System equalization analysis method, device, equipment and storage medium

Abstract

Embodiments of the present application disclose a system balance analysis method and device, equipment and a storage medium, wherein the system balance analysis method and device are applied to a balance analysis equipment, the balance analysis equipment comprises a control panel and a control system for setting configuration parameters, the control system performs the following steps: generating vibration description data based on preset configuration parameters; collecting vibration data output by the system as back-drawing data in the process of driving the system to vibrate by using the vibration description data; performing analysis on at least one dimension data of the vibration description data and corresponding back-drawing data to obtain a mapping relationship set between the at least one dimension data in the vibration description data and the back-drawing data, and obtaining an effect balance analysis result of the system through the mapping relationship set.

Description

Technical Field

[0001] This application relates to, but is not limited to, the field of electronic testing technology, and in particular to a system equilibrium analysis method, apparatus, equipment, and storage medium. Background Technology

[0002] With the development of mobile internet, electronic products are becoming increasingly popular among users. As electronic products become increasingly thinner, lighter, and more powerful, linear motors and power amplifiers are becoming mainstream applications. However, there are currently no standardized equalizer (EQ) analysis tools for these mainstream technologies, resulting in a lack of systematic and complete methods and low efficiency in equalization effect analysis. Summary of the Invention

[0003] In view of this, embodiments of this application provide at least one system equilibrium analysis method, apparatus, device, and storage medium.

[0004] The technical solution of this application embodiment is implemented as follows:

[0005] In a first aspect, embodiments of this application provide a system equilibrium analysis method applied to an equilibrium analysis device. The equilibrium analysis device includes a control panel for setting configuration parameters and a control system, wherein the control system performs the following steps:

[0006] Vibration description data is generated based on preset configuration parameters; during the process of driving the system to vibrate using the vibration description data, vibration data output by the system is collected as back-collected data; at least one dimension of data is analyzed on the vibration description data and the corresponding back-collected data to obtain a mapping relationship set between the vibration description data and the at least one dimension of data in the back-collected data, and the effect balance analysis result of the system is obtained through the mapping relationship set.

[0007] Secondly, embodiments of this application provide a system balancing analysis device applied to a balancing analysis equipment. The balancing analysis equipment includes a control panel for setting configuration parameters and a control system. The device includes:

[0008] The description generation module is used to generate vibration description data based on preset configuration parameters;

[0009] The data acquisition module is used to acquire the vibration data output by the system as back-collected data during the process of driving the system to vibrate using the vibration description data.

[0010] The equilibrium analysis module is used to analyze the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and to obtain the effect equilibrium analysis result of the system through the mapping relationship set.

[0011] Thirdly, embodiments of this application provide a balance analysis device, including a control panel for setting configuration parameters and a control system, wherein the control system performs some or all of the steps in the above method.

[0012] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements some or all of the steps in the above-described method.

[0013] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and are not intended to limit the technical solutions of this disclosure. Attached Figure Description

[0014] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application.

[0015] Figure 1 A schematic flowchart of an optional system equilibrium analysis method provided in an embodiment of this application;

[0016] Figure 2A A schematic flowchart of an optional system equilibrium analysis method provided in an embodiment of this application;

[0017] Figure 2B A schematic diagram of the frequency mapping expression provided in the embodiments of this application;

[0018] Figure 3A A schematic flowchart of an optional system equilibrium analysis method provided in an embodiment of this application;

[0019] Figure 3B A schematic diagram of the intensity mapping expression provided in the embodiments of this application;

[0020] Figure 4A A schematic flowchart of an optional system equilibrium analysis method provided in an embodiment of this application;

[0021] Figure 4B A schematic diagram of the intensity serialization expression provided in the embodiments of this application;

[0022] Figure 5A A logic flowchart of a system equilibrium analysis method provided in an embodiment of this application;

[0023] Figure 5B A system framework for a system equilibrium analysis method provided in the embodiments of this application;

[0024] Figure 6 A schematic diagram of the composition structure of a system equilibrium analysis device provided in this application embodiment;

[0025] Figure 7 This is a schematic diagram of the hardware entity of a balance analysis device provided in an embodiment of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application are further described in detail below with reference to the accompanying drawings and embodiments. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0028] The terms “first / second / third” are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that “first / second / third” may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used herein is for descriptive purposes only and is not intended to limit the scope of this application.

[0030] Before providing a further detailed description of the embodiments of this application, the nouns and terms involved in the embodiments of this application will be explained, and the nouns and terms involved in the embodiments of this application shall be interpreted as follows.

[0031] This application provides a system equilibrium analysis method applied to an equilibrium analysis device, which includes a control panel for setting configuration parameters and a control system. In implementation, different combinations of configuration parameters can be constructed through the control panel to generate vibration description data. This method can be executed by the control system of the equilibrium analysis device. The equilibrium analysis device can refer to devices with system equilibrium analysis capabilities, such as servers, laptops, tablets, desktop computers, smart TVs, set-top boxes, and mobile devices (e.g., mobile phones, portable video players, personal digital assistants, dedicated messaging devices, portable gaming devices).

[0032] Figure 1 The following is a schematic diagram of an optional process for the system equilibrium analysis method provided in the embodiments of this application, such as... Figure 1 As shown, the control system performs the following steps S110 to S130:

[0033] Step S110: Generate vibration description data based on preset configuration parameters.

[0034] Here, the preset configuration parameters are those defined by mainstream standards in the relevant field for analyzing the performance of equalization effects. These parameters may include at least one of frequency parameters and intensity parameters describing the vibration. The vibration description data may include at least one of vibration description files, vibration parameters, and vibration drive data. In implementation, vibration description data can be generated through various configuration combinations, such as at least one frequency parameter and at least one intensity parameter.

[0035] Step S120: During the process of driving the system to vibrate using the vibration description data, the vibration data output by the system is collected as back-collected data.

[0036] Here, the types of vibration data include vibration acceleration, voltage, current, etc. In implementation, the vibration description data is first input into the system to be analyzed manually or automatically, then the system is driven to vibrate, and the actual vibration data output by the system is collected and stored as back-collected data.

[0037] Step S130: Analyze the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and obtain the effect balance analysis result of the system through the mapping relationship set.

[0038] Here, because the acquired data includes velocity, acceleration, displacement, current, and voltage, signal processing, such as Discrete Fourier Transform, is first performed on the acquired data to obtain the actual frequency data and the actual intensity data at each moment corresponding to each waveform unit in the acquired data. A waveform unit includes, but is not limited to, a waveform of a complete vibration cycle, a waveform of half a vibration cycle, and a waveform of a quarter vibration cycle. In some implementations, intensity can be equivalent to amplitude, that is, the amplitude can reflect the intensity of the wave of the given material.

[0039] In some implementations, if the back-acquired data is collected when the system is driven by vibration description data generated using at least one frequency parameter, the back-acquired data can be analyzed in the frequency dimension to obtain the functional expressions of different frequency parameters or the mapping expressions between frequency parameters and actual frequencies as a set of mapping relationships between vibration description data and corresponding back-acquired data. Then, the system's performance balance can be analyzed using this set of mapping relationships.

[0040] In some implementations, if the back-collected data is collected when the system is driven by vibration description data generated using at least one strength parameter, the back-collected data can be analyzed in terms of strength dimension to obtain functional expressions of different strength parameters or mapping expressions between strength parameters and actual strength as a set of mapping relationships between vibration description data and corresponding back-collected data. Then, the system's performance balance can be analyzed using this set of mapping relationships.

[0041] In some implementations, if the acquired data is collected when the system is driven by vibration description data generated by a combination of at least one frequency parameter and at least one intensity parameter, then the acquired data can be comprehensively analyzed in terms of frequency and intensity dimensions to obtain functional expressions for different intensity parameters or mapping expressions between intensity parameters and actual intensity, as well as functional expressions for different frequency parameters or mapping expressions between frequency parameters and actual frequency. These are used as a set of mapping relationships between vibration description data and corresponding acquired data, and then the system's performance balance can be analyzed using this set of mapping relationships.

[0042] In this embodiment, vibration description data is first generated based on preset configuration parameters. Then, during the vibration process driven by the vibration description data, vibration data output by the system is collected as back-collected data. Finally, at least one dimension of the vibration description data and the corresponding back-collected data is analyzed to obtain a mapping relationship set between the vibration description data and the at least one dimension of the back-collected data. The system's effect balance analysis result is obtained through this mapping relationship set. Thus, by combining vibration description data generated with different configuration parameters and the calculation and analysis of actual vibration effects, a mapping relationship set between the input vibration description data and the final actual balance effect is obtained. This forms a systematic and complete balance effect analysis method, thereby improving the efficiency of system adjustment and optimization.

[0043] In some embodiments, before step S130 above, at least one of the following preprocessing operations can be performed on the acquired data: data pruning, shifting, and filtering; thus, step S130 above is further implemented as performing at least one dimension of analysis on the preprocessed acquired data to obtain the system's performance balance analysis result. In this way, performing analysis on the preprocessed acquired data from various dimensions can obtain more accurate and efficient analysis results.

[0044] In some embodiments, after step S130, the method further includes: verifying whether the effect balance analysis result meets the expected expression; if the effect balance analysis result does not meet the expected expression, adjusting the mapping relationship set of the configuration parameters and generating new vibration description data.

[0045] Here, the expected expression can be an expression between vibration description data summarized based on actual experience and the actual equalization effect, or it can be an ideal representation of vibration description data and actual equalization effect provided by a competitor. This application does not limit this.

[0046] In some implementations, a pre-set expected expression is used. After data is collected using a set of vibration description data and the effect balance analysis results are obtained, the obtained effect balance analysis results are compared with the expected expression to see if they are consistent. This enables autonomous and efficient analysis of the system's effect balance performance. In other implementations, the effect balance analysis results are used to redesign the mapping relationship set of configuration parameters using design software so that the final effect balance analysis results satisfy the expected expression. This forms a complete effect balance analysis process and achieves the purpose of adjusting the system's vibration effect.

[0047] In this way, by utilizing the gap between the effect balance analysis results and the expected expression, the preset configuration parameters are continuously adjusted so that the final effect balance analysis results meet the expected expression, thereby achieving the purpose of adjusting the system vibration effect.

[0048] In some embodiments, the preset configuration parameters include at least one frequency parameter, and the at least one dimension includes a frequency dimension. For example, by using the controlled variable method, other parameters besides the frequency parameter are fixed, vibration description data based on different combinations of frequency parameters are generated, input into the system, and then the data is re-collected for further analysis. Figure 1 , Figure 2A The following is a schematic diagram of an optional process for the system equilibrium analysis method provided in the embodiments of this application, such as... Figure 2A As shown, step S130 above, "analyzing the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and obtaining the effect balance analysis result of the system through the mapping relationship set," may include the following steps S210 to S220:

[0049] Step S210: Determine the frequency mapping expression between the at least one frequency parameter and the actual frequency corresponding to the back-collected data using data analysis methods.

[0050] Here, the data analysis method is a commonly used analysis method in the field of data processing, such as data fitting and numerical analysis, and this application embodiment does not limit it.

[0051] In some implementations, the preset configuration parameters include a frequency parameter, such as only a frequency intrinsic parameter. In this case, the frequency parameter and the actual frequency corresponding to the back-collected data are directly analyzed and processed to determine the frequency mapping expression.

[0052] In some implementations, the preset configuration parameters include multiple frequency parameters, such as frequency parameter 1 and frequency parameter 2. In practice, these multiple frequency parameters and the actual frequencies corresponding to the back-collected data can be directly analyzed and processed to determine the frequency mapping expression, i.e., F(frequency parameter 1, frequency parameter 2). Alternatively, numerical analysis can be performed on the multiple frequency parameters first to determine the first functional expression that the multiple frequency parameters satisfy. The first functional expression represents the functional relationship between different frequency parameters. Then, based on the first functional expression and the actual frequencies corresponding to the back-collected data, analysis and processing can be performed to obtain the frequency mapping expression.

[0053] For example, multiple frequency parameters represent the intrinsic and extrinsic frequency parameters describing motor vibration. These are used to obtain the frequency level parameter Fp through arithmetic operations such as addition, subtraction, multiplication, and division. For instance, for frequency parameters 1, 2, and 3, the first function expression can be expressed as: Fp = frequency parameter 1 + frequency parameter 2 - frequency parameter 3. For frequency parameters 4 and 5, it can also be expressed as Fp = frequency parameter 4 / frequency parameter 5. In practice, this first function expression can be determined through methods such as data fitting and numerical analysis.

[0054] Understandably, after signal processing, the acquired data is usually represented as a series of waveform units (such as sine or cosine waves). The actual frequency of each waveform unit is calculated based on the time interval corresponding to the zero crossing point of each waveform unit, and the maximum intensity is represented by the peak or trough of each waveform unit.

[0055] The frequency mapping expression characterizes the functional mapping between frequency parameters and the corresponding actual frequencies in the acquired data. It can be a piecewise frequency mapping or a linear frequency mapping. In implementation, the corresponding actual frequencies are obtained by performing an FFT transform on each acquired data point under each combination of frequency parameters, such as... Figure 2B As shown, the frequency level parameter Fp corresponding to each combination of frequency parameters is used as the horizontal axis, and the actual frequency Fr corresponding to the back-collected data is used as the vertical axis. Taking three sets of data (50,100), (51,101), and (52,104) as examples, frequency curve 21 is obtained through data fitting. The functional relationship corresponding to frequency curve 21 is the frequency mapping expression.

[0056] Step S220: Analyze the system's performance balance using the frequency mapping expression.

[0057] In some implementations, the influence of the system on the actual frequency under different frequency parameters is analyzed using only the frequency mapping expression, thereby analyzing the effect of equalization of the actual frequency; in other implementations, the effect of equalization of the actual frequency output by the system is analyzed by combining the first function expression and the frequency mapping expression.

[0058] In the above embodiments, by constructing at least one frequency parameter to form a vibration description file for the input system, and then collecting data and calculating and analyzing the collected actual frequencies, the expression and representation of the input vibration description file and the effect equalization are obtained, thereby forming a complete and efficient equalization effect analysis process.

[0059] In some embodiments, step S220 is followed by steps S230 and S240:

[0060] Step S230: Perform numerical analysis on the actual frequencies corresponding to at least two waveform units in the acquired data to determine the frequency serialization expression;

[0061] Here, the frequency serialization expression characterizes the functional relationship between the actual frequency corresponding to the waveform unit and time. This can be a piecewise change, a linear change, or a quadratic change. When the system vibration is a gradual vibration from one frequency to another, through data fitting, numerical analysis, and other methods, not only can the mapping relationship between each combination of frequency parameters and the actual frequency be fitted and calculated, but also the fitted curve expression, i.e., the frequency serialization expression, can be calculated between the actual frequency at the first moment and the actual frequency at the second moment during the frequency gradual change process.

[0062] It should be noted that when the motor vibrates at a single frequency, the actual frequency corresponding to different waveform units remains unchanged over time. In this case, the frequency serialization expression is simplified to a constant, namely the single frequency value.

[0063] Step S240: Analyze the system's performance balance using the frequency serialization expression.

[0064] Here, under different combinations of frequency parameters, we analyze whether the actual frequency variation of each waveform unit in the system output data over time conforms to the expected trend.

[0065] In the above embodiments, vibration description data of the input system is generated by constructing parameter combinations of different frequency sequences, and the data is collected back. The actual frequency output by the system is processed and calculated, and finally the functional relationship of frequency change with time, i.e., the frequency serialization expression, is obtained, so as to better analyze the equalization effect of the system.

[0066] In some embodiments, the preset configuration parameters include at least one intensity parameter, and the at least one dimension includes an intensity dimension. For example, by using the controlled variable method, other parameters besides the intensity parameter are fixed, vibration description data based on different combinations of intensity parameters are generated, input into the system, and then the data is re-collected for further analysis. Figure 1 , Figure 3A The following is a schematic diagram of an optional process for the system equilibrium analysis method provided in the embodiments of this application, such as... Figure 3A As shown, step S130 above, "analyzing the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and obtaining the effect balance analysis result of the system through the mapping relationship set," may include the following steps S310 to S320:

[0067] Step S310: Determine the intensity mapping expression between the at least one intensity parameter and the actual intensity corresponding to the back-collected data using data analysis methods.

[0068] In some implementations, the preset configuration parameters include a strength parameter, such as the intrinsic strength parameter of the motor. The strength parameter and the actual strength corresponding to the back-collected data are directly analyzed and processed to determine the strength mapping expression.

[0069] In some implementations, the preset configuration parameters include multiple strength parameters, such as strength parameter 1 and strength parameter 2. In practice, these multiple strength parameters and the actual strength corresponding to the backfill data can be directly analyzed and processed to determine the strength mapping expression, i.e., I(strength parameter 1, strength parameter 2). Alternatively, numerical analysis can be performed on the multiple strength parameters first to determine the second function expression that the multiple strength parameters satisfy. The second function expression represents the functional relationship between different strength parameters. Then, based on the second function expression and the actual strength corresponding to the backfill data, analysis and processing can be performed to obtain the strength mapping expression.

[0070] For example, various strength parameters represent the intrinsic and extrinsic strength parameters describing motor vibration. The strength level parameter Ip is obtained through certain arithmetic operations such as addition, subtraction, multiplication, and division. For instance, for strength parameters 1, 2, and 3, the second function expression can be expressed as: Ip = Strength parameter 1 + Strength parameter 2 - Strength parameter 3; for strength parameters 4 and 5, it can also be expressed as Ip = Strength parameter 4 / Strength parameter 5. In implementation, this second function expression can be determined through methods such as data fitting and numerical analysis.

[0071] The intensity mapping expression characterizes the functional relationship between intensity parameters and the actual intensity at each moment in the acquired data. In implementation, signal processing is performed on the acquired data obtained under multiple sets of intensity parameters to obtain the actual intensity data corresponding to each combination of intensity parameters, such as... Figure 3B As shown, the intensity level parameter Ip after each combination of intensity parameters is used as the horizontal axis, and the actual intensity Ir corresponding to each moment in the back-collected data is used as the vertical axis. Taking three sets of data (64,128), (66,132), and (68,136) as examples, the intensity curve 31 is calculated through data fitting, numerical analysis and other methods. The functional relationship corresponding to the intensity curve 31 is the intensity mapping expression mentioned above.

[0072] Step S320: Analyze the system's performance balance using the intensity mapping expression.

[0073] In some implementations, the influence of the system on the actual strength under different strength parameters is analyzed using only the strength mapping expression, thereby analyzing the effect balance of the actual strength. In other implementations, the effect balance of the actual strength output by the system is analyzed by combining the second function expression and the strength mapping expression.

[0074] In the above embodiments, by constructing at least one intensity parameter to form vibration description data of the input system, and then collecting data and calculating and analyzing the actual intensity collected, the relationship and manifestation of the input vibration description file and the effect equalization are obtained, thereby forming a complete and efficient equalization effect analysis process.

[0075] In some embodiments, step S320 is followed by steps S330 and S340:

[0076] Step S330: Perform numerical analysis on the actual intensity corresponding to each time point in the back-collected data to determine the intensity serialization expression.

[0077] Here, the intensity serialization expression characterizes the functional relationship between the actual intensity and time. When the system vibration is a gradual vibration that gradually changes from one intensity to another, through methods such as data fitting and numerical analysis, it is possible not only to fit and calculate the mapping relationship between each combination of intensity parameters and the actual intensity, but also to calculate the fitting curve expression, i.e., the intensity serialization expression, between the actual intensity at the first moment and the actual intensity at the second moment during the intensity gradual change process.

[0078] Step S340: Analyze the system's performance balance using the intensity serialization expression.

[0079] Here, under different combinations of intensity parameters, we analyze whether the variation pattern of the actual intensity at each moment in the system output data over time conforms to the expected trend.

[0080] In the above embodiments, vibration description data of the input system is generated by constructing parameter combinations of different intensity sequences, and the actual intensity in the back-collected data is processed and calculated to finally obtain a functional expression of intensity changing with time, i.e., an intensity serialization expression, so as to better analyze the system's equilibrium performance.

[0081] In some embodiments, the preset configuration parameters include at least one frequency parameter and at least one intensity parameter, and the at least one dimension includes a frequency dimension and an intensity dimension. Based on Figure 1 , Figure 4A The following is a schematic diagram of an optional process for the system equilibrium analysis method provided in the embodiments of this application, such as... Figure 4AAs shown, step S130 above, "analyzing the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and obtaining the effect balance analysis result of the system through the mapping relationship set," may include the following steps S410 to S450:

[0082] Step S410: With the at least one intensity parameter fixed, perform numerical analysis on the at least one frequency parameter and the actual frequency corresponding to each waveform unit in the acquired data to determine the frequency serialization expression.

[0083] Here, the frequency serialization expression characterizes the functional relationship between the actual frequency corresponding to the waveform unit and time. This can be a piecewise change, a linear change, or a quadratic change. In implementation, the intensity parameter can be fixed, and the frequency parameter can be input into the system. The actual frequency at different times of system output can be obtained through data acquisition. When the system vibration is a gradual vibration from one frequency to another, the frequency serialization expression can be obtained through methods such as data fitting and numerical analysis, for example, by performing linear fitting or numerical analysis on the actual frequency at the first and second times.

[0084] like Figure 4B As shown, time t is used as the horizontal axis and the actual frequency Fr obtained at different times is used as the vertical axis. Taking three sets of data (t1,100), (t1,102), and (t1,104) as examples, the frequency change curve 41 is calculated by data fitting, numerical analysis and other methods. The functional relationship corresponding to the frequency change curve 41 is the frequency serialization expression mentioned above.

[0085] Step S420: With the at least one frequency parameter fixed, perform numerical analysis on the at least one intensity parameter and the actual intensity corresponding to each moment in the acquired data to determine the intensity serialization expression.

[0086] Here, the intensity serialization expression characterizes the functional relationship between the actual intensity and time. In implementation, the frequency parameter can be fixed, the intensity parameter can be input into the system, and the actual intensity at different times of the system output can be obtained through data acquisition. When the system vibration is a gradual vibration from one intensity to another, the intensity serialization expression can be obtained by using methods such as data fitting and numerical analysis, for example, by performing linear fitting or numerical analysis on the actual intensity at the first time and the actual intensity at the second time.

[0087] Step S430: Combine the frequency serialization expression and the intensity serialization expression to analyze the effect balance performance of the system.

[0088] Here, multiple sets of frequency and intensity data that change over time are constructed using the frequency serialization expression and the intensity serialization expression. Then, the system's performance balance is analyzed by fitting the data of the other dimension while fixing one dimension (intensity or frequency).

[0089] Step S440: Under the condition of fixed frequency parameter bandwidth or frequency bandwidth, numerical analysis is performed on the at least one frequency parameter and the actual frequency corresponding to each waveform unit in the back-acquired data, and on the at least one intensity parameter and the actual intensity corresponding to each moment in the back-acquired data, to determine the comprehensive function expression.

[0090] Here, regarding the case of variable frequency vibration, i.e., the actual frequency variation corresponding to different waveform units, the frequency parameter bandwidth is determined based on the upper and lower limits of the frequency parameter among the at least one frequency parameter; the frequency bandwidth is determined based on the upper and lower limits of the actual frequencies corresponding to different waveform units in the acquired data. It can be understood that the numerical setting of the frequency parameter has a range, for example -50 to 200, meaning the upper limit of the frequency parameter is 200 and the lower limit is -50. Therefore, the frequency parameter bandwidth is determined as ΔF. P =250. Additionally, frequency bandwidth represents the range of actual frequency variation in the acquired data from the lower frequency limit to the upper frequency limit, denoted as ΔF.

[0091] Combinations of frequency parameters within different ranges can achieve the same frequency parameter bandwidth. For example, the frequency parameter bandwidth between frequency parameter 1 (value -100) and frequency parameter 2 (value 0) is 100, and the frequency parameter bandwidth between frequency parameter 1 (value -90) and frequency parameter 2 (value 10) is also 100. Since there is a mapping relationship between the frequency level parameters obtained from the frequency parameter combinations and the actual frequencies, the frequency bandwidth of the actual frequencies in the re-collected data is also fixed if the frequency parameter bandwidth is kept constant.

[0092] In practice, under the premise of fixed frequency parameter bandwidth, different combinations of frequency parameters and different combinations of intensity parameters can be directly configured and input into the system. By acquiring back sampled data, the actual frequency and actual intensity of different waveform units output by the system can be obtained. Through data fitting, numerical analysis and other methods, such as constructing a multivariate function set, the fixed frequency parameter bandwidth and multiple sets of actual intensities and actual frequencies can be substituted into the multivariate function set and solved to finally obtain the comprehensive function expression.

[0093] Step S450: Combine the frequency serialization expression, the intensity serialization expression, and the comprehensive function expression to analyze the performance balance of the system.

[0094] Here, in some implementations, frequency serialization expressions can be used to analyze the change of the actual frequency of the system output over time when the intensity remains constant; in some implementations, intensity serialization expressions can be used to analyze the change of the actual intensity of the system output over time when the frequency remains constant; in some implementations, comprehensive function expressions can be used to analyze the change of the actual intensity of the system output under different frequency parameter bandwidths or frequency bandwidths, or to analyze the relationship between the change of the actual frequency from f1 to f2 and the change of the actual intensity.

[0095] In the above embodiments, vibration description data of the input system is generated by constructing parameter combinations of different frequency sequences and parameter combinations of different intensity sequences. The data is then collected and processed to calculate the actual frequency and actual intensity output by the system. Finally, the function expressions of frequency and intensity over time are obtained, which enable a more comprehensive analysis of the system's performance balance.

[0096] The above system equilibrium analysis method will be described below with reference to a specific embodiment. However, it should be noted that this specific embodiment is only for better illustration of this application and does not constitute an improper limitation of this application.

[0097] The equalization effect analysis tool provided in this application is based on parameters established by current mainstream standards and is used to analyze the performance of equalization effects. It collects corresponding vibration outputs from a system by inputting a vibration description file, vibration parameters, or vibration drive. By analyzing the vibration data output by the current system, the performance of the equalization effect is determined.

[0098] Figure 5A A logic flowchart of a system equilibrium analysis method provided in this application embodiment is shown below. Figure 5A As shown, it includes the following steps:

[0099] Step S510, parameter configuration.

[0100] Step S520: Generate vibration description data.

[0101] By combining various configurations, vibration description files, vibration parameters, or vibration drive data supported by the system can be generated.

[0102] Step S530, data acquisition.

[0103] The vibration description data described above is manually or automatically input into the system to be analyzed. Then, the system is driven to vibrate, and the actual vibration data of the system is collected and stored. There are various types of collected data, such as vibration acceleration, voltage, and current.

[0104] Step S540, data preprocessing.

[0105] Preprocessing of the collected data can be done manually or automatically. This includes tasks such as data cropping, shifting, and filtering, ultimately yielding the data required for analysis by each module.

[0106] Step S550, frequency analysis.

[0107] Different frequency parameters are constructed, for example, by using the controlled variable method to fix parameters such as intensity and duration, to generate vibration description data for the input system, acquire the collected data, and perform preprocessing calculations on the data.

[0108] Step S560, Intensity Analysis.

[0109] Construct different intensity parameters, such as using the controlled variable method, fixing parameters like frequency and duration. Generate vibration description data for the input system, acquire the collected data, and perform preprocessing calculations on the data.

[0110] Step S570, comprehensive analysis.

[0111] Construct parameters for different frequencies and intensities. Generate input data to describe the vibration of the system, acquire back-collected data, and preprocess and calculate the back-collected data.

[0112] Steps S550 to S570 above perform frequency analysis, intensity analysis, and comprehensive analysis on the preprocessed vibration data, respectively. Finally, the calculation and analysis yield the relationship and manifestation of the input vibration description or vibration parameters or vibration drive and effect balance.

[0113] Figure 5B A system framework for a system equilibrium analysis method provided in the embodiments of this application, such as Figure 5B As shown, the system framework includes a preprocessing module 51, a frequency analysis module 52, an intensity analysis module 53, and a comprehensive analysis module 54. The preprocessing module 51 is divided into a parameter configuration unit 511 for configuring different parameters, a vibration description generation unit 512, a data acquisition unit 513, and a data preprocessing unit 514. The data output from the preprocessing module 51 is input into the other three analysis modules. The frequency analysis module 52 and the intensity analysis module 53 are independent modules and do not depend on other analysis modules. The comprehensive analysis module 54 depends on the results of the frequency analysis module 52 and the intensity analysis module 53. The various analysis units within the larger analysis module are independent of each other and have no dependencies.

[0114] In some implementations, where the configuration parameters include multiple frequency parameters, the frequency analysis module 52 may include a frequency parameter relationship analysis unit 521, which can specifically perform the following operations:

[0115] Preprocessing: Construct different frequency parameters, such as by using the controlled variable method to fix frequency parameters such as intensity and duration, to generate input data, i.e., back-collected data, and perform preprocessing calculations on the data.

[0116] Analysis: By calculating and analyzing the preprocessed data, frequency parameter expressions (equivalent to the first function expression mentioned above) are obtained for different frequency parameters and frequencies. For example, through data fitting, numerical analysis, and other methods, the frequency parameter expression F is calculated. p =f(F p1 ,F p2 ,...), where F p1 Indicates frequency parameter 1, F p2 Indicates frequency parameter 2, F p This represents the expression for the frequency parameter.

[0117] In some implementations, the frequency analysis module 52 may include a frequency mapping analysis unit 522, which specifically performs the following operations:

[0118] Preprocessing: Similar to the method of constructing input data in frequency parameter expression analysis, the sampled data is calculated and analyzed, and the data is preprocessed and calculated.

[0119] Analysis: By calculating and analyzing the preprocessed data, the frequency mapping expression between the frequency parameter and the actual frequency is obtained, such as piecewise frequency mapping and linear frequency mapping. For example, through data fitting, numerical analysis, and other methods, the frequency mapping expression between the frequency parameter and the actual frequency is calculated: F r =f(F p ), where F p F represents the frequency parameter. r This represents the actual frequency function. It should be noted that the frequency mapping analysis unit 522 can directly analyze the frequency parameters and the actual frequency, or it can first obtain the frequency parameter expressions for different frequency parameters through the frequency parameter analysis unit 521, and then process the frequency parameter expressions and the actual frequency to obtain the frequency mapping expression.

[0120] In some implementations, the frequency analysis module 52 may further include a frequency serialization analysis unit 523, which specifically performs the following operations:

[0121] Preprocessing: Construct parameter combinations for different frequency sequences, generate input data, re-sample data, and perform preprocessing calculations on the data.

[0122] Analysis: By calculating and analyzing the preprocessed data, the frequency sequence detection results are obtained. For example, through data fitting, numerical analysis, and other methods, the frequency serialization expression is calculated: F seq= f(F1,F2,t), where F1 represents frequency 1, F2 represents frequency 2, t represents time, F seq It represents the frequency change from F1 to F2 over time.

[0123] In some implementations, where the configuration parameters include multiple strength parameters, the strength analysis module 53 may include a strength parameter relationship analysis unit 531, which can specifically perform the following operations:

[0124] Preprocessing: Construct different intensity parameters, such as by using the controlled variable method, fixing parameters such as frequency and duration. Generate input data, collect back data, and perform preprocessing calculations on the data.

[0125] Analysis: By calculating and analyzing the preprocessed data, different strength parameters and the strength parameter expression between them are obtained (equivalent to the second function expression mentioned above). For example, through data fitting and numerical analysis, the strength parameter function expression is calculated as: I = f(I p1 ,I p2 ,...), where I p1 Indicates strength parameter 1, I p2 Let I represent the strength parameter 2, and let I represent the expression for the strength parameter.

[0126] In some implementations, the intensity analysis module 53 may include an intensity mapping analysis unit 532, which specifically performs the following operations:

[0127] Similar to the method used to construct input data in the strength parameter relationship analysis unit 531, the mapping expression between the strength parameter and the actual strength is obtained by calculating and analyzing the preprocessed data. For example, through data fitting, numerical analysis, and other methods, the strength mapping expression between the strength parameter and the actual strength is calculated: I r =f(I p ), where I p I represents the strength parameter. r This represents the actual strength. It should be noted that the strength mapping analysis unit 532 can directly analyze the strength parameters and the actual strength, or it can first obtain the strength parameter expressions for different strength parameters through the strength parameter analysis unit 531, and then process the strength parameter expressions and the actual strength to obtain the strength mapping expression.

[0128] In some implementations, the intensity analysis module 53 may further include an intensity serialization analysis unit 533, which specifically performs the following operations:

[0129] Preprocessing: Construct parameter combinations for sequences of different intensities, generate input data, re-sample data, and perform preprocessing calculations on the data.

[0130] Analysis: By calculating and analyzing the preprocessed data, the intensity sequence detection results are obtained. For example, through data fitting, numerical analysis, and other methods, the intensity sequence expression is calculated: I seq = f(I1,I2,t), where I1 represents intensity 1, I2 represents intensity 2, t represents time, I seq It represents the function of intensity changing from I1 to I2 over time.

[0131] Finally, the comprehensive analysis module 54 performs the following operations:

[0132] Preprocessing: Construct parameters for different frequencies and intensities. Generate input data, re-acquired data, and perform preprocessing calculations on the data.

[0133] Analysis: By calculating and analyzing the preprocessed data, the final comprehensive effect analysis result is obtained. For example, through data fitting, numerical analysis, and other methods, the comprehensive function expression E = f(F, I, t) is calculated. In some implementations, F is the frequency serialization expression, i.e., Ft. seq = f(F1,F2,t), where I is the intensity serialization expression and t represents time; in some implementations, F is F(F1,F2,F1'-F2'), F1' = max(min(F 上限 ,F1),F 下限 ), F2' = max(min(F 上限 ,F2),F 下限 ), where F 上限 F represents the upper limit of the frequency parameter's value. 下限 Here, I represents the lower limit of the frequency parameter value, t represents the intensity serialization expression, and F1'-F2' represents the bandwidth concept, indicating the bandwidth of the frequency or the bandwidth of the frequency parameter (denoted as δF or δF). P ).

[0134] This application embodiment acquires corresponding vibration output in a system by inputting a vibration description file, vibration parameters, or vibration drive. By analyzing the vibration data output by the current system, the performance of the equalization effect is determined. This application embodiment, through calculation and analysis of different input data and actual vibration effects, obtains an expression between the input vibration description and the final actual equalization effect, thereby providing a systematic, efficient, and complete equalization effect analysis method and tool.

[0135] Based on the foregoing embodiments, this application provides a system equalization analysis device, which includes various modules and sub-modules included in each module. It can be implemented by the control system in the equalization analysis device; of course, it can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), microprocessor unit (MPU), digital signal processor (DSP), or field programmable gate array (FPGA), etc.

[0136] Figure 6 This is a schematic diagram of the composition structure of a system equilibrium analysis device provided in an embodiment of this application. It is applied to an equilibrium analysis equipment, which includes a control panel and a control system for setting configuration parameters. Figure 6 As shown, the device 600 includes: a description generation module 610, a data acquisition module 620, and a balance analysis module 630, wherein:

[0137] The description generation module 610 is used to generate vibration description data based on preset configuration parameters;

[0138] The data acquisition module 620 is used to acquire the vibration data output by the system as back-collected data during the process of driving the system to vibrate using the vibration description data.

[0139] The equilibrium analysis module 630 is used to analyze at least one dimension of the vibration description data and the corresponding back-collected data to obtain a mapping relationship set between the vibration description data and the back-collected data, and to obtain the effect equilibrium analysis result of the system through the mapping relationship set.

[0140] In some possible embodiments, the preset configuration parameters include at least one frequency parameter, the at least one dimension includes a frequency dimension, and the equalization analysis module 630 is specifically used to determine the frequency mapping expression between the at least one frequency parameter and the actual frequency corresponding to the back-collected data; and to analyze the performance equalization of the system using the frequency mapping expression.

[0141] In some possible embodiments, the preset configuration parameters include at least one intensity parameter, the at least one dimension includes an intensity dimension, and the equilibrium analysis module 630 is specifically used to determine the intensity mapping expression between the at least one intensity parameter and the actual intensity corresponding to the back-collected data; and to analyze the effect equilibrium performance of the system using the intensity mapping expression.

[0142] In some possible embodiments, the equalization analysis module 630 is further configured to perform numerical analysis on the actual frequencies corresponding to at least two waveform units in the acquired data, and determine a frequency serialization expression; the frequency serialization expression characterizes the functional expression of the actual frequency corresponding to the waveform unit changing with time; and the frequency serialization expression is used to analyze the effect equalization performance of the system.

[0143] In some possible embodiments, the equalization analysis module 630 is further used to perform numerical analysis on the actual intensity corresponding to each moment in the acquired data to determine the intensity serialization expression; the intensity serialization expression characterizes the functional relationship of the maximum intensity of the waveform unit changing with time; and the effect equalization performance of the system is analyzed using the intensity serialization expression.

[0144] In some possible embodiments, the preset configuration parameters include at least one frequency parameter and at least one intensity parameter, and the at least one dimension includes a frequency dimension and an intensity dimension; the equalization analysis module 630 is specifically used to perform numerical analysis on the at least one frequency parameter and the actual frequency corresponding to each waveform unit in the back-acquired data when the at least one intensity parameter is fixed, to determine a frequency serialization expression; to perform numerical analysis on the at least one intensity parameter and the actual intensity corresponding to each moment in the back-acquired data when the at least one frequency parameter is fixed, to determine an intensity serialization expression; and to analyze the effect equalization performance of the system by combining the frequency serialization expression and the intensity serialization expression.

[0145] In some possible embodiments, the equalization analysis module 630 is further configured to, under a fixed frequency parameter bandwidth or frequency bandwidth, perform numerical analysis on the at least one frequency parameter and the actual frequency corresponding to each waveform unit in the back-acquired data, and on the at least one intensity parameter and the actual intensity corresponding to each moment in the back-acquired data, to determine a comprehensive function expression; wherein, the frequency parameter bandwidth is determined based on the upper and lower limits of the frequency parameter in the at least one frequency parameter; the frequency bandwidth is based on the upper and lower limits of the actual frequencies corresponding to different waveform units in the back-acquired data; and the system's performance equalization is analyzed by combining the frequency serialization expression, the intensity serialization expression, and the comprehensive function expression.

[0146] In some possible embodiments, the apparatus further includes a preprocessing module for performing at least one of the following preprocessing operations on the acquired data: data pruning, shifting, and filtering; correspondingly, the equilibrium analysis module 630 is used to perform at least one dimension of analysis on the preprocessed acquired data to obtain the effect equilibrium analysis result of the system.

[0147] The descriptions of the apparatus embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. In some embodiments, the functions or modules included in the apparatus provided in this disclosure can be used to perform the methods described in the method embodiments above. For technical details not disclosed in the apparatus embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0148] It should be noted that, in the embodiments of this application, if the above-described system equilibrium analysis method is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the related technology, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a equilibrium analysis device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware, software, or firmware, or any combination of hardware, software, and firmware.

[0149] This application provides a balance analysis device, including a control panel for setting configuration parameters and a control system, wherein the control system performs some or all of the steps in the above method.

[0150] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements some or all of the steps in the above-described method. The computer-readable storage medium can be transient or non-transient.

[0151] This application provides a computer program including computer-readable code. When the computer-readable code runs in a leveling analysis device, the control system in the leveling analysis device performs some or all of the steps in the above method.

[0152] This application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the above-described method. This computer program product can be implemented specifically through hardware, software, or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium; in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0153] It should be noted that the descriptions of the various embodiments above tend to emphasize the differences between them, while their similarities or commonalities can be referred to interchangeably. The descriptions of the above embodiments of the device, storage medium, computer program, and computer program product are similar to the descriptions of the above method embodiments and have similar beneficial effects. For technical details not disclosed in the embodiments of the device, storage medium, computer program, and computer program product of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0154] It should be noted that, Figure 7 This is a schematic diagram of a hardware entity of the equalization analysis device in an embodiment of this application, such as... Figure 7 As shown, the hardware entity of the equalization analysis device 700 includes: a control system 701, a communication interface 702, a memory 703, and a control panel 704, wherein:

[0155] The control system 701 can be a processor, which typically controls the overall operation of the equalization analysis device 700.

[0156] The control panel 704 is used to set configuration parameters. These parameters are established by mainstream standards in the relevant field for analyzing the performance of equalization effects, and may include at least one of frequency parameters and intensity parameters describing vibration. Different initial configuration parameters need to be set according to different equipment models or user needs. These initial configuration parameters are usually fixed in the panel firmware before the control panel leaves the factory. The control panel also provides a function to modify parameters, allowing for flexible and efficient changes to the initial configuration parameters through manual setting or system input. In some embodiments, the control panel 704 includes a panel and a display mounted on the panel, which displays the currently set specific configuration parameters and their corresponding values ​​in real time.

[0157] Communication interface 702 enables the equalization analysis device to communicate with other terminals or servers via a network.

[0158] The memory 703 is configured to store instructions and applications executable by the control system 701, and can also cache data to be processed or already processed (e.g., image data, audio data, voice communication data, and video communication data) from various modules in the control system 701 and the equalization analysis device 700. It can be implemented using flash memory or random access memory (RAM). Data transmission between the control system 701, communication interface 702, memory 703, and control panel 704 can be performed via bus 705.

[0159] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above steps / processes do not imply a sequential order of execution; the execution order of each step / process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above embodiments of this application are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0160] 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 apparatus 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 apparatus. 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 apparatus that includes that element.

[0161] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0162] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0163] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0164] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0165] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence or the part that contributes to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a load balancer (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, magnetic disks, or optical disks.

[0166] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A system equilibrium analysis method, characterized in that, The method is applied to a balance analysis device, which includes a control panel for setting configuration parameters and a control system, wherein the control system performs the following steps: Vibration description data is generated based on preset configuration parameters; During the process of driving the system to vibrate using the vibration description data, the vibration data output by the system is collected as back-collected data. The vibration description data and the corresponding back-collected data are analyzed in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension. The effect balance analysis result of the system is obtained through the mapping relationship set. The preset configuration parameters include at least one frequency parameter, and the at least one dimension includes a frequency dimension. The analysis of the vibration description data and the corresponding re-acquired data in at least one dimension yields a mapping relationship set between the vibration description data and the re-acquired data in the at least one dimension. The system's performance balance analysis result is obtained through this mapping relationship set, including: Numerical analysis is performed on the actual frequencies corresponding to at least two waveform units in the acquired data to determine the frequency serialization expression; the frequency serialization expression characterizes the functional relationship between the actual frequency corresponding to the waveform unit and time. The system's performance balance is analyzed using the frequency serialization expression.

2. The method according to claim 1, characterized in that, The step of analyzing the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and obtaining the effect balance analysis result of the system through the mapping relationship set, further includes: The frequency mapping expression between the at least one frequency parameter and the actual frequency corresponding to the retrieval data is determined by data analysis methods. The frequency mapping expression is used to analyze the system's performance balance.

3. The method according to claim 1, characterized in that, The preset configuration parameters include at least one intensity parameter, and the at least one dimension includes an intensity dimension. The analysis of the vibration description data and the corresponding re-acquired data in at least one dimension yields a mapping relationship set between the vibration description data and the re-acquired data in the at least one dimension. The system's effect balance analysis result is obtained through this mapping relationship set, including: The intensity mapping expression between the at least one intensity parameter and the actual intensity corresponding to the recovered data is determined by data analysis methods. The effect balance performance of the system is analyzed using the intensity mapping expression.

4. The method according to claim 3, characterized in that, The step of analyzing the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and obtaining the effect balance analysis result of the system through the mapping relationship set, further includes: Numerical analysis is performed on the actual intensity at each time point in the collected data to determine the intensity serialization expression; the intensity serialization expression characterizes the functional relationship between the actual intensity and time. The system's performance balance is analyzed using the intensity serialization expression.

5. The method according to claim 1, characterized in that, The preset configuration parameters include at least one frequency parameter and at least one intensity parameter, and the at least one dimension includes a frequency dimension and an intensity dimension; the analysis of the vibration description data and the corresponding re-acquired data in at least one dimension yields a mapping relationship set between the vibration description data and the re-acquired data in the at least one dimension, and the system's effect balance analysis result is obtained through the mapping relationship set, including: With the at least one intensity parameter fixed, numerical analysis is performed on the at least one frequency parameter and the actual frequency corresponding to each waveform unit in the acquired data to determine the frequency serialization expression; With at least one frequency parameter fixed, numerical analysis is performed on the at least one intensity parameter and the actual intensity corresponding to each moment in the acquired data to determine the intensity serialization expression; The system's performance balance is analyzed by combining the frequency serialization expression and the intensity serialization expression.

6. The method according to claim 5, characterized in that, The method further includes: With a fixed frequency parameter bandwidth or frequency bandwidth, numerical analysis is performed on the at least one frequency parameter and the actual frequency corresponding to each waveform unit in the acquired data, and on the at least one intensity parameter and the actual intensity corresponding to each moment in the acquired data, to determine a comprehensive function expression; wherein, the frequency parameter bandwidth is determined based on the upper and lower limits of the frequency parameter in the at least one frequency parameter; the frequency bandwidth is determined based on the upper and lower limits of the actual frequencies corresponding to different waveform units in the acquired data; The system's performance balance is analyzed by combining the frequency serialization expression, the intensity serialization expression, and the comprehensive function expression.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: The collected data shall be subjected to at least one of the following preprocessing operations: data pruning, shifting, and filtering; Accordingly, the preprocessed recycled data is analyzed in at least one dimension to obtain the system's performance balance analysis results.

8. A system equilibrium analysis device, characterized in that, An apparatus for use in a balance analysis device, the balance analysis device including a control panel for setting configuration parameters and a control system, the apparatus comprising: The description generation module is used to generate vibration description data based on preset configuration parameters; The data acquisition module is used to acquire the vibration data output by the system as back-collected data during the process of driving the system to vibrate using the vibration description data. The equilibrium analysis module is used to analyze the vibration description data and the corresponding back-collected data in at least one dimension to obtain a mapping relationship set between the vibration description data and the back-collected data in at least one dimension, and to obtain the effect equilibrium analysis result of the system through the mapping relationship set. The preset configuration parameters include at least one frequency parameter, and the at least one dimension includes a frequency dimension. The equalization analysis module is also used to perform numerical analysis on the actual frequencies corresponding to at least two waveform units in the back-collected data to determine the frequency serialization expression. The frequency serialization expression characterizes the functional relationship between the actual frequency corresponding to the waveform unit and time. The frequency serialization expression is used to analyze the effect equalization performance of the system.

9. A balance analysis device, characterized in that, It includes a control panel for setting configuration parameters and a control system, the control system performing the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 7.

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