Noise control methods and devices for range hoods

Abstract

This application discloses a noise control method and apparatus for a range hood. The method includes: during the operation of the range hood, acquiring a current length value, a turbine noise signal, and a current turbine noise value; if the current turbine noise value is greater than a preset turbine noise threshold, performing signal segmentation processing on the turbine noise signal to obtain at least two noise signal segments; determining a desired noise signal based on the at least two noise signal segments and a primary path transfer function; determining an actual noise immunity signal based on the at least two noise signal segments, filter coefficients, and a secondary path transfer function; superimposing the desired noise signal and the actual noise immunity signal to obtain a current noise error signal; and updating the operating frequency of the range hood based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold. This application reduces the noise generated during the operation of the range hood.

Description

Technical Field

[0001] This application relates to the field of integrated stove control technology, and in particular to a noise control method and device for a range hood. Background Technology

[0002] Integrated cooktops, as a new type of kitchen appliance that integrates multiple cooking function modules, require a large air volume and air pressure due to their strong suction working principle, which is to efficiently remove oil fumes. This may generate noise during operation, especially in high-load scenarios such as stir-frying.

[0003] Because of this strong suction principle, it creates a powerful noise in the room. On the one hand, the oil pan itself makes some noise when cooking, and on the other hand, the noise from the range hood makes it unbearable for some users.

[0004] Therefore, in order to reduce the impact of noise during the operation of integrated stoves, traditional technologies such as fan selection, duct structure optimization, and the use of sound insulation materials are generally used to reduce noise. However, this noise reduction method is relatively mature and it is difficult to make significant breakthroughs or progress. Summary of the Invention

[0005] This application provides a noise control method and device for a range hood, which can reduce the noise generated during the operation of the range hood.

[0006] On the one hand, this application provides a noise control method for a range hood, wherein the range hood is equipped with a turbine, and the method includes: During the operation of the range hood, the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value are obtained. If the current turbine noise value is greater than a preset turbine noise threshold, the turbine noise signal is segmented according to the current length value to obtain at least two noise signal segments. The at least two noise signal segments and the primary path transfer function are convolved to obtain the desired noise signal. The at least two noise signal segments and the filter coefficients of the adaptive filter are convolved to obtain the noise reduction driving signal, and the noise reduction driving signal and the secondary path transfer function are convolved to obtain the actual noise reduction signal. The desired noise signal and the actual noise-resistant signal are superimposed to obtain the current noise error signal; The operating frequency of the range hood is updated based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0007] In one exemplary embodiment, before convolving the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise-reducing driving signal, and convolving the noise-reducing driving signal and the secondary path transfer function to obtain the actual noise-resistant signal, the method further includes: In response to the secondary path transfer function update instruction, a test input signal is generated; The test input signal and the initial secondary path transfer function are convolved to obtain the test output signal; The test input signal is processed by FFT to obtain the frequency domain input signal; The test output signal is processed by FFT to obtain the frequency domain output signal; Calculate the ratio between the frequency domain output signal and the frequency domain input signal to obtain the secondary path frequency response; The initial secondary path transfer function is updated based on the secondary path frequency response, and the updated secondary path transfer function is used as the secondary path transfer function.

[0008] In one exemplary embodiment, updating the initial secondary path transfer function based on the secondary path frequency response and using the updated secondary path transfer function as the secondary path transfer function includes: The amplitude of the frequency response of the secondary path is normalized to obtain the processed frequency response; The processed frequency response is subjected to IFFT processing to obtain the compensation coefficients corresponding to the initial secondary path transfer function; The initial secondary path transfer function and the compensation coefficient are convolved to obtain the updated secondary path transfer function. The updated secondary path transfer function is used as the secondary path transfer function.

[0009] In one exemplary embodiment, the step of convolving the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise reduction driving signal, and then convolving the noise reduction driving signal and the secondary path transfer function to obtain an actual noise-resistant signal, includes: Each noise signal segment is polled sequentially. For the current noise signal segment polled, the desired noise signal segment adjacent to the current noise signal segment is obtained. The sampling point corresponding to the desired noise signal segment is smaller than the sampling point corresponding to the current noise signal segment. The current noise signal segment is spliced ​​with the desired noise signal segment to obtain the target noise signal segment; Perform FFT processing on the target noise signal segment to obtain the frequency domain noise signal segment; The length of the adaptive filter is extended to obtain an updated adaptive filter. The actual noise-resistant signal is determined based on the frequency domain noise signal segment, the updated adaptive filter, and the secondary path transfer function.

[0010] In one exemplary embodiment, determining the actual noise-resistant signal based on the frequency domain noise signal segment, the updated adaptive filter, and the secondary path transfer function includes: The updated adaptive filter coefficients are subjected to FFT processing to obtain the frequency domain filter coefficients; The frequency domain noise signal segment and the frequency domain filter coefficients are subjected to point-by-point complex multiplication to obtain the frequency domain noise reduction drive signal. The frequency domain noise reduction driving signal is processed by IFFT to obtain the time domain noise reduction driving signal; The time-domain denoising driving signal is filtered to obtain the denoising driving signal; The noise reduction driving signal and the secondary path transfer function are convolved to obtain the actual noise-resistant signal.

[0011] In one exemplary embodiment, the range hood further includes a motor; the step of updating the operating frequency of the range hood based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold, includes: The filter coefficients of the adaptive filter are updated based on the current noise error signal and the at least two noise signal segments to obtain the updated filter coefficients. The duty cycle of the motor is updated based on the updated filter coefficients to obtain the updated duty cycle of the motor. The motor is controlled to operate at the updated duty cycle so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0012] In one exemplary embodiment, updating the filter coefficients of the adaptive filter based on the current noise error signal and the at least two noise signal segments to obtain updated filter coefficients includes: If the current noise error signal does not meet the preset noise error condition, the current noise error signal is expanded to obtain an expanded noise error signal segment. The expanded noise error signal segment is processed by FFT to obtain the frequency domain error signal segment; Based on the frequency domain error signal segment and the current noise signal segment, the filter coefficients of the adaptive filter are updated until a preset condition is met, thus obtaining the updated filter coefficients.

[0013] In one exemplary embodiment, updating the filter coefficients of the adaptive filter based on the frequency domain error signal segment and the current noise signal segment until a preset condition is met, to obtain the updated filter coefficients, includes: The current noise signal segment and the preset filter transfer function are convolved to obtain a corrected reference noise signal; the preset filter transfer function is an estimate of the secondary path transfer function. Based on the frequency domain error signal segment and the corrected reference noise signal, the filter coefficients of the adaptive filter are updated until the output noise error signal meets the preset noise error condition, thus obtaining the updated filter coefficients.

[0014] In one exemplary embodiment, updating the duty cycle of the motor based on the updated filter coefficients to obtain the updated duty cycle corresponding to the motor includes: The noise reduction driving signal corresponding to the noise error signal that satisfies the preset noise error condition is taken as the target noise reduction driving signal; Calculate the root mean square value of the target noise reduction driving signal to obtain the target root mean square value; The target duty cycle is obtained by searching the preset root mean square value duty cycle relationship library for a duty cycle that matches the target root mean square value; the preset root mean square value duty cycle relationship library includes a mapping relationship between preset root mean square values ​​and preset duty cycles. The target duty cycle is used as the updated duty cycle.

[0015] On the other hand, this application provides a noise control method for a range hood, wherein the range hood is equipped with a turbine and a motor, and the method includes: In response to the secondary path transfer function update instruction, a test input signal is generated; The test input signal and the initial secondary path transfer function are convolved to obtain the test output signal; The test input signal is processed by FFT to obtain the frequency domain input signal; The test output signal is processed by FFT to obtain the frequency domain output signal; Calculate the ratio between the frequency domain output signal and the frequency domain input signal to obtain the secondary path frequency response; The amplitude of the frequency response of the secondary path is normalized to obtain the processed frequency response; The processed frequency response is subjected to IFFT processing to obtain the compensation coefficients corresponding to the initial secondary path transfer function; The initial secondary path transfer function and the compensation coefficient are convolved to obtain the updated secondary path transfer function. The updated secondary path transfer function is used as the secondary path transfer function.

[0016] During the operation of the range hood, the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value are obtained. If the current turbine noise value is greater than a preset turbine noise threshold, the turbine noise signal is segmented according to the current length value to obtain at least two noise signal segments. The at least two noise signal segments and the primary path transfer function are convolved to obtain the desired noise signal. Each noise signal segment is polled sequentially. For the current noise signal segment polled, the desired noise signal segment adjacent to the current noise signal segment is obtained. The sampling point corresponding to the desired noise signal segment is smaller than the sampling point corresponding to the current noise signal segment. The current noise signal segment is spliced ​​with the desired noise signal segment to obtain the target noise signal segment; Perform FFT processing on the target noise signal segment to obtain the frequency domain noise signal segment; The length of the adaptive filter is extended to obtain an updated adaptive filter. The updated adaptive filter coefficients are subjected to FFT processing to obtain the frequency domain filter coefficients; The frequency domain noise signal segment and the frequency domain filter coefficients are subjected to point-by-point complex multiplication to obtain the frequency domain noise reduction drive signal. The frequency domain noise reduction driving signal is processed by IFFT to obtain the time domain noise reduction driving signal; The time-domain denoising drive signal is filtered to obtain a denoising drive signal; The noise reduction driving signal and the secondary path transfer function are convolved to obtain the actual noise-resistant signal; The desired noise signal and the actual noise-resistant signal are superimposed to obtain the current noise error signal; If the current noise error signal does not meet the preset noise error condition, the current noise error signal is expanded to obtain an expanded noise error signal segment. The expanded noise error signal segment is processed by FFT to obtain the frequency domain error signal segment; The current noise signal segment and the preset filter transfer function are convolved to obtain a corrected reference noise signal; the preset filter transfer function is an estimate of the secondary path transfer function. Based on the frequency domain error signal segment and the corrected reference noise signal, the filter coefficients of the adaptive filter are updated until the output noise error signal meets the preset noise error condition, thus obtaining the updated filter coefficients. The noise reduction driving signal corresponding to the noise error signal that satisfies the preset noise error condition is taken as the target noise reduction driving signal; Calculate the root mean square value of the target noise reduction driving signal to obtain the target root mean square value; The target duty cycle is obtained by searching the preset root mean square value duty cycle relationship library for a duty cycle that matches the target root mean square value; the preset root mean square value duty cycle relationship library includes a mapping relationship between preset root mean square values ​​and preset duty cycles. Use the target duty cycle as the updated duty cycle; The motor is controlled to operate at the updated duty cycle so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0017] On the other hand, a noise control device for a range hood is provided, wherein a turbine is installed inside the range hood, and the device includes: The acquisition module is used to acquire the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value during the operation of the range hood. The segmentation module is used to perform signal segmentation processing on the turbine noise signal according to the current length value if the current turbine noise value is greater than a preset turbine noise threshold, so as to obtain at least two noise signal segments. The desired noise signal determination module is used to perform convolution processing on the at least two noise signal segments and the primary path transfer function to obtain the desired noise signal. The actual noise reduction signal determination module is used to perform convolution processing on the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise reduction driving signal, and to perform convolution processing on the noise reduction driving signal and the secondary path transfer function to obtain an actual noise reduction signal. The current noise error signal determination module is used to superimpose the desired noise signal and the actual anti-noise signal to obtain the current noise error signal; The noise reduction module is used to update the operating frequency of the range hood based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0018] On the other hand, an integrated stove is provided, which is equipped with the range hood described above and performs the noise control method of the range hood described above.

[0019] On the other hand, an electronic device is provided, the device including a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded by the processor and executed as described above for the noise control method of a range hood.

[0020] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored therein, the at least one instruction or at least one program being loaded and executed by a processor to implement the noise control method for the range hood as described above.

[0021] On the other hand, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the noise control method for the range hood as described above.

[0022] This application provides a noise control method and apparatus for a range hood, which has the following technical effects: During the operation of the range hood, the method acquires the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value; if the current turbine noise value is greater than a preset turbine noise threshold, the turbine noise signal is segmented according to the current length value to obtain at least two noise signal segments; the at least two noise signal segments and the primary path transfer function are convolved to obtain a desired noise signal; the at least two noise signal segments and the filter coefficients of the adaptive filter are convolved to obtain a noise reduction drive signal, and the noise reduction drive signal and the secondary path transfer function are convolved to obtain an actual noise reduction signal; the desired noise signal and the actual noise reduction signal are superimposed to obtain a current noise error signal; the operating frequency of the range hood is updated according to the current noise error signal and the at least two noise signal segments to make the noise generated by the turbine during operation less than the preset turbine noise threshold. During the operation of the range hood, the current length value of the adaptive filter, the turbine noise signal, and the current turbine noise value are acquired in real time. When the current turbine noise value exceeds the limit, the turbine noise signal is segmented according to the current length value to reduce the amount of computation. Based on the segmented noise signal segments, the primary path transfer function, the filter coefficients of the adaptive filter, and the secondary path transfer function, the current noise error signal is determined to obtain accurate range hood noise. The operating frequency of the range hood is updated based on the noise error signal and the noise signal segments to achieve precise control of the noise generated by the range hood during operation, so that the range hood operates in the low-noise zone for as long as possible, thereby minimizing the user's exposure to high-noise environments. Attached Figure Description

[0023] To more clearly illustrate the technical solutions and advantages in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating a noise control method for a range hood provided in the embodiments of this specification; Figure 2 This is a schematic diagram of an Fx-LMS adaptive control system provided in the embodiments of this specification; Figure 3 This is a flowchart illustrating a first noise control method for an integrated stove provided in an embodiment of this specification. Figure 4 This is a flowchart illustrating a second noise control method for an integrated stove provided in an embodiment of this specification. Figure 5 This is a structural schematic diagram of the noise control device for the range hood provided in the embodiments of this specification.

[0025] Figure 6 This is a schematic diagram of the server structure for a noise control method for a range hood provided in the embodiments of this specification. Detailed Implementation The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0027] The following describes a noise control method for a range hood according to this application. Figure 1 This is a flowchart illustrating a noise control method for a range hood provided in an embodiment of this specification. This specification provides the operational steps of the method described in the embodiment or flowchart, but based on conventional or non-inventive labor, more or fewer operational steps may be included. The order of steps listed in the embodiment is merely one possible execution order among many and does not represent the only possible execution order. In actual system or server product execution, the method can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment) as shown in the embodiment or drawings. Specifically, as... Figure 1 As shown, the method can be applied to the control unit of a range hood, which contains a turbine. The method includes: S101: During the operation of the range hood, the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value are obtained.

[0028] In the embodiments of this specification, during the operation of the range hood, the suction power data of the range hood and the current length value of the adaptive filter corresponding to the range hood are acquired in real time; wherein, the suction power data includes one or more of the following: turbine noise signal corresponding to the turbine, turbine wind pressure, air volume of the range hood, and resistance of the common flue; wherein, the turbine wind pressure can be acquired by a pressure sensor, and the air volume of the range hood is also acquired by a sensor, such as a Hall element; After obtaining the suction power data, the system can use the standard wind pressure curve under a preset airflow to determine whether the turbine wind pressure and the range hood airflow are matched. If an inconsistency is found, the system determines that the current kitchen is in a negative pressure environment and transmits the result to the speaker to remind the user. The user can then alleviate the negative pressure in the kitchen by opening a door or window, thereby reducing noise. Regarding the resistance of the common flue, it can be compared with a preset threshold to adaptively adjust the motor's duty cycle. This avoids insufficient exhaust when the back pressure is high and excessive noise when the back pressure is low. The system also reminds the user when the resistance of the common flue is too high, allowing the user to turn on the range hood at off-peak times to avoid excessive noise caused by high resistance. Regarding turbine noise, in some cases, the vibration generated by the motor can resonate with the integrated stove (which includes the range hood). The system can determine the resonance range between the motor and the range hood and automatically adjust the motor's duty cycle to achieve active noise reduction. To determine whether the noise generated by the turbine during operation exceeds the limit, the acquired turbine noise signal needs to be processed to obtain the current turbine noise value. Since the turbine noise signal is a voltage signal including multiple sampling points, the root mean square (RMS) value of the turbine noise signal can be calculated based on the number of sampling points and the voltage value corresponding to each sampling point. This RMS value represents the current turbine noise value. Alternatively, the turbine noise decibel value can be calculated based on the calculated RMS value and a reference sound pressure level (such as 20 micropascals, which corresponds to the hearing threshold of the human ear). In this case, the turbine noise decibel value is used as the current turbine noise value. Meanwhile, in order to provide a reasonable basis for subsequent segmentation processing of the turbine noise signal acquired in real time, and to make frequency domain block processing and time domain convolution mathematically equivalent, it is necessary to obtain the current length value of the adaptive filter to ensure the correctness of the subsequent frequency domain fast convolution algorithm.

[0029] S103: If the current turbine noise value is greater than the preset turbine noise threshold, the turbine noise signal is segmented according to the current length value to obtain at least two noise signal segments.

[0030] In the embodiments of this specification, the preset turbine noise threshold is a threshold for determining whether the noise generated by the turbine during operation exceeds the limit; if the current turbine noise value is greater than the preset turbine noise threshold, the turbine noise signal is segmented according to the current length value, that is, the turbine noise signal is divided into at least two noise signal segments, and the total number of sampling points of each noise signal segment is the current length value; for example, the current length value of the adaptive filter is N, and the turbine noise signal x(n) is divided into a block according to every N points, the first block x(1) = [x(1), x(2), ... x(N)], the second block x(2) = [x(N+1), x(N+2), ... x(2N)], the third block x(3) = [x(2N+1), ... x(3N)] ... and so on.

[0031] S105: Convolve the at least two noise signal segments and the primary path transfer function to obtain the desired noise signal.

[0032] In the embodiments described in this specification, such as Figure 2 As shown, Figure 2 This document provides a schematic diagram of an Fx-LMS adaptive control system, where x(n) is a reference signal, the input source of the entire adaptive control system, and here it represents at least two noise signal segments. P(z) is the primary path transfer function, used to simulate the characteristics of noise transmission from the noise source (turbine) to the error point (e.g., near the range hood). When processing the turbine noise signal, it is done in the time domain, and the time domain form of the primary path transfer function P(z) is its impulse response p(n). Each noise signal segment is polled sequentially, and for the current noise signal segment, convolution is performed on the current noise signal segment and the primary path transfer function, i.e., the impulse response p(n) of the primary path, to obtain the output of the primary path, i.e., the desired noise signal d(n) corresponding to the current noise signal segment. This convolution process simulates real noise propagation. Specifically, the desired noise signal d(n) heard at the error microphone is not the original turbine noise signal x(n), but a version distorted by the actual physical path (e.g., a public flue or kitchen).

[0033] S107: Convolve the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise reduction driving signal, and convolve the noise reduction driving signal and the secondary path transfer function to obtain an actual noise reduction signal.

[0034] In the embodiments of this specification, each noise signal segment is polled sequentially. For the current noise signal segment polled, it is concatenated with the adjacent noise signal segments to form a target noise signal segment. Based on the target noise signal segment and the filter coefficients of the adaptive filter w(z), the initial noise reduction driving signal corresponding to the current noise signal segment is obtained. The initial noise reduction driving signals corresponding to each noise signal segment are concatenated to obtain the noise reduction driving signal y(n). The noise reduction driving signal y(n) and the secondary path transfer function S(z) are convolved to obtain the actual noise-resistant signal y´(n). The actual noise-resistant signal has the same frequency and opposite phase to the desired noise signal.

[0035] In the embodiments of this specification, before convolving the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain the noise reduction driving signal, and convolving the noise reduction driving signal and the secondary path transfer function to obtain the actual noise-resistant signal, the method further includes: In response to the secondary path transfer function update instruction, a test input signal is generated; In the embodiments of this specification, the spectral characteristics of the filter will change after the acquired turbine noise signal and the secondary path transfer function are convolved, resulting in an uneven frequency response of the secondary network. That is, some frequencies are enhanced and some frequencies are attenuated, which leads to uneven noise reduction. Therefore, it is necessary to perform equalization processing on the secondary path, that is, to perform frequency domain processing on the impulse response of the secondary path to force it to have a uniform amplitude response throughout the entire frequency band, so that the adaptive algorithm will not be affected by the frequency distortion of the secondary path itself during subsequent operation, thereby achieving uniform cancellation of noise at different frequencies. In response to the secondary path transfer function update instruction, a test input signal is generated. For example, a known excitation signal (such as white noise or a swept frequency signal) can be played in the range hood.

[0036] The test input signal and the initial secondary path transfer function are convolved to obtain the test output signal; In the embodiments of this specification, the test input signal and the initial secondary path transfer function are convolved to obtain the test output signal; wherein, the secondary path impulse response corresponding to the initial secondary path transfer function is real and unprocessed.

[0037] The test input signal is processed by FFT to obtain the frequency domain input signal; In the embodiments of this specification, the test input signal is processed by fast Fourier transform (FFT) to transform it to the frequency domain, thus obtaining the frequency domain input signal.

[0038] The test output signal is processed by FFT to obtain the frequency domain output signal; In the embodiments of this specification, the test output signal is subjected to FFT processing to convert it to the frequency domain, thereby obtaining the frequency domain output signal.

[0039] Calculate the ratio between the frequency domain output signal and the frequency domain input signal to obtain the secondary path frequency response; In the embodiments of this specification, the ratio between the frequency domain output signal and the frequency domain input signal is calculated to obtain the secondary path frequency response, that is, the complex representation of the initial secondary path in the frequency domain, which includes amplitude and phase information.

[0040] The initial secondary path transfer function is updated based on the secondary path frequency response, and the updated secondary path transfer function is used as the secondary path transfer function.

[0041] In the embodiments of this specification, the frequency response of the secondary path is equalized, retaining only its phase information while forcibly setting its amplitude to 1, resulting in a processed frequency response with a constant amplitude of 1, but with phase characteristics completely consistent with the initial secondary path. The processed frequency response is then converted back to the time domain, and based on the processed frequency response and the initial secondary path transfer function, an updated secondary path transfer function is determined and used as the final secondary path transfer function. By equalizing the secondary path, the enhancement or attenuation effect of the secondary path itself on certain frequencies is effectively eliminated, ensuring that the convergence process of the subsequent adaptive filter is no longer interfered with. This results in a more uniform and stable noise reduction effect across the entire frequency band, faster convergence speed, and significantly improved noise control performance and robustness of the range hood during operation.

[0042] In this embodiment of the specification, updating the initial secondary path transfer function based on the secondary path frequency response and using the updated secondary path transfer function as the secondary path transfer function includes: The amplitude of the frequency response of the secondary path is normalized to obtain the processed frequency response; In the embodiments of this specification, in order to flatten the uneven frequency response of the secondary path, a filter is needed whose frequency response is exactly the reciprocal of the secondary path frequency response. That is, the amplitude of the secondary path frequency response is normalized to obtain the processed frequency response, which is exactly the reciprocal of the secondary path frequency response. In order to prevent division by zero or amplification of noise, the amplitude can be appropriately limited. That is, when the amplitude is very small, excessive amplification is not performed, so that the overall gain is 1.

[0043] The processed frequency response is subjected to IFFT processing to obtain the compensation coefficients corresponding to the initial secondary path transfer function; In the embodiments of this specification, the processed frequency response is subjected to inverse fast Fourier transform (IFFT) to obtain the compensation coefficients corresponding to the initial secondary path transfer function. Essentially, the processed frequency response is the impulse response in the time domain, which can be understood as an equalization filter.

[0044] The initial secondary path transfer function and the compensation coefficient are convolved to obtain the updated secondary path transfer function. In the embodiments of this specification, from the perspective of signal processing, it can be understood that an equalization filter is connected in series between the adaptive filter and the secondary path, so that the input signal is processed in the order of adaptive filter-equalization filter-secondary path. From an operational perspective, the series connection between the equalization filter and the secondary path is equivalent to convolution in the time domain. Therefore, convolution processing is performed on the initial secondary path transfer function and the compensation coefficients, that is, convolution processing is performed on the impulse response of the initial secondary path transfer function and the impulse response of the equalization filter to obtain the updated secondary path transfer function.

[0045] The updated secondary path transfer function is used as the secondary path transfer function.

[0046] In the embodiments of this specification, the updated secondary path transfer function is used as the secondary path transfer function. By performing equalization processing on the secondary path transfer function, the overall response after convolution is made close to an ideal flat frequency response, avoiding uneven noise reduction during actual use of the range hood, which helps to improve the noise reduction performance of the range hood during operation and optimize the user experience.

[0047] In the embodiments of this specification, the step of convolving the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise reduction driving signal, and then convolving the noise reduction driving signal and the secondary path transfer function to obtain an actual noise-resistant signal, includes: Each noise signal segment is polled sequentially. For the current noise signal segment polled, the desired noise signal segment adjacent to the current noise signal segment is obtained. The sampling point corresponding to the desired noise signal segment is smaller than the sampling point corresponding to the current noise signal segment. In the embodiments of this specification, each noise signal segment is polled sequentially. For the current noise signal segment polled, in order to avoid circular convolution while performing linear convolution in the frequency domain, the data block needs to be expanded by concatenating the current block x(k) with the previous block x(k-1), that is, obtaining the desired noise signal segment adjacent to the current noise signal segment, and the sampling point corresponding to the desired noise signal segment is smaller than the sampling point corresponding to the current noise signal segment.

[0048] The current noise signal segment is spliced ​​with the desired noise signal segment to obtain the target noise signal segment; In the embodiments described in this specification, the current noise signal segment x(k) and the desired noise signal segment x(k-1) are concatenated to obtain the target noise signal segment [x]. T (k-1), x T (k)】 T It is essentially an extension block of length 2N.

[0049] Perform FFT processing on the target noise signal segment to obtain the frequency domain noise signal segment; In the embodiments of this specification, the target noise signal segment is subjected to FFT processing to convert it to the frequency domain, thereby obtaining the frequency domain noise signal segment.

[0050] The length of the adaptive filter is extended to obtain an updated adaptive filter. In the embodiments of this specification, in the time domain, filtering is linear convolution. If two sequences of length N are directly multiplied by FFT and then IFFT, the result is circular convolution, which will produce aliasing error. Therefore, both sequences are expanded to at least 2N points. Then, the first N points of the time domain result corresponding to the frequency domain multiplication are the result of linear convolution. When the overlap preservation method is used, the last N points are taken as the effective output. Since the length of the target noise signal segment is already 2N, the length of the adaptive filter is extended, that is, the filter coefficients of the adaptive filter are extended to form a new sequence of length 2N, thus obtaining the updated adaptive filter.

[0051] The actual noise-resistant signal is determined based on the frequency domain noise signal segment, the updated adaptive filter, and the secondary path transfer function.

[0052] In the embodiments described in this specification, the frequency domain noise signal segment is sequentially passed through an updated adaptive filter and a secondary path to obtain the actual noise-resistant signal. By segmenting the turbine noise signal into blocks, the continuous signal is divided into fixed-length data blocks. Combined with a frequency domain filter, the time-consuming time-domain convolution operation is transformed into a computationally efficient frequency domain multiplication using FFT, which significantly reduces processing latency and computational load, generating the actual noise-resistant signal and achieving efficient, real-time active noise control.

[0053] In the embodiments of this specification, determining the actual noise-resistant signal based on the frequency domain noise signal segment, the updated adaptive filter, and the secondary path transfer function includes: The updated adaptive filter coefficients are subjected to FFT processing to obtain the frequency domain filter coefficients; In the embodiments of this specification, the filter coefficients of the updated adaptive filter are subjected to FFT processing to obtain its frequency domain representation, namely the frequency domain filter coefficients, which are frequency domain vectors of length 2N.

[0054] The frequency domain noise signal segment and the frequency domain filter coefficients are subjected to point-by-point complex multiplication to obtain the frequency domain noise reduction drive signal. In the embodiments of this specification, since the frequency domain noise signal segment has 2N points and the frequency domain filter coefficients also have 2N points, the frequency domain noise signal segment and the frequency domain filter coefficients are multiplied point by point to obtain the frequency domain noise reduction driving signal.

[0055] The frequency domain noise reduction driving signal is processed by IFFT to obtain the time domain noise reduction driving signal; In the embodiments of this specification, the frequency domain noise reduction driving signal is processed by IFFT and converted to the time domain to obtain the time domain noise reduction driving signal.

[0056] The time-domain denoising driving signal is filtered to obtain the denoising driving signal; In the embodiments of this specification, the time-domain noise reduction driving signal is filtered, the first N points are discarded because these points are distorted due to circular convolution, and the last N points are retained as the effective filter output of the current noise signal segment to obtain the noise reduction driving signal corresponding to the current noise signal segment.

[0057] The noise reduction driving signal and the secondary path transfer function are convolved to obtain the actual noise-resistant signal.

[0058] In the embodiments of this specification, the noise reduction driving signal is input into the secondary path and convolved with the impulse response of the secondary path transfer function S(z) to obtain the actual noise reduction signal y´(n).

[0059] By multiplying the expanded filter coefficients point-by-point in the frequency domain with the segmented frequency domain noise signal, it is equivalent to generating a frequency domain noise reduction driving signal using time domain convolution, which greatly reduces computational complexity and improves real-time performance. Discarding aliasing points ensures the continuity of the output waveform, so that after the output noise reduction driving signal is physically propagated through the secondary path, it generates an actual anti-noise signal with the same amplitude and opposite phase to the current noise signal segment at the error point, thereby achieving accurate and efficient active noise reduction.

[0060] S109: The desired noise signal and the actual noise immunity signal are superimposed to obtain the current noise error signal.

[0061] In the embodiments of this specification, the difference between the desired noise signal and the actual noise-resistant signal is calculated to obtain the current noise error signal e(n), which represents the residual noise after noise reduction.

[0062] S111: The operating frequency of the range hood is updated based on the current noise error signal and the turbine noise signal, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0063] In the embodiments of this specification, when the current noise error signal is large, i.e., does not meet the preset noise error condition, the filter coefficients of the adaptive filter are updated based on the current noise error signal and at least two noise signal segments. When the output noise error signal meets the preset noise error condition, the operating frequency of the range hood, specifically the duty cycle of the motor inside the range hood, is updated using the noise reduction drive signal corresponding to the noise error signal that meets the preset noise error condition. The motor operates with the updated duty cycle so that the noise generated by the turbine during operation is less than the preset noise threshold, ensuring that the noise is effectively suppressed.

[0064] In this embodiment of the specification, the range hood further includes a motor; the step of updating the operating frequency of the range hood based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold, includes: The filter coefficients of the adaptive filter are updated based on the current noise error signal and the at least two noise signal segments to obtain the updated filter coefficients. In the embodiments described in this specification, the current noise signal segment is passed through a preset filter transfer function. The corrected reference noise signal is obtained, and the filter coefficients of the adaptive filter are updated by combining the current noise error signal, the corrected reference noise signal and the LMS algorithm to obtain the updated filter coefficients.

[0065] In this embodiment of the specification, the step of updating the filter coefficients of the adaptive filter based on the current noise error signal and the at least two noise signal segments to obtain the updated filter coefficients includes: If the current noise error signal does not meet the preset noise error condition, the current noise error signal is expanded to obtain an expanded noise error signal segment. In the embodiments of this specification, the current noise error signal consists of multiple voltage signals corresponding to multiple sampling points. The mean square value (MSF) or average square value (MSB) corresponding to the current noise error signal can be calculated based on the number of sampling points and the multiple voltage signal values. The calculated MSF or MSB is compared with a preset voltage threshold, which is adjusted according to the type of calculation result to achieve accurate comparison. If the calculated MSF or MSB is less than the preset voltage threshold, it indicates that the residual noise energy within several sampling points is very low, meeting the noise reduction requirements, i.e., satisfying the preset noise error condition. In this case, there is no need to update the filter coefficients of the adaptive filter. If the calculated MSF or MSB is greater than or equal to the preset voltage threshold, it indicates that the residual noise is too large, and the noise reduction effect does not meet the requirements, i.e., the preset noise error condition is not satisfied. In this case, the filter coefficient update process is triggered. Specifically, for the current noise error signal segment, a zero column vector of length N, 0 = [0, 0, ..., 0], is created. T The zero vector is vertically spliced ​​with the current noise error signal segment, which expands the current noise error signal segment to obtain a column vector of length 2N, which is the expanded noise error signal segment.

[0066] The expanded noise error signal segment is processed by FFT to obtain the frequency domain error signal segment; In the embodiments of this specification, the expanded noise error signal segment is subjected to FFT processing to convert it to the frequency domain, thereby obtaining the frequency domain error signal segment corresponding to the current noise error signal segment.

[0067] Based on the frequency domain error signal segment and the current noise signal segment, the filter coefficients of the adaptive filter are updated until a preset condition is met, thus obtaining the updated filter coefficients.

[0068] In the embodiments described in this specification, the current noise signal segment is compared with the preset filter transfer function. Convolution processing is performed to obtain a corrected reference noise signal, and the current filter coefficients of the adaptive filter are obtained. The filter coefficients of the adaptive filter are updated by combining the frequency domain error signal segment, the corrected reference noise signal, and the current filter coefficients until a preset condition is met, i.e., the noise error signal is less than a preset noise error threshold. When the current noise error signal is too large, the filter coefficients are updated in conjunction with the current noise signal segment. This achieves real-time evaluation of the noise reduction gap using the current noise error signal, and calculates the filter coefficient correction amount based on the noise characteristics of the current noise signal segment for dynamic and precise noise reduction. The filter dynamically tracks noise changes and generates inverse acoustic waves to continuously suppress the error energy below the preset noise error threshold, achieving stable convergence.

[0069] In this embodiment of the specification, updating the filter coefficients of the adaptive filter based on the frequency domain error signal segment and the current noise signal segment until a preset condition is met, to obtain the updated filter coefficients, includes: The current noise signal segment and the preset filter transfer function are convolved to obtain a corrected reference noise signal; the preset filter transfer function is an estimate of the secondary path transfer function. In the embodiments of this specification, the preset filter transfer function is an estimate of the secondary path transfer function; the impulse response of the current noise signal segment and the preset filter transfer function is convolved to obtain the corrected reference noise signal.

[0070] Based on the frequency domain error signal segment and the corrected reference noise signal, the filter coefficients of the adaptive filter are updated until the output noise error signal meets the preset noise error condition, thus obtaining the updated filter coefficients.

[0071] In the embodiments of this specification, the corrected reference noise signal is processed by FFT to transform it to the frequency domain, obtaining a frequency domain filtered reference signal, which is essentially a complex vector. The complex conjugate of the frequency domain filtered reference signal is calculated, that is, for each frequency point of the frequency domain filtered reference signal, the imaginary part of each complex number is inverted while the real part remains unchanged. The complex conjugate of the frequency domain filtered reference signal and the frequency domain filtered reference signal are multiplied point by point to obtain the frequency domain instantaneous gradient estimate, which is also essentially a complex vector. It indicates the direction and magnitude in which the filter coefficients should be updated at each frequency component under the current noise signal segment to reduce the noise error signal. Then, the frequency... The instantaneous gradient estimate in the frequency domain is multiplied by a step size factor to obtain the frequency domain coefficient update. The step size factor controls the update step size, ensuring smooth and stable convergence of the coefficients and avoiding oscillations or divergence. The frequency domain filter coefficients of the adaptive filter are then added to the frequency domain filter coefficient update to obtain the updated frequency domain filter coefficients. This updated frequency domain filter coefficients are then processed by IFFT to obtain the updated filter coefficients. Next, the next noise signal segment is used as input, and the corresponding noise error signal is obtained. If the noise error signal meets the preset noise error condition, the updated filter coefficients obtained at this time are used as the updated filter coefficients; otherwise, the filter coefficients are updated again. By calculating the frequency domain gradient, the complex time-domain convolution is transformed into an efficient frequency-domain dot product, significantly reducing computational complexity and achieving uniform and stable convergence. While ensuring the noise reduction depth, the system power consumption and processing latency are significantly reduced, achieving efficient and accurate full-band adaptive noise reduction and improving the performance of the range hood.

[0072] The duty cycle of the motor is updated based on the updated filter coefficients to obtain the updated duty cycle of the motor. In the embodiments of this specification, the moment when the updated filter coefficients are obtained indicates that the noise error signal at this time meets the preset noise error condition. The duty cycle of the motor is updated according to the noise reduction drive signal output at this time to obtain the updated duty cycle of the motor.

[0073] In this embodiment of the specification, updating the duty cycle of the motor based on the updated filter coefficients to obtain the updated duty cycle corresponding to the motor includes: The noise reduction driving signal corresponding to the noise error signal that satisfies the preset noise error condition is taken as the target noise reduction driving signal; In the embodiments of this specification, when the mean square value of the output noise error signal is less than the preset noise error threshold, it indicates that the system has entered a good noise reduction state. The noise reduction driving signal corresponding to the noise error signal that meets the preset noise error condition is taken as the target noise reduction driving signal, and the duty cycle optimization process based on the target noise reduction driving signal is started.

[0074] Calculate the root mean square value of the target noise reduction driving signal to obtain the target root mean square value; In the embodiments of this specification, the number of sampling points in the target noise reduction driving signal and the voltage value corresponding to each sampling point are obtained. Based on the two, the root mean square value of the target noise reduction driving signal is calculated to obtain the target root mean square value, which reflects the noise immunity strength.

[0075] The target duty cycle is obtained by searching the preset root mean square value duty cycle relationship library for a duty cycle that matches the target root mean square value; the preset root mean square value duty cycle relationship library includes a mapping relationship between preset root mean square values ​​and preset duty cycles. In the embodiments of this specification, a preset root mean square (RMS) duty cycle library is provided, which includes a mapping relationship between preset RMS values ​​and preset duty cycles. The target duty cycle is obtained by searching the preset RMS duty cycle library for a duty cycle that matches the target RMS value. If the target noise reduction drive signal is strong, it indicates that a larger cancellation force is required. At this time, the turbine noise is strong, and the duty cycle can be reduced, i.e., the target duty cycle is low. If the target noise reduction drive signal is low, it indicates that the noise cancellation requirement is small. At this time, the turbine noise is weak, and the current duty cycle may already be in an optimal state. Therefore, the target duty cycle decreases less than the existing duty cycle.

[0076] The target duty cycle is used as the updated duty cycle.

[0077] In the embodiments of this specification, the target duty cycle is used as the updated duty cycle to achieve noise adjustment of the range hood; when the noise reduction effect meets the requirements, the duty cycle is adjusted using the current noise reduction drive signal to achieve active suppression of source noise and energy efficiency optimization, so that the range hood automatically seeks the optimal energy consumption operating point while maintaining the noise reduction effect, achieving dual optimization of quietness and energy saving.

[0078] The motor is controlled to operate at the updated duty cycle so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0079] In the embodiments of this specification, during the operation of the range hood, the duty cycle of the motor directly determines its average speed. An increase in the duty cycle leads to a higher motor speed, while a decrease in the duty cycle leads to a lower motor speed. An increase in motor speed directly results in a faster turbine rotation speed, enhancing suction (airflow and air pressure). Simultaneously, the aerodynamic noise generated by the turbine's high-speed rotation cutting the air, as well as the electromagnetic and mechanical noise of the motor itself, are significantly increased. Therefore, the updated duty cycle is lower than the original duty cycle. When the noise generated by the turbine is too high, the motor is controlled to run with the updated duty cycle, thereby reducing the motor speed and directly reducing the intensity of the turbine noise from the source, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold. By monitoring the update status of the filter coefficients of the adaptive filter and mapping them to the motor duty cycle, the noise generation is reduced from the source.

[0080] In one exemplary implementation, such as Figure 3 As shown, Figure 3 A flowchart illustrating a first noise control method for an integrated stove provided in this specification, comprising: S301: Real-time acquisition of suction power data from the range hood.

[0081] In the embodiments of this specification, the integrated stove includes a range hood; the range hood is equipped with a turbine and is connected to a common flue; during the operation of the range hood, the suction power data of the range hood is acquired in real time; wherein, the suction power data includes one or more of the following: turbine wind pressure, range hood air volume, turbine noise, and common flue resistance; S302: Determine whether the turbine noise exceeds the preset noise threshold.

[0082] In the embodiments of this specification, a preset noise threshold is set to compare with the turbine noise obtained in real time to determine whether the turbine noise exceeds the limit.

[0083] S303: Determine the resonance range of the range hood based on turbine noise.

[0084] In the embodiments described in this specification, a vibration sensor and an onboard microphone can be installed inside the range hood. During the operation of the range hood, the noise frequency of the turbine is acquired in real time through the onboard microphone, and the vibration frequency of the turbine is acquired through the vibration sensor; these frequency data are then quickly analyzed. When a sudden and abnormal increase in noise and vibration intensity is detected at a specific frequency point, it is determined that the current motor speed (corresponding to a specific PWM duty cycle) just matches the turbine's excitation frequency with the cooktop's natural frequency, indicating that the range hood has entered the resonance range.

[0085] S304: Adjust the duty cycle of the motor in the range hood according to the resonance range.

[0086] In the embodiments described in this specification, in order to avoid resonance, the system immediately takes action by finely adjusting the PWM duty cycle output to the motor to change the motor speed. As long as the current air volume demand allows, the duty cycle will be reduced, that is, the speed will be reduced and the gear will be downshifted, so that the speed deviates from the resonance range, thereby restoring the abnormally increased noise and vibration to normal. After adjustment, the system continues to return to S301 for monitoring to ensure that the resonance phenomenon has been eliminated, forming a continuous and automatic silent control closed loop.

[0087] In this embodiment, during the operation of the range hood, the built-in high-sensitivity microphone and vibration sensor continuously collect the noise and vibration frequencies generated by the turbine assembly. When a sharp increase in amplitude is detected at a specific frequency point and it matches the resonance characteristics in its pre-stored database, it is immediately determined that the motor's current speed has entered the resonance range. Based on the diagnostic results, a decision is made instantly. Under the premise of meeting basic smoke extraction requirements, a speed reduction and downshifting strategy is adopted to smoothly reduce the speed to a stable point below the resonance range. The duty cycle of the drive motor signal is finely adjusted, and the motor speed is slightly changed, causing the excitation frequency to quickly deviate from the structure's inherent resonance frequency point. This actively eliminates the noise source itself, allowing the machine to maintain a more stable and quieter operating state at any speed, greatly improving the comfort of the kitchen environment, effectively reducing the additional mechanical stress on the machine body and its internal components, thereby reducing the failure rate, extending the life of the stove, and improving the reliability of the stove.

[0088] In one exemplary implementation, such as Figure 4 As shown, Figure 4 A flowchart illustrating a second noise control method for an integrated stove provided in this specification, comprising: S401: Real-time acquisition of suction power data from the range hood.

[0089] In the embodiments of this specification, the integrated stove includes a range hood; the range hood is equipped with a turbine and is connected to a common flue; during the operation of the range hood, the suction power data of the range hood is acquired in real time; wherein, the suction power data includes one or more of the following: turbine wind pressure, range hood air volume, turbine noise, and common flue resistance; S402: Determine whether the resistance of the common flue is less than the first preset threshold; if the resistance of the common flue is greater than or equal to the first preset threshold, proceed to S404.

[0090] In the embodiments of this specification, a first preset threshold is preset, which represents the critical point of whether the common flue connected to the range hood is unobstructed; it is determined whether the resistance of the common flue is less than the first preset threshold, thereby determining the corresponding motor control strategy.

[0091] S403: Reduce the duty cycle of the motor in the range hood.

[0092] In the embodiments of this specification, when the resistance of the common flue is less than the first preset threshold, it indicates that the common flue is very unobstructed and the external resistance is very small. Smoke can be discharged smoothly without the need for maximum power. Therefore, by appropriately reducing the duty cycle of the motor in the range hood, energy saving and noise reduction can be achieved by reducing the motor speed, without affecting the smoke extraction effect.

[0093] S404: Determine whether the resistance of the public flue is greater than the second preset threshold.

[0094] In the embodiments of this specification, when the resistance of the common flue is greater than or equal to the first preset threshold, it is then determined whether the resistance of the common flue is greater than the second preset threshold, and the second preset threshold is greater than the first preset threshold. The second preset threshold is a critical value for determining that the pressure in the common flue is too high.

[0095] S405: Increase the duty cycle of the motor inside the range hood.

[0096] In the embodiments of this specification, when the resistance of the common flue is greater than the second preset threshold, it indicates that the pressure inside the common flue is very high, posing a risk of backflow of cooking fumes. Therefore, the duty cycle of the motor inside the range hood is automatically increased, thereby increasing the motor speed and air pressure, so as to use stronger thrust to overcome the greater resistance of the common flue and forcefully expel the cooking fumes, thereby effectively preventing the cooking fumes from flowing back into the home; at the same time, the result that the resistance of the common flue is greater than the second preset threshold is transmitted to the speaker to remind the user.

[0097] In this embodiment, during periods when the public exhaust duct is unobstructed, the duty cycle of the motor inside the range hood is automatically reduced, thereby reducing the motor speed, significantly reducing power consumption, and also greatly reducing operating noise. During peak periods when the exhaust environment is most severe, the boost mode is automatically detected and activated to provide stronger air pressure, ensuring effective exhaust under any circumstances, preventing backflow of fumes, and improving the user experience.

[0098] This manual also provides information on noise control devices for the range hood, such as... Figure 5 As shown, the range hood is equipped with a turbine, and the device includes: The acquisition module 501 is used to acquire the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value during the operation of the range hood. The segmentation module 502 is used to perform signal segmentation processing on the turbine noise signal according to the current length value if the current turbine noise value is greater than a preset turbine noise threshold, so as to obtain at least two noise signal segments. The desired noise signal determination module 503 is used to perform convolution processing on the at least two noise signal segments and the primary path transfer function to obtain the desired noise signal. The actual noise reduction signal determination module 504 is used to perform convolution processing on the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise reduction driving signal, and to perform convolution processing on the noise reduction driving signal and the secondary path transfer function to obtain an actual noise reduction signal. The current noise error signal determination module 505 is used to superimpose the expected noise signal and the actual anti-noise signal to obtain the current noise error signal. The noise reduction module 506 is used to update the operating frequency of the range hood based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0099] In some embodiments, the apparatus further includes: The test input signal generation module is used to generate test input signals in response to the secondary path transfer function update instruction; The test output signal determination module is used to perform convolution processing on the test input signal and the initial secondary path transfer function to obtain the test output signal; The frequency domain input signal determination module is used to perform FFT processing on the test input signal to obtain the frequency domain input signal; The frequency domain output signal determination module is used to perform FFT processing on the test output signal to obtain the frequency domain output signal; The secondary path frequency response determination module is used to calculate the ratio between the frequency domain output signal and the frequency domain input signal to obtain the secondary path frequency response; The secondary path transfer function determination module is used to update the initial secondary path transfer function according to the secondary path frequency response, and use the updated secondary path transfer function as the secondary path transfer function.

[0100] In some embodiments, the secondary path transfer function determination module further includes: The post-processing frequency response determination submodule is used to normalize the amplitude of the frequency response of the secondary path to obtain the post-processing frequency response; The compensation coefficient determination submodule is used to perform IFFT processing on the processed frequency response to obtain the compensation coefficients corresponding to the initial secondary path transfer function; The updated secondary path transfer function determination submodule is used to perform convolution processing on the initial secondary path transfer function and the compensation coefficient to obtain the updated secondary path transfer function. The secondary path transfer function determination submodule is used to use the updated secondary path transfer function as the secondary path transfer function.

[0101] In some embodiments, the actual noise immunity signal determination module further includes: The desired noise signal segment acquisition submodule is used to sequentially poll each noise signal segment, and for the polled current noise signal segment, acquire the desired noise signal segment adjacent to the current noise signal segment; the sampling point corresponding to the desired noise signal segment is smaller than the sampling point corresponding to the current noise signal segment; The target noise signal segment determination submodule is used to concatenate the current noise signal segment with the desired noise signal segment to obtain the target noise signal segment; The frequency domain noise signal segment determination submodule is used to perform FFT processing on the target noise signal segment to obtain the frequency domain noise signal segment; The updated adaptive filter determination submodule is used to extend the length of the adaptive filter to obtain the updated adaptive filter. The actual noise immunity signal determination submodule is used to determine the actual noise immunity signal based on the frequency domain noise signal segment, the updated adaptive filter, and the secondary path transfer function.

[0102] In some embodiments, the actual noise immunity signal determination submodule further includes: The frequency domain filter coefficient determination unit is used to perform FFT processing on the filter coefficients of the updated adaptive filter to obtain the frequency domain filter coefficients. A frequency domain noise reduction drive signal determination unit is used to perform point-by-point complex multiplication on the frequency domain noise signal segment and the frequency domain filter coefficients to obtain a frequency domain noise reduction drive signal. A time-domain denoising drive signal determination unit is used to perform IFFT processing on the frequency-domain denoising drive signal to obtain a time-domain denoising drive signal. A noise reduction drive signal determination unit is used to filter the time-domain noise reduction drive signal to obtain the noise reduction drive signal; The actual noise reduction signal determination unit is used to perform convolution processing on the noise reduction driving signal and the secondary path transfer function to obtain the actual noise reduction signal.

[0103] In some embodiments, the noise reduction module further includes: The updated filter coefficient determination submodule is used to update the filter coefficients of the adaptive filter based on the current noise error signal and the at least two noise signal segments to obtain the updated filter coefficients. The updated duty cycle determination submodule is used to update the duty cycle of the motor according to the updated filter coefficients to obtain the updated duty cycle of the motor. The noise reduction submodule is used to control the motor to operate at the updated duty cycle so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

[0104] In some embodiments, the updated filter coefficient determination submodule further includes: An expanded noise error signal segment determination unit is used to expand the current noise error signal to obtain an expanded noise error signal segment if the current noise error signal does not meet the preset noise error conditions. A frequency domain error signal segment determination unit is used to perform FFT processing on the expanded noise error signal segment to obtain a frequency domain error signal segment. The noise reduction unit is used to update the filter coefficients of the adaptive filter according to the frequency domain error signal segment and the current noise signal segment until a preset condition is met, so as to obtain the updated filter coefficients.

[0105] In some embodiments, the noise reduction unit further includes: A modified reference noise signal determination subunit is used to perform convolution processing on the current noise signal segment and a preset filter transfer function to obtain a modified reference noise signal; the preset filter transfer function is an estimate of the secondary path transfer function; The updated filter coefficient determination subunit is used to update the filter coefficients of the adaptive filter based on the frequency domain error signal segment and the corrected reference noise signal until the output noise error signal meets the preset noise error condition, thereby obtaining the updated filter coefficients.

[0106] In some embodiments, the updated duty cycle determination submodule further includes: The target noise reduction driving signal determination unit is used to take the noise reduction driving signal corresponding to the noise error signal that satisfies the preset noise error condition as the target noise reduction driving signal. The target root mean square value determination unit is used to calculate the root mean square value of the target noise reduction driving signal to obtain the target root mean square value; The target duty cycle determination unit is used to search for a duty cycle that matches the target root mean square value in a preset root mean square value duty cycle relation library to obtain the target duty cycle; the preset root mean square value duty cycle relation library includes a preset mapping relationship between preset root mean square values ​​and preset duty cycles; The updated duty cycle determination unit is used to use the target duty cycle as the updated duty cycle.

[0107] The apparatus and method embodiments described herein are based on the same inventive concept.

[0108] This specification provides an electronic device including a processor and a memory. The memory stores at least one instruction or at least one program, which is loaded and executed by the processor to implement the noise control method for a range hood as provided in the above method embodiments.

[0109] Embodiments of this application also provide a computer storage medium, which can be disposed in a terminal to store at least one instruction or at least one program related to implementing a noise control method for a range hood in the method embodiments. The at least one instruction or at least one program is loaded and executed by the processor to implement the noise control method for the range hood provided in the above method embodiments.

[0110] Embodiments of this application also provide a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the noise control method for a range hood provided in the above-described method embodiments.

[0111] The memory described in the embodiments of this specification can be used to store software programs and modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for the functions, etc.; the data storage area may store data created according to the use of the device, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory may also include a memory controller to provide the processor with access to the memory.

[0112] The noise control method for range hoods provided in this specification can be executed on a mobile terminal, computer terminal, server, or similar computing device. Taking a server as an example... Figure 6 This is a hardware structure block diagram of a server for a noise control method for a range hood provided in an embodiment of this specification. (As shown...) Figure 6 As shown, the server 600 can vary significantly due to different configurations or performance. It may include one or more Central Processing Units (CPUs) 610 (CPUs 610 may include, but are not limited to, microprocessors (MCUs) or programmable logic devices (FPGAs), a memory 630 for storing data, and one or more storage media 620 (e.g., one or more mass storage devices) for storing application programs 623 or data 622. The memory 630 and storage media 620 may be temporary or persistent storage. The program stored in the storage media 620 may include one or more modules, each module may include a series of instruction operations on the server. Furthermore, the CPU 610 may be configured to communicate with the storage media 620 and execute the series of instruction operations stored in the storage media 620 on the server 600. Server 600 may also include one or more power supplies 660, one or more wired or wireless network interfaces 650, one or more input / output interfaces 640, and / or one or more operating systems 621, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0113] The input / output interface 640 can be used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of server 600. In one example, input / output interface 640 includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, input / output interface 640 may be a radio frequency (RF) module used for wireless communication with the Internet.

[0114] Those skilled in the art will understand that Figure 6 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, server 600 may also include... Figure 6 The more or fewer components shown, or having the same Figure 6 The different configurations shown.

[0115] As can be seen from the embodiments of the noise control method and apparatus for range hoods provided in this application, during the operation of the range hood, this application acquires the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value; if the current turbine noise value is greater than a preset turbine noise threshold, the turbine noise signal is segmented according to the current length value to obtain at least two noise signal segments; the at least two noise signal segments and the primary path transfer function are convolved to obtain a desired noise signal; the at least two noise signal segments and the filter coefficients of the adaptive filter are convolved to obtain a noise reduction drive signal, and the noise reduction drive signal and the secondary path transfer function are convolved to obtain an actual noise reduction signal; the desired noise signal and the actual noise reduction signal are superimposed to obtain a current noise error signal; the operating frequency of the range hood is updated according to the current noise error signal and the at least two noise signal segments so that the noise generated by the turbine during operation is less than the preset turbine noise threshold. By pre-equalizing the secondary path, the noise reduction effect of the adaptive system is made more uniform and stable across the entire frequency band, and the convergence speed is accelerated, avoiding uneven noise reduction during actual use of the range hood. During the operation of the range hood, the current length value of the adaptive filter, the turbine noise signal, and the current turbine noise value are acquired in real time. When the current turbine noise value exceeds the limit, the turbine noise signal is segmented according to the current length value, thereby reducing processing latency and computational load. Based on the segmented noise signal segment, the primary path transfer function, the filter coefficients of the adaptive filter, and the secondary path transfer function, the current noise error signal is determined, achieving accurate acquisition of range hood noise. The operating frequency of the range hood is updated based on the noise error signal and the noise signal segment, realizing efficient and real-time active noise control, so that the range hood operates in the low-noise zone as much as possible, thereby minimizing the user's exposure to strong noise environments.

[0116] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0117] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0118] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer storage medium, such as a read-only memory, a disk, or an optical disk.

[0119] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A noise control method for a range hood, characterized in that, The range hood is equipped with a turbine, and the method includes: During the operation of the range hood, the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value are obtained. If the current turbine noise value is greater than a preset turbine noise threshold, the turbine noise signal is segmented according to the current length value to obtain at least two noise signal segments. The at least two noise signal segments and the primary path transfer function are convolved to obtain the desired noise signal. The at least two noise signal segments and the filter coefficients of the adaptive filter are convolved to obtain the noise reduction driving signal, and the noise reduction driving signal and the secondary path transfer function are convolved to obtain the actual noise reduction signal. The desired noise signal and the actual noise-resistant signal are superimposed to obtain the current noise error signal; The operating frequency of the range hood is updated based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

2. The method according to claim 1, characterized in that, Before performing convolution processing on the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain the noise reduction driving signal, and then performing convolution processing on the noise reduction driving signal and the secondary path transfer function to obtain the actual noise-resistant signal, the method further includes: In response to the secondary path transfer function update instruction, a test input signal is generated; The test input signal and the initial secondary path transfer function are convolved to obtain the test output signal; The test input signal is processed by FFT to obtain the frequency domain input signal; The test output signal is processed by FFT to obtain the frequency domain output signal; Calculate the ratio between the frequency domain output signal and the frequency domain input signal to obtain the secondary path frequency response; The initial secondary path transfer function is updated based on the secondary path frequency response, and the updated secondary path transfer function is used as the secondary path transfer function.

3. The method according to claim 2, characterized in that, The step of updating the initial secondary path transfer function based on the secondary path frequency response, and using the updated secondary path transfer function as the secondary path transfer function, includes: The amplitude of the frequency response of the secondary path is normalized to obtain the processed frequency response; The processed frequency response is subjected to IFFT processing to obtain the compensation coefficients corresponding to the initial secondary path transfer function; The initial secondary path transfer function and the compensation coefficient are convolved to obtain the updated secondary path transfer function. The updated secondary path transfer function is used as the secondary path transfer function.

4. The method according to claim 3, characterized in that, The process of convolving the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise reduction driving signal, and then convolving the noise reduction driving signal and the secondary path transfer function to obtain the actual noise-resistant signal, includes: Each noise signal segment is polled sequentially. For the current noise signal segment polled, the desired noise signal segment adjacent to the current noise signal segment is obtained. The sampling point corresponding to the desired noise signal segment is smaller than the sampling point corresponding to the current noise signal segment. The current noise signal segment is spliced ​​with the desired noise signal segment to obtain the target noise signal segment; Perform FFT processing on the target noise signal segment to obtain the frequency domain noise signal segment; The length of the adaptive filter is extended to obtain an updated adaptive filter. The actual noise-resistant signal is determined based on the frequency domain noise signal segment, the updated adaptive filter, and the secondary path transfer function.

5. The method according to claim 4, characterized in that, The step of determining the actual noise-resistant signal based on the frequency domain noise signal segment, the updated adaptive filter, and the secondary path transfer function includes: The updated adaptive filter coefficients are subjected to FFT processing to obtain the frequency domain filter coefficients; The frequency domain noise signal segment and the frequency domain filter coefficients are subjected to point-by-point complex multiplication to obtain the frequency domain noise reduction drive signal. The frequency domain noise reduction driving signal is processed by IFFT to obtain the time domain noise reduction driving signal; The time-domain denoising driving signal is filtered to obtain the denoising driving signal; The noise reduction driving signal and the secondary path transfer function are convolved to obtain the actual noise-resistant signal.

6. The method according to claim 5, characterized in that, The range hood also includes a motor; the step of updating the operating frequency of the range hood based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold, includes: The filter coefficients of the adaptive filter are updated based on the current noise error signal and the at least two noise signal segments to obtain the updated filter coefficients. The duty cycle of the motor is updated based on the updated filter coefficients to obtain the updated duty cycle of the motor. The motor is controlled to operate at the updated duty cycle so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

7. The method according to claim 6, characterized in that, The step of updating the filter coefficients of the adaptive filter based on the current noise error signal and the at least two noise signal segments to obtain the updated filter coefficients includes: If the current noise error signal does not meet the preset noise error condition, the current noise error signal is expanded to obtain an expanded noise error signal segment. The expanded noise error signal segment is processed by FFT to obtain the frequency domain error signal segment; Based on the frequency domain error signal segment and the current noise signal segment, the filter coefficients of the adaptive filter are updated until a preset condition is met, thus obtaining the updated filter coefficients.

8. The method according to claim 7, characterized in that, The step of updating the filter coefficients of the adaptive filter based on the frequency domain error signal segment and the current noise signal segment until a preset condition is met, to obtain the updated filter coefficients, includes: The current noise signal segment and the preset filter transfer function are convolved to obtain a corrected reference noise signal; the preset filter transfer function is an estimate of the secondary path transfer function. Based on the frequency domain error signal segment and the corrected reference noise signal, the filter coefficients of the adaptive filter are updated until the output noise error signal meets the preset noise error condition, thus obtaining the updated filter coefficients.

9. The method according to claim 8, characterized in that, The step of updating the duty cycle of the motor based on the updated filter coefficients to obtain the updated duty cycle of the motor includes: The noise reduction driving signal corresponding to the noise error signal that satisfies the preset noise error condition is taken as the target noise reduction driving signal; Calculate the root mean square value of the target noise reduction driving signal to obtain the target root mean square value; The target duty cycle is obtained by searching the preset root mean square value duty cycle relationship library for a duty cycle that matches the target root mean square value; the preset root mean square value duty cycle relationship library includes a mapping relationship between preset root mean square values ​​and preset duty cycles. The target duty cycle is used as the updated duty cycle.

10. A noise control device for a range hood, characterized in that, The range hood is equipped with a turbine, and the device includes: The acquisition module is used to acquire the current length value of the adaptive filter corresponding to the range hood, the turbine noise signal corresponding to the turbine, and the current turbine noise value during the operation of the range hood. The segmentation module is used to perform signal segmentation processing on the turbine noise signal according to the current length value if the current turbine noise value is greater than a preset turbine noise threshold, so as to obtain at least two noise signal segments. The desired noise signal determination module is used to perform convolution processing on the at least two noise signal segments and the primary path transfer function to obtain the desired noise signal. The actual noise reduction signal determination module is used to perform convolution processing on the at least two noise signal segments and the filter coefficients of the adaptive filter to obtain a noise reduction driving signal, and to perform convolution processing on the noise reduction driving signal and the secondary path transfer function to obtain an actual noise reduction signal. The current noise error signal determination module is used to superimpose the desired noise signal and the actual anti-noise signal to obtain the current noise error signal; The noise reduction module is used to update the operating frequency of the range hood based on the current noise error signal and the at least two noise signal segments, so that the noise generated by the turbine during operation is less than the preset turbine noise threshold.

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