Air conditioner outdoor unit noise prediction method and device, air conditioner, and storage medium

Abstract

The application provides a noise prediction method and device for an air conditioner outdoor unit, an air conditioner and a storage medium. The prediction method comprises the following steps: obtaining target information of a first detection position and a second detection position of the air conditioner, wherein the target information comprises a noise value and displacement information; calculating a noise correlation coefficient of the first detection position and the second detection position according to the target information; obtaining a fitting coefficient according to the noise correlation coefficient; and calculating a noise prediction value according to the fitting coefficient and the displacement information; wherein the first detection position is the position of a compressor, and the second detection position is different from the first detection position; the displacement information of the first detection position is the rotating speed of the compressor; the displacement information of the second detection position is the vibration acceleration of the second detection position; the noise value comprises a first frequency band noise value and a second frequency band noise value; and the first frequency band noise value is greater than the second frequency band noise value. The prediction method has low requirements on the prediction environment, high accuracy, and can quickly and accurately obtain the noise prediction value.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, and more specifically, to a method, apparatus, air conditioner, and storage medium for predicting the noise of an outdoor air conditioning unit. Background Technology

[0002] With fierce competition in the home appliance market and rising living standards, users are increasingly prioritizing the comfort of their appliances. Currently, noise control in air conditioners has become a key focus for improving comfort. Air conditioner noise primarily originates from the outdoor unit. Existing outdoor unit noise testing requires a demanding environment, necessitating anechoic chambers. Furthermore, the testing equipment is expensive, the testing cycle is long, and both new outdoor unit development and product modifications require retesting, failing to meet the demands of product development. Summary of the Invention

[0003] To address the aforementioned problems, this invention provides a method, apparatus, air conditioner, and storage medium for predicting the noise of an outdoor air conditioning unit. It has low requirements for the prediction environment, the noise prediction method is simple, and the accuracy is high. It can quickly and accurately obtain the predicted noise value of a product, providing assistance in rapidly estimating product performance during the product development stage.

[0004] Therefore, the first objective of this invention is to provide a method for predicting the noise of an outdoor air conditioning unit.

[0005] A second objective of the present invention is to provide an air conditioner noise prediction device.

[0006] A third objective of this invention is to provide an air conditioner.

[0007] A fourth objective of this invention is to provide a readable storage medium.

[0008] To achieve the first objective of this invention, the technical solution of this invention provides a method for predicting the noise of an outdoor unit of an air conditioner. The prediction method includes: acquiring target information of a first detection position and a second detection position of the air conditioner, the target information including: noise value and displacement information; calculating the noise correlation coefficient between the first detection position and the second detection position based on the target information; obtaining a fitting coefficient based on the noise correlation coefficient; and calculating a predicted noise value based on the fitting coefficient and the displacement information. The first detection position is the position of the compressor, and the second detection position is different from the first detection position. The displacement information of the first detection position is the compressor speed. The displacement information of the second detection position is the vibration acceleration of the second detection position. The noise value includes: a noise value in a first frequency band and a noise value in a second frequency band; the noise value in the first frequency band is greater than the noise value in the second frequency band.

[0009] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: This invention obtains target information of the detection location of the outdoor unit of the air conditioner, calculates the noise correlation coefficient, fitting coefficient and noise prediction value, has low requirements for the test environment of the prediction method, the noise prediction method is easy and has high accuracy, and can quickly and accurately obtain the noise prediction value of the product through the target information, which helps to quickly estimate the product performance in the product development stage.

[0010] Furthermore, the noise value of the first frequency band is greater than the noise value of 200Hz.

[0011] Furthermore, the noise value of the second frequency band is the noise value of 0Hz-200Hz.

[0012] Furthermore, the second detection location is near the compressor.

[0013] Understandably, conventional noise detection can measure low-frequency and high-frequency values ​​separately. Prediction methods divide noise values ​​into first-band noise values ​​and second-band noise values ​​according to the frequency bands that the human ear can hear, in order to improve the accuracy of the prediction method.

[0014] It is understandable that the noise from the outdoor unit of an air conditioner is mainly generated when the compressor is working. This invention sets the second detection position to be close to the compressor in order to improve the accuracy of the prediction method.

[0015] In one technical solution of the present invention, calculating the noise correlation coefficient between the first detection position and the second detection position based on the target information specifically includes: calculating the noise correlation coefficient of the first frequency band noise value based on the first frequency band noise value and rotational speed or acceleration of the first and second detection positions; the first noise correlation coefficient of the compressor is calculated according to formula (Ⅰ):

[0016]

[0017] In equation (Ⅰ), x i This refers to the compressor speed at any of the multiple operating frequencies. y represents the average compressor speed. i This refers to the noise level of the first frequency band at any given operating frequency of the compressor. r is the average value of the first frequency band noise of the compressor. 11 The first noise correlation coefficient of the compressor; the first noise correlation coefficient of the second detection location is calculated according to equation (II):

[0018]

[0019] In formula (II), x i The acceleration of the vibration at any frequency among multiple operating frequencies at the second detection position. y represents the average acceleration of the vibration at the second detection position. i The noise value of the first frequency band at any of the multiple operating frequencies at the second detection location. r is the average value of the first frequency band noise at the second detection location. 12 The first noise correlation coefficient is the value at the second detection location.

[0020] Compared with the prior art, the technical effect achieved by adopting this technical solution is as follows: The present invention improves the accuracy of the first noise correlation coefficient by calculating the first noise correlation coefficient through a formula based on the different detection positions and the corresponding displacement information of the obtained first frequency band noise value.

[0021] In one technical solution of the present invention, calculating the noise correlation coefficient between the first detection position and the second detection position based on the target information further includes: calculating the noise correlation coefficient of the second frequency band noise value based on the second frequency band noise value and rotational speed or acceleration of the first detection position and the second detection position; the second noise correlation coefficient of the compressor is calculated according to formula (Ⅲ):

[0022]

[0023] In equation (Ⅲ), x i The speed of the compressor at any of its multiple operating frequencies. y represents the average compressor speed. i This refers to the second-band noise value at any of the compressor's multiple operating frequencies. r is the average value of the second frequency band noise of the compressor. 21 The second noise correlation coefficient of the compressor; the second noise correlation coefficient at the second detection position is calculated according to equation (Ⅳ):

[0024]

[0025] In equation (Ⅳ), x i The acceleration of the vibration at any frequency among multiple operating frequencies at the second detection position. y represents the average acceleration of the vibration at the second detection position. i The second-band noise value at any of the multiple operating frequencies at the second detection location. r is the average value of the second frequency band noise at the second detection location. 22 This is the second noise correlation coefficient at the second detection location.

[0026] Compared with the prior art, the technical effect achieved by adopting this technical solution is as follows: The present invention improves the accuracy of the second noise correlation coefficient by calculating the second noise correlation coefficient through a formula based on the different detection positions and the corresponding displacement information of the obtained second frequency band noise value.

[0027] In one technical solution of the present invention, obtaining the fitting coefficient based on the noise correlation coefficient specifically includes: sorting m1 first frequency band noise correlation coefficients from largest to smallest; selecting the first n1 first frequency band noise correlation coefficients and fitting them to obtain n1+1 first frequency band noise value fitting coefficients; wherein, m1>n1; the first frequency band noise correlation coefficients include: the first noise correlation coefficient of the compressor and the first noise correlation coefficient of the second detection position.

[0028] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: This invention selects a larger first noise correlation coefficient and obtains the fitting coefficient through harmonic response simulation. The calculation method is simple and has a short cycle. It can quickly and accurately obtain the noise prediction value of the product without the need for experiments, thereby reducing costs and saving time for product performance prediction during the product development stage.

[0029] In one technical solution of the present invention, obtaining the fitting coefficient based on the noise correlation coefficient specifically includes: sorting the m2 second-frequency band noise correlation coefficients from largest to smallest; selecting the first n2 second-frequency band noise correlation coefficients and fitting them to obtain n2+1 second-frequency band noise value fitting coefficients; wherein, m2>n2; the second-frequency band noise correlation coefficients include: the second noise correlation coefficient of the compressor and the second noise correlation coefficient of the second detection position.

[0030] Compared with existing technologies, the technical effects achieved by adopting this technical solution are as follows: This invention selects a larger second noise correlation coefficient and obtains the fitting coefficient through harmonic response simulation. The calculation method is simple and has a short cycle. It can quickly and accurately obtain the noise prediction value of the product without the need for experiments, thereby reducing costs and saving time for product performance prediction during the product development stage.

[0031] In one technical solution of the present invention, the noise prediction value is obtained based on the fitting coefficient and displacement information and calculated according to equation (V):

[0032]

[0033] in, This is the n1th fitting coefficient. The rotational speed or acceleration is the n1th first or second detection position.

[0034] Compared with the prior art, the technical effects achieved by adopting this technical solution are as follows: This invention can obtain the noise prediction value based on the noise value of the first frequency band and the fitting coefficient. By distinguishing the noise value by frequency band, the accuracy of the first noise correlation coefficient and even the fitting coefficient is improved, thereby improving the accuracy of the noise prediction value. The prediction method is simple and has a short cycle.

[0035] In one technical solution of the present invention, the noise prediction value is obtained based on the fitting coefficient and displacement information and calculated according to equation (VI):

[0036]

[0037] in, The n2th fitting coefficient, The rotational speed or acceleration is the n2th first or second detection position.

[0038] Compared with the existing technology, the technical effects achieved by adopting this technical solution are as follows: This invention can obtain the noise prediction value based on the noise value of the second frequency band and the fitting coefficient. By distinguishing the noise value by frequency band, the accuracy of the second noise correlation coefficient and even the fitting coefficient is improved, thereby improving the accuracy of the noise prediction value. The prediction method is simple and has a short cycle.

[0039] To achieve the second objective of this invention, the technical solution of this invention provides an air conditioner noise prediction device, the prediction device comprising: an acquisition module, used to acquire target information of a first detection position and a second detection position of the air conditioner, the target information including: noise value and displacement information; a calculation module, used to calculate the noise correlation coefficient of the first detection position and the second detection position based on the target information, and to calculate the noise prediction value based on the fitting coefficient and the displacement information; and a fitting coefficient acquisition module, used to obtain the fitting coefficient based on the noise correlation coefficient.

[0040] The prediction device of the present invention implements the steps of the prediction method of any of the technical solutions of the present invention, and therefore has all the beneficial effects of the prediction method of any of the technical solutions of the present invention, which will not be repeated here.

[0041] To achieve the third objective of this invention, the technical solution of this invention provides an air conditioner, which includes: a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, they implement the steps of the prediction method as described in any technical solution of this invention.

[0042] The prediction system of the present invention implements the steps of the prediction method of any of the technical solutions of the present invention, and therefore has all the beneficial effects of the prediction method of any of the technical solutions of the present invention, which will not be repeated here.

[0043] To achieve the fourth objective of this invention, the technical solution of this invention provides a readable storage medium on which a program or instructions are stored, and when the program or instructions are executed by a processor, the steps of the prediction method as described in any technical solution of this invention are implemented.

[0044] The readable storage medium of the present invention implements the steps of the prediction method of any of the technical solutions of the present invention, and therefore has all the beneficial effects of the prediction method of any of the technical solutions of the present invention, which will not be repeated here. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the prediction method according to an embodiment of the present invention.

[0046] Figure 2 This is a schematic diagram of the prediction device according to an embodiment of the present invention.

[0047] Explanation of reference numerals in the attached figures:

[0048] 100 - Prediction device; 110 - Acquisition module; 120 - Calculation module; 130 - Fitting coefficient acquisition module. Detailed Implementation

[0049] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other. Many specific details are set forth in the following description to provide a thorough understanding of the present invention; however, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0050] The following reference Figures 1 to 2 The technical solutions of some embodiments of the present invention are described below.

[0051] Reference Figure 1 As shown, an embodiment of the present invention provides a method for predicting the noise of an outdoor unit of an air conditioner. The prediction method includes: acquiring target information of a first detection position and a second detection position of the air conditioner, the target information including: noise value and displacement information; calculating the noise correlation coefficient between the first detection position and the second detection position based on the target information; obtaining a fitting coefficient based on the noise correlation coefficient; and calculating a predicted noise value based on the fitting coefficient and the displacement information. The first detection position is the position of the compressor, and the second detection position is different from the first detection position. The displacement information of the first detection position is the compressor speed. The displacement information of the second detection position is the vibration acceleration of the second detection position. The noise value includes: a noise value in a first frequency band and a noise value in a second frequency band. The noise value in the first frequency band is greater than the noise value in the second frequency band.

[0052] This invention obtains target information of the detection location of the outdoor unit of an air conditioner, calculates the noise correlation coefficient, fitting coefficient, and noise prediction value. It has low requirements for the test environment of the prediction method, low difficulty in noise prediction, and high accuracy. It can quickly and accurately obtain the noise prediction value of the product through target information, and provides assistance in quickly estimating product performance during the product development stage.

[0053] For example, the noise value of the first frequency band is greater than 200Hz.

[0054] For example, the noise value of the second frequency band is the noise value of 0Hz-200Hz.

[0055] For example, the second detection location is near the compressor.

[0056] For example, the second inspection location is the base, outdoor unit top cover, mounting bracket, compressor feet, left arm of mounting bracket, right arm of mounting bracket, chassis, right side panel, left side panel, and front panel.

[0057] Understandably, conventional noise detection can measure low-frequency and high-frequency values ​​separately. Prediction methods divide noise values ​​into first-band noise values ​​and second-band noise values ​​according to the frequency bands that the human ear can hear, in order to improve the accuracy of the prediction method.

[0058] It is understandable that the noise from the outdoor unit of an air conditioner is mainly generated when the compressor is working. This invention sets the second detection position to be close to the compressor in order to improve the accuracy of the prediction method.

[0059] Specifically, in the embodiments of the present invention, calculating the noise correlation coefficient between the first detection position and the second detection position based on the target information specifically includes: calculating the noise correlation coefficient of the first frequency band noise value based on the first frequency band noise value and rotational speed or acceleration of the first and second detection positions; the first noise correlation coefficient of the compressor is calculated according to formula (I):

[0060]

[0061] In equation (Ⅰ), x i This refers to the compressor speed at any of the multiple operating frequencies. y represents the average compressor speed. i This refers to the noise level of the first frequency band at any given operating frequency of the compressor. r is the average value of the first frequency band noise of the compressor. 11 The first noise correlation coefficient of the compressor; the first noise correlation coefficient of the second detection location is calculated according to equation (II):

[0062]

[0063] In formula (II), x i The acceleration of the vibration at any frequency among multiple operating frequencies at the second detection position. y represents the average acceleration of the vibration at the second detection position. i The noise value of the first frequency band at any of the multiple operating frequencies at the second detection location. r is the average value of the first frequency band noise at the second detection location. 12 The first noise correlation coefficient is the value at the second detection location.

[0064] This invention improves the accuracy of the first noise correlation coefficient by calculating the first noise correlation coefficient using a formula based on the obtained first frequency band noise value according to different detection positions and its corresponding displacement information.

[0065] Specifically, in the embodiments of the present invention, calculating the noise correlation coefficient between the first detection position and the second detection position based on the target information further includes: calculating the noise correlation coefficient of the second frequency band noise value based on the second frequency band noise value and rotational speed or acceleration of the first detection position and the second detection position; the second noise correlation coefficient of the compressor is calculated according to formula (III):

[0066]

[0067] In equation (Ⅲ), x i The speed of the compressor at any of its multiple operating frequencies. y represents the average compressor speed. i This refers to the second-band noise value at any of the compressor's multiple operating frequencies. r is the average value of the second frequency band noise of the compressor. 21 The second noise correlation coefficient of the compressor; the second noise correlation coefficient at the second detection position is calculated according to equation (Ⅳ):

[0068]

[0069] In equation (Ⅳ), x i The acceleration of the vibration at any frequency among multiple operating frequencies at the second detection position. Let be the average acceleration of the vibration at the second detection position, and yi be the second-band noise value at any frequency among multiple operating frequencies at the second detection position. r is the average value of the second frequency band noise at the second detection location. 22 This is the second noise correlation coefficient at the second detection location.

[0070] This invention improves the accuracy of the second noise correlation coefficient by calculating the second noise correlation coefficient using a formula based on the obtained second frequency band noise value according to different detection positions and its corresponding displacement information.

[0071] Specifically, in the embodiments of the present invention, obtaining fitting coefficients based on noise correlation coefficients specifically includes: sorting m1 noise correlation coefficients of the first frequency band from largest to smallest; selecting the first n1 noise correlation coefficients of the first frequency band and fitting them to obtain n1+1 noise value fitting coefficients of the first frequency band; wherein, m1>n1; the noise correlation coefficients of the first frequency band include: the first noise correlation coefficient of the compressor and the first noise correlation coefficient of the second detection position.

[0072] This invention selects a large first noise correlation coefficient and obtains the fitting coefficient through harmonic response simulation. The calculation method is simple and has a short cycle. It can quickly and accurately obtain the noise prediction value of the product without the need for experiments, thereby reducing costs and saving time for product performance prediction during the product development stage.

[0073] Specifically, in the embodiments of the present invention, obtaining fitting coefficients based on noise correlation coefficients specifically includes: sorting m2 second-frequency band noise correlation coefficients from largest to smallest; selecting the first n2 second-frequency band noise correlation coefficients and fitting them to obtain n2+1 second-frequency band noise value fitting coefficients; wherein, m2>n2; the second-frequency band noise correlation coefficients include: the second noise correlation coefficient of the compressor and the second noise correlation coefficient of the second detection position.

[0074] This invention selects a larger second noise correlation coefficient and obtains the fitting coefficient through harmonic response simulation. The calculation method is simple and has a short cycle. It can quickly and accurately obtain the noise prediction value of the product without the need for experiments, thereby reducing costs and saving time for product performance prediction during the product development stage.

[0075] Specifically, in the embodiments of the present invention, the noise prediction value obtained based on the fitting coefficients and displacement information is calculated according to equation (V):

[0076]

[0077] in, This is the n1th fitting coefficient. The rotational speed or acceleration is the n1th first or second detection position.

[0078] This invention can obtain noise prediction values ​​based on noise values ​​in a first frequency band and fitting coefficients. By distinguishing noise values ​​by frequency band, the accuracy of the first noise correlation coefficient and even the fitting coefficient is improved, thereby enhancing the accuracy of the noise prediction values. The prediction method is simple and has a short cycle.

[0079] Specifically, in the embodiments of the present invention, the noise prediction value obtained based on the fitting coefficients and displacement information is calculated according to equation (VI):

[0080]

[0081] in, The n2th fitting coefficient, The rotational speed or acceleration is the n2th first or second detection position.

[0082] This invention can obtain noise prediction values ​​based on the noise value of the second frequency band and the fitting coefficient. By distinguishing the noise value by frequency band, the accuracy of the second noise correlation coefficient and even the fitting coefficient is improved, thereby enhancing the accuracy of the noise prediction value. The prediction method is simple and has a short cycle.

[0083] Reference Figure 2 As shown, in some embodiments of this application, an air conditioner noise prediction device is provided. The prediction device 100 includes: an acquisition module 110, which is used to acquire target information of a first detection position and a second detection position of the air conditioner, the target information including noise value and displacement information; a calculation module 120, which is used to calculate the noise correlation coefficient of the first detection position and the second detection position based on the target information, and to calculate the noise prediction value based on the fitting coefficient and the displacement information; and a fitting coefficient acquisition module 130, which is used to obtain the fitting coefficient based on the noise correlation coefficient.

[0084] The prediction device 100 of this embodiment implements the steps of the prediction method as described in any embodiment of this invention, and thus has all the beneficial effects of the prediction method as described in any embodiment of this invention, which will not be repeated here.

[0085] In some embodiments of this application, an air conditioner is provided, comprising: a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the prediction method as described in any embodiment of the present invention.

[0086] The air conditioner of this invention implements the steps of the prediction method as described in any embodiment of this invention, and therefore has all the beneficial effects of the manufacturing method as described in any embodiment of this invention, which will not be repeated here.

[0087] In some embodiments of this application, a readable storage medium is provided, on which a program or instructions are stored, which, when executed by a processor, implement the steps of the prediction method as described in any embodiment of the present invention.

[0088] [First Embodiment]

[0089] Table 1 shows the fitting coefficients of a certain outdoor unit obtained according to the noise prediction method.

[0090] Table 1

[0091]

[0092] The predicted noise values ​​and the actual measured noise values ​​for the first frequency band, as shown in Table 1, are presented in Table 2.

[0093] Table 2

[0094]

[0095]

[0096] The predicted noise values ​​and the actual measured noise values ​​for the second frequency band, based on the noise values ​​measured in Table 1, are shown in Table 3.

[0097] Table 3

[0098]

[0099]

[0100] As can be seen from Tables 2 and 3, the noise prediction values ​​obtained by the noise prediction method of this invention have small errors compared with the actual measured noise values. The testing method is highly flexible and has a short cycle, which is of great reference value for quickly estimating product performance during the product development stage.

[0101] The readable storage medium of the present invention implements the steps of the prediction method as described in any embodiment of the present invention, and thus has all the beneficial effects of the method as described in any embodiment of the present invention, which will not be repeated here.

[0102] In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0103] The use of terms such as "S10", "S20", "S30", "S40" and "S50" in this specification is for the convenience of describing the embodiments of the present invention. The present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited by the order of the specific embodiments described above.

[0104] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A method for predicting the noise of an air conditioner outdoor unit, characterized in that, The prediction method includes: Obtain target information of the first and second detection positions of the air conditioner, the target information including: noise value and displacement information; The noise correlation coefficients between the first detection position and the second detection position are calculated based on the target information. The fitting coefficients are obtained based on the noise correlation coefficients. The noise prediction value is calculated based on the fitting coefficient and the displacement information; Wherein, the first detection position is the position of the compressor, and the second detection position is different from the first detection position; The displacement information at the first detection position is the rotational speed of the compressor; The displacement information at the second detection position is the vibration acceleration at the second detection position; The noise value includes: a first frequency band noise value and a second frequency band noise value; the first frequency band noise value is greater than the second frequency band noise value; The calculation of the noise correlation coefficient between the first detection position and the second detection position based on the target information specifically includes: The noise correlation coefficient of the first frequency band noise value is calculated based on the first frequency band noise value at the first detection position and the second detection position, and the rotational speed or the acceleration. The first noise correlation coefficient of the compressor is calculated according to equation (Ⅰ): Equation (I) In formula (Ⅰ), The speed of the compressor at any of the multiple operating frequencies. This represents the average rotational speed of the compressor. The noise value of the first frequency band at any of the multiple operating frequencies of the compressor. r is the average value of the first frequency band noise value of the compressor. 11 The first noise correlation coefficient of the compressor; The first noise correlation coefficient at the second detection location is calculated according to equation (II): Formula (II) In formula (II), The acceleration of the vibration at the second detection position at any of the multiple operating frequencies. The average acceleration of the vibration at the second detection position. The noise value of the first frequency band at any of the multiple operating frequencies at the second detection location. r is the average value of the first frequency band noise at the second detection location. 12 The first noise correlation coefficient is the second detection position; The fitting coefficients obtained based on the noise correlation coefficient specifically include: Sort the m1 first-band noise correlation coefficients from largest to smallest; The first n1 noise correlation coefficients of the first frequency band are selected and fitted to obtain n1+1 fitting coefficients of the noise value of the first frequency band. Where m1>n1; The first frequency band noise correlation coefficient includes: the first noise correlation coefficient of the compressor and the first noise correlation coefficient of the second detection location; The noise prediction value obtained based on the fitting coefficients and the displacement information is calculated according to equation (V): Noise prediction value Formula (V) in, The n1th fitting coefficient is... The rotational speed or acceleration is the n1th rotational speed or acceleration at the first or second detection position.

2. The method for predicting noise from an outdoor air conditioning unit according to claim 1, characterized in that, The step of calculating the noise correlation coefficient between the first detection position and the second detection position based on the target information further includes: The noise correlation coefficient of the second frequency band noise value is calculated based on the second frequency band noise value at the first detection position and the second detection position, and the rotational speed or the acceleration. The second noise correlation coefficient of the compressor is calculated according to equation (Ⅲ): Formula (III) In formula (Ⅲ), The rotational speed of the compressor at any of its multiple operating frequencies. This represents the average rotational speed of the compressor. The second frequency band noise value is given at any of the multiple operating frequencies of the compressor. r is the average value of the second frequency band noise value of the compressor. 21 This is the second noise correlation coefficient of the compressor; The second noise correlation coefficient at the second detection location is calculated according to equation (Ⅳ): Equation (Ⅳ) In formula (Ⅳ), The acceleration of the vibration at the second detection position at any of the multiple operating frequencies. The average acceleration of the vibration at the second detection position. The second frequency band noise value at any of the multiple operating frequencies at the second detection location. r is the average value of the second frequency band noise at the second detection location. 22 The second noise correlation coefficient is the second detection location.

3. The method for predicting the noise of an air conditioner outdoor unit according to claim 2, characterized in that, The specific steps of obtaining the fitting coefficient based on the noise correlation coefficient include: Sort the m2 second-band noise correlation coefficients from largest to smallest; The first n2 noise correlation coefficients of the second frequency band are selected and fitted to obtain n2+1 noise value fitting coefficients of the second frequency band. Where m2 > n2; The second frequency band noise correlation coefficient includes: the second noise correlation coefficient of the compressor and the second noise correlation coefficient of the second detection position.

4. The method for predicting the noise of an air conditioner outdoor unit according to claim 3, characterized in that, The noise prediction value obtained based on the fitting coefficient and the displacement information is calculated according to equation (VI): Noise prediction value Formula (VI) in, The n2th fitting coefficient, The rotational speed or acceleration is the n2th first detection position or the second detection position.

5. A device for predicting air conditioner noise, characterized in that, The method for predicting noise from an outdoor air conditioning unit as described in claim 1, wherein the prediction device (100) comprises: The acquisition module (110) is used to acquire target information of the first detection position and the second detection position of the air conditioner, the target information including: noise value and displacement information; The calculation module (120) is used to calculate the noise correlation coefficient between the first detection position and the second detection position based on the target information, and to calculate the noise prediction value based on the fitting coefficient and the displacement information; The fitting coefficient acquisition module (130) is used to obtain the fitting coefficient based on the noise correlation coefficient.

6. An air conditioner, characterized in that, The air conditioner includes: A processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the prediction method as described in any one of claims 1 to 4.

7. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the prediction method as described in any one of claims 1 to 4.

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