Method, system and equipment for predicting overall performance of water heater, medium and program product

Abstract

The invention provides a water heater whole machine performance prediction method, system and device, a medium and a program product, and the prediction method comprises the steps that a draught fan in a water heater whole machine is tested, performance data of the draught fan are obtained, and the performance data comprise at least one of the test vacuum degree, the test flow and the test rotating speed; the whole water heater is simulated based on the test flow, and the simulation vacuum degree corresponding to the test flow is obtained; comparing the test vacuum degree with the simulation vacuum degree to obtain a comparison result; obtaining a target fitting relation curve corresponding to the comparison result; the whole water heater flow is obtained based on the target fitting relation curve; and predicting the water heater whole machine performance based on the water heater whole machine flow. According to the method, the test data of the fan in the whole water heater is combined with the simulation data of the whole water heater, the flow of the whole water heater can be accurately obtained, errors between the test data and actual data are avoided, the simulation difficulty is reduced, and accurate and rapid prediction of the performance of the whole water heater is achieved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of water heater performance prediction, and in particular to a method, system, device, medium and program product for predicting the performance of a water heater. Background Art

[0002] The flow rate of the water heater is an important parameter in the combustion of the whole machine. It must be in a certain ratio with the gas to ensure the combustion efficiency. The performance of the water heater is usually predicted by the flow rate of the water heater. At present, the flow rate of the water heater is mainly determined by performance testing or whole machine simulation.

[0003] The shortcomings of testing the whole machine flow rate through the performance test bench: the water heater needs to burn when it actually works. When the water heater burns, the waste gas with high temperature flows out of the water heater. The high temperature waste gas cannot be directly discharged into the whole machine test bench. When the water heater is not burning and the whole machine flow rate is tested, there is a difference between the whole machine air volume and the whole machine flow rate during combustion, resulting in a large error between the whole machine performance flow parameters tested in the test and the actual ones, and the performance test data is inaccurate;

[0004] The shortcomings of analyzing the whole machine flow by simulation method: the whole flow channel of the water heater contains porous media components such as heat exchangers and silencers, whose resistance cannot be analyzed by simulation analysis methods, and the error by testing methods is large. In addition, analyzing the whole machine flow by simulation analysis method requires modeling of the high-speed fan in the whole machine flow channel, and the simulation calculation amount is large. In summary, the error of analyzing the whole machine flow by simulation analysis method is large, and the simulation resource investment is large. Summary of the invention

[0005] The technical problem to be solved by the present disclosure is to overcome the defects of inaccurate performance prediction data, large errors and great simulation difficulty in the prior art of testing the whole machine flow through a performance test bench or analyzing the whole machine flow through simulation, and to provide a method, system, device, medium and program product for predicting the performance of the whole water heater.

[0006] The present invention solves the above technical problems through the following technical solutions:

[0007] A first aspect of the present disclosure provides a method for predicting the performance of a water heater, the method comprising:

[0008] Testing a fan in the water heater to obtain performance data of the fan, wherein the performance data includes at least one of a test vacuum degree, a test flow rate, and a test speed;

[0009] Simulating the water heater based on the test flow rate to obtain a simulated vacuum degree corresponding to the test flow rate;

[0010] Comparing the test vacuum degree with the simulated vacuum degree to obtain a comparison result;

[0011] Acquire a target fitting relationship curve corresponding to the comparison result;

[0012] Obtaining the whole flow rate of the water heater based on the target fitting relationship curve;

[0013] The performance of the water heater is predicted based on the water heater flow rate.

[0014] Preferably, the prediction method further comprises:

[0015] Obtain a fitting relationship curve between the test rotation speed and the test flow rate.

[0016] Preferably, the prediction method further comprises:

[0017] Performing noise spectrum test and analysis on the water heater as a whole to obtain the base frequency of the water heater as a whole;

[0018] The actual rotation speed of the fan corresponding to the operation of the water heater is obtained based on the fundamental frequency of the water heater.

[0019] Preferably, the step of predicting the performance of the water heater based on the water heater flow rate comprises:

[0020] In response to the water heater whole machine flow being greater than or equal to a preset whole machine flow, it is determined that the water heater whole machine performance is normal.

[0021] Preferably, the step of predicting the performance of the water heater based on the water heater flow rate also includes:

[0022] In response to the water heater whole machine flow being less than a preset whole machine flow, it is determined that the water heater whole machine performance is abnormal.

[0023] Preferably, the step of obtaining a target fitting relationship curve corresponding to the comparison result comprises:

[0024] In response to the comparison result being that the simulated vacuum degree is greater than the tested vacuum degree, the target fitting relationship curve is a first fitting relationship curve;

[0025] The step of obtaining the whole flow rate of the water heater based on the target fitting relationship curve comprises:

[0026] Acquire the whole flow rate of the water heater based on the first fitting relationship curve;

[0027] or,

[0028] The step of obtaining a target fitting relationship curve corresponding to the comparison result comprises:

[0029] In response to the comparison result being that the simulated vacuum degree is less than or equal to the test vacuum degree, the target fitting relationship curve is a second fitting relationship curve;

[0030] The step of obtaining the whole flow rate of the water heater based on the target fitting relationship curve comprises:

[0031] The whole flow rate of the water heater is obtained based on the second fitting relationship curve.

[0032] A second aspect of the present disclosure provides a prediction system for the performance of a water heater, the prediction system comprising:

[0033] A test module, used to test the fan in the water heater to obtain performance data of the fan, wherein the performance data includes at least one of a test vacuum degree, a test flow rate and a test speed;

[0034] A first acquisition module, configured to simulate the water heater based on the test flow rate, and acquire a simulated vacuum degree corresponding to the test flow rate;

[0035] A comparison module, used for comparing the test vacuum degree with the simulated vacuum degree to obtain a comparison result;

[0036] A second acquisition module, used to acquire a target fitting relationship curve corresponding to the comparison result;

[0037] A third acquisition module is used to acquire the flow rate of the water heater based on the target fitting relationship curve;

[0038] The prediction module is used to predict the performance of the water heater based on the flow rate of the water heater.

[0039] Preferably, the prediction system further comprises:

[0040] The fourth acquisition module is used to obtain a fitting relationship curve between the test rotation speed and the test flow rate.

[0041] Preferably, the prediction system further comprises:

[0042] An analysis module, used to perform noise spectrum test and analysis on the water heater as a whole to obtain the fundamental frequency of the water heater as a whole;

[0043] The fifth acquisition module is used to acquire the actual rotation speed of the fan corresponding to the operation of the water heater based on the fundamental frequency of the water heater.

[0044] Preferably, the prediction module comprises:

[0045] The first determination unit is used to determine that the performance of the water heater is normal in response to the water heater flow being greater than or equal to a preset flow.

[0046] Preferably, the prediction module further includes:

[0047] The second determination unit is configured to determine that the performance of the water heater is abnormal in response to the water heater flow rate being less than a preset water heater flow rate.

[0048] Preferably, the second acquisition module is specifically configured to respond to the comparison result that the simulation vacuum degree is greater than the test vacuum degree, and the target fitting relationship curve is the first fitting relationship curve;

[0049] The third acquisition module is specifically used to acquire the flow rate of the water heater based on the first fitting relationship curve;

[0050] or,

[0051] The second acquisition module is specifically configured to respond to the comparison result that the simulation vacuum degree is less than or equal to the test vacuum degree, and the target fitting relationship curve is a second fitting relationship curve;

[0052] The third acquisition module is specifically used to acquire the flow rate of the water heater based on the second fitting relationship curve.

[0053] A third aspect of the present disclosure provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and used to run on the processor, wherein the processor implements the method for predicting the performance of the water heater as described in the first aspect when executing the computer program.

[0054] A fourth aspect of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for predicting the performance of the entire water heater described in the first aspect is implemented.

[0055] A fifth aspect of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements the method for predicting the performance of a water heater as described in the first aspect.

[0056] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present disclosure.

[0057] The positive and progressive effects of this disclosure are:

[0058] The present invention combines the test data of the fan in the water heater whole machine with the simulation data of the water heater whole machine, which can accurately obtain the flow rate of the water heater whole machine, avoid the error between the test data and the actual data, reduce the simulation difficulty, and realize accurate and rapid prediction of the performance of the water heater whole machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1This is a flow chart of a method for predicting the performance of a water heater as provided in Example 1 of the present disclosure.

[0060] Figure 2 A schematic diagram of the performance data of the fan in the water heater provided in Examples 1 and 2 of the present disclosure.

[0061] Figure 3 A schematic diagram of the modules of the water heater overall performance prediction system provided in Example 2 of the present disclosure.

[0062] Figure 4 This is a schematic diagram of the structure of an electronic device for implementing a method for predicting the performance of a water heater according to Embodiment 3 of the present disclosure. DETAILED DESCRIPTION

[0063] The present disclosure is further described below by way of examples, but the present disclosure is not limited to the scope of the examples.

[0064] Prefixes such as "first" and "second" are used in the embodiments of the present disclosure only to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects. The use of prefixes such as ordinal numbers to distinguish description objects in the embodiments of the present disclosure does not constitute a limitation on the described objects. For the statement of the described objects, please refer to the description in the context of the claims or embodiments, and no unnecessary limitation should be constituted due to the use of such prefixes. In addition, in the description of the present embodiment, unless otherwise specified, the meaning of "plurality" is two or more.

[0065] In the embodiments of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0066] Example 1

[0067] Figure 1 A flow chart of a method for predicting the performance of a water heater provided in Example 1 of the present disclosure, such as Figure 1 As shown, the prediction method includes:

[0068] S1. Testing the fan in the water heater to obtain performance data of the fan, where the performance data includes at least one of a test vacuum degree, a test flow rate, and a test speed;

[0069] In this embodiment, the performance data of the fan applied to the water heater is first tested through experiments. During the test, the working condition of the fan is the same as the power of the whole machine. The performance data includes the test vacuum degree, test flow rate and corresponding test speed under different apertures. Table 1 shows the performance data of a fan applied to the water heater. The speed of the fan of the water heater has the following characteristics. As shown in Table 1, with hole 19 as the dividing line, from holes 19 to holes 3, the test speed of the fan gradually increases with the increase of the test vacuum degree; from holes 19 to holes 50, the test speed of the fan gradually increases with the decrease of the vacuum degree. For the fan, the test vacuum degree corresponding to the minimum test speed RPM0 of the fan is defined as H0, and the corresponding test flow rate of the fan is Q0.

[0070] Table 1

[0071]

[0072] S2. Simulate the water heater based on the test flow rate to obtain a simulated vacuum degree corresponding to the test flow rate;

[0073] In this embodiment, the whole water heater is simulated and analyzed. When simulating the whole water heater, it is not necessary to add porous media components such as HEPA and silencer cotton, and it is not necessary to model the fan in the whole water heater. It is only necessary to simulate and analyze the simple components in the whole water heater. When the flow rate of this simple flow channel is Q0, the corresponding simulation vacuum degree is H. 整 ;

[0074] S3, comparing the test vacuum degree with the simulated vacuum degree to obtain a comparison result;

[0075] S4, obtaining a target fitting relationship curve corresponding to the comparison result;

[0076] S5, obtaining the flow rate of the water heater based on the target fitting relationship curve;

[0077] S6. Predict the performance of the water heater based on the water heater flow rate.

[0078] In an optional embodiment, the prediction method further includes:

[0079] Obtain the fitting relationship curve between the test speed and the test flow rate.

[0080] In this embodiment, the performance test data of the fan is analyzed, and the aperture corresponding to the lowest test speed RPM0 of the fan is used as the reference. The speed RPM and flow rate corresponding to the aperture greater than this can be fitted into the following formula (1): Q = A 1* RPM 2+B1*RPM+C1(1)(where Q represents the fitted flow rate of the fan, and A1, B1, and C1 are all coefficients). The speed and flow rate corresponding to the aperture smaller than this aperture (i.e., the aperture corresponding to the fan's lowest test speed RPM0) can be fitted into the following formula (1): Q=A 2* RPM 2 +B 2* RPM+C2 (2), (where A2, B2, and C2 are all coefficients); the speed and flow fitting data corresponding to the reference aperture are as follows Figure 2 As shown;

[0081] In an optional embodiment, the prediction method further includes:

[0082] Conduct noise spectrum test and analysis on the water heater to obtain the base frequency of the water heater;

[0083] The actual speed of the fan corresponding to the operation of the water heater is obtained based on the base frequency of the water heater.

[0084] In this embodiment, the noise spectrum test and analysis of the water heater is carried out, and the fundamental frequency of the water heater is analyzed to be ω, and the actual speed RPM of the fan corresponding to the operation of the water heater is calculated. 整 =60*ω.

[0085] In an optional embodiment, step S6 includes:

[0086] In response to the water heater whole machine flow being greater than or equal to a preset whole machine flow, it is determined that the water heater whole machine performance is normal.

[0087] In this embodiment, the preset whole machine flow is set according to the actual situation and is not specifically limited here.

[0088] In an optional embodiment, step S6 further includes:

[0089] In response to the water heater whole machine flow being less than a preset whole machine flow, it is determined that the water heater whole machine performance is abnormal.

[0090] In an optional embodiment, step S4 includes:

[0091] In response to the comparison result that the simulated vacuum degree is greater than the tested vacuum degree, the target fitting relationship curve is a first fitting relationship curve;

[0092] Step S5 includes:

[0093] Obtaining the entire flow rate of the water heater based on the first fitting relationship curve;

[0094] In an optional embodiment, step S4 includes:

[0095] In response to the comparison result being that the simulated vacuum degree is less than or equal to the tested vacuum degree, the target fitting relationship curve is a second fitting relationship curve;

[0096] Step S5 includes:

[0097] The whole flow rate of the water heater is obtained based on the second fitting relationship curve.

[0098] In this embodiment, when H 整 When >H0, it means that the resistance of the water heater must be greater than the reference aperture, the speed of the water heater corresponds to the speed greater than the reference aperture of the fan, and the target fitting relationship curve is the first fitting relationship curve (that is, the target fitting relationship curve is the above formula (2)). Therefore, the expression of the water heater flow rate is: Q 整 =A 2* RPM 整 2 +B 2* RPM 整 +C2; (where Q 整 Indicates the flow rate of the water heater, RPM 整 Indicates the speed of the water heater, A2, B2, C2 are all coefficients); on the contrary, when H 整 When ≤H0, it means that the resistance of the water heater must be smaller than the reference aperture, the corresponding speed of the water heater corresponds to the speed smaller than the reference speed of the fan, and the target fitting relationship curve is the second fitting relationship curve (that is, the target fitting relationship curve is the above formula (1)). Therefore, the expression of the water heater flow rate is: Q 整 =A 1* RPM 整 2 +B 1* RPM 整 +C1, (where A1, B1, and C1 are all coefficients).

[0099] This embodiment combines the test data of the fan in the water heater with the simulation data of the water heater, which can accurately obtain the flow of the water heater, avoid the error between the test data and the actual data, reduce the simulation difficulty, and realize accurate and rapid prediction of the performance of the water heater.

[0100] Example 2

[0101] Corresponding to the aforementioned embodiment of a method for predicting the performance of a water heater as a whole, the present disclosure also provides an embodiment of a system for predicting the performance of a water heater as a whole.

[0102] Figure 3 A schematic diagram of a module of a water heater performance prediction system provided in Embodiment 2 of the present disclosure, such as Figure 3 As shown, the prediction system includes:

[0103] The test module 21 is used to test the fan in the water heater to obtain performance data of the fan, where the performance data includes at least one of a test vacuum degree, a test flow rate and a test speed;

[0104] In this embodiment, the performance data of the fan applied to the water heater is first tested through experiments. During the test, the working condition of the fan is the same as the power of the whole machine. The performance data includes the test vacuum degree, test flow rate and corresponding test speed under different apertures. Table 1 in Example 1 is the performance data of a fan applied to the water heater. The speed of the fan of the water heater has the following characteristics, as shown in Table 1 in Example 1. With 19 holes as the dividing line, from 19 holes to 3 holes, the test speed of the fan gradually increases with the increase of the test vacuum degree; from 19 holes to 50 holes, the test speed of the fan gradually increases with the decrease of the vacuum degree. For the fan, the test vacuum degree corresponding to the minimum test speed RPM0 of the fan is defined as H0, and the corresponding test flow rate of the fan is Q0.

[0105] A first acquisition module 22 is used to simulate the water heater based on the test flow rate and obtain a simulated vacuum degree corresponding to the test flow rate;

[0106] In this embodiment, the whole water heater is simulated and analyzed. When simulating the whole water heater, it is not necessary to add porous media components such as HEPA and silencer cotton, and it is not necessary to model the fan in the whole water heater. It is only necessary to simulate and analyze the simple components in the whole water heater. When the flow rate of this simple flow channel is Q0, the corresponding simulation vacuum degree is H. 整 ;

[0107] A comparison module 23 is used to compare the test vacuum degree with the simulated vacuum degree to obtain a comparison result;

[0108] A second acquisition module 24 is used to acquire a target fitting relationship curve corresponding to the comparison result;

[0109] The third acquisition module 25 is used to obtain the flow rate of the water heater based on the target fitting relationship curve;

[0110] The prediction module 26 is used to predict the performance of the water heater based on the flow rate of the water heater.

[0111] In an optional embodiment, the prediction system further includes:

[0112] The fourth acquisition module is used to obtain a fitting relationship curve between the test rotation speed and the test flow rate.

[0113] In this embodiment, the performance test data of the fan is analyzed, and the aperture corresponding to the lowest test speed RPM0 of the fan is used as the reference. The speed RPM and flow rate corresponding to the aperture greater than this can be fitted into the following formula (1): Q = A1* RPM 2 +B1*RPM+C1(1)(where Q represents the fitted flow rate of the fan, and A1, B1, and C1 are all coefficients). The speed and flow rate corresponding to the aperture smaller than this aperture (i.e., the aperture corresponding to the fan's lowest test speed RPM0) can be fitted into the following formula (1): Q=A 2* RPM 2 +B 2* RPM+C2 (2), (where A2, B2, and C2 are all coefficients); the speed and flow fitting data corresponding to the reference aperture are as follows Figure 2 As shown;

[0114] In an optional embodiment, the prediction system further includes:

[0115] An analysis module is used to perform noise spectrum test and analysis on the water heater as a whole to obtain the fundamental frequency of the water heater as a whole;

[0116] The fifth acquisition module is used to acquire the actual rotation speed of the fan corresponding to the operation of the water heater based on the fundamental frequency of the water heater.

[0117] In this embodiment, the noise spectrum test and analysis of the water heater is carried out, and the fundamental frequency of the water heater is analyzed to be ω, and the actual speed RPM of the fan corresponding to the operation of the water heater is calculated. 整 =60*ω.

[0118] In an optional embodiment, the prediction module includes:

[0119] The first determination unit is used to determine that the performance of the water heater is normal in response to the water heater flow being greater than or equal to a preset flow.

[0120] In this embodiment, the preset whole machine flow is set according to the actual situation and is not specifically limited here.

[0121] In an optional embodiment, the prediction module further includes:

[0122] The second determination unit is configured to determine that the performance of the water heater is abnormal in response to the water heater flow rate being less than a preset water heater flow rate.

[0123] In an optional embodiment, the second acquisition module is specifically configured to respond to the comparison result that the simulated vacuum degree is greater than the test vacuum degree, and the target fitting relationship curve is the first fitting relationship curve;

[0124] A third acquisition module is specifically used to acquire the flow rate of the water heater based on the first fitting relationship curve;

[0125] In an alternative embodiment,

[0126] A second acquisition module is specifically configured to, in response to the comparison result being that the simulation vacuum degree is less than or equal to the test vacuum degree, set the target fitting relationship curve to be a second fitting relationship curve;

[0127] The third acquisition module is specifically used to acquire the whole flow rate of the water heater based on the second fitting relationship curve.

[0128] In this embodiment, when H 整 When >H0, it means that the resistance of the water heater must be greater than the reference aperture, the speed of the water heater corresponds to the speed greater than the reference aperture of the fan, and the target fitting relationship curve is the first fitting relationship curve (that is, the target fitting relationship curve is the above formula (2)). Therefore, the expression of the water heater flow rate is: Q 整 =A 2* RPM 整 2 +B 2* RPM 整 +C2; (where Q 整 Indicates the flow rate of the water heater, RPM 整 Indicates the speed of the water heater, A2, B2, C2 are all coefficients); on the contrary, when H 整 When ≤H0, it means that the resistance of the water heater must be smaller than the reference aperture, the corresponding speed of the water heater corresponds to the speed smaller than the reference speed of the fan, and the target fitting relationship curve is the second fitting relationship curve (that is, the target fitting relationship curve is the above formula (1)). Therefore, the expression of the water heater flow rate is: Q 整 =A 1* RPM 整 2 +B 1* RPM 整 +C1, (where A1, B1, and C1 are all coefficients).

[0129] This embodiment combines the test data of the fan in the water heater with the simulation data of the water heater, which can accurately obtain the flow of the water heater, avoid the error between the test data and the actual data, reduce the simulation difficulty, and realize accurate and rapid prediction of the performance of the water heater.

[0130] As for the system embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The system embodiment described above is only illustrative, wherein the units described as separate components may or may not be physically separated, and the components as units may or may not be physical units, that is, 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 disclosed solution.

[0131] Example 3

[0132] Figure 4 This is a schematic diagram of the structure of an electronic device shown in Embodiment 3 of the present disclosure, wherein the electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor, and when the processor executes the computer program, the method for predicting the performance of the whole water heater described in any of the above embodiments is implemented. Figure 4 The electronic device 90 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0133] like Figure 4 As shown, the electronic device 90 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 90 may include, but are not limited to: at least one processor 91, at least one memory 92, and a bus 93 connecting different system components (including the memory 92 and the processor 91).

[0134] The bus 93 includes a data bus, an address bus, and a control bus.

[0135] The memory 92 may include a volatile memory, such as a random access memory (RAM) 921 and / or a cache memory 922 , and may further include a read only memory (ROM) 923 .

[0136] The memory 92 may also include a program tool 925 (or utility) having a set (at least one) of program modules 924, such program modules 924 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0137] The processor 91 executes various functional applications and data processing by running the computer program stored in the memory 92, such as the method for predicting the performance of the water heater provided in any of the above embodiments.

[0138] The electronic device 90 may also communicate with one or more external devices 94 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 95. Furthermore, the electronic device 90 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 96. Figure 4As shown, the network adapter 96 communicates with other modules of the electronic device 90 via the bus 93. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 90, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0139] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0140] Example 4

[0141] Embodiment 4 of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the method for predicting the performance of the water heater provided in any of the above embodiments is implemented.

[0142] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0143] Example 5

[0144] Embodiment 5 of the present disclosure further provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for predicting the performance of a water heater.

[0145] Among them, the program code for executing the computer program product of the present disclosure can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0146] Although the specific embodiments of the present disclosure are described above, those skilled in the art should understand that this is only an example, and the protection scope of the present disclosure is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present disclosure, but these changes and modifications all fall within the protection scope of the present disclosure.

Claims

1. A method for predicting the performance of a water heater, characterized in that: The prediction method comprises: Testing a fan in the water heater to obtain performance data of the fan, wherein the performance data includes at least one of a test vacuum degree, a test flow rate, and a test speed; Simulating the water heater based on the test flow rate to obtain a simulated vacuum degree corresponding to the test flow rate; Comparing the test vacuum degree with the simulated vacuum degree to obtain a comparison result; Acquire a target fitting relationship curve corresponding to the comparison result; Obtaining the whole flow rate of the water heater based on the target fitting relationship curve; The performance of the water heater is predicted based on the water heater flow rate.

2. The method for predicting the performance of a water heater as claimed in claim 1, characterized in that: The prediction method further comprises: Obtain a fitting relationship curve between the test rotation speed and the test flow rate.

3. The method for predicting the performance of a water heater as claimed in claim 1, characterized in that: The prediction method further comprises: Performing noise spectrum test and analysis on the water heater as a whole to obtain the base frequency of the water heater as a whole; The actual rotation speed of the fan corresponding to the operation of the water heater is obtained based on the fundamental frequency of the water heater.

4. The method for predicting the performance of a water heater as claimed in claim 1, characterized in that: The step of predicting the performance of the water heater based on the water heater flow rate comprises: In response to the water heater whole machine flow being greater than or equal to a preset whole machine flow, it is determined that the water heater whole machine performance is normal.

5. The method for predicting the performance of a water heater as claimed in claim 1, characterized in that: The step of predicting the performance of the water heater based on the water heater flow rate also includes: In response to the water heater whole machine flow being less than a preset whole machine flow, it is determined that the water heater whole machine performance is abnormal.

6. The method for predicting the performance of a water heater as claimed in claim 1, characterized in that: The step of obtaining a target fitting relationship curve corresponding to the comparison result comprises: In response to the comparison result being that the simulated vacuum degree is greater than the tested vacuum degree, the target fitting relationship curve is a first fitting relationship curve; The step of obtaining the whole flow rate of the water heater based on the target fitting relationship curve comprises: Acquire the whole flow rate of the water heater based on the first fitting relationship curve; or, The step of obtaining a target fitting relationship curve corresponding to the comparison result comprises: In response to the comparison result being that the simulated vacuum degree is less than or equal to the test vacuum degree, the target fitting relationship curve is a second fitting relationship curve; The step of obtaining the whole flow rate of the water heater based on the target fitting relationship curve comprises: The whole flow rate of the water heater is obtained based on the second fitting relationship curve.

7. A prediction system for the performance of a water heater, characterized in that: The prediction system comprises: A test module, used to test the fan in the water heater to obtain performance data of the fan, wherein the performance data includes at least one of a test vacuum degree, a test flow rate and a test speed; A first acquisition module, configured to simulate the water heater based on the test flow rate, and acquire a simulated vacuum degree corresponding to the test flow rate; A comparison module, used for comparing the test vacuum degree with the simulated vacuum degree to obtain a comparison result; A second acquisition module, used to acquire a target fitting relationship curve corresponding to the comparison result; A third acquisition module is used to acquire the flow rate of the water heater based on the target fitting relationship curve; The prediction module is used to predict the performance of the water heater based on the flow rate of the water heater.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and used to run on the processor, characterized in that: When the processor executes the computer program, the method for predicting the performance of the water heater as claimed in any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for predicting the performance of the water heater as claimed in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for predicting the performance of a water heater as claimed in any one of claims 1 to 6 is implemented.

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