Noise testing method, apparatus, device, and storage medium

Abstract

This invention relates to the field of product testing technology, and in particular to a noise testing method, apparatus, equipment, and storage medium. The invention acquires multiple sets of noise data generated during the operation of a product sample device, superimposes and denoises these multiple sets of noise data to obtain product operating noise data, and performs frame-by-frame processing on the product operating noise data to obtain multi-frame standard product operating noise data. This allows for the comprehensive calculation of the product noise level during the operation of the product sample device, avoiding the technical problem in the prior art where it is difficult to test product noise when the product noise is low, and reducing the impact of environmental noise.

Description

Technical Field

[0001] This invention relates to the field of product testing technology, and in particular to a noise testing method, apparatus, equipment, and storage medium. Background Technology

[0002] Mechanical noise testing is a common testing requirement for industrial products. Due to the inherent background noise in the testing environment, the noise data collected during noise testing is actually the result of the superposition of product noise and background noise. Furthermore, because some existing products have relatively low mechanical noise, the environmental noise can affect the mechanical noise testing process, making it impossible to effectively extract and test the noise generated during product operation.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this invention is to provide a noise testing method, apparatus, device, and storage medium, aiming to solve the technical problem in the prior art that it is difficult to conduct noise testing on products with low noise levels.

[0005] To achieve the above objectives, the present invention provides a noise testing method, the method comprising the following steps:

[0006] Acquire multiple sets of noise data during the operation of the product sample equipment;

[0007] The noise data of the multiple sets of noise data are denoised to obtain the product motion noise data;

[0008] The product operating noise data is divided into frames to obtain at least one frame of target product operating noise data.

[0009] The noise level of the product sample during operation is calculated based on at least one frame of target product operating noise data.

[0010] Optionally, the step of denoising the multiple sets of noise data to obtain product motion noise data includes:

[0011] Determine the start time of the sudden sound in the product's operating noise data;

[0012] The target noise data is obtained by superimposing the multiple sets of noise data based on the start time of the burst sound;

[0013] The average value of the target noise data is calculated based on the number of groups of the noise data to obtain the product motion noise data.

[0014] Optionally, the step of segmenting the product operating noise data into frames to obtain at least one frame of target product operating noise data includes:

[0015] The product motion noise data is processed into frames based on the start time of the burst sound corresponding to the product operation noise data to obtain at least one frame of target product operation noise data.

[0016] Optionally, the step of performing frame-based processing on the product motion noise data according to the burst sound start time corresponding to the product operation noise data to obtain at least one frame of target product operation noise data includes:

[0017] Determine the noise data frame length corresponding to the preset sampling rate;

[0018] The product motion noise data is segmented into frames based on the noise data frame length and the start time of the sudden sound, to obtain at least one frame of target product running noise data.

[0019] Optionally, calculating the product noise level during the operation of the product sample equipment based on the at least one frame of target product operating noise data includes:

[0020] Obtain the duration and amplitude of the operating noise of each target product;

[0021] Calculate the target sound pressure level of the target product's operating noise based on the duration, the reference air sound pressure level, and the noise amplitude.

[0022] The noise level of the product sample during equipment operation is determined based on the target sound pressure level.

[0023] Optionally, determining the product noise level during the operation of the product sample equipment based on the target sound pressure level includes:

[0024] Determine the temporal relationship of the operating noise of each target product;

[0025] The sound pressure level variation value is determined based on the aforementioned time sequence relationship and the target sound pressure level corresponding to the operating noise of each target product;

[0026] The noise level of the product sample during equipment operation is determined based on the change in sound pressure level.

[0027] Optionally, the acquisition of multiple sets of noise data during the operation of the product sample acquisition equipment includes:

[0028] The device for driving the product prototype will run continuously for the first duration.

[0029] The burst sound device is activated according to the preset sampling rate, and audio segment data within the first duration is recorded;

[0030] The audio segment data is divided according to the operating frequency of the burst sound device to obtain multiple sets of noise data.

[0031] Furthermore, to achieve the above objectives, the present invention also proposes a noise testing device, the noise testing device comprising:

[0032] The acquisition module is used to acquire multiple sets of noise data during the operation of the product sample equipment.

[0033] A noise reduction module is used to denoise the multiple sets of noise data to obtain product motion noise data;

[0034] The framing module is used to segment the product operating noise data into frames to obtain at least one frame of target product operating noise data.

[0035] The calculation module is used to calculate the product noise level during the operation of the product sample equipment based on the at least one frame of target product operating noise data.

[0036] Furthermore, to achieve the above objectives, the present invention also proposes a noise testing device, which includes: a memory, a processor, and a noise testing program stored in the memory and executable on the processor, the noise testing program being configured to implement the steps of the noise testing method described above.

[0037] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a noise testing program, which, when executed by a processor, implements the steps of the noise testing method described above.

[0038] This invention discloses a noise testing method, which includes: acquiring multiple sets of noise data during the operation of a product sample device; denoising the multiple sets of noise data to obtain product motion noise data; segmenting the product motion noise data into frames to obtain at least one frame of target product motion noise data; and calculating the product noise level during the operation of the product sample device based on the at least one frame of target product motion noise data. Compared with the prior art, this invention acquires multiple sets of noise data generated by the product sample device during operation, superimposes and denoises these multiple sets of noise data to obtain product motion noise data, and segments the product motion noise data into frames to obtain multiple frames of target product motion noise data. This allows for the comprehensive calculation of the product noise level during the operation of the product sample device, avoiding the technical problem in the prior art where it is difficult to test product noise when the product noise is low, and reducing the impact of environmental noise. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the structure of a noise testing device for the hardware operating environment involved in the embodiments of the present invention;

[0040] Figure 2 This is a flowchart illustrating the first embodiment of the noise testing method of the present invention;

[0041] Figure 3 This is a schematic diagram of the test environment for an embodiment of the noise testing method of the present invention;

[0042] Figure 4 This is a flowchart illustrating the second embodiment of the noise testing method of the present invention;

[0043] Figure 5 This is a flowchart illustrating the third embodiment of the noise testing method of the present invention;

[0044] Figure 6 This is a structural block diagram of the first embodiment of the noise testing device of the present invention.

[0045] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0046] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0047] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a noise testing device for the hardware operating environment involved in an embodiment of the present invention.

[0048] like Figure 1 As shown, the noise testing device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0049] Those skilled in the art will understand that Figure 1The structure shown does not constitute a limitation on the noise testing equipment and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0050] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a noise testing program.

[0051] exist Figure 1 In the noise testing device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the noise testing device of the present invention can be set in the noise testing device, and the noise testing device calls the noise testing program stored in the memory 1005 through the processor 1001 and executes the noise testing method provided in the embodiment of the present invention.

[0052] This invention provides a noise testing method, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of a noise testing method according to the present invention.

[0053] In this embodiment, the noise testing method includes the following steps:

[0054] Step S10: Obtain multiple sets of noise data during the operation of the product sample equipment.

[0055] It should be noted that the execution subject of the method in this embodiment can be a device with functions such as data acquisition, data processing and program execution, such as a test computer or computer, or other devices that can achieve the same or similar functions. This embodiment does not impose specific limitations on this. In this embodiment and the following embodiments, a test computer will be used as an example for explanation.

[0056] It is worth noting that as people have higher and higher requirements for the NVH performance of industrial products, the mechanical noise of small structural components such as motors and micro robots on the market has reached a very low level, which puts forward high requirements for noise testing.

[0057] In traditional technologies, noise testing requirements are typically met by constructing high-performance anechoic chambers and precision-grade anechoic boxes. However, traditional anechoic chamber environments cannot achieve very low background noise levels. Therefore, many noise detection methods with lower background noise requirements, such as "spectrum detection" and "pattern recognition," have emerged. These methods are largely similar, all based on the spectral information of the test signal, using statistical or machine learning methods to identify the spectral characteristics of the signal and thus detect abnormal noise. However, these methods can only be used for abnormal noise detection and cannot directly test product noise; moreover, they still have certain requirements for background noise and cannot be applied to scenarios where the background noise is higher than the product noise across the entire frequency range.

[0058] To address the aforementioned issues, this embodiment acquires multiple sets of noise data generated during the operation of the product sample equipment, superimposes and denoises these multiple sets of noise data, eliminates environmental noise based on the random signal characteristics of environmental noise, and then restores the product operating noise data after denoising. Furthermore, the product operating noise data is processed by frame segmentation to obtain multi-frame standard product operating noise data, and then the product noise level during the operation of the product sample equipment is comprehensively calculated, thus enabling noise testing of products or equipment with relatively low product noise.

[0059] To achieve the noise test extraction in this embodiment, refer to... Figure 3 In this embodiment, the product sample equipment and the audio acquisition device can be placed in the test environment. The audio acquisition device collects the sound signal and transmits the signal to the data acquisition system. After sampling, analog-to-digital conversion and data processing, the noise value is calculated.

[0060] Furthermore, the multiple sets of noise data obtained during the operation of the product sample acquisition equipment include:

[0061] The device for driving the product prototype will run continuously for the first duration.

[0062] The burst sound device is activated according to the preset sampling rate, and audio segment data within the first duration is recorded;

[0063] The audio segment data is divided according to the operating frequency of the burst sound device to obtain multiple sets of noise data.

[0064] In the specific implementation, in order to accurately obtain multiple sets of noise data with equal duration so that there will be no data redundancy or data incompleteness when superimposing audio data later, which would affect the noise reduction effect, this embodiment can also set a sound-emitting device (such as a speaker) in the test environment to emit a custom sound, thereby achieving the effect of aligning the duration of the noise data.

[0065] For example, the product sample equipment can be started first. After the product sample equipment is running stably, the audio acquisition device is turned on and begins to collect audio data. At this time, the control device emits prominent intermittent bursts of sound to calibrate the duration of the noise data. Taking the bursts of sound emitted every 10 seconds as an example, the duration of the noise data is also 10 seconds, which is convenient for subsequent data superposition and noise reduction. By repeatedly collecting noise data and dividing the collected noise data according to the interval of the bursts of sound, multiple sets of noise data with equal duration can be obtained.

[0066] Step S20: Denoise the multiple sets of noise data to obtain product motion noise data.

[0067] It should be noted that the process of denoising multiple sets of noise data refers to aligning and superimposing noise data of equal duration to obtain a superimposed noise data, and then restoring the superimposed noise data to obtain the denoised product operating noise data.

[0068] Step S30: Segment the product operating noise data into frames to obtain at least one frame of target product operating noise data.

[0069] It should be understood that, in this embodiment, in order to accurately calculate the noise level of the product operating noise data and achieve accurate noise testing, this embodiment divides the restored product operating noise data into frames to obtain multiple frame data, and calculates the sound pressure level data corresponding to each target product operating noise data respectively, thereby improving the accuracy of noise testing.

[0070] Step S40: Calculate the product noise level during the operation of the product sample equipment based on the at least one frame of target product operating noise data.

[0071] In this embodiment, calculating the noise level of the product mainly involves calculating the change in sound pressure level of the noise data in adjacent frames after framing, that is, the data on the change in sound pressure level of the noise data of each target product over time.

[0072] Further, the step of calculating the product noise level during the operation of the product sample equipment based on the at least one frame of target product operating noise data includes:

[0073] Obtain the duration and amplitude of the operating noise of each target product;

[0074] Calculate the target sound pressure level of the target product's operating noise based on the duration, the reference air sound pressure level, and the noise amplitude.

[0075] The noise level of the product sample during equipment operation is determined based on the target sound pressure level.

[0076] Since the noise generated during the operation of the product prototype equipment may be intermittent rather than continuous, the duration in this embodiment refers to the total duration of noise generated within the noise data of a target product. In this embodiment, the reference air sound pressure level can be taken as 20*e. -6 Pa, this embodiment does not impose specific limitations on this.

[0077] In the specific implementation, the formula for calculating the sound pressure level for each frame of data is as follows:

[0078]

[0079] Where P ref P represents the reference sound pressure level in air. ref =20*e -6 Pa.

[0080] Further, determining the product noise level during the operation of the product sample equipment based on the target sound pressure level includes:

[0081] Determine the temporal relationship of the operating noise of each target product;

[0082] The sound pressure level variation value is determined based on the aforementioned time sequence relationship and the target sound pressure level corresponding to the operating noise of each target product;

[0083] The noise level of the product sample during equipment operation is determined based on the change in sound pressure level.

[0084] It is understandable that after calculating the sound pressure level of the operating noise data of each target product, the sound pressure level of the operating noise data of the target product in adjacent frames is determined according to their temporal correlation, and then the data of the sound pressure level changing with time is obtained, that is, the product noise level.

[0085] This embodiment acquires multiple sets of noise data generated by the product sample equipment during operation, and superimposes and denoises these multiple sets of noise data to obtain product operating noise data. The product operating noise data is then processed by frame segmentation to obtain multi-frame standard product operating noise data. The product noise level during the operation of the product sample equipment is then comprehensively calculated, avoiding the technical problem in the prior art that it is difficult to conduct noise testing on the product when the product noise is low, and reducing the impact of environmental noise.

[0086] refer to Figure 4 , Figure 4 This is a flowchart illustrating a second embodiment of a noise testing method according to the present invention.

[0087] Based on the first embodiment described above, in this embodiment, step S30 includes:

[0088] Step S301: Based on the start time of the burst sound corresponding to the product running noise data, the product motion noise data is processed into frames to obtain at least one frame of target product running noise data.

[0089] It is understandable that the start time of the burst sound corresponding to the product operation noise data is the starting point of the product motion noise data. This ensures that the frame data is aligned during frame processing, avoids excessive errors in the subsequent noise calculation process, and improves the accuracy of product noise calculation. After determining the starting point of the product motion noise data, it is also necessary to determine the frame length. In this embodiment, the frame length can be divided according to the sampling rate when collecting noise data.

[0090] Further, the step of performing frame-based processing on the product motion noise data according to the burst sound start time corresponding to the product operation noise data to obtain at least one frame of target product operation noise data includes:

[0091] Determine the noise data frame length corresponding to the preset sampling rate;

[0092] The product motion noise data is segmented into frames based on the noise data frame length and the start time of the sudden sound, to obtain at least one frame of target product running noise data.

[0093] In the specific implementation, X[k] represents the product motion noise data. As described above, the signal is framed with a frame length of 125, and the sound pressure level is calculated. The target product running noise data is obtained after the signal is framed. The calculation formula for the target product running noise data is as follows:

[0094] P t [i] = X[fs*0.125*t+i]

[0095] Among them, P t [i] represents the signal of frame t. The value of i ranges from 0 to fs*0.125. The value of t ranges from 0 to T.

[0096] In addition, in this embodiment, the target product operating noise data can also be set by the user to a certain fixed value. As long as the frame length of the target product operating noise data obtained after framing is the same, if there is redundant noise data after framing according to the fixed frame length, it can be discarded.

[0097] This embodiment determines the start time of the burst sound of the product's operating noise data, and performs frame processing on the product's motion noise data according to the start time of the burst sound corresponding to the product's operating noise data to obtain at least one frame of target product operating noise data. By performing frame processing on the noise data, the influence of noise is reduced and the accuracy of noise sound pressure level calculation is improved.

[0098] refer to Figure 5 , Figure 5 This is a flowchart illustrating a third embodiment of a noise testing method according to the present invention.

[0099] In one embodiment, the step of denoising the multiple sets of noise data to obtain product motion noise data includes:

[0100] Step S201: Determine the start time of the sudden sound of the product's operating noise data.

[0101] It should be noted that, in this embodiment, the audio acquisition and sound generation device is activated after the product sample equipment is running stably. When the acquired audio data is segmented to obtain multiple sets of noise data, the segmentation is also based on the start time of the burst sound. In the subsequent frame segmentation process, in order to improve the accuracy of the sound pressure level calculation, this embodiment further segments the product operation noise data according to the start time of the burst sound, with a preset frame length, to obtain at least one frame of target product operation noise data.

[0102] Step S202: Based on the start time of the burst sound, superimpose the multiple sets of noise data to obtain the target noise data.

[0103] Step S203: Calculate the average value of the target noise data based on the number of groups of the noise data to obtain the product motion noise data.

[0104] Understandably, the collected noise data includes product noise generated during the operation of the product sample equipment and ambient noise. Background noise is a random signal, while product noise is a regular and invariant signal. The two signals are incoherent and satisfy a linear superposition relationship. Since the result of multiple superpositions of random signals in the time domain tends towards 0, if n is large enough, the ambient noise, due to its random nature, will offset and eliminate the noise after the n noise data are added together. This can be considered as the product noise being superimposed n times. By averaging the superimposed data, the pure product noise can be obtained. Compared to traditional methods of filtering and analyzing noise data, this approach is simpler to operate and offers a certain level of accuracy.

[0105] As described above, in this embodiment, by setting a sound - emitting device, a burst sound is emitted while driving the product to start moving. The burst - sound signal serves as the synchronous time axis and the starting time point of the product's movement. This can align the starting times of each product movement. The aligned signals are equal in the time domain. Superimposing n times is equivalent to multiplying the signal by n, reducing the need for the step of precisely splitting the noise data due to different durations of the noise data, and improving the efficiency of noise recognition and extraction. Among them, since the burst sound is also an audio signal, to avoid interfering with the product noise, this embodiment can set the burst sound as a sine - pulse signal, which is easy to identify and eliminate in the collected signal data according to the characteristics of being short in the time domain and having a single frequency.

[0106] For example: collect n sets of noise data, and each set of collected data is denoted as S n [k], and use E n [k] and X n [k] to represent the background noise and the product noise respectively. According to the linear superposition relationship, we have S n [k] = E n [k]+X n [k]. Here, k refers to the serial number of the discrete signal, and its value range is 0...fs*t1 - 1. fs refers to the sampling rate, which represents the sequence length of the discrete signal per second. Perform the same processing on the n sets of collected noise data: starting from the time t(n) seconds recorded by the burst - sound signal as the starting point, intercept the data D n [k] = S n [t(n)*fs + fs*t2], where t(n)+t2 < t1, and the value range of k is 0...fs*t2 - 1. Add all the data and take the average D[k] = ∑D n [k] / n, where D[k] = E[k]+X[k]. According to the properties of random signals, ∑E n [k] / n ∼ 0, so X[k] ∼ D[k], and then the product - movement noise data is obtained.

[0107] This embodiment utilizes the randomness of environmental noise. By superimposing multiple sets of noise data, it eliminates environmental noise and retains the noise generated during the product operation. The denoising step is simple and effective, improving the efficiency of noise testing.

[0108] In addition, an embodiment of the present invention also proposes a storage medium, on which a noise - testing program is stored. When the noise - testing program is executed by a processor, it implements the steps of the noise - testing method described above.

[0109] Since this storage medium adopts all the technical solutions of the above - mentioned all embodiments, it at least has all the beneficial effects brought by the technical solutions of the above - mentioned embodiments, and will not be elaborated here one by one.

[0110] Reference Figure 6 , Figure 6 This is a structural block diagram of the first embodiment of the noise testing device of the present invention.

[0111] like Figure 6 As shown, the noise testing device proposed in this embodiment of the invention includes:

[0112] The acquisition module 10 is used to acquire multiple sets of noise data during the operation of the product sample equipment.

[0113] The noise reduction module 20 is used to denoise the multiple sets of noise data to obtain product motion noise data.

[0114] The framing module 30 is used to segment the product operating noise data into frames to obtain at least one frame of target product operating noise data.

[0115] The calculation module 40 is used to calculate the product noise level during the operation of the product sample equipment based on the at least one frame of target product operating noise data.

[0116] In one embodiment, the noise reduction module 20 is further configured to determine the start time of the burst sound of the product operation noise data; to obtain target noise data by superimposing the multiple sets of noise data based on the start time of the burst sound; and to calculate the average value of the target noise data based on the number of sets of noise data to obtain product motion noise data.

[0117] In one embodiment, the framing module 30 is further configured to perform framing processing on the product motion noise data according to the burst sound start time corresponding to the product running noise data, so as to obtain at least one frame of target product running noise data.

[0118] In one embodiment, the framing module 30 is further configured to determine the noise data frame length corresponding to the preset sampling rate; and to perform framing processing on the product motion noise data according to the noise data frame length and the start time of the burst sound to obtain at least one frame of target product running noise data.

[0119] In one embodiment, the calculation module 40 is further configured to obtain the duration and amplitude of the operating noise of each target product; calculate the target sound pressure level of the operating noise of the target product based on the duration, the reference air sound pressure level, and the noise amplitude; and determine the product noise level during the operation of the product sample equipment based on the target sound pressure level.

[0120] In one embodiment, the calculation module 40 is further configured to determine the temporal relationship of the operating noise of each target product; determine the sound pressure level change value based on the temporal relationship and the target sound pressure level corresponding to the operating noise of each target product; and determine the product noise level during the operation of the product sample equipment based on the sound pressure level change value.

[0121] In one embodiment, the acquisition module 10 is further configured to drive the product sample device to run continuously for a first duration; activate the burst sound device according to a preset sampling rate and record audio segment data within the first duration; and segment the audio segment data according to the operating frequency of the burst sound device to obtain multiple sets of noise data.

[0122] This embodiment acquires multiple sets of noise data generated during the operation of the product sample equipment, and performs noise reduction by superimposing these multiple sets of noise data to obtain product operating noise data. The product operating noise data is then processed by frame segmentation to obtain multi-frame standard product operating noise data. The product noise level during the operation of the product sample equipment is then calculated comprehensively. This avoids the technical problem in the prior art that it is difficult to conduct noise testing on the product when the product noise is low, and reduces the impact of environmental noise.

[0123] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0124] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0125] In addition, for technical details not described in detail in this embodiment, please refer to the noise testing method provided in any embodiment of the present invention, which will not be repeated here.

[0126] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0127] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0128] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0129] The above are merely preferred embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method of noise testing, characterized by, The noise testing method includes: Acquire multiple sets of noise data during the operation of the product sample equipment; The noise data of the multiple sets of noise data are denoised to obtain the product operating noise data; The product operating noise data is divided into frames to obtain at least one frame of target product operating noise data. Calculate the product noise level during the operation of the product sample equipment based on at least one frame of target product operating noise data; The noise reduction process for the multiple sets of noise data to obtain product operating noise data includes: The start time of the burst sound in the product operating noise data is determined, wherein the sound-generating device set in the test environment corresponding to the product sample equipment emits a burst sound signal when driving the product sample equipment to start moving, and the start time of the burst sound is the time when the burst sound signal is emitted; The target noise data is obtained by superimposing the multiple sets of noise data based on the start time of the burst sound; The average value of the target noise data is calculated based on the number of groups of the noise data to obtain the product operating noise data.

2. The noise testing method as described in claim 1, characterized in that, The step of framing the product operating noise data to obtain at least one frame of target product operating noise data includes: The product operating noise data is divided into frames based on the start time of the burst sound corresponding to the product operating noise data to obtain at least one frame of target product operating noise data.

3. The noise testing method as described in claim 2, characterized in that, The step of segmenting the product operating noise data into frames based on the burst sound start time corresponding to the product operating noise data to obtain at least one frame of target product operating noise data includes: Determine the noise data frame length corresponding to the preset sampling rate; The product operating noise data is divided into frames based on the noise data frame length and the start time of the burst sound to obtain at least one frame of target product operating noise data.

4. The noise testing method as described in claim 1, characterized in that, The step of calculating the product noise level during the operation of the product sample equipment based on the at least one frame of target product operating noise data includes: Obtain the duration and amplitude of the operating noise of each target product; Calculate the target sound pressure level of the target product's operating noise based on the duration, the reference air sound pressure level, and the noise amplitude. The noise level of the product sample during equipment operation is determined based on the target sound pressure level.

5. The noise testing method as described in claim 4, characterized in that, Determining the product noise level during the operation of the product sample equipment based on the target sound pressure level includes: Determine the temporal relationship of the operating noise of each target product; The sound pressure level variation value is determined based on the aforementioned time sequence relationship and the target sound pressure level corresponding to the operating noise of each target product; The noise level of the product sample during equipment operation is determined based on the change in sound pressure level.

6. The noise testing method as described in claim 1, characterized in that, The multiple sets of noise data obtained during the operation of the equipment for acquiring product samples include: The device for driving the product prototype will run continuously for the first duration. The burst sound device is activated according to the preset sampling rate, and audio segment data within the first duration is recorded; The audio segment data is divided according to the operating frequency of the burst sound device to obtain multiple sets of noise data.

7. A noise testing device, characterized in that, The noise testing device includes: The acquisition module is used to acquire multiple sets of noise data during the operation of the product sample equipment. A noise reduction module is used to remove noise from the multiple sets of noise data to obtain product operating noise data; The framing module is used to segment the product operating noise data into frames to obtain at least one frame of target product operating noise data. The calculation module is used to calculate the product noise level during the operation of the product sample equipment based on the at least one frame of target product operating noise data; The noise reduction module is further configured to determine the start time of the burst sound in the product operating noise data, wherein a sound-generating device set in the test environment corresponding to the product sample equipment emits a burst sound signal when driving the product sample equipment to start moving, and the start time of the burst sound is the time when the burst sound signal is emitted; based on the start time of the burst sound, the multiple sets of noise data are superimposed to obtain target noise data; based on the number of sets of noise data, the average value of the target noise data is calculated to obtain the product operating noise data.

8. A noise testing device, characterized in that, The noise testing device includes: a memory, a processor, and a noise testing program stored in the memory and executable on the processor, the noise testing program being configured to implement the noise testing method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a noise testing program, which, when executed by a processor, implements the noise testing method as described in any one of claims 1 to 6.

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