Method and system for controlling melody vibration motor

Abstract

The invention discloses a melody vibration motor control method, which comprises the following steps of: extracting frequency and volume change characteristics in an audio signal, and transmitting the characteristic data to a digital signal processing module for subsequent processing; noise in the audio signals is removed through adaptive filtering and signal enhancement technologies, and key frequency components are enhanced; according to the enhanced audio characteristics, converting the frequency and the intensity of the audio signal into corresponding vibration frequency and amplitude parameters, and generating a driving signal for controlling a vibration motor; the audio processing chip receives a vibration control signal generated by the digital signal processing module, and the working voltage and current of the vibration motor are adjusted in real time through the power adjusting circuit. In a driving circuit of the vibration motor, the response state of the vibration motor is detected in real time, and a driving signal is finely adjusted; dynamically adjusting the working power of the vibration motor according to the working state of the vibration motor and the characteristics of the audio signal; and more stable and reliable tactile feedback experience is provided for the user.

Description

Technical Field

[0001] The present invention relates to the technical field of vibration motor control, and in particular to a method and system for controlling a rhythmic vibration motor. Background Art

[0002] In recent years, vibration motors have been widely used in consumer electronics, gaming devices, and fitness equipment. In particular, with the development of audio drive technology, using sound to trigger vibration feedback is gradually becoming a means to enhance user experience. By controlling the vibration of the motor through sound, users can get tactile feedback in addition to hearing, making the application scenarios more diverse.

[0003] For example, in scenarios such as smart watches, game controllers, and audio equipment, combining vibration feedback with sound can greatly enhance the immersive experience and interactivity. There are already some technologies that use audio signals to drive vibration motors, usually based on the following methods: (1) Audio filtering + amplification: A specific frequency band is extracted from the audio signal through filtering and amplification circuits to drive the vibration motor. This method can simply achieve a vibration response based on a specific frequency; (2) Audio spectrum analysis: Use spectrum analysis chips or software algorithms to perform spectrum analysis on audio signals, and control different vibration intensities or modes based on the analysis results; (3) Vibration control based on volume or rhythm: The vibration effect is triggered by real-time detection of the volume or rhythm of the audio. It is suitable for some music-driven scenarios with a strong sense of rhythm.

[0004] The prior art has the following disadvantages: (1) Response delay: Due to delays in filtering and signal processing, the vibration motor response often lags behind the audio signal, making it impossible to achieve synchronous tactile feedback.

[0005] (2) Single frequency band response: Most solutions can only vibrate a specific frequency band or rhythm, making it difficult to achieve more detailed audio vibration matching and unable to fully restore complex sound effect changes.

[0006] (3) High power consumption: Audio signal processing and vibration motor control consume a lot of electricity, which is not energy-efficient when used in portable devices. Summary of the invention

[0007] In order to solve the above-mentioned technical problems, the present invention provides a method and system for controlling a rhythmic vibration motor.

[0008] The technical solution of the present invention is achieved in this way: A rhythm vibration motor control method comprises the following steps: S1, extracting the frequency and volume change characteristics in the audio signal, and passing these characteristic data to the digital signal processing module for subsequent processing; S2, removes noise from audio signals and enhances key frequency components through adaptive filtering and signal enhancement technology; S3, converting the frequency and intensity of the audio signal into corresponding vibration frequency and amplitude parameters according to the enhanced audio characteristics, and generating a driving signal for controlling the vibration motor; S4, the audio processing chip receives the vibration control signal generated by the digital signal processing module, and adjusts the working voltage and current of the vibration motor in real time through the power regulation circuit; S5. In the driving circuit of the vibration motor, the response state of the vibration motor is detected in real time, and the driving signal is fine-tuned; S6. Dynamically adjust the working power of the vibration motor according to the working state of the vibration motor and the characteristics of the audio signal.

[0009] Furthermore, the process of extracting the frequency and volume change characteristics in the audio signal in step S1 is specifically as follows: Acquire an audio signal to be processed, preprocess the audio signal, and obtain a preprocessed audio signal; Perform spectrum analysis on the preprocessed audio signal, use the fast Fourier transform algorithm to convert the time domain signal into the frequency domain signal, and obtain the spectrum characteristics of the audio signal; According to the frequency spectrum characteristics, the frequency characteristics of the audio signal are extracted to obtain a frequency characteristic vector; Performing rhythm detection on the preprocessed audio signal, using the autocorrelation function algorithm to calculate the rhythm period of the audio signal, and obtaining the rhythm characteristics of the audio signal; According to the rhythm features, the volume change features of the audio signal are extracted to obtain a volume change feature vector; The frequency feature vector and the volume change feature vector are fused and the comprehensive feature vector of the audio signal is obtained by feature splicing.

[0010] Furthermore, the process of enhancing the key frequency in step S2 is specifically as follows: According to the received audio feature data, the audio signal is processed using an adaptive filtering algorithm, and the filter parameters are adaptively adjusted to dynamically adapt to the changes in the audio signal to achieve noise removal; Through frequency domain analysis technology, the filtered audio signal is analyzed to identify the key frequency components that have a greater impact on the vibration effect; Based on the identified key frequency components, a signal enhancement algorithm is used to selectively amplify these frequency components.

[0011] Furthermore, the process of generating the driving signal for controlling the vibration motor in step S3 is specifically as follows: Performing time-domain synthesis on the enhanced audio signal and restoring it to a time-domain waveform signal as optimized audio feature data; According to the optimized audio feature data, the frequency and intensity of the audio signal are converted into corresponding vibration frequency and amplitude parameters through frequency mapping and amplitude mapping algorithms to generate a driving signal for controlling the vibration motor; Pulse width modulation technology is used to convert the drive signal into a control signal acceptable to the vibration motor.

[0012] Furthermore, the process of converting the frequency and intensity of the audio signal into corresponding vibration frequency and amplitude parameters through the frequency mapping and amplitude mapping algorithms is specifically as follows: According to the frequency and amplitude characteristics of the audio signal, a frequency mapping table and an amplitude mapping table are established to convert the audio characteristics into vibration parameters; Preprocess the audio signal, use an adaptive filtering algorithm to process the audio signal, and adaptively adjust the filter parameters to dynamically adapt to changes in the audio signal, remove noise, and obtain an enhanced audio feature signal; According to the frequency mapping table, the frequency of the optimized audio feature data is converted into corresponding vibration frequency parameters; According to the amplitude mapping table, the amplitude of the optimized audio feature data is converted into a corresponding amplitude parameter; The converted vibration frequency and amplitude parameters are combined to subsequently generate a drive signal for controlling the vibration motor.

[0013] Furthermore, the process of adjusting the working voltage and current of the vibration motor in real time in step S4 is specifically as follows: The audio processing chip is used to receive the vibration control signal output by the digital signal processing module, and the audio signal intensity change information is extracted; Based on the extracted audio signal strength change information, a support vector machine algorithm is used to establish a mapping model between audio signal strength and the working voltage and current of the vibration motor; During audio playback, the intensity change data of the audio signal is obtained in real time and input into the established mapping model; The mapping model is used to calculate the vibration motor operating voltage and current parameter values ​​that match the current audio signal strength; The calculated voltage and current parameter values ​​are output to the power regulation circuit to dynamically adjust the actual working voltage and current of the vibration motor.

[0014] Furthermore, the process of real-time detection of the response state of the vibration motor and fine-tuning the driving signal in step S5 is specifically as follows: Acquire characteristic parameters of the audio signal and use them as control targets of the vibration motor drive signal; According to the characteristic parameters of the audio signal, an adaptive filtering algorithm is used to pre-process the driving signal to generate an initial driving signal; Inputting the initial driving signal to the vibration motor driving circuit, and detecting the response state of the vibration motor in real time; The Kalman filter algorithm is used to filter the vibration motor response state to obtain a stable state estimation value; Compare the state estimation value with the audio signal characteristic parameters and calculate the error signal as the input of closed-loop control; According to the error signal, the PID control algorithm is used to fine-tune the drive signal to generate an optimized drive signal; The optimized driving signal is input into the vibration motor driving circuit to control the vibration frequency and amplitude of the vibration motor to produce a vibration effect matching the audio signal; By establishing a mapping relationship between audio features and vibration parameters, the automatic conversion of audio signals to vibration signals is realized; Evaluate and provide feedback on vibration effects, and continuously optimize the parameters of the closed-loop control algorithm through user experience data and objective measurement indicators.

[0015] Furthermore, the process of dynamically adjusting the working power of the vibration motor in step S6 is specifically as follows: Obtaining current working status information and characteristic parameters of the audio signal, and using them as inputs of the intelligent power management algorithm; By analyzing the working status information and audio signal characteristic parameters, the optimal working power required by the current vibration motor is determined; Dynamically adjust the actual working power of the vibration motor according to the optimal working power determined by the intelligent power management algorithm; In the process of adjusting the working power of the vibration motor, real-time monitoring is performed to determine whether the vibration effect reaches the preset vibration intensity threshold; Specifically, if the vibration effect does not reach the preset threshold, the working power of the vibration motor is appropriately increased until the vibration effect meets the requirements; if the vibration effect has reached or exceeded the preset threshold, the current working power of the vibration motor is maintained unchanged to reduce energy consumption; Continuously tracks changes in working status and audio signal characteristics, and adjusts the intelligent power management algorithm in real time to optimize vibration effect and energy consumption balance.

[0016] A musical vibration motor control system, comprising an audio processing chip and a digital signal processing module; The audio processing chip receives the vibration control signal generated by the digital signal processing module and extracts the audio signal intensity change information therefrom; According to the extracted audio signal strength change information, a mapping model between the audio signal strength and the working voltage and current of the vibration motor is established to realize the conversion of the audio signal strength to the working voltage and current parameters of the vibration motor; During audio playback, the intensity change data of the audio signal is obtained in real time, and the operating voltage and current parameter values ​​of the vibration motor that match the current audio signal intensity are calculated; The calculated voltage and current parameter values ​​are output to the power regulation circuit, thereby dynamically adjusting the actual working voltage and current of the vibration motor; Receive feedback information from the vibration motor drive circuit.

[0017] Furthermore, the digital signal processing module extracts frequency and volume change characteristics from the audio signal to be processed, obtains a frequency feature vector and a volume change feature vector, and transmits these feature data to the audio processing chip; Process the audio signal, adaptively adjust the filter parameters, dynamically adapt to the changes of the audio signal, and achieve noise removal; The key frequency components are identified through frequency domain analysis technology, and these frequency components are selectively amplified using signal enhancement algorithms; Performing time-domain synthesis on the enhanced audio signal to restore it to a time-domain waveform signal; According to the optimized audio feature data, the frequency and intensity of the audio signal are converted into corresponding vibration frequency and amplitude parameters, and pulse width modulation technology is used to convert these parameters into control signals acceptable to the vibration motor; Obtaining current working status information and characteristic parameters of the audio signal as input to the intelligent power management algorithm; By analyzing this information, the optimal working power required by the current vibration motor can be determined.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention reduces the delay of audio signal processing and vibration motor response through real-time signal processing and closed-loop control optimization, so that the vibration motor can generate tactile feedback synchronously with the audio signal, avoiding the problem of response lag, providing users with a more timely and accurate tactile experience, and enhancing immersion and interactivity; 2. The present invention adopts multi-feature fusion and fine mapping technology, which can produce corresponding vibration effects according to the different frequencies and intensities of audio signals, better restore complex sound effect changes, overcome the limitation of the single frequency band response of the existing technology, and make the vibration feedback richer and more delicate, and more closely match the audio content, thereby enhancing the user's perception and understanding of the audio content.

[0019] 3. The present invention implements intelligent power management and dynamically adjusts the working power of the vibration motor according to actual needs, thereby avoiding unnecessary energy waste and improving the energy efficiency of the vibration motor. At the same time, if a low-power audio processing chip and a digital signal processing module are used, the overall power consumption will be further reduced, making it more suitable for use in scenarios with strict requirements on energy consumption, such as portable devices, thereby extending the use time and battery life of the device.

[0020] 4. The present invention utilizes the Kalman filter algorithm to filter the response state of the vibration motor to obtain a stable state estimate, and then combines it with the PID control algorithm for fine-tuning to form a closed-loop control, thereby enhancing the adaptability to various interferences and changes, improving the stability and reliability of the vibration motor, ensuring the accuracy and consistency of the vibration effect, and providing users with a more stable and reliable tactile feedback experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of a method for controlling a rhythmic vibration motor according to Example 1; Figure 2 This is a framework diagram of a music vibration motor control system according to Example 2. DETAILED DESCRIPTION

[0022] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Example 1 like Figure 1 As shown, a rhythm vibration motor control method comprises the following steps: S1, extracting the frequency and volume change characteristics in the audio signal, and passing these characteristic data to the digital signal processing module for subsequent processing; S2, removes noise from audio signals and enhances key frequency components through adaptive filtering and signal enhancement technology; S3, converting the frequency and intensity of the audio signal into corresponding vibration frequency and amplitude parameters according to the enhanced audio characteristics, and generating a driving signal for controlling the vibration motor; S4, the audio processing chip receives the vibration control signal generated by the digital signal processing module, and adjusts the working voltage and current of the vibration motor in real time through the power regulation circuit; S5. In the driving circuit of the vibration motor, the response state of the vibration motor is detected in real time, and the driving signal is fine-tuned; S6. Dynamically adjust the working power of the vibration motor according to the working state of the vibration motor and the characteristics of the audio signal.

[0024] Furthermore, the process of extracting the frequency and volume change characteristics in the audio signal in step S1 is specifically as follows: Acquire an audio signal to be processed, preprocess the audio signal, and obtain a preprocessed audio signal; Perform spectrum analysis on the preprocessed audio signal, use the fast Fourier transform algorithm to convert the time domain signal into the frequency domain signal, and obtain the spectrum characteristics of the audio signal; According to the frequency spectrum characteristics, the frequency characteristics of the audio signal are extracted to obtain a frequency characteristic vector; Performing rhythm detection on the preprocessed audio signal, using the autocorrelation function algorithm to calculate the rhythm period of the audio signal, and obtaining the rhythm characteristics of the audio signal; According to the rhythm features, the volume change features of the audio signal are extracted to obtain a volume change feature vector; The frequency feature vector and the volume change feature vector are fused and the comprehensive feature vector of the audio signal is obtained by feature splicing. The specific process can be described as follows: first, a 10-second audio signal is obtained, low-pass filtered to remove high-frequency noise, and the signal amplitude is normalized to the range of [-1, 1]; Then, the fast Fourier transform algorithm is used to perform spectrum analysis on the preprocessed audio signal to obtain the spectrum characteristics of the signal, where the frequency resolution is set to 1Hz. The fundamental frequency and the first three overtone frequencies of the audio signal are extracted according to the spectrum characteristics to form a frequency feature vector. Then, the autocorrelation function algorithm is used to detect the rhythm of the audio signal and calculate the rhythm period. If the rhythm period is greater than 0.5 seconds, it is judged as a slow rhythm, and if it is less than 0.5 seconds, it is judged as a fast rhythm. The volume change features are extracted based on the rhythm features, including the average volume and the volume standard deviation, to form a volume change feature vector. The frequency feature vector and the volume change feature vector are concatenated to obtain a 12-dimensional comprehensive feature vector, and the comprehensive feature vector is classified using the support vector machine algorithm. If the confidence level is greater than 0.8, it is determined to be a music signal, otherwise it is determined to be a non-music signal. For music signals, their frequencies are mapped to vibration frequencies in the range of 20Hz-200Hz, and their volumes are mapped to vibration amplitudes of 0.5G-2G to generate a PWM drive signal for controlling the vibration motor. Finally, the PWM signal is passed to the GPIO interface of the lower computer to control the vibration motor to vibrate at the specified frequency and amplitude to achieve the tactile feedback effect of the audio signal.

[0025] Furthermore, the process of enhancing the key frequency in step S2 is specifically as follows: According to the received audio feature data, the audio signal is processed using an adaptive filtering algorithm, and the filter parameters are adaptively adjusted to dynamically adapt to the changes in the audio signal to achieve noise removal; Through frequency domain analysis technology, the filtered audio signal is analyzed to identify the key frequency components that have a greater impact on the vibration effect; Based on the identified key frequency components, a signal enhancement algorithm is used to selectively amplify these frequency components; The process can be described as follows. Specifically, in the adaptive filtering process, the LMS (least mean square) algorithm is used, the filter order is set to 128, the step size is 0.01, and the error between the output signal and the expected signal is minimized by continuously adjusting the filter coefficient, thereby achieving noise removal; By performing a 1024-point FFT transformation on the filtered audio signal, a spectrum diagram is obtained, and key frequency components with energy concentrated in the 500Hz-2kHz frequency band are identified. These key frequency components are selectively amplified by 6dB to highlight the key information in the vibration effect. Through a 1024-point IFFT transformation, the enhanced frequency domain signal is restored to a time domain waveform as the optimized audio feature data; According to the optimized audio features, a linear mapping algorithm is used to map the frequency range of 500Hz-2kHz to the operating frequency range of the vibration motor, 50Hz-200Hz, and the intensity of the audio signal is mapped to a vibration amplitude value between 0-1 to generate a PWM drive signal for controlling the vibration motor. By adjusting the duty cycle and frequency of the PWM signal in real time, the vibration motor is controlled to produce a vibration effect that matches the audio signal, the delay is controlled within 20ms, and a mapping table of audio features and vibration parameters is established to achieve automatic conversion from audio signals to vibration signals, and the conversion error is controlled within 5%; By collecting acceleration sensor data and subjective scores from users during use, the vibration effect is evaluated, and key parameters such as vibration frequency, amplitude, and duration are extracted. These parameters are compared with the preset quality experience threshold, and the algorithm parameters of the digital signal processing module are dynamically adjusted according to the deviation value, such as adjusting the step size of the adaptive filter and the amplification factor of the signal enhancement, so as to achieve continuous optimization of the vibration effect and enhance the user's interactive experience.

[0026] Furthermore, the process of generating the driving signal for controlling the vibration motor in step S3 is specifically as follows: Performing time-domain synthesis on the enhanced audio signal and restoring it to a time-domain waveform signal as optimized audio feature data; According to the optimized audio feature data, the frequency and intensity of the audio signal are converted into corresponding vibration frequency and amplitude parameters through frequency mapping and amplitude mapping algorithms to generate a driving signal for controlling the vibration motor; The pulse width modulation technology is used to convert the driving signal into a control signal acceptable to the vibration motor; The process can be described as follows. Specifically, when establishing the frequency mapping table and the amplitude mapping table, the audio frequency range of 20Hz-20kHz can be divided into multiple frequency bands, each frequency band corresponds to a vibration frequency, for example, 20-100Hz is mapped to a vibration frequency of 10-50Hz, 100-500Hz is mapped to a vibration frequency of 50-100Hz, etc. At the same time, the amplitude range of the audio signal can be divided into multiple levels, each level corresponds to an amplitude value, for example, -60dB to -30dB is mapped to an amplitude of 20%, -30dB to 0dB is mapped to an amplitude of 50%, etc.; When preprocessing audio signals, adaptive filtering algorithms, such as the least mean square error (LMS) algorithm, can be used to minimize the error by continuously adjusting the filter coefficients to achieve dynamic noise removal. Frequency domain analysis can use the fast Fourier transform (FFT) algorithm to convert time domain signals into frequency domain signals and identify key frequency components with concentrated energy. When selectively amplifying these key frequency components, a bandpass filter can be used to amplify the signal within the target frequency range by 1.5-2 times, while suppressing other frequency components. According to the frequency mapping table and the amplitude mapping table, the optimized audio feature data is converted into vibration parameters. For example, a 500Hz, -20dB audio signal is converted into a 100Hz, 50% amplitude vibration parameter. When generating a driving signal, the pulse width modulation (PWM) technology can be used to convert the amplitude parameter into a duty cycle and the frequency parameter into a period to generate a corresponding square wave signal. The generated control signal is output to the vibration motor to realize the conversion of the audio signal into the vibration signal. By collecting user experience data and objective measurement indicators such as vibration intensity and frequency response, machine learning algorithms are used to continuously optimize the parameters of the digital signal processing module to improve the quality of the vibration effect.

[0027] Furthermore, the process of converting the frequency and intensity of the audio signal into corresponding vibration frequency and amplitude parameters through the frequency mapping and amplitude mapping algorithms is specifically as follows: According to the frequency and amplitude characteristics of the audio signal, a frequency mapping table and an amplitude mapping table are established to convert the audio characteristics into vibration parameters; Preprocess the audio signal, use an adaptive filtering algorithm to process the audio signal, and adaptively adjust the filter parameters to dynamically adapt to changes in the audio signal, remove noise, and obtain an enhanced audio feature signal; According to the frequency mapping table, the frequency of the optimized audio feature data is converted into corresponding vibration frequency parameters; According to the amplitude mapping table, the amplitude of the optimized audio feature data is converted into a corresponding amplitude parameter; The converted vibration frequency and amplitude parameters are combined to subsequently generate a driving signal for controlling the vibration motor; The process can be described as follows. Specifically, after the audio processing chip receives the vibration control signal output by the digital signal processing module, it extracts the intensity change information of the audio signal in different frequency bands by performing Fourier transform on the signal, and uses the support vector machine algorithm to take the low-frequency, medium-frequency and high-frequency intensities of the audio signal as input features to establish a hyperplane in a three-dimensional space, and maps the audio signal intensity to the working voltage and current parameters of the vibration motor to obtain a mapping model; During audio playback, the audio signal is sampled every 10 milliseconds, and the audio intensity feature vector at the current moment is extracted and input into the trained support vector machine model to calculate the corresponding operating voltage and current values ​​of the vibration motor, such as 3.7V for voltage and 200mA for current. These parameter values ​​are transmitted to the power regulation circuit in real time, and the supply voltage and current of the vibration motor are dynamically changed through PWM pulse width modulation to synchronize the vibration intensity with the strength changes of the audio signal. If the intensity of the audio signal changes by more than 20% within 1 second, the recalculation of the vibration parameters is triggered, and the working status of the vibration motor is updated in the next sampling cycle to ensure that the vibration effect is synchronized with the audio playback in real time. The user's subjective rating of the vibration effect and objective parameters such as the energy consumption and temperature of the vibration motor are continuously collected, and the optimal combination of vibration parameters is found through cluster analysis, and used to retrain the support vector machine model to continuously improve the expressiveness of the vibration effect and user experience.

[0028] Furthermore, the process of adjusting the working voltage and current of the vibration motor in real time in step S4 is specifically as follows: The audio processing chip is used to receive the vibration control signal output by the digital signal processing module, and the audio signal intensity change information is extracted; Based on the extracted audio signal strength change information, a support vector machine algorithm is used to establish a mapping model between audio signal strength and the working voltage and current of the vibration motor; During audio playback, the intensity change data of the audio signal is obtained in real time and input into the established mapping model; The mapping model is used to calculate the vibration motor operating voltage and current parameter values ​​that match the current audio signal strength; The calculated voltage and current parameter values ​​are output to the power regulation circuit to dynamically adjust the actual working voltage and current of the vibration motor; The process can be described as follows. Specifically, first, the frequency domain analysis technology is used to analyze the spectrum of the audio signal to identify the key frequency components that have a greater impact on the vibration effect, such as the low frequency band of 20Hz-100Hz. Then, an adaptive filtering algorithm, such as the LMS algorithm, is used to pre-process the drive signal, dynamically adjust the filter coefficient, and generate an initial drive signal. Next, the initial drive signal is input into the vibration motor drive circuit, and the response state of the vibration motor is detected in real time at a sampling frequency of 1kHz; The Kalman filter algorithm is used to filter the detected amplitude, frequency, phase and other parameters to estimate the stable state value. The estimated value is compared with the characteristic parameters of the audio signal to calculate the error signal, such as the amplitude error within ±10%; According to the error signal, the PID control algorithm is used, such as setting the proportional coefficient Kp=2.5, the integral coefficient Ki=0.8, and the differential coefficient Kd=0.1, to fine-tune the drive signal and generate an optimized drive signal; The optimized driving signal is input to the vibration motor driving circuit to control the vibration motor to vibrate at a frequency and amplitude matching the audio signal. For example, when the audio signal frequency is 50Hz and the amplitude is 2V, the vibration motor's vibration frequency is also 50Hz and the amplitude is 2V. By establishing a mapping table between audio features and vibration parameters, the automatic conversion of audio signals to vibration signals is realized, and the conversion delay is controlled within 20ms. Through user experience questionnaire scores and objective measurement indicators such as vibration frequency and amplitude, the vibration effect is evaluated and feedback is provided, and the parameters of the closed-loop control algorithm are continuously optimized. For example, the sampling period of PID control is adjusted from 1ms to 0.5ms to continuously improve the quality of the vibration effect and ensure that the synchronization error between the vibration effect and the audio signal is within ±5%.

[0029] Furthermore, the process of real-time detection of the response state of the vibration motor and fine-tuning the driving signal in step S5 is specifically as follows: Acquire characteristic parameters of the audio signal and use them as control targets of the vibration motor drive signal; According to the characteristic parameters of the audio signal, an adaptive filtering algorithm is used to pre-process the driving signal to generate an initial driving signal; Inputting the initial driving signal to the vibration motor driving circuit, and detecting the response state of the vibration motor in real time; The Kalman filter algorithm is used to filter the vibration motor response state to obtain a stable state estimation value; Compare the state estimation value with the audio signal characteristic parameters and calculate the error signal as the input of closed-loop control; According to the error signal, the PID control algorithm is used to fine-tune the drive signal to generate an optimized drive signal; The optimized driving signal is input into the vibration motor driving circuit to control the vibration frequency and amplitude of the vibration motor to produce a vibration effect matching the audio signal; By establishing a mapping relationship between audio features and vibration parameters, the automatic conversion of audio signals to vibration signals is realized; Evaluate and provide feedback on vibration effects, and continuously optimize the parameters of the closed-loop control algorithm through user experience data and objective measurement indicators; The process can be described as follows. Specifically, the current operating temperature obtained by the sensor is 65°C, the CPU occupancy rate is 80%, and the frequency of the audio signal collected is 1kHz and the amplitude is 2.5V. The intelligent power management algorithm determines that the current optimal working power is 1.2W based on the above parameters through the table lookup method. The algorithm controls the power management chip to adjust the working voltage of the vibration motor to 3.6V and the current is limited to 0.33A. The vibration frequency and amplitude of the vibration motor are monitored in real time. It is found that the current vibration frequency is 90Hz and the amplitude is 1.8g, which is lower than the preset vibration intensity threshold of 2g. Therefore, the operating voltage of the vibration motor is increased to 3.8V and the current is increased to 0.36A, so that the vibration frequency reaches 95Hz and the amplitude reaches 2.1g, which meets the vibration intensity requirements. When the temperature drops to 60℃ and the CPU occupancy rate drops to 75%, the intelligent power management algorithm reduces the operating power of the vibration motor to 1.1W according to the new state parameters to reduce energy consumption. The audio signal is processed by a 6th-order Butterworth low-pass filter, and the cutoff frequency is adaptively adjusted to 800Hz, effectively removing high-frequency noise. A 2048-point FFT transform is performed on the filtered signal, identifying that the energy is concentrated near the two frequencies of 120Hz and 350Hz, and increasing the amplitude of these two frequency components by 1.5 times, thereby enhancing the low-frequency and mid-frequency components in the vibration effect. The frequency domain signal is restored to a time domain waveform through IFFT transformation, and the audio feature data is updated. According to the optimized audio features, the vibration frequency of the vibration motor is dynamically adjusted between 80-130Hz and the amplitude between 1.5-2.5g, realizing real-time conversion and matching of audio signals to vibration signals.

[0030] Furthermore, the process of dynamically adjusting the working power of the vibration motor in step S6 is specifically as follows: Obtaining current working status information and characteristic parameters of the audio signal, and using them as inputs of the intelligent power management algorithm; By analyzing the working status information and audio signal characteristic parameters, the optimal working power required by the current vibration motor is determined; Dynamically adjust the actual working power of the vibration motor according to the optimal working power determined by the intelligent power management algorithm; In the process of adjusting the working power of the vibration motor, real-time monitoring is performed to determine whether the vibration effect reaches the preset vibration intensity threshold; Specifically, if the vibration effect does not reach the preset threshold, the working power of the vibration motor is appropriately increased until the vibration effect meets the requirements; if the vibration effect has reached or exceeded the preset threshold, the current working power of the vibration motor is maintained unchanged to reduce energy consumption; Continuously tracks changes in working status and audio signal characteristics, and adjusts the intelligent power management algorithm in real time to optimize vibration effect and energy consumption balance.

[0031] This embodiment realizes the precise extraction and conversion of audio signal features, generates a vibration control signal sequence that is highly matched with the audio signal, significantly improves the response speed and synchronization of the vibration motor, enhances the richness and delicacy of the vibration feedback, and reduces system power consumption through intelligent power management, providing users with a more immersive and interactive experience. It is particularly suitable for consumer electronics and entertainment devices such as smart watches, game controllers, and audio equipment, and effectively improves the user experience and market competitiveness of the product.

[0032] Example 2 like Figure 2 As shown, this embodiment provides a music vibration motor control system, which is used to implement the above-mentioned music vibration motor control method, including an audio processing chip and a digital signal processing module; The audio processing chip receives the vibration control signal generated by the digital signal processing module and extracts the audio signal intensity change information therefrom; According to the extracted audio signal strength change information, a mapping model between the audio signal strength and the working voltage and current of the vibration motor is established to realize the conversion of the audio signal strength to the working voltage and current parameters of the vibration motor; During audio playback, the intensity change data of the audio signal is obtained in real time, and the operating voltage and current parameter values ​​of the vibration motor that match the current audio signal intensity are calculated; The calculated voltage and current parameter values ​​are output to the power regulation circuit, thereby dynamically adjusting the actual working voltage and current of the vibration motor; Receive feedback information from the vibration motor drive circuit.

[0033] Furthermore, the digital signal processing module extracts frequency and volume change characteristics from the audio signal to be processed, obtains a frequency feature vector and a volume change feature vector, and transmits these feature data to the audio processing chip; Process the audio signal, adaptively adjust the filter parameters, dynamically adapt to the changes of the audio signal, and achieve noise removal; The key frequency components are identified through frequency domain analysis technology, and these frequency components are selectively amplified using signal enhancement algorithms; Performing time-domain synthesis on the enhanced audio signal to restore it to a time-domain waveform signal; According to the optimized audio feature data, the frequency and intensity of the audio signal are converted into corresponding vibration frequency and amplitude parameters, and pulse width modulation technology is used to convert these parameters into control signals acceptable to the vibration motor; Obtaining current working status information and characteristic parameters of the audio signal as input to the intelligent power management algorithm; By analyzing this information, the optimal working power required by the current vibration motor can be determined.

[0034] This embodiment realizes in-depth processing and precise control of audio signals through the collaborative work of the audio processing chip and the digital signal processing module. The digital signal processing module uses wavelet analysis to extract the time-frequency domain characteristics of the audio signal, and generates a vibration control signal sequence containing different frequency bands, intensities and durations through threshold segmentation and mapping algorithms. The audio processing chip dynamically adjusts the operating voltage and current of the vibration motor according to these signals to ensure the synchronization and matching between the vibration effect and the audio signal, and receives feedback information for real-time optimization. This not only improves the response speed and stability of the system, but also enhances the richness and delicacy of the vibration feedback, effectively reduces power consumption, and provides users with a more immersive and interactive experience.

[0035] The specific embodiments of the invention are described in detail above, but they are only examples. The present invention is not limited to the specific embodiments described above. Those skilled in the art should understand that the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A rhythm vibration motor control method, characterized in that: The following steps are involved: S1, extracting the frequency and volume change characteristics in the audio signal, and passing these characteristic data to the digital signal processing module for subsequent processing; S2, removes noise from audio signals and enhances key frequency components through adaptive filtering and signal enhancement technology; S3, converting the frequency and intensity of the audio signal into corresponding vibration frequency and amplitude parameters according to the enhanced audio characteristics, and generating a driving signal for controlling the vibration motor; S4, the audio processing chip receives the vibration control signal generated by the digital signal processing module, and adjusts the working voltage and current of the vibration motor in real time through the power regulation circuit; S5. In the driving circuit of the vibration motor, the response state of the vibration motor is detected in real time, and the driving signal is fine-tuned; S6. Dynamically adjust the working power of the vibration motor according to the working state of the vibration motor and the characteristics of the audio signal.

2. The method for controlling a musical vibration motor according to claim 1, characterized in that: The process of extracting the frequency and volume change characteristics in the audio signal in step S1 is specifically as follows: Acquire an audio signal to be processed, preprocess the audio signal, and obtain a preprocessed audio signal; Perform spectrum analysis on the preprocessed audio signal, use the fast Fourier transform algorithm to convert the time domain signal into the frequency domain signal, and obtain the spectrum characteristics of the audio signal; According to the frequency spectrum characteristics, the frequency characteristics of the audio signal are extracted to obtain a frequency characteristic vector; Performing rhythm detection on the preprocessed audio signal, using the autocorrelation function algorithm to calculate the rhythm period of the audio signal, and obtaining the rhythm characteristics of the audio signal; According to the rhythm features, the volume change features of the audio signal are extracted to obtain a volume change feature vector; The frequency feature vector and the volume change feature vector are fused and the comprehensive feature vector of the audio signal is obtained by feature splicing.

3. The method for controlling a musical vibration motor according to claim 1, characterized in that: The process of enhancing the key frequency in step S2 is specifically as follows: According to the received audio feature data, the audio signal is processed using an adaptive filtering algorithm, and the filter parameters are adaptively adjusted to dynamically adapt to the changes in the audio signal to achieve noise removal; Through frequency domain analysis technology, the filtered audio signal is analyzed to identify the key frequency components that have a greater impact on the vibration effect; Based on the identified key frequency components, a signal enhancement algorithm is used to selectively amplify these frequency components.

4. The method for controlling a musical vibration motor according to claim 1, characterized in that: The process of generating the driving signal for controlling the vibration motor in step S3 is specifically as follows: Performing time-domain synthesis on the enhanced audio signal and restoring it to a time-domain waveform signal as optimized audio feature data; According to the optimized audio feature data, the frequency and intensity of the audio signal are converted into corresponding vibration frequency and amplitude parameters through frequency mapping and amplitude mapping algorithms to generate a driving signal for controlling the vibration motor; Pulse width modulation technology is used to convert the drive signal into a control signal acceptable to the vibration motor.

5. A rhythm vibration motor control method according to claim 4, characterized in that: The process of converting the frequency and intensity of the audio signal into corresponding vibration frequency and amplitude parameters through the frequency mapping and amplitude mapping algorithms is specifically as follows: According to the frequency and amplitude characteristics of the audio signal, a frequency mapping table and an amplitude mapping table are established to convert the audio characteristics into vibration parameters; Preprocess the audio signal, use an adaptive filtering algorithm to process the audio signal, and adaptively adjust the filter parameters to dynamically adapt to changes in the audio signal, remove noise, and obtain an enhanced audio feature signal; According to the frequency mapping table, the frequency of the optimized audio feature data is converted into corresponding vibration frequency parameters; According to the amplitude mapping table, the amplitude of the optimized audio feature data is converted into a corresponding amplitude parameter; The converted vibration frequency and amplitude parameters are combined to subsequently generate a drive signal for controlling the vibration motor.

6. The method for controlling a musical vibration motor according to claim 1, characterized in that: The process of adjusting the working voltage and current of the vibration motor in real time in step S4 is specifically as follows: The audio processing chip is used to receive the vibration control signal output by the digital signal processing module, and the audio signal intensity change information is extracted; Based on the extracted audio signal strength change information, a support vector machine algorithm is used to establish a mapping model between audio signal strength and the working voltage and current of the vibration motor; During audio playback, the intensity change data of the audio signal is obtained in real time and input into the established mapping model; The mapping model is used to calculate the vibration motor operating voltage and current parameter values ​​that match the current audio signal strength; The calculated voltage and current parameter values ​​are output to the power regulation circuit to dynamically adjust the actual working voltage and current of the vibration motor.

7. The method for controlling a musical vibration motor according to claim 1, characterized in that: The process of real-time detection of the response state of the vibration motor and fine-tuning the driving signal in step S5 is specifically as follows: Acquire characteristic parameters of the audio signal and use them as control targets of the vibration motor drive signal; According to the characteristic parameters of the audio signal, an adaptive filtering algorithm is used to pre-process the driving signal to generate an initial driving signal; Inputting the initial driving signal to the vibration motor driving circuit, and detecting the response state of the vibration motor in real time; The Kalman filter algorithm is used to filter the vibration motor response state to obtain a stable state estimation value; Compare the state estimation value with the audio signal characteristic parameters and calculate the error signal as the input of closed-loop control; According to the error signal, the PID control algorithm is used to fine-tune the drive signal to generate an optimized drive signal; The optimized driving signal is input into the vibration motor driving circuit to control the vibration frequency and amplitude of the vibration motor to produce a vibration effect matching the audio signal; By establishing a mapping relationship between audio features and vibration parameters, the automatic conversion of audio signals to vibration signals is realized; Evaluate and provide feedback on vibration effects, and continuously optimize the parameters of the closed-loop control algorithm through user experience data and objective measurement indicators.

8. The method for controlling a musical vibration motor according to claim 1, characterized in that: The process of dynamically adjusting the working power of the vibration motor in step S6 is specifically as follows: Obtaining current working status information and characteristic parameters of the audio signal, and using them as inputs of the intelligent power management algorithm; By analyzing the working status information and audio signal characteristic parameters, the optimal working power required by the current vibration motor is determined; Dynamically adjust the actual working power of the vibration motor according to the optimal working power determined by the intelligent power management algorithm; In the process of adjusting the working power of the vibration motor, real-time monitoring is performed to determine whether the vibration effect reaches the preset vibration intensity threshold; Specifically, if the vibration effect does not reach the preset threshold, the working power of the vibration motor is appropriately increased until the vibration effect meets the requirement; If the vibration effect has reached or exceeded the preset threshold, the current operating power of the vibration motor is maintained unchanged to reduce energy consumption; Continuously tracks changes in working status and audio signal characteristics, and adjusts the intelligent power management algorithm in real time to optimize vibration effect and energy consumption balance.

9. A musical vibration motor control system, characterized in that: Including audio processing chip and digital signal processing module; The audio processing chip receives the vibration control signal generated by the digital signal processing module and extracts the audio signal intensity change information therefrom; According to the extracted audio signal strength change information, a mapping model between the audio signal strength and the working voltage and current of the vibration motor is established to realize the conversion of the audio signal strength to the working voltage and current parameters of the vibration motor; During audio playback, the intensity change data of the audio signal is obtained in real time, and the operating voltage and current parameter values ​​of the vibration motor that match the current audio signal intensity are calculated; The calculated voltage and current parameter values ​​are output to the power regulation circuit, thereby dynamically adjusting the actual working voltage and current of the vibration motor; Receive feedback information from the vibration motor drive circuit.

10. The musical vibration motor control system according to claim 9, characterized in that: The digital signal processing module extracts frequency and volume change characteristics from the audio signal to be processed, obtains a frequency feature vector and a volume change feature vector, and transmits these feature data to the audio processing chip; Process the audio signal, adaptively adjust the filter parameters, dynamically adapt to the changes of the audio signal, and achieve noise removal; The key frequency components are identified through frequency domain analysis technology, and these frequency components are selectively amplified using signal enhancement algorithms; Performing time-domain synthesis on the enhanced audio signal to restore it to a time-domain waveform signal; According to the optimized audio feature data, the frequency and intensity of the audio signal are converted into corresponding vibration frequency and amplitude parameters, and pulse width modulation technology is used to convert these parameters into control signals acceptable to the vibration motor; Obtaining current working status information and characteristic parameters of the audio signal as input to the intelligent power management algorithm; By analyzing this information, the optimal working power required by the current vibration motor can be determined.

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