A sound quality adjustment method combining vacuum tube and TFT screen display

Abstract

The present invention provides a sound quality adjustment method combining a vacuum tube and a TFT screen display, and relates to the technical field of audio processing. The present invention obtains spectrum optimization information through a vacuum tube module to preliminarily implement sound quality processing, and uses a TFT screen to display the initial sound quality parameter combination and distortion information in real time, so that the user can intuitively understand the current sound quality status; based on a deep learning model, the user's physiological feedback data is analyzed to generate a sound quality adjustment strategy that dynamically adapts to the user's status, further optimizes the sound quality parameter combination, and makes the adjustment process more intelligent; the user can modify the sound quality parameters in real time on an interactive adjustment interface, generate a final optimized secondary sound quality parameter combination indicator, and apply it to the adjustment of digital audio equipment; the accuracy and personalization of sound quality adjustment are improved, and at the same time, efficient real-time feedback and interactive experience are provided.

Description

Technical Field

[0001] The present invention relates to the technical field of audio processing, and in particular to a sound quality adjustment method combining a vacuum tube and a TFT screen display. Background Art

[0002] With the widespread adoption of audio playback devices, users' demand for personalized sound quality continues to rise. Traditional sound quality tuning methods rely primarily on preset sound effect modes and lack the ability to adjust in real time to individual user characteristics. While the use of vacuum tubes in audio signal processing can provide unique timbre characteristics, their optimization strategies are often fixed and cannot be dynamically adjusted based on the user's real-time state.

[0003] Existing sound quality tuning technologies still have many shortcomings in achieving sound quality optimization and user interaction. First, traditional vacuum tube audio equipment generally lacks an intuitive user interface, making it difficult for users to monitor and adjust various audio parameters in real time during sound quality tuning, resulting in a cumbersome and experience-dependent tuning process.

[0004] Second, while existing digital audio processing methods offer high-precision sound quality optimization, they often neglect the user's subjective auditory experience and lack dynamic adjustment mechanisms based on physiological feedback. Furthermore, the displays on many audio devices are limited in functionality, presenting only basic audio parameters and failing to implement complex interactive operations and real-time feedback, limiting the user's control and understanding of sound quality optimization.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0006] The purpose of the present invention is to provide a sound quality adjustment method combining vacuum tube and TFT screen display to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A sound quality adjustment method combining a vacuum tube and a TFT screen display, comprising the following steps:

[0009] Step S1: Obtain spectrum optimization information of the vacuum tube module on the input audio signal at the current moment to obtain an initial sound quality parameter combination;

[0010] Step S2: responding to the spectrum optimization information, and using a TFT screen to display in real time the initial sound quality parameter combination after spectrum optimization, and simultaneously displaying the distortion evaluated after adjustment based on the initial sound quality parameter combination;

[0011] Step S3: Collecting real-time physiological parameters of the user terminal under different sound quality parameter combinations and distortion levels, and analyzing these data through a deep learning model to generate a sound quality adjustment strategy based on the real-time physiological parameters to adapt to the current initial sound quality parameter combination and distortion level, and obtain an adjusted first-level sound quality parameter combination indicator;

[0012] Step S4: responding to the sound quality adjustment strategy and displaying the interactive adjustment interface and the adjusted first-level sound quality parameter combination index through the TFT screen;

[0013] Step S5: receiving the operation information adjusted in real time by the user terminal through the TFT screen interactive adjustment interface, and making final adjustments to the first-level sound quality parameter combination index based on the operation information to generate a final optimized second-level sound quality parameter combination index;

[0014] Step S6: The secondary sound quality parameter combination index is used to adjust the audio signal gain and spectrum distribution of the digital audio device, and the adjustment result of the sound quality parameter combination is displayed on the TFT screen.

[0015] Compared with the existing technology, the beneficial effects of the present invention are: spectrum optimization information is obtained through the vacuum tube module, sound quality processing is preliminarily realized, and the initial sound quality parameter combination and distortion information are displayed in real time on the TFT screen, so that the user can intuitively understand the current sound quality status; based on the deep learning model, the user's physiological feedback data is analyzed, and a sound quality adjustment strategy that dynamically adapts to the user's status is generated, and the sound quality parameter combination is further optimized to make the adjustment process more intelligent; the user can modify the sound quality parameters in real time in the interactive adjustment interface, generate the final optimized secondary sound quality parameter combination index, and apply it to the adjustment of digital audio equipment; the accuracy and personalization of sound quality adjustment are improved, and efficient real-time feedback and interactive experience are provided; combined with the data analysis of the user's physiological status, the invention realizes high-quality, personalized sound quality optimization, and provides an innovative path for the intelligent development of audio equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of the overall method of the present invention. DETAILED DESCRIPTION

[0017] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0019] Example 1:

[0020] See also Figure 1 , the present invention provides a technical solution:

[0021] A sound quality adjustment method combining a vacuum tube and a TFT screen display is applied to a digital audio device connected to a wearable device with a physiological parameter monitoring function, and is characterized by comprising:

[0022] Step S1: Obtain spectrum optimization information of the vacuum tube module on the input audio signal at the current moment to obtain an initial sound quality parameter combination;

[0023] Further explanation: the objects of spectrum optimization information include spectrum distribution parameters and signal gain parameters; the specific operation steps are as follows:

[0024] Receive external audio signals through the input interface of digital audio equipment;

[0025] Start the vacuum tube module to perform preliminary processing on the received input audio signal;

[0026] Extract spectrum distribution parameters from the vacuum tube module, that is, the energy distribution of the audio signal in different frequency bands;

[0027] Extract signal gain parameters from the vacuum tube module, that is, the amplification or attenuation of the signal in each frequency band;

[0028] The extracted spectrum distribution parameters and signal gain parameters are combined into spectrum optimization information;

[0029] The vacuum tube module includes a dynamic operating temperature monitoring unit, which is used to monitor the temperature changes of the vacuum tube in real time and trigger corresponding graded warnings. Different levels of warnings trigger optimization strategies for the following spectrum distribution parameters and signal gain parameters:

[0030] In this embodiment, real-time monitoring of the temperature change of the vacuum tube is achieved by collecting temperature data of the vacuum tube during operation and recording the temperature change curve;

[0031] Set at least two temperature warning values ​​for different levels of temperature warnings, specifically:

[0032] When the temperature of the vacuum tube is within the range of two temperature warning values, the first level warning is activated;

[0033] Level 1 warning includes:

[0034] Start the spectrum distribution parameter optimization module to soften the high frequency band: adjust the spectrum distribution parameters of the high frequency band to reduce the gain of the high frequency signal and reduce the harshness;

[0035] When the temperature of the vacuum tube is above the maximum temperature warning value, the second level warning is activated;

[0036] Level 2 warnings include:

[0037] Start the signal gain parameter optimization module and adjust the amplitude of the signal gain parameters of each frequency band: reduce the amplitude of the signal gain parameters; in the high power driving frequency band, reduce the heat load on the vacuum tube;

[0038] The initially optimized spectrum distribution parameters and signal gain parameters are expressed as an initial sound quality parameter combination;

[0039] receiving initially optimized spectrum distribution parameters and signal gain parameters;

[0040] Through the digital signal processing module, the input audio signal is initially optimized by corresponding high-frequency softening or signal gain adjustment.

[0041] It should be noted that the specific implementation instructions for different levels of temperature warnings are as follows:

[0042] Start the working temperature dynamic monitoring unit and start real-time monitoring of the working temperature of the vacuum tube module;

[0043] The temperature data of the vacuum tube during operation is collected once per second;

[0044] Record the temperature change curve and store the temperature data in the internal memory of the device;

[0045] Perform real-time analysis on the collected temperature data and calculate the difference between the current temperature and multiple preset temperature warning values;

[0046] According to the monitoring results of the working temperature dynamic monitoring unit, the implementation steps for triggering the corresponding level of graded warning are as follows:

[0047] Set the following temperature warning values:

[0048] Level 1 warning value: 60℃; Level 2 warning value: 75℃;

[0049] The approaching range of the first-level warning is defined as 60℃≤vacuum tube temperature<75℃;

[0050] The range of the second-level warning is defined as the vacuum tube temperature ≥ 75°C;

[0051] When the real-time monitored vacuum tube temperature enters the first-level warning approach range of 60℃≤vacuum tube temperature<75℃, the first-level warning is activated;

[0052] When the real-time monitored vacuum tube temperature is above 75°C, the second-level warning is activated;

[0053] When a Level 1 warning is triggered, the high frequency band is softened by the spectrum distribution parameter optimization module. The specific steps are as follows:

[0054] Receive the first-level warning signal and confirm that the vacuum tube temperature has entered the first-level warning approach range of 60°C ≤ vacuum tube temperature < 75°C;

[0055] Start the spectrum distribution parameter optimization module to perform softening processing on the high frequency band, specifically reducing the spectrum distribution parameters of the high frequency band above 2kHz by 3dB;

[0056] Adjust the filter gain of the high frequency band to reduce the output strength of the high frequency signal;

[0057] Feeding the optimized spectrum distribution parameters back to the digital signal processing module for real-time processing of audio signals;

[0058] Execute the signal gain parameter optimization strategy under the second-level warning. When the second-level warning is triggered, the signal gain parameter optimization module will adjust the amplitude of the signal gain parameters of each frequency band;

[0059] Specific steps:

[0060] Receive the second-level warning signal and confirm that the vacuum tube temperature is above 75°C;

[0061] Characterize each frequency band into a low frequency band, a mid frequency band, and a high frequency band;

[0062] Low frequency band: 20Hz-250Hz, mid-frequency band: 250Hz-2kHz, high frequency band: 2kHz-20kHz;

[0063] Start the signal gain parameter optimization module to adjust the signal gain parameters of each frequency band, specifically reducing the signal gain parameters of all frequency bands by 5%;

[0064] The high-power drive frequency band in the high-frequency band is set to 4kHz-6kHz, and the secondary warning signal is used to reduce the signal gain parameter by 10% in the high-power drive frequency band;

[0065] It should be noted that to verify the effectiveness of further reducing the signal gain by 10% in the high-power drive frequency band of 4kHz-6kHz in reducing power load, this experiment designed a multi-stage test plan with both control and experimental groups. The purpose of the experiment was to explore the specific effects of adjusting the gain in this frequency band on vacuum tube temperature, power consumption, audio signal quality, and device stability.

[0066] 1. Equipment selection and setup:

[0067] The experiment used two identical digital audio devices, designated Sample A (control group) and Sample B (experimental group). Both devices were equipped with vacuum tube modules and were tested under identical environmental conditions. The ambient temperature was maintained at a constant 22°C, and the devices were operated continuously to simulate the load of prolonged audio playback.

[0068] Each device is equipped with a high-precision temperature sensor for real-time monitoring of the vacuum tube's operating temperature. A power consumption recording device is also installed to ensure accurate measurement of power consumption at different gain settings.

[0069] 2. Signal generation and processing:

[0070] An audio signal generator was used to generate a sweep signal covering the entire frequency range (20Hz to 20kHz) to test the device's response characteristics. The control group (Sample A) had no gain adjustment, while the experimental group (Sample B) had the signal gain reduced by 10% within the high-power drive frequency range of 4kHz-6kHz. This adjustment was performed using a digital signal processing unit to ensure accurate gain adjustment.

[0071] 3. Experimental steps:

[0072] Initial test: Start sample A and sample B, play the same frequency sweep audio signal, and record the vacuum tube temperature, power consumption, and audio spectrum distribution in the initial state.

[0073] Gain Adjustment: Reduce the signal gain parameter by 10% in the high-power drive frequency band of 4kHz-6kHz for Sample B. Keep the original gain setting for Sample A unchanged.

[0074] Operation and data collection: During the experiment, the audio signal was played continuously, and the device's vacuum tube temperature, power consumption, and spectrum analysis results were recorded every 10 minutes until the experiment was completed.

[0075] Sound quality analysis: After the experiment, use audio analysis software to evaluate the sound quality of the two devices, especially the changes in the high-frequency sound quality, including harshness and sound balance.

[0076] 4. Experimental variables:

[0077] Experimental variables included gain settings (original settings for sample A and 10% gain reduction for sample B), as well as changes in vacuum tube operating temperature and power consumption. Data was collected every 10 minutes, and the experiment lasted 60 minutes.

[0078] 1. Temperature and power comparison:

[0079] In the control group sample A, the temperature of the vacuum tube gradually increased during the experiment, eventually reaching 77°C, and the power consumption gradually increased from 100W to 130W, showing the high power consumption characteristics when the gain is not adjusted.

[0080] Under the same experimental conditions, the temperature of the vacuum tube of sample B in the experimental group increased more slowly due to the 10% reduction in signal gain in the 4kHz-6kHz frequency band, and the final temperature only rose to 68°C. The power consumption also remained at a low level, increasing from 100W to 88W, significantly reducing the power burden.

[0081] 2. Sound quality analysis:

[0082] Comparative analysis revealed that Sample B in the experimental group significantly reduced the harshness of the sound quality due to the reduced gain in the high-frequency band. User listening tests showed that when Sample B played the same audio signal, the high-frequency sound became softer and more balanced, avoiding excessively harsh high-frequency interference and thus improving the overall listening experience.

[0083] 3. Power load and equipment stability:

[0084] By adjusting the gain of the high-power drive frequency band, Sample B significantly reduced the power load of the device, reduced the risk of vacuum tube overheating, improved the stability of the device, and avoided the impact of long-term high-temperature operation on the life of the vacuum tube.

[0085] The following data is collected during the experiment, showing the temperature change, power consumption, audio spectrum, and gain parameter comparison of Sample A and Sample B at different time points.

[0086] Table 1: Study on reducing signal gain parameters by 10% in the high power driving frequency band 4kHz-6kHz:

[0087]

[0088] Table 1 Data analysis and demonstration:

[0089] 1. Temperature and power comparison:

[0090] The temperature of the vacuum tube of sample A increased from 50°C to 77°C, and the power consumption increased from 100W to 130W, indicating that the temperature and power consumption of the device were high when the gain adjustment was not performed.

[0091] The vacuum tube temperature of sample B increased from 50°C to 68°C, and the power consumption increased from 100W to 88W, showing a significant effect after gain reduction. The increase in temperature and power consumption was much lower than that of sample A.

[0092] 2. Sound quality evaluation:

[0093] In the spectrum analysis, the high-frequency band of sample A (especially 4kHz-6kHz) shows a strong sense of sharpness, while sample B reduces the gain of this frequency band, making the audio output more balanced and gentle, greatly improving the sound quality performance of the high-frequency part and reducing auditory fatigue.

[0094] 3. Equipment stability:

[0095] By reducing the gain in the 4kHz-6kHz frequency band, Sample B significantly reduced the power load and the heat load on the vacuum tube, thereby improving the stability of the device and avoiding performance degradation caused by overheating. Compared with Sample A, Sample B achieved better temperature control during the experiment, resulting in a more durable and stable device.

[0096] This experiment verified the effectiveness of reducing the signal gain by 10% in the high-power drive frequency band of 4kHz-6kHz in reducing power load. By reducing the gain in this frequency band, the device's power consumption and the temperature rise of the vacuum tube can be significantly reduced, thereby improving the device's stability and extending its service life. At the same time, the optimization of sound quality reduces the harshness in the high-frequency band, and the sound quality is more balanced and soft. The above experimental data fully supports the practicality of further reducing the signal gain parameter by 10% in the high-power drive frequency band of 4kHz-6kHz to reduce power load, proving its advantages in practical applications.

[0097] Feedback the optimized signal gain parameters to the digital signal processing module for real-time processing of audio signals;

[0098] The digital signal processing module is used to soften the high frequency of the input audio signal or adjust the signal gain. Specific operation steps:

[0099] Receive optimized spectrum distribution parameters and signal gain parameters.

[0100] Based on the optimized parameters, the digital signal processing module performs the following processing:

[0101] Apply a low-pass filter to high-frequency signals to ensure that signals above 2kHz are attenuated by 3dB;

[0102] Adjust the gain value of each frequency band according to the signal gain parameter. It should be noted that the high-power drive frequency band of 4kHz-6kHz is the area that needs attention in the high frequency band.

[0103] Most existing technologies use a single-module sound quality adjustment system. This solution integrates a vacuum tube module with a TFT screen to display optimized parameters in real time, enhancing user experience and ease of operation.

[0104] Dynamic temperature monitoring and graded warning: The dynamic operating temperature monitoring unit monitors the temperature of the vacuum tube in real time and triggers corresponding optimization strategies based on different temperature levels, improving the intelligence and safety of the equipment and preventing performance degradation or damage due to overheating.

[0105] Quantitative optimization strategy: Specific temperature warning values ​​and adjustment ranges are set to make the sound quality adjustment strategy operational and feasible.

[0106] Step S2: responding to the spectrum optimization information, and using a TFT screen to display in real time the initial sound quality parameter combination after spectrum optimization, and simultaneously displaying the distortion evaluated after adjustment based on the initial sound quality parameter combination;

[0107] Further explanation: The TFT screen is a touch screen, which outputs the audio signal that has undergone initial optimization processing to the TFT screen display unit through the digital signal processing module, thereby realizing the real-time display of the sound quality adjustment effect. The sound quality adjustment effect display includes displaying the sound quality parameter combination and distortion after spectrum optimization;

[0108] The specific implementation contents are as follows:

[0109] The spectrum optimization information from the signal gain parameter optimization module is received through the digital signal processing module; the information includes the gain value adjustment instructions of each frequency band and related sound quality parameters.

[0110] Parse the received spectrum optimization information to extract the specific gain values, filter types, and parameter settings for each frequency band to ensure data accuracy in subsequent processing steps;

[0111] Generate an initial sound quality parameter combination based on the analyzed spectrum optimization information; the initial sound quality parameter combination includes the spectrum distribution parameters and signal gain parameters after initial optimization;

[0112] Configure filter settings: Determine and configure the filter type (such as low-pass, high-pass, and band-pass filters) and its parameters (such as cutoff frequency and filter order) corresponding to each frequency band to achieve the desired spectrum optimization effect.

[0113] Integrate sound quality parameters: Integrate the generated spectrum distribution parameters with the signal gain parameters to form a complete initial sound quality parameter combination, ensuring that the audio signal processing module can accurately apply these parameters to optimize sound quality.

[0114] Activate the distortion evaluation module to calculate the distortion of the generated initial sound quality parameter combination; use the total harmonic distortion (THD) calculation method to quantify the distortion of the audio signal under the optimized parameters; and record the distortion as THD.

[0115] Total harmonic distortion calculation formula:

[0116]

[0117] Formula parameter explanation: V1 is the fundamental voltage, which refers to the voltage amplitude of the fundamental frequency component in the audio signal;

[0118] V2,V3,V4,…,V n It is the voltage of each order harmonic, corresponding to the voltage amplitude of the second, third, fourth harmonic components of the fundamental frequency;

[0119] n is the highest order of harmonics, which depends on the complexity of the audio signal and the processing capability of the equipment;

[0120] Calculation process of THD (%):

[0121] Measure the fundamental voltage V1 and each harmonic voltage V2, V3, V4, ..., V n .

[0122] Add the squares of each harmonic voltage and calculate the square root to obtain the total harmonic voltage.

[0123] Divide the total harmonic voltage by the fundamental voltage and multiply by 100 to get the total harmonic distortion percentage.

[0124] Record the calculated THD value as a reference indicator for subsequent optimization.

[0125] For the TFT touch screen display unit, perform the following configurations:

[0126] The communication interface between the TFT touch screen and the digital signal processing module is set to ensure that the sound quality parameters and distortion information can be transmitted to the display unit in real time.

[0127] Design user interface layout on TFT touch screen, including:

[0128] Sound quality parameter display area: displays the gain value of each frequency band, filter type and its parameter settings in the initial sound quality parameter combination;

[0129] Distortion display area: displays the calculated distortion percentage (THD value);

[0130] Interactive control area: Provides touch-operated buttons or sliders, allowing users to adjust sound quality parameters.

[0131] The digital signal processing module transmits the generated initial sound quality parameter combination to the TFT touch screen display unit, which displays the gain value and filter settings of each frequency band in real time.

[0132] Display distortion evaluation results: The calculated distortion (THD value) is displayed in the distortion display area for user reference;

[0133] Ensure that changes in sound quality parameters are updated synchronously with distortion calculation results to provide real-time feedback.

[0134] In the above operation steps, the TFT touch screen is chosen to display the initial sound quality parameter combination and distortion after spectrum optimization in real time because the TFT touch screen has high resolution and sensitive touch response capabilities, and can intuitively display complex sound quality parameters and real-time distortion information.

[0135] Step S3: Collecting real-time physiological parameters of the user terminal under different sound quality parameter combinations and distortion levels, and analyzing these data through a deep learning model to generate a sound quality adjustment strategy based on the real-time physiological parameters to adapt to the current initial sound quality parameter combination and distortion level, and obtain an adjusted first-level sound quality parameter combination indicator;

[0136] Further explanation: The connection method between digital audio equipment and wearable devices with physiological parameter monitoring function is as follows:

[0137] Pair and connect the digital audio device with the wearable device via Bluetooth or other wireless communication methods;

[0138] Collect real-time physiological parameters of the user from wearable devices, including heart rate and skin electrical response.

[0139] The collected real-time physiological parameter data is transmitted to the digital audio equipment for subsequent deep learning analysis;

[0140] The real-time physiological parameters include the user's heart rate and skin electrical signals detected by wearable devices;

[0141] Acquisition of sound quality tuning strategies includes:

[0142] The collected real-time physiological parameters are combined with the current initial sound quality parameters and distortion data into the deep learning model;

[0143] The deep learning model loads the pre-trained sound quality parameter combination sample library and distortion optimization sample library to conduct in-depth analysis of the collected user's real-time physiological parameter data, current sound quality parameter combination, and audio distortion data;

[0144] The deep learning model extracts features from the input data and matches the dynamic changing characteristics of the real-time physiological parameters with the current sound quality parameter combination;

[0145] The deep learning model identifies the correlation between the user's real-time physiological parameters and the current sound quality parameter combination, and ultimately generates a sound quality adjustment strategy for adjusting the current initial sound quality parameter combination and optimizing distortion.

[0146] Applying the generated sound quality adjustment strategy to the digital signal processing module to achieve the first-level optimization of the initial sound quality parameter combination and obtain the first-level sound quality parameter combination;

[0147] The specific implementation content of this embodiment is as follows:

[0148] The collected heart rate and skin electrical response data are combined into a real-time physiological parameter data set to ensure the integrity and accuracy of the data;

[0149] Pair each real-time physiological parameter data set with the current initial sound quality parameter combination and its corresponding distortion to form a data pair;

[0150] Ensure that real-time physiological parameter data sets are recorded synchronously with the combination of sound quality parameters and distortion to facilitate accurate analysis by subsequent deep learning models.

[0151] The paired real-time physiological parameter data set is transmitted to the digital audio device via wireless communication, ensuring low latency and high reliability of data transmission.

[0152] A data storage and caching mechanism is established inside the digital audio equipment to temporarily store the received real-time physiological parameter data in preparation for deep learning analysis.

[0153] The initial sound quality parameter combination is expressed as an initial sound quality parameter combination index G;

[0154] The steps for obtaining the initial sound quality parameter combination index G are as follows:

[0155] The normalized spectrum parameter of each frequency band is multiplied by the normalized signal gain parameter to obtain the comprehensive sound quality contribution of the frequency band.

[0156] Take the average value of the comprehensive sound quality contribution of all frequency bands to obtain the current initial sound quality parameter combination index G; the calculation formula is as follows:

[0157]

[0158] Among them, G is the current initial sound quality parameter combination index, the valid range is 0<G≤1; N is the number of frequency bands; F i is the spectrum distribution parameter of the i-th frequency band; F maxIt is the maximum value of the spectrum distribution parameters of all frequency bands and is used for standardization; A i is the signal gain parameter of the i-th frequency band; A max It is the maximum value of the signal gain parameters of all frequency bands and is used for standardization;

[0159] The spectrum distribution parameter F for each frequency band i Normalize by dividing by the maximum value F of the parameter max , ensuring standardized results in within the scope;

[0160] The signal gain parameter A for each frequency band i Normalize by dividing by the maximum value A of the parameter max , ensuring standardized results in within the scope;

[0161] Spectral distribution parameter F i : Indicates the spectrum energy distribution of each frequency band. The higher the value, the stronger the energy of the frequency band.

[0162] Signal gain parameter A i : Indicates the signal gain level of each frequency band. The higher the value, the greater the gain of the frequency band.

[0163] Initial sound quality parameter combination index G: used to comprehensively evaluate the overall sound quality performance of the current initial sound quality parameter combination;

[0164] When G is closer to 1, it means that the optimization status of the current initial sound quality parameter combination in all frequency bands is better;

[0165] When G is closer to 0, it means that the current initial sound quality parameter combination has more room to be optimized in multiple frequency bands;

[0166] The deep learning model loads the pre-trained sound quality parameter combination sample library and distortion optimization sample library to ensure that the model has sufficient learning and matching capabilities;

[0167] Input data preparation: The collected real-time physiological parameter data HR, galvanic skin response SE, the current initial sound quality parameter combination index G and its corresponding distortion data THD are input into the deep learning model to form the model's input layer data structure;

[0168] The deep learning model extracts features from the input data and comprehensively represents the relationship between the real-time physiological parameters and the current initial sound quality parameter combination; the specific formula is as follows:

[0169] P=σ(w1·HR norm +w2·SE norm +w3·G+w4·THD norm );

[0170] Where P is the comprehensive physiological parameter score, ranging from 0 < P < 1; σ is the normalization function, defined as:

[0171]

[0172] w1, w2, w3, w4 are the weight coefficients of the corresponding parameters, and the values ​​of w1, w2, w3, w4 are all in the interval (0, 1), w1 + w2 + w3 + w4 = 1;

[0173] w1 is the heart rate weight coefficient, which indicates the degree of influence of heart rate on the comprehensive score; w2 is the skin electrical response weight coefficient, which indicates the degree of influence of skin electrical response on the comprehensive score; w3 is the sound quality parameter combination weight coefficient, which indicates the degree of influence of the sound quality parameter combination index on the comprehensive score; w4 is the distortion weight coefficient, which indicates the degree of influence of distortion on the comprehensive score;

[0174] HR norm is the normalized value of real-time heart rate data, and the calculation formula is:

[0175]

[0176] Among them, the value range of heart rate HR is HR min ≤HR≤HR max , after standardization 0≤HR norm ≤1. min and max are index marks of lower and upper limits respectively;

[0177] SE norm is the normalized value of real-time skin electrical response data, and the calculation formula is:

[0178]

[0179] Among them, the value range of skin electrical response SE is SE min ≤SE≤SE max , after standardization 0≤SE norm ≤1.

[0180] G is the current initial sound quality parameter combination index;

[0181] THD norm is the normalized value of distortion, which is calculated as:

[0182]

[0183] The value range of the distortion THD is determined by the performance of the equipment. After standardization, 0≤THD norm ≤1.

[0184] Heart rate HR: Heart rate affects the user's mood and physical state. A high heart rate indicates excitement or stress, while a low heart rate indicates relaxation or fatigue.

[0185] Galvanic skin response (SE): The galvanic skin response reflects the user's emotional changes and physiological stress state. A high galvanic skin response indicates anxiety or excitement, while a low galvanic skin response indicates calmness or relaxation.

[0186] Initial sound quality parameter combination index G: Comprehensively evaluates the overall sound quality performance of the current initial sound quality parameter combination. A higher value indicates better sound quality.

[0187] Distortion THD: uses the total harmonic distortion (THD) calculation method to quantify the distortion of the audio signal under optimized parameters. The lower the value, the less distortion in the sound quality.

[0188] Comprehensive physiological parameter score P: used to measure the degree of match between the current initial sound quality parameter combination and the user's physiological state.

[0189] When P is closer to 1, it means that the current initial sound quality parameter combination matches the user's physiological state more closely, and the sound quality optimization effect is more ideal;

[0190] When P is closer to 0, it means that the current initial sound quality parameter combination is less compatible with the user's physiological state;

[0191] The weight coefficients w1, w2, w3, and w4 are determined through experiments based on the pre-training model to reflect the actual impact of each parameter on the comprehensive score;

[0192] The comprehensive physiological parameter score P is used to identify the correlation between the mapping relationship between the real-time physiological parameters and the current initial sound quality parameter combination. The formula for the sound quality adjustment strategy score S is:

[0193]

[0194] Where S is the sound quality adjustment strategy score, ranging from 0 < S < 1; β is the adjustment sensitivity coefficient, reflecting the sensitivity of the adjustment process;

[0195] α is the adjustment amplitude coefficient of the tuning strategy, and α is set to 0<α≤1. The adjustment amplitude coefficient α is used to control the adjustment strength of the tuning strategy to ensure that the adjustment amplitude is within a reasonable range.

[0196] It reflects the relative strength of the comprehensive physiological parameter score P;

[0197] The setting of the logarithmic function can alleviate the impact of extreme values ​​and ensure that the value of S increases smoothly;

[0198] γ is the weight coefficient of the dynamic correlation feature of the input layer parameters, which indicates the influence of the real-time parameters on the sound quality adjustment strategy;

[0199] f(G,THD norm ,HR norm ,SE norm ) A mapping function for dynamically extracting features from the original data of the input layer;

[0200] Mapping function f(G,THD norm ,HR norm ,SE norm ) is used to quantify the dynamic relationship between input layer parameters; the selected function form is based on weighted linear combination or exponential mapping, specifically defined as:

[0201] f(G,THD norm ,HR norm ,SE norm )=w5·|G-THD norm |+w6·HR norm SE norm ;

[0202] w5 reflects the current initial sound quality parameter combination index G and distortion THD norm The influence weight of dynamic differences on sound quality adjustment;

[0203] w6 reflects real-time heart rate HR norm and skin galvanic response SE norm The weight of the interaction on the sound quality adjustment; w5+w6=1;

[0204] |G-THD norm |Used to calculate the initial sound quality parameter combination index G and distortion THD norm The absolute difference between the two parameters indicates the impact of the dynamic changes between the two parameters on the sound quality optimization; it captures the impact of the difference between the initial sound quality parameter combination index G and the distortion on the optimization strategy;

[0205] HR norm SE norm It is the interactive feature of heart rate and skin electrical response, reflecting the contribution of the user's physiological state to sound quality optimization.

[0206] When S is closer to 1, it means that the initial sound quality parameter combination index G needs to be adjusted more;

[0207] When S is closer to 0, it means that the initial sound quality parameter combination index G needs to be adjusted less;

[0208] If G and THD norm The difference increases, f(G,THD norm ,HR norm ,SE norm) increases, resulting in an increase in S, indicating that the distortion needs to be improved;

[0209] If HR norm SE norm An increase indicates that the user's emotions fluctuate greatly, and the sound quality needs to be adjusted to better meet the needs of this state.

[0210] Sound quality tuning strategies include:

[0211] The generated sound quality adjustment strategy score S is applied to the digital signal processing module to adjust the initial sound quality parameter combination index G and distortion THD according to the following formula;

[0212] G′=G+S·ΔG;

[0213] THD′=THD-S·ΔTHD;

[0214] Among them, G′ is the adjusted first-level sound quality parameter combination index, ranging from 0<G′≤1;

[0215] THD′ is the adjusted distortion, and its range is determined by the performance of the device. In this embodiment, 0≤THD′≤THD max ;

[0216] ΔG is the adjustment amplitude of the preset initial sound quality parameter combination index G, and the ΔG range is 0.3≤G≤8.1. It represents the maximum increase in the initial sound quality parameter combination index during each adjustment, ensuring the smoothness of the adjustment process.

[0217] ΔTHD is the preset distortion optimization range, with a ΔTHD range of 0.32≤ΔTHD≤0.65. It represents the maximum distortion optimization range for each adjustment, ensuring the effectiveness of the optimization process.

[0218] According to the sound quality adjustment strategy score S, the current initial sound quality parameter combination index G is adjusted to generate an adjusted first-level sound quality parameter combination index G′;

[0219] According to the sound quality adjustment strategy score S, the current distortion THD is optimized to generate the optimized distortion THD′;

[0220] When G′ increases, it means that the overall sound quality performance of the initial sound quality parameter combination is improved;

[0221] When THD′ decreases, it means that the sound distortion is reduced and the sound quality is purer;

[0222] According to the first-level sound quality parameter combination index G′, the adjusted spectrum distribution parameter F is obtained through the mapping formula i ′ and signal gain parameter A i ′.

[0223] For the spectral distribution parameter F i 'illustrate:

[0224]

[0225] Among them, F i ′ is the adjusted spectrum distribution parameter in the first-level sound quality parameter combination index; F i is the spectrum distribution parameter of the initial sound quality parameter combination index; G′ is the first-level sound quality parameter combination index; G max is the maximum reference value of G′, used for normalization;

[0226] For signal gain parameter adjustment:

[0227]

[0228] Among them, A i ′ is the signal gain parameter after adjustment in the first-level sound quality parameter combination index; A i is the signal gain parameter of the initial sound quality parameter combination index; G ideal It is the target index value required for ideal sound quality performance;

[0229] The adjusted first-level sound quality parameter combination should enter the next round of dynamic adjustment mechanism based on the user's physiological feedback.

[0230] The beneficial effects of the above embodiments are as follows:

[0231] By dynamically matching and identifying the correlation between multi-dimensional physiological parameters such as heart rate and galvanic skin response and the combination indicators and distortion of sound quality parameters, we ensure that the sound quality adjustment is not only based on technical parameters, but also more in line with the user's immediate physiological feedback, thereby improving the user's auditory experience and the level of intelligent application of the device; in addition, the designed mathematical formula realizes the quantitative relationship between the combination of physiological parameters and sound quality parameters through comprehensive physiological parameter scoring and correlation calculation formula, and realizes dynamic optimization of sound quality through comprehensive scoring and sound quality adjustment strategy scores, ensuring the effectiveness and rational design of the formula in real-world technical applications.

[0232] Step S4: responding to the sound quality adjustment strategy and displaying the interactive adjustment interface and the adjusted first-level sound quality parameter combination index through the TFT screen;

[0233] Further explanation: The interactive adjustment interface and the adjusted first-level sound quality parameter combination indicators are displayed on the TFT screen. The specific logic includes:

[0234] Sending the adjusted first-level sound quality parameter combination index to the TFT screen display unit;

[0235] The adjusted spectrum distribution parameter F is displayed in real time on the TFT screen i′ and signal gain parameter A i ';

[0236] The interactive calibration interface includes a display layout of an interactive display interface, including spectrum distribution parameters F i ′ and signal gain parameter A i ′’s distribution diagram and specific values, so that users can intuitively understand the adjusted sound quality parameter information. Specifically including:

[0237] Spectrum distribution curve: Generate the spectrum distribution parameters F of each frequency band through the drawing algorithm i ′’s linear trend graph;

[0238] Signal gain histogram: The signal gain parameter A of each frequency band i ' is drawn as a bar graph;

[0239] The spectrum distribution curve is presented in the center of the interface;

[0240] A signal gain bar graph is displayed at the bottom of the interface.

[0241] Set the TFT screen to dynamic interaction mode, allowing users to interact with the interface content through touch or other operations, including but not limited to: selecting a specific frequency band to view frequency band details.

[0242] Step S5: receiving the operation information adjusted in real time by the user terminal through the TFT screen interactive adjustment interface, and making final adjustments to the first-level sound quality parameter combination index based on the operation information to generate a final optimized second-level sound quality parameter combination index;

[0243] Further explanation: The interactive adjustment interface also includes multiple preset sound quality profiles. The user selects one of the preset sound quality profiles through the TFT screen interactive adjustment interface, and the system receives and confirms the identification information of the selected preset sound quality profile; specific operations:

[0244] The TFT screen displays multiple preset sound quality profiles, including but not limited to "Movie Mode", "Music Mode", and "Game Mode";

[0245] The user selects one of the preset sound quality profiles on the TFT screen through touch operation;

[0246] The control module receives a selection instruction from the user and identifies identification information of the selected preset sound quality configuration file;

[0247] The control module confirms the validity of the selected configuration file and prepares to apply the corresponding sound quality adjustment strategy;

[0248] After receiving the preset sound quality profile identifier selected by the user, the control module calls the corresponding sound quality adjustment strategy parameters and applies them to the first-level sound quality parameter combination index to generate the intermediate-adjusted second-level sound quality parameter combination index; specifically:

[0249] The control module retrieves a pre-stored corresponding sound quality adjustment strategy parameter set according to the identification information of the preset sound quality configuration file; the sound quality adjustment strategy parameter set includes a spectrum distribution parameter and a signal gain parameter;

[0250] The retrieved sound quality adjustment strategy parameters are applied to the current first-level sound quality parameter combination index through the control module to adjust the corresponding spectrum distribution parameters and signal gain parameters.

[0251] Based on the adjusted first-level sound quality parameter combination index, calculate and generate the intermediate second-level sound quality parameter combination index G″ for subsequent optimization;

[0252] Furthermore, based on the application of the preset sound quality profile, the user can fine-tune the first-level sound quality parameter combination indicators through the TFT screen interactive adjustment interface and obtain fine-tuning operation information; specifically, it includes:

[0253] Receive and analyze the user's fine-tuning operation information to further refine and adjust the secondary sound quality parameter combination index or the primary sound quality parameter combination index;

[0254] The TFT screen displays fine-tuning controls for sound quality parameters, such as sliders or knobs, for fine-tuning the sum signal gain parameters of each frequency band;

[0255] The user increases or decreases the spectrum distribution parameters and signal gain parameters of a specific frequency band through touch operations.

[0256] The control module receives the user's fine-tuning operation instructions and analyzes the specific adjustment range and target parameters;

[0257] The control module verifies whether the received fine-tuning instruction is within the allowable adjustment range to ensure the effectiveness and safety of the parameter adjustment.

[0258] After receiving the user's fine-tuning operation information, the control module adjusts the first-level sound quality parameter combination index, finally generates an optimized second-level sound quality parameter combination index, and updates the system's sound quality adjustment status.

[0259] Step S6: The secondary sound quality parameter combination index is used to adjust the audio signal gain and spectrum distribution of the digital audio device, and the adjustment result of the sound quality parameter combination is displayed on the TFT screen.

[0260] Further explanation: receiving and storing the generated final optimized secondary sound quality parameter combination index G″ as the basic data for subsequent adjustment of the audio signal gain parameter and spectrum distribution parameter; specific steps:

[0261] The control module transmits the final optimized secondary sound quality parameter combination index to the sound quality adjustment module through the internal communication interface;

[0262] Data reception and storage: The sound quality adjustment module receives the transmitted secondary sound quality parameter combination index and stores it in the internal memory in preparation for subsequent sound quality adjustment operations;

[0263] Verify data integrity: The sound quality adjustment module performs integrity verification on the received secondary sound quality parameter combination indicators to ensure that the data is not lost or damaged during transmission.

[0264] Based on the received secondary sound quality parameter combination index, adjust the audio signal gain parameter of the digital audio device to achieve a preset sound quality optimization effect; specific steps:

[0265] Signal gain parameter extraction: extract the signal gain adjustment value corresponding to each frequency band from the stored secondary sound quality parameter combination index;

[0266] Signal gain parameter calculation: Calculate the specific gain adjustment amount for each frequency band based on the extracted signal gain adjustment value. The formula is as follows:

[0267]

[0268] Among them, A i ″ is the signal gain parameter in the secondary sound quality parameter combination index, A i ′ is the signal gain parameter in the first-level sound quality parameter combination index, and k is the adjustment coefficient, which is used to control the gain adjustment amplitude.

[0269] Signal gain application: The calculated A i The gain control module used in the audio decoder adjusts the signal gain parameters of each frequency band to optimize the sound quality.

[0270] Signal gain parameter adjustment confirmation: The sound quality adjustment module confirms that the signal gain parameter has been successfully applied and records the adjusted signal gain parameter value for subsequent use.

[0271] Based on the received secondary sound quality parameter combination index, the spectrum distribution parameters of the digital audio device are adjusted to achieve a preset sound quality optimization effect; specific steps:

[0272] Spectrum distribution parameter extraction: extract the spectrum distribution adjustment value corresponding to each frequency band from the stored secondary sound quality parameter combination index;

[0273] Spectrum distribution parameter calculation: Based on the extracted spectrum distribution parameters, calculate the specific spectrum distribution adjustment amount for each frequency band. The formula is as follows:

[0274]

[0275] Among them, F i ′ is the spectrum distribution parameter in the first-level sound quality parameter combination index, F i ″ is the spectrum distribution parameter in the secondary sound quality parameter combination index, and m is the adjustment coefficient, which is used to control the adjustment amplitude of the spectrum distribution;

[0276] The calculated F i The spectrum adjustment function applied to the audio signal processing module adjusts the spectrum distribution parameters of each frequency band to optimize the sound quality performance;

[0277] The sound quality adjustment module confirms that the spectrum distribution parameters have been successfully applied and records the adjusted spectrum distribution parameter values ​​for subsequent use.

[0278] Based on the adjusted audio signal gain parameters and spectrum distribution parameters, the adjustment result data is generated and sent to the TFT screen display module through the communication interface to display the adjusted sound quality parameter combination results on the display interface; specific steps:

[0279] The signal gain parameter A after integration adjustment i ″ and spectrum distribution parameter F i ″, forming a complete adjustment result data set.

[0280] The adjustment result data set is encoded and converted into a format suitable for the TFT screen display module, such as JSON or binary data packet.

[0281] The encoded adjustment result data packet is sent to the TFT screen display module through the internal communication interface.

[0282] The sound quality adjustment module waits for and receives a confirmation signal from the TFT screen display module to ensure that the adjustment result data has been successfully transmitted.

[0283] The TFT screen display module receives the adjustment result data sent, and displays the adjusted signal gain parameter A through the display driver. i ″ and spectrum distribution parameter F i "The data is displayed in real time on the TFT screen in graphical and numerical form for users to view. Specific steps:

[0284] The TFT screen display module receives the adjustment result data packet from the sound quality adjustment module and decodes and extracts the A i ″ and F i ″.

[0285] Interface update preparation: Based on the parsed parameters, prepare to update the specific content of the display interface, including the numerical display of signal gain and the graphical display of spectrum distribution.

[0286] Graphical display generation: Through the graphics processing algorithm, F i Generate a spectrum distribution curve and i Generates a signal gain histogram.

[0287] Updated the TFT screen display interface to show the adjusted sound quality parameter combination results, including:

[0288] Display the final optimized secondary sound quality parameter combination index;

[0289] Spectrum distribution curve; signal gain histogram;

[0290] The TFT screen display module confirms that the page has been successfully updated and feeds back a completion signal to the sound quality adjustment module, ending the operation process of step S6.

[0291] It should be noted that: All calculation formulas in this application document use regression analysis including but not limited to machine learning algorithms to deeply analyze the relevant parameters collected and identify their natural trends and relationships. Use professional software, such as Python's Scikit-learn library or R language, to automatically generate mathematical models that match the data. Then, objectively evaluate the performance of the model through methods such as cross-validation, and combine continuous feedback and optimization to ensure that the created formula truly reflects the inherent laws of the data, thereby ensuring its effectiveness and accuracy. In all calculation formulas in this application, the parameters in each formula are dimensionally non-dimensionalized within a consistent range to ensure that different physical quantities are compared on the same scale; dimensionless technical means include but are not limited to Min-Max Normalization and Z-Score standardization;

[0292] The technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0293] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0294] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0295] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A sound quality adjustment method combining vacuum tube and TFT screen display, characterized in that: The specific steps include: Obtaining spectrum optimization information of the vacuum tube module on the input audio signal at the current moment to obtain an initial sound quality parameter combination; Responding to the spectrum optimization information, the TFT screen is used to display in real time the initial sound quality parameter combination after spectrum optimization, and the distortion degree evaluated after adjustment based on the initial sound quality parameter combination; Collect real-time physiological parameters of the user end under different sound quality parameter combinations and distortion levels, and analyze these data through a deep learning model to generate a sound quality adjustment strategy based on the real-time physiological parameters to adapt to the current initial sound quality parameter combination and distortion level, and obtain the adjusted first-level sound quality parameter combination index; The real-time physiological parameters include the user's heart rate and skin electrical signals detected by wearable devices; Acquisition of sound quality tuning strategies includes: The collected real-time physiological parameters are combined with the current initial sound quality parameters and distortion data into the deep learning model; The deep learning model loads the pre-trained sound quality parameter combination sample library and distortion optimization sample library to conduct in-depth analysis of the collected user's real-time physiological parameter data, current sound quality parameter combination, and audio distortion data; The deep learning model extracts features from the input data and matches the dynamic changing characteristics of the real-time physiological parameters with the current sound quality parameter combination; The deep learning model identifies the correlation between the user's real-time physiological parameters and the current sound quality parameter combination, and ultimately generates a sound quality adjustment strategy for adjusting the current initial sound quality parameter combination and optimizing distortion. Applying the generated sound quality adjustment strategy to the digital signal processing module to achieve the first-level optimization of the initial sound quality parameter combination and obtain the first-level sound quality parameter combination; The initial sound quality parameter combination is expressed as an initial sound quality parameter combination index G; The steps for obtaining the initial sound quality parameter combination index G are as follows: Multiply the normalized spectrum parameter of each frequency band by the normalized signal gain parameter to obtain the comprehensive sound quality contribution of the frequency band; Take the average value of the comprehensive sound quality contribution of all frequency bands to obtain the current initial sound quality parameter combination index G; The deep learning model extracts features from the input data and comprehensively represents the relationship between the real-time physiological parameters and the current initial sound quality parameter combination; the specific formula is as follows: ； in, It is a comprehensive physiological parameter score, with a range of ; is the normalization function, is the weight coefficient of the corresponding parameter, and The values ​​are all in the interval (0,1). ; is the normalized value of real-time heart rate data, is the normalized value of real-time skin electrical response data, is the distortion normalized value; When P is closer to 1, it means that the current initial sound quality parameter combination matches the user's physiological state more closely, and the sound quality optimization effect is more ideal; When P is closer to 0, it means that the current initial sound quality parameter combination is less compatible with the user's physiological state; Respond to the sound quality adjustment strategy and display the interactive adjustment interface and the adjusted first-level sound quality parameter combination indicators through the TFT screen; Receive the operation information adjusted in real time by the user through the interactive adjustment interface of the TFT screen, and make final adjustments to the first-level sound quality parameter combination index based on the operation information to generate the final optimized second-level sound quality parameter combination index; The secondary sound quality parameter combination index is used to adjust the audio signal gain and spectrum distribution of the digital audio equipment, and the adjustment result of the sound quality parameter combination is displayed on the TFT screen.

2. The sound quality adjustment method combining vacuum tube and TFT display according to claim 1, characterized in that: The objects of spectrum optimization information include spectrum distribution parameters and signal gain parameters; The vacuum tube module includes a dynamic operating temperature monitoring unit, which is used to monitor the temperature changes of the vacuum tube in real time and trigger corresponding graded warnings. Different levels of warnings trigger optimization strategies for the following spectrum distribution parameters and signal gain parameters: Set at least two temperature warning values ​​for different levels of temperature warnings, specifically: When the temperature of the vacuum tube is within the range of two temperature warning values, the first level warning is activated; Level 1 warning includes: Start the spectrum distribution parameter optimization module to perform softening processing on the high frequency band: adjust the spectrum distribution parameters of the high frequency band and reduce the gain of the high frequency signal; When the temperature of the vacuum tube is above the maximum temperature warning value, the second level warning is activated; Level 2 warnings include: Start the signal gain parameter optimization module and adjust the amplitude of the signal gain parameters of each frequency band: reduce the amplitude of the signal gain parameters; The initially optimized spectrum distribution parameters and signal gain parameters are expressed as an initial sound quality parameter combination; receiving initially optimized spectrum distribution parameters and signal gain parameters; Through the digital signal processing module, the input audio signal is initially optimized by corresponding high-frequency softening or signal gain adjustment.

3. The sound quality adjustment method combining vacuum tube and TFT display according to claim 2, characterized in that: Characterize each frequency band into a low frequency band, a mid frequency band, and a high frequency band; The high-power driving frequency band in the high-frequency band is set to 4kHz-6kHz, and the secondary warning signal is used to reduce the signal gain parameter by 10% in the high-power driving frequency band.

4. The sound quality adjustment method combining vacuum tube and TFT display according to claim 3, characterized in that: The TFT screen is a touch screen, which outputs the audio signal that has undergone initial optimization processing to the TFT screen display unit through the digital signal processing module, thereby realizing the real-time display of the sound quality adjustment effect. The sound quality adjustment effect display includes displaying the sound quality parameter combination and distortion after spectrum optimization; The total harmonic distortion calculation method is used to quantify the distortion of the audio signal under the optimized parameters; and the distortion is recorded as .

5. The sound quality adjustment method combining vacuum tube and TFT display according to claim 4, characterized in that: The comprehensive physiological parameter score P is used to identify the correlation between the mapping relationship between the real-time physiological parameters and the current initial sound quality parameter combination; ； Among them, S is the sound quality adjustment strategy score, the range is ; is the adjustment sensitivity coefficient, which reflects the sensitivity of the adjustment process; is the adjustment coefficient of the tuning strategy, Pick ; is the weight coefficient of the dynamic correlation feature of the input layer parameters, A mapping function that dynamically extracts features from the raw data of the input layer. When S approaches 1, the greater the adjustment of the initial sound quality parameter combination index G needs to be. When S is closer to 0, it means that the initial sound quality parameter combination index G needs to be adjusted less; Sound quality tuning strategies include: The generated sound quality adjustment strategy score S is applied to the digital signal processing module to adjust the initial sound quality parameter combination index G and distortion THD according to the following formula; ； ； in, It is the adjusted first-level sound quality parameter combination index, the range is ; is the adjusted distortion, It is the adjustment range of the preset initial sound quality parameter combination index G. is the preset distortion optimization range. When it increases, it means that the overall sound quality performance of the initial sound quality parameter combination is improved; when When it decreases, it means that the degree of sound distortion is reduced and the sound quality is purer; According to the first-level sound quality parameter combination index , the adjusted spectrum distribution parameters are obtained through the mapping formula Sum signal gain parameter .

6. The sound quality adjustment method combining vacuum tube and TFT display according to claim 5, characterized in that: The TFT screen displays an interactive tuning interface and the adjusted first-level sound quality parameter combination indicators. The specific logic includes: Sending the adjusted first-level sound quality parameter combination index to the TFT screen display unit; The adjusted spectrum distribution parameters are displayed in real time on the TFT screen Sum signal gain parameter ; The interactive adjustment interface includes a display layout of the interactive display interface, including spectrum distribution parameters Sum signal gain parameter distribution diagram and specific values.

7. The sound quality adjustment method combining vacuum tube and TFT display according to claim 6, characterized in that: The interactive adjustment interface also includes a plurality of preset sound quality profiles. The user selects one of the preset sound quality profiles through the TFT screen interactive adjustment interface, and the system receives and confirms the identification information of the selected preset sound quality profile; Receiving a preset sound quality profile identifier selected by a user, the control module calls the corresponding sound quality adjustment strategy parameters and applies them to the first-level sound quality parameter combination index to generate an intermediate-adjusted second-level sound quality parameter combination index; Based on the preset sound quality profile, users can fine-tune the first-level sound quality parameter combination indicators through the interactive adjustment interface on the TFT screen and obtain fine-tuning operation information; After receiving the user's fine-tuning operation information, the control module adjusts the first-level sound quality parameter combination index, finally generates an optimized second-level sound quality parameter combination index, and updates the system's sound quality adjustment status.

8. The sound quality adjustment method combining vacuum tube and TFT display according to claim 7, characterized in that: Receive and store the generated final optimized secondary sound quality parameter combination index , which serves as the basic data for subsequent adjustment of audio signal gain parameters and spectrum distribution parameters; Based on the received secondary sound quality parameter combination index, the audio signal gain parameter of the digital audio device is adjusted, and the signal gain parameter in the secondary sound quality parameter combination index is set to ; adjusting spectrum distribution parameters of the digital audio device based on the received secondary sound quality parameter combination index; Set the spectrum distribution parameter in the secondary sound quality parameter combination index to ; Based on the adjusted audio signal gain parameters and spectrum distribution parameters, adjustment result data is generated and sent to the TFT screen display module through the communication interface to present the adjusted sound quality parameter combination results on the display interface; The TFT screen display module receives the adjustment result data sent, and displays the signal gain parameter in the secondary sound quality parameter combination index through the display driver. and spectrum distribution parameters The data is displayed in real time on the TFT screen in graphical and numerical form for users to view.

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