WO2023116133A1 - 基于马达的振感调整方法、设备和计算机可读存储介质 - Google Patents

基于马达的振感调整方法、设备和计算机可读存储介质 Download PDF

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WO2023116133A1
WO2023116133A1 PCT/CN2022/124546 CN2022124546W WO2023116133A1 WO 2023116133 A1 WO2023116133 A1 WO 2023116133A1 CN 2022124546 W CN2022124546 W CN 2022124546W WO 2023116133 A1 WO2023116133 A1 WO 2023116133A1
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motor
displacement
predicted
predicted displacement
audio signal
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PCT/CN2022/124546
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English (en)
French (fr)
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刘钰佳
刘兵
杨鑫峰
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歌尔股份有限公司
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
    • H02P23/14—Estimation or adaptation of motor parameters, e.g. rotor time constant, flux, speed, current or voltage
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/06—Linear motors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

Definitions

  • the present application relates to the technical field of linear motors, in particular to a motor-based vibration adjustment method, device and computer-readable storage medium.
  • linear Resonant Actuator LRA
  • LRA Linear Resonant Actuator
  • the audio signal is usually used to directly drive the linear motor, which may cause the motor to have a weak high-frequency vibration and easy to sound, and the low-frequency vibration is not strong at a low volume.
  • the method of increasing the voltage in the time domain is usually used, but this method cannot guarantee the richness of the vibration of the motor, and the overall vibration intensity is still weak.
  • the present application provides a method, device, and computer-readable storage medium for adjusting vibration perception based on a motor, aiming at solving the technical problem of weak vibration perception when an audio signal is used to directly drive a linear motor.
  • the present application provides a motor-based vibration adjustment method, which includes the following steps:
  • the displacement of the motor is predicted by frequency band to obtain the predicted displacement
  • a drive voltage is synthesized according to the compressed and limited predicted displacement and model parameters of the motor to drive the motor to vibrate.
  • filtering out the ultra-low frequency signal and the sound frequency band signal in the audio signal through preprocessing
  • Displacement prediction is performed on the plurality of sub-band audio signals to obtain predicted displacements.
  • the predicted displacement is calculated according to the displacement voltage transfer function and the output voltage of the sub-band audio signal.
  • the compressed predicted displacements are combined, and the combined predicted displacements are overall limited according to the maximum vibration space reserved by the linear motor.
  • the digital signal is compressed in segments according to a preset compression formula to obtain a compressed predicted displacement.
  • the preset compression formula is:
  • input is a digital signal
  • output is a predicted displacement after compression
  • a mechanical end model of voltage synthesis is constructed based on the model parameters of the motor
  • a drive voltage is synthesized from the predicted displacement after compression and confinement and the mechanical end model.
  • the present application also proposes a motor-based shock adjustment device, which includes a memory, a processor, and a motor-based device stored in the memory and operable on the processor.
  • a vibration adjustment program, the motor-based vibration adjustment method is implemented when the motor-based vibration adjustment program is executed by the processor.
  • the present application also proposes a computer-readable storage medium, on which a motor-based vibration adjustment program is stored, and when the motor-based vibration adjustment program is executed by a processor, the Motor-based vibration adjustment method.
  • the displacement of the motor is predicted in sub-frequency bands to obtain the predicted displacement; then the predicted displacement is compressed and limited; and synthesized according to the compressed and limited predicted displacement and the model parameters of the motor driving voltage.
  • the present application does not directly drive the linear motor with the audio signal, but synthesizes the driving voltage according to the audio signal to drive the linear motor.
  • the predicted displacement is compressed and limited, and the driving voltage is synthesized according to the compressed and limited predicted displacement to drive the linear motor to vibrate, which not only ensures the richness of the vibration of the linear motor and improves the vibration feeling, but also ensures that the linear motor is in Vibration within the maximum allowable space avoids damage to the motor or noise.
  • FIG. 1 is a schematic diagram of a module structure of a motor-based vibration adjustment method according to an embodiment of the present application
  • FIG. 2 is a flow chart of a motor-based vibration adjustment method according to an embodiment of the present application
  • FIG. 3 is an example diagram of a motor-based vibration adjustment method according to an embodiment of the present application.
  • FIG. 4 is an example of a motor-based vibration adjustment method according to an embodiment of the present application.
  • FIG. 5 is a flowchart of a motor-based vibration adjustment method according to an embodiment of the present application.
  • FIG. 6 is a flowchart of a motor-based vibration adjustment method according to an embodiment of the present application.
  • FIG. 1 is a schematic diagram of a hardware structure of a motor-based vibration adjustment device provided in various embodiments of the present application.
  • the motor-based vibration adjustment device includes an execution module 01, a memory 02, a processor 03, a battery system and other components.
  • the device shown in FIG. 1 may also include more or fewer components than those shown in the illustration, or combine some components, or arrange different components.
  • the processor 03 is respectively connected to the memory 02 and the execution module 01, the memory 02 stores a motor-based vibration adjustment program, and the motor-based vibration adjustment program is executed by the processor 03 at the same time.
  • Executing module 01 which can perform frequency band displacement prediction according to the received audio signal to obtain the predicted displacement, compress and limit the predicted displacement, and synthesize the driving voltage according to the compressed and limited predicted displacement and the model parameters of the motor, and at the same time
  • the above information is fed back and sent to the processor 03 .
  • Memory 02 can be used to store software programs and various data.
  • the memory 02 can mainly include a program storage area and a data storage area, wherein the program storage area can store the operating system, at least one application program required by a function, etc.; the data storage area can store data or information created according to the use of the IoT terminal wait.
  • the memory 02 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.
  • Processor 03 is the control center of the processing platform. It uses various interfaces and lines to connect various parts of the entire Internet of Things terminal, and runs or executes software programs and/or modules stored in memory 02, and calls stored in memory 02. data, perform various functions of the IoT terminal and process data, so as to perform overall monitoring of the motor-based vibration adjustment equipment.
  • the processor 03 may include one or more processing units; preferably, the processor 03 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application programs, etc., and the modem
  • the processor mainly handles wireless communication. It can be understood that the foregoing modem processor may not be integrated into the processor 03 .
  • linear Resonant Actuator LRA
  • LRA Linear Resonant Actuator
  • the audio signal is usually used to directly drive the linear motor, which may cause the motor to have a weak high-frequency vibration and easy to sound, and the low-frequency vibration is not strong at a low volume.
  • the method of increasing the voltage in the time domain is usually used, but this method cannot guarantee the richness of the vibration of the motor, and the overall vibration intensity is still weak.
  • the present application proposes a motor-based vibration adjustment method.
  • the motor-based vibration adjustment method includes :
  • Step S100 performing frequency band displacement prediction according to the received audio signal to obtain predicted displacement
  • the motor multi-band vibration enhancement adjustment method based on displacement protection proposed in this design is applied to the linear motor, which is an adjustment method for the vibration displacement of the linear motor.
  • the audio signal is pre-processed first, wherein the pre-processing step is to perform high-pass filtering on the audio signal to remove ultra-low frequency signals, and then perform low-pass filtering on the audio signal to remove motor sound frequency band signals.
  • the received audio signal can be the sound effect actually output by the game application in the terminal device installed with the linear motor, or it can be a broadband signal customized and designed according to the AR/VR/game scene, and stored and input in audio format.
  • the preprocessed audio signal is frequency-divided and filtered to obtain a plurality of sub-band audio signals, and the displacement of the motor is predicted according to the output voltage of the sub-band audio signals to obtain the predicted displacement.
  • the displacement prediction information is the prediction of the displacement of multiple sub-band audio signals.
  • the displacement prediction includes constructing a displacement model according to relevant parameters, and then performing displacement prediction on multiple sub-band audio signals according to the constructed displacement model.
  • the displacement refers to the displacement of the motor vibration.
  • Step S200 compressing and limiting the predicted displacement
  • the predicted displacement needs to be compressed and limited in sequence.
  • the specific way of compression is set in advance by those skilled in the art, and the way of compression is different for audio signals of different frequency bands.
  • the maximum preset value and the minimum preset value of the vibration range of each frequency band displacement are input into the dynamic range compression module by those skilled in the art, and the vibration range smaller than the minimum preset value of the frequency band where the sub-band audio signal is located
  • the small predicted displacement signal is amplified according to the dynamic range compression rate, and the large predicted displacement signal greater than the maximum preset value of the frequency band where the sub-band audio signal is located is reduced according to the dynamic range compression rate; in order to ensure the richness of motor vibration and improve the vibration feeling.
  • the sub-band audio signals are combined, and the combined audio signals are observed, and the overall displacement is restricted to ensure that the predicted displacement is within the maximum spatial range of the motor.
  • the overall limitation is specifically to enlarge or reduce the predicted displacement according to a certain ratio, so as to ensure that the motor will not touch the external casing during the vibration process.
  • Step S300 synthesizing a driving voltage according to the compressed and limited predicted displacement and the model parameters of the motor to drive the motor to vibrate.
  • the driving voltage can be synthesized according to the compressed and limited predicted displacement and the model parameters of the motor.
  • the model parameters of the motor include vibrator mass m, magnetic field strength Bl, spring stiffness coefficient Kms, damping coefficient Rms, and coil DC resistance Re.
  • the compressed and restricted displacement information and model parameters are input into the vibration dynamic end model modeling module to calculate the discrete time velocity model and the discrete model of displacement to force, and finally the model parameters of the motor, force, velocity and other information are input to the driving voltage synthesizing module to synthesize the driving voltage.
  • the vibration of the linear motor is driven by the synthesized driving voltage.
  • the audio signal is processed through a series of algorithms to obtain the driving voltage, and the power of the driving voltage is amplified to drive the motor to vibrate, resulting in enhanced broadband vibration feedback.
  • the predicted displacement is compressed and limited, and the driving voltage is synthesized according to the compressed and limited predicted displacement to drive the linear motor to vibrate, which not only ensures the richness of the vibration of the linear motor and improves the vibration feeling, but also ensures that the linear motor is in Vibration within the maximum allowable space avoids damage to the motor or noise.
  • the step of obtaining the predicted displacement by performing frequency band displacement prediction according to the received audio signal includes:
  • the audio signal is first preprocessed, specifically, the audio signal is subjected to high-pass filtering to remove the ultra-low frequency signal, and then the audio signal is subjected to low-pass filtering to remove the motor sound frequency band signal.
  • Displacement prediction is performed on the plurality of sub-band audio signals to obtain predicted displacements.
  • frequency division filtering is performed on the preprocessed audio signal to obtain multiple subband audio signals.
  • the various parameters of the filter used in frequency division filtering such as the cut-off frequency, are set in advance by those skilled in the art according to the vibration perception requirements to be improved, wherein the vibration perception requirements to be enhanced It can be the frequency band or gain that needs to improve the vibration feeling.
  • low-pass filtering, band-pass filtering, and high-pass filtering are performed on the input audio signal in sequence to obtain multiple sub-band audio signals BD1, BD2...BDn, and the sub-band output voltages are u1, u2... un.
  • the step of performing displacement prediction on the plurality of sub-band audio signals to obtain the predicted displacement comprises:
  • the predicted displacement is calculated according to the displacement voltage transfer function and the output voltage of the sub-band audio signal.
  • the model parameters of the motor are known: vibrator mass m, magnetic field strength B1, spring stiffness coefficient Kms, damping coefficient Rms, and coil DC resistance Re
  • the displacement prediction is the output displacement voltage transfer function
  • the displacement voltage transfer function can be converted into a discretized transfer function of the displacement voltage.
  • the displacement prediction formula can be obtained by formula deformation. Then, the output voltage of the sub-band audio signal obtained by sampling is substituted into the displacement prediction formula to obtain the predicted displacement of the sub-band audio signal.
  • the displacement voltage transfer function of the linear motor is:
  • the discretized transfer function is:
  • the displacement prediction formula can be further converted into a sub-band displacement prediction formula, and the sub-band displacement prediction formula is:
  • the output displacement of subband 1 ⁇ subband n is x 1 (k) ⁇ x n (k)
  • the voltage of subband 1 ⁇ subband n is expressed as u 1 (k) ⁇ un (k)
  • i 1, 2,...n
  • Ts is the sampling time
  • m is the vibrator mass
  • Bl is the magnetic field strength
  • Kms is the spring stiffness coefficient
  • Rms is the damping coefficient
  • Re is the coil DC resistance
  • x(z) is the output of the transfer function Predict displacement
  • u(z) is the input output voltage of the transfer function
  • z is the conventional coefficient of the transfer function.
  • the predicted displacement of the sub-band audio signal can be obtained.
  • the step of compressing and limiting the predicted displacement includes:
  • the compressed predicted displacements are combined, and the combined predicted displacements are overall limited according to the maximum vibration space reserved by the linear motor.
  • the maximum preset value and the minimum preset value of the vibration range of each frequency band displacement are input into the dynamic range compression module by those skilled in the art, and will be less than The small predicted displacement signal of the minimum preset value in the frequency band where the sub-band audio signal is located is amplified according to the dynamic range compression rate, and the large predicted displacement signal greater than the maximum preset value of the frequency band where the sub-band audio signal is located is reduced according to the dynamic range compression rate; to ensure that the motor The richness of vibration and can enhance the sense of vibration.
  • the sub-band audio signals are combined, and the combined audio signals are observed, and the overall displacement is restricted to ensure that the predicted displacement is within the maximum spatial range of the motor.
  • the overall limitation is to calculate the ratio of the maximum vibration space reserved by the linear motor to the maximum value of the predicted displacement, and to enlarge or reduce the overall predicted displacement according to the ratio of the maximum vibration space reserved by the linear motor to the maximum value of the predicted displacement , so as to ensure that during the vibration process of the motor, the maximum value of the predicted displacement will not exceed the maximum vibration space reserved by the linear motor, so it will not touch the outer casing.
  • the step of compressing the predicted displacement includes:
  • the digital signal is compressed in segments according to a preset compression formula to obtain a compressed predicted displacement.
  • the preset compression formula is a compression method set in advance by those skilled in the art according to preset rules, and can be adjusted according to actual needs. Since this application needs to amplify small displacement signals and reduce large displacement signals, audio signals with different displacements are compressed in different ways, so different preset compression formulas need to be used to compress audio signals with different displacements. Specifically, before compression, the predicted displacement of the sub-band audio signal corresponding to the audio signal is first converted into a digital signal, and the specific conversion method is:
  • BD is the predicted displacement
  • input is the converted digital signal.
  • the digital signals need to be segmented, and different digital signals are substituted into different preset compression formulas. Get the predicted displacement after compression.
  • the preset compression formula is set in advance by those skilled in the art according to preset rules, and can be adjusted in real time according to actual conditions.
  • the preset compression formula is:
  • input is a digital signal
  • output is a predicted displacement after compression
  • the preset compression formula is a linear piecewise function with three inflection points, and the inflection points of the function are (-15, -10) (-10,-5)(-5,-2).
  • the step of limiting the combined predicted displacement as a whole according to the maximum vibration space reserved by the linear motor includes:
  • x1, x2...xn is the predicted displacement of each sub-band audio signal. Firstly, each sub-band audio signal is combined, and then the combined sub-band The audio signal is input to the x_limiter module to limit the predicted displacement as a whole to ensure that the predicted displacement is smaller than the maximum vibration space of the motor.
  • the x_limiter module After inputting the combined sub-band audio signals to the x_limiter module, detect the maximum value xmax of the combined predicted displacement x, obtain the maximum vibration space x_lim reserved for the linear motor design, and calculate the maximum value and linear motor
  • the limiting ratio x_ratio of the reserved maximum vibration space x_lim is calculated as:
  • x_ratio xmax/x_lim.
  • the way of zooming in or zooming out as a whole is:
  • the step of synthesizing the driving voltage according to the compressed and limited predicted displacement and the model parameters of the motor includes:
  • a drive voltage is synthesized from the predicted displacement after compression and confinement and the mechanical end model.
  • a corresponding driving voltage is also synthesized according to the predicted displacement after compression and overall limiting. Furthermore, synthesizing the driving voltage requires the construction of a mechanical end model of voltage synthesis, where the mechanical end model includes a discrete model of velocity and a discretized model of displacement to force.
  • the mechanics equation is:
  • the vibration velocity equation of the voice coil is:
  • equation for driving voltage synthesis can be derived as:
  • T s is the sampling time
  • mm ms is the vibrator mass
  • Bl is the magnetic field strength
  • K ms is the spring stiffness coefficient
  • R ms is the damping coefficient
  • Re is the DC resistance of the coil
  • x is the predicted displacement of the linear motor
  • v is The vibration speed of the voice coil
  • f is the driving force of the motor
  • u is the synthesized driving voltage
  • k is the conventional coefficient.
  • the driving voltage is synthesized according to the mechanical end model.
  • the present application also proposes a motor-based shock adjustment device, which includes a memory, a processor, and a motor-based shock adjustment program stored in the memory and operable on the processor.
  • the motor-based shock The adjustment program is used to implement the methods described in various embodiments of the present application.
  • the present application also proposes a computer-readable storage medium on which a motor-based shock adjustment program is stored.
  • Described computer-readable storage medium comprises computer-readable computer-readable storage medium, and described computer-readable computer-readable storage medium can be the memory in Fig. 1, also can be as ROM (Read-Only Memory, read-only memory) )/RAM (Random Access Memory, random access memory), magnetic disk, optical disc at least one, the computer-readable storage medium includes several instructions to make an Internet of Things terminal device with a processor (can It is a mobile phone, a computer, a server, an Internet of Things terminal, or a network device, etc.) to execute the method described in each embodiment of the present application.
  • a processor can It is a mobile phone, a computer, a server, an Internet of Things terminal, or a network device, etc.

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Abstract

本申请公开了一种基于马达的振感调整方法、设备和计算机可读存储介质，所述方法包括以下步骤：根据接收的音频信号对马达进行分频段位移预测得到预测位移；对所述预测位移进行压缩和限制；根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压。通过本申请既保证了线性马达振动的丰富性并提升了振感，又能够保证线性马达在允许的最大空间范围内振动，避免了马达破损或出现杂音等情况。

Description

基于马达的振感调整方法、设备和计算机可读存储介质 技术领域
本申请涉及线性马达技术领域，具体涉及一种基于马达的振感调整方法、设备和计算机可读存储介质。
背景技术
目前，线性马达(Linear Resonant Actuator，LRA)凭借其振感强烈、丰富、清脆，能耗低等优点，已经广泛应用于消费电子的各种振动场合，包括游戏与AR(AugmentedReality，增强现实)/VR(Virtual Reality，虚拟现实)产品。
为了保证振感强度和丰富性，在宽频驱动场景，通常用音频信号直接驱动线性马达，因此可能导致马达的高频振感弱且容易发声、小音量情况下低频振感也不强，为了提升振感强调和丰富性，通常使用时域整体加大电压的方法，但该方法也无法保证提升马达的振感丰富性，并且整体振感强度仍然较弱。
发明内容
本申请提供了一种基于马达的振感调整方法、设备和计算机可读存储介质，旨在解决用音频信号直接驱动线性马达时振感弱的技术问题。
为实现上述目的，本申请提供了一种基于马达的振感调整方法，该方法包括以下步骤：
根据接收的音频信号对马达进行分频段位移预测得到预测位移；
对所述预测位移进行压缩和限制；
根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压，以驱动马达振动。
可选地，通过预处理滤除音频信号中超低频信号和发声频段信号；
对预处理后的所述音频信号进行分频滤波，得到多个子带音频信号；
对所述多个子带音频信号进行位移预测以得到预测位移。
可选地，构建输出电压为输入，预测位移为输出的位移电压传递函数；
根据所述位移电压传递函数和所述子带音频信号的输出电压计算得到预测位移。
可选地，对所述预测位移进行压缩；
对所述压缩后的预测位移进行合并，并根据线性马达预留的最大振动空间整体限制合并后的所述预测位移。
可选地，将所述音频信号对应的子带音频信号的预测位移转换为数字信号；
根据预设压缩公式将所述数字信号分段进行压缩，得到压缩后的预测位移。
可选地，预设压缩公式为：
output＝2input+20，input∈(-20dB，-15dB)
output＝input+5，input∈(-15dB，-10dB)
output＝0.6input+1，input∈(-10dB，-5dB)
output＝0.4input，input∈(-5dB，0dB)
其中，input为数字信号，output为压缩后的预测位移。
可选地，检测合并后的所述预测位移的最大值；
计算所述最大值和所述线性马达预留的最大振动空间的限制比率；
将所述预测位移按所述限制比率进行整体放大或缩小。
可选地，基于马达的模型参数构建电压合成的力学端模型；
根据压缩和限制后的所述预测位移和所述力学端模型合成驱动电压。
为实现上述目的，本申请还提出一种基于马达的震感调整设备，基于马达的震感调整设备包括存储器、处理器、以及存储在所述存储器上并可在所述处理器上运行的基于马达的震感调整程序，所述基于马达的震感调整程序被处理器执行时实现所述基于马达的振感调整方法。
为实现上述目的，本申请还提出一种计算机可读存储介质，所述计算机可读存储介质上存储有基于马达的震感调整程序，所述基于马达的震感调整程序被处理器执行时实现所述基于马达的振感调整方法。
本申请技术方案中，根据接收的音频信号对马达进行分频段位移预测得 到预测位移；然后对所述预测位移进行压缩和限制；并根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压。和现有技术相比，本申请并非用音频信号直接驱动线性马达，而是根据音频信号合成驱动电压以驱动线性马达。通过本申请对预测位移进行压缩和限制，并根据压缩和限制后的预测位移合成驱动电压以驱动线性马达振动，既保证了线性马达振动的丰富性并提升了振感，又能够保证线性马达在允许的最大空间范围内振动，避免了马达破损或出现杂音等情况。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图示出的结构获得其他的附图。
图1为本申请一实施例的基于马达的振感调整方法的模块结构示意图；
图2为本申请一实施例的基于马达的振感调整方法的流程图；
图3为本申请一实施例的基于马达的振感调整方法的实例图；
图4为本申请一实施例的基于马达的振感调整方法的实例；
图5为本申请一实施例的基于马达的振感调整方法的流程图；
图6为本申请一实施例的基于马达的振感调整方法的流程图。
具体实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
请参照图1，图1为本申请各个实施例中所提供的基于马达的震感调整设备的硬件结构示意图。所述基于马达的震感调整设备包括执行模块01、存储器02、处理器03、电池系统等部件。本领域技术人员可以理解，图1中所示出的设备还可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。其中，所述处理器03分别与所述存储器02和所述执行模块01连接，所述存储器02上存储有基于马达的震感调整程序，所述基于马达的 震感调整程序同时被处理器03执行。
执行模块01，可根据接收的音频信号进行分频段位移预测得到预测位移，对所述预测位移进行压缩和限制，并根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压，同时反馈以上信息发送给所述处理器03。
存储器02，可用于存储软件程序以及各种数据。存储器02可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序等；存储数据区可存储根据物联网终端的使用所创建的数据或信息等。此外，存储器02可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。
处理器03，是处理平台的控制中心，利用各种接口和线路连接整个物联网终端的各个部分，通过运行或执行存储在存储器02内的软件程序和/或模块，以及调用存储在存储器02内的数据，执行物联网终端的各种功能和处理数据，从而对基于马达的震感调整设备进行整体监控。处理器03可包括一个或多个处理单元；优选的，处理器03可集成应用处理器和调制解调处理器，其中，应用处理器主要处理操作系统、用户界面和应用程序等，调制解调处理器主要处理无线通信。可以理解的是，上述调制解调处理器也可以不集成到处理器03中。
本领域技术人员可以理解，图1中示出的基于马达的震感调整设备结构并不构成对设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
根据上述硬件结构，提出本申请方法各个实施例。
目前，线性马达(Linear Resonant Actuator，LRA)凭借其振感强烈、丰富、清脆，能耗低等优点，已经广泛应用于消费电子的各种振动场合，包括游戏与AR(AugmentedReality，增强现实)/VR(Virtual Reality，虚拟现实)产品。
为了保证振感强度和丰富性，在宽频驱动场景，通常用音频信号直接驱动线性马达，因此可能导致马达的高频振感弱且容易发声、小音量情况下低频振感也不强，为了提升振感强调和丰富性，通常使用时域整体加大电压的方法，但该方法也无法保证提升马达的振感丰富性，并且整体振感强度仍然 较弱。
为了解决上述问题，本申请提出了一种基于马达的振感调整方法，参照图2，在本申请基于马达的振感调整方法的第一实施例中，所述基于马达的振感调整方法包括：
步骤S100，根据接收的音频信号进行分频段位移预测得到预测位移；
本实施例中，本设计提出的基于位移保护的马达多频带振感增强调整方法应用在线性马达上，为对线性马达振动位移的调整方法。具体地，先对音频信号进行预处理，其中预处理的步骤为对音频信号进行高通滤波以去除超低频信号，再对音频信号进行低通滤波去除马达发声频段信号。其中，接收的音频信号可以是安装线性马达的终端设备中游戏应用实际输出的音效，也可以是根据AR/VR/游戏场景定制设计的宽频信号，并以音频格式存储与输入。然后，将预处理后的音频信号分频滤波，得到多个子带音频信号，并根据子带音频信号的输出电压对马达进行位移预测以得到预测位移。具体地，位移预测信息为对多个子带音频信号位移的预测。位移预测包括根据相关参数构建位移模型，然后根据构建的位移模型对多个子带音频信号进行位移预测。其中，位移指的是马达振动的位移。
步骤S200，对所述预测位移进行压缩和限制；
本实施例中，在对多个子带音频信号进行位移预测，并得到预测位移之后，为了保证马达振动的丰富性和振感强度，且保证马达振动位移不会过大以至于碰壳，出现马达破损或出现杂音等情况，需要对预测位移依次进行压缩和限制。压缩的具体方式由本领域技术人员提前设置，且对于不同频段的音频信号，其压缩的方式并不相同。在一实施例中，由本领域技术人员将每个频段位移的振动范围的最大预设值和最小预设值输入到动态范围压缩模块中，并将小于子带音频信号所在频段最小预设值的小预测位移信号根据动态范围压缩率进行放大，大于子带音频信号所在频段最大预设值的大预测位移信号根据动态范围压缩率进行缩小；以保证马达振动的丰富性且能提升振感。压缩完成之后，将各子带音频信号进行合并，并观测合并后的音频信号，并对位移进行整体限制，保证预测位移在马达的最大空间范围内。整体限制具体为将预测位移按照一定的比例进行整体放大或整体缩小，从而保证马达在振动过程中不会触碰到外部壳体。
步骤S300，根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压，以驱动马达振动。
本实施例中，在对预测位移进行压缩和限制之后，可根据压缩和限制后的预测位移和马达的模型参数合成驱动电压。其中，马达的模型参数包括振子质量m、磁场强度Bl、弹簧劲度系数Kms、阻尼系数Rms、线圈直流电阻Re。具体地，在将压缩和限制后的位移信息和模型参数输入到振动力学端模型建模模块中，以计算离散时间速度模型和位移到力的离散模型，最后将马达的模型参数、力、速度等信息输入到驱动电压合成模块合成驱动电压。并以该合成的驱动电压来驱动线性马达的振动。
如图5所示，本实施例中，在接收到输入的音频信号之后，通过一系列的算法对音频信号进行处理，以得到驱动电压，并将驱动电压的功率放大以驱动马达振动，产生增强的宽频振动反馈。
通过本申请对预测位移进行压缩和限制，并根据压缩和限制后的预测位移合成驱动电压以驱动线性马达振动，既保证了线性马达振动的丰富性并提升了振感，又能够保证线性马达在允许的最大空间范围内振动，避免了马达破损或出现杂音等情况。
在一实施例中，所述根据接收的音频信号进行分频段位移预测得到预测位移的步骤包括：
通过预处理滤除音频信号中超低频信号和发声频段信号；
本实施例中，在接收到音频信号之后，首先对音频信号进行预处理，具体地，对音频信号进行高通滤波以去除超低频信号，再对音频信号进行低通滤波去除马达发声频段信号。
对预处理后的所述音频信号进行分频滤波，得到多个子带音频信号；
对所述多个子带音频信号进行位移预测以得到预测位移。
本实施例中，在通过预处理滤除音频信号中超低频信号和发声频段信号之后，再对预处理后的音频信号进行分频滤波，得到多个子带音频信号。具体地，如图6所示，分频滤波使用的滤波器的各项参数，如截止频率由本领域技术人员根据所需提升的振感需求来提前设定，其中，所需提升的振感需求可以是所需提升振感的频段或增益等。在设定好滤波器截止频率之后，依次对输入的音频信号进行低通滤波、带通滤波、高通滤波，得到多个子带音 频信号BD1,BD2…BDn，其子带输出电压为u1,u2…un。
在一实施例中，所述对所述多个子带音频信号进行位移预测以得到预测位移的步骤包括：
构建输出电压为输入，预测位移为输出的位移电压传递函数；
根据所述位移电压传递函数和所述子带音频信号的输出电压计算得到预测位移。
本实施例中，在已知马达的模型参数：振子质量m、磁场强度Bl、弹簧劲度系数Kms、阻尼系数Rms、线圈直流电阻Re的情况下，可以得到以音频信号的输出电压为输入、位移预测为输出的位移电压传递函数，并可将该位移电压传递函数转换为位移电压的离散化传递函数，在得到离散化传递函数之后，通过公式变形可获得位移预测公式。然后，将采样得到的子带音频信号的输出电压代入位移预测公式，即可得到子带音频信号的预测位移。
具体地，线性马达的位移电压传递函数为：
Figure PCTCN2022124546-appb-000001
其中，
Figure PCTCN2022124546-appb-000002
具体地，离散化传递函数为：
Figure PCTCN2022124546-appb-000003
其中，
Figure PCTCN2022124546-appb-000004
Figure PCTCN2022124546-appb-000005
进一步地，转换得到的位移预测公式为：
Figure PCTCN2022124546-appb-000006
由于本实施例中是为了预测多个子带音频信号的预测位移，因此可将位移预测公式进一步转换为子带位移预测公式，该子带位移预测公式为：
Figure PCTCN2022124546-appb-000007
其中，子带1～子带n输出位移是x 1(k)～x n(k)，子带1～子带n电压表示为u 1(k)～u n(k)，i＝1,2,...n，Ts为采样时间，m为振子质量、Bl为磁场强度、Kms为弹簧劲度系数、Rms为阻尼系数、Re为线圈直流电阻，x(z)为传递函数的输出量预测位移，u(z)为传递函数的输入量输出电压，z为传递函数的常规系数。
因此，将子带音频信号的输出电压代入子带位移预测公式，即可得到子带音频信号的预测位移。
在一实施例中，所述对所述预测位移进行压缩和限制的步骤包括：
对所述预测位移进行压缩；
对所述压缩后的预测位移进行合并，并根据线性马达预留的最大振动空间整体限制合并后的所述预测位移。
本实施例中，在根据位移电压传递函数和子带音频信号的输出电压计算得到子带音频信号的预测位移之后，为了保证马达振动的丰富性和振感强度，且保证马达振动位移不会过大以至于碰壳，出现马达破损或出现杂音等情况，需要对预测位移依次进行压缩和整体限制。压缩的具体方式由本领域技术人员提前设置，在一实施例中，由本领域技术人员将每个频段位移的振动范围的最大预设值和最小预设值输入到动态范围压缩模块中，并将小于子带音频信号所在频段最小预设值的小预测位移信号根据动态范围压缩率进行放大，大于子带音频信号所在频段最大预设值的大预测位移信号根据动态范围压缩率进行缩小；以保证马达振动的丰富性且能提升振感。压缩完成之后，将各子带音频信号进行合并，并观测合并后的音频信号，并对位移进行整体限制，保证预测位移在马达的最大空间范围内。具体地，整体限制为计算得到线性马达预留的最大振动空间和预测位移最大值的比值，将预测位移整体按照该线性马达预留的最大振动空间和预测位移最大值的比值进行放大或整体缩小，从而保证马达在振动过程中，预测位移的最大值不会超过线性马达预留的最大振动空间，因此不会触碰到外部壳体。
在一实施例中，所述对所述预测位移进行压缩的步骤包括：
将所述子带音频信号的预测位移转换为数字信号；
根据预设压缩公式将所述数字信号分段进行压缩，得到压缩后的预测位移。
本实施例中，预设压缩公式为本领域技术人员根据预设规则提前设置的压缩方式，并可根据实际需求进行调整。由于本申请需要对小位移信号进行放大，将大位移信号进行缩小，因而不同位移的音频信号的压缩方式不同，所以需要用不同的预设压缩公式压缩不同位移的音频信号。具体地，在压缩之前，先将音频信号对应的子带音频信号的预测位移转换为数字信号，具体的转换方式为：
input＝20*log10(BD)
其中，BD为预测位移，input为转换获得的数字信号。
由于不同的预测位移其压缩方式并不相同，因此在应用上述方法将预测位移转换为数字信号之后，还需要将数字信号进行分段，并将不同的数字信号代入不同的预设压缩公式，以得到压缩后的预测位移。其中，预设压缩公式为本领域技术人员根据预设规则提前设置，并可根据实际情况实时调整。
在一实施例中，所述预设压缩公式为：
output＝2input+20，input∈(-20dB，-15dB)
output＝input+5，input∈(-15dB，-10dB)
output＝0.6input+1，input∈(-10dB，-5dB)
output＝0.4input，input∈(-5dB，0dB)
其中，input为数字信号，output为压缩后的预测位移。
本实施例中，将不同大小的数字信号代入对应的预设压缩公式中，即可得到压缩后的预测位移。进一步地，通过上述预设压缩公式，可以达到对小位移信号进行放大，对大位移信号进行缩小。具体地，当输入的数字信号在处于(-20dB，-15dB)的区间内，预测位移的计算公式为output＝2input+20；当输入的数字信号在处于(-15dB，-10dB)的区间内，预测位移的计算公式为output＝input+5；当输入的数字信号在处于(-10dB，-5dB)的区间内，预测位移的计算公式为output＝0.6input+1；当输入的数字信号在处于(-5dB，0dB)的区间内，预测位移的计算公式为output＝0.4input。例如，若输入的数字信号为-16dB时，则选取公式output＝2input+20进行计算，计算得到的输出的预测位移为-13dB。若输入的数字信号为-10dB，则可以选取output＝input+5或output＝ 0.6input+1进行计算，计算得到的输出的预测位移为-5dB。如图3所示，以数字信号为横轴，预测位移为纵轴的坐标系上，预设压缩公式为存在3个拐点的线性分段函数，函数的拐点分别为(-15，-10)(-10，-5)(-5，-2)。
在一实施例中，所述根据线性马达预留的最大振动空间整体限制合并后的所述预测位移的步骤包括：
检测合并后的所述预测位移的最大值；
计算所述最大值和所述线性马达预留的最大振动空间的限制比率；
将所述预测位移按所述限制比率进行整体放大或缩小。
本实施例中，在对各子带音频信号压缩后的预测位移进行压缩之后，将各压缩后的预测位移进行合并，然后对预测位移进行整体限位，保证预测位移小于马达振动最大空间。在一实施例中，如图4所示，x1、x2......xn为各子带音频信号的预测位移，首先将各子带音频信号进行合并，然后将合并后的各子带音频信号输入至x_limiter模块，对预测位移进行整体限位，保证预测位移小于马达振动最大空间。具体地，将合并后的各子带音频信号输入至x_limiter模块之后，检测合并后的预测位移x的最大值xmax，并获取线性马达设计预留的最大振动空间x_lim，并计算最大值和线性马达预留的最大振动空间x_lim的限制比率x_ratio，计算式为：
x_ratio＝xmax/x_lim。
在得到限制比率x_ratio之后，再对预测位移整体放大或缩小限制比率x_ratio对应的倍数，以保证线性马达在振动的过程中，不会超过预留的振动最大空间。在一实施例中，整体放大或缩小的方式为：
x_out＝x/x_ratio
其中，x_out为整体限制之后的预测位移。
在一实施例中，所述根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压的步骤包括：
基于马达的模型参数构建电压合成的力学端模型；
根据压缩和限制后的所述预测位移和所述力学端模型合成驱动电压。
本实施例中，在对线性马达的预测位移进行压缩和整体限制之后，还根据压缩和整体限制之后的预测位移合成对应的驱动电压。进一步地，合成驱动电压需要构建电压合成的力学端模型，其中，力学端模型包括速度的离散 模型、位移到力的离散化模型。
具体地，在一实施例中，力学方程为：
f＝K msx+m msa+R msv
音圈振动速度方程为：
Figure PCTCN2022124546-appb-000008
又根据u＝Bl*v+i*Re，f＝Bl*i
从而能够推导得到驱动电压合成的方程为：
Figure PCTCN2022124546-appb-000009
其中，T s为采样时间，m ms为振子质量、Bl为磁场强度、K ms为弹簧劲度系数、R ms为阻尼系数、R e为线圈直流电阻，x为线性马达的预测位移，v为音圈振动的速度，f为马达的驱动力，u为合成的驱动电压，k为常规系数。
在得到上述驱动电压合成的方程之后，根据所述力学端模型合成驱动电压。
本申请还提出一种基于马达的震感调整设备，设备包括存储器、处理器、以及存储在所述存储器上并可在所述处理器上运行的基于马达的震感调整程序，所述基于马达的震感调整程序用于执行本申请各个实施例所述的方法。
本申请还提出一种计算机可读存储介质，其上存储有基于马达的震感调整程序。所述计算机可读存储介质包括计算机可读计算机可读存储介质，所述计算机可读计算机可读存储介质可以是图1的中的存储器，也可以是如ROM(Read-Only Memory，只读存储器)/RAM(Random Access Memory，随机存取存储器)、磁碟、光盘中的至少一种，所述计算机计算机可读存储介质包括若干指令用以使得一台具有处理器的物联网终端设备(可以是手机，计算机，服务器，物联网终端，或者网络设备等)执行本申请各个实施例所述的方法。
在本申请中，术语“第一”“第二”“第三”“第四”“第五”仅用于描述的目的，而不能理解为指示或暗示相对重要性，对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本申请中的具体含义。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描 述的具体特征、结构、材料或者特点包含于本申请的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
尽管上面已经示出和描述了本申请的实施例，本申请保护的范围并不局限于此，可以理解的是，上述实施例是示例性的，不能理解为对本申请的限制，本领域的普通技术人员在本申请的范围内可以对上述实施例进行变化、修改和替换，这些变化、修改和替换都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (10)

  1. 一种基于马达的振感调整方法，其特征在于，所述方法包括以下步骤：
    根据接收的音频信号进行分频段位移预测得到预测位移；
    对所述预测位移进行压缩和限制；
    根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压，以驱动马达振动。
  2. 如权利要求1所述的基于马达的振感调整方法，其特征在于，所述根据接收的音频信号进行分频段位移预测得到预测位移的步骤包括：
    通过预处理滤除音频信号中超低频信号和发声频段信号；
    对预处理后的所述音频信号进行分频滤波，得到多个子带音频信号；
    对所述多个子带音频信号进行位移预测以得到预测位移。
  3. 如权利要求2所述的基于马达的振感调整方法，其特征在于，所述对所述多个子带音频信号进行位移预测以得到预测位移的步骤包括：
    构建输出电压为输入，预测位移为输出的位移电压传递函数；
    根据所述位移电压传递函数和所述子带音频信号的输出电压计算得到预测位移。
  4. 如权利要求1所述的基于马达的振感调整方法，其特征在于，所述对所述预测位移进行压缩和限制的步骤包括：
    对所述预测位移进行压缩；
    对所述压缩后的预测位移进行合并，并根据线性马达预留的最大振动空间整体限制合并后的所述预测位移。
  5. 如权利要求4所述的基于马达的振感调整方法，其特征在于，所述对所述预测位移进行压缩的步骤包括：
    将所述音频信号对应的子带音频信号的预测位移转换为数字信号；
    根据预设压缩公式将所述数字信号分段进行压缩，得到压缩后的预测位移。
  6. 如权利要求5所述的基于马达的振感调整方法，其特征在于，所述预设压缩公式为：
    output＝2input+20，input∈(-20dB，-15dB)
    output＝input+5，input∈(-15dB，-10dB)
    output＝0.6input+1，input∈(-10dB，-5dB)
    output＝0.4input，input∈(-5dB，0dB)
    其中，input为数字信号，output为压缩后的预测位移。
  7. 如权利要求4所述的基于马达的振感调整方法，其特征在于，所述根据线性马达预留的最大振动空间整体限制合并后的所述预测位移的步骤包括：
    检测合并后的所述预测位移的最大值；
    计算所述最大值和所述线性马达预留的最大振动空间的限制比率；
    将所述预测位移按所述限制比率进行整体放大或缩小。
  8. 如权利要求1所述的基于马达的振感调整方法，其特征在于，所述根据压缩和限制后的所述预测位移和马达的模型参数合成驱动电压的步骤包括：
    基于马达的模型参数构建电压合成的力学端模型；
    根据压缩和限制后的所述预测位移和所述力学端模型合成驱动电压。
  9. 一种基于马达的震感调整设备，其特征在于，包括存储器、处理器、以及存储在所述存储器上并可在所述处理器上运行的基于马达的震感调整程序，所述基于马达的震感调整程序被处理器执行时实现如权利要求1至8中任一项所述基于马达的振感调整方法的步骤。
  10. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质 上存储有基于马达的震感调整程序，所述基于马达的震感调整程序被处理器执行时实现如权利要求1至8中任一项所述基于马达的振感调整方法的步骤。
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