A method and system for online design optimization based on record player structure

Abstract

The present invention relates to the technical field of online design optimization, and in particular to an online design optimization method and system based on the structure of a record player. The method comprises the following steps: obtaining the structure data of the record player; extracting the structure information of the structure data of the record player to obtain a key structure data set; performing data processing on the key structure data set to obtain a standard structure data set; performing three-dimensional mapping on the standard structure data set to generate structure distribution information; obtaining the technical specification document of the record player; performing semantic analysis on the technical specification document of the record player to obtain the design index data of the record player; performing influence analysis on the design index data of the record player based on the structure distribution information to generate a design parameter influence map. The present invention comprehensively evaluates the influence of the structure data of the record player on the audio performance through the Internet of Things technology, semantic analysis technology, audio analysis and mutual information technology, and improves the accuracy of the evaluation, thereby realizing the online optimization of the structure data of the record player.

Description

Technical Field

[0001] The present invention relates to the technical field of online design optimization, and in particular to an online design optimization method and system based on a record player structure. Background Art

[0002] The sound quality characteristics of a record player not only come from its analog playback nature, but are also closely related to its precise mechanical design. Every detail in the design process, such as the precision machining of the stylus, the dynamic balance of the turntable, and the acoustic characteristics of the speaker, all play a decisive role in the final sound quality performance. The contact and pressure between the stylus and the record directly affect the pickup accuracy of the audio signal; the stability and shock absorption performance of the turntable determine the noise level and sound purity during playback; and the design of the speaker is related to the diffusion, frequency response, and dynamic range of the sound. However, the design process of traditional record players requires a lot of experiments and subjective listening to adjust these structural parameters, which makes it difficult to achieve comprehensive parameter optimization. In addition, due to the lack of precise quantitative methods and data support, it is difficult for designers to evaluate the specific impact of structural parameters on sound quality and provide direct guidance for the optimization of structural parameters. Summary of the invention

[0003] Based on this, it is necessary to provide an online design optimization method and system based on the record player structure to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for online design optimization based on a record player structure is provided, the method comprising the following steps:

[0005] Step S1: acquiring the structure data of the record player; extracting the structure information of the structure data of the record player to obtain a key structure data set; performing data processing on the key structure data set to obtain a standard structure data set; performing three-dimensional mapping on the standard structure data set to generate structure distribution information;

[0006] Step S2: obtaining a record player technical specification document; performing semantic analysis on the record player technical specification document to obtain record player design index data; performing influence analysis on the record player design index data based on structural distribution information to generate a design parameter influence map; performing influence factor extraction on the design parameter influence map to obtain influence factor information;

[0007] Step S3: acquiring the real-time working state data of the record player; extracting the dynamic structure motion data from the real-time working state data of the record player to obtain the dynamic structure motion data; performing sound unit motion structure analysis on the dynamic structure motion data according to the influencing factor information to obtain the dynamic sound unit structure data;

[0008] Step S4: Acquire the audio information of the record player; perform spectrum processing on the audio information of the record player to obtain audio spectrum information; extract the frequency response, spectrum centroid and spectrum smoothness characteristics of the audio spectrum information to obtain audio feature data; perform time-frequency analysis on the audio spectrum information of the record player based on the audio feature data to generate audio time-frequency data; construct an audio performance model based on the audio time-frequency data to obtain an audio performance model;

[0009] Step S5: quantitatively associate the dynamic sound unit structure data with the record player audio information to generate dynamic audio association data; import the dynamic audio association data into the audio performance model to evaluate the sound quality and timbre performance to obtain an audio performance evaluation report; adjust the structure parameters of the record player structure data according to the audio performance evaluation report to generate structure parameter adjustment data;

[0010] Step S6: constructing a visualization platform for online design optimization of the record player structure according to the structural parameter adjustment data to execute the online optimization design operation of the record player structure.

[0011] The present invention obtains the structure data of the record player to ensure a comprehensive understanding of the structure of the record player, provides basic data support for subsequent analysis, enhances the recognition and understanding of the core elements in the record player design by identifying key structural information, performs data processing on the key structural data set, improves the quality and availability of the data, realizes data normalization by converting the key data set into a standard structural data set, converts the two-dimensional data into a three-dimensional view, enhances the intuitive understanding of the spatial relationship of the record player structure, and helps to conduct a more in-depth morphological analysis, and the structural distribution information obtained through three-dimensional mapping reveals the spatial layout and mutual relationship of each component of the record player. By obtaining the technical specification document of the record player, it is ensured that the source of the design indicator data is authoritative and accurate, and the semantic analysis of the technical specification document of the record player is deeply understood to obtain the record player design indicator data, which can accurately capture the design requirements and standards, and the influence analysis of the record player design indicator data based on the structural distribution information can identify the key design parameters that affect the performance of the record player, generate the design parameter influence map, which helps to intuitively understand the complex interaction of the design parameters, and extract the influence factors of the design parameter influence map, which can identify the parameters that should be given priority or adjusted in the design. By acquiring the real-time working status data of the record player, the real-time status data of the record player can be captured. The dynamic structural motion data can be extracted from the real-time working status data of the record player, providing a data basis for further structural analysis. The dynamic structural motion data can be deeply analyzed by using the influencing factor information, focusing on the motion characteristics of the sound unit, so as to more accurately understand the physical mechanism of sound generation and propagation. By acquiring the audio information of the record player, the comprehensive recording of the audio played by the record player is ensured. The audio signal is converted into a spectrum representation, revealing the frequency components of the audio signal, providing a visualization method for understanding the frequency characteristics of the sound. The key features of the extracted audio spectrum provide quantitative parameters for in-depth analysis of audio performance, which is helpful for further time-frequency analysis. The time-frequency analysis of the audio spectrum information can identify the frequency changes of the audio signal in different time periods, and can better understand the dynamic characteristics of the audio. The generated audio time-frequency data helps to capture the instantaneous changes of the audio signal. The audio performance model is constructed based on the audio time-frequency data to obtain the audio performance model, which can quantitatively evaluate the sound quality of the record player and provide an objective sound quality evaluation standard.By quantitatively associating the dynamic sound unit structure data with the record player audio information, the specific connection between the structural features and the sound quality performance can be identified. The generated dynamic audio associated data integrates two types of information, structure and audio, and provides a comprehensive perspective for in-depth analysis. The dynamic audio associated data is evaluated by using the audio performance model, and the overall performance of the sound quality and timbre can be systematically analyzed and understood. The obtained audio performance evaluation report provides a detailed analysis and evaluation of the record player performance. Adjusting the record player structure parameters according to the evaluation report helps to improve the record player performance in a targeted manner and achieve the optimization of the record player structure design. The generated structural parameter adjustment data provides precise guidance for design changes, ensuring the scientificity and effectiveness of the optimization measures. The visualization platform for online design optimization of the record player structure is constructed based on the structural parameter adjustment data, so that the record player structure design work can be carried out remotely and in real time, which improves the accessibility and efficiency of the design, and the effect of the structural parameter adjustment is displayed by visualization means, so that the production team can intuitively understand the impact of the design change. Therefore, the present invention comprehensively evaluates the impact of the record player structure data on the audio performance through the Internet of Things technology, semantic analysis technology, audio analysis and mutual information technology, and improves the accuracy of the evaluation, thereby realizing the online optimization of the record player structure data.

[0012] Preferably, step S1 comprises the following steps:

[0013] Step S11: using a sensor to obtain the structure data of the record player;

[0014] Step S12: extracting morphological features from the record player structure data to obtain a key structure data set;

[0015] Step S13: performing data processing on the key structure data set to obtain a standard structure data set, wherein the data processing includes data decryption, data cleaning, data denoising and data standardization;

[0016] Step S14: Perform three-dimensional mapping on the standard structure data set to obtain structure three-dimensional mapping data; perform projection transformation on the structure three-dimensional mapping data to generate structure distribution information.

[0017] The present invention uses sensor technology to obtain the record player structure data in real time, ensuring the timeliness and accuracy of the data, providing an original and real-time information source for subsequent analysis, extracting morphological features from the record player structure data, helping to identify and define key structural attributes that affect sound quality, and processing the key structural data set to obtain a standard structural data set, thereby improving the quality and reliability of the data and ensuring the validity of the analysis results. The standard structural data set is mapped in three dimensions, converting complex structural information into a visual three-dimensional model, enhancing the spatial information cognition of the record player structure, and obtaining structural distribution information through projection transformation, revealing the spatial layout and mutual relationship of the various components of the record player, and providing an intuitive reference for structural design and optimization.

[0018] Preferably, step S2 comprises the following steps:

[0019] Step S21: obtaining a record player technical specification document; performing semantic analysis on the record player technical specification document to obtain design requirement information and standard parameter information; performing data integration on the design requirement information and the standard parameter information to obtain record player design data;

[0020] Step S22: performing mutual information influence analysis on the record player design index data and structure distribution information to obtain mutual information;

[0021] Step S23: using the record player design index data as network node data, and judging the correlation strength of the network node data by using a preset mutual information threshold, and when the network node data is greater than or equal to the preset mutual information threshold, performing weighted edge connection on the network node data to generate weighted edge data;

[0022] Step S24: constructing an influence map of network node data and weighted edge data using a graph theory analysis method to generate a design parameter influence map;

[0023] Step S25: extracting significant influencing factors from the design parameter influence map to obtain influencing factor information.

[0024] The present invention obtains and analyzes the technical specification documents of record players to ensure the accuracy and authority of design requirements and standard parameter information, provides a reliable source for design data, uses semantic analysis technology to deeply understand the document content, automatically extracts key design requirements and standard parameters, improves the efficiency and accuracy of information extraction, integrates the extracted design requirements and standard parameters to form unified record player design data, lays a solid data foundation for subsequent analysis, performs mutual information analysis on design indicator data and structural distribution information, quantifies the mutual influence and dependency between different design parameters, and uses a preset mutual information threshold to distinguish network node data and screen Parameter pairs with significant correlation strength are selected, which provides a basis for constructing an influence map. Network node data that meets the correlation strength conditions are weightedly connected to generate weighted edge data, which quantitatively represents the degree of mutual influence between design parameters. Graph theory analysis methods are used to process node and weighted edge data to construct a comprehensive design parameter influence map, revealing the complex network relationship between design parameters. The generated design parameter influence map provides an intuitive visualization tool for understanding the role and relationship of each parameter in record player design. Through influence map analysis, the key factors that have a significant impact on the performance of the record player are extracted, providing a focus for design optimization and problem diagnosis.

[0025] Preferably, step S3 comprises the following steps:

[0026] Step S31: using sensors to obtain real-time working status data of the record player;

[0027] Step S32: performing dynamic characteristic measurement on the real-time data of the working state of the record player to obtain dynamic characteristic measurement data, wherein the dynamic characteristic measurement includes measuring the displacement, strain and acceleration motion information of the record player structure;

[0028] Step S33: extracting dynamic structural motion data from the dynamic characteristic measurement data to obtain dynamic structural motion data;

[0029] Step S34: extract the sound unit information of the dynamic structural motion data according to the influencing factor information to obtain the sound unit data; extract the displacement information, acceleration information and frequency response information of the sound unit data to obtain the dynamic sound unit data; perform structural analysis on the dynamic sound unit data to obtain the dynamic sound unit structure data.

[0030] The present invention obtains the working status data of the record player in real time through sensor technology, provides a technical means for capturing the precise status of the device during operation, and measures the dynamic characteristics of the record player structure such as displacement, strain and acceleration, so as to understand in detail the performance of the record player under actual working conditions. It extracts key dynamic structural motion data from the dynamic characteristic measurement data, and provides a basis for further analyzing the structural dynamic response of the record player. Analyzing the dynamic structural motion data based on the influencing factor information is helpful to identify and understand the role of the sound unit in the sound quality performance. It focuses on the displacement, acceleration and frequency response of the sound unit, and provides data support for in-depth analysis of the sound generation and propagation mechanism. The dynamic sound unit structure data is directly related to the sound quality characteristics of the record player, and provides a basis for structural optimization. Structural analysis of the dynamic sound unit data can identify structural design problems that affect the sound quality.

[0031] Preferably, step S4 comprises the following steps:

[0032] Step S41: using an audio collector to obtain a record player audio signal of a record player; converting the record player audio signal into a digital audio file format to generate record player audio information;

[0033] Step S42: performing spectrum conversion on the audio information of the record player to generate a spectrum graph; extracting frequency information and amplitude data in the spectrum graph to obtain audio spectrum information;

[0034] Step S43: extracting audio features from the audio spectrum information to obtain audio feature data, wherein the extracted audio features include frequency response, spectrum centroid and spectrum smoothness;

[0035] Step S44: performing time window segmentation on the audio spectrum information of the record player according to the audio feature data to generate an audio time window; performing time domain analysis on the audio time window to generate audio time-frequency data;

[0036] Step S45: construct an audio performance model based on the audio time-frequency data to obtain an audio performance model.

[0037] The present invention ensures high-quality capture of the audio signal of the record player through an audio collector, provides high-fidelity original data for audio analysis, converts analog audio signals into digital formats, makes audio information easier to store, process and analyze, generates a spectrum diagram through spectrum conversion technology, visually displays the frequency components and energy distribution of the audio signal, extracts key frequency information and amplitude data from the spectrum diagram, provides a quantitative basis for in-depth analysis of the audio, extracts audio features such as frequency response, spectrum centroid and spectrum smoothness, provides key parameters for evaluating sound quality, uses audio feature data to perform time window segmentation on the audio spectrum, provides a structured data view for time-frequency analysis, performs time domain analysis on the audio time window, further explores the characteristic changes of the audio signal in different time periods, generates audio time-frequency data, provides detailed data support for capturing the instantaneous and dynamic characteristics of the audio signal, constructs an audio performance model based on time-frequency data, provides a scientific method for systematically evaluating and understanding the sound quality performance of the record player, and realizes standardized evaluation of the sound quality of the record player through the audio performance model.

[0038] Preferably, step S45 includes the following steps:

[0039] Step S451: extracting the time-frequency response, distortion, signal-to-noise ratio and dynamic range of the audio time-frequency data to obtain audio time-frequency feature data;

[0040] Step S452: Performing sound quality and timbre performance mapping analysis according to the audio time-frequency feature data to generate sound quality and timbre performance mapping data;

[0041] Step S453: constructing an audio performance model according to the sound quality and timbre performance mapping data to obtain an audio performance pre-model; and training the audio performance pre-model using the sound quality and timbre performance mapping data to obtain an audio performance training model;

[0042] Step S454: perform model cross-validation evaluation on the audio performance training model to obtain audio performance model evaluation data; adjust model parameters of the audio performance training model using the audio performance model evaluation data to obtain an audio performance model.

[0043] The present invention provides comprehensive time-frequency feature data for audio analysis by extracting key parameters such as time-frequency frequency response, distortion, signal-to-noise ratio and dynamic range from time-frequency data, and uses audio time-frequency feature data to perform sound quality and timbre performance mapping analysis, so as to convert abstract audio data into quantifiable performance indicators. The generated sound quality and timbre performance mapping data provides detailed data support for the evaluation of audio performance, and constructs an audio performance pre-model based on the sound quality and timbre performance mapping data, laying a foundation for subsequent model training and evaluation. The pre-model is trained by using the mapping data to optimize the model parameters and improve the accuracy of the model in audio performance evaluation. The frequency performance training model is cross-validated and evaluated to ensure the stability and generalization ability of the audio performance model and improve the reliability of the model. The model parameters are adjusted according to the audio performance model evaluation data to further improve the applicability of the audio performance model. Through a continuous evaluation and adjustment process, an optimized audio performance model is finally obtained, which can accurately evaluate the sound quality performance.

[0044] Preferably, step S5 comprises the following steps:

[0045] Step S51: performing time sequence feature matching on the dynamic sound unit structure data and the record player audio information to generate time sequence matching feature data;

[0046] Step S52: aligning the dynamic sound unit structure data and the record player audio information based on the time sequence matching feature data to generate a time sequence matching matrix; performing correlation analysis on the time sequence matching matrix to generate dynamic audio correlation data;

[0047] Step S53: converting the dynamic audio associated data into a standard input format to generate dynamic audio input data; importing the dynamic audio input data into an audio performance model to perform sound quality and timbre performance evaluation to generate a sound quality and timbre performance index; performing a sound quality and timbre scoring analysis on the sound quality and timbre performance index to obtain an audio performance evaluation report;

[0048] Step S54: Perform sensitivity analysis on the audio performance evaluation report to obtain sensitivity analysis data; adjust the structure parameters of the record player structure data according to the sensitivity analysis data to generate structure parameter adjustment data.

[0049] The present invention performs timing feature matching on the dynamic sound unit structure data and the record player audio information, thereby ensuring the consistency of the dynamic sound unit structure data and the record player audio information in the time series, and providing a basis for accurately analyzing the correlation between the two. The dynamic sound unit structure data and the record player audio information are aligned by timing matching feature data, so that the dynamic sound unit structure data and the record player audio information are synchronized on the time axis, which is convenient for analyzing the dynamic response of the structure in the audio generation process. Through the correlation analysis of the timing matching matrix, the correlation between the dynamic sound unit structure data and the record player audio information can be identified, and dynamic audio correlation data can be generated to facilitate further analysis. The method provides a basis for the one-step performance evaluation, converts the dynamic audio-related data into a standard input format, ensures that the data can adapt to the input requirements of the audio performance model, improves the standardization of data processing, uses the audio performance model to evaluate the dynamic audio input data, generates sound quality and timbre performance indicators, provides a quantitative description of the sound quality performance of the record player, conducts in-depth analysis of the sound quality and timbre performance indicators, obtains an audio performance evaluation report, and provides objective data support for the evaluation of audio performance. The audio performance evaluation report is subjected to sensitivity analysis to identify the key structural parameters that affect the sound quality, and obtains sensitivity analysis data, which helps to understand the impact of key structural parameters on the sound quality.

[0050] The record player structure data is adjusted according to the sensitivity analysis data to generate structure parameter adjustment data, which provides parameter adjustment data support for the record player structure design optimization.

[0051] Preferably, step S53 includes the following steps:

[0052] Step S531: converting the dynamic audio associated data into a standard input format to generate dynamic audio input data, wherein the standard input format conversion includes format unification, sampling rate synchronization and bit depth standardization;

[0053] Step S532: importing the dynamic audio input data into the audio performance evaluation model to calculate the sound quality and timbre parameters, and generating the sound quality and timbre performance index;

[0054] Step S533: extracting sound quality and timbre feature data according to the sound quality and timbre performance index to obtain sound quality and timbre feature data; weighting the sound quality and timbre feature data according to the preset audio performance contribution weight to generate weighted feature data; accumulating and averaging the feature values ​​of the weighted feature data to generate a quantitative score of audio performance;

[0055] Step S534: The audio performance quantification score is graded to obtain an audio performance evaluation report.

[0056] The present invention converts the dynamic audio-related data into a standard input format, thereby ensuring the consistency and compatibility of the dynamic audio-related data and facilitating subsequent processing and analysis. The unified sampling rate ensures the consistency of the audio data in terms of time resolution and avoids the analysis error caused by sampling rate mismatch. Bit depth standardization ensures the quantization accuracy of the audio data and improves the accuracy of the audio signal representation. The dynamic audio input data is imported into the audio performance evaluation model, and the computing power of the audio performance evaluation model is used to comprehensively calculate the sound quality and timbre parameters. The generated sound quality and timbre performance indicators provide key quantitative data for evaluating the audio performance of the record player. Sound quality and timbre feature data are extracted based on the sound quality and timbre performance indicators to obtain sound quality and timbre feature data, which further refines the sound quality and timbre of the audio performance and provides a basis for subsequent in-depth analysis. The analysis provides a data basis, and weighted processing is performed on the sound quality and timbre feature data according to the preset audio performance contribution weight to obtain weighted feature data, which reflects the importance of different sound quality and timbre features in the overall audio performance. The audio performance quantitative score is generated by accumulating and averaging the characteristic values ​​of the weighted feature data, which provides a comprehensive evaluation for the audio performance. The audio performance quantitative score is divided into scoring levels, and the audio performance quantitative score is converted into a level with practical significance, which is easy for the production team to understand and use. The generated audio performance evaluation report provides a comprehensive audio performance analysis result that can reflect the audio performance.

[0057] Preferably, step S54 includes the following steps:

[0058] Step S541: performing sensitivity analysis on the record player structure data based on the audio performance evaluation report to obtain sensitivity analysis data;

[0059] Step S542: performing a multiple linear regression analysis based on the sensitivity analysis data to generate multiple linear regression coefficients; performing an impact weight analysis on the record player structure data according to the multiple linear regression coefficients to obtain impact weight data;

[0060] Step S543: Performing statistical significance analysis on the impact weight data to obtain significant impact weight data; sorting the record player structure data in descending order according to the significant impact weight data to obtain influential structure parameters;

[0061] Step S544: numerically identifying the influential structural parameters to obtain the most influential structural parameters;

[0062] Step S545: Adjust the record player structure data according to the most influential structural parameter to obtain structural parameter adjustment data.

[0063] The present invention identifies the record player structural parameters that have the most significant impact on sound quality and timbre through sensitivity analysis data, applies multivariate linear regression analysis to quantify the specific impact of the record player structural data on audio performance, generates regression coefficients to reveal the linear relationship between the record player structural data and the audio performance, uses the multivariate linear regression coefficients to perform influence weight analysis on the record player structural data, and can evaluate the contribution of each record player structural data to the overall audio performance, performs statistical significance analysis on the influence weight data to obtain significant influence weight data, and can screen out weight data that has a significant impact on audio performance to ensure that the optimization measures are targeted at truly important factors, sorts the significant influence weight data in descending order to obtain influential structural parameters, clarifies the priority of the impact of each record player structural data on audio performance, performs numerical identification on the influential structural parameters, and identifies the structural parameter with the greatest impact, which is the object that should be focused on and adjusted in the record player design optimization, performs corresponding structural adjustments on the record player structural data according to the structural parameter with the greatest impact to improve the sound quality and timbre performance, and the generated structural parameter adjustment data provides data support for formulating a specific record player optimization plan, thereby improving the efficiency of record player optimization design.

[0064] In this specification, a system for online design and optimization of a record player structure is provided, which is used to execute the above-mentioned method for online design and optimization of a record player structure. The system for online design and optimization of a record player structure comprises:

[0065] The structure distribution information module is used to obtain the structure data of the record player; extract the structure information of the structure data of the record player to obtain the key structure data set; perform data processing on the key structure data set to obtain the standard structure data set; perform three-dimensional mapping on the standard structure data set to generate structure distribution information;

[0066] The impact factor module is used to obtain the technical specification document of the record player; perform semantic analysis on the technical specification document of the record player to obtain the design index data of the record player; perform influence analysis on the design index data of the record player based on the structural distribution information to generate a design parameter influence map; perform influence factor extraction on the design parameter influence map to obtain influence factor information;

[0067] The dynamic sound unit structure module is used to obtain the real-time working state data of the record player; extract the dynamic structure motion data from the real-time working state data of the record player to obtain the dynamic structure motion data; perform sound unit motion structure analysis on the dynamic structure motion data according to the influencing factor information to obtain the dynamic sound unit structure data;

[0068] The audio performance model module is used to obtain the audio information of the record player; perform spectrum processing on the audio information of the record player to obtain the audio spectrum information; extract the frequency response, spectrum centroid and spectrum smoothness characteristics of the audio spectrum information to obtain audio feature data; perform time-frequency analysis on the audio spectrum information of the record player based on the audio feature data to generate audio time-frequency data; construct an audio performance model based on the audio time-frequency data to obtain an audio performance model;

[0069] The record player structure adjustment module is used to quantitatively associate the dynamic sound unit structure data with the record player audio information to generate dynamic audio association data; import the dynamic audio association data into the audio performance model to evaluate the sound quality and timbre performance to obtain an audio performance evaluation report; adjust the structure parameters of the record player structure data according to the audio performance evaluation report to generate structure parameter adjustment data;

[0070] The visualization module is used to build a visualization platform for online design optimization of the record player structure according to the structural parameter adjustment data, so as to perform the online optimization design operation of the record player structure.

[0071] The present invention constructs an online design optimization system based on the structure of a record player. The structural distribution information module obtains the structural data of the record player to ensure a comprehensive understanding of the structure of the record player, provides basic data support for subsequent analysis, and enhances the recognition and understanding of core elements in the design of the record player by identifying key structural information. The key structural data set is processed to improve the quality and availability of the data. The key data set is converted into a standard structural data set to achieve data normalization. The two-dimensional data is converted into a three-dimensional view to enhance the intuitive understanding of the spatial relationship of the record player structure, which is helpful for a more in-depth morphological analysis. The structural distribution information obtained through three-dimensional mapping reveals the spatial layout and mutual relationship of the various components of the record player. The impact factor module obtains the technical specification documents of the record player to ensure that the source of the design indicator data is authoritative and accurate. It conducts a semantic analysis of the technical specification documents of the record player to obtain the design indicator data of the record player, which can accurately capture the design requirements and standards. It conducts an impact analysis on the design indicator data of the record player based on the structural distribution information, which can identify the key design parameters that affect the performance of the record player, and generates a design parameter impact map, which helps to intuitively understand the complex interaction of the design parameters. The impact factor is extracted from the design parameter impact map, which can identify the parameters that should be given priority or adjusted in the design. The dynamic sound unit structure module can capture the real-time status data of the record player in operation by obtaining the real-time working status data of the record player. It extracts dynamic structural motion data from the real-time working status data of the record player, which provides a data basis for further structural analysis. It uses the impact factor information to conduct an in-depth analysis of the dynamic structural motion data, which can focus on the motion characteristics of the sound unit, so as to more accurately understand the physical mechanism of sound generation and propagation. The audio performance model module obtains the audio information of the record player to ensure the comprehensive recording of the audio played by the record player, converts the audio signal into a spectrum representation, reveals the frequency components of the audio signal, and provides a visual means for understanding the frequency characteristics of the sound. The key features of the extracted audio spectrum provide quantitative parameters for in-depth analysis of audio performance, which is helpful for further time-frequency analysis. Time-frequency analysis of the audio spectrum information can identify the frequency changes of the audio signal in different time periods and enable a better understanding of the dynamic characteristics of the audio. The generated audio time-frequency data helps to capture the instantaneous changes of the audio signal. The audio performance model is constructed based on the audio time-frequency data to obtain an audio performance model that can quantitatively evaluate the sound quality of the record player and provide an objective sound quality evaluation standard.The record player structure adjustment module can identify the specific connection between structural features and sound quality performance by quantitatively correlating the dynamic sound unit structure data with the record player audio information. The generated dynamic audio correlation data integrates two types of information, structure and audio, and provides a comprehensive perspective for in-depth analysis. The dynamic audio correlation data is evaluated by using the audio performance model, which can systematically analyze and understand the overall performance of sound quality and timbre. The obtained audio performance evaluation report provides a detailed analysis and evaluation of the record player performance. Adjusting the record player structure parameters according to the evaluation report helps to improve the record player performance in a targeted manner and achieve the optimization of the record player structure design. The generated structural parameter adjustment data provides precise guidance for design changes, ensuring the scientificity and effectiveness of the optimization measures. The visualization module constructs a visualization platform for the online design optimization of the record player structure based on the structural parameter adjustment data, so that the record player structure design work can be carried out remotely and in real time, improving the accessibility and efficiency of the design, and showing the effect of the structural parameter adjustment through visualization means, so that the production team can intuitively understand the impact of the design change. Therefore, the present invention comprehensively evaluates the impact of record player structural data on audio performance through Internet of Things technology, semantic analysis technology, audio analysis and mutual information technology, and improves the accuracy of the evaluation, thereby realizing online optimization of record player structural data. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A schematic flow chart of the steps of the online design optimization method based on the record player structure;

[0073] Figure 2 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0074] Figure 3 for Figure 2 Detailed implementation steps of step S45 are shown in the flowchart;

[0075] Figure 4 for Figure 1 Detailed implementation steps of step S5;

[0076] Figure 5 for Figure 4 Detailed implementation steps of step S54;

[0077] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0078] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0079] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0080] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0081] To achieve this, please refer to Figures 1 to 5 , a method for online design optimization based on a record player structure, the method comprising the following steps:

[0082] Step S1: acquiring the structure data of the record player; extracting the structure information of the structure data of the record player to obtain a key structure data set; performing data processing on the key structure data set to obtain a standard structure data set; performing three-dimensional mapping on the standard structure data set to generate structure distribution information;

[0083] Step S2: obtaining a record player technical specification document; performing semantic analysis on the record player technical specification document to obtain record player design index data; performing influence analysis on the record player design index data based on structural distribution information to generate a design parameter influence map; performing influence factor extraction on the design parameter influence map to obtain influence factor information;

[0084] Step S3: acquiring the real-time working state data of the record player; extracting the dynamic structure motion data from the real-time working state data of the record player to obtain the dynamic structure motion data; performing sound unit motion structure analysis on the dynamic structure motion data according to the influencing factor information to obtain the dynamic sound unit structure data;

[0085] Step S4: Acquire the audio information of the record player; perform spectrum processing on the audio information of the record player to obtain audio spectrum information; extract the frequency response, spectrum centroid and spectrum smoothness characteristics of the audio spectrum information to obtain audio feature data; perform time-frequency analysis on the audio spectrum information of the record player based on the audio feature data to generate audio time-frequency data; construct an audio performance model based on the audio time-frequency data to obtain an audio performance model;

[0086] Step S5: quantitatively associate the dynamic sound unit structure data with the record player audio information to generate dynamic audio association data; import the dynamic audio association data into the audio performance model to evaluate the sound quality and timbre performance to obtain an audio performance evaluation report; adjust the structure parameters of the record player structure data according to the audio performance evaluation report to generate structure parameter adjustment data;

[0087] Step S6: constructing a visualization platform for online design optimization of the record player structure according to the structural parameter adjustment data to execute the online optimization design operation of the record player structure.

[0088] The present invention obtains the structure data of the record player to ensure a comprehensive understanding of the structure of the record player, provides basic data support for subsequent analysis, enhances the recognition and understanding of the core elements in the record player design by identifying key structural information, performs data processing on the key structural data set, improves the quality and availability of the data, realizes data normalization by converting the key data set into a standard structural data set, converts the two-dimensional data into a three-dimensional view, enhances the intuitive understanding of the spatial relationship of the record player structure, and helps to conduct a more in-depth morphological analysis, and the structural distribution information obtained through three-dimensional mapping reveals the spatial layout and mutual relationship of each component of the record player. By obtaining the technical specification document of the record player, it is ensured that the source of the design indicator data is authoritative and accurate, and the semantic analysis of the technical specification document of the record player is deeply understood to obtain the record player design indicator data, which can accurately capture the design requirements and standards, and the influence analysis of the record player design indicator data based on the structural distribution information can identify the key design parameters that affect the performance of the record player, generate the design parameter influence map, which helps to intuitively understand the complex interaction of the design parameters, and extract the influence factors of the design parameter influence map, which can identify the parameters that should be given priority or adjusted in the design. By acquiring the real-time working status data of the record player, the real-time status data of the record player can be captured. The dynamic structural motion data can be extracted from the real-time working status data of the record player, providing a data basis for further structural analysis. The dynamic structural motion data can be deeply analyzed by using the influencing factor information, focusing on the motion characteristics of the sound unit, so as to more accurately understand the physical mechanism of sound generation and propagation. By acquiring the audio information of the record player, the comprehensive recording of the audio played by the record player is ensured. The audio signal is converted into a spectrum representation, revealing the frequency components of the audio signal, providing a visualization method for understanding the frequency characteristics of the sound. The key features of the extracted audio spectrum provide quantitative parameters for in-depth analysis of audio performance, which is helpful for further time-frequency analysis. The time-frequency analysis of the audio spectrum information can identify the frequency changes of the audio signal in different time periods, and can better understand the dynamic characteristics of the audio. The generated audio time-frequency data helps to capture the instantaneous changes of the audio signal. The audio performance model is constructed based on the audio time-frequency data to obtain the audio performance model, which can quantitatively evaluate the sound quality of the record player and provide an objective sound quality evaluation standard.By quantitatively associating the dynamic sound unit structure data with the record player audio information, the specific connection between the structural features and the sound quality performance can be identified. The generated dynamic audio associated data integrates two types of information, structure and audio, and provides a comprehensive perspective for in-depth analysis. The dynamic audio associated data is evaluated by using the audio performance model, and the overall performance of the sound quality and timbre can be systematically analyzed and understood. The obtained audio performance evaluation report provides a detailed analysis and evaluation of the record player performance. Adjusting the record player structure parameters according to the evaluation report helps to improve the record player performance in a targeted manner and achieve the optimization of the record player structure design. The generated structural parameter adjustment data provides precise guidance for design changes, ensuring the scientificity and effectiveness of the optimization measures. The visualization platform for online design optimization of the record player structure is constructed based on the structural parameter adjustment data, so that the record player structure design work can be carried out remotely and in real time, which improves the accessibility and efficiency of the design, and the effect of the structural parameter adjustment is displayed by visualization means, so that the production team can intuitively understand the impact of the design change. Therefore, the present invention comprehensively evaluates the impact of the record player structure data on the audio performance through the Internet of Things technology, semantic analysis technology, audio analysis and mutual information technology, and improves the accuracy of the evaluation, thereby realizing the online optimization of the record player structure data.

[0089] In the embodiment of the present invention, reference Figure 1 The above is a schematic flow chart of the steps of the on-line design optimization method for the record player structure of the present invention. In this example, the on-line design optimization method for the record player structure includes the following steps:

[0090] Step S1: acquiring the structure data of the record player; extracting the structure information of the structure data of the record player to obtain a key structure data set; performing data processing on the key structure data set to obtain a standard structure data set; performing three-dimensional mapping on the standard structure data set to generate structure distribution information;

[0091] In an embodiment of the present invention, structural data of a record player, including size, shape and material properties, are collected by high-precision measuring equipment and sensors, key structural features of the record player structural data are extracted by data analysis software to obtain a key structural data set, and data processing is performed on the key structural data set to obtain a standard structural data set, the data processing includes data cleaning to remove outliers, data denoising to reduce noise interference and data standardization to unify the data format, computer-aided design (CAD) software or three-dimensional modeling tools are used to perform three-dimensional spatial mapping of the standard structural data set to generate a three-dimensional mapping result, and graphics processing is performed on the three-dimensional mapping result to generate structural distribution information, and the structural distribution information includes the spatial positions and relationships of components.

[0092] Step S2: obtaining a record player technical specification document; performing semantic analysis on the record player technical specification document to obtain record player design index data; performing influence analysis on the record player design index data based on structural distribution information to generate a design parameter influence map; performing influence factor extraction on the design parameter influence map to obtain influence factor information;

[0093] In an embodiment of the present invention, by collecting technical specification documents of record players, which include design manuals, operating instructions and maintenance guides, natural language processing (NLP) technology is used to analyze the technical specification documents of record players to identify design requirements and standard parameters in the documents, and design indicator data is extracted from the results of semantic analysis to obtain the design indicator data of the record player. Based on the structural distribution information, a statistical analysis method or a machine learning algorithm is used to perform an impact analysis on the design indicator data to determine the potential impact of each design indicator on the performance of the record player. The results of the impact analysis are presented in a graphical manner to generate a design parameter impact map. According to the design parameter impact map, graph theory technology is used to identify and extract key factors that have a significant impact on the performance of the record player to obtain impact factor information.

[0094] Step S3: acquiring the real-time working state data of the record player; extracting the dynamic structure motion data from the real-time working state data of the record player to obtain the dynamic structure motion data; performing sound unit motion structure analysis on the dynamic structure motion data according to the influencing factor information to obtain the dynamic sound unit structure data;

[0095] In an embodiment of the present invention, sensors are deployed to monitor the working status of the record player in real time, collect data generated during the operation of the record player, use signal processing technology to identify the real-time collected data, extract key parameters reflecting the dynamic behavior of the record player structure, such as displacement, velocity and acceleration, use structural dynamics analysis methods to conduct in-depth analysis of the dynamic structural motion data, identify the mechanical motion characteristics of the sound unit, and obtain dynamic sound unit structural data, which describes the structural behavior of the sound unit in the working state.

[0096] Step S4: Acquire the audio information of the record player; perform spectrum processing on the audio information of the record player to obtain audio spectrum information; extract the frequency response, spectrum centroid and spectrum smoothness characteristics of the audio spectrum information to obtain audio feature data; perform time-frequency analysis on the audio spectrum information of the record player based on the audio feature data to generate audio time-frequency data; construct an audio performance model based on the audio time-frequency data to obtain an audio performance model;

[0097] In an embodiment of the present invention, an audio signal played by a record player is acquired through an audio acquisition instrument to ensure that the acquisition quality of the signal meets the analysis requirements, a fast Fourier transform (FFT) is performed on the acquired audio signal to convert the time domain signal into a frequency domain signal to obtain audio spectrum information, and audio features of the audio spectrum information are extracted to obtain audio feature data. The audio feature data includes parameters such as frequency response, spectrum centroid, and spectrum smoothness. The audio spectrum information is further analyzed in time and frequency through short-time Fourier transform (STFT) time-frequency analysis technology to generate audio time-frequency data. The audio time-frequency data can reflect the time-frequency data of the frequency characteristics of the audio signal in different time periods. Statistical analysis technology is used to construct an audio performance model based on the time-frequency data. The audio performance model can quantitatively analyze the performance of the audio signal.

[0098] Step S5: quantitatively associate the dynamic sound unit structure data with the record player audio information to generate dynamic audio association data; import the dynamic audio association data into the audio performance model to evaluate the sound quality and timbre performance to obtain an audio performance evaluation report; adjust the structure parameters of the record player structure data according to the audio performance evaluation report to generate structure parameter adjustment data;

[0099] In an embodiment of the present invention, by performing multivariate data analysis, the structural data of the dynamic sound-emitting unit is matched and synchronized with the audio information of the record player to establish a quantitative relationship between the two, generate dynamic audio associated data, use the dynamic audio associated data as input data of the audio performance model, use the audio performance model to process and analyze the dynamic audio associated data input data, calculate various performance indicators of sound quality and timbre, and generate an audio performance evaluation report based on the analysis results of the audio performance model. The audio performance evaluation report includes quantitative evaluation data of sound quality and timbre. Based on the performance indicators and potential improvement directions indicated in the audio performance evaluation report, the record player structural data is deeply analyzed to generate structural parameter adjustment data.

[0100] Step S6: constructing a visualization platform for online design optimization of the record player structure according to the structural parameter adjustment data to execute the online optimization design operation of the record player structure.

[0101] In an embodiment of the present invention, structural parameter adjustment data is integrated into an online design optimization platform, an online visualization platform is developed, and an intuitive user interface is designed to allow users to easily input, modify and update structural parameters. The platform is capable of processing and displaying online design optimization of the record player structure, and interactive functions are implemented on the platform, allowing the production team to interact in real time and perform parameter adjustment and optimization.

[0102] Preferably, step S1 comprises the following steps:

[0103] Step S11: using a sensor to obtain the structure data of the record player;

[0104] Step S12: extracting morphological features from the record player structure data to obtain a key structure data set;

[0105] Step S13: performing data processing on the key structure data set to obtain a standard structure data set, wherein the data processing includes data decryption, data cleaning, data denoising and data standardization;

[0106] Step S14: Perform three-dimensional mapping on the standard structure data set to obtain structure three-dimensional mapping data; perform projection transformation on the structure three-dimensional mapping data to generate structure distribution information.

[0107] In an embodiment of the present invention, sensors are deployed to monitor the structure of a record player in real time, record player structural data are collected, morphological features of the record player structural data are extracted using a feature extraction algorithm, a key structural data set is generated, data processing is performed on the key structural data set, errors and incomplete records in the data set are removed, signal filter processing technology is applied to remove noise components in the data, the data is converted into a unified format to obtain a standard structural data set, computer-aided design (CAD) software is used to convert the standardized structural data into a three-dimensional model to obtain structural three-dimensional mapping data, geometric transformations such as projection and perspective conversion are performed on the structural three-dimensional mapping data to generate information describing the structural distribution.

[0108] Preferably, step S2 comprises the following steps:

[0109] Step S21: obtaining a record player technical specification document; performing semantic analysis on the record player technical specification document to obtain design requirement information and standard parameter information; performing data integration on the design requirement information and the standard parameter information to obtain record player design data;

[0110] Step S22: performing mutual information influence analysis on the record player design index data and structure distribution information to obtain mutual information;

[0111] Step S23: using the record player design index data as network node data, and judging the correlation strength of the network node data by using a preset mutual information threshold, and when the network node data is greater than or equal to the preset mutual information threshold, performing weighted edge connection on the network node data to generate weighted edge data;

[0112] Step S24: constructing an influence map of network node data and weighted edge data using a graph theory analysis method to generate a design parameter influence map;

[0113] Step S25: extracting significant influencing factors from the design parameter influence map to obtain influencing factor information.

[0114] In an embodiment of the present invention, technical specification documents of a record player are collected, and natural language processing technology is used to perform semantic analysis on the documents to obtain design requirement information and standard parameter information, and data integration is performed on the design requirement information and standard parameter information to obtain record player design data, and statistical analysis is performed on the design indicator data and structural distribution information, and the mutual information is calculated to quantify the mutual dependence between the two. A threshold value of the mutual information is set, and the correlation strength of the network node data is judged. When the network node data is greater than or equal to the preset threshold value of the mutual information, the network node data is weightedly connected to generate weighted edge data. A graph theory analysis method is used to combine the network node and weighted edge data to further construct a design parameter influence map, and key factors are identified and extracted according to the design parameter influence map to obtain the influence factor information. The influence factor information has a significant impact on the design of the record player.

[0115] Preferably, step S3 comprises the following steps:

[0116] Step S31: using sensors to obtain real-time working status data of the record player;

[0117] Step S32: performing dynamic characteristic measurement on the real-time data of the working state of the record player to obtain dynamic characteristic measurement data, wherein the dynamic characteristic measurement includes measuring the displacement, strain and acceleration motion information of the record player structure;

[0118] Step S33: extracting dynamic structural motion data from the dynamic characteristic measurement data to obtain dynamic structural motion data;

[0119] Step S34: extract the sound unit information of the dynamic structural motion data according to the influencing factor information to obtain the sound unit data; extract the displacement information, acceleration information and frequency response information of the sound unit data to obtain the dynamic sound unit data; perform structural analysis on the dynamic sound unit data to obtain the dynamic sound unit structure data.

[0120] In an embodiment of the present invention, a high-precision sensor array is used to capture in real time the physical state data of the record player in operation, wherein the physical state data includes the position, speed and vibration of mechanical parts; a detailed dynamic characteristic measurement is performed on the real-time working state data of the record player to obtain dynamic characteristic measurement data, wherein the dynamic characteristic measurement data includes accurate monitoring of multiple dimensions of displacement, strain and acceleration of the record player structure; characteristic data describing the dynamic structural motion of the record player is extracted based on the dynamic characteristic measurement data to obtain dynamic structural motion data; the dynamic structural motion data is deeply analyzed based on the influencing factor information to identify the dynamic response characteristics of the sound unit; the analysis is further refined to extract the displacement information, acceleration information and frequency response information of the sound unit data to obtain dynamic sound unit data; a comprehensive structural analysis is performed on the sound unit data to evaluate its contribution to the sound quality and timbre; the extracted and analyzed sound unit data are integrated to obtain dynamic sound unit structure data.

[0121] As an example of the present invention, refer to Figure 2 As shown, in this example, step S4 includes:

[0122] Step S41: using an audio collector to obtain a record player audio signal of a record player; converting the record player audio signal into a digital audio file format to generate record player audio information;

[0123] Step S42: performing spectrum conversion on the audio information of the record player to generate a spectrum graph; extracting frequency information and amplitude data in the spectrum graph to obtain audio spectrum information;

[0124] Step S43: extracting audio features from the audio spectrum information to obtain audio feature data, wherein the extracted audio features include frequency response, spectrum centroid and spectrum smoothness;

[0125] Step S44: performing time window segmentation on the audio spectrum information of the record player according to the audio feature data to generate an audio time window; performing time domain analysis on the audio time window to generate audio time-frequency data;

[0126] Step S45: construct an audio performance model based on the audio time-frequency data to obtain an audio performance model.

[0127] In an embodiment of the present invention, an audio signal played by a record player is captured in real time by an audio collector, and the audio signal is subsequently converted into a digital format to ensure that the signal is recorded as a digital audio file in a high-fidelity manner. The record player audio information is spectrally converted, and a time domain signal is converted into a frequency domain signal by using a fast Fourier transform (FFT), and a spectrogram is generated. According to the spectrogram, key frequency information and amplitude data are identified and extracted to obtain audio spectrum information, and audio features in the audio spectrum information are extracted to obtain audio feature data. The audio feature data includes frequency response, spectrum centroid and spectrum smoothness, which provide key parameter support for in-depth analysis of audio. The audio feature data is used to divide the record player audio spectrum information into time windows by using a window partitioning technology, and decomposed into multiple short time segments, each segment corresponding to an audio time window, and each audio time window is analyzed in the time domain to obtain the dynamic characteristics of the audio signal in different time periods, thereby generating audio time-frequency data, and an audio performance model is constructed based on the audio time-frequency data. The audio performance model uses advanced signal processing technology and machine learning algorithms to evaluate the audio signal, including sound quality and timbre, to obtain an audio performance model.

[0128] As an example of the present invention, refer to Figure 3 As shown, in this example, step S45 includes:

[0129] Step S451: extracting the time-frequency response, distortion, signal-to-noise ratio and dynamic range of the audio time-frequency data to obtain audio time-frequency feature data;

[0130] Step S452: Performing sound quality and timbre performance mapping analysis according to the audio time-frequency feature data to generate sound quality and timbre performance mapping data;

[0131] Step S453: constructing an audio performance model according to the sound quality and timbre performance mapping data to obtain an audio performance pre-model; and training the audio performance pre-model using the sound quality and timbre performance mapping data to obtain an audio performance training model;

[0132] Step S454: perform model cross-validation evaluation on the audio performance training model to obtain audio performance model evaluation data; adjust model parameters of the audio performance training model using the audio performance model evaluation data to obtain an audio performance model.

[0133] In an embodiment of the present invention, the audio time-frequency data is analyzed in detail, and key audio characteristics are extracted therefrom to obtain audio time-frequency feature data, wherein the audio time-frequency feature data includes time-frequency frequency response, distortion, signal-to-noise ratio and dynamic range. Sound quality and timbre performance mapping analysis is performed through the audio time-frequency feature data to generate sound quality and timbre performance mapping data. A preliminary audio performance pre-model is constructed using the sound quality and timbre performance mapping data. In the process of constructing the audio performance pre-model, the model structure is first defined, and a network structure including 5 hidden layers is determined, each layer including 64 nodes. The activation function uses the ReLU function because of its high efficiency in dealing with nonlinear problems. According to the sound quality and timbre performance mapping data, the data set is divided into a training set and a validation set, usually divided in a ratio of 8:2. In the model training stage, the pre-model is trained using the training set data. During the training process, the prediction value is calculated by forward propagation, and the model parameters are adjusted by back propagation. The number of training iterations (epochs) is set to 1000, the batch size is set to 32, the learning rate is initially set to 0.001, and the learning rate decay strategy is adopted, that is, the learning rate decreases by 10% every 100 epochs. In addition, an optimization algorithm with a momentum of 0.9 will be introduced to accelerate convergence and improve model stability. In the model evaluation stage, a k-fold cross-validation evaluation is performed, and a 5-fold cross-validation is selected. The data set is divided into 5 subsets, and one of the subsets is used as the test set in turn, and the rest are used as the training set. Repeat 5 times to obtain a more robust performance evaluation. Analyze the results of cross-validation, including the bias, variance, and generalization ability of the evaluation model, and obtain the audio performance model evaluation data. According to the audio performance model evaluation data, adjust the model parameters of the audio performance training model. If the model is overfitting, the measures taken include adding an L2 regularization term, setting the regularization coefficient to 0.001, and reducing the number of layers and nodes of the model; if the model is underfitting, the number of layers and nodes of the model is increased, and the activation function is adjusted to Sigmoid, so as to adjust the data according to the parameters, and obtain the audio performance model.

[0134] As an example of the present invention, refer to Figure 4 As shown, in this example, step S5 includes:

[0135] Step S51: performing time sequence feature matching on the dynamic sound unit structure data and the record player audio information to generate time sequence matching feature data;

[0136] Step S52: aligning the dynamic sound unit structure data and the record player audio information based on the time sequence matching feature data to generate a time sequence matching matrix; performing correlation analysis on the time sequence matching matrix to generate dynamic audio correlation data;

[0137] Step S53: converting the dynamic audio associated data into a standard input format to generate dynamic audio input data; importing the dynamic audio input data into an audio performance model to perform sound quality and timbre performance evaluation to generate a sound quality and timbre performance index; performing a sound quality and timbre scoring analysis on the sound quality and timbre performance index to obtain an audio performance evaluation report;

[0138] Step S54: Perform sensitivity analysis on the audio performance evaluation report to obtain sensitivity analysis data; adjust the structure parameters of the record player structure data according to the sensitivity analysis data to generate structure parameter adjustment data.

[0139] In the embodiment of the present invention, the dynamic sound unit structure data and the record player audio information are matched with timing features through algorithm analysis to identify the time series correspondence between the two. The timing feature matching involves synchronous processing of the audio signal and the structural response data to ensure that the two can correspond to each other on the time axis, generate timing matching feature data, accurately align the dynamic sound unit structure data and the audio information, generate a timing matching matrix, and the timing matching matrix records the correspondence between the structural response and the audio signal at different time points. An in-depth correlation analysis is performed on the timing matching matrix to identify the correlation and potential causal relationship between the data, generate dynamic audio correlation data, convert the dynamic audio correlation data into the standard input format required by the audio performance model, and generate dynamic audio. Input data, wherein the conversion operations include data normalization, dimensionality adjustment and encoding to ensure that the data can adapt to the requirements of the model input layer, and import the dynamic audio input data into the audio performance model for sound quality and timbre performance evaluation. The audio performance model will output sound quality and timbre performance indicators to generate sound quality and timbre performance indicators. The sound quality and timbre performance indicators reflect the performance of audio signals in different aspects. Furthermore, the sound quality and timbre performance indicators are subjected to a comprehensive sound quality and timbre scoring analysis to obtain an audio performance evaluation report, and a sensitivity analysis is performed on the audio performance evaluation report to obtain sensitivity analysis data, wherein the sensitivity analysis data includes the sensitivity of the record player structure data to the sound quality and timbre, and the structure parameters of the record player structure data are adjusted according to the sensitivity analysis data to generate structure parameter adjustment data.

[0140] Preferably, step S53 includes the following steps:

[0141] Step S531: converting the dynamic audio associated data into a standard input format to generate dynamic audio input data, wherein the standard input format conversion includes format unification, sampling rate synchronization and bit depth standardization;

[0142] Step S532: importing the dynamic audio input data into the audio performance evaluation model to calculate the sound quality and timbre parameters, and generating the sound quality and timbre performance index;

[0143] Step S533: extracting sound quality and timbre feature data according to the sound quality and timbre performance index to obtain sound quality and timbre feature data; weighting the sound quality and timbre feature data according to the preset audio performance contribution weight to generate weighted feature data; accumulating and averaging the feature values ​​of the weighted feature data to generate a quantitative score of audio performance;

[0144] Step S534: The audio performance quantification score is graded to obtain an audio performance evaluation report.

[0145] In an embodiment of the present invention, a standard input format conversion operation is performed on dynamic audio associated data to generate dynamic audio input data to meet the input requirements of an audio performance evaluation model, wherein the standard input format conversion operation includes format unification to ensure that all audio data follow the same file format and encoding standard; sampling rate synchronization to adjust the sampling rates of different audio data to ensure data consistency in the time dimension; bit depth standardization to convert all audio data into a unified bit depth, such as 16 bits or 24 bits, to eliminate quantization errors caused by different bit depths, and the dynamic audio input data is imported into the audio performance evaluation model to calculate sound quality and timbre parameters to generate sound quality and timbre performance indicators, wherein the sound quality and timbre performance indicators include frequency response, harmonic distortion and signal-to-noise ratio, and based on the sound quality and timbre performance indicators, key sound quality and timbre feature data are further extracted to obtain sound quality and timbre feature data, and the sound quality and timbre feature data are weighted to assign a preset value to each feature. Weight: Set the weight of the contribution of audio performance to reflect the importance of each feature to the overall sound quality evaluation. For example, frequency response is given a higher weight because it has a greater impact on the sound quality. The weighted processing is completed by multiplying each eigenvalue by its corresponding weight to obtain weighted feature data. The weighted feature data is accumulated to obtain a sum, which reflects the combined impact of all sound quality features. By calculating the average of these weighted eigenvalues, a single value representing the overall audio performance is obtained, namely the audio performance quantitative score, which provides a quantitative evaluation for the audio signal. The generated audio performance quantitative score is used for rating level division, and the quantitative score is mapped to the predefined rating level. The threshold of each level is determined according to the statistical distribution of the score. A score of 90 or above is set as "excellent", 80 to 89 is set as "good", 70 to 79 is set as "average", and 60 or below is set as "poor", and an audio performance evaluation report is obtained.

[0146] As an example of the present invention, refer to Figure 5 As shown, in this example, step S54 includes:

[0147] Step S541: performing sensitivity analysis on the record player structure data based on the audio performance evaluation report to obtain sensitivity analysis data;

[0148] Step S542: performing a multiple linear regression analysis based on the sensitivity analysis data to generate multiple linear regression coefficients; performing an impact weight analysis on the record player structure data according to the multiple linear regression coefficients to obtain impact weight data;

[0149] Step S543: Performing statistical significance analysis on the impact weight data to obtain significant impact weight data; sorting the record player structure data in descending order according to the significant impact weight data to obtain influential structure parameters;

[0150] Step S544: numerically identifying the influential structural parameters to obtain the most influential structural parameters;

[0151] Step S545: Adjust the record player structure data according to the most influential structural parameter to obtain structural parameter adjustment data.

[0152] In the embodiment of the present invention, a sensitivity analysis is performed on the record player structure data by means of partial differential technology, the influence of each parameter on the sound quality and timbre performance index is quantified, and the sensitivity analysis data is obtained. The relationship between the record player structure data and the audio performance is determined by using a multiple linear regression analysis method based on the sensitivity analysis data, and multiple independent variables (record player structure data) are associated with dependent variables (audio performance indexes). Through multiple linear fitting, multiple linear regression coefficients are generated. The multiple linear regression coefficients describe the influence trend and intensity of the record player structure data on the audio performance. The multiple linear regression coefficients are subjected to a statistical significance analysis to obtain significant influence weight data. The statistical significance analysis is performed on the multiple linear regression coefficients. The analysis involves calculating a t-statistic and a corresponding p-value, wherein coefficients with p-values ​​below a certain threshold (such as 0.05) are considered statistically significant, sorting the influence weight data in descending order according to the significance influence weight data, identifying the structural parameters with the greatest influence on the audio performance, obtaining the influential structural parameters, numerically identifying the influential structural parameters, and in particular identifying the structural parameters with the highest influence weights, i.e., the most influential structural parameters, to obtain the most influential structural parameters, and adjusting the record player structural data based on the identified most influential structural parameters to obtain structural parameter adjustment data, wherein the structural parameter adjustment data includes modifying the size, material or design of the components to optimize the audio performance.

[0153] In this specification, a system for online design and optimization of a record player structure is provided, which is used to execute the above-mentioned method for online design and optimization of a record player structure. The system for online design and optimization of a record player structure comprises:

[0154] The structure distribution information module is used to obtain the structure data of the record player; extract the structure information of the structure data of the record player to obtain the key structure data set; perform data processing on the key structure data set to obtain the standard structure data set; perform three-dimensional mapping on the standard structure data set to generate structure distribution information;

[0155] The impact factor module is used to obtain the technical specification document of the record player; perform semantic analysis on the technical specification document of the record player to obtain the design index data of the record player; perform influence analysis on the design index data of the record player based on the structural distribution information to generate a design parameter influence map; perform influence factor extraction on the design parameter influence map to obtain influence factor information;

[0156] The dynamic sound unit structure module is used to obtain the real-time working state data of the record player; extract the dynamic structure motion data from the real-time working state data of the record player to obtain the dynamic structure motion data; perform sound unit motion structure analysis on the dynamic structure motion data according to the influencing factor information to obtain the dynamic sound unit structure data;

[0157] The audio performance model module is used to obtain the audio information of the record player; perform spectrum processing on the audio information of the record player to obtain the audio spectrum information; extract the frequency response, spectrum centroid and spectrum smoothness characteristics of the audio spectrum information to obtain audio feature data; perform time-frequency analysis on the audio spectrum information of the record player based on the audio feature data to generate audio time-frequency data; construct an audio performance model based on the audio time-frequency data to obtain an audio performance model;

[0158] The record player structure adjustment module is used to quantitatively associate the dynamic sound unit structure data with the record player audio information to generate dynamic audio association data; import the dynamic audio association data into the audio performance model to evaluate the sound quality and timbre performance to obtain an audio performance evaluation report; adjust the structure parameters of the record player structure data according to the audio performance evaluation report to generate structure parameter adjustment data;

[0159] The visualization module is used to build a visualization platform for online design optimization of the record player structure according to the structural parameter adjustment data, so as to perform the online optimization design operation of the record player structure.

[0160] The present invention constructs an online design optimization system based on the structure of a record player. The structural distribution information module obtains the structural data of the record player to ensure a comprehensive understanding of the structure of the record player, provides basic data support for subsequent analysis, and enhances the recognition and understanding of core elements in the design of the record player by identifying key structural information. The key structural data set is processed to improve the quality and availability of the data. The key data set is converted into a standard structural data set to achieve data normalization. The two-dimensional data is converted into a three-dimensional view to enhance the intuitive understanding of the spatial relationship of the record player structure, which is helpful for a more in-depth morphological analysis. The structural distribution information obtained through three-dimensional mapping reveals the spatial layout and mutual relationship of the various components of the record player. The impact factor module obtains the technical specification documents of the record player to ensure that the source of the design indicator data is authoritative and accurate. It conducts a semantic analysis of the technical specification documents of the record player to obtain the design indicator data of the record player, which can accurately capture the design requirements and standards. It conducts an impact analysis on the design indicator data of the record player based on the structural distribution information, which can identify the key design parameters that affect the performance of the record player, and generates a design parameter impact map, which helps to intuitively understand the complex interaction of the design parameters. The impact factor is extracted from the design parameter impact map, which can identify the parameters that should be given priority or adjusted in the design. The dynamic sound unit structure module can capture the real-time status data of the record player in operation by obtaining the real-time working status data of the record player. It extracts dynamic structural motion data from the real-time working status data of the record player, which provides a data basis for further structural analysis. It uses the impact factor information to conduct an in-depth analysis of the dynamic structural motion data, which can focus on the motion characteristics of the sound unit, so as to more accurately understand the physical mechanism of sound generation and propagation. The audio performance model module obtains the audio information of the record player to ensure the comprehensive recording of the audio played by the record player, converts the audio signal into a spectrum representation, reveals the frequency components of the audio signal, and provides a visual means for understanding the frequency characteristics of the sound. The key features of the extracted audio spectrum provide quantitative parameters for in-depth analysis of audio performance, which is helpful for further time-frequency analysis. Time-frequency analysis of the audio spectrum information can identify the frequency changes of the audio signal in different time periods and enable a better understanding of the dynamic characteristics of the audio. The generated audio time-frequency data helps to capture the instantaneous changes of the audio signal. The audio performance model is constructed based on the audio time-frequency data to obtain an audio performance model that can quantitatively evaluate the sound quality of the record player and provide an objective sound quality evaluation standard.The record player structure adjustment module can identify the specific connection between structural features and sound quality performance by quantitatively correlating the dynamic sound unit structure data with the record player audio information. The generated dynamic audio correlation data integrates two types of information, structure and audio, and provides a comprehensive perspective for in-depth analysis. The dynamic audio correlation data is evaluated by using the audio performance model, which can systematically analyze and understand the overall performance of sound quality and timbre. The obtained audio performance evaluation report provides a detailed analysis and evaluation of the record player performance. Adjusting the record player structure parameters according to the evaluation report helps to improve the record player performance in a targeted manner and achieve the optimization of the record player structure design. The generated structural parameter adjustment data provides precise guidance for design changes, ensuring the scientificity and effectiveness of the optimization measures. The visualization module constructs a visualization platform for the online design optimization of the record player structure based on the structural parameter adjustment data, so that the record player structure design work can be carried out remotely and in real time, improving the accessibility and efficiency of the design, and showing the effect of the structural parameter adjustment through visualization means, so that the production team can intuitively understand the impact of the design change. Therefore, the present invention comprehensively evaluates the impact of record player structural data on audio performance through Internet of Things technology, semantic analysis technology, audio analysis and mutual information technology, and improves the accuracy of the evaluation, thereby realizing online optimization of record player structural data.

[0161] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0162] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for online design optimization based on a record player structure, characterized in that: The following steps are involved: Step S1: acquiring the structure data of the record player; extracting the structure information of the structure data of the record player to obtain a key structure data set; performing data processing on the key structure data set to obtain a standard structure data set; performing three-dimensional mapping on the standard structure data set to generate structure distribution information; Step S2: obtaining a record player technical specification document; performing semantic analysis on the record player technical specification document to obtain record player design index data; performing influence analysis on the record player design index data based on structural distribution information to generate a design parameter influence map; performing influence factor extraction on the design parameter influence map to obtain influence factor information; Step S3: acquiring the real-time working state data of the record player; extracting the dynamic structure motion data from the real-time working state data of the record player to obtain the dynamic structure motion data; performing sound unit motion structure analysis on the dynamic structure motion data according to the influencing factor information to obtain the dynamic sound unit structure data; Step S4: Acquire the audio information of the record player; perform spectrum processing on the audio information of the record player to obtain audio spectrum information; extract the frequency response, spectrum centroid and spectrum smoothness characteristics of the audio spectrum information to obtain audio feature data; perform time-frequency analysis on the audio spectrum information of the record player based on the audio feature data to generate audio time-frequency data; construct an audio performance model based on the audio time-frequency data to obtain an audio performance model; Step S5: quantitatively associate the dynamic sound unit structure data with the record player audio information to generate dynamic audio association data; The dynamic audio associated data is imported into the audio performance model to evaluate the sound quality and timbre performance, and an audio performance evaluation report is obtained; the structure parameters of the record player structure data are adjusted according to the audio performance evaluation report to generate structure parameter adjustment data; step S5 includes the following steps: Step S51: performing time sequence feature matching on the dynamic sound unit structure data and the record player audio information to generate time sequence matching feature data; Step S52: aligning the dynamic sound unit structure data and the record player audio information based on the time sequence matching feature data to generate a time sequence matching matrix; performing correlation analysis on the time sequence matching matrix to generate dynamic audio correlation data; Step S53: converting the dynamic audio associated data into a standard input format to generate dynamic audio input data; importing the dynamic audio input data into an audio performance model to perform sound quality and timbre performance evaluation to generate a sound quality and timbre performance index; performing a sound quality and timbre scoring analysis on the sound quality and timbre performance index to obtain an audio performance evaluation report; Step S54: Perform sensitivity analysis on the audio performance evaluation report to obtain sensitivity analysis data; adjust the structure parameters of the record player structure data according to the sensitivity analysis data to generate structure parameter adjustment data; the specific steps of step S54 are: Step S541: performing sensitivity analysis on the record player structure data based on the audio performance evaluation report to obtain sensitivity analysis data; Step S542: performing a multiple linear regression analysis based on the sensitivity analysis data to generate multiple linear regression coefficients; performing an impact weight analysis on the record player structure data according to the multiple linear regression coefficients to obtain impact weight data; Step S543: Performing statistical significance analysis on the impact weight data to obtain significant impact weight data; sorting the record player structure data in descending order according to the significant impact weight data to obtain influential structure parameters; Step S544: numerically identifying the influential structural parameters to obtain the most influential structural parameters; Step S545: adjusting the record player structure data according to the most influential structure parameter to obtain structure parameter adjustment data; Step S6: constructing a visualization platform for online design optimization of the record player structure according to the structural parameter adjustment data to execute the online optimization design operation of the record player structure.

2. The method for online design optimization based on the structure of a record player according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: using a sensor to obtain the structure data of the record player; Step S12: extracting morphological features from the record player structure data to obtain a key structure data set; Step S13: performing data processing on the key structure data set to obtain a standard structure data set, wherein the data processing includes data decryption, data cleaning, data denoising and data standardization; Step S14: Perform three-dimensional mapping on the standard structure data set to obtain structure three-dimensional mapping data; perform projection transformation on the structure three-dimensional mapping data to generate structure distribution information.

3. The method for online design optimization based on the structure of a record player according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: obtaining a record player technical specification document; performing semantic analysis on the record player technical specification document to obtain design requirement information and standard parameter information; performing data integration on the design requirement information and the standard parameter information to obtain record player design data; Step S22: performing mutual information influence analysis on the record player design index data and structure distribution information to obtain mutual information; Step S23: using the record player design index data as network node data, and judging the correlation strength of the network node data by using a preset mutual information threshold, and when the network node data is greater than or equal to the preset mutual information threshold, performing weighted edge connection on the network node data to generate weighted edge data; Step S24: constructing an influence map of network node data and weighted edge data using a graph theory analysis method to generate a design parameter influence map; Step S25: extracting significant influencing factors from the design parameter influence map to obtain influencing factor information.

4. The method for online design optimization based on the structure of a record player according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: using sensors to obtain real-time working status data of the record player; Step S32: performing dynamic characteristic measurement on the real-time data of the working state of the record player to obtain dynamic characteristic measurement data, wherein the dynamic characteristic measurement includes measuring the displacement, strain and acceleration motion information of the record player structure; Step S33: extracting dynamic structural motion data from the dynamic characteristic measurement data to obtain dynamic structural motion data; Step S34: extract the sound unit information of the dynamic structural motion data according to the influencing factor information to obtain the sound unit data; extract the displacement information, acceleration information and frequency response information of the sound unit data to obtain the dynamic sound unit data; perform structural analysis on the dynamic sound unit data to obtain the dynamic sound unit structure data.

5. The method for online design optimization based on the structure of a record player according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: using an audio collector to obtain a record player audio signal of a record player; converting the record player audio signal into a digital audio file format to generate record player audio information; Step S42: performing spectrum conversion on the audio information of the record player to generate a spectrum graph; extracting frequency information and amplitude data in the spectrum graph to obtain audio spectrum information; Step S43: extracting audio features from the audio spectrum information to obtain audio feature data, wherein the extracted audio features include frequency response, spectrum centroid and spectrum smoothness; Step S44: performing time window segmentation on the audio spectrum information of the record player according to the audio feature data to generate an audio time window; performing time domain analysis on the audio time window to generate audio time-frequency data; Step S45: construct an audio performance model based on the audio time-frequency data to obtain an audio performance model.

6. The method for online design optimization based on the structure of a record player according to claim 5 is characterized in that: Step S45 includes the following steps: Step S451: extracting the time-frequency response, distortion, signal-to-noise ratio and dynamic range of the audio time-frequency data to obtain audio time-frequency feature data; Step S452: Performing sound quality and timbre performance mapping analysis according to the audio time-frequency feature data to generate sound quality and timbre performance mapping data; Step S453: constructing an audio performance model according to the sound quality and timbre performance mapping data to obtain an audio performance pre-model; and training the audio performance pre-model using the sound quality and timbre performance mapping data to obtain an audio performance training model; Step S454: perform model cross-validation evaluation on the audio performance training model to obtain audio performance model evaluation data; adjust model parameters of the audio performance training model using the audio performance model evaluation data to obtain an audio performance model.

7. The method for online design optimization based on the structure of a record player according to claim 1 is characterized in that: Step S53 includes the following steps: Step S531: converting the dynamic audio associated data into a standard input format to generate dynamic audio input data, wherein the standard input format conversion includes format unification, sampling rate synchronization and bit depth standardization; Step S532: importing the dynamic audio input data into the audio performance evaluation model to calculate the sound quality and timbre parameters, and generating the sound quality and timbre performance index; Step S533: extracting sound quality and timbre feature data according to the sound quality and timbre performance index to obtain sound quality and timbre feature data; weighting the sound quality and timbre feature data according to the preset audio performance contribution weight to generate weighted feature data; accumulating and averaging the feature values ​​of the weighted feature data to generate a quantitative score of audio performance; Step S534: The audio performance quantification score is graded to obtain an audio performance evaluation report.

8. An online design optimization system based on the structure of a record player, characterized in that: The method for performing the online design optimization method based on the structure of a record player as claimed in claim 1 comprises: The structure distribution information module is used to obtain the structure data of the record player; extract the structure information of the structure data of the record player to obtain the key structure data set; perform data processing on the key structure data set to obtain the standard structure data set; perform three-dimensional mapping on the standard structure data set to generate structure distribution information; The impact factor module is used to obtain the technical specification document of the record player; perform semantic analysis on the technical specification document of the record player to obtain the design index data of the record player; perform influence analysis on the design index data of the record player based on the structural distribution information to generate a design parameter influence map; perform influence factor extraction on the design parameter influence map to obtain influence factor information; The dynamic sound unit structure module is used to obtain the real-time working state data of the record player; extract the dynamic structure motion data from the real-time working state data of the record player to obtain the dynamic structure motion data; perform sound unit motion structure analysis on the dynamic structure motion data according to the influencing factor information to obtain the dynamic sound unit structure data; The audio performance model module is used to obtain the audio information of the record player; perform spectrum processing on the audio information of the record player to obtain the audio spectrum information; extract the frequency response, spectrum centroid and spectrum smoothness characteristics of the audio spectrum information to obtain audio feature data; perform time-frequency analysis on the audio spectrum information of the record player based on the audio feature data to generate audio time-frequency data; construct an audio performance model based on the audio time-frequency data to obtain an audio performance model; The record player structure adjustment module is used to quantitatively associate the dynamic sound unit structure data with the record player audio information to generate dynamic audio association data; import the dynamic audio association data into the audio performance model to evaluate the sound quality and timbre performance to obtain an audio performance evaluation report; adjust the structure parameters of the record player structure data according to the audio performance evaluation report to generate structure parameter adjustment data; the record player structure adjustment module is specifically used to: Step S51: performing time sequence feature matching on the dynamic sound unit structure data and the record player audio information to generate time sequence matching feature data; Step S52: aligning the dynamic sound unit structure data and the record player audio information based on the time sequence matching feature data to generate a time sequence matching matrix; performing correlation analysis on the time sequence matching matrix to generate dynamic audio correlation data; Step S53: converting the dynamic audio associated data into a standard input format to generate dynamic audio input data; importing the dynamic audio input data into an audio performance model to perform sound quality and timbre performance evaluation to generate a sound quality and timbre performance index; performing a sound quality and timbre scoring analysis on the sound quality and timbre performance index to obtain an audio performance evaluation report; Step S54: Perform sensitivity analysis on the audio performance evaluation report to obtain sensitivity analysis data; adjust the structure parameters of the record player structure data according to the sensitivity analysis data to generate structure parameter adjustment data; the specific steps of step S54 are: Step S541: performing sensitivity analysis on the record player structure data based on the audio performance evaluation report to obtain sensitivity analysis data; Step S542: performing a multiple linear regression analysis based on the sensitivity analysis data to generate multiple linear regression coefficients; performing an impact weight analysis on the record player structure data according to the multiple linear regression coefficients to obtain impact weight data; Step S543: Performing statistical significance analysis on the impact weight data to obtain significant impact weight data; sorting the record player structure data in descending order according to the significant impact weight data to obtain influential structure parameters; Step S544: numerically identifying the influential structural parameters to obtain the most influential structural parameters; Step S545: adjusting the record player structure data according to the most influential structure parameter to obtain structure parameter adjustment data; The visualization module is used to build a visualization platform for online design optimization of the record player structure according to the structural parameter adjustment data, so as to perform the online optimization design operation of the record player structure.

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