Method and device for recognizing filth blockage rate of air conditioner and air conditioner

Abstract

The invention provides an air conditioner filth blockage rate recognition method and device and an air conditioner. The recognition method for the filth blockage rate of the air conditioner comprises the steps that a filth blockage rate recognition model among the filth blockage rate of the air conditioner, the air speed of a fan driving module and electrical parameters of the fan driving module is established; acquiring actual wind speed and actual electric parameters of the current fan driving module; and based on the filth blockage rate identification model, the actual wind speed and the actual electrical parameters, determining the actual filth blockage rate corresponding to the actual wind speed and the actual electrical parameters. According to the air conditioner filth blockage rate recognition method and device and the air conditioner, on one hand, the air conditioner based on position sensor-free draught fan control has the current detection capacity, other sensors do not need to be additionally arranged, and accurate prediction of the filth blockage rate and the frosting rate is achieved only on the basis of hardware of the air conditioner, and on the other hand, accurate prediction of the filth blockage rate and the frosting rate is achieved. The frosting rate can be truly reflected, the defrosting control condition of the air conditioner is optimized, and the operation capacity of the air conditioner is optimized.

Description

Technical Field

[0001] The present invention relates to the field of electrical appliance technology, and in particular to an identification method and device for identifying the dirtiness and blockage rate of an air conditioner, and an air conditioner. Background Art

[0002] In the related technology, the existing defrost judgment conditions and the dirty and blocked conditions of the condenser will cause the air conditioner outdoor unit to defrost, especially under ultra-low temperature ambient temperature conditions. The existing defrost conditions cannot meet market needs, and the dirty and blocked rate of the air conditioner caused by frosting of the condenser is often not accurately obtained. In this way, under the premise that the dirty and blocked rate of the air conditioner cannot be accurately obtained, the air conditioner cannot achieve accurate and thorough defrosting during the defrosting process, which often leads to frequent defrosting, no defrosting or false defrosting of the air conditioner, which reduces the capacity of the air conditioner and provides a poor user experience. Summary of the invention

[0003] The present invention provides an identification method, an identification device and an air conditioner for the dirtiness and blockage rate of an air conditioner, so as to solve the defects existing in the prior art and achieve the following technical effects: on the one hand, the air conditioner based on position sensorless fan control has the current detection capability itself, and no other sensors need to be added. The accurate prediction of the dirtiness and blockage rate and the frost rate can be achieved only on the basis of the hardware of the air conditioner itself; on the other hand, the true reflection of the frost rate can be achieved, and the defrost control conditions of the air conditioner can be optimized, so as to achieve the optimization of the air conditioner operation capacity.

[0004] The method for identifying the dirty blockage rate of an air conditioner according to the first embodiment of the present invention includes:

[0005] Establish a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module;

[0006] Obtaining the actual wind speed and actual electrical parameters of the current fan drive module;

[0007] Based on the dirt and blockage rate identification model, the actual wind speed and the actual electrical parameter, an actual dirt and blockage rate corresponding to the actual wind speed and the actual electrical parameter is determined.

[0008] According to an embodiment of the present invention, the step of establishing a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan driving module, and the electrical parameters of the fan driving module specifically includes:

[0009] Acquire multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters, wherein in the multiple groups of measurement data, the dirt and blockage rate, the wind speed and the electrical parameters correspond one to one;

[0010] Counting multiple groups of the measurement data to generate a corresponding relationship table between the dirt and blockage rate, the wind speed and the electrical parameter;

[0011] A dirt and blockage rate identification model between the dirt and blockage rate, the wind speed and the electrical parameter is established according to the corresponding relationship table.

[0012] According to an embodiment of the present invention, the step of obtaining multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters specifically includes:

[0013] Test each wind speed of the fan drive module at each air volume level under normal static pressure conditions;

[0014] Fixing the fan driving module at one of the wind speeds, adjusting the dirtiness and blockage rate of the air conditioner, and measuring the electrical parameters corresponding to the fan driving module at each of the dirtiness and blockage rates;

[0015] Repeat the previous step until multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters are obtained, wherein in the multiple groups of measurement data, the dirt and blockage rate, the wind speed and the electrical parameters correspond one to one.

[0016] According to an embodiment of the present invention, the step of obtaining multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters specifically includes:

[0017] Preset multiple dirtiness and blockage rate values ​​for the air conditioner;

[0018] Fixing the air conditioner at one of the dirt and blockage rate values, adjusting the wind speed of the air conditioner, and measuring the electrical parameters corresponding to the fan drive module at each wind speed;

[0019] Repeat the previous step until multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters are obtained, wherein in the multiple groups of measurement data, the dirt and blockage rate, the wind speed and the electrical parameters correspond one to one.

[0020] According to an embodiment of the present invention, the step of establishing a dirty blockage rate identification model between the dirty blockage rate, the wind speed and the electrical parameter according to the correspondence table specifically includes:

[0021] According to the correspondence table between the dirty blockage rate, the wind speed and the electrical parameters, a dirty blockage rate recognition model between the dirty blockage rate, the wind speed and the electrical parameters is obtained through a preset learning algorithm and training data.

[0022] According to one embodiment of the present invention, in the step of establishing a dirty and blockage rate identification model between the dirty and blockage rate of the air conditioner, the wind speed of the fan driving module and the electrical parameters of the fan driving module, the electrical parameters of the fan driving module include the current value or power value of the fan driving module.

[0023] According to an embodiment of the present invention, the step of establishing a dirty and blockage rate identification model between the dirty and blockage rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module further includes:

[0024] An automated testing tool is established to automatically adjust the dirtiness and blockage rate of the air-conditioning condenser and the wind speed of the fan drive module under the current static pressure conditions, and detect the electrical parameters corresponding to the current dirtiness and blockage rate and the current wind speed, so as to realize the automatic test output of the correspondence table between the wind speed, dirtiness and blockage rate and the electrical parameters.

[0025] According to the second aspect of the present invention, the device for identifying the dirty and blocked rate of an air conditioner includes:

[0026] A first acquisition module is used to establish a dirty and blocked rate recognition model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module;

[0027] A second acquisition module is used to acquire the actual wind speed and actual electrical parameters of the current wind turbine driving module;

[0028] A control module is used to determine the actual dirty blockage rate corresponding to the actual wind speed and the actual electrical parameter based on the dirty blockage rate identification model, the actual wind speed and the actual electrical parameter.

[0029] An air conditioner according to an embodiment of the third aspect of the present invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the method for identifying the dirty blockage rate of the air conditioner as described in the embodiment of the first aspect of the present invention is implemented.

[0030] According to an embodiment of the present invention, the fan driving module includes a position sensorless device and a permanent magnet synchronous motor.

[0031] In order to solve the technical defects existing in the above-mentioned related technologies, the present invention provides a method for identifying the dirty and blocked rate of an air conditioner. The method establishes a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan driving module and the electrical parameters of the fan driving module, and obtains the actual wind speed and the actual electrical parameters of the fan driving module and inputs them into the dirty and blocked rate identification model. The actual dirty and blocked rate corresponding to the actual wind speed and the actual electrical parameters can be calculated, thereby completing the identification of the dirty and blocked rate of the air conditioner condenser. In this way, on the one hand, the air conditioner based on position sensorless fan control has current detection capability itself, and there is no need to add other sensors. Only on the basis of the hardware of the air conditioner itself, accurate prediction of the dirty and blocked rate and frosting rate can be achieved. On the other hand, the true reflection of the frosting rate can be achieved, and the defrost control conditions of the air conditioner can be optimized, thereby optimizing the operation capacity of the air conditioner. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 It is a flow chart of the method for identifying the dirty and blocked rate of an air conditioner provided by the present invention;

[0034] Figure 2 It is a structural schematic diagram of the device for identifying the dirty and blocked rate of an air conditioner provided by the present invention;

[0035] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0038] The following describes the method, device and air conditioner for identifying the dirty and blocked rate of the air conditioner proposed in the present invention with reference to the accompanying drawings. Before describing the embodiments of the present invention in detail, the entire application scenario is described first. The method, device, electronic device and computer-readable storage medium for identifying the dirty and blocked rate of the air conditioner in the embodiments of the present invention can be applied to the air conditioner locally, to the cloud platform in the Internet field, or to other types of cloud platforms in the Internet field, or to third-party devices. Third-party devices may include various types such as mobile phones, tablet computers, notebooks, car computers and other smart terminals.

[0039] The following description only takes the control method applicable to air conditioners as an example. It should be understood that the control method of the embodiment of the present invention can also be applied to cloud platforms and third-party devices.

[0040] It should also be noted that the air conditioner control method proposed in the present invention is universal, that is, the method is applicable to the air conditioner for cooling or heating in a low-temperature environment or a high-temperature environment.

[0041] like Figure 1 As shown, the method for identifying the dirty blockage rate of an air conditioner according to the first aspect of the present invention includes:

[0042] Step S1, establishing a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module;

[0043] Step S2, obtaining the actual wind speed and actual electrical parameters of the current wind turbine drive module;

[0044] Step S3, based on the dirty and blocked rate identification model, the actual wind speed and the actual electrical parameters, determine the actual dirty and blocked rate corresponding to the actual wind speed and the actual electrical parameters.

[0045] According to the method for identifying the dirty blockage rate of an air conditioner according to an embodiment of the present invention, its specific working process is as follows: first, a dirty blockage rate identification model between the dirty blockage rate of the air conditioner, the wind speed of the fan drive module and the electrical parameters of the fan drive module is established, and the above-mentioned dirty blockage rate identification model is written into the controller of the air conditioner. It should be pointed out that in the dirty blockage rate identification model, the dirty blockage rate of the air conditioner, the wind speed of the fan drive module and the electrical parameters of the fan drive module are all one-to-one corresponding, that is, by obtaining two of the data among the dirty blockage rate of the air conditioner, the wind speed of the fan drive module and the electrical parameters of the fan drive module, the other data among the dirty blockage rate of the air conditioner, the wind speed of the fan drive module and the electrical parameters of the fan drive module can be calculated through the dirty blockage rate identification model.

[0046] After determining that the air conditioner is in the startup state, while the current operating parameters and environmental parameters of the air conditioner remain unchanged, the actual wind speed and actual electrical parameters of the current fan drive module are obtained. After obtaining the above-mentioned actual wind speed and actual electrical parameters, the controller can input the actual wind speed and actual electrical parameters of the fan drive module into the dirty blockage rate identification model obtained in step S1. Since the three types of data in the dirty blockage rate identification model are the dirty blockage rate of the air conditioner, the wind speed of the fan drive module and the electrical parameters of the fan drive module, and since two of the above three types of data (i.e., the actual wind speed and the actual electrical parameters) are known, based on the above-mentioned actual wind speed, actual electrical parameters and dirty blockage rate identification model, the actual dirty blockage rate corresponding to the actual wind speed and actual electrical parameters can be calculated, thereby completing the identification of the dirty blockage rate of the air conditioner condenser.

[0047] In the related technology, the existing defrost judgment conditions and the dirty and blocked conditions of the condenser will cause the air conditioner outdoor unit to defrost, especially under ultra-low temperature ambient temperature conditions. The existing defrost conditions cannot meet market needs, and the dirty and blocked rate of the air conditioner caused by frosting of the condenser is often not accurately obtained. In this way, under the premise that the dirty and blocked rate of the air conditioner cannot be accurately obtained, the air conditioner cannot achieve accurate and thorough defrosting during the defrosting process, which often leads to frequent defrosting, no defrosting or false defrosting of the air conditioner, which reduces the capacity of the air conditioner and provides a poor user experience.

[0048] In summary, in order to solve the technical defects existing in the above-mentioned related technologies, the present invention provides a method for identifying the dirty and blocked rate of an air conditioner. The method establishes a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan driving module and the electrical parameters of the fan driving module, and obtains the actual wind speed and the actual electrical parameters of the fan driving module and inputs them into the dirty and blocked rate identification model. The actual dirty and blocked rate corresponding to the actual wind speed and the actual electrical parameters can be calculated, thereby completing the identification of the dirty and blocked rate of the air conditioner condenser. In this way, on the one hand, the air conditioner based on position sensorless fan control has current detection capability itself, and there is no need to add other sensors. It can realize accurate prediction of the dirty and blocked rate and frosting rate only on the basis of the hardware of the air conditioner itself. On the other hand, it can realize the true reflection of the frosting rate, optimize the defrost control conditions of the air conditioner, and optimize the operation capacity of the air conditioner.

[0049] It should be explained that when the condenser of the air conditioner is not dirty, blocked or frosted, the wind speed is constant, and the air volume (ie wind speed) of the system is constant. The fan drive module of the present invention uses a position sensorless permanent magnet synchronous motor to achieve wind speed control of the air conditioner.

[0050] By conducting a static pressure test on a duct air conditioner, it was found that when the air outlet of the duct air conditioner is restricted (the air intake is greater than the air outlet), and under normal circumstances, the fan phase current detected in the drive circuit of the permanent magnet synchronous motor controlled by a position sensorless control is different. Therefore, due to the existence of current detection, a closed loop of fan current and air volume control is formed, that is, a closed loop of fan current to condenser dirtiness, blockage rate and frost rate is formed.

[0051] This method uses the preset dirty blockage area (i.e., dirty blockage rate) of the air conditioner condenser, and collects the feedback power (or current) of the fan drive module under different dirty blockage rates at a fixed wind speed. The collected data is summarized, and the collected data is trained using machine learning algorithm models such as RealityAI (RealityAI is a software provided by an embedded AI solution provider, mainly engaged in the research, development, application and promotion of embedded AI and micro machine learning, and provides signal processing, intelligent algorithms, and software environment construction services) and neural networks to generate a mathematical model of condenser blockage ratio, fan speed, and fan power (i.e., dirty blockage rate identification model). The mathematical model (i.e., dirty blockage rate identification model) is combined with the outdoor ambient temperature, air conditioner operation mode, and air conditioner condenser temperature (defrost temperature) to determine whether the current air conditioner outdoor unit is dirty or frosted.

[0052] According to some embodiments of the present invention, the step of establishing a dirty and clogging rate identification model between the dirty and clogging rate of the air conditioner, the wind speed of the fan driving module, and the electrical parameters of the fan driving module specifically includes:

[0053] Acquire multiple sets of measurement data including dirt and blockage rates, wind speeds, and electrical parameters, wherein in the multiple sets of measurement data, the dirt and blockage rates, wind speeds, and electrical parameters correspond to each other one by one;

[0054] Count multiple groups of measurement data to generate a corresponding relationship table between dirt and blockage rate, wind speed and electrical parameters;

[0055] A dirty blockage rate identification model among dirty blockage rate, wind speed and electrical parameters is established according to the corresponding relationship table.

[0056] It can be understood that in this embodiment, the steps for establishing the dirty congestion rate identification model are as follows: first, obtaining multiple sets of measurement data, and each set of measurement data includes one-to-one corresponding dirty congestion rate, wind speed and electrical parameters; second, generating a correspondence table between the dirty congestion rate, wind speed and electrical parameters based on the multiple sets of measurement data; third, generating a dirty congestion rate identification model based on the above correspondence table.

[0057] It should be pointed out that the above-mentioned multiple sets of measurement data can be obtained in any of the following ways: first, preset an arbitrary size of dirtiness and blockage rate for the air conditioner condenser and preset an arbitrary size of wind speed for the fan drive module, and measure the electrical parameters (including current value or power value) under the current dirtiness and blockage rate and wind speed; second, fix the dirtiness and blockage rate of the air conditioner condenser to a value, adjust the wind speed of the fan drive module, and measure the electrical parameters under the current wind speed, then fix the dirtiness and blockage rate of the air conditioner condenser to another value and repeat the above operation; fix the wind speed of the fan drive module to a value, adjust the dirtiness and blockage rate of the air conditioner condenser, and measure the electrical parameters under the current dirtiness and blockage rate, then fix the wind speed of the fan drive module to another value and repeat the above operation.

[0058] Of course, the above-mentioned methods for obtaining multiple groups of measurement data are only some of the various embodiments of the present invention, and do not constitute a specific limitation on the method for obtaining measurement data. In different usage scenarios and usage requirements, the method for obtaining measurement data can be independently selected according to actual needs, and the present invention does not make any special restrictions here.

[0059] In a specific embodiment of the present invention, the step of obtaining multiple groups of measurement data including dirt and blockage rate, wind speed and electrical parameters specifically includes:

[0060] Test each wind speed of the fan drive module at each air volume level under normal static pressure conditions;

[0061] Fix the fan drive module at one of the wind speeds, adjust the dirty and blocked rate of the air conditioner, and measure the electrical parameters of the fan drive module corresponding to each dirty and blocked rate;

[0062] Repeat the previous step until multiple sets of measurement data including dirt and blockage rates, wind speeds, and electrical parameters are obtained, wherein in the multiple sets of measurement data, the dirt and blockage rates, wind speeds, and electrical parameters correspond one to one.

[0063] In this way, by fixing the wind speed of the fan drive module and adjusting the dirt and blockage rate to obtain the corresponding electrical parameters, the fixed value of the wind speed can be adjusted again to obtain other electrical parameter data, making the acquisition of measurement data simpler, more convenient and easy to implement.

[0064] In another embodiment of the present invention, the step of obtaining multiple sets of measurement data including dirt and blockage rate, wind speed and electrical parameters specifically includes:

[0065] Preset multiple dirtiness and blockage rate values ​​for the air conditioner;

[0066] Fix the air conditioner at one of the dirty and blockage rate values, adjust the air conditioner wind speed, and measure the electrical parameters corresponding to the fan drive module at each wind speed;

[0067] Repeat the previous step until multiple sets of measurement data including dirt and blockage rates, wind speeds, and electrical parameters are obtained, wherein in the multiple sets of measurement data, the dirt and blockage rates, wind speeds, and electrical parameters correspond one to one.

[0068] In this way, by fixing the dirty and clogging rate of the air-conditioning condenser, adjusting the wind speed of the fan driving module to obtain the corresponding electrical parameters, and adjusting the dirty and clogging rate of the air-conditioning condenser again to obtain other electrical parameter data, the acquisition of measurement data is simpler, more convenient, and easy to implement.

[0069] According to some embodiments of the present invention, the step of establishing a dirty blockage rate identification model between the dirty blockage rate, wind speed and electrical parameters according to the correspondence table specifically includes:

[0070] According to the correspondence table between the dirty congestion rate, wind speed and electrical parameters, a dirty congestion rate recognition model between the dirty congestion rate, wind speed and electrical parameters is obtained through the preset learning algorithm and training data.

[0071] For example, according to the current of the wind turbine drive module, the correspondence table of dirt and blockage, current and wind speed is reversed, and the mathematical model of the relationship between dirt and blockage rate, current and wind speed is obtained through training data through machine learning algorithms such as RealityAI and neural network deep learning. The C code automatic editor such as Matlab (Matlab is a commercial mathematical software used in data analysis, wireless communications, deep learning, image processing and computer vision, signal processing, quantitative finance and risk management, robotics, control systems, etc.) is collected to generate a C language model.

[0072] In this way, the model can be based on cloud tools and can continuously learn and analyze data, and use automated programming tools to realize the automatic conversion of mathematical models into C code. Now it is possible to build an HVAC (HVAC is the abbreviation of Heating, Ventilation and Air Conditioning) air conditioning frost rate model that uses a position sensorless fan drive solution to achieve an accuracy of up to 95% in detecting and distinguishing frost rates. The model occupies less than 5K of chip Flash capacity, occupies very little chip computing power, and has entered the reliability verification stage in the heat pump unit. The output of AI intelligent dirty blockage rate and frost rate is completed with extremely small chip resources, providing a solution to the problem of false defrosting.

[0073] According to some embodiments of the present invention, in the step of establishing a dirty and blockage rate identification model between the dirty and blockage rate of the air conditioner, the wind speed of the fan drive module and the electrical parameters of the fan drive module, the electrical parameters of the fan drive module include the current value or power value of the fan drive module.

[0074] According to some embodiments of the present invention, the step of establishing a dirty and blockage rate identification model between the dirty and blockage rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module further includes:

[0075] An automated testing tool is established to automatically adjust the dirty and blockage rate of the air-conditioning condenser and the wind speed of the fan drive module under the current static pressure conditions, and detect the electrical parameters corresponding to the current dirty and blockage rate and the current wind speed, so as to realize the automatic test output of the correspondence table between the wind speed, dirty and blockage rate and electrical parameters.

[0076] In this embodiment, by establishing an automated testing tool, the automatic test output of the correspondence table between wind speed, dirt blockage rate and electrical parameters can be achieved without manual operation, and the data is more accurate and has a lower error rate than manual measurement.

[0077] A specific embodiment of the method for identifying the dirty and blocked rate of an air conditioner according to the present invention is described below with reference to the accompanying drawings.

[0078] STEP 1: Test the wind speed at each air volume level under normal static pressure (0Pa) and the fan phase current value (power value) fed back by the fan drive module.

[0079] STEP 2: Fix the wind speed, adjust the dirty or frosted area of ​​the air conditioner condenser, and test the fan drive module feedback fan phase current value (power value) under the current dirty or frosted rate to form the basic data of the learning model.

[0080] STEP 3: Statistical data is used to establish a corresponding relationship table between dirt blockage rate or frost rate, current (power) and wind speed.

[0081] STEP 4: According to the above steps, establish an automated test tooling to automatically control the dirty or frosted area of ​​the air-conditioning condenser and the wind speed of the fan drive module; and detect the wind speed and current to achieve automatic test output of the corresponding relationship table of air volume, static pressure, current and wind speed.

[0082] STEP5: Transplant the corresponding relationship table of the dirty blockage rate or frosting rate, current (power) and wind speed to the air conditioning wind speed control module, and the air conditioning controller detects the fan drive module to detect the fan phase current.

[0083] SETP6: According to the wind turbine current, the corresponding relationship table of dirt blockage rate or frosting rate, current (power) and wind speed is reversed. Through machine learning algorithms such as RealityAI and neural network deep learning, the training data is used to obtain the mathematical model of the relationship between dirt blockage rate or frosting rate, current (power) and wind speed, and C code automatic editors such as Matlab are collected to generate a C language model.

[0084] STEP 7: The air conditioning controller determines the current changes in the air conditioning condenser based on the learning model, and determines the condenser dirtiness or frost rate.

[0085] In summary, the preset air conditioner condenser dirty blockage area and fixed wind speed are used to collect the feedback power (current) of the fan drive module under different dirty blockage areas. The collected data is summarized and trained using machine learning algorithm models such as RealityAI and neural networks to generate mathematical models of condenser blockage ratio, fan speed, and fan power. The mathematical model is combined with the outdoor ambient temperature, air conditioner operation mode, and air conditioner condenser temperature (defrost temperature) to determine whether the current air conditioner outdoor unit is dirty or frosted.

[0086] The following is a description of the device for identifying the dirty and blocked rate of an air conditioner provided by the present invention. The device for identifying the dirty and blocked rate of an air conditioner described below and the method for identifying the dirty and blocked rate of an air conditioner described above can be referred to each other.

[0087] like Figure 2 As shown, the device for identifying the dirty and blocked rate of an air conditioner according to the second aspect of the present invention includes:

[0088] The first acquisition module 110 is used to establish a dirty and blocked rate recognition model between the dirty and blocked rate of the air conditioner, the wind speed of the fan driving module, and the electrical parameters of the fan driving module;

[0089] The second acquisition module 120 is used to obtain the actual wind speed and actual electrical parameters of the current wind turbine drive module;

[0090] The control module 130 is used to determine the actual dirty and blockage rate corresponding to the actual wind speed and the actual electrical parameter based on the dirty and blockage rate identification model, the actual wind speed and the actual electrical parameter.

[0091] An air conditioner according to an embodiment of the third aspect of the present invention comprises the device for identifying the dirty and blocked rate of the air conditioner as described in the embodiment of the second aspect of the present invention.

[0092] According to one embodiment of the present invention, an air conditioner includes a fan driving module, and the fan driving module includes a position sensorless device and a permanent magnet synchronous motor.

[0093] According to the air conditioner and the device for identifying the dirty blockage rate of the air conditioner thereof of the embodiment of the present invention, by establishing a dirty blockage rate identification model between the dirty blockage rate of the air conditioner, the wind speed of the fan driving module and the electrical parameters of the fan driving module, and obtaining the actual wind speed and the actual electrical parameters of the fan driving module and inputting them into the dirty blockage rate identification model, the actual dirty blockage rate corresponding to the actual wind speed and the actual electrical parameters can be calculated, thereby completing the identification of the dirty blockage rate of the air conditioner condenser. In this way, on the one hand, the air conditioner based on position sensorless fan control has the current detection capability itself, and there is no need to add other sensors. Only on the basis of the hardware of the air conditioner itself, the accurate prediction of the dirty blockage rate and the frost rate can be achieved. On the other hand, the true reflection of the frost rate can be achieved, and the air conditioner defrost control conditions can be optimized, thereby optimizing the air conditioner operation capacity.

[0094] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820 and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute the method for identifying the dirty and blocked rate of the air conditioner, including: establishing a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module and the electrical parameters of the fan drive module; obtaining the actual wind speed and the actual electrical parameters of the current fan drive module; and determining the actual dirty and blocked rate corresponding to the actual wind speed and the actual electrical parameters based on the dirty and blocked rate identification model, the actual wind speed and the actual electrical parameters.

[0095] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0096] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a method for identifying the dirty and blocked rate of an air conditioner, including: establishing a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module; obtaining the actual wind speed and actual electrical parameters of the current fan drive module; and determining the actual dirty and blocked rate corresponding to the actual wind speed and the actual electrical parameters based on the dirty and blocked rate identification model, the actual wind speed, and the actual electrical parameters.

[0097] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, a method for identifying the dirty and blocked rate of an air conditioner is implemented, including: establishing a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module; obtaining the actual wind speed and actual electrical parameters of the current fan drive module; and determining the actual dirty and blocked rate corresponding to the actual wind speed and the actual electrical parameters based on the dirty and blocked rate identification model, the actual wind speed, and the actual electrical parameters.

[0098] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0099] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying the dirty and blocked rate of an air conditioner, characterized in that: include: Establish a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module; Obtaining the actual wind speed and actual electrical parameters of the current fan drive module; Based on the dirt and blockage rate identification model, the actual wind speed and the actual electrical parameter, an actual dirt and blockage rate corresponding to the actual wind speed and the actual electrical parameter is determined.

2. The method for identifying the dirty and blocked rate of an air conditioner according to claim 1, characterized in that: The step of establishing a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan driving module, and the electrical parameters of the fan driving module specifically includes: Acquire multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters, wherein in the multiple groups of measurement data, the dirt and blockage rate, the wind speed and the electrical parameters correspond one to one; Counting multiple groups of the measurement data to generate a corresponding relationship table between the dirt and blockage rate, the wind speed and the electrical parameter; A dirt and blockage rate identification model between the dirt and blockage rate, the wind speed and the electrical parameter is established according to the corresponding relationship table.

3. The method for identifying the dirty and blocked rate of an air conditioner according to claim 2, characterized in that: The step of obtaining multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters specifically includes: Test each wind speed of the fan drive module at each air volume level under normal static pressure conditions; Fixing the fan driving module at one of the wind speeds, adjusting the dirtiness and blockage rate of the air conditioner, and measuring the electrical parameters corresponding to the fan driving module at each of the dirtiness and blockage rates; Repeat the previous step until multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters are obtained, wherein in the multiple groups of measurement data, the dirt and blockage rate, the wind speed and the electrical parameters correspond one to one.

4. The method for identifying the dirty and blocked rate of an air conditioner according to claim 2, characterized in that: The step of obtaining multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters specifically includes: Preset multiple dirtiness and blockage rate values ​​for the air conditioner; Fixing the air conditioner at one of the dirt and blockage rate values, adjusting the wind speed of the air conditioner, and measuring the electrical parameters corresponding to the fan drive module at each wind speed; Repeat the previous step until multiple groups of measurement data including the dirt and blockage rate, wind speed and electrical parameters are obtained, wherein in the multiple groups of measurement data, the dirt and blockage rate, the wind speed and the electrical parameters correspond one to one.

5. The method for identifying the dirty and blocked rate of an air conditioner according to claim 2, characterized in that: The step of establishing a dirty blockage rate identification model between the dirty blockage rate, the wind speed and the electrical parameter according to the corresponding relationship table specifically includes: According to the correspondence table between the dirty blockage rate, the wind speed and the electrical parameters, a dirty blockage rate recognition model between the dirty blockage rate, the wind speed and the electrical parameters is obtained through a preset learning algorithm and training data.

6. The method for identifying the dirty and blocked rate of an air conditioner according to any one of claims 1 to 5, characterized in that: In the step of establishing a dirty and blockage rate identification model between the dirty and blockage rate of the air conditioner, the wind speed of the fan driving module and the electrical parameters of the fan driving module, the electrical parameters of the fan driving module include the current value or power value of the fan driving module.

7. The method for identifying the dirty and blocked rate of an air conditioner according to any one of claims 2 to 5, characterized in that: The step of establishing a dirty and blocked rate identification model between the dirty and blocked rate of the air conditioner, the wind speed of the fan driving module, and the electrical parameters of the fan driving module also includes: An automated testing tool is established to automatically adjust the dirtiness and blockage rate of the air-conditioning condenser and the wind speed of the fan drive module under the current static pressure conditions, and detect the electrical parameters corresponding to the current dirtiness and blockage rate and the current wind speed, so as to realize the automatic test output of the correspondence table between the wind speed, dirtiness and blockage rate and the electrical parameters.

8. A device for identifying the dirty and blocked rate of an air conditioner, characterized in that: include: A first acquisition module is used to establish a dirty and blocked rate recognition model between the dirty and blocked rate of the air conditioner, the wind speed of the fan drive module, and the electrical parameters of the fan drive module; A second acquisition module is used to acquire the actual wind speed and actual electrical parameters of the current wind turbine driving module; A control module is used to determine the actual dirty blockage rate corresponding to the actual wind speed and the actual electrical parameter based on the dirty blockage rate identification model, the actual wind speed and the actual electrical parameter.

9. An air conditioner, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for identifying the dirty and blocked rate of the air conditioner as described in any one of claims 1 to 7 is implemented.

10. The air conditioner according to claim 9, characterized in that: The fan drive module includes a position sensorless and a permanent magnet synchronous motor.

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