Signal noise reduction and power supply optimization method for earphone internal circuit

Abstract

The invention discloses a signal noise reduction and power supply optimization method for an earphone internal circuit, and the method comprises the core steps: collecting a real-time power supply voltage, a real-time interference signal frequency, a real-time circuit temperature and a real-time load resistance based on a synchronous collection time sequence control logic, correcting a reference noise reduction coefficient based on a parameter coupling effect, and obtaining a dynamic noise reduction coefficient; and adjusting the reference power supply current based on the dynamic noise reduction coefficient and the real-time load resistance to obtain a self-adaptive power supply current, and calculating a noise reduction-power supply comprehensive performance index based on the dynamic noise reduction coefficient and the self-adaptive power supply efficiency. According to the method, through synchronous acquisition and multi-parameter coupling linkage adjustment, the core problem of independent optimization of noise reduction and power supply in the prior art is solved, collaborative adaptation of noise reduction and power supply is realized, and the operation stability of an earphone circuit is improved.

Description

Technical Field

[0001] This invention relates to the field of headphone electronic circuit technology, specifically to a method for signal noise reduction and power supply optimization of the internal circuit of a headphone. Background Technology

[0002] In current headphone internal circuit designs, noise cancellation and power supply modules often employ independent control logic, with a fixed noise reduction coefficient and power supply current matched only to fixed load requirements. When headphones are under complex conditions such as low battery, strong interference, or temperature fluctuations, the fixed noise reduction coefficient cannot adapt to the performance degradation of the noise cancellation module caused by power supply voltage fluctuations. Simultaneously, the fixed power supply current cannot match the load changes after adjusting the noise reduction coefficient, leading to a sharp drop in noise cancellation effectiveness or increased power supply redundancy losses. This problem stems from the lack of a linkage optimization mechanism between noise cancellation and power supply in existing technologies, making it impossible to achieve coordinated adaptation under multiple operating conditions. This has become a key bottleneck affecting the operational stability of headphones under complex conditions.

[0003] Based on the above problems, there is an urgent need for a technical solution that can achieve coordinated optimization of noise reduction and power supply. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and to propose a method for signal noise reduction and power supply optimization of the internal circuit of headphones, comprising the following steps: S1: Based on synchronous acquisition timing control logic, collect the real-time power supply voltage, real-time interference signal frequency, real-time circuit temperature and real-time load resistance of the internal circuit of the earphone. S2: Based on the coupling effect of real-time power supply voltage, real-time interference signal frequency, and real-time circuit temperature, the reference noise reduction coefficient is corrected to obtain the dynamic noise reduction coefficient; S3: Based on the dynamic noise reduction coefficient and real-time load resistance, the reference supply current is adjusted to obtain the adaptive supply current; S4: Calculate the comprehensive performance index of noise reduction and power supply based on the dynamic noise reduction coefficient and the power supply efficiency corresponding to adaptive power supply.

[0005] Preferably, the synchronous acquisition timing control logic in step S1 specifically involves setting the acquisition trigger timestamps for the voltage acquisition unit, frequency acquisition unit, temperature acquisition unit, and resistance acquisition unit. Each acquisition unit triggers the acquisition action at the same timestamp, and after the acquisition is completed, the data is transmitted to the main control unit.

[0006] In a further preferred embodiment, the dynamic noise reduction coefficient is obtained by correcting the reference noise reduction coefficient based on the coupling effect of real-time power supply voltage, real-time interference signal frequency, and real-time circuit temperature in step S2. Specifically, the following steps are taken: a rated power supply voltage, a reference interference signal frequency, a reference circuit temperature, a voltage sensitivity coefficient, a frequency sensitivity coefficient, and a temperature sensitivity coefficient are set. A power supply voltage correction factor is obtained by combining the ratio of real-time power supply voltage to rated power supply voltage with the voltage sensitivity coefficient. An interference frequency correction factor is obtained by combining the ratio of real-time interference signal frequency to reference interference signal frequency with the frequency sensitivity coefficient. A circuit temperature correction factor is obtained by combining the difference between real-time circuit temperature and reference circuit temperature with the temperature sensitivity coefficient. The dynamic noise reduction coefficient is obtained by multiplying the power supply voltage correction factor, interference frequency correction factor, circuit temperature correction factor, and reference noise reduction coefficient.

[0007] In a further preferred embodiment, step S3, which adjusts the reference power supply current based on the dynamic noise reduction coefficient and the real-time load resistance to obtain the adaptive power supply current, specifically involves: setting the reference load resistance and the load sensitivity coefficient; obtaining the load correction factor by combining the ratio of the real-time load resistance to the reference load resistance with the load sensitivity coefficient; and obtaining the adaptive power supply current by multiplying the ratio of the dynamic noise reduction coefficient to the reference noise reduction coefficient, the load correction factor, and the reference power supply current.

[0008] More preferably, the dynamic noise reduction coefficient is calculated by a dynamic noise reduction coefficient correction formula, which is associated with the power supply voltage correction factor, interference frequency correction factor, circuit temperature correction factor and reference noise reduction coefficient, to achieve dynamic correction of the noise reduction coefficient under multi-parameter coupling.

[0009] More preferably, the adaptive power supply current is calculated by the adaptive adjustment formula of the power supply current, which is related to the ratio of the dynamic noise reduction coefficient to the reference noise reduction coefficient, the load correction factor and the reference power supply current, so as to realize the adaptive adjustment of the power supply current based on the noise reduction requirements.

[0010] In a further preferred embodiment, the noise reduction-power supply integrated performance index is calculated using a noise reduction-power supply integrated performance quantification formula. This formula is related to the ratio of the dynamic noise reduction coefficient to the adaptive power supply efficiency relative to the benchmark power supply efficiency, thereby achieving synergistic quantification of noise reduction effect and power supply efficiency.

[0011] Further preferred, the values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient are obtained through experimental calibration. Specifically, the calibration method is as follows: under different combinations of power supply voltage, different interference signal frequency, and different circuit temperature, the corresponding noise reduction coefficient change is measured. Based on the ratio relationship between the noise reduction coefficient change and the power supply voltage change rate, the interference signal frequency change rate, and the circuit temperature change value, the calibration values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient are determined.

[0012] In a further preferred embodiment, the load sensitivity coefficient is obtained through experimental calibration. Specifically, the calibration method is as follows: under different load resistance conditions, the corresponding power supply current adjustment is tested and obtained. Based on the ratio of the power supply current adjustment to the load resistance change rate, the calibration value of the load sensitivity coefficient is determined.

[0013] A further preferred embodiment includes step S5: comparing the noise reduction-power supply comprehensive performance index with a preset performance threshold. If the noise reduction-power supply comprehensive performance index does not reach the preset performance threshold, the values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, temperature sensitivity coefficient, and load sensitivity coefficient are adjusted, and steps S2 to S4 are repeated until the noise reduction-power supply comprehensive performance index reaches the preset performance threshold. The preset performance threshold is determined by experimental calibration.

[0014] Technical effects: This invention achieves precise synchronous acquisition of multiple parameters through synchronous acquisition timing control logic, corrects the noise reduction coefficient based on the coupling effect of multiple parameters, and establishes a linkage adjustment mechanism between noise reduction and power supply. It accurately solves the core problem of poor adaptability to complex working conditions caused by independent control of noise reduction and power supply in the background technology, realizes the coordinated adaptation of noise reduction effect and power supply efficiency, and ensures the stability of headphone operation under complex working conditions. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the signal noise reduction and power supply optimization method for the internal circuitry of the earphone in this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] In existing technologies, the noise reduction module and power supply module in the internal circuit of headphones generally adopt independent control mode, and no effective linkage optimization mechanism is established between the two. When the headphones are in a complex working condition where the power supply voltage fluctuates due to low power and the interference signal frequency is highly variable, or the circuit temperature rises after long-term operation, the fixed noise reduction coefficient cannot adapt to the performance degradation of the noise reduction module caused by the power supply voltage fluctuation. At the same time, the fixed power supply current cannot match the dynamic changes of the load after the noise reduction coefficient is adjusted. Ultimately, this leads to a significant decrease in noise reduction effect or a significant increase in power supply redundancy loss, which seriously affects the operating stability of the headphones under complex working conditions.

[0018] Based on this, please refer to Figure 1 This embodiment provides a method for signal noise reduction and power supply optimization of the internal circuit of an earphone, including the following steps: S1: Based on synchronous acquisition timing control logic, collect the real-time power supply voltage, real-time interference signal frequency, real-time circuit temperature and real-time load resistance of the internal circuit of the earphone. S2: Based on the coupling effect of real-time power supply voltage, real-time interference signal frequency, and real-time circuit temperature, the reference noise reduction coefficient is corrected to obtain the dynamic noise reduction coefficient; S3: Based on the dynamic noise reduction coefficient and real-time load resistance, the reference supply current is adjusted to obtain the adaptive supply current; S4: Calculate the comprehensive performance index of noise reduction and power supply based on the dynamic noise reduction coefficient and the power supply efficiency corresponding to adaptive power supply.

[0019] The core innovation of this technical solution lies in constructing a complete logic chain encompassing synchronous parameter acquisition, multi-parameter coupling noise reduction and correction, noise reduction, power supply linkage adjustment, and comprehensive performance quantification. Through the close connection and synergistic effect of each link, it breaks down the barriers of independent noise reduction and power supply control in traditional technologies. Specifically, the synchronous acquisition timing control logic is the fundamental prerequisite for ensuring the accuracy of subsequent multi-parameter coupling correction. Its implementation logic involves the main control unit generating a high-precision clock signal, which is then transmitted to four independent acquisition modules: voltage acquisition unit, frequency acquisition unit, temperature acquisition unit, and resistance acquisition unit. A fixed acquisition trigger timestamp is set within each preset acquisition cycle. When the clock signal reaches the time corresponding to that timestamp, the four acquisition units simultaneously initiate the acquisition action. This synchronous triggering mechanism ensures that the four key parameters—real-time power supply voltage, real-time interference signal frequency, real-time circuit temperature, and real-time load resistance—are acquired in the same time dimension, effectively avoiding errors caused by parameter mismatch with actual operating conditions due to differences in acquisition timing. This provides a precise and synchronous data foundation for subsequent multi-parameter coupling correction.

[0020] The multi-parameter coupling correction stage breaks through the limitations of traditional technologies that only correct the noise reduction coefficient for a single parameter. It fully considers the combined impact of three key factors—supply voltage fluctuations, interference signal frequency changes, and circuit temperature drift—on noise reduction performance. In actual headphone operation, these three factors often coexist and influence each other. Single-parameter correction cannot achieve accurate adaptation of the noise reduction coefficient to complex operating conditions. This solution, by constructing a multi-dimensional coupling correction logic, enables the noise reduction coefficient to dynamically adjust according to changes in operating conditions, ensuring the stability of the noise reduction effect.

[0021] The noise reduction-power supply linkage adjustment mechanism is the core element for achieving synergistic optimization. This mechanism breaks down the control barriers between the noise reduction module and the power supply module, enabling the power supply current to adaptively change according to the adjustment of the dynamic noise reduction coefficient. When the dynamic noise reduction coefficient increases, it means that the computational load of the noise reduction module increases, and the load demand increases. At this time, the power supply current can be increased synchronously to meet the load demand. When the dynamic noise reduction coefficient decreases, the power supply current also decreases accordingly, avoiding unnecessary power supply redundancy losses and achieving a synergistic balance between noise reduction effect and power supply efficiency.

[0022] The comprehensive performance quantification step provides a clear basis for evaluating the effectiveness of the entire optimization scheme. By integrating and quantifying the two core indicators of dynamic noise reduction coefficient and power supply efficiency, a comprehensive noise reduction-power supply performance index is formed. This index can intuitively reflect the synergistic optimization effect of noise reduction and power supply under the current operating conditions, providing a clear judgment standard for possible subsequent closed-loop adjustments. Through the organic combination of each step, the entire technical solution forms a complete synergistic optimization system, which can effectively cope with various challenges under complex operating conditions and ensure the stable operation of the headphone circuit.

[0023] In existing technologies, when collecting multiple key parameters of the internal circuitry of headphones, each acquisition unit often employs an independent trigger timing sequence, resulting in differences in the acquisition time for different parameters. However, the operating conditions of the internal circuitry of headphones are dynamically changing; parameters such as power supply voltage and interference signal frequency may fluctuate within a very short time. This asynchrony in acquisition timing leads to the acquired parameters not accurately corresponding to the same operating condition, resulting in parameter matching errors. These errors are directly transmitted to subsequent optimization calculations, causing problems such as inaccurate noise reduction coefficient correction and power supply current adjustment deviations, ultimately affecting the accuracy of the entire optimization scheme.

[0024] Based on this, the synchronous acquisition timing control logic in step S1 is as follows: set the acquisition trigger timestamps for the voltage acquisition unit, frequency acquisition unit, temperature acquisition unit, and resistance acquisition unit, and each acquisition unit triggers the acquisition action at the same timestamp. After the acquisition is completed, the data is transmitted to the main control unit.

[0025] The core of this technical solution lies in achieving synchronous triggering of multiple acquisition units through a unified timestamp, ensuring the time consistency of the acquired parameters. In the specific implementation, the main control unit uses a high-precision microcontroller with an integrated clock generator capable of generating a clock signal with extremely high frequency stability. The frequency accuracy of this clock signal can reach the 10^-6 level, ensuring the accuracy of the timestamp setting. The main control unit transmits the preset acquisition trigger timestamp information to the four acquisition units via the I2C bus. Each acquisition unit has an internal timestamp comparator used to compare its local clock with the trigger timestamp sent by the main control unit in real time.

[0026] When the local clock of the acquisition unit reaches the time corresponding to the trigger timestamp, the timestamp comparator immediately outputs a trigger signal. This trigger signal will activate the analog-to-digital converter or signal detection module inside the acquisition unit to begin acquiring the target parameters. For the voltage acquisition unit, it integrates a high-precision operational amplifier and a 16-bit analog-to-digital converter, enabling accurate sampling of the supply voltage. The frequency acquisition unit filters and amplifies interference signals through a signal conditioning circuit, and then uses a frequency counter to acquire the frequency. The temperature acquisition unit uses an integrated temperature sensor, converting the resistance change of a thermistor into a voltage signal for acquisition. The resistance acquisition unit calculates the load resistance value by combining constant current source excitation with voltage sampling.

[0027] After the four acquisition units start acquiring data at the same timestamp, they will complete data acquisition within a preset sampling duration. The sampling duration is set to 10 microseconds based on the parameter variation characteristics to ensure that the acquired data accurately reflects the instantaneous values ​​of the parameters. After acquisition, each acquisition unit synchronously transmits the acquired digital signals to the main control unit via a parallel data bus. This parallel data transmission method ensures the synchronization of data transmission and avoids delay differences during data transmission. After receiving all acquired data, the main control unit performs a preliminary validity check on the data, eliminating invalid data caused by acquisition anomalies, ensuring the reliability of the data used for subsequent optimization calculations. Through this synchronous acquisition timing control logic, the time difference in parameter acquisition can be effectively eliminated, parameter matching errors can be avoided, and a solid data foundation can be provided for subsequent accurate optimization calculations.

[0028] In existing technologies, most corrections to headphone noise reduction coefficients only consider the influence of a single parameter, such as adjusting the coefficient based solely on changes in the power supply voltage. However, in real-world applications, the operating conditions of the headphone's internal circuitry are complex and variable. Multiple factors, such as power supply voltage fluctuations, changes in interference signal frequency, and circuit temperature drift, simultaneously affect the noise reduction module. Correcting a single parameter cannot fully reflect the combined impact of these factors. This one-sided approach leads to a mismatch between the noise reduction coefficient and actual operating conditions. When multiple factors change significantly simultaneously, the noise reduction effect deteriorates significantly, failing to meet users' sound quality requirements.

[0029] Based on this, in step S2, the dynamic noise reduction coefficient is obtained by correcting the reference noise reduction coefficient based on the coupling effect of real-time power supply voltage, real-time interference signal frequency, and real-time circuit temperature. Specifically, the rated power supply voltage, reference interference signal frequency, reference circuit temperature, voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient are set. The power supply voltage correction factor is obtained by combining the ratio of real-time power supply voltage to rated power supply voltage with the voltage sensitivity coefficient. The interference frequency correction factor is obtained by combining the ratio of real-time interference signal frequency to reference interference signal frequency with the frequency sensitivity coefficient. The circuit temperature correction factor is obtained by combining the difference between real-time circuit temperature and reference circuit temperature with the temperature sensitivity coefficient. The dynamic noise reduction coefficient is obtained by multiplying the power supply voltage correction factor, interference frequency correction factor, circuit temperature correction factor, and reference noise reduction coefficient.

[0030] This technical solution achieves precise correction of the noise reduction coefficient by constructing a multi-parameter, multi-dimensional, and holistically coupled correction logic. In the specific implementation process, the rated power supply voltage, reference interference signal frequency, and reference circuit temperature were all determined experimentally under the standard operating conditions of the headphones. The standard operating conditions were set as a power supply voltage of 3.7 volts, an ambient interference signal frequency of 1 kHz, and a circuit temperature of 25 degrees Celsius. Under these conditions, the noise reduction coefficient corresponding to the optimal noise reduction effect of the headphones was obtained through testing with professional audio testing equipment, and this coefficient was set as the reference noise reduction coefficient.

[0031] The voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient were obtained through extensive orthogonal experiments. These experiments selected three factors: supply voltage, interference signal frequency, and circuit temperature, with five levels for each factor, resulting in 25 sets of experiments. In each set of experiments, the change in noise reduction coefficient under different parameter combinations was tested. The experimental data was fitted using the least squares method to obtain the linear relationship between the change in each parameter and the change in the noise reduction coefficient, thus determining the values ​​of each sensitivity coefficient. For example, when calibrating the voltage sensitivity coefficient, the interference signal frequency and circuit temperature were fixed as baseline values. The supply voltage was varied, and the corresponding change in the noise reduction coefficient was tested. The voltage sensitivity coefficient was obtained through fitting, and this coefficient can accurately quantify the percentage change in the noise reduction coefficient for every 1% change in supply voltage.

[0032] In the actual noise reduction coefficient correction, the ratio of the real-time supply voltage to the rated supply voltage is first calculated. This ratio is then substituted into a preset voltage correction formula, and combined with a voltage sensitivity coefficient, a supply voltage correction factor is obtained. Similarly, the ratio of the real-time interference signal frequency to the reference interference signal frequency is calculated, and combined with a frequency sensitivity coefficient, an interference frequency correction factor is obtained. The difference between the real-time circuit temperature and the reference circuit temperature is calculated, and combined with a temperature sensitivity coefficient, a circuit temperature correction factor is obtained. Finally, these three correction factors are multiplied with the reference noise reduction coefficient to obtain the dynamic noise reduction coefficient. This multi-parameter coupled correction method comprehensively considers the impact of various factors on noise reduction performance, enabling the dynamic noise reduction coefficient to accurately adapt to the current complex operating conditions and ensuring the stability of the noise reduction effect.

[0033] When calculating the dynamic noise reduction coefficient, a dynamic noise reduction coefficient correction formula is used, which is specifically as follows:

[0034] The theoretical design of this formula stems from an in-depth analysis of the operating characteristics of the noise reduction module. The core components of the noise reduction module are the operational amplifier and the filter circuit, and its noise reduction performance is closely related to the supply voltage, operating temperature, and input signal frequency. From a circuit theory perspective, the open-loop gain of the operational amplifier is positively correlated with the supply voltage. When the supply voltage decreases, the open-loop gain of the operational amplifier will decrease, leading to a reduction in the noise reduction module's ability to suppress noise signals. Therefore, it is necessary to compensate for this performance degradation by adjusting the noise reduction coefficient. The frequency of the interference signal affects the noise reduction effect of the filter circuit. The filter circuit has different attenuation characteristics for signals of different frequencies. When the frequency of the interference signal exceeds the reference frequency, the noise reduction effect of the filter circuit will weaken, requiring an increase in the noise reduction coefficient to enhance the suppression capability for high-frequency interference. Temperature changes cause the parameters of internal components to drift. For example, the parameters of resistors and capacitors change with temperature, thus affecting the cutoff frequency and gain of the filter circuit, leading to a decrease in noise reduction performance. Therefore, it is also necessary to compensate for the effects of temperature drift by adjusting the noise reduction coefficient.

[0035] Based on the above theoretical analysis, the formula uses three correction terms to quantify and correct the effects of the supply voltage, interference signal frequency, and circuit temperature. Used to quantify the degree of attenuation of the supply voltage, when the real-time supply voltage... Lower than the rated supply voltage When this difference is positive, it is compared with the voltage sensitivity coefficient. Multiplying these values ​​yields the voltage correction factor for the noise reduction coefficient. A positive correction factor indicates that the noise reduction coefficient needs to be increased to compensate for the performance degradation caused by voltage attenuation. Used to quantify the extent to which the frequency of the interference signal exceeds a reference value, when the real-time interference signal frequency... Higher than the reference interference signal frequency When this difference is positive, it is combined with the frequency sensitivity coefficient. Once the frequency correction is obtained, the noise reduction coefficient also needs to be increased to enhance the suppression of high-frequency interference. Used to quantify the temperature drift of the circuit, when the real-time circuit temperature... Temperature higher than the reference circuit When this difference is positive, it is compared with the temperature sensitivity coefficient. Multiplying these values ​​yields a temperature correction, which increases the noise reduction coefficient to compensate for performance loss caused by temperature drift. Each correction term uses the form of 1 + correction amount to ensure that the correction factor is a relative ratio to the baseline noise reduction coefficient. The dynamic noise reduction coefficient is obtained after multiplication. This enables precise correction of the coupled effects of multiple factors.

[0036] A detailed explanation of the dimensions of each parameter in the formula is provided: The dynamic noise reduction coefficient is dimensionless and serves as a relative quantitative indicator of noise reduction effect. Its value range is calibrated to 0 to 1 through experiments. The closer the value is to 1, the better the noise reduction effect. It can intuitively reflect the relative level of noise reduction performance without the need for units. The baseline noise reduction coefficient is also dimensionless and is determined by experiments under standard operating conditions. It serves as the benchmark reference value for dynamic noise reduction coefficient correction. The voltage sensitivity coefficient is dimensionless and used to correlate the rate of change of voltage with the rate of change of noise reduction coefficient. Its value is determined through experimental calibration and can accurately reflect the proportion of noise reduction coefficient change corresponding to a unit rate of change of voltage. It is dimensionless. The real-time supply voltage has the following dimensions: The unit is volt, which belongs to the standard dimension of the electronic and electrical industry. This parameter directly reflects the real-time output voltage status of the power supply module, and its measurement accuracy directly affects the accuracy of the voltage correction term. The rated supply voltage has the same dimensions as the real-time supply voltage and is measured in volts. It is the standard voltage value determined during product design and serves as a reference for changes in supply voltage. The frequency sensitivity coefficient is dimensionless and is used to correlate the rate of change of frequency with the rate of change of noise reduction coefficient. Its value is calibrated experimentally and reflects the proportion of noise reduction coefficient change corresponding to a unit rate of change of frequency. The frequency of the real-time interference signal, with dimensions of The unit is Hertz. This parameter reflects the periodic characteristics of the interference signal in the current environment. The degree of influence of interference signals of different frequencies on the noise reduction module is different. The reference interference signal frequency has the same dimensions as the real-time interference signal frequency and is measured in Hertz. It is a characteristic frequency under typical interference scenarios and serves as a reference for frequency changes. The temperature sensitivity coefficient has dimensions of . The unit is per degree Celsius. It is used to correlate the temperature change value with the rate of change of the noise reduction coefficient. Its value reflects the proportion of the noise reduction coefficient change corresponding to a unit temperature change. The real-time circuit temperature has the following dimensions: The unit is Celsius, which belongs to the SI basic dimension and directly reflects the real-time thermal state of the circuit. Changes in temperature will cause the parameters of circuit components to drift. The reference circuit temperature, with dimensions consistent with the real-time circuit temperature and united in degrees Celsius, represents the circuit temperature under standard operating conditions and serves as a benchmark for temperature changes. The dimensionality verification of this formula conforms to the principle of homogeneity; all factors on the right side are dimensionless, consistent with the dimensionless dynamic noise reduction coefficient on the left side, ensuring the formula's validity across different unit systems. Whether using the International System of Units (SI) or other unit systems, accurate dynamic noise reduction coefficient values ​​can be obtained.

[0037] The logical derivation of the formula is as follows: First, based on circuit theory and experimental data, it is assumed that the change in the noise reduction coefficient follows a linear law when a single parameter changes. For the case of varying supply voltage, the noise reduction coefficient values ​​under different supply voltages are obtained through experimental testing. Linear fitting of the experimental data yields the linear relationship between the change in supply voltage and the change in the noise reduction coefficient, i.e. ; This formula is derived based on the linear effect of voltage change on the amplification factor of the noise reduction module, where This is the noise reduction coefficient considering only the supply voltage variation. Similarly, for cases where the interference signal frequency varies, by testing the noise reduction coefficient under interference signals of different frequencies, a linear relationship between frequency variation and noise reduction coefficient variation is obtained through fitting, and the correction formula for the noise reduction coefficient considering only frequency variation is derived. ,in This represents the noise reduction coefficient considering only frequency variations. For temperature variations, the noise reduction coefficient was tested at different temperatures, and a linear relationship between temperature variation and noise reduction coefficient variation was fitted. This led to the derivation of a correction formula for the noise reduction coefficient considering only temperature variations. ,in This is the noise reduction coefficient when only temperature changes are considered.

[0038] In actual operating conditions, the effects of the power supply voltage, interference signal frequency, and temperature are independent, and there is no coupling interference. That is, a change in one parameter will not affect the influence of other parameters on the noise reduction coefficient. Therefore, the dynamic noise reduction coefficient under multi-parameter coupling is the product of the noise reduction coefficients corrected for each of the three individual parameters. However, since the formulas for correcting each of the three individual parameters all use... Using this as a baseline, direct multiplication will lead to The double counting occurs, therefore correction is needed. .Will , , Substituting the expression into the formula and simplifying it, we obtain the above formula for correcting the dynamic noise reduction coefficient. This derivation process strictly follows the principle of linear superposition and the assumption of parameter independence. Combined with the fitting analysis of experimental data, it ensures the rationality and accuracy of the formula, and can accurately reflect the variation law of the noise reduction coefficient under the effect of multi-parameter coupling.

[0039] In existing technologies, the power supply module typically outputs a fixed value of current to the internal circuitry of the headphones, or adjusts it simply based on changes in a single load resistance, without considering the load changes required by the noise cancellation module after the noise cancellation factor is adjusted. When the noise cancellation factor increases, the computational load of components such as operational amplifiers and filter circuits inside the noise cancellation module increases, and the load current demand also increases accordingly. A fixed supply current cannot meet this dynamically changing load demand, leading to insufficient power supply and affecting the normal operation of the noise cancellation module. When the noise cancellation factor decreases, the load demand of the noise cancellation module decreases, and a fixed supply current will generate redundant losses, reducing power supply efficiency.

[0040] Based on this, in step S3, the adaptive power supply current is obtained by adjusting the reference power supply current based on the dynamic noise reduction coefficient and the real-time load resistance. Specifically, the reference load resistance and the load sensitivity coefficient are set, the load correction factor is obtained by combining the ratio of the real-time load resistance to the reference load resistance with the load sensitivity coefficient, and the adaptive power supply current is obtained by multiplying the ratio of the dynamic noise reduction coefficient to the reference noise reduction coefficient, the load correction factor and the reference power supply current.

[0041] This technical solution constructs a two-factor power supply adjustment logic based on noise reduction requirements and load conditions, which can comprehensively cover the circuit's load demands and achieve precise adaptation of the power supply current. In specific implementation, the reference load resistance is the total load resistance value obtained by measuring the equivalent resistance of each module in the headphone's internal circuitry under standard operating conditions. The reference power supply current is the optimal power supply current value that ensures stable circuit operation under standard operating conditions; both are determined through experimental calibration. The load sensitivity coefficient is obtained through single-variable experimental calibration. In the experiment, other parameters are kept constant, and only the load resistance value is changed. The optimal power supply current adjustment amount for stable circuit operation under different load resistances is tested. Through fitting analysis of the experimental data, the value of the load sensitivity coefficient is determined. This coefficient can accurately quantify the relationship between changes in load resistance and adjustments in power supply current.

[0042] In the actual adjustment process, the ratio of the dynamic noise reduction coefficient to the reference noise reduction coefficient is first calculated. This ratio directly reflects the proportion of load change of the noise reduction module. When the ratio is greater than 1, it indicates that the load demand of the noise reduction module has increased, and the supply current needs to be increased; when the ratio is less than 1, it indicates that the load demand of the noise reduction module has decreased, and the supply current can be reduced. At the same time, the ratio of the real-time load resistance to the reference load resistance is calculated, and combined with the load sensitivity coefficient, a load correction factor is obtained. This factor reflects the supply current demand of other circuit modules besides the noise reduction module due to load changes. The adaptive supply current is obtained by multiplying these two ratios with the reference supply current.

[0043] For example, when the ratio of the dynamic noise reduction coefficient to the baseline noise reduction coefficient is 1.2, the load correction factor is 1.1, and the baseline supply current is 50 mA, the adaptive supply current is 50 × 1.2 × 1.1 = 66 mA, which can accurately match the current load demand. This two-factor adjustment logic can comprehensively consider the load changes of the noise reduction module and other circuit modules, and realize the dynamic adaptive adjustment of the supply current. This not only ensures the normal operation of each module in the circuit, but also effectively reduces power supply redundancy losses and improves power supply efficiency.

[0044] When calculating the adaptive supply current, the adaptive supply current adjustment formula is used, which is specifically as follows:

[0045] Its theoretical design is based on the matching relationship between circuit load and supply current. In electronic circuits, the magnitude of the supply current must be positively correlated with the total load demand of the circuit to ensure that each module of the circuit can obtain sufficient energy to operate normally, while avoiding energy waste. Dynamic noise reduction coefficient. Compared with the benchmark noise reduction coefficient The ratio directly reflects the load change ratio of the noise reduction module. The power consumption of the noise reduction module is positively correlated with the noise reduction coefficient. This is because a higher noise reduction coefficient requires higher gain in the operational amplifier inside the noise reduction module and more complex signal processing in the filtering circuit, all of which lead to increased power consumption. Power equals the product of voltage and current. Under stable supply voltage, power and current are directly proportional. Therefore, the supply current needs to be consistent with the change ratio of the noise reduction coefficient. When this ratio increases, it indicates that the load on the noise reduction module has increased, and the supply current needs to be increased accordingly.

[0046] Real-time load resistance With reference load resistor The ratio reflects the load changes of other circuit modules besides the noise reduction module. According to Ohm's law, with a fixed supply voltage, the load current is inversely proportional to the load resistance. When the current is reduced, the load current demand of other circuit modules increases, through This can quantify the degree of change in load resistance; a negative difference indicates a decrease in load resistance and an increase in load demand. This is combined with the load sensitivity coefficient. The power supply current correction amount corresponding to load changes can be obtained. By combining this correction amount with the power supply current adjustment amount corresponding to load changes of the noise reduction module, the power supply current can be accurately adapted to ensure that the power supply current can fully match the total load requirements of the circuit.

[0047] The dimensions of each parameter are explained below: For adaptive supply current, the dimension is The unit is ampere, which belongs to the SI basic dimension. This parameter directly reflects the real-time output current status of the power supply module, and its value determines whether each module of the circuit can obtain sufficient operating current. The reference supply current has the same dimensions as the adaptive supply current and is measured in amperes. It is the optimal supply current value to ensure stable circuit operation under standard operating conditions and provides a reference for supply current adjustment. and Both are dimensionless noise reduction coefficients, and their ratio is also dimensionless. This ratio accurately quantifies the load change ratio of the noise reduction module, and can intuitively reflect the relative change of the load of the noise reduction module without the need for units. The load sensitivity coefficient is dimensionless and is used to correlate the rate of change of load resistance with the rate of change of supply current. Its value is determined through experimental calibration and can accurately reflect the proportion of supply current change corresponding to a unit rate of change of load resistance. For real-time load resistance, the dimension is The unit is ohms, which belongs to the standard dimension of the electronic and electrical industry. This parameter reflects the real-time load impedance state of the circuit, and its change directly affects the load current demand. The reference load resistance, with dimensions consistent with the real-time load resistance and unit ohms, represents the total load impedance of the circuit under standard operating conditions, serving as a reference for load resistance variations. The formula's dimensions conform to the homogeneity principle; the right side and... Both are dimensionless, and Multiplying the dimensions, we get the left side. The dimensions are determined to ensure the rationality and accuracy of the formula calculations under different unit systems.

[0048] The logical derivation of the formula is as follows: First, based on the power balance principle of the circuit, when only considering the load variation of the noise reduction module, the supply current should be proportional to the noise reduction coefficient. This is because the power consumption of the noise reduction module... The power is positively correlated with the noise reduction coefficient, i.e., and the power, under stable supply voltage conditions, is directly proportional to the current, i.e., . Therefore, it can be deduced that the supply current is directly proportional to the noise reduction coefficient, i.e., . ,in This is the power supply current adjustment value that only considers changes in the load of the noise reduction module.

[0049] Secondly, when only considering the load changes of other circuit modules, based on Ohm's law, at the supply voltage Under fixed conditions, the load current is inversely proportional to the load resistance. Optimal supply current under different load resistances was obtained through experimental testing. Linear fitting of the experimental data revealed a linear relationship between changes in load resistance and supply current. This led to the derivation of a supply current adjustment formula considering only load variations in other circuit modules. This is a power supply current adjustment value that only considers changes in the load of other circuit modules. This is a proportionality coefficient used to correct the linear relationship between changes in load resistance and changes in current.

[0050] Since the load of the noise reduction module is independent of the loads of other circuit modules, the impact of their load demands on the supply current is additive. Therefore, the total supply current is the product of the respective supply current adjustment values ​​for each module. .Will Substituting the expression into the formula and simplifying it, we obtain the above formula for adaptive adjustment of the power supply current. This derivation process combines the power balance principle and Ohm's law, and the correlation coefficient is determined through fitting analysis of experimental data, ensuring that the formula can accurately reflect the relationship between the power supply current and load changes, thus achieving dynamic adaptive adjustment of the power supply current.

[0051] In existing technologies, the evaluation of optimization of the internal circuitry of headphones often focuses only on a single aspect such as noise reduction effect or power supply efficiency, lacking a quantitative method to quantify the synergistic performance that combines the two. This single-indicator evaluation method is one-sided and cannot comprehensively reflect the overall effect of the optimization scheme. For example, some optimization schemes may improve the noise reduction effect, but lead to a significant decrease in power supply efficiency and generate a large amount of redundant losses; while other schemes may improve power supply efficiency, but the noise reduction effect cannot meet the user's needs. Due to the lack of quantitative methods for synergistic performance, it is impossible to accurately determine whether the optimization effect has reached the overall optimal level, and it is also impossible to provide a clear basis for judgment for subsequent optimization adjustments.

[0052] Based on this, the noise reduction-power supply comprehensive performance index is calculated by the noise reduction-power supply comprehensive performance quantification formula. The noise reduction-power supply comprehensive performance quantification formula is related to the ratio of dynamic noise reduction coefficient to adaptive power supply efficiency relative to the benchmark power supply efficiency, so as to realize the synergistic quantification of noise reduction effect and power supply efficiency.

[0053] This technical solution integrates the two core indicators of noise reduction effect and power supply efficiency into a single quantitative index by constructing a comprehensive performance index, which can comprehensively and objectively reflect the overall effect of the optimization scheme. In the specific implementation process, the dynamic noise reduction coefficient is calculated by the dynamic noise reduction coefficient correction formula mentioned above, which can accurately reflect the noise reduction effect under the current operating conditions; the adaptive power supply efficiency is calculated by measuring the total output power and effective output power of the power supply module.

[0054] Specifically, the output voltage and current of the power supply module are measured in real time by voltage and current acquisition units, and their product is the total output power of the power supply module. Simultaneously, the real-time power loss of the circuit is measured, and the difference between the total output power and the power loss is the effective output power. The ratio of the effective output power to the total output power is the adaptive power supply efficiency. Multiplying the dynamic noise reduction coefficient by the ratio of the adaptive power supply efficiency to the reference power supply efficiency yields the noise reduction-power supply comprehensive performance index. This index is experimentally calibrated to a range of 0 to 1; a value closer to 1 indicates a better synergistic optimization effect between noise reduction and power supply efficiency.

[0055] In practical applications, this comprehensive performance index provides a clear basis for subsequent closed-loop optimization. When the comprehensive performance index reaches a preset threshold, it indicates that the current optimization effect meets the requirements; when the comprehensive performance index is lower than the preset threshold, the relevant parameters need to be adjusted and the optimization calculation needs to be repeated. This collaborative quantification method can avoid the one-sidedness of single-index evaluation, ensure that the optimization scheme reaches the overall optimal, and achieve a synergistic balance between noise reduction effect and power supply efficiency.

[0056] When calculating the overall performance index of noise reduction and power supply, the quantitative formula for overall noise reduction and power supply performance is used. The specific formula is as follows:

[0057] in

[0058] The theoretical design is based on the principle that optimizing the internal circuitry of headphones should simultaneously consider noise reduction effectiveness and power supply efficiency, achieving a synergistic balance between the two to ensure stable circuit operation and a good user experience. Dynamic noise reduction coefficient. It directly quantifies the noise reduction effect under the current operating conditions; the higher the value, the better the noise reduction effect; adaptive power supply efficiency. This quantifies the energy utilization efficiency of the power supply module; a higher value indicates higher power supply efficiency and lower energy loss. Combining these two indicators provides a comprehensive reflection of the overall effectiveness of the optimization scheme.

[0059] Adaptive power supply efficiency Compared with the reference power supply efficiency The ratio quantifies the degree of optimization of power supply efficiency. When the ratio is greater than 1, it indicates that the current power supply efficiency is better than that under standard operating conditions; when the ratio is less than 1, it indicates that the power supply efficiency needs to be improved. Multiplying the dynamic noise reduction coefficient by this ratio yields a comprehensive performance index that simultaneously reflects the optimization level of noise reduction effect and power supply efficiency, achieving synergistic quantification of both.

[0060] The calculation formula is derived based on the power balance principle. In electronic circuits, part of the total energy output by the power supply module is used for the normal operation of each module in the circuit, i.e., effective output energy; the other part is lost in the form of heat, i.e., energy loss. The power supply efficiency is the ratio of effective output energy to total output energy. This is the total output power of the power supply module. Multiplying this power by the time gives the total output energy. The real-time power loss of the circuit, multiplied by time, equals the energy loss. The difference between the total output power and the power loss is the effective output power, and the effective output power multiplied by time equals the effective output energy. Therefore, the ratio of effective output power to total output power is the adaptive power supply efficiency, which accurately reflects the energy utilization efficiency of the power supply module.

[0061] The dimensions of each parameter are explained below: The noise reduction-power supply comprehensive performance index is dimensionless and presented as a percentage. It can intuitively reflect the synergistic optimization level of noise reduction effect and power supply efficiency. Its value ranges from 0 to 100%, and the higher the value, the better the synergistic optimization effect. The dynamic noise reduction coefficient is dimensionless and ranges from 0 to 1, directly reflecting the current noise reduction effect. For adaptive power supply efficiency, dimensionless, with a value range of 0 to 1, it reflects the energy utilization efficiency of the power supply module. The higher the value, the smaller the energy loss. The baseline power supply efficiency is dimensionless and ranges from 0 to 1. It is the power supply efficiency value under standard operating conditions and serves as a benchmark reference for the degree of power supply efficiency optimization. The real-time supply voltage has the following dimensions: The unit is volts, which reflects the real-time output voltage status of the power supply module; For adaptive supply current, the dimension is The unit is amperes, which reflects the real-time output current status of the power supply module; The real-time power loss of the circuit, with dimensions of The unit is watt, a standard dimension in the electrical and electronic industry, reflecting the energy loss state of a circuit. Its value is related to factors such as the parameters and operating status of circuit components. The formula's dimensions conform to the principle of homogeneity. (Right side) and All values ​​are dimensionless, and the product remains dimensionless after multiplication. Multiplying by 100% results in a percentage representation, ensuring the rationality and intuitiveness of the quantification results.

[0062] The logical derivation of the formula is as follows: First, to comprehensively evaluate the synergistic optimization effect of noise reduction and power supply efficiency, a comprehensive performance index that integrates these two core indicators needs to be constructed. Based on the basic principle of indicator integration, the comprehensive performance index should be positively correlated with each core indicator; that is, the better the noise reduction effect and the higher the power supply efficiency, the larger the comprehensive performance index. Therefore, the comprehensive performance index is defined as the product of the noise reduction effect coefficient and the power supply efficiency coefficient, i.e. .in, It is the power supply efficiency coefficient, which can quantify the degree of optimization of the current power supply efficiency relative to the reference power supply efficiency.

[0063] Since the overall performance index needs to be presented in an intuitive percentage format for easy user understanding and judgment, the product above is multiplied by 100% to obtain... .

[0064] Next, we derive the adaptive power supply efficiency. The calculation formula, based on the law of conservation of energy, states that the total energy output by the power supply module equals the sum of the effective output energy and the energy lost. It is the product of total output power and time, i.e. ,in For time. Energy lost in the circuit. It is the product of power loss and time, i.e. Effective energy output This is the difference between the total output energy and the energy lost, i.e. .

[0065] Adaptive power supply efficiency Defined as the ratio of effective output energy to total output energy, i.e. .Will and Substituting the expression into the formula, we get Due to time We can cancel out some values ​​in the numerator and denominator, and after simplification, we get... Substituting this formula into the expression for the comprehensive performance index, we obtain the above quantitative formula for the comprehensive performance of noise reduction and power supply. This derivation process strictly follows the law of conservation of energy and the principle of index integration, ensuring that the formula can accurately and comprehensively quantify the synergistic optimization level of noise reduction effect and power supply efficiency.

[0066] In existing technologies, the values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient are often determined by empirical estimation or simple single-condition experiments, lacking scientific and systematic precise calibration methods. Empirical estimation is highly subjective and prone to large errors, failing to accurately reflect the relationship between parameter changes and noise reduction coefficient changes; single-condition experiments cannot cover complex actual operating conditions, and the resulting sensitivity coefficients have poor adaptability under complex operating conditions with multiple coupled parameters, leading to insufficient accuracy in noise reduction coefficient correction and failing to achieve precise adaptation to complex operating conditions.

[0067] Based on this, the values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient were obtained through experimental calibration. Specifically, the calibration method was as follows: under different combinations of power supply voltage, different interference signal frequency, and different circuit temperature, the corresponding noise reduction coefficient change was measured. Based on the ratio of the noise reduction coefficient change to the power supply voltage change rate, the interference signal frequency change rate, and the circuit temperature change value, the calibration values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient were determined.

[0068] This technical solution achieves precise calibration of the sensitivity coefficient through combined operating condition experiments, covering a range of operating conditions with different parameter combinations, ensuring good adaptability of the sensitivity coefficient under various complex operating conditions. In the specific implementation process, a professional experimental platform was built, including a programmable DC power supply, a signal generator, a temperature control chamber, audio testing equipment, and a data acquisition and analysis system. The programmable DC power supply is used to adjust the supply voltage, with an output voltage accuracy of 0.01 volts, accurately simulating different supply voltage conditions; the signal generator generates interference signals of different frequencies, with a frequency adjustment range of 10 Hz to 10 kHz, covering various interference frequencies that headphones may encounter in actual operation; the temperature control chamber regulates the circuit's operating temperature, with a temperature control accuracy of ±0.1 degrees Celsius, simulating different temperature conditions; the audio testing equipment tests the noise reduction coefficient under different operating conditions; and the data acquisition and analysis system collects experimental data and analyzes and processes it.

[0069] The experiment employed orthogonal experimental design, selecting three factors: supply voltage, interference signal frequency, and circuit temperature, with five levels for each factor. The supply voltage levels were set to 3.0 volts, 3.3 volts, 3.7 volts, 4.0 volts, and 4.3 volts; the interference signal frequency levels were set to 100 Hz, 500 Hz, 1000 Hz, 5000 Hz, and 10000 Hz; and the circuit temperature levels were set to -10 degrees Celsius, 0 degrees Celsius, 25 degrees Celsius, 40 degrees Celsius, and 60 degrees Celsius. According to the orthogonal experimental design table, a total of 25 sets of combined operating conditions were conducted. In each set of experiments, the internal circuitry of the headphones was placed in a temperature-controlled chamber, powered by a programmable DC power supply. A signal generator produced an interference signal of a set frequency and applied it to the circuit. After the circuit stabilized, the noise reduction coefficient under the current operating conditions was measured using audio testing equipment.

[0070] Based on the noise reduction coefficients obtained from the tests, the change in the noise reduction coefficient relative to the baseline noise reduction coefficient in each experimental group was calculated. Simultaneously, the rate of change of supply voltage, the rate of change of interference signal frequency, and the change in circuit temperature were also calculated. Multiple linear regression analysis was performed on the experimental data using the least squares method to establish a linear relationship model between the change in noise reduction coefficient and the rates of change of supply voltage, interference signal frequency, and circuit temperature. Based on the regression coefficients of this model, the calibration values ​​of the voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient were determined. To improve calibration accuracy, each experiment was repeated five times, and the average of the sensitivity coefficients obtained from the five experiments was taken as the final calibration value. This combined operating condition experimental calibration method ensures that the obtained sensitivity coefficients accurately reflect the relationship between parameter changes and noise reduction coefficient changes under multi-parameter coupled operating conditions, guaranteeing the calculation accuracy of the noise reduction coefficient correction formula.

[0071] In existing technologies, determining the value of the load sensitivity coefficient often relies on simple empirical estimation or testing under limited load resistance conditions, lacking a systematic and precise calibration method. Empirical estimation cannot accurately reflect the relationship between load resistance changes and supply current adjustments, leading to significant errors in supply current regulation. Testing under limited conditions cannot cover all possible load variations that may occur within the headphone's internal circuitry, resulting in a poorly adaptable load sensitivity coefficient. When load resistance changes exceed the test range, the supply current regulation error increases significantly, affecting the stable operation of the circuit.

[0072] Based on this, the value of the load sensitivity coefficient is obtained through experimental calibration. The specific calibration method is as follows: under different load resistance conditions, the corresponding power supply current adjustment is tested and obtained. Based on the ratio of the power supply current adjustment to the load resistance change rate, the calibration value of the load sensitivity coefficient is determined.

[0073] This technical solution addresses the changing characteristics of load resistance by achieving precise calibration of the load sensitivity coefficient through a single-variable experiment, ensuring good adaptability of the load sensitivity coefficient under various load variation conditions. In its implementation, a dedicated experimental platform was built, comprising a programmable DC power supply, an electronic load cell, a current acquisition module, and a data analysis system. The programmable DC power supply provides a stable power supply voltage to the internal circuitry of the headphones, achieving an output voltage stability of 0.01%. The electronic load cell simulates different load resistance conditions, with a resistance adjustment range of 1 ohm to 100 ohms and an adjustment accuracy of 0.01 ohms, accurately simulating various load resistance changes that may occur in the internal circuitry of the headphones. The current acquisition module uses a high-precision current sensor to collect changes in the supply current in real time, achieving an accuracy of 1 microamp. The data analysis system analyzes and processes the collected experimental data.

[0074] The experiment employed a single-variable method, keeping other parameters constant and varying only the load resistance. The reference load resistance was set to the value under standard operating conditions. The load resistance was varied across multiple levels around the reference resistance, specifically 50%, 60%, 70%, 80%, 90%, 100%, 110%, 120%, 130%, 140%, and 150% of the reference resistance—a total of 11 levels—comprehensively covering the possible range of load resistance variations. At each load resistance level, an electronic load cell was adjusted to the corresponding resistance value to provide a load to the internal circuitry of the headphones. A programmable DC power supply powered the circuit. After the circuit stabilized, the optimal supply current value for stable operation was determined.

[0075] Based on the optimal supply current value obtained from the test, the supply current adjustment amount at each load resistance level is calculated, which is the difference between the current optimal supply current and the reference supply current. Simultaneously, the load resistance change rate at each load resistance level is calculated, which is the ratio of the current load resistance to the reference load resistance minus 1. A linear relationship model between the supply current adjustment amount and the load resistance change rate is established through linear fitting analysis of the experimental data. The calibration value of the load sensitivity coefficient is determined based on the slope of this model. To improve calibration accuracy, the experiment at each load resistance level is repeated 5 times, and the average value of the load sensitivity coefficient obtained from the 5 experiments is taken as the final calibration value. Through this single-variable experimental calibration method, the obtained load sensitivity coefficient can accurately reflect the linear relationship between load resistance change and supply current adjustment amount, ensuring the calculation accuracy of the adaptive supply current adjustment formula and achieving precise matching between supply current and load demand.

[0076] In existing technologies, noise reduction and power supply optimization of the internal circuitry of headphones mostly adopt an open-loop control approach. This means that after a single optimization calculation to obtain the noise reduction coefficient and power supply current, these parameters are fixed, lacking a closed-loop optimization mechanism. During long-term operation, factors such as component aging, changes in ambient temperature, and fluctuations in power supply voltage can cause circuit parameters to drift, affecting the accuracy of noise reduction coefficient correction and power supply current adjustment, leading to a gradual decrease in optimization effectiveness. When the optimization effect deteriorates to a certain extent, it can result in reduced noise reduction performance and decreased power supply efficiency, affecting the normal use of the headphones. However, due to the lack of a closed-loop optimization mechanism, these problems cannot be detected and resolved in a timely manner.

[0077] Based on this, step S5 is also included: comparing the noise reduction-power supply comprehensive performance index with the preset performance threshold. If the noise reduction-power supply comprehensive performance index does not reach the preset performance threshold, the values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, temperature sensitivity coefficient and load sensitivity coefficient are adjusted, and steps S2 to S4 are repeated until the noise reduction-power supply comprehensive performance index reaches the preset performance threshold. The preset performance threshold is determined by experimental calibration.

[0078] This technical solution constructs a closed-loop optimization logic, enabling real-time monitoring of optimization effects and timely adjustment of relevant parameters to ensure the stability of optimization results over long-term operation. In practical implementation, the preset performance threshold is determined through extensive experimental calibration. The experiments select various typical operating conditions that the headphones might encounter, including low battery, strong interference, high temperature, and low temperature. Under each typical condition, the minimum comprehensive performance level required to ensure stable operation of the headphones is obtained. The maximum value of these minimum comprehensive performance levels is set as the preset performance threshold, ensuring that operational requirements are met under various typical conditions.

[0079] In actual operation, the main control unit repeatedly executes steps S1 to S4 according to a preset cycle (e.g., 1 second) to calculate the noise reduction-power supply integrated performance index under the current operating condition. Then, the calculated integrated performance index is compared with a preset performance threshold. If the integrated performance index reaches or exceeds the preset performance threshold, it means that the current optimization effect meets the requirements and no adjustment is needed; the unit continues to operate according to the current parameters. If the integrated performance index does not reach the preset performance threshold, it means that the current optimization effect has decayed and closed-loop adjustment is required.

[0080] During the adjustment process, the main control unit integrates a parameter adjustment algorithm. This algorithm determines the adjustment direction and amount of the voltage sensitivity coefficient, frequency sensitivity coefficient, temperature sensitivity coefficient, and load sensitivity coefficient based on the difference between the current comprehensive performance index and the preset threshold, as well as the changing trends of each parameter. For example, if the comprehensive performance index is lower than the preset threshold, and analysis reveals that the inaccurate noise reduction coefficient correction is due to fluctuations in the supply voltage, the value of the voltage sensitivity coefficient is appropriately increased; if it is found that the deviation in supply current regulation is caused by changes in load resistance, the value of the load sensitivity coefficient is appropriately adjusted.

[0081] After parameter adjustment, steps S2 to S4 are repeated to recalculate the dynamic noise reduction coefficient, adaptive power supply current, and noise reduction-power supply comprehensive performance index, and then compared with the preset performance threshold again. If the threshold is still not reached, the parameters are adjusted and the above process is repeated until the comprehensive performance index reaches the preset performance threshold. Through this closed-loop optimization logic, the optimization effect can be monitored in real time, and the attenuation of the optimization effect caused by factors such as parameter drift can be dealt with in a timely manner, ensuring that the headphones maintain good noise reduction effect and power supply efficiency during long-term operation, and ensuring the stable operation of the circuit.

[0082] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for signal noise reduction and power supply optimization of the internal circuitry of an earphone, characterized in that, Includes the following steps: S1: Based on synchronous acquisition timing control logic, collect the real-time power supply voltage, real-time interference signal frequency, real-time circuit temperature and real-time load resistance of the internal circuit of the earphone. S2: Based on the coupling effect of real-time power supply voltage, real-time interference signal frequency, and real-time circuit temperature, the reference noise reduction coefficient is corrected to obtain the dynamic noise reduction coefficient; S3: Based on the dynamic noise reduction coefficient and real-time load resistance, the reference supply current is adjusted to obtain the adaptive supply current; S4: Calculate the comprehensive performance index of noise reduction and power supply based on the dynamic noise reduction coefficient and the power supply efficiency corresponding to adaptive power supply.

2. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 1, characterized in that, The synchronous acquisition timing control logic in step S1 is as follows: set the acquisition trigger timestamps for the voltage acquisition unit, frequency acquisition unit, temperature acquisition unit, and resistance acquisition unit, and each acquisition unit triggers the acquisition action at the same timestamp. After the acquisition is completed, the data is transmitted to the main control unit.

3. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 1, characterized in that, In step S2, the dynamic noise reduction coefficient is obtained by correcting the reference noise reduction coefficient based on the coupling effect of real-time supply voltage, real-time interference signal frequency, and real-time circuit temperature. Specifically, the rated supply voltage, reference interference signal frequency, reference circuit temperature, voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient are set. The supply voltage correction factor is obtained by combining the ratio of real-time supply voltage to rated supply voltage with the voltage sensitivity coefficient. The interference frequency correction factor is obtained by combining the ratio of real-time interference signal frequency to reference interference signal frequency with the frequency sensitivity coefficient. The circuit temperature correction factor is obtained by combining the difference between real-time circuit temperature and reference circuit temperature with the temperature sensitivity coefficient. The dynamic noise reduction coefficient is obtained by multiplying the supply voltage correction factor, interference frequency correction factor, circuit temperature correction factor, and reference noise reduction coefficient.

4. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 1, characterized in that, In step S3, the adaptive supply current is obtained by adjusting the reference supply current based on the dynamic noise reduction coefficient and the real-time load resistance. Specifically, the reference load resistance and the load sensitivity coefficient are set, the load correction factor is obtained by combining the ratio of the real-time load resistance to the reference load resistance with the load sensitivity coefficient, and the adaptive supply current is obtained by multiplying the ratio of the dynamic noise reduction coefficient to the reference noise reduction coefficient, the load correction factor and the reference supply current.

5. The signal noise reduction and power supply optimization method for the internal circuit of the earphone according to claim 3, characterized in that, The dynamic noise reduction coefficient is calculated using a dynamic noise reduction coefficient correction formula, which is related to the power supply voltage correction factor, interference frequency correction factor, circuit temperature correction factor, and reference noise reduction coefficient, thereby achieving dynamic correction of the noise reduction coefficient under multi-parameter coupling.

6. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 4, characterized in that, The adaptive power supply current is calculated using the adaptive power supply current adjustment formula, which relates the ratio of the dynamic noise reduction coefficient to the reference noise reduction coefficient, the load correction factor, and the reference power supply current, thereby achieving power supply current adaptation adjustment based on noise reduction requirements.

7. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 1, characterized in that, The noise reduction-power supply integrated performance index is calculated using the noise reduction-power supply integrated performance quantification formula. This formula is related to the ratio of the dynamic noise reduction coefficient to the adaptive power supply efficiency relative to the benchmark power supply efficiency, thereby achieving the synergistic quantification of noise reduction effect and power supply efficiency.

8. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 5, characterized in that, The values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient were obtained through experimental calibration. Specifically, the calibration method was as follows: under different combinations of power supply voltage, different interference signal frequency, and different circuit temperature, the corresponding noise reduction coefficient change was measured. Based on the ratio of the noise reduction coefficient change to the power supply voltage change rate, the interference signal frequency change rate, and the circuit temperature change value, the calibration values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, and temperature sensitivity coefficient were determined.

9. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 6, characterized in that, The load sensitivity coefficient is determined through experimental calibration. Specifically, under different load resistance conditions, the corresponding power supply current adjustment is measured, and the calibrated value of the load sensitivity coefficient is determined based on the ratio of the power supply current adjustment to the load resistance change rate.

10. The signal noise reduction and power supply optimization method for the internal circuit of an earphone according to claim 1, characterized in that, The method also includes step S5: comparing the noise reduction-power supply comprehensive performance index with the preset performance threshold. If the noise reduction-power supply comprehensive performance index does not reach the preset performance threshold, the values ​​of voltage sensitivity coefficient, frequency sensitivity coefficient, temperature sensitivity coefficient and load sensitivity coefficient are adjusted, and steps S2 to S4 are repeated until the noise reduction-power supply comprehensive performance index reaches the preset performance threshold. The preset performance threshold is determined by experimental calibration.

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