Noise order analysis method, device, computer equipment and readable storage medium

Abstract

The present application relates to a noise order analysis method, device, computer equipment and readable storage medium. The method includes: obtaining frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; for each working condition in the frequency domain noise data, determining the noise frequency value corresponding to each working condition; dividing the noise frequency value by the corresponding working condition value to perform working condition normalization processing, obtaining a normalized noise frequency value, and determining the frequency domain noise data; classifying the frequency domain noise data according to a preset feature dimension to obtain the corresponding noise feature data under the preset feature dimension; splicing the noise feature data to obtain a noise feature data set; generating a bubble chart for analyzing the noise order according to the noise feature data set; wherein the horizontal and vertical coordinates of the bubble chart and the size of the bubbles in the bubble chart are determined according to multiple feature dimensions. The use of this method can improve resource utilization.

Description

Technical Field

[0001] The present application relates to the field of signal processing technology, and in particular to a noise order analysis method, device, computer equipment and readable storage medium. Background Art

[0002] Electromechanical products will generate noise when there are problems such as imbalance and bearing failure, which can cause equipment performance degradation or damage. The order of noise reflects the periodicity of the operation of components in electromechanical products. The order of noise can be used to identify and evaluate vibration and noise problems in rotating machinery, which can provide a deeper understanding of the dynamic behavior of rotating machinery and take appropriate measures to reduce vibration and noise and improve the performance and reliability of machinery.

[0003] In the related art, noise order analysis is performed in the form of waterfall graphs and color maps. However, the noise order analysis in the related art has a complex procedure and consumes a large amount of resources, resulting in a technical problem of low resource utilization. Summary of the invention

[0004] Based on this, it is necessary to provide a noise order analysis method, device, computer equipment, computer-readable storage medium and computer program product that can improve resource utilization in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for analyzing noise orders, comprising:

[0006] Acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition;

[0007] For each operating condition in the frequency domain noise data, determining a noise frequency value corresponding to each operating condition;

[0008] Dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data;

[0009] Classifying the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension;

[0010] The noise characteristic data are spliced ​​according to a preset format to obtain a noise characteristic data set;

[0011] According to the noise characteristic data set, a bubble chart for analyzing the noise order is generated, and the order frequency information of the noise is obtained based on the bubble chart, and / or the change of the noise with the working condition is obtained, and / or the components that generate the order noise are located; wherein the horizontal coordinate and the vertical coordinate of the bubble chart and the size of the bubbles in the bubble chart are determined according to the multiple characteristic dimensions.

[0012] In one embodiment, the method further comprises:

[0013] For each operating condition in the frequency domain noise data, the amplitude of the noise under each operating condition that is less than the preset amplitude is filtered out to obtain the frequency domain noise data.

[0014] In one embodiment, the classifying the frequency domain noise data according to a preset feature dimension to obtain the corresponding noise feature data under the preset feature dimension includes:

[0015] Determining an amplitude influence index affecting the noise amplitude according to the characteristics of the multiple characteristic dimensions;

[0016] The frequency domain noise data is classified according to the amplitude influence index to obtain noise feature data under a feature dimension that affects the amplitude.

[0017] In one embodiment, the classifying the frequency domain noise data according to the amplitude influence index to obtain the noise characteristic data under the characteristic dimension affecting the amplitude includes:

[0018] Classifying the frequency domain noise data according to the working conditions in the amplitude influence index to obtain a plurality of target amplitudes and target frequency values ​​under the same working condition;

[0019] The step of splicing the noise feature data to obtain a noise feature data set includes:

[0020] A plurality of target amplitudes and target frequency values ​​under the same working condition are concatenated to obtain a noise characteristic data set.

[0021] In one embodiment, generating a bubble chart for analyzing noise orders according to the noise feature data set includes:

[0022] Determine a first numerical range of the horizontal axis in the bubble graph according to the noise frequency in the noise characteristic data, and determine a second numerical range of the vertical axis in the bubble graph according to the operating condition value;

[0023] Taking the operating condition value of each operating condition in the noise characteristic data set and each target frequency corresponding to the operating condition value as the center of the bubble;

[0024] The size of the bubble is determined according to the target amplitude corresponding to each target frequency, and a bubble diagram for analyzing the noise order is generated, wherein the bubble size is the bubble area or the bubble diameter.

[0025] In one embodiment, the features of the multiple feature dimensions further include a load value, the noise feature data set includes a plurality of target amplitudes, target frequency values, and target load values ​​under the same working condition, and generating a bubble chart for analyzing noise orders according to the noise feature data set includes:

[0026] Determine a first numerical range of the horizontal axis in the bubble graph according to the noise frequency in the noise characteristic data, and determine a second numerical range of the vertical axis in the bubble graph according to the operating condition value;

[0027] Taking the operating condition value of each operating condition in the noise characteristic data set and each target frequency corresponding to the operating condition value as the center of the bubble;

[0028] The size of the bubble is determined according to the target amplitude corresponding to each target frequency, and the color or shape of the bubble is determined according to the target load value corresponding to the target amplitude, so as to generate a bubble diagram for analyzing the noise order.

[0029] In one embodiment, obtaining frequency domain noise data of the electromechanical product to be tested under different working conditions includes:

[0030] Obtain the time domain noise data of the electromechanical products under test under different working conditions;

[0031] Converting the time domain noise data to obtain intermediate frequency domain noise data under different working conditions;

[0032] The noise amplitude in the intermediate frequency domain noise data is normalized to obtain frequency domain noise data.

[0033] In a second aspect, the present application also provides a noise order analysis device, comprising:

[0034] A data acquisition module, used to acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition;

[0035] A normalization module, for determining, for each operating condition in the frequency domain noise data, a noise frequency value corresponding to each operating condition;

[0036] Dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data;

[0037] A classification module, used to classify the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension;

[0038] A splicing module, used for splicing the noise characteristic data according to a preset format to obtain a noise characteristic data set;

[0039] A display module is used to generate a bubble chart for analyzing noise orders based on the noise feature data set, obtain order frequency information of noise based on the bubble chart, and / or obtain changes in noise with working conditions, and / or locate components that generate order noise; wherein the horizontal and vertical coordinates of the bubble chart and the size of the bubbles in the bubble chart are determined based on the multiple feature dimensions.

[0040] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0041] Acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the features of the multiple feature dimensions include at least the noise frequency and the noise amplitude under each working condition;

[0042] For each operating condition in the frequency domain noise data, determining a noise frequency value corresponding to each operating condition;

[0043] Dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data;

[0044] Classifying the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension;

[0045] The noise characteristic data are spliced ​​according to a preset format to obtain a noise characteristic data set;

[0046] According to the noise characteristic data set, a bubble chart for analyzing the noise order is generated, and the order frequency information of the noise is obtained based on the bubble chart, and / or the change of the noise with the working condition is obtained, and / or the components that generate the order noise are located; wherein the horizontal coordinate and the vertical coordinate of the bubble chart and the size of the bubbles in the bubble chart are determined according to the multiple characteristic dimensions.

[0047] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0048] Acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition;

[0049] For each operating condition in the frequency domain noise data, determining a noise frequency value corresponding to each operating condition;

[0050] Dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data;

[0051] Classifying the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension;

[0052] The noise characteristic data are spliced ​​according to a preset format to obtain a noise characteristic data set;

[0053] According to the noise characteristic data set, a bubble chart for analyzing the noise order is generated, and the order frequency information of the noise is obtained based on the bubble chart, and / or the change of the noise with the working condition is obtained, and / or the components that generate the order noise are located; wherein the horizontal coordinate and the vertical coordinate of the bubble chart and the size of the bubbles in the bubble chart are determined according to the multiple characteristic dimensions.

[0054] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0055] Acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition;

[0056] For each operating condition in the frequency domain noise data, determining a noise frequency value corresponding to each operating condition;

[0057] Dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data;

[0058] Classifying the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension;

[0059] The noise characteristic data are spliced ​​according to a preset format to obtain a noise characteristic data set;

[0060] According to the noise characteristic data set, a bubble chart for analyzing the noise order is generated, and the order frequency information of the noise is obtained based on the bubble chart, and / or the change of the noise with the working condition is obtained, and / or the components that generate the order noise are located; wherein the horizontal coordinate and the vertical coordinate of the bubble chart and the size of the bubbles in the bubble chart are determined according to the multiple characteristic dimensions.

[0061] The noise order analysis method, device, computer equipment, computer-readable storage medium and computer program product obtain frequency domain noise data of the electromechanical product to be tested under different working conditions, and determine the noise frequency value corresponding to each working condition for each working condition in the frequency domain noise data; divide the noise frequency value by the corresponding working condition value to perform working condition normalization processing to obtain the normalized noise frequency value, determine the frequency domain noise data, classify the frequency domain noise data according to the preset feature dimension, and obtain the corresponding noise feature data under the preset feature dimension; splice the noise feature data to obtain a noise feature data set, and generate a noise feature data set for analyzing the noise according to the noise feature data set. The bubble chart of the sound order can be used to determine the noise frequency value and amplitude change trend of each order. This method only needs to classify and splice the frequency domain noise data according to the preset feature dimensions to obtain the noise feature data set used to generate the bubble chart. No additional processing of the frequency domain noise data is required, which simplifies the data processing process. At the same time, the noise characteristics of electromechanical products are analyzed in a simple data visualization way by generating a bubble chart. This process does not require a large amount of computing resources, that is, the noise characteristics of electromechanical products can be analyzed in an efficient and low-resource consumption manner. Moreover, this noise order analysis method can be extended to different working conditions and products, and has strong versatility. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0063] Figure 1 is an application environment diagram of a noise order analysis method in one embodiment;

[0064] Figure 2 Schematic diagram of a flow chart of a noise order analysis method in one embodiment;

[0065] Figure 3 It is a schematic flow chart of a working condition normalization processing method in one embodiment;

[0066] Figure 4An example of a time domain data acquisition result of noise in one embodiment;

[0067] Figure 5 An example of a frequency domain conversion result of noise data in one embodiment;

[0068] Figure 6 is a schematic flow chart of step 208 in one embodiment;

[0069] Figure 7 Schematic diagram of a method for generating a bubble chart in one embodiment;

[0070] Figure 8 A schematic diagram of a bubble diagram in one embodiment;

[0071] Fig. 9 is a flow chart of a noise order analysis method in another embodiment;

[0072] Fig.10 is a structural block diagram of a noise order analysis device in one embodiment;

[0073] Fig.11 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0075] It is understandable that the noise of electromechanical products not only directly affects the sensory experience of users, but is also a key factor restricting its performance improvement and an important reference for fault diagnosis. The order of noise reflects the periodicity of the operation of components in electromechanical products. Through noise order analysis, it can be used to determine the main components that generate noise and the working conditions that produce resonance, thereby providing guidance for product improvement. Electromechanical products can be, but are not limited to, hydraulic pumps, engines, and generators.

[0076] Existing noise order analysis is mainly presented in the form of waterfall charts, color maps, order slice charts, etc. These presentation forms can intuitively show the state of noise order and the trend of changes with working conditions (such as speed), but cannot intuitively read the noise frequency value and trend value of each order, and all need complex processing programs or professional tools to produce, resulting in complex noise order analysis, low efficiency and high resource consumption.

[0077] In order to solve the technical problem that the noise order analysis method is complex and requires a lot of resources, continuously occupies resources and leads to low resource utilization, a noise order analysis method is proposed, which obtains frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes characteristics of multiple feature dimensions; for each working condition in the frequency domain noise data, the noise frequency value corresponding to each working condition is determined; the noise frequency value is divided by the corresponding working condition value for working condition normalization processing to obtain the normalized noise frequency value, and the frequency domain noise data is determined, and the frequency domain noise data is classified according to the preset feature dimension to obtain the corresponding noise feature data under the preset feature dimension; the noise feature data is spliced ​​to obtain a noise feature data set; based on the noise feature data set, a bubble chart for analyzing the noise order is generated. This method can analyze the noise characteristics of electromechanical products in an efficient and low resource consumption manner.

[0078] The noise order analysis method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the electromechanical product 104 through the network. The data storage system can store the data that the terminal 102 needs to process. The data storage system can be integrated on the terminal 102, or it can be placed on a cloud server or other network server. The terminal obtains the frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the frequency domain noise data is classified according to the preset feature dimensions to obtain the corresponding noise feature data under the preset feature dimensions; the noise feature data is spliced ​​to obtain a noise feature data set; according to the noise feature data set, a bubble chart for analyzing the noise order is generated. Among them, the terminal 102 can be but is not limited to various personal computers, laptops, smart phones, tablets, Internet of Things devices, portable wearable devices, etc. The electromechanical product 104 can be different types of electromechanical products, which are not limited here.

[0079] In an exemplary embodiment, Figure 2 As shown in the figure, a noise order analysis method is provided, which can be applied to Figure 1 The terminal in the example is used to illustrate, including the following steps 202 to 208. Among them:

[0080] Step 202, obtaining frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions, and the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition.

[0081] It is understandable that in rotating machinery, the frequency of the noise signal is often related to the speed (rotational frequency) in multiples, and this relationship is called order. Each rotating component, such as the engine crankshaft, transmission gear, piston or tire, will produce a response at a specific order, which may include vibration and noise. The analysis of noise order can achieve product noise performance improvement, operating condition impact analysis, and fault or defect location of complex electromechanical products.

[0082] The different working conditions here can be any of the state parameters of the operation of the electromechanical product, such as different speeds, reciprocating frequencies, ambient temperatures, working temperatures, etc. For example, the different working conditions can be the speed of a rotating machine, or the reciprocating frequency of a reciprocating machine. This embodiment takes different speeds as an example for explanation.

[0083] The frequency domain noise data under different working conditions can be data on the change of noise over time, or data on the change of noise over other physical quantities such as running distance. In this embodiment, the frequency domain noise data under different working conditions is the change of noise amplitude over time under different working conditions, and the data under different working conditions are obtained. This data includes but is not limited to working condition data, noise amplitude, and noise frequency data. The frequency domain noise data of the electromechanical product to be tested can be collected by a signal acquisition device, and the type of signal acquisition device is not limited here. The multiple feature dimensions can be but are not limited to at least one of amplitude, frequency, and working condition.

[0084] Exemplarily, according to the time domain acquisition standard of noise, when the electromechanical product to be tested is in operation, the change of its noise amplitude over time under different operating conditions is tested, and the time, noise amplitude and other data under different operating conditions are obtained, and the noise time domain data under different operating conditions are obtained. The noise time domain data is converted to obtain the corresponding frequency domain noise data under different operating conditions.

[0085] Step 204 : for each operating condition in the frequency domain noise data, determine the noise frequency value corresponding to each operating condition.

[0086] Step 206 , dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data.

[0087] It should be noted that the operating conditions may affect the noise periodicity of the electromechanical products under test, resulting in the noise amplitude being incomparable, and thus resulting in low reliability of the analysis results of the noise order. Therefore, the operating conditions need to be normalized.

[0088] The normalization process here can be understood as dividing the frequency value in the noise frequency domain data under each working condition by the corresponding working condition value. For example, for the time domain data obtained by testing the rotating machinery at a speed of 1000r / min, for the frequency domain noise data obtained after conversion, the frequency is divided by the speed per second (i.e. 1000 / 60 r / s) to obtain the normalized frequency value for the working condition of 1000r / min. After normalizing the working condition of the frequency, the periodicity of the working condition will not be taken into account when comparing the amplitude, eliminating the influence of the periodicity of the working condition.

[0089] Step 208: classify the frequency domain noise data according to the preset feature dimension to obtain the corresponding noise feature data under the preset feature dimension.

[0090] Among them, the preset characteristic dimension can be determined based on the multiple characteristic dimensions included in the frequency domain noise data. When specifically determining which characteristic dimension is determined as the preset characteristic dimension, it can be determined according to the actual application scenario. For example, the working condition that affects the amplitude can be used as the preset characteristic dimension, or the frequency that affects the amplitude can be used as the preset characteristic dimension. In this embodiment, the working condition that affects the amplitude is used as the preset characteristic dimension. For the electromechanical product to be tested, there will be at least one frequency under the same working condition. The amplitude corresponding to at least one frequency may be the same, different, or partially the same and partially different.

[0091] It is understandable that the frequency domain noise data includes data under different working conditions, that is, the frequency domain noise data can be regarded as a data set, which includes the frequency domain noise data under each working condition. Exemplarily, by classifying all the obtained frequency domain noise data according to the working condition, noise characteristic data such as the frequency and noise amplitude belonging to each working condition can be obtained. For example, noise characteristic data such as the frequency and noise amplitude corresponding to working condition 1, working condition 2, ..., working condition n can be obtained respectively.

[0092] Step 210: splice the noise feature data according to a preset format to obtain a noise feature data set.

[0093] Among them, the splicing method can be that all the noise feature data obtained in step 208 are based on the preset feature dimension, and the corresponding noise feature data are sequentially spliced ​​according to the preset format to obtain a noise feature data set. The splicing method can be to aggregate all the noise feature data together to obtain a 3×n table or matrix. The preset format can be working condition-frequency-noise amplitude. Taking a table as an example, the first column of the table is the working condition, the second column is the frequency, and the third column is the noise amplitude.

[0094] When the preset feature dimension is the working condition, the corresponding noise feature data may be concatenated in sequence according to the size of the working condition value to obtain a noise feature data set.

[0095] It is understandable that, on the basis of obtaining the noise characteristic data set, the obtained noise characteristic data set can also be directly analyzed without visualizing it, to determine the noise frequency values ​​with larger bubble sizes that exist under different working conditions, and to obtain the trend of bubble size changes with working conditions at the same frequency. In addition, based on the periodic relationship between the order frequency domain and the component structure, the components that generate order noise can be located, so that improvements can be made to the components. For the frequencies with the fastest and largest changes in bubble size at the same frequency, the source of the parts causing the order noise can be located, and improvements and optimizations can be made. For the frequency differences with larger bubble sizes under different working conditions, the impact of working condition differences on noise can be analyzed. By comparing the bubble size and order frequency differences between qualified products and faulty parts (or unqualified products), faulty or defective components can be analyzed and located.

[0096] Step 212, based on the noise feature data set, generate a bubble chart for analyzing the noise order, obtain the noise order frequency information based on the bubble chart, and / or obtain the change of noise with the working condition, and / or locate the components that generate the order noise; wherein the horizontal and vertical coordinates of the bubble chart and the size of the bubbles in the bubble chart are determined according to multiple feature dimensions.

[0097] Among them, the noise feature data set includes features such as frequency and noise amplitude under different working conditions. The frequencies of multiple feature dimensions are used as the horizontal coordinates of the bubble chart, and the working conditions in multiple feature dimensions are used as the vertical coordinates of the bubble chart. The size of the bubble chart is used to characterize the noise amplitude. The bubble form can be set to a shape with only a border and no filling. The shape can be but not limited to a circle.

[0098] Exemplarily, for each frequency under each operating condition in the noise characteristic data set and the noise amplitude corresponding to each frequency, a coordinate point is determined in the bubble chart according to each operating condition and each frequency under each operating condition, and a bubble chart with the bubble size as the noise amplitude is determined with the coordinate point as a reference. Based on the obtained bubble chart, the noise frequency value with larger bubble size that exists under different operating conditions can be intuitively obtained, that is, the order frequency information of the noise can be obtained, wherein the multiple relationship between the frequencies with larger bubble sizes is the multiple frequency relationship of the order. Based on the bubble chart, the trend of the bubble size changing with the operating condition at the same frequency can be obtained, that is, the change of noise with the operating condition. It can be understood that the larger of the larger bubble sizes is relative to the reference bubble size, and the reference bubble size can be determined according to actual needs, which is not limited here.

[0099] Furthermore, based on the periodic relationship between the order frequency domain and the component structure, the component that generates order noise can be located so that improvement can be made to the component; for the frequency at which the bubble size changes the fastest and the largest under the same frequency, the source of the component that generates order noise can be located and improvement and optimization can be carried out; for the large frequency differences in bubble size under different working conditions, the impact of the working condition differences on noise can be analyzed; by comparing the bubble size and order frequency differences between qualified products and faulty parts (or unqualified products), faulty or defective components can be analyzed and located.

[0100] In the above noise order analysis method, by obtaining the frequency domain noise data of the electromechanical product to be tested under different working conditions, the frequency domain noise data is classified according to the preset feature dimension to obtain the corresponding noise feature data under the preset feature dimension; the noise feature data is spliced ​​to obtain a noise feature data set, and a bubble chart for analyzing the noise order is generated according to the noise feature data set. The noise frequency value and amplitude change trend of each order can be determined in the form of a bubble chart. This method only needs to classify and splice the frequency domain noise data according to the preset feature dimension to obtain the noise feature data set for generating the bubble chart. No additional processing of the frequency domain noise data is required, which simplifies the data processing process. At the same time, the noise characteristics of the electromechanical product are analyzed in a simple data visualization method of generating a bubble chart. This process does not require a large amount of computing resources, and this noise order analysis method can be extended to different working conditions and products, that is, the noise characteristics of the electromechanical product can be analyzed in an efficient and low resource consumption manner.

[0101] Furthermore, after normalizing the frequency conditions, in order to reduce the amount of data processing, for each condition in the frequency domain noise data, the amplitude of the noise under each condition that is less than the preset amplitude can be filtered out to obtain the frequency domain noise data. This method can remove the frequencies with amplitudes less than a specific threshold in the noise frequency domain data under each condition, thereby retaining the frequency domain data with larger amplitudes.

[0102] It can be explained that, in order to facilitate the comparability of the amplitude and to facilitate the better display of the noise feature data set in the form of a bubble chart, the noise amplitude can also be normalized. Figure 3 As shown, a noise amplitude normalization processing method is provided, including steps 302 to 306, wherein:

[0103] Step 302: Acquire time domain noise data of the electromechanical product to be tested under different working conditions.

[0104] Step 304 , convert the time domain noise data to obtain intermediate frequency domain noise data under different working conditions.

[0105] Step 306: normalize the noise amplitude in the intermediate frequency domain noise data to obtain frequency domain noise data.

[0106] The time domain noise data may be converted by, but not limited to, Fourier transform, fast Fourier transform, etc. The specific processing method may be implemented by existing methods, which will not be described in detail here. The normalization processing here may be to normalize the noise amplitude to a preset numerical range, and the preset numerical range may be, but not limited to, the range from 0 to 1.

[0107] For example, according to the time domain acquisition standard of noise, when the electromechanical product to be tested is running, the change of its noise amplitude over time under different working conditions is tested, and the time, noise amplitude and other data under different working conditions are obtained, and the noise time domain data under different working conditions are obtained. The time domain noise data is subjected to Fourier transform or fast Fourier transform FFT to obtain the intermediate frequency domain noise data under different working conditions; the noise amplitude in the intermediate frequency domain noise data is normalized to obtain the frequency domain noise data. Figure 4 As shown in FIG. 1 , an example of the time domain data acquisition result of noise in an embodiment is shown. The horizontal axis represents time in seconds (S), and the vertical axis represents the noise amplitude. Figure 4 After converting the time domain data shown, we get Figure 5 An example of the frequency domain conversion results of the noise data shown, Figure 5 In the graph shown, the horizontal axis represents frequency in Hertz (Hz), and the vertical axis represents the normalized noise amplitude. This approach ensures the comparability of the amplitude and better displays the noise feature data set in the form of a bubble chart.

[0108] In an exemplary embodiment, Figure 6 As shown, step 208 includes steps 602 to 604, wherein:

[0109] Step 602: Determine an amplitude influence index that affects the noise amplitude according to the characteristics of the multiple characteristic dimensions.

[0110] It is understandable that the number of amplitude influence indicators of the noise amplitude can be one or more, for example, it can be the working condition or the load size, or it can be the working condition and the load size. The amplitude influence indicator affecting the noise amplitude can be determined based on the operating environment and actual needs of the electromechanical product to be tested. This embodiment is described using the amplitude influence indicator as the working condition.

[0111] Step 604 , classify the frequency domain noise data according to the amplitude influence index to obtain noise feature data under the feature dimension that affects the amplitude.

[0112] Optionally, the frequency domain noise data is classified according to the working conditions in the amplitude influence index to obtain multiple target amplitudes and target frequency values ​​under the same working condition. Further, the target amplitudes and target frequency values ​​under the same working condition can be spliced ​​to obtain a noise feature data set.

[0113] Among them, the frequency domain noise data here can be the data determined by not undergoing normalization processing for the frequency working condition in the above-mentioned embodiment, and / or not undergoing normalization processing for the noise amplitude, and / or not filtering out the data whose noise amplitude is less than the preset amplitude under each working condition, or it can be the data determined by undergoing normalization processing for the noise amplitude, normalization processing for the frequency working condition, and filtering out the data whose noise amplitude is less than the preset amplitude under each working condition.

[0114] In this embodiment, the influence of the working conditions on the noise amplitude is taken into consideration, and a noise feature data set is obtained by grouping and summarizing the frequency, working conditions and noise amplitude. The noise feature data set is divided into a group of three variables to display the influence relationship one by one, which can intuitively display the noise order frequency and the noise amplitude at different orders with the working conditions.

[0115] It should be noted that the bubble chart can intuitively display the order frequency of the noise and the change trend of the noise amplitude under different orders with the working conditions. In an exemplary embodiment, Figure 7 As shown, a method for generating a bubble chart is provided, comprising steps 702 to 706, wherein:

[0116] Step 702, determining a first value range of the horizontal axis in the bubble chart according to the noise frequency in the noise characteristic data, and determining a second value range of the vertical axis in the bubble chart according to the operating condition value.

[0117] It is understandable that bubble charts can display data in at least three or even four dimensions, for example, through the size, color, and horizontal and vertical coordinate positions of bubbles, which helps to analyze and understand the relationship between different variables. For example, the relationship between noise frequency and operating value can be observed at the same time, as well as their impact on bubble size (which may represent noise intensity or other indicators). Moreover, the comparison between different bubbles becomes more intuitive, and the size and color differences of the bubbles can be used to identify which frequencies or operating values ​​have significant noise characteristics.

[0118] The noise frequency may be a normalized noise frequency or an unnormalized noise frequency. Optionally, the first numerical range of the horizontal axis in the bubble chart is determined according to the noise frequency in the noise characteristic data, and the second numerical range of the vertical axis in the bubble chart is determined according to the operating condition value, so as to reasonably determine the rationality of the numerical values ​​of the horizontal and vertical axes of the bubble chart.

[0119] It is understandable that when the amount of data in the obtained noise characteristic data set is relatively large, if all the noise characteristic data are displayed in the form of a bubble chart, it may cause the bubble chart to be dense and unable to obtain the order frequency of the noise, and the change trend of the noise amplitude at different orders with the working conditions. Optionally, in an exemplary embodiment, the corresponding amplitude or frequency in the noise characteristic data set can be filtered according to a preset amplitude range or a preset frequency range, and the noise characteristic data of a specified part can be displayed in a targeted manner through a bubble chart.

[0120] Step 704: The operating condition value of each operating condition in the noise characteristic data set and each target frequency corresponding to the operating condition value are taken as the center of the bubble.

[0121] Step 706, determining the size of the bubble according to the target amplitude corresponding to each target frequency, and generating a bubble diagram for analyzing the noise order, wherein the bubble size is the bubble area or the bubble diameter.

[0122] Exemplarily, the first numerical range of the horizontal axis in the bubble chart is determined according to the noise frequency in the noise feature data, and the second numerical range of the vertical axis in the bubble chart is determined according to the operating value; the operating value of each operating condition in the noise feature data set and each target frequency corresponding to the operating value are used as the center of the bubble; the size of the bubble is determined according to the target amplitude corresponding to each target frequency, and a bubble chart for analyzing the noise order is generated. The influence relationship is displayed one by one in the form of a group of three variables: operating condition, frequency, and noise amplitude. It can be understood that it can also be extended to more variables, and the influence relationship of multiple variables can be displayed using a high-dimensional graph. The variables here can be understood as variables that affect the amplitude.

[0123] like Figure 8 As shown, it is a bubble chart in an embodiment, the working condition is the speed, the horizontal axis is the frequency normalized by the speed, the vertical axis is the working condition, that is, the speed, and the bubble size represents the noise amplitude. When the frequency normalized by the speed is 15, bubbles exist under different working conditions, and the number of bubbles with larger sizes is the largest, which means that the vibration is very serious. Then, according to the mechanism design of the electromechanical product to be tested and the properties of the structure itself, it can be determined that the vibration is caused by the gear, and then the analysis result of the component can be generated, and the analysis result can be sent to the terminal where the user is located, so that the user can improve the component.

[0124] In the above embodiment, by displaying the influence relationship one by one in the form of a group of three variables, namely, working condition, frequency and noise amplitude, it is possible to intuitively display the order frequency of the noise and the changing trend of the noise amplitude at different orders with the working condition, locate the source of the parts of the order noise, and analyze the influence of the working condition difference on the noise for the large frequency difference of the bubble size under different working conditions; further, by comparing the bubble size and order frequency differences between qualified products and faulty parts, it is possible to analyze and locate the parts with faults or defects.

[0125] Optionally, in an exemplary embodiment, the features of the multiple feature dimensions also include load values, and the noise feature data set includes multiple target amplitudes, target frequency values, and target load values ​​under the same operating condition. Based on the noise feature data set, a bubble chart for analyzing noise orders is generated, including: determining a first numerical range of the horizontal axis in the bubble chart according to the noise frequency in the noise feature data, and determining a second numerical range of the vertical axis in the bubble chart according to the operating condition value; taking the operating condition value of each operating condition in the noise feature data set and each target frequency corresponding to the operating condition value as the center of the bubble; determining the size of the bubble according to the target amplitude corresponding to each target frequency, and determining the color or shape of the bubble according to the target load value corresponding to the target amplitude, to generate a bubble chart for analyzing noise orders. This method uses the four variables of operating condition, frequency, noise amplitude, and load value as a group to display the influence relationship one by one.

[0126] In an exemplary embodiment, Fig. 9 As shown in the figure, a noise order analysis method is provided, which can be applied to Figure 1 The terminal in is taken as an example to illustrate, including the following steps 902 to 916. Among them:

[0127] Step 902: Acquire time domain noise data of the electromechanical product to be tested under different working conditions.

[0128] Step 904: convert the time domain noise data to obtain intermediate frequency domain noise data under different working conditions.

[0129] Step 906: normalize the noise amplitude in the intermediate frequency domain noise data to obtain frequency domain noise data.

[0130] Step 908: for each operating condition in the frequency domain noise data, determine the noise frequency value corresponding to each operating condition.

[0131] Step 910, divide the noise frequency value by the corresponding working condition value to perform working condition normalization processing to obtain a normalized noise frequency value, and filter out the noise amplitude under each working condition that is less than a preset amplitude to obtain frequency domain noise data.

[0132] Step 912: classify the frequency domain noise data according to the preset feature dimension to obtain the corresponding noise feature data under the preset feature dimension.

[0133] Step 914, concatenate the noise feature data to obtain a noise feature data set.

[0134] Step 916: Generate a bubble chart for analyzing noise orders based on the noise feature data set.

[0135] It should be noted that the specific implementation of this embodiment can be achieved in the above-mentioned manner, which will not be elaborated here.

[0136] In the above embodiment, the order analysis of noise frequency can be realized through the time domain acquisition of noise data, the frequency domain conversion of noise data, the working condition normalization processing of frequency, the amplitude filtering of noise frequency domain data, the splicing of noise frequency domain data and the bubble chart display of noise frequency domain data. This method only needs to classify and splice the frequency domain noise data according to the preset feature dimensions to obtain the noise feature data set for generating the bubble chart. No additional processing of the frequency domain noise data is required, which simplifies the data processing process. At the same time, the noise characteristics of electromechanical products are analyzed by generating a bubble chart, which is a simple data visualization method. No professional tools are required, and the noise order can be intuitively analyzed and displayed to obtain the change trend of the noise amplitude with the working condition under different orders, which can be used for product noise performance improvement, working condition impact analysis, and fault or defect location of complex electromechanical products. Furthermore, this method can also be used for periodic analysis of other physical quantities other than noise.

[0137] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0138] Based on the same inventive concept, the embodiment of the present application also provides a noise order analysis device for implementing the noise order analysis method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more noise order analysis devices provided below can refer to the limitations of the noise order analysis method above, and will not be repeated here.

[0139] In an exemplary embodiment, Fig.10 As shown, a noise order analysis device is provided, comprising: a data acquisition module 1002, a normalization module 1004, a classification module 1006, a splicing module 1008 and a display module 1010, wherein:

[0140] The data acquisition module 1002 is used to acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions, and the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition.

[0141] A normalization module 1004 is used to determine the noise frequency value corresponding to each operating condition for each operating condition in the frequency domain noise data;

[0142] The noise frequency value is divided by the corresponding operating condition value to perform operating condition normalization processing, obtain the normalized noise frequency value, and determine the frequency domain noise data.

[0143] The classification module 1006 is used to classify the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension.

[0144] The splicing module 1008 is used to splice the noise feature data according to a preset format to obtain a noise feature data set.

[0145] The display module 1010 is used to generate a bubble chart for analyzing noise orders based on a noise feature data set, obtain order frequency information of noise based on the bubble chart, and / or obtain the change of noise with working conditions, and / or locate components that generate order noise; wherein the horizontal and vertical coordinates of the bubble chart and the size of the bubbles in the bubble chart are determined based on multiple feature dimensions.

[0146] The above-mentioned noise order analysis device obtains frequency domain noise data of the electromechanical product to be tested under different working conditions, classifies the frequency domain noise data according to preset feature dimensions, and obtains corresponding noise feature data under the preset feature dimensions; splices the noise feature data to obtain a noise feature data set, and generates a bubble chart for analyzing the noise order based on the noise feature data set. The noise frequency value and amplitude change trend of each order can be determined in the form of a bubble chart. This method only needs to classify and splice the frequency domain noise data according to the preset feature dimensions to obtain the noise feature data set for generating the bubble chart. No additional processing of the frequency domain noise data is required, which simplifies the data processing process. At the same time, the noise characteristics of the electromechanical product are analyzed in a simple data visualization method of generating a bubble chart. This process does not require a large amount of computing resources, and this noise order analysis method can be extended to different working conditions and products, that is, the noise characteristics of the electromechanical product can be analyzed in an efficient and low-resource manner.

[0147] In an exemplary embodiment, the noise order analysis device also includes a filtering module, which is used to filter out the noise amplitude under each operating condition that is less than a preset amplitude for each operating condition in the frequency domain noise data to obtain frequency domain noise data.

[0148] In an exemplary embodiment, the classification module 1006 is also used to determine the amplitude influence index that affects the noise amplitude according to the characteristics of multiple characteristic dimensions; classify the frequency domain noise data according to the amplitude influence index to obtain the noise characteristic data under the characteristic dimension that affects the amplitude.

[0149] In an exemplary embodiment, the classification module 1006 is further used to classify the frequency domain noise data according to the working conditions in the amplitude influence index to obtain multiple target amplitudes and target frequency values ​​under the same working condition;

[0150] The noise feature data are spliced ​​to obtain a noise feature data set, including:

[0151] The target amplitude and target frequency values ​​under multiple same working conditions are spliced ​​to obtain a noise feature data set.

[0152] In an exemplary embodiment, the display module 1010 is further used to determine a first value range of the horizontal axis in the bubble graph according to the noise frequency in the noise characteristic data, and to determine a second value range of the vertical axis in the bubble graph according to the operating condition value;

[0153] The operating value of each operating condition in the noise characteristic data set and each target frequency corresponding to the operating value are taken as the center of the bubble;

[0154] The size of the bubble is determined according to the target amplitude corresponding to each target frequency, and a bubble diagram for analyzing the noise order is generated, wherein the bubble size is the bubble area or the bubble diameter.

[0155] In an exemplary embodiment, the display module 1010 is further used to determine a first value range of the horizontal axis in the bubble graph according to the noise frequency in the noise feature data set, and to determine a second value range of the vertical axis in the bubble graph according to the operating condition value;

[0156] The operating value of each operating condition in the noise characteristic data set and each target frequency corresponding to the operating value are taken as the center of the bubble;

[0157] The size of the bubble is determined according to the target amplitude corresponding to each target frequency, and the color or shape of the bubble is determined according to the target load value corresponding to the target amplitude, so as to generate a bubble diagram for analyzing the noise order.

[0158] In an exemplary embodiment, the noise order analysis device also includes a signal processing module for obtaining time domain noise data of the electromechanical product to be tested under different working conditions; converting the time domain noise data to obtain intermediate frequency domain noise data under different working conditions; and normalizing the noise amplitude in the intermediate frequency domain noise data to obtain frequency domain noise data.

[0159] Each module in the above noise order analysis device can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0160] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Fig.11As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a noise order analysis method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0161] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0162] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0163] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0164] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0165] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0166] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0167] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0168] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A noise order analysis method, characterized in that: The method comprises: Acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition; For each operating condition in the frequency domain noise data, determining a noise frequency value corresponding to each operating condition; Dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data; Classifying the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension; The noise characteristic data are spliced ​​according to a preset format to obtain a noise characteristic data set; Generate a bubble graph for analyzing the noise order according to the noise feature data set, obtain the order frequency information of the noise based on the bubble graph, and / or obtain the change of the noise with the working condition, and / or locate the components that generate the order noise; wherein the abscissa and ordinate of the bubble graph and the size of the bubbles in the bubble graph are determined according to the multiple feature dimensions; The features of the multiple feature dimensions also include a load value, the noise feature data set includes a plurality of target amplitudes, target frequency values, and target load values ​​under the same working condition, and the bubble chart for analyzing the noise order is generated according to the noise feature data set, including: Determine a first numerical range of the horizontal axis in the bubble graph according to the noise frequency in the noise feature data set, and determine a second numerical range of the vertical axis in the bubble graph according to the operating condition value; Taking the operating condition value of each operating condition in the noise characteristic data set and each target frequency corresponding to the operating condition value as the center of the bubble; The size of the bubble is determined according to the target amplitude corresponding to each target frequency, and the color or shape of the bubble is determined according to the target load value corresponding to the target amplitude, to generate a bubble diagram for analyzing the noise order, wherein the size of the bubble is the bubble area or the bubble diameter.

2. The method according to claim 1, characterized in that The method further comprises: For each operating condition in the frequency domain noise data, the amplitude of the noise under each operating condition that is less than the preset amplitude is filtered out to obtain the frequency domain noise data.

3. The method according to claim 2, characterized in that The classifying the frequency domain noise data according to a preset feature dimension to obtain the corresponding noise feature data under the preset feature dimension includes: Determining an amplitude influence index affecting the noise amplitude according to the characteristics of the multiple characteristic dimensions; The frequency domain noise data is classified according to the amplitude influence index to obtain noise feature data under a feature dimension that affects the amplitude.

4. The method according to claim 3, characterized in that: The classifying the frequency domain noise data according to the amplitude influence index to obtain noise feature data under the feature dimension affecting the amplitude includes: Classifying the frequency domain noise data according to the working conditions in the amplitude influence index to obtain a plurality of target amplitudes and target frequency values ​​under the same working condition; The step of splicing the noise feature data to obtain a noise feature data set includes: A plurality of target amplitudes and target frequency values ​​under the same working condition are concatenated to obtain a noise characteristic data set.

5. The method according to claim 1, characterized in that The obtaining of frequency domain noise data of the electromechanical product to be tested under different working conditions includes: Obtain the time domain noise data of the electromechanical products under test under different working conditions; Converting the time domain noise data to obtain intermediate frequency domain noise data under different working conditions; The noise amplitude in the intermediate frequency domain noise data is normalized to obtain frequency domain noise data.

6. A noise order analysis device, characterized in that: The device implements the steps of the method described in claim 1, and the device comprises: A data acquisition module, used to acquire frequency domain noise data of the electromechanical product to be tested under different working conditions; the frequency domain noise data includes features of multiple feature dimensions; the features of the multiple feature dimensions include at least the noise frequency and noise amplitude under each working condition; A normalization module, for determining, for each operating condition in the frequency domain noise data, a noise frequency value corresponding to each operating condition; Dividing the noise frequency value by the corresponding operating condition value to perform operating condition normalization processing, obtain a normalized noise frequency value, and determine frequency domain noise data; A classification module, used to classify the frequency domain noise data according to a preset feature dimension to obtain corresponding noise feature data under the preset feature dimension; A splicing module, used for splicing the noise characteristic data according to a preset format to obtain a noise characteristic data set; A display module is used to generate a bubble chart for analyzing noise orders based on the noise feature data set, obtain order frequency information of noise based on the bubble chart, and / or obtain the change of noise with working conditions, and / or locate components that generate order noise; wherein the horizontal and vertical coordinates of the bubble chart and the size of the bubbles in the bubble chart are determined based on multiple feature dimensions.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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