unit i is denoted as "". T 设定_i ".

[0218] In one exemplary embodiment of this disclosure, for the target inner ambient temperature T 设定 The preferred value, if it satisfies T 设定 =T 内环 -10℃ ≥ 16℃, then T 设定 = T 内环Take the value at -10℃, otherwise follow the value. T 设定 =Value taken at 16℃.

[0219] In one exemplary embodiment of this disclosure, after obtaining the air conditioning ventilation status diagnostic result, the method further includes: The diagnostic results of the air conditioning ventilation status are fed back to the client and / or server, and / or a shutdown command is executed on the air conditioner.

[0220] In an exemplary embodiment of this disclosure, the test air conditioning ventilation status diagnosis result is obtained, an indoor unit ventilation intelligent diagnosis report is output, and it can also be sent to after-sales technicians. At the same time, the air conditioning ventilation status diagnosis program sends an instruction to the test air conditioner to exit the residential multi-split air conditioning ventilation status diagnosis mode, and then executes a shutdown instruction.

[0221] Figure 6 This is a schematic diagram of an air conditioning ventilation status diagnostic device 600 according to an exemplary embodiment of the present disclosure.

[0222] like Figure 6 As shown, in some embodiments, the air conditioning ventilation status diagnostic device 600 of this disclosure example is provided with a data acquisition module 602 and a status diagnostic module 604, specifically implemented as follows: Data acquisition module 602 is configured to collect air conditioner operating parameters; The status diagnosis module 604 is configured to predict the air conditioning operating parameters through an air conditioning ventilation status prediction model to determine the air conditioning ventilation status diagnosis result. The air conditioning ventilation status diagnosis result is determined based on the indoor pipe temperature prediction information and / or the indoor unit superheat prediction information.

[0223] Figure 7 This is a schematic diagram of an air conditioner 700 according to an exemplary embodiment of the present disclosure.

[0224] like Figure 7 As shown, in some embodiments, an air conditioner 700 is provided, comprising: Processor 702 is configured to perform the air conditioning ventilation status diagnosis method as described in any of the above technical solutions.

[0225] Figure 8 This is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure. For example, the electronic device 800 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0226] Reference Figure 8The electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0227] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0228] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of such data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0229] Power supply component 806 provides power to various components of electronic device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0230] Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0231] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0232] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0233] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 may detect the on / off state of device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0234] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, 3G, 4G, 8G, other communication standards, or combinations thereof. In some embodiments of this disclosure, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In some embodiments of this disclosure, communication component 816 further includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0235] In some embodiments of this disclosure, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0236] In some embodiments of this disclosure, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions that can be executed by a processor 820 of an electronic device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0237] In some embodiments of this disclosure, a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of a mobile terminal, enables the mobile terminal to perform an air conditioning ventilation status diagnosis method.

[0238] In some embodiments of this disclosure, a computer program product is also provided, including a computer program / instructions, which, when executed by a processor, implement an air conditioning ventilation status diagnosis method.

[0239] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0240] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for diagnosing the condition of air conditioning ventilation, characterized in that, include: Collect air conditioner operating parameters; The air conditioning operating parameters are predicted using an air conditioning ventilation status prediction model to determine the air conditioning ventilation status diagnosis results, including: The air conditioning ventilation status prediction model includes an inner pipe temperature prediction model, and the prediction information includes inner pipe temperature prediction information. The prediction method using the inner pipe temperature prediction model includes: A first operating parameter is determined from the air conditioning operating parameters, and this first operating parameter is related to the predicted inner pipe temperature information. The first operating parameter includes at least one of the following: compressor operating frequency, exhaust temperature, exhaust superheat, outdoor ambient temperature, external pipe midpoint temperature, average evaporator inlet temperature, and average evaporator outlet temperature; The first operating parameter is predicted using the inner tube temperature prediction model to obtain inner tube temperature prediction information. The diagnostic results for the air conditioning ventilation status are determined based on the predicted information of the internal pipe temperature and / or the predicted information of the indoor unit overheating.

2. The air conditioning ventilation status diagnosis method according to claim 1, characterized in that, The methods for training the air conditioning ventilation status prediction model include: Construct a test environment for the air conditioning ventilation status prediction model; In the test environment, historical operating data samples are input into the air conditioning ventilation status prediction model, and the prediction information output by the air conditioning ventilation status prediction model is obtained. The predicted information is compared with the corresponding air conditioning ventilation status label to adjust the parameters of the air conditioning ventilation status prediction model.

3. The air conditioning ventilation status diagnosis method according to claim 2, characterized in that, The methods for obtaining the historical operational data samples include: Collect at least one set of sample data corresponding to the air conditioner operating parameters; Determine the actual air conditioning and ventilation status corresponding to the sample data; Based on the actual air conditioning and ventilation status, each group of sample data is labeled to obtain historical operating data samples labeled with air conditioning and ventilation status tags. The air conditioning ventilation status label includes good ventilation and / or poor ventilation.

4. The air conditioning ventilation status diagnosis method according to claim 1, characterized in that, The air conditioning ventilation status prediction model includes an indoor unit overheat prediction model, and the prediction information includes indoor unit overheat prediction information. Prediction using the indoor unit overheat prediction model also includes: A second operating parameter is determined from the air conditioner operating parameters, and this second operating parameter is related to the indoor unit superheat prediction information. The second operating parameter includes at least one of the following: average indoor ambient temperature, average evaporator inlet temperature, average evaporator intermediate temperature, and average evaporator outlet temperature; The second operating parameter is predicted using the indoor unit overheating prediction model to obtain indoor unit overheating prediction information.

5. The air conditioning ventilation status diagnosis method according to claim 1, characterized in that, Methods for determining the diagnostic results of air conditioning ventilation status include: Obtain the measured information and preset tolerance value of the air conditioner. The measured information includes measured information on the inner tube temperature and / or measured information on the superheat of the indoor unit. The preset tolerance value is the preset difference between the predicted information and the measured information. The prediction information includes prediction information for the inner tube temperature and / or prediction information for the indoor unit superheat. Based on the predicted information, the measured information, and the preset tolerance value, the diagnostic result of the air conditioning ventilation status is obtained.

6. The air conditioning ventilation status diagnosis method according to claim 5, characterized in that, The air conditioning ventilation status diagnosis result is either a first ventilation status or a second ventilation status, wherein the wind speed in the first ventilation status is lower than the wind speed in the second ventilation status. The method for determining the air conditioning ventilation status diagnosis result includes: Determine the proportion of the air conditioning operating parameters under the first ventilation state within the target operating parameters. The target operating parameters include the air conditioning operating parameters under the first ventilation state and the air conditioning operating parameters under the second ventilation state; The diagnostic result of the air conditioning ventilation status is determined based on the relationship between the stated proportion and the preset proportion.

7. The air conditioning ventilation status diagnosis method according to claim 6, characterized in that, The methods for determining the percentage include: Determine the proportion of the first operating parameter under the first ventilation state in the target first operating parameter. The target first operating parameter includes the first operating parameter under the first ventilation state and the first operating parameter under the second ventilation state; And / or, determine the proportion of the second operating parameter under the first ventilation state in the target second operating parameter. The target second operating parameter includes the second operating parameter under the first ventilation state and the second operating parameter under the second ventilation state.

8. The air conditioning ventilation status diagnosis method according to claim 7, characterized in that, The methods for determining the diagnostic results of the air conditioning ventilation status include: Based on the proportion of the first operating parameter under the first ventilation state, And / or, the percentage of the second operating parameter under the first ventilation state, Determine the diagnostic results of the air conditioning ventilation status.

9. The air conditioning ventilation status diagnosis method according to claim 1, characterized in that, The methods for determining the diagnostic results of the air conditioning ventilation status include: In response to the acquired prediction information, the prediction information is corrected based on the indoor unit vent installation information; Based on the correction results of the predicted information, the diagnostic result of the air conditioning ventilation status is determined.

10. The air conditioning ventilation status diagnosis method according to claim 9, characterized in that, The methods for correcting the prediction information include: Determine the correction factor corresponding to the indoor unit air vent installation information; The prediction information is corrected based on the correction coefficient.

11. The air conditioning ventilation status diagnosis method according to claim 10, characterized in that, Correcting the predicted information according to the correction coefficient specifically includes: At least one of the correction coefficients is weighted and summed according to preset weights; The prediction information is corrected based on the weighted summation result.

12. The air conditioning ventilation status diagnosis method according to claim 10, characterized in that, The indoor unit air vent installation information includes at least one of the following: return air method, return air vent extension pipe installation information, and louver installation information. The return air method includes bottom return air and / or rear return air.

13. The air conditioning ventilation status diagnosis method according to claim 12, characterized in that, The correction factor includes at least one of the following: the correction factor corresponding to the return air method, the correction factor corresponding to the extension pipe installation information of the return air vent, and the correction factor corresponding to the louver installation information of the return air vent.

14. The air conditioning ventilation status diagnosis method according to claim 1, characterized in that, Before obtaining the prediction information, the process also includes: Obtain the basic parameters of the air conditioner, including indoor unit platform parameter information and / or indoor unit return air vent installation information; In response to the fact that the basic parameters are within the preset parameter range, it is determined to send an operation command to the outdoor unit of the air conditioner; And / or, in response to the basic parameter not falling within the preset parameter range, or the basic parameter being incorrect, or the basic parameter being missing, Send input prompts for the basic parameters, and / or switch to the input interface corresponding to the basic parameters.

15. The air conditioning ventilation status diagnosis method according to claim 14, characterized in that, The indoor unit platform parameter information includes at least one of the following: indoor unit model parameters, indoor unit fan model parameters, and indoor unit driver version.

16. The air conditioning ventilation status diagnosis method according to claim 14, characterized in that, Before obtaining the basic parameters of the air conditioner, the following is also included: The air conditioner unit components are reset, including the components of the indoor unit and / or the components of the outdoor unit.

17. The air conditioning ventilation status diagnosis method according to claim 16, characterized in that, The reset operation includes the following methods: Perform a power-off operation on the air conditioner and time the duration of the power-off. In response to the power outage duration reaching the preset power outage duration, the air conditioner is powered on; In response to the air conditioner being powered on, the standby status parameters of the air conditioner are detected to determine whether they fall within the preset standby parameter range. In response to the standby state parameter falling within the preset standby parameter range, the reset operation is determined to be completed.

18. The air conditioning ventilation status diagnosis method according to claim 17, characterized in that, The standby state parameters include at least one of the following: outer tube outlet temperature, outdoor ambient temperature, outer tube correction temperature, average inner tube temperature, average indoor ambient temperature, and inner tube correction temperature.

19. The air conditioning ventilation status diagnosis method according to any one of claims 1-15, characterized in that, The methods for collecting the air conditioner operating parameters include: Determine the cumulative operating time of the air conditioner; In response to the cumulative working time reaching a first preset time, the air conditioner operating parameters are collected.

20. The air conditioning ventilation status diagnosis method according to claim 19, characterized in that, The collection of the air conditioner operating parameters specifically includes: At least one set of the air conditioner operating parameters is collected at preset time intervals until the number of sets of air conditioner operating parameters reaches the preset number.

21. The air conditioning ventilation status diagnosis method according to claim 19, characterized in that, The methods to stop collecting the air conditioner operating parameters include: The cumulative collection time for the air conditioner operating parameters; In response to the cumulative collection time reaching a second preset time, the collection of the air conditioner operating parameters is stopped.

22. The air conditioning ventilation status diagnosis method according to any one of claims 1-15, characterized in that, Before collecting the air conditioner operating parameters, the following is also included: Send an operating command to the outdoor unit of the air conditioner; In response to the operation of the outdoor unit, a start-up command is sent to the indoor unit of the air conditioner; In response to the indoor unit being powered on, a target operating parameter command is sent to the indoor unit. The target operating parameter instructions include the target indoor ambient temperature and / or the target wind speed setting.

23. The air conditioning ventilation status diagnosis method according to any one of claims 1-15, characterized in that, After obtaining the diagnostic results of the air conditioning ventilation status, the method further includes: The diagnostic results of the air conditioning ventilation status are fed back to the client and / or server. And / or, execute a shutdown command on the air conditioner.

24. An air conditioning ventilation status diagnostic device, characterized in that, The air conditioning ventilation status diagnostic device is used to perform the method as described in any one of claims 1-23, and the air conditioning ventilation status diagnostic device comprises: The data acquisition module is configured to collect air conditioner operating parameters; The status diagnosis module is configured to predict the air conditioning operating parameters using an air conditioning ventilation status prediction model to determine the air conditioning ventilation status diagnosis result, including: The air conditioning ventilation status prediction model includes an inner pipe temperature prediction model, and the prediction information includes inner pipe temperature prediction information. The prediction method using the inner pipe temperature prediction model includes: A first operating parameter is determined from the air conditioning operating parameters, and this first operating parameter is related to the predicted inner pipe temperature information. The first operating parameter includes at least one of the following: compressor operating frequency, exhaust temperature, exhaust superheat, outdoor ambient temperature, external pipe midpoint temperature, average evaporator inlet temperature, and average evaporator outlet temperature; The first operating parameter is predicted using the inner tube temperature prediction model to obtain inner tube temperature prediction information. The diagnostic results for the air conditioning ventilation status are determined based on the predicted information of the internal pipe temperature and / or the predicted information of the indoor unit overheating.

25. An air conditioner, characterized in that, include: The processor is configured to implement the air conditioning ventilation status diagnosis method according to any one of claims 1-23.

26. An electronic device, characterized in that... include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the air conditioning ventilation status diagnosis method according to any one of claims 1-23.

27. A non-transitory computer-readable storage medium, wherein when instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to perform the air conditioning ventilation status diagnosis method according to any one of claims 1-23.

28. A computer program product, characterized in that... It includes a computer program that, when executed by a processor, implements the air conditioning ventilation status diagnosis method as described in any one of claims 1-23.

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