Air conditioner fault detection method, device, air conditioner and electronic equipment

Abstract

The present invention provides an air conditioner fault detection method, device, air conditioner, and electronic device. The method comprises: obtaining multiple second shutdown spectrum data groups and second operating spectrum data groups; pairing the multiple second shutdown spectrum data groups with the multiple second operating spectrum data groups to obtain multiple comparison spectrum data groups, and selecting a target comparison spectrum data group from the multiple comparison spectrum data groups; sending the target comparison spectrum data group to the air conditioner cloud, performing matching analysis on the target comparison spectrum data group via the air conditioner cloud, and outputting the analysis results; based on the analysis results, determining whether there is an abnormality in the air conditioner operating system and prompting the user. The present invention can update the collected spectrum data groups in real time, thereby ensuring timeliness and accuracy. Furthermore, through cloud computing, air conditioner fault information can be more accurately detected and the user can be prompted in a timely manner, thereby improving the efficiency of air conditioner fault detection.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent air conditioners, and in particular to an air conditioner fault detection method and device, an air conditioner, and an electronic device. Background Art

[0002] In people's daily work and life, air conditioners provide people with convenient services such as cooling, heating, and dehumidification. However, the detection of air conditioner failures is not smart enough, and the air conditioner's action after detection is not perfect.

[0003] Therefore, how to improve the fault detection efficiency of air conditioners and promptly remind users when air conditioners fail is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] The present invention provides an air conditioner fault detection method, device, air conditioner and electronic equipment, which are used to solve the defect that the detection of air conditioner faults in the existing technology is not intelligent enough, thereby improving the fault detection efficiency of the air conditioner and promptly reminding the user when the air conditioner fails.

[0005] The present invention provides an air conditioner fault detection method, comprising:

[0006] Based on the environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition are obtained, as well as a plurality of second stop spectrum data groups in a stop state and a plurality of second running spectrum data groups in a running state under a second time condition are obtained;

[0007] confirming that the second time is later than the first time, and replacing each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; pairing the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and selecting a target comparison spectrum data group from the plurality of comparison spectrum data groups;

[0008] Sending the target comparison spectrum data group to the air conditioning cloud, performing matching analysis on the target comparison spectrum data group through the air conditioning cloud, and outputting the analysis results;

[0009] Based on the analysis result, it is determined whether there is an abnormality in the air-conditioning operation system and a prompt is given to the user.

[0010] According to an air conditioner fault detection method provided by the present invention, the method of acquiring multiple shutdown spectrum data groups of the air conditioner outdoor unit in a shutdown state and multiple operating spectrum data groups in an operating state in real time based on environmental conditions includes:

[0011] Acquire, based on environmental conditions, a plurality of first shutdown spectrum data groups of the air conditioner outdoor unit in a shutdown state at a first time, and a plurality of first operating spectrum data groups in a running state at a first time;

[0012] confirming a second time based on the first time and a preset statistical time interval;

[0013] Based on the environmental conditions and the second time, a plurality of second shutdown spectrum data groups of the air conditioner outdoor unit in the shutdown state at the second time and a plurality of second operating spectrum data groups in the operating state at the second time are obtained.

[0014] According to an air conditioner fault detection method provided by the present invention, based on environmental conditions and a second time, after acquiring a plurality of second shutdown spectrum data groups when the air conditioner outdoor unit is in a shutdown state at a second time, and a plurality of second operating spectrum data groups when the air conditioner outdoor unit is in an operating state at a second time, the method further includes:

[0015] replacing each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups;

[0016] Pairing the plurality of shutdown spectrum data groups with the plurality of operating spectrum data groups includes:

[0017] The plurality of second shutdown spectrum data groups are paired with the plurality of second operating spectrum data groups.

[0018] According to an air conditioner fault detection method provided by the present invention, the matching analysis of the target comparison spectrum data group is performed by the air conditioner cloud and the analysis result is output, including:

[0019] Matching and analyzing the target comparison spectrum data group with a preset standard spectrum group through the air conditioning cloud;

[0020] Acquire a reference spectrum data group corresponding to the target comparison spectrum data group in the standard spectrum group; wherein the reference outdoor temperature, the reference indoor temperature, and the reference user setting data of the reference spectrum data group correspond one-to-one to the second outdoor temperature, the second indoor temperature, and the second user setting data of the target comparison spectrum data group;

[0021] The difference data between the sound pressure level of the target comparison spectrum data group corresponding to the operating frequency and the sound pressure level of the reference spectrum data group corresponding to the operating frequency is obtained, and the difference data is output as an analysis result.

[0022] According to an air conditioner fault detection method provided by the present invention, determining whether there is an abnormality in the air conditioner operating system based on the analysis result and prompting the user includes:

[0023] Matching the operating frequency of the target comparison spectrum data group with a preset abnormality determination data group, and performing abnormality determination on the air-conditioning operation system based on the difference data;

[0024] When the difference data is greater than a first target preset threshold, or when the difference data is less than a second target preset threshold, it is confirmed that the air-conditioning operation system is abnormal and a prompt is given to the user.

[0025] According to an air conditioner fault detection method provided by the present invention, after matching the operating frequency of the target comparison spectrum data group with a preset abnormality determination data group and performing an abnormality determination on the air conditioner operating system based on the difference data, the method further includes:

[0026] When the difference data is smaller than or equal to the first target preset threshold and the difference data is greater than or equal to the second target preset threshold, it is confirmed that the air-conditioning operation system is normal.

[0027] According to the present invention, a method for detecting air conditioner faults, wherein the method confirms that the air conditioner operating system is abnormal and prompts the user, includes:

[0028] If the air-conditioning system is abnormal and the operating frequency is less than a preset critical value, the user is prompted that the compressor module is abnormal;

[0029] When the air-conditioning system is abnormal and the operating frequency is greater than or equal to a preset critical value, the user is prompted that the fan module is abnormal.

[0030] The present invention also provides an air conditioner fault detection device, comprising:

[0031] an acquisition unit, configured to acquire, based on environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition, as well as a plurality of second stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of second running spectrum data groups under a second time condition;

[0032] a replacing unit, configured to confirm that the second time is later than the first time, and replace each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; a comparing unit, configured to pair the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and select a target comparison spectrum data group from the plurality of comparison spectrum data groups;

[0033] a matching unit, configured to send the target comparison spectrum data group to the air conditioning cloud, perform matching analysis on the target comparison spectrum data group through the air conditioning cloud, and output an analysis result;

[0034] The determination unit is used to determine whether there is an abnormality in the air-conditioning operation system based on the analysis result and to prompt the user.

[0035] The present invention also provides an air conditioner, comprising an indoor unit, an outdoor unit, and a processor and a memory arranged in the indoor unit or the outdoor unit; and also comprising a program or instruction stored on the memory and executable on the processor, wherein when the program or instruction is executed by the processor, any of the above-mentioned air conditioner fault detection methods is executed.

[0036] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the above-described air conditioning fault detection methods is implemented.

[0037] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described air conditioning fault detection methods.

[0038] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned air-conditioning fault detection methods.

[0039] The air conditioner fault detection method, device, air conditioner, and electronic device provided by the present invention obtain multiple shutdown spectrum data groups of the air conditioner outdoor unit in the shutdown state and multiple operating spectrum data groups in the operating state based on environmental conditions, then compare the multiple shutdown spectrum data groups with the multiple operating spectrum data to obtain a target comparison spectrum data group, further match and analyze each target comparison spectrum data group through the air conditioner cloud, and output the analysis results. Finally, based on the analysis results, it is determined whether there is an abnormality in the air conditioner operating system and prompt the user. The present invention obtains the target comparison spectrum data group in real time and updates the collected spectrum data group in real time, so that the statistical data is continuously replaced, thereby ensuring timeliness and accuracy. In addition, the target comparison spectrum data group can be used to eliminate other factors that affect the air conditioner operating frequency and sound pressure level, and then analyzed and processed through the cloud, which can more accurately detect the air conditioner fault information and promptly prompt the user, thereby improving the efficiency of air conditioner fault detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to 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 any creative work.

[0041] Figure 1 This is one of the flow charts of the air conditioner fault detection method provided by the present invention;

[0042] Figure 2 This is the second flow chart of the air conditioner fault detection method provided by the present invention;

[0043] Figure 3 It is a structural schematic diagram of the air conditioner fault detection device provided by the present invention;

[0044] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0046] The following combination Figure 1-Figure 4 The present invention describes an air conditioner fault detection method, device, air conditioner and electronic equipment.

[0047] It should be noted that the air conditioner in the embodiment of the present invention can be a wall-mounted air conditioner, a cabinet-type air conditioner, a ceiling-mounted air conditioner, etc., and there is no limitation on the type of air conditioner.

[0048] The air conditioner fault detection method according to the embodiment of the present invention may be executed by a controller. Of course, in some embodiments, the air conditioner fault detection method according to the embodiment of the present invention may also be executed by a server. This is not a limitation on the execution entity. The air conditioner fault detection method according to the embodiment of the present invention will be described below using a controller as an example.

[0049] Reference Figure 1 The air conditioner fault detection method provided by the present invention comprises the following steps:

[0050] Step 110, based on environmental conditions, obtain multiple first shutdown spectrum data groups of the air-conditioning outdoor unit in a shutdown state under a first time condition and multiple first running spectrum data groups in a running state, as well as multiple second shutdown spectrum data groups in a shutdown state under a second time condition and multiple second running spectrum data groups in a running state.

[0051] Specifically, this embodiment is based on spectrum data sets under different environmental conditions when the air conditioner is in a stopped state and in a running state, which are respectively recorded as a stopped spectrum data set and a running spectrum data set.

[0052] It should be noted that the environmental conditions in this embodiment primarily refer to time and temperature conditions, such as data collection time, indoor temperature, and outdoor temperature. This embodiment acquires spectrum data sets in real time to eliminate the influence of time factors. Because the operating frequency of the air conditioner may vary due to environmental influences under different time conditions, real-time acquisition of spectrum data in both the shutdown and operating states can improve the accuracy and effectiveness of the spectrum data, thereby improving the accuracy of air conditioner operation anomaly detection.

[0053] It should also be noted that the operating spectrum data set represents the frequency and intensity of the air conditioner's operation (i.e., the sound pressure level corresponding to the frequency). It should be noted that sound pressure level is a logarithmic quantity representing sound intensity based on the human ear's response to changes in sound intensity. Research shows that the square of sound pressure is proportional to sound intensity, so sound intensity level can be converted to sound pressure level.

[0054] The sound pressure level in this embodiment is the characteristic of the sound intensity of the air conditioner operation that can be heard by the human ear. The operating status of the compressor module and the fan module of the air conditioner is represented by the sound pressure level at different operating frequencies.

[0055] Step 120: confirm that the second time is later than the first time, and replace each first shutdown spectrum data group and each first operating spectrum data group with the multiple second shutdown spectrum data groups and the multiple second operating spectrum data groups.

[0056] It should be noted that the detailed process of confirming that the second time is later than the first time and collecting spectrum data at the second time is: first, the first spectrum data is acquired based on environmental conditions (i.e., outdoor temperature, indoor temperature, etc.), and the first time, i.e., the first time, is recorded.

[0057] Then, the second time for collecting spectrum data is determined according to the preset statistical time interval, ie, the second time. It should be noted that the statistical time interval in this embodiment can be set to 1 hour, that is, spectrum data is collected once every hour.

[0058] Finally, according to the second time and the environmental conditions corresponding to the second time, the shutdown spectrum data group and the running spectrum data group of the air-conditioning outdoor unit at the second time are obtained.

[0059] To ensure the accuracy of air conditioner fault detection, this embodiment requires collecting spectrum data for the air conditioner in both the shutdown and operating states at different times. For example, spectrum data groups A1, A2, and A3 are set for the shutdown state, respectively, under outdoor temperatures of Tx1, Tx2, and Tx3; indoor temperatures of tx1, tx2, and tx3; times of Nx1, Nx2, and Nx3; and user-set data of Vx1, Vx2, and Vx3. Furthermore, spectrum data groups B1, B2, and B3 are set for outdoor temperatures of Ty1, Ty2, and Ty3; indoor temperatures of ty1, ty2, and ty3; times of Ny1, Ny2, and Ny3; and user-set data of Vy1, Vy2, and Vy3. Their operating frequencies are H1, H2, and H3, respectively, and their corresponding sound pressure levels are Hy1, Hy2, and Hy3, respectively.

[0060] Refer to Table 1-3 below:

[0061] Table 1:

[0062]

[0063] Table 2:

[0064]

[0065] Table 3:

[0066] Spectrum data frequency sound pressure level B1 H1, H2, H3… Hy1, Hy2, Hy3… B2 H1, H2, H3… Hy1, Hy2, Hy3… … … …

[0067] This embodiment acquires spectrum data of different outdoor temperatures, indoor temperatures, and user-set data in the operating state and the shutdown state at different times, thereby obtaining multiple sets of common data at different times, thereby ensuring that data matching the comparison spectrum data group can be found in the cloud data based on the real-time collected data, and then obtaining the difference with the cloud data, thereby ensuring the accuracy of air conditioning fault detection and improving the efficiency of data matching.

[0068] Furthermore, in this embodiment, the spectrum data set needs to be continuously updated over time. Specifically, as time progresses, more and more data is generated, potentially causing data confusion and mismatching between the acquired data and the time. Therefore, each time a new spectrum data set is acquired, the previously acquired shutdown spectrum data set and the previously acquired running spectrum data set need to be replaced.

[0069] As described above, this embodiment acquires spectrum data every hour, replacing and updating the data every hour. The updated spectrum data set is retained, and a comparative spectrum data set is obtained based on the updated spectrum data set for cloud computing and air conditioning anomaly analysis. By updating spectrum data in real time, this embodiment further improves the accuracy of spectrum data and the efficiency of obtaining comparative spectrum data sets, thereby improving the efficiency of cloud computing and air conditioning anomaly analysis.

[0070] Step 130 : Pair the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and select a target comparison spectrum data group from the plurality of comparison spectrum data groups.

[0071] Specifically, this embodiment matches data from the shutdown state with data from the running state. Specifically, based on the temperature conditions of any running spectrum data set, the spectrum and sound pressure level corresponding to the shutdown spectrum data set under that temperature condition are found. In other words, by controlling irrelevant variables, factors other than air conditioner operation are eliminated, and only the spectrum data sets in the shutdown and running states are considered.

[0072] By using the difference between the running state and the shutdown state as the comparison spectrum data group, other factors that affect the air conditioner's operating frequency and sound pressure level are eliminated, thereby improving the accuracy of the data and being able to more accurately detect air conditioner fault information.

[0073] Step 140 : Send the target comparison spectrum data set to the air-conditioning cloud, perform matching analysis on the target comparison spectrum data set through the air-conditioning cloud, and output the analysis result.

[0074] Specifically, the air conditioning cloud in this embodiment can be a remote Internet used for cloud computing. The comparison spectrum data group is analyzed through cloud data, and the indoor temperature, outdoor temperature and air conditioning user set temperature of the comparison spectrum data group are respectively matched one by one with the cloud data. The difference between the sound pressure level under the actual operating state corresponding to the comparison spectrum data group and the standard data on the cloud is obtained as the analysis result and output.

[0075] Step 150: Determine whether there is any abnormality in the air-conditioning operating system based on the analysis result and prompt the user.

[0076] Specifically, this embodiment determines whether there is an abnormality in the air conditioner's operating system based on the difference between the sound pressure level in the actual operating state and the standard data in the cloud at different frequencies of the air conditioner operation, so that the user can further determine whether there is an abnormality in the fan module and the compressor module. If an abnormality occurs, the user will be prompted in time. If it is normal, the operating state will be maintained and continued.

[0077] It should be noted that in this embodiment, when an abnormality occurs in the compressor module and fan module of the air conditioner, that is, the air conditioner fails, it can be directly displayed on the screen of the air conditioner indoor unit, and a fault light can be used to send a warning signal to prompt the user. A fault code can also be generated and sent to the user end. The user end can feed back the fault code to the maintenance personnel through the cloud for fault inspection.

[0078] It should be further explained that in order to enable maintenance personnel to clearly understand the fault location, the compressor module fault and the fan module fault can be set to different fault codes, such as the compressor module fault code is F1, and the fan fault code is F2.

[0079] The air conditioner fault detection method provided by the embodiment of the present invention obtains multiple shutdown spectrum data groups of the air conditioner outdoor unit in the shutdown state and multiple operating spectrum data groups in the operating state based on environmental conditions, then compares the multiple shutdown spectrum data groups with the multiple operating spectrum data to obtain a target comparison spectrum data group, further performs matching analysis on each target comparison spectrum data group through the air conditioner cloud, and outputs the analysis results. Finally, based on the analysis results, it is determined whether there is an abnormality in the air conditioner operating system and prompts the user. The present invention obtains the target comparison spectrum data group in real time and updates the collected spectrum data group in real time, so that the statistical data is continuously replaced, thereby ensuring timeliness and accuracy. In addition, the target comparison spectrum data group can be used to eliminate other factors that affect the air conditioner operating frequency and sound pressure level, and then analyzed and processed through the cloud, which can more accurately detect the air conditioner fault information and promptly prompt the user, thereby improving the efficiency of air conditioner fault detection.

[0080] Reference Figure 2 Based on the above embodiment, the matching analysis of the target comparison spectrum data group is performed through the air conditioning cloud, and the analysis results are output, including:

[0081] Step 210 : performing matching analysis on the target comparison spectrum data group and a preset standard spectrum group through the air conditioner cloud.

[0082] Step 220: Obtain a reference spectrum data group corresponding to the target comparison spectrum data group in the standard spectrum group; wherein the reference outdoor temperature, reference indoor temperature, and reference user setting data of the reference spectrum data group correspond one-to-one to the second outdoor temperature, second indoor temperature, and second user setting data of the target comparison spectrum data group.

[0083] Step 230 : Obtain the difference data between the sound pressure level of the target comparison spectrum data set corresponding to the operating frequency and the sound pressure level of the reference spectrum data set corresponding to the operating frequency, and output the difference data as the analysis result.

[0084] Specifically, this embodiment provides a process for performing data analysis using a target comparison spectrum data set and a reference spectrum data set.

[0085] The acquisition process of the target comparison spectrum data group is as follows: each collected shutdown spectrum data group is compared with the operating spectrum data group, and the difference calculation is performed on the data corresponding to the shutdown spectrum data group matched under the temperature conditions of the operating spectrum data group to obtain multiple comparison spectrum data groups.

[0086] It's important to note that in actual air conditioning operation, the intensity of the operating spectrum isn't solely determined by the air conditioner's operating frequency; it's also influenced by other factors, such as outdoor and indoor temperatures. Therefore, under the same external conditions, it's necessary to measure the difference in sound pressure levels between the air conditioner's running and stopped states, and then recalculate the difference between that and the standard value through the cloud.

[0087] From among the multiple comparison spectrum data sets, a data set under a specific temperature condition is selected as the target comparison spectrum data set K1. The values of the target comparison spectrum data set are the difference between the operating spectrum data set B1 and the shutdown spectrum data set A1 under this temperature condition. Specifically, based on the temperature value of B1, the value of A1 where Ty1 = Tx1, ty1 = Tx1, and Vy1 = Vx1 is found in the data of A1. The calculation K1 = B1 - A1 is then performed to generate data set K.

[0088] As shown in Tables 4 and 5 below.

[0089] Table 4:

[0090]

[0091]

[0092] Table 5:

[0093] Spectrum data frequency sound pressure level K1 H1, H2, H3… Hk1, Hk2, Hk3… K2 H1, H2, H3… Hk1, Hk2, Hk3… … … …

[0094] On the other hand, this embodiment provides a detailed process for matching spectrum data sets through the air conditioning cloud. First, the obtained comparison spectrum data set is matched with the standard spectrum data set preset in the cloud. That is, K1, K2, and K3 are matched with the corresponding data sets C1, C2, and C3 in the cloud data. Refer to Tables 6 and 7 below:

[0095] Table 6:

[0096]

[0097] Table 7:

[0098] Spectrum data frequency sound pressure level C1 H1, H2, H3… Hz1, Hz2, Hz3… C2 H1, H2, H3… Hz1, Hz2, Hz3… C3 H1, H2, H3… Hz1, Hz2, Hz3…

[0099] Then, using K1 as the target comparison spectrum data set, based on K1's corresponding Tk1, tk1, and Vk1, we find the corresponding standard spectrum data set C1 in the cloud data set with Ty1 = Tz1, ty1 = Tz1, Nk1 = Nz1, and Vy1 = Vz1 as the reference spectrum data set, thereby obtaining the sound pressure level of C1. In other words, we find the standard sound pressure level data of the cloud data under K1's outdoor temperature, indoor temperature, and user-set data.

[0100] Then, the difference X in the sound pressure level between the reference spectrum data group C1 and the target comparison spectrum data group K1 is calculated, and the difference X is output as an analysis result to perform fault analysis on the air conditioner.

[0101] Refer to Table 8 below:

[0102] frequency K1 C1 X 1Hz Hk1 Hz1 X1=Hk1-Hz1 2Hz Hk2 Hz2 X2=Hk2-Hz2 … … … …

[0103] This embodiment matches the data in the air-conditioning cloud with the comparison spectrum data group. On the premise of excluding time factors and external influencing factors, it can obtain the standard data of the sound pressure level of the cloud data under different outdoor temperatures, indoor temperatures and user-set data, and thus calculate the difference with the actual sound pressure level for fault analysis, thereby ensuring the accuracy of fault analysis and improving the efficiency of fault detection.

[0104] Based on the above embodiment, the method of determining whether there is an abnormality in the air-conditioning operation system based on the analysis result and prompting the user includes:

[0105] Matching the operating frequency of the target comparison spectrum data group with a preset abnormality determination data group, and performing abnormality determination on the air-conditioning operation system based on the difference data;

[0106] When the difference data is greater than a first target preset threshold, or when the difference data is less than a second target preset threshold, it is confirmed that the air-conditioning operation system is abnormal and a prompt is given to the user.

[0107] Specifically, it can be reflected as follows:

[0108] 1. When the operating frequency is lower than a preset critical value, the user is prompted that an abnormality has occurred in the press module;

[0109] 2. When the operating frequency is greater than or equal to a preset critical value, the user is prompted that an abnormality has occurred in the fan module.

[0110] When the difference data is smaller than or equal to the first target preset threshold and the difference data is greater than or equal to the second target preset threshold, it is confirmed that the air-conditioning operation system is normal.

[0111] Specifically, the above embodiment provides a detailed process for determining compressor module and fan module faults based on the difference X in sound pressure levels between the reference spectrum data group C1 and the target comparison spectrum data group K1 at different operating frequencies.

[0112] The first preset range of the air conditioner operating frequency is set to 1Hz-50Hz, mainly used to determine whether there is an abnormality in the compressor module; the second preset range is set to be greater than or equal to 50Hz, mainly used to determine whether there is an abnormality in the fan module. The first target preset threshold is set to 10DB, and the second target preset threshold is set to -10DB.

[0113] Based on the above difference X, the preset range and the preset threshold, the following situations can be classified:

[0114] When the operating frequency is 1-50Hz, if X>10DB, or X<-10DB, the press module is judged to be abnormal;

[0115] When the operating frequency is 1-50Hz, if 10DB≤X≤10DB, the press module is judged to be normal;

[0116] When the operating frequency is above 50Hz, if X>10DB, or X<-10DB, the fan module is determined to be abnormal;

[0117] When the operating frequency is above 50 Hz, if 10DB≤X≤10DB, the fan module is determined to be normal.

[0118] The details are shown in Table 9 below:

[0119]

[0120] This embodiment performs fault judgment on the sound pressure level difference at different operating frequencies, thereby more accurately detecting faults in the compressor module and fan module of the air conditioner. Different fault detection results are obtained corresponding to different operating frequencies and different differences, thereby improving the efficiency and accuracy of fault detection.

[0121] The air conditioning fault detection device provided by the present invention is described below. The air conditioning fault detection device described below and the air conditioning fault detection method described above can be referenced to each other.

[0122] Reference Figure 3 The air conditioner fault detection device provided by the present invention comprises:

[0123] The acquisition unit 310 is configured to acquire a plurality of shutdown spectrum data groups of the air conditioner outdoor unit in a shutdown state, and a plurality of operation spectrum data groups of the air conditioner outdoor unit in an operation state;

[0124] a comparing unit 320 configured to pair the plurality of shutdown spectrum data groups with the plurality of operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and select a target comparison spectrum data group from the plurality of comparison spectrum data groups;

[0125] The matching unit 330 is configured to send the target comparison spectrum data group to the air conditioning cloud, perform matching analysis on the target comparison spectrum data group through the air conditioning cloud, and output the analysis result;

[0126] The determination unit 340 is configured to determine whether there is any abnormality in the air-conditioning operation system based on the analysis result and to prompt the user.

[0127] The air conditioner fault detection device provided by the embodiment of the present invention obtains multiple shutdown spectrum data groups of the air conditioner outdoor unit in the shutdown state and multiple operating spectrum data groups in the operating state based on environmental conditions, then compares the multiple shutdown spectrum data groups with the multiple operating spectrum data to obtain a target comparison spectrum data group, further performs matching analysis on each target comparison spectrum data group through the air conditioner cloud, and outputs the analysis results. Finally, based on the analysis results, it is determined whether there is an abnormality in the air conditioner operating system and prompts the user. The present invention obtains the target comparison spectrum data group in real time and updates the collected spectrum data group in real time, so that the statistical data is continuously replaced, thereby ensuring timeliness and accuracy. In addition, the target comparison spectrum data group can be used to eliminate other factors that affect the air conditioner operating frequency and sound pressure level, and then analyzed and processed through the cloud, which can more accurately detect the fault information of the air conditioner and prompt the user in a timely manner, thereby improving the efficiency of air conditioner fault detection.

[0128] Based on the above embodiments, the matching unit is specifically used for:

[0129] Matching and analyzing the target comparison spectrum data group with a preset standard spectrum group through the air conditioning cloud;

[0130] Acquire a reference spectrum data group corresponding to the target comparison spectrum data group in the standard spectrum group; wherein the reference outdoor temperature, the reference indoor temperature, and the reference user setting data of the reference spectrum data group correspond one-to-one to the second outdoor temperature, the second indoor temperature, and the second user setting data of the target comparison spectrum data group;

[0131] The difference data between the sound pressure level of the target comparison spectrum data group corresponding to the operating frequency and the sound pressure level of the reference spectrum data group corresponding to the operating frequency is obtained, and the difference data is output as an analysis result.

[0132] Based on the above embodiment, the determination unit is specifically configured to:

[0133] Matching the operating frequency of the target comparison spectrum data group with a preset abnormality determination data group, and performing abnormality determination on the air-conditioning operation system based on the difference data;

[0134] When the difference data is greater than a first target preset threshold, or when the difference data is less than a second target preset threshold, it is confirmed that the air-conditioning operation system is abnormal and a prompt is given to the user.

[0135] When the difference data is smaller than or equal to the first target preset threshold and the difference data is greater than or equal to the second target preset threshold, it is confirmed that the air-conditioning operation system is normal.

[0136] Based on the above embodiment, the determination unit is specifically configured to:

[0137] If the air-conditioning system is abnormal and the operating frequency is less than a preset critical value, the user is prompted that the compressor module is abnormal;

[0138] When the air-conditioning system is abnormal and the operating frequency is greater than or equal to a preset critical value, the user is prompted that the fan module is abnormal.

[0139] An embodiment of the present invention further provides an air conditioner, comprising an indoor unit, an outdoor unit, and a processor and memory disposed in the indoor unit or the outdoor unit; the air conditioner also comprises a program or instruction stored in the memory and executable by the processor, wherein when the program or instruction is executed by the processor, the air conditioner fault detection method described above is performed. The method comprises:

[0140] Based on the environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition are obtained, as well as a plurality of second stop spectrum data groups in a stop state and a plurality of second running spectrum data groups in a running state under a second time condition are obtained;

[0141] confirming that the second time is later than the first time, and replacing each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; pairing the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and selecting a target comparison spectrum data group from the plurality of comparison spectrum data groups;

[0142] Sending the target comparison spectrum data group to the air conditioning cloud, performing matching analysis on the target comparison spectrum data group through the air conditioning cloud, and outputting the analysis results;

[0143] Based on the analysis result, it is determined whether there is an abnormality in the air-conditioning operation system and a prompt is given to the user.

[0144] Figure 4 An example of a physical structure diagram of an electronic device is shown below. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the air conditioner fault detection method, which includes:

[0145] Based on the environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition are obtained, as well as a plurality of second stop spectrum data groups in a stop state and a plurality of second running spectrum data groups in a running state under a second time condition are obtained;

[0146] confirming that the second time is later than the first time, and replacing each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; pairing the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and selecting a target comparison spectrum data group from the plurality of comparison spectrum data groups;

[0147] Sending the target comparison spectrum data group to the air conditioning cloud, performing matching analysis on the target comparison spectrum data group through the air conditioning cloud, and outputting the analysis results;

[0148] Based on the analysis result, it is determined whether there is an abnormality in the air-conditioning operation system and a prompt is given to the user.

[0149] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, 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. The computer software product is stored in a storage medium and includes several instructions for enabling 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 method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0150] On the other hand, the present invention further provides a computer program product, comprising a computer program. The computer program may be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the air conditioner fault detection method provided by the above methods, the method comprising:

[0151] Based on the environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition are obtained, as well as a plurality of second stop spectrum data groups in a stop state and a plurality of second running spectrum data groups in a running state under a second time condition are obtained;

[0152] confirming that the second time is later than the first time, and replacing each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; pairing the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and selecting a target comparison spectrum data group from the plurality of comparison spectrum data groups;

[0153] Sending the target comparison spectrum data group to the air conditioning cloud, performing matching analysis on the target comparison spectrum data group through the air conditioning cloud, and outputting the analysis results;

[0154] Based on the analysis result, it is determined whether there is an abnormality in the air-conditioning operation system and a prompt is given to the user.

[0155] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the air conditioner fault detection method provided by the above methods is implemented, and the method includes:

[0156] Based on the environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition are obtained, as well as a plurality of second stop spectrum data groups in a stop state and a plurality of second running spectrum data groups in a running state under a second time condition are obtained;

[0157] confirming that the second time is later than the first time, and replacing each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; pairing the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and selecting a target comparison spectrum data group from the plurality of comparison spectrum data groups;

[0158] Sending the target comparison spectrum data group to the air conditioning cloud, performing matching analysis on the target comparison spectrum data group through the air conditioning cloud, and outputting the analysis results;

[0159] Based on the analysis result, it is determined whether there is an abnormality in the air-conditioning operation system and a prompt is given to the user.

[0160] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0161] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0162] 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 various embodiments of the present invention.

Claims

1. A method for detecting air conditioner faults, characterized in that: include: Based on the environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition are obtained, as well as a plurality of second stop spectrum data groups in a stop state and a plurality of second running spectrum data groups in a running state under a second time condition are obtained; confirming that the second time is later than the first time, and replacing each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; pairing the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and selecting a target comparison spectrum data group from the plurality of comparison spectrum data groups; Sending the target comparison spectrum data group to the air conditioning cloud, performing matching analysis on the target comparison spectrum data group through the air conditioning cloud, and outputting the analysis results; Determine whether there is an abnormality in the air-conditioning operation system based on the analysis result and prompt the user; The matching analysis of the target comparison spectrum data group through the air-conditioning cloud and outputting the analysis results include: matching and analyzing the target comparison spectrum data group with a preset standard spectrum group through the air-conditioning cloud; obtaining a reference spectrum data group corresponding to the target comparison spectrum data group in the standard spectrum group; wherein the reference outdoor temperature, reference indoor temperature and reference user setting data of the reference spectrum data group correspond one-to-one to the second outdoor temperature, second indoor temperature and second user setting data of the target comparison spectrum data group; obtaining difference data between the sound pressure level of the operating frequency corresponding to the target comparison spectrum data group and the sound pressure level of the operating frequency corresponding to the reference spectrum data group, and outputting the difference data as the analysis result.

2. The air conditioner fault detection method according to claim 1, characterized in that: The determining whether there is an abnormality in the air-conditioning operation system based on the analysis result and prompting the user includes: Matching the operating frequency of the target comparison spectrum data group with a preset abnormality determination data group, and performing abnormality determination on the air-conditioning operation system based on the difference data; When the difference data is greater than a first target preset threshold, or when the difference data is less than a second target preset threshold, it is confirmed that the air-conditioning operation system is abnormal and a prompt is given to the user.

3. The air conditioner fault detection method according to claim 2, characterized in that: After matching the operating frequency of the target comparison spectrum data group with a preset abnormality determination data group and performing abnormality determination on the air-conditioning operation system based on the difference data, the method further includes: When the difference data is smaller than or equal to the first target preset threshold and the difference data is greater than or equal to the second target preset threshold, it is confirmed that the air-conditioning operation system is normal.

4. The air conditioner fault detection method according to claim 2, characterized in that: The method of confirming that the air-conditioning system is abnormal and prompting the user includes: If the air-conditioning system is abnormal and the operating frequency is less than the preset critical value, the user is prompted that the compressor module is abnormal; When the air-conditioning system is abnormal and the operating frequency is greater than or equal to a preset critical value, the user is prompted that the fan module is abnormal.

5. An air conditioner fault detection device, characterized in that: include: an acquisition unit, configured to acquire, based on environmental conditions, a plurality of first stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of first running spectrum data groups in a running state under a first time condition, as well as a plurality of second stop spectrum data groups of the air conditioner outdoor unit in a stop state and a plurality of second running spectrum data groups under a second time condition; a replacing unit, configured to confirm that the second time is later than the first time, and replace each first shutdown spectrum data group and each first operating spectrum data group with the plurality of second shutdown spectrum data groups and the plurality of second operating spectrum data groups; a comparing unit, configured to pair the plurality of second shutdown spectrum data groups with the plurality of second operating spectrum data groups to obtain a plurality of comparison spectrum data groups, and select a target comparison spectrum data group from the plurality of comparison spectrum data groups; a matching unit, configured to send the target comparison spectrum data group to the air conditioning cloud, perform matching analysis on the target comparison spectrum data group through the air conditioning cloud, and output the analysis result, including: performing matching analysis on the target comparison spectrum data group and a preset standard spectrum group through the air conditioning cloud; obtaining a reference spectrum data group corresponding to the target comparison spectrum data group in the standard spectrum group; wherein the reference outdoor temperature, reference indoor temperature, and reference user setting data of the reference spectrum data group correspond one-to-one to the second outdoor temperature, second indoor temperature, and second user setting data of the target comparison spectrum data group; obtaining difference data between the sound pressure level of the operating frequency corresponding to the target comparison spectrum data group and the sound pressure level of the operating frequency corresponding to the reference spectrum data group, and outputting the difference data as the analysis result; The determination unit is used to determine whether there is an abnormality in the air-conditioning operation system based on the analysis result and to prompt the user.

6. An air conditioner, characterized in that: It includes an indoor unit, an outdoor unit, and a processor and a memory arranged in the indoor unit or the outdoor unit; it also includes a program or instruction stored in the memory and executable on the processor, and when the program or instruction is executed by the processor, the air conditioning fault detection method according to any one of claims 1 to 4 is executed.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the air conditioning fault detection method according to any one of claims 1 to 4 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the air conditioning fault detection method according to any one of claims 1 to 4 is implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the air conditioning fault detection method according to any one of claims 1 to 4 is implemented.

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