Active noise reduction method and device, electronic equipment and related product

Abstract

The invention discloses an active noise reduction method and device, electronic equipment and related products, and the method comprises the steps: determining a noise reduction cost function according to an error noise signal set corresponding to a plurality of error microphones; under the condition that the noise reduction cost function is not converged, determining a step length factor set according to the reference noise signal sets corresponding to the plurality of reference microphones; wherein step length factors in the step length factor set are in one-to-one correspondence with reference noise signals in the reference noise signal set, and the step length factors are related to fluctuation characteristics of the reference noise signals; determining a current filter coefficient set of the adaptive filter according to the reference noise signal set, the error noise signal set and the step length factor set; wherein the current filter coefficient set comprises a current filter coefficient between each reference microphone and each secondary loudspeaker; according to the reference noise signal set and the current filter coefficient set, the noise compensation signal of each secondary loudspeaker is determined, and the noise reduction effect of the scene environment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of noise processing, and in particular, to an active noise reduction method, device, electronic device, and related products. Background Art

[0002] In today's era of pursuing high-quality acoustic environments, active noise reduction technology aims to cancel out noise by generating compensatory sound waves with opposite phases to the noise, and is widely used in many scenarios such as headphones, automobiles, aerospace, and medical fields.

[0003] Traditional active noise reduction technology updates the filter coefficients using a single and fixed step factor. However, in application scenarios where the noise changes dynamically, the filter coefficients cannot adapt to the changes in the noise, resulting in poor noise reduction effects. In application scenarios where the noise is relatively stable, the frequent adjustment of the filter coefficients will lead to poor convergence speed and stability of the adaptive filter. Summary of the Invention

[0004] Embodiments of the present invention provide an active noise reduction method, device, electronic device, and related products to solve the problem that active noise reduction technology cannot meet the complex scenario requirements, while ensuring the noise reduction quality and efficiency in the scenario environment.

[0005] According to an embodiment of the present invention, an active noise reduction method is provided, and the method includes:

[0006] Determine a noise reduction cost function according to an error noise signal set corresponding to a plurality of error microphones;

[0007] In the case where the noise reduction cost function has not converged, determine a step factor set according to a reference noise signal set corresponding to a plurality of reference microphones; wherein, the step factors in the step factor set correspond one-to-one to the reference noise signals in the reference noise signal set, and the step factor is related to the fluctuation characteristics of the reference noise signal;

[0008] Determine a current filter coefficient set of the adaptive filter according to the reference noise signal set, the error noise signal set, and the step factor set; wherein, the current filter coefficient set includes the current filter coefficients between each reference microphone and each secondary speaker;

[0009] Determine a noise compensation signal for each secondary speaker according to the reference noise signal set and the current filter coefficient set.

[0010] According to another embodiment of the present invention, an active noise reduction device is provided, and the device includes:

[0011] A noise reduction cost function determination module, configured to determine a noise reduction cost function according to an error noise signal set corresponding to a plurality of error microphones;

[0012] A step - size factor set determination module, configured to determine a step - size factor set according to a set of reference noise signals corresponding to multiple reference microphones when the noise reduction cost function does not converge; wherein, the step - size factors in the step - size factor set correspond one - to - one with the reference noise signals in the set of reference noise signals, and the step - size factors are related to the fluctuation characteristics of the reference noise signals.

[0013] A current filter coefficient set determination module, configured to determine a current filter coefficient set of an adaptive filter according to the set of reference noise signals, the set of error noise signals, and the step - size factor set; wherein, the current filter coefficient set includes current filter coefficients between each reference microphone and each secondary speaker.

[0014] A noise compensation signal determination module, configured to determine a noise compensation signal for each secondary speaker according to the set of reference noise signals and the current filter coefficient set.

[0015] According to another embodiment of the present invention, there is provided an electronic device, which includes:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the active noise reduction method according to any embodiment of the present invention.

[0019] According to another embodiment of the present invention, there is provided an active noise reduction system, which includes multiple reference microphones, multiple secondary speakers, multiple error microphones, and the electronic device according to any embodiment of the present invention;

[0020] Wherein, the reference microphones are arranged near the noise source position and are configured to acquire reference noise signals;

[0021] The secondary speakers are arranged in the acoustic path between the reference microphones and the error microphones and are configured to output noise compensation signals;

[0022] The error microphones are arranged away from the noise source position and are configured to acquire error noise signals.

[0023] According to another embodiment of the present invention, there is provided a medical device host, which includes a radiator, a main board card, a main body protection shell, and the active noise reduction system according to any embodiment of the present invention;

[0024] Among them, the radiator is arranged on the main board card, and the main board card is arranged on the bottom plate of the main machine protection shell;

[0025] The reference microphone in the active noise cancellation system is arranged on the main board card at a position close to the radiator, the secondary speaker and the error microphone are respectively arranged on the side plate of the main machine protection shell, the secondary speaker is embedded in the side plate, and the electronic device is arranged on the main board card at a position other than the acoustic coverage area formed by the radiator and the error microphone.

[0026] According to another embodiment of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the active noise cancellation method according to any embodiment of the present invention when executed.

[0027] According to another embodiment of the present invention, there is provided a computer program product including a computer program that implements the active noise cancellation method according to any embodiment of the present invention when executed by a processor.

[0028] The technical solution of this embodiment determines a set of step factors according to a set of reference noise signals corresponding to multiple reference microphones, determines the current filter coefficient set of the adaptive filter according to the set of reference noise signals, the set of step factors, and a set of error noise signals corresponding to multiple error microphones, and determines the noise compensation signal of each secondary speaker according to the set of reference noise signals and the current filter coefficient set, achieving the purpose of dynamically adjusting the step factor according to the fluctuation characteristics of the reference noise signal, solving the problem that the active noise cancellation technology cannot adapt to complex scenario requirements, ensuring both the noise reduction quality of the noise compensation signal in a scenario environment with dynamic noise changes and the noise reduction efficiency and stability of the noise compensation signal in a scenario environment with relatively stable noise.

[0029] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0031] Figure 1Schematic diagram of a multi-channel active noise cancellation system provided by an embodiment of the present invention;

[0032] Figure 2 Schematic diagram of a single-channel example of an active noise cancellation system provided by an embodiment of the present invention;

[0033] Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present invention;

[0034] Figure 4 Flowchart of an active noise cancellation method provided by an embodiment of the present invention;

[0035] Figure 5 Flowchart of another active noise cancellation method provided by an embodiment of the present invention;

[0036] Figure 6 Schematic diagram of an active noise cancellation device provided by an embodiment of the present invention;

[0037] Figure 7 Schematic diagram of a medical device host provided by an embodiment of the present invention. Detailed implementation manners

[0038] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0039] It should be noted that the terms "error", "reference", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0040] Figure 1Schematic diagram of the structure of a multi-channel active noise cancellation system provided by an embodiment of the present invention. Specifically, the active noise cancellation system 100 includes a plurality of reference microphones 110, a plurality of secondary speakers 120, a plurality of error microphones 130, and an electronic device 140.

[0041] Among them, the reference microphone 110 is arranged near the noise source and is used to acquire a reference noise signal; the secondary speaker 120 is arranged in the acoustic path between the reference microphone 110 and the error microphone 130 and is used to output a noise compensation signal; the error microphone 130 is arranged away from the noise source and is used to acquire an error noise signal.

[0042] Specifically, in the scenario environment, the secondary speaker 120 is located at a downstream position of the acoustic path from the noise source to the reference microphone 110, and the error microphone 130 is arranged in the noise reduction area in the scenario environment, and the noise reduction area is located at a downstream position of the acoustic path from the reference microphone 110 to the secondary speaker 120.

[0043] Exemplarily, the scenario object configured with the active noise cancellation system 100 can be a medical device host, headphones, an automobile, a pipeline, a household appliance, etc., but is not limited to the example situation. For example, the medical device host includes but is not limited to an ultrasonic soft tissue cutting and hemostasis host, an ultrasonic osteotome host, an electrosurgical unit host, or an orthopedic power host, etc.

[0044] In an alternative embodiment, the reference microphone 110 is communicatively connected to the electronic device 140 through a reference processing module, and / or the error microphone 130 is communicatively connected to the electronic device 140 through an error processing module. Among them, each of the reference processing module and the error processing module includes a voltage amplifier, an anti-aliasing filter, and an analog-to-digital converter (A / D) connected in series.

[0045] Specifically, the reference processing module is used to sequentially perform voltage amplification processing, anti-aliasing filtering processing, and digitization processing on the original reference signal collected by the reference microphone 110 to obtain a reference noise signal, and output the reference noise signal to the electronic device 140. The error processing module is used to sequentially perform voltage amplification processing, anti-aliasing filtering processing, and digitization processing on the original error signal collected by the error microphone 130 to obtain an error noise signal, and output the error noise signal to the electronic device 140. Among them, the original reference signal and the original error signal are analog signals collected by the reference microphone 110 and the error microphone 130 respectively.

[0046] When performing digital processing, if the sampling frequency does not satisfy the Nyquist sampling theorem (i.e., the sampling frequency should be greater than or equal to twice the highest frequency of the signal), signal aliasing will occur, causing signals with originally different frequencies to appear as the same frequency in the digital domain, resulting in signal distortion. Anti-aliasing filtering is a low-pass filtering algorithm used to filter out the frequency components in the analog signal that are higher than half of the sampling frequency, thereby achieving the effect of anti-aliasing.

[0047] Specifically, the number of reference processing modules and error processing modules can be one or multiple. Exemplarily, the reference processing modules correspond one-to-one with the reference microphones 110, and the error processing modules correspond one-to-one with the error microphones 130.

[0048] The advantage of setting the voltage amplifier and the anti-aliasing filter is that it ensures the signal quality of the reference noise signal and the error noise signal, and thus ensures the noise reduction effect in the scene environment.

[0049] In an alternative embodiment, the secondary speaker 120 is communicatively connected to the electronic device 140 through a speaker processing module. The speaker processing module includes a Digital-to-Analog Converter (D / A), a reconstruction filter, and a power amplifier connected in series. Exemplarily, the reconstruction filter can be a low-pass filter or a wavelet filter, but is not limited to the exemplary situation.

[0050] Specifically, the speaker processing module is configured to perform analog processing, reconstruction filtering processing, and power amplification processing on the noise control signal output by the electronic device 140 in sequence to obtain a noise compensation signal, and output the noise compensation signal to the secondary speaker 120.

[0051] Specifically, the number of speaker processing modules can be one or multiple. Exemplarily, the speaker processing modules correspond one-to-one with the secondary speakers 120.

[0052] The advantage of setting the reconstruction filter and the power amplifier is that it ensures the signal quality of the noise compensation signal, and thus ensures the noise reduction effect in the scene environment.

[0053] Figure 2 It is a schematic structural diagram of a single-channel example of an active noise reduction system provided by an embodiment of the present invention. Figure 2Take a reference microphone 110, a secondary loudspeaker 120, and an error microphone 130 as an example. Among them, the path from the noise source to the error microphone 130 is denoted as P′(z), the acoustic path from the noise source to the reference microphone 110, the path between the reference microphone 110, the voltage amplifier, the anti-aliasing filter, and the A / D converter is denoted as C(z), and the noise control signal y(n) output by the voltage amplifier electronic device 140 passes through the D / A converter, the reconstruction filter, the power amplifier, the secondary loudspeaker 120, and the acoustic path from the secondary loudspeaker 120 to the error microphone 130, which is denoted as the path S′(z), and the path from the error microphone 130, the voltage amplifier, the anti-aliasing filter, and the A / D converter is denoted as R(z).

[0054] Among them, the initial noise signal generated by the noise source at the nth acquisition moment is denoted as x p (n), the reference noise signal input to the electronic device 140 is denoted as x(n), the noise control signal output by the electronic device 140 is denoted as y(n), and the error noise signal input to the electronic device 140 is denoted as e(n).

[0055] Figure 2 The F(z) shown in represents the acoustic feedback path transfer function, including the D / A converter, the reconstruction filter, the power amplifier, the secondary loudspeaker 120, the acoustic path from the secondary loudspeaker 120 to the reference microphone 110, the reference microphone 110, the voltage amplifier, the anti-aliasing filter, and the A / D converter. Specifically, the remaining sound signals corresponding to the paths P′(z) and S′(z) both pass through the path R(z). Correspondingly, the main transfer function P(z) = R(z)P′(z), and the secondary transfer function is S(z) = R(z)S′(z).

[0056] Figure 3 This is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. The electronic device 140 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, servers, blade servers, mainframe computers, minicomputers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0057] Such as Figure 3As shown, the electronic device 140 includes at least one processor 11 and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor 11. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 140 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0058] Multiple components in the electronic device 140 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 140 to exchange information or data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0059] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the active noise reduction method provided in the following embodiments.

[0060] In some embodiments, the active noise cancellation method provided in the following embodiments can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 140 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the active noise cancellation method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the active noise cancellation method by any other suitable means (e.g., by means of firmware).

[0061] Figure 4 FIG. is a flowchart of an active noise cancellation method provided by an embodiment of the present invention. This embodiment is applicable to the situation of active noise cancellation of a scene environment. The method can be executed by an active noise cancellation device, which can be implemented in the form of hardware and / or software, and the active noise cancellation device can be configured in an electronic device. As Figure 4 shown, the method includes:

[0062] S210. Determine a noise cancellation cost function according to an error noise signal set corresponding to a plurality of error microphones.

[0063] Specifically, the error noise signals in the error noise signal set represent the residual error signals after noise cancellation processing, and can also represent the superimposed signals of the initial noise signals generated by the noise source passing through the main propagation path P′(z) and the noise control signals passing through the secondary propagation path S′(z) at the positions of the error microphones.

[0064] Exemplarily, the error noise signal set E = [e1(n),..., e m (n),..., e M (n)], where e1(n) represents the error noise signal of the first error microphone at the nth acquisition moment, e m (n) represents the error noise signal of the mth error microphone at the nth acquisition moment, e M (n) represents the error noise signal of the Mth error microphone at the nth acquisition moment, M represents the number of error microphones, and M > 1.

[0065] In an alternative embodiment, the method further includes: performing signal processing on an original reference signal set collected by a plurality of reference microphones through a reference processing module to obtain a reference noise signal set; wherein, the reference processing module includes a voltage amplifier, an anti-aliasing filter, and an analog-to-digital converter connected in series.

[0066] Specifically, the original reference signal set contains original reference signals respectively collected by a plurality of reference microphones, where the original reference signals are analog signals.

[0067] Specifically, the optimization objective of the noise reduction cost function is to minimize the error between the error noise signal and the desired noise signal, so as to achieve the purpose of noise suppression. Among them, the desired noise signal can be 0.

[0068] In an alternative embodiment, the noise reduction cost function characterizes the total signal energy or average signal energy corresponding to all error noise reduction signals, or the noise reduction cost function characterizes the signal energy corresponding to the error noise signal with the largest amplitude in the error noise signal set.

[0069] In an alternative embodiment, the noise reduction cost function is the LP norm. Exemplarily, the noise reduction cost function P satisfies the following formula:

[0070]

[0071] Among them, p≥1. When p = 1, the noise reduction cost function is the Manhattan norm; when p = 2, the noise reduction cost function is the Euclidean norm; when p→∞, the noise reduction cost function is the amplitude information corresponding to the error noise signal with the largest amplitude.

[0072] In another alternative embodiment, the noise reduction cost function P satisfies the following formula:

[0073]

[0074] As the number of channels increases, the number of parameters in the active noise reduction process increases, resulting in a significant increase in the computational complexity of the active noise reduction process. In this embodiment, by determining the noise reduction cost function based on the error noise signal with the largest amplitude, the computational complexity is reduced, thereby further improving the noise reduction efficiency in the scenario environment and reducing the resource consumption of deploying the active noise reduction system.

[0075] S220. In the case where the noise reduction cost function does not converge, determine a set of step size factors according to the set of reference noise signals corresponding to a plurality of reference microphones.

[0076] Specifically, the non-convergence of the noise reduction cost function means that the optimization objective of the adaptive filter in the active noise reduction method is not achieved.

[0077] Based on the above embodiments, optionally, the method further includes: in the case where the noise reduction cost function converges, using the noise compensation signal corresponding to the last iteration filtering process of the adaptive filter for each secondary speaker as the final noise compensation signal for each secondary speaker.

[0078] Specifically, the reference noise signals in the reference noise signal set represent the sound signals of the noise sources at the positions of the reference microphones.

[0079] Exemplarily, the reference noise signal set X = [x1(n),..., x j (n),..., x J (n)], where x1(n) represents the reference noise signal of the 1st reference microphone at the nth acquisition moment, x j (n) represents the reference noise signal of the jth reference microphone at the nth acquisition moment, x J (n) represents the reference noise signal of the Jth reference microphone at the nth acquisition moment, and J represents the number of reference microphones, where J > 1.

[0080] In an optional embodiment, the method further includes: through an error processing module, performing signal processing on the original error signal set collected by multiple error microphones to obtain an error noise signal set. The error processing module includes a voltage amplifier, an anti-aliasing filter, and an analog-to-digital converter connected in series.

[0081] Specifically, the original error signal set contains the original error signals respectively collected by multiple error microphones, where the original error signals are analog signals.

[0082] In this embodiment, the step factors in the step factor set correspond one-to-one with the reference noise signals in the reference noise signal set, and the step factors are related to the fluctuation characteristics of the reference noise signals.

[0083] In an optional embodiment, determining the step factor set according to the reference noise signal sets corresponding to multiple reference microphones includes: determining the step factor corresponding to each reference noise signal according to the fluctuation index value corresponding to each reference noise signal in the reference noise signal set; determining the step factor set according to the multiple step factors.

[0084] Specifically, the fluctuation index value characterizes the fluctuation characteristics of the reference noise signal. Exemplarily, the fluctuation index value can be the standard deviation, peak-to-peak value, root mean square value, peak factor, or spectral flatness, etc., but is not limited to the example cases.

[0085] Specifically, the fluctuation index value corresponds one-to-one with the step factor, and there is a negative correlation between the fluctuation index value and the step factor. The larger the fluctuation index value, the smaller the step factor, and vice versa, the smaller the fluctuation index value, the larger the step factor.

[0086] In another alternative embodiment, determining a set of step factors according to a set of reference noise signals corresponding to multiple reference microphones includes: for each reference microphone, obtaining the reference noise signal corresponding to the reference microphone in the set of reference noise signals, determining the average signal power according to the smoothing window length and the reference noise signal, and determining the step factor corresponding to the reference microphone according to the average signal power and the filter order of the adaptive filter; determining the set of step factors according to the step factors corresponding to the multiple reference microphones respectively.

[0087] Exemplarily, the average signal power is expressed as:

[0088]

[0089] where N represents the smoothing window length and x represents the reference noise signal.

[0090] In this embodiment, the product result of the average signal power and the filter order is inversely proportional to the step factor. Exemplarily, the step factor u j (n) corresponding to the j-th reference microphone at the n-th acquisition moment is expressed as:

[0091]

[0092] where α ∈ (0, 2), γ represents a very small lower bound constraint value, and L represents the filter order.

[0093] The advantage of such a setting is that it ensures the adaptability between the step factor and the adaptive filter, and further improves the noise reduction stability in the scenario environment.

[0094] In a specific embodiment, when L = N, the step factor u j (n) corresponding to the j-th reference microphone at the n-th acquisition moment can be expressed as:

[0095]

[0096] S230. Determine the current filter coefficient set of the adaptive filter according to the set of reference noise signals, the set of error noise signals, and the set of step factors.

[0097] In this embodiment, the current filter coefficient set includes the current filter coefficients between each reference microphone and each secondary speaker.

[0098] In an alternative embodiment, the adaptive algorithm adopted by the adaptive filter is the Least Mean Square (LMS) algorithm. Among them, the mean square error in the least mean square algorithm represents the average of the squares of the differences between the predicted value and the actual value. The adaptive filter adjusts the control parameters to find the parameter values that can minimize the mean square error. This process can be represented as finding an optimal surface in the parameter space.

[0099] In an alternative embodiment, according to the reference noise signal set, the error noise signal set, and the step factor set, the current filter coefficient set of the adaptive filter is determined, including: for each set of reference microphones and secondary speakers, obtaining the reference noise signal and the step factor corresponding to the reference microphone in the reference noise signal set and the step factor set respectively; determining the current filter coefficient corresponding to the reference microphone and the secondary speaker according to the error noise signal set, the reference noise signal, and the step factor; and determining the current filter coefficient set of the adaptive filter according to the current filter coefficients corresponding to multiple sets of reference microphones and secondary speakers.

[0100] Specifically, determining the current filter coefficient corresponding to the reference microphone and the secondary speaker according to the error noise signal set, the reference noise signal, and the step factor includes: obtaining the historical filter coefficient of the reference microphone and the secondary speaker at the previous adaptive iteration moment; determining the update gradient according to the error noise signal set, the reference noise signal, and the step factor; and determining the current filter coefficient corresponding to the reference microphone and the secondary speaker according to the historical filter coefficient and the update gradient.

[0101] Specifically, the update gradient represents the gradient of the noise reduction cost function. In an alternative embodiment, the update gradient is the gradient value determined based on the reference noise signal and all the error noise signals in the error noise signal set, representing the overall change of the error noise signal set.

[0102] Taking the jth reference microphone and the kth secondary speaker as an example, the current filter coefficient w kj (n + 1) satisfies the following formula:

[0103]

[0104] w kj (n) = [w kj，0 (n), w kj，1 (n),..., w kj，L-1 (n)] T

[0105] x j (n) = [x j (n), x j (n - 1),..., x j(n - L + 1)

[0106] where w kj (n) represents the historical filter coefficient corresponding to the j-th reference microphone and the k-th secondary speaker at the n-th adaptive iteration moment, and w kj，0 (n) represents the 0-th order coefficient in the historical filter coefficients, and w kj，1 (n) represents the 1-st order coefficient in the historical filter coefficients, and w kj，L-1 (n) represents the (L - 1)-th order coefficient in the historical filter coefficients, L represents the filtering order of the adaptive filter, T represents the transpose, and μ j represents the step size factor corresponding to the j-th reference microphone, and x j (n) represents the reference noise signal vector corresponding to the j-th reference microphone and the n-th acquisition moment.

[0107] In another alternative embodiment, the updated gradient is the gradient value determined based on the reference noise signal and the error noise signal with the largest magnitude in the error noise signal set, which characterizes the maximum change condition of the error noise signal set.

[0108] Taking the j-th reference microphone and the k-th secondary speaker as an example, the current filter coefficient w kj (n + 1) satisfies the following formula:

[0109] w kj (n + 1) = w kj (n) - μ j e max，m (n)x j (n)

[0110] w kj (n) = [w kj，0 (n), w kj，1 (n),..., w kj，L-1 (n)]

[0111] x j (n) = [x j (n), x j (n - 1),..., x j (n - L + 1)]

[0112] where e max，m (n) represents the error noise signal with the largest magnitude in the error noise signal set.

[0113] The advantage of such a setting is that it reduces the computational complexity of the active noise cancellation process, further improves the noise cancellation efficiency in the scenario environment, and reduces the resource consumption for deploying the active noise cancellation system.

[0114] S240. Determine the noise compensation signal for each secondary speaker according to the reference noise signal set and the current filter coefficient set.

[0115] In an optional embodiment, determining the noise compensation signal for each secondary speaker according to the reference noise signal set and the current filter coefficient set includes: for each secondary speaker, obtaining a plurality of current filter coefficients corresponding to the secondary speaker in the current filter coefficient set; determining a reference compensation signal corresponding to each reference microphone of the secondary speaker according to the reference noise signal set and the plurality of current filter coefficients; and determining the noise compensation signal of the secondary speaker according to the plurality of reference compensation signals.

[0116] Specifically, the reference compensation signal represents a sound signal with a phase opposite to that of the reference noise signal of the secondary speaker and the reference microphone.

[0117] Taking the j-th reference microphone and the k-th secondary speaker as an example, the reference compensation signal a kj (n + 1) satisfies the following formula:

[0118]

[0119] where w kj (n + 1) represents the current filter coefficient corresponding to the j-th reference microphone and the k-th secondary speaker in the current filter coefficient set, w kj，0 (n + 1) represents the 0th-order coefficient in the current filter coefficients, w kj，1 (n + 1) represents the 1st-order coefficient in the current filter coefficients, w kj，L-1 (n + 1) represents the (L - 1)th-order coefficient in the current filter coefficients, x j (n + 1) represents the reference noise signal vector corresponding to the j-th reference microphone and the (n + 1)th acquisition moment, L represents the filtering order of the adaptive filter, and T represents the transpose.

[0120] In an optional embodiment, determining the noise compensation signal of the secondary speaker according to the plurality of reference compensation signals includes: taking the summation result corresponding to the plurality of reference compensation signals as the noise control signal of the secondary speaker; through the speaker processing module, performing signal processing on the noise control signal to obtain the noise compensation signal, and outputting the noise compensation signal to the secondary speaker; wherein the speaker processing module includes a digital-to-analog converter, a reconstruction filter, and a power amplifier connected in series.

[0121] Exemplarily, the noise control signal y(n + 1) corresponding to the k-th secondary speaker satisfies the following formula:

[0122]

[0123] Where J represents the number of reference microphones.

[0124] In the technical solution of this embodiment, by determining a step factor set according to a reference noise signal set corresponding to multiple reference microphones, determining a current filter coefficient set of an adaptive filter according to the reference noise signal set, the step factor set, and an error noise signal set corresponding to multiple error microphones, and determining a noise compensation signal for each secondary speaker according to the reference noise signal set and the current filter coefficient set, the purpose of dynamically adjusting the step factor according to the fluctuation characteristics of the reference noise signal is achieved, and the problem that the active noise reduction technology cannot meet the requirements of complex scenarios is solved. This not only ensures the noise reduction quality of the noise compensation signal in a scenario environment with dynamic noise changes but also ensures the noise reduction efficiency and stability of the noise compensation signal in a scenario environment with relatively stable noise.

[0125] Figure 5 The flowchart of another active noise reduction method provided by an embodiment of the present invention further refines the step of "determining the current filter coefficient set of the adaptive filter according to the reference noise signal set, the error noise signal set, and the step factor set" in the above embodiment. As Figure 5 shown, the method includes:

[0126] S310. Determine a noise reduction cost function according to an error noise signal set corresponding to multiple error microphones.

[0127] S320. When the noise reduction cost function has not converged, determine a step factor set according to a reference noise signal set corresponding to multiple reference microphones.

[0128] S310 - S320 in this embodiment is the same as or similar to Figure 4 S210 - S220 shown above, and will not be elaborated herein.

[0129] S330. For each group of reference microphones and secondary speakers, obtain the reference noise signal and the step factor in the reference noise signal set and the step factor set respectively corresponding to the reference microphones, determine a secondary filter signal set corresponding to the reference microphones and the secondary speakers according to the reference noise signal, and determine the current filter coefficient corresponding to the reference microphones and the secondary speakers according to the step factor, the error noise signal set, and the secondary filter signal set.

[0130] In this embodiment, the secondary filter signal corresponding to each error microphone in the secondary filter signal set represents the noise signal after the reference noise signal of the reference microphone passes through the secondary propagation path between the secondary speaker and the error microphone.

[0131] In an alternative embodiment, according to the reference noise signal, a set of secondary filter signals corresponding to the reference microphone and the secondary speaker is determined, including: for each error microphone, obtaining a secondary transfer function corresponding to the secondary propagation path between the secondary speaker and the error microphone, and determining a secondary filter signal corresponding to the error microphone according to the reference noise signal and the secondary transfer function; determining a set of secondary filter signals corresponding to the reference microphone and the secondary speaker according to the secondary filter signals respectively corresponding to a plurality of error microphones.

[0132] Taking the k-th secondary speaker and the m-th error microphone as an example, the estimation model corresponding to the secondary transfer function S(z) can be expressed as:

[0133] Taking the j-th reference microphone, the k-th secondary speaker and the m-th error microphone as an example, the secondary filter signal x′ mkj (n) satisfies the formula:

[0134] x′ mkj (n) = [x′ mkj (n), x′ mkj (n - 1),.., x′ mkj (n - L + 1)]

[0135]

[0136] where x j (n) represents the reference noise signal corresponding to the j-th reference microphone.

[0137] In an alternative embodiment, according to the step factor, the set of error noise signals, and the set of secondary filter signals, the current filter coefficients corresponding to the reference microphone and the secondary speaker are determined, including: obtaining the historical filter coefficients of the reference microphone and the secondary speaker at the previous adaptive iteration moment; determining an update gradient according to the step factor, the set of error noise signals, and the set of secondary filter signals; determining the current filter coefficients corresponding to the reference microphone and the secondary speaker according to the historical filter coefficients and the update gradient.

[0138] In this embodiment, the update gradient represents the overall change situation of the set of error noise signals. Exemplarily, the current filter coefficient w kj (n + 1) satisfies the following formula:

[0139]

[0140] w kj (n) = [w kj，0 (n), w kj，1 (n),..., w kj，L-1 (n)]

[0141] Among them, w kj (n) represents the historical filter coefficient corresponding to the j-th reference microphone and the k-th secondary speaker at the n-th adaptive iteration moment, w kj，0 (n) represents the 0th-order coefficient in the historical filter coefficient, w kj，1 (n) represents the 1st-order coefficient in the historical filter coefficient, w kj，L-1 (n) represents the (L - 1)-th order coefficient in the historical filter coefficient, L represents the filtering order of the adaptive filter, T represents the transpose, μ j represents the step size factor corresponding to the j-th reference microphone.

[0142] In another optional embodiment, according to the step size factor, the error noise signal set, and the secondary filtered signal set, determining the current filter coefficients corresponding to the reference microphone and the secondary speaker includes: obtaining the historical filter coefficients of the reference microphone and the secondary speaker at the previous adaptive iteration moment; taking the error noise signal with the largest amplitude in the error noise signal set as the target error noise signal, and obtaining the target secondary filtered signal from the secondary filtered signal set according to the error microphone corresponding to the target error noise signal; determining the update gradient according to the step size factor, the target error noise signal, and the target secondary filtered signal; and determining the current filter coefficients corresponding to the reference microphone and the secondary speaker according to the historical filter coefficients and the update gradient.

[0143] In this embodiment, the update gradient represents the maximum change situation of the error noise signal set. Exemplarily, the current filter coefficient w kj (n + 1) satisfies the following formula:

[0144] w kj (n + 1) = w kj (n) - μ j e max，m (n)x′ max，mkj (n)

[0145] w kj (n) = [w kj，0 (n), w kj，1 (n),..., w kj，L-1 (n)]

[0146] Among them, e max，m (n) represents the target error noise signal, x′ max，mkj (n) represents the target secondary filtered signal.

[0147] In traditional multi-channel active noise cancellation technology, as the number of channels increases, the computational complexity grows exponentially, which is not conducive to the technical implementation of hardware systems. In this embodiment, by updating the filter coefficients according to the error noise signal with the largest amplitude in the error noise signal concentration, a balanced consideration is given to the convergence speed, steady-state error, and hardware resource consumption, reducing the computational complexity of the active noise cancellation process, further improving the noise cancellation efficiency in the scenario environment, and reducing the resource consumption for deploying the active noise cancellation system.

[0148] S340. Determine the current filter coefficient set of the adaptive filter according to the current filter coefficients corresponding to multiple groups of reference microphones and secondary speakers.

[0149] Specifically, the number of current filter coefficients in the current filter coefficient set is the product result of the number of reference microphones and the number of secondary speakers.

[0150] S350. Determine the noise compensation signal of each secondary speaker according to the reference noise signal set and the current filter coefficient set.

[0151] S350 in this embodiment is the same or similar to Figure 4 S240 shown in the above embodiment, and will not be elaborated in this embodiment.

[0152] In the active noise cancellation system, the noise control signal y(n) is collected by the error microphone after passing through the secondary propagation path S′(z). The existence of the secondary propagation path S′(z) causes a phase delay between the noise control signal y(n) and the error noise signal e(n), resulting in poor noise cancellation effect in the scenario environment.

[0153] The technical solution of this embodiment determines the secondary filter signal set corresponding to the reference microphones and secondary speakers according to the reference noise signal, and determines the current filter coefficients corresponding to the reference microphones and secondary speakers according to the step size factor, the error noise signal set, and the secondary filter signal set, solving the problem of feedback imbalance caused by the existence of the secondary propagation path. It not only enables the adaptive filter to adjust the filter coefficients more accurately, speeds up the convergence speed, further improves the noise cancellation efficiency in the scenario environment, but also improves the stability of the noise cancellation compensation signal, further improving the noise cancellation effect in the scenario environment.

[0154] The following is an embodiment of the active noise cancellation device provided by the embodiment of the present invention. This device and the active noise cancellation method in the above embodiment belong to the same inventive concept. For the details not elaborated in the embodiment of the active noise cancellation device, reference can be made to the content about the active noise cancellation method in the above embodiment.

[0155] Figure 6 It is a schematic structural diagram of an active noise cancellation device provided by an embodiment of the present invention. AsFigure 6 As shown in the figure, the device includes: a noise reduction cost function determination module 410, a step size factor set determination module 420, a current filter coefficient set determination module 430, and a noise compensation signal determination module 440.

[0156] Among them, the noise reduction cost function determination module 410 is used to determine the noise reduction cost function according to the error noise signal set corresponding to multiple error microphones;

[0157] The step size factor set determination module 420 is used to determine the step size factor set according to the reference noise signal set corresponding to multiple reference microphones when the noise reduction cost function does not converge; among them, the step size factors in the step size factor set correspond one-to-one with the reference noise signals in the reference noise signal set, and the step size factors are related to the fluctuation characteristics of the reference noise signals;

[0158] The current filter coefficient set determination module 430 is used to determine the current filter coefficient set of the adaptive filter according to the reference noise signal set, the error noise signal set, and the step size factor set; among them, the current filter coefficient set contains the current filter coefficients between each reference microphone and each secondary speaker;

[0159] The noise compensation signal determination module 440 is used to determine the noise compensation signal of each secondary speaker according to the reference noise signal set and the current filter coefficient set.

[0160] The technical solution of this embodiment realizes the purpose of dynamically adjusting the step size factor according to the fluctuation characteristics of the reference noise signal by determining the step size factor set according to the reference noise signal set corresponding to multiple reference microphones, determining the current filter coefficient set of the adaptive filter according to the reference noise signal set, the step size factor set, and the error noise signal set corresponding to multiple error microphones, and determining the noise compensation signal of each secondary speaker according to the reference noise signal set and the current filter coefficient set. It solves the problem that the active noise reduction technology cannot adapt to complex scenario requirements, and ensures both the noise reduction quality of the noise compensation signal in the scenario environment with dynamic noise changes and the noise reduction efficiency and stability of the noise compensation signal in the scenario environment with relatively stable noise.

[0161] In an alternative embodiment, the step size factor set determination module 420 is specifically used for:

[0162] For each reference microphone, obtain the reference noise signal corresponding to the reference microphone in the reference noise signal set, determine the average signal power according to the smoothing window length and the reference noise signal, and determine the step size factor corresponding to the reference microphone according to the average signal power and the filter order of the adaptive filter;

[0163] Determine the step size factor set according to the step size factors corresponding to multiple reference microphones respectively;

[0164] Among them, the product result of the average signal power and the filtering order is inversely proportional to the step factor.

[0165] In an alternative embodiment, the current filter coefficient set determination module 430 includes:

[0166] The current filter coefficient determination unit is configured to, for each set of reference microphones and secondary speakers, obtain the reference noise signal and the step factor corresponding to the reference microphone from the reference noise signal set and the step factor set respectively, and determine the secondary filter signal set corresponding to the reference microphone and the secondary speaker according to the reference noise signal, and determine the current filter coefficient corresponding to the reference microphone and the secondary speaker according to the step factor, the error noise signal set, and the secondary filter signal set;

[0167] The current filter coefficient set determination unit is configured to determine the current filter coefficient set of the adaptive filter according to the current filter coefficients corresponding to multiple sets of reference microphones and secondary speakers respectively.

[0168] Among them, the secondary filter signal corresponding to each error microphone in the secondary filter signal set represents the noise signal after the reference noise signal of the reference microphone passes through the secondary propagation path between the secondary speaker and the error microphone.

[0169] In an alternative embodiment, the current filter coefficient determination unit includes:

[0170] The secondary filter signal set determination subunit is configured to, for each error microphone, obtain the secondary transfer function corresponding to the secondary propagation path between the secondary speaker and the error microphone, and determine the secondary filter signal corresponding to the error microphone according to the reference noise signal and the secondary transfer function;

[0171] Determine the secondary filter signal set corresponding to the reference microphone and the secondary speaker according to the secondary filter signals corresponding to multiple error microphones respectively.

[0172] In an alternative embodiment, the current filter coefficient determination unit includes:

[0173] The current filter coefficient determination subunit is configured to obtain the historical filter coefficients of the reference microphone and the secondary speaker at the previous adaptive iteration moment;

[0174] Use the error noise signal with the largest amplitude in the error noise signal set as the target error noise signal, and obtain the target secondary filter signal from the secondary filter signal set according to the error microphone corresponding to the target error noise signal;

[0175] Determine the update gradient according to the step factor, the target error noise signal, and the target secondary filter signal;

[0176] Determine the current filter coefficients corresponding to the reference microphone and the secondary speaker according to the historical filter coefficients and the updated gradient.

[0177] In an alternative embodiment, the noise compensation signal determination module 440 includes:

[0178] A noise compensation signal determination unit, configured to obtain, for each secondary speaker, a plurality of current filter coefficients corresponding to the secondary speaker in the current filter coefficient set;

[0179] Determine a reference compensation signal corresponding to the secondary speaker and each reference microphone according to the reference noise signal set and the plurality of current filter coefficients;

[0180] Determine the noise compensation signal of the secondary speaker according to the plurality of reference compensation signals.

[0181] In an alternative embodiment, the noise compensation signal determination unit is specifically configured to:

[0182] Use the summation result corresponding to the plurality of reference compensation signals as the noise control signal of the secondary speaker;

[0183] Through the speaker processing module, perform signal processing on the noise control signal to obtain a noise compensation signal, and output the noise compensation signal to the secondary speaker;

[0184] Wherein, the speaker processing module includes a digital-to-analog converter, a reconstruction filter, and a power amplifier connected in series.

[0185] In an alternative embodiment, the device further includes:

[0186] A reference noise signal set determination module, configured to perform signal processing on the original reference signal set collected by a plurality of reference microphones through a reference processing module to obtain a reference noise signal set;

[0187] An error noise signal set determination module, configured to perform signal processing on the original error signal set collected by a plurality of error microphones through an error processing module to obtain an error noise signal set;

[0188] Wherein, the reference processing module and the error processing module each include a voltage amplifier, an anti-aliasing filter, and an analog-to-digital converter connected in series.

[0189] The active noise reduction device provided by the embodiments of the present invention can execute the active noise reduction method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0190] Figure 7 This is a schematic structural diagram of a medical device host provided by an embodiment of the present invention. As Figure 7As shown, the medical device host 500 includes a radiator 510, a main board card 520, a main body protection case 530, and the active noise reduction system in the above embodiments. For example, the medical device host 500 includes, but is not limited to, an ultrasonic soft tissue cutting and hemostasis host, an ultrasonic osteotome host, an electrosurgical unit host, or an osteodynamic host, etc.

[0191] Among them, the radiator 510 is arranged on the main board card 520, and the main board card 520 is arranged on the bottom plate of the main body protection case 530. Specifically, a fan 511 is arranged on the radiator 510 to realize the heat dissipation function of the radiator 510. In this embodiment, the fan 511 is a noise source in the scene environment.

[0192] Among them, the reference microphone 540 in the active noise reduction system is arranged on the main board card 520 at a position close to the radiator 510, the secondary speaker 550 and the error microphone 560 are respectively arranged on the side plates of the main body protection case 530, the secondary speaker 550 is embedded in the side plate, and the electronic device 570 is arranged on the main board card 520 at a position other than the acoustic coverage area formed by the radiator 510 and the error microphone 560.

[0193] Figure 7 The dotted line shown in the figure represents the acoustic path through which the noise generated by the fan 511 is sequentially transmitted to the reference microphone 540 and the error microphone 560.

[0194] When the medical device host 500 is working, the fan 511 needs to rotate at a high speed to realize the heat dissipation function, so it will generate a large amount of wind noise, and heat dissipation holes are usually arranged on the main body protection case 530, which further aggravates the noise pollution caused by the medical device host 500 to the scene environment. In this embodiment, the reference microphone 540 can pick up the reference noise signal and output it to the electronic device 570, and the error microphone 560 can pick up the error noise signal and output it to the electronic device 570, so that the electronic device 570 controls the secondary speaker 550 to output a noise compensation signal to achieve the effect of noise elimination and reduction.

[0195] On the basis of the above embodiments, optionally, the medical device host 500 further includes sound absorption and sound insulation materials. The installation position of the sound absorption and sound insulation materials in the medical device host 500 can be determined according to the spectral information of the sound field modeling. Exemplarily, sound absorption and sound insulation materials are arranged on the high-frequency noise propagation path.

[0196] It can be understood that the reference microphone 540, the secondary speaker 550, the error microphone 560, and the electronic device 570 in the active noise reduction system mentioned in this embodiment are the same as those in the above embodiments Figure 1 or Figure 2The reference microphone 110, secondary speaker 120, error microphone 130, and electronic device 140 in the active noise cancellation system shown are each the same.

[0197] The various embodiments of the systems and techniques described above in this document can be implemented in the following systems or combinations thereof: digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard parts (ASSPs), system on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0198] The computer program for implementing the active noise cancellation method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer programs are executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0199] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable storage medium. Examples of machine-readable storage media would include electrical connections based on at least one wire, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0200] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a terminal device having: a display device for displaying information to the user (e.g., a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the terminal device. Other kinds of devices can also provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0201] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0202] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is created by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and virtual private server (VPS) services.

[0203] It should be understood that various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0204] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An active noise reduction method, characterized in that: include: Determining a noise reduction cost function according to a set of error noise signals corresponding to a plurality of error microphones; In the case where the noise reduction cost function has not converged, determining a step factor set according to a reference noise signal set corresponding to a plurality of reference microphones; wherein the step factors in the step factor set correspond one-to-one to the reference noise signals in the reference noise signal set, and the step factors are related to the fluctuation characteristics of the reference noise signals; Determine a current filter coefficient set of the adaptive filter according to the reference noise signal set, the error noise signal set and the step factor set; wherein the current filter coefficient set includes current filter coefficients between each reference microphone and each secondary speaker; A noise compensation signal for each secondary speaker is determined based on the reference noise signal set and the current filter coefficient set.

2. The method according to claim 1, characterized in that The step of determining a step factor set according to a reference noise signal set corresponding to a plurality of reference microphones comprises: For each reference microphone, obtain a reference noise signal corresponding to the reference microphone in the reference noise signal set, determine an average signal power according to a smoothing window length and the reference noise signal, and determine a step size factor corresponding to the reference microphone according to the average signal power and a filter order of the adaptive filter; Determining a step factor set according to the step factors corresponding to the multiple reference microphones; The product of the average signal power and the filter order is in inverse proportion to the step factor.

3. The method according to claim 1, characterized in that The step of determining a current filter coefficient set of an adaptive filter according to the reference noise signal set, the error noise signal set and the step factor set comprises: For each group of reference microphones and secondary speakers, obtain reference noise signals and step factors corresponding to the reference microphones in the reference noise signal set and the step factor set, respectively, and determine secondary filter signal sets corresponding to the reference microphones and the secondary speakers according to the reference noise signals, and determine current filter coefficients corresponding to the reference microphones and the secondary speakers according to the step factor, the error noise signal set, and the secondary filter signal set; Determining a current filter coefficient set of the adaptive filter according to the current filter coefficients corresponding to the multiple groups of reference microphones and the secondary speakers respectively; The secondary filter signal corresponding to each error microphone in the secondary filter signal set represents a noise signal of the reference noise signal of the reference microphone after passing through the secondary propagation path from the secondary speaker to the error microphone.

4. The method according to claim 3, characterized in that The step of determining, according to the reference noise signal, a set of secondary filter signals corresponding to the reference microphone and the secondary speaker comprises: For each error microphone, obtaining a secondary transfer function corresponding to a secondary propagation path from the secondary loudspeaker to the error microphone, and determining a secondary filter signal corresponding to the error microphone according to the reference noise signal and the secondary transfer function; A secondary filter signal set corresponding to the reference microphone and the secondary speaker is determined according to the secondary filter signals respectively corresponding to the plurality of error microphones.

5. The method according to claim 3, characterized in that: The determining, according to the step size factor, the error noise signal set, and the secondary filter signal set, current filter coefficients corresponding to the reference microphone and the secondary speaker comprises: Obtaining historical filter coefficients of the reference microphone and the secondary speaker at a previous adaptive iteration moment; Taking the error noise signal with the largest amplitude in the error noise signal set as the target error noise signal, and acquiring the target secondary filter signal from the secondary filter signal set according to the error microphone corresponding to the target error noise signal; determining an update gradient according to the step size factor, the target error noise signal and the target secondary filtered signal; According to the historical filter coefficients and the update gradient, current filter coefficients corresponding to the reference microphone and the secondary speaker are determined.

6. The method according to claim 1, characterized in that The step of determining the noise compensation signal of each secondary speaker according to the reference noise signal set and the current filter coefficient set comprises: For each secondary speaker, obtaining a plurality of current filter coefficients corresponding to the secondary speaker in the current filter coefficient set; Determine, according to the reference noise signal set and the plurality of current filter coefficients, a reference compensation signal corresponding to the secondary speaker and each reference microphone; A noise compensation signal of the secondary speaker is determined according to a plurality of reference compensation signals.

7. The method according to claim 6, characterized in that The step of determining the noise compensation signal of the secondary speaker according to the plurality of reference compensation signals comprises: Using the summation result corresponding to the plurality of reference compensation signals as the noise control signal of the secondary speaker; The noise control signal is processed by a speaker processing module to obtain a noise compensation signal, and the noise compensation signal is output to the secondary speaker; The loudspeaker processing module includes a digital-to-analog converter, a reconstruction filter and a power amplifier connected in series.

8. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: The reference processing module performs signal processing on the original reference signal set collected by multiple reference microphones to obtain a reference noise signal set; The error processing module processes the original error signal set collected by the multiple error microphones to obtain an error noise signal set; The reference processing module and the error processing module each include a voltage amplifier, an anti-aliasing filter and an analog-to-digital converter connected in series.

9. An active noise reduction device, characterized in that: include: A noise reduction cost function determination module, used to determine a noise reduction cost function according to a set of error noise signals corresponding to a plurality of error microphones; A step factor set determination module, configured to determine a step factor set according to a reference noise signal set corresponding to a plurality of reference microphones when the noise reduction cost function has not converged; wherein the step factors in the step factor set correspond one-to-one to the reference noise signals in the reference noise signal set, and the step factors are related to the fluctuation characteristics of the reference noise signals; A current filter coefficient set determination module, configured to determine a current filter coefficient set of an adaptive filter according to the reference noise signal set, the error noise signal set and the step factor set; wherein the current filter coefficient set includes current filter coefficients between each reference microphone and each secondary speaker; The noise compensation signal determination module is used to determine the noise compensation signal of each secondary speaker according to the reference noise signal set and the current filter coefficient set.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the active noise reduction method according to any one of claims 1 to 8.

11. An active noise reduction system, characterized in that: The active noise reduction system comprises a plurality of reference microphones, a plurality of secondary speakers, a plurality of error microphones, and the electronic device as claimed in claim 10; Wherein, the reference microphone is arranged near the noise source and is used to obtain a reference noise signal; The secondary speaker is arranged in the acoustic path between the reference microphone and the error microphone, and is used to output a noise compensation signal; The error microphone is arranged at a position far away from the noise source and is used to obtain an error noise signal.

12. A medical device host, characterized in that: The medical device host comprises a heat sink, a host board, a host protective shell and the active noise reduction system according to claim 11; Wherein, the heat sink is arranged on the host board, and the host board is arranged on the bottom plate of the host protective shell; The reference microphone in the active noise reduction system is arranged on the host board at a position close to the radiator, the secondary speaker and the error microphone are respectively arranged on the side panels of the host protective shell, the secondary speaker is embedded in the side panel, and the electronic device is arranged on the host board at a position other than the acoustic coverage area formed by the radiator and the error microphone.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the active noise reduction method according to any one of claims 1 to 8 when executed.

14. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the active noise reduction method according to any one of claims 1 to 8.

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