Range hood noise reduction method and device, range hood and storage medium
By setting up a triangular sound field monitoring topology at the duct position of the range hood, noise signals are collected and separated, and anti-phase sound waves are generated for precise positioning and noise reduction. This solves the problem of poor noise reduction effect of range hoods and achieves efficient active noise reduction and equipment health monitoring.
Patent Information
- Application Number
- CN202511752229.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-26
- Publication Date
- 2026-02-10
AI Technical Summary
Existing noise reduction technologies for range hoods cannot effectively distinguish the types of noise sources, making it difficult to accurately reduce overlapping noises in the time and frequency domains, resulting in limited noise reduction effects.
A triangular sound field monitoring topology is set up at the duct of the range hood. The original noise signal is collected by three sets of anti-oil microphone arrays, and the time and frequency domains are separated to determine the noise sound pattern characteristics. An inverse sound wave signal is generated and accurately located and output based on the noise distribution heat map to achieve active noise reduction.
It improves the active noise reduction effect of the range hood, achieves precise location and separation of noise sources, enhances noise reduction efficiency, and can monitor equipment faults in real time, thereby reducing energy consumption.
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Figure CN121498093A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of kitchen appliances, in particular to a range hood noise reduction method, a range hood noise reduction device, a range hood and a computer readable storage medium. BACKGROUND
[0002] In the related art, range hood noise reduction is mainly achieved by passive noise reduction through sound insulation materials, or by active noise reduction through a single sensor collecting mixed noise and generating a reverse sound wave. However, it is unable to distinguish the noise source types, resulting in limited noise reduction effect. For example, when wind noise, motor vibration and foreign object impact sound overlap in the time-frequency domain, it is difficult to accurately reduce the noise. SUMMARY
[0003] In view of the above problems, the present application embodiments are proposed in order to provide a range hood noise reduction method, a range hood noise reduction device, a range hood and a computer readable storage medium which overcome the above problems or at least partially solve the above problems.
[0004] In order to solve the above problems, in a first aspect of the present application, the present application embodiments disclose a range hood noise reduction method, a triangular sound field monitoring topology is arranged at an air duct position of the range hood, the triangular sound field monitoring topology is used to collect an original noise signal when the range hood is running, and the method comprises: Separating the original noise signal in the time domain, separating the parts existing overlap in the time domain in the frequency domain, and determining a noise print feature; Determining a reverse sound wave signal based on the noise print feature; Performing sound source positioning on the original noise signal to determine a noise distribution heat map; In the noise distribution heat map, determining a noise target position corresponding to the noise print feature; Outputting the reverse sound wave signal at the noise target position.
[0005] Optionally, the step of separating the original noise signal in the time domain, separating the parts existing overlap in the time domain in the frequency domain, and determining a noise print feature comprises: Extracting an acoustic characteristic parameter of the original noise signal; Classifying the acoustic characteristic parameter to determine a noise type; Performing component separation on the original noise signal based on the noise type to determine a noise print feature.
[0006] Optionally, the noise type comprises motor fundamental harmonic noise, blade aerodynamic noise, broadband wind noise and pulse abnormal sound, and the step of classifying the acoustic characteristic parameter to determine a noise type comprises: The acoustic feature parameter is compared with a preset acoustic reference feature to determine one of the motor fundamental harmonic noise, the blade aerodynamic noise, the broadband wind noise or the pulse abnormal sound.
[0007] Optionally, the step of determining the anti-phase sound wave signal based on the noise soundprint feature comprises: synthesizing a candidate set of anti-phase waveforms based on the noise soundprint feature; determining a target anti-phase waveform that matches the spectrum of the noise soundprint feature in the candidate set of anti-phase waveforms; determining the anti-phase sound wave signal based on the target anti-phase waveform.
[0008] Optionally, the step of performing sound source localization on the original noise signal to determine a noise distribution heat map comprises: performing sound source localization on the original noise signal to determine a sound source position; determining an energy frequency band of the original noise signal; determining a noise distribution heat map in combination with the sound source position and the energy frequency band.
[0009] Optionally, the extractor hood is provided with a plurality of loudspeakers, and the step of outputting the anti-phase sound wave signal at the noise target position comprises: determining a target loudspeaker among the plurality of loudspeakers based on the noise target position; outputting the anti-phase sound wave signal based on the loudspeaker.
[0010] Optionally, the method further comprises: performing frequency domain conversion on the noise soundprint feature to determine an energy mutation trend; determining a fault level based on the energy mutation trend; performing maintenance processing based on the fault level.
[0011] Optionally, the triangular sound field monitoring topology comprises: a first group of anti-oil dirt microphone arrays installed on the inner side of the inlet air duct of the extractor hood, a second group of anti-oil dirt microphone arrays installed on the center guard plate of the impeller of the extractor hood, and a third group of anti-oil dirt microphone arrays installed on the surface of the outlet air duct of the extractor hood.
[0012] Optionally, the surfaces of the first group of anti-oil dirt microphone arrays, the second group of anti-oil dirt microphone arrays and the third group of anti-oil dirt microphone arrays are provided with an oil dirt-repellent coating.
[0013] In a second aspect, an embodiment of the present invention discloses a noise reduction device for a range hood, wherein a triangular sound field monitoring topology is provided at the air duct position of the range hood, the triangular sound field monitoring topology being used to collect the original noise signal of the range hood during operation, and the device comprising: The separation module is used to separate the original noise signal in the time domain and separate the overlapping parts in the time domain in the frequency domain to determine the noise acoustic features; The inverting module is used to determine the inverted acoustic wave signal based on the noise acoustic signature characteristics; The distribution module is used to locate the sound source of the original noise signal and determine the noise distribution heatmap. The positioning module is used to determine the location of the noise target corresponding to the noise soundprint features in the noise distribution heatmap. A noise reduction module is used to output the anti-phase acoustic wave signal at the noise target location.
[0014] In a third aspect of the present invention, an embodiment of the present invention discloses a range hood, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of the range hood noise reduction method as described above.
[0015] In a fourth aspect, embodiments of the present invention disclose a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the range hood noise reduction method as described above.
[0016] The embodiments of the present invention have the following advantages: This invention provides an embodiment of a triangular sound field monitoring topology installed at the duct location of a range hood. This topology is used to collect the original noise signal during the operation of the range hood, separate the original noise signal in the time domain, and separate overlapping portions in the time domain in the frequency domain to determine noise signature characteristics. Based on these noise signature characteristics, an inverse sound wave signal is determined. The original noise signal is then used to locate the sound source and determine a noise distribution heatmap. Within the noise distribution heatmap, the noise target location corresponding to the noise signature characteristics is determined. Finally, the inverse sound wave signal is output at the noise target location. By utilizing a triangular acoustic field monitoring topology, the noise source localization accuracy can be maximized within the limited space of the range hood's duct, acquiring complete and accurate original noise signals. Time-frequency domain separation is then performed on the original noise signal to achieve time-frequency decoupling, separating even noise superimposed in the time domain. This identifies the noise signature characteristics of the original noise signal, enabling component quantization and significantly improving noise source separation accuracy. Furthermore, the noise signature characteristics provide precise input for generating the anti-phase acoustic signal, making the waveform of the anti-phase acoustic signal more closely match the original noise signal, thus improving noise reduction efficiency. Finally, the noise distribution heatmap based on physical location and component quantization jointly outputs the anti-phase acoustic signal at the noise target location, allowing the anti-phase acoustic signal to resist the original noise signal to the greatest extent, thereby improving the active noise reduction effect of the range hood. Attached Figure Description
[0017] Figure 1 This is a flowchart illustrating the steps of an embodiment of a noise reduction method for a range hood according to the present invention; Figure 2 This is a flowchart illustrating the steps of another embodiment of the noise reduction method for a range hood according to the present invention; Figure 3 This is a schematic diagram of the location of a triangular sound field monitoring topology for a range hood according to the present invention; Figure 4 This is a schematic diagram of a microphone array structure for a triangular sound field monitoring topology of a range hood according to the present invention. Figure 5 This is a structural block diagram of an embodiment of a noise reduction device for a range hood according to the present invention; Figure 6 This is a structural block diagram of a range hood provided in an embodiment of the present invention; Figure 7 This is a structural block diagram of a storage medium provided in an embodiment of the present invention. Detailed Implementation
[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0019] ReferenceFigure 1 This document illustrates a flowchart of an embodiment of a noise reduction method for a range hood according to the present invention. A triangular sound field monitoring topology is installed at the duct location of the range hood. This topology is used to collect the original noise signal during the operation of the range hood. The triangular sound field monitoring topology at the duct location of the range hood means that three sets of audio acquisition sensors can be installed at the duct location of the range hood, arranged in a triangular pattern. Each set of audio acquisition sensors collects the noise from the range hood, and the noise from the three sets of sensors is combined to form the original noise signal of the range hood. The triangular distribution of the three sets of audio acquisition sensors allows for accurate noise collection. Furthermore, multiple triangular sound field monitoring topologies can be installed at the duct location of the range hood, using multiple topologies to collect noise, filter, and combine the data to output a single original noise signal. The range hood used in this embodiment is an energy-saving range hood with low energy consumption. The energy-saving range hood in this embodiment can effectively reduce energy consumption.
[0020] The noise reduction method for the range hood may specifically include the following steps: Step 101: Separate the original noise signal in the time domain and separate the overlapping parts in the time domain in the frequency domain to determine the noise acoustic features; The original noise signal can be separated in the time domain into multiple different noise segments. These time-domain noise segments are then transformed to the frequency domain, where overlapping noise segments from the time domain are further separated to form distinct noise components. This time-frequency domain separation of the original noise signal results in multiple distinct noise segments, allowing for the determination of the noise signature characteristics for each segment. These noise signature characteristics can be represented using various coefficients, such as wavelet transform coefficients, short-time energy, zero-crossing rate, Mel-frequency cepstral coefficients, linear prediction coefficients, etc. At least one parameter can be used as a noise signature feature.
[0021] Step 102: Determine the antiphase acoustic wave signal based on the noise acoustic signature characteristics; Based on the sound waveform corresponding to each noise acoustic feature, an inverse acoustic signal is determined. The inverse acoustic signal and the sound waveform corresponding to the noise acoustic feature have the same frequency and propagate in the same direction, but are 180° out of phase. When the inverse acoustic signals meet the noise corresponding to the noise acoustic feature in space, they undergo destructive interference, causing the vibration displacements to cancel each other out.
[0022] Step 103: Locate the sound source of the original noise signal and determine the noise distribution heatmap; It can also perform sound source localization on the original noise signal, determining the location of the noise source corresponding to each noise segment in the original noise signal, and forming a noise distribution heatmap by combining the noise parameters of the noise segments. The noise distribution heatmap is used to characterize the noise distribution in a range hood.
[0023] Step 104: In the noise distribution heatmap, determine the location of the noise target corresponding to the noise soundprint feature; The location of the noise target corresponding to the noise soundprint characteristics can be determined from the noise distribution heatmap.
[0024] Step 105: Output the anti-phase acoustic wave signal at the noise target location.
[0025] The anti-phase sound wave signal is output at the noise target location corresponding to the noise sound pattern characteristics. The anti-phase sound wave signal is used to cancel the original noise, thereby reducing the original noise and realizing the active noise reduction of the range hood.
[0026] This invention provides an embodiment of a triangular sound field monitoring topology installed at the duct location of a range hood. This topology is used to collect the original noise signal during the operation of the range hood, separate the original noise signal in the time domain, and separate overlapping portions in the time domain in the frequency domain to determine noise signature characteristics. Based on these noise signature characteristics, an inverse sound wave signal is determined. The original noise signal is then used to locate the sound source and determine a noise distribution heatmap. Within the noise distribution heatmap, the noise target location corresponding to the noise signature characteristics is determined. Finally, the inverse sound wave signal is output at the noise target location. By employing a triangular sound field monitoring topology, the noise source localization accuracy can be maximized within the limited space of the range hood's duct, acquiring complete and accurate original noise signals. Then, time-frequency domain separation is performed on the original noise signal to achieve time-frequency decoupling, separating even noise superimposed in the time domain. This identifies the noise signature characteristics of the original noise signal, enabling component quantization and significantly improving noise source separation accuracy. Furthermore, the noise signature characteristics provide precise input for generating the anti-phase sound wave signal, making the waveform of the anti-phase sound wave signal more closely match the original noise signal, thus improving noise reduction efficiency. Finally, the noise distribution heatmap based on physical location and component quantization jointly outputs the anti-phase sound wave signal at the noise target location, allowing the anti-phase sound wave signal to resist the original noise signal to the greatest extent, improving the active noise reduction effect of the range hood.
[0027] Reference Figure 2This diagram illustrates a flowchart of another embodiment of the noise reduction method for a range hood according to the present invention. A triangular sound field monitoring topology is installed at the air duct location of the range hood. This topology is used to collect the original noise signal during the operation of the range hood, and the collected original noise signal is used as a reference signal for noise reduction. The triangular sound field monitoring topology includes three sets of oil-resistant microphone arrays. See also... Figure 3 The three sets of anti-oil microphone arrays include a first set installed inside the air inlet guide shroud of the range hood, a second set installed on the impeller center guard plate, and a third set installed on the surface of the air outlet volute. Specifically, the first set is embedded inside the air inlet guide shroud, close to the airflow inlet, to capture wind noise and the sound of foreign objects impacting the air; the second set is deployed on the impeller center guard plate, directly facing the motor vibration source, to accurately monitor bearing wear characteristics; and the third set is integrated on the surface of the air outlet volute, covering the main area of aerodynamic turbulence. The three sets of anti-oil microphone arrays have the same structure. The surfaces of the first, second, and third sets of anti-oil microphone arrays are all coated with an oleophobic coating. (See reference...) Figure 4 Each set of oil-resistant microphone arrays employs a metal oleophobic mesh as its microphone cavity structure for oil protection, and is internally filled with high-temperature resistant damping material to suppress oil adhesion and cavity resonance. The oleophobic structure, combined with oil-guiding grooves, directs oil droplets to the oil collection box, ensuring the accuracy of acoustic signal acquisition in high-temperature, oily environments. The surface oleophobic coating reduces oil droplet adhesion, and the oil-guiding structure at the bottom of the cavity guides the oil into the collection box. Periodic current pulses remove residual contaminants from the electrodes. Furthermore, multiple high-temperature resistant speakers can be simultaneously embedded in the top of the motor nacelle, at the impeller spacing points, and at duct bends. Specifically, the speaker array is deployed at the top of the motor nacelle (to cover motor vibration noise), at the impeller spacing points (to address blade imbalance noise), and at duct bends (to handle duct reflection noise). The speaker surfaces are covered with an insulating protective layer, and the wires are coated with high-temperature resistant materials to ensure stable sound wave output in high-temperature environments.
[0028] The noise reduction method for the range hood may specifically include the following steps: Step 201: Separate the original noise signal in the time domain and separate the overlapping parts in the time domain in the frequency domain to determine the noise acoustic features; The acquired raw noise signal can be separated into time and frequency domains, and the raw noise signal can be separated into noise segments in both the time and frequency domains to determine the noise voiceprint features corresponding to the noise segments.
[0029] In an optional embodiment of the present invention, the step of separating the original noise signal in the time domain and separating the overlapping portions in the time domain in the frequency domain to determine the noise acoustic signature features includes: Sub-step S201: Extract the acoustic feature parameters of the original noise signal; It can extract acoustic feature parameters of the original noise signal, such as wavelet transform coefficients, short-time energy, zero-crossing rate, Mel frequency cepstral coefficients, linear prediction coefficients, etc.
[0030] Sub-step S202: Classify the acoustic feature parameters to determine the noise type; Based on acoustic feature parameters, noise segments in the original noise signal are classified to determine the specific noise type. In practical applications, the noise types include motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise. Classifying the acoustic feature parameters to determine the noise type includes comparing the acoustic feature parameters with preset acoustic reference features to determine whether it is one of the following: motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, or pulse abnormal noise.
[0031] The preset acoustic reference features can include acoustic reference features for motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise. The acoustic feature parameters of each noise segment can be compared with the preset acoustic reference features for each of these categories to determine the corresponding type of acoustic feature parameter. The acoustic feature parameters can then be classified into one of the following categories: motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise.
[0032] Sub-step S203: Based on the noise type, the original noise signal is component-separated to determine the noise voiceprint characteristics.
[0033] The sound components in the original noise signal can be separated based on the obtained noise type. The separated components are the attribute characteristics of motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise and pulse abnormal noise, which can be used as noise soundprint features.
[0034] Furthermore, neural network models can be used for acoustic feature parameter classification and component analysis. Samples containing acoustic reference features of motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise can be used to train the neural network model, resulting in a deep acoustic signature model. The original neural network models used include, but are not limited to, convolutional neural networks, decision tree models, ResNet (residual network), and LSTM (long short-term memory network). For example, feature extraction of noise signals can be performed, such as calculating the short-time Fourier transform (STFT) or Mel spectrum to extract the frequency domain features of the noise. Secondly, the model uses a pre-trained acoustic classifier to determine the noise type and then identifies the corresponding noise acoustic signature features. That is, the original noise signal collected by the microphone array can be used to separate the four noise components—motor fundamental frequency harmonic noise (hardware vibration noise), blade aerodynamic noise (impeller aerodynamic characteristics), broadband wind noise (duct turbulence), and pulse abnormal noise (foreign object impact)—in the time-frequency domain using a deep acoustic signature model to obtain noise acoustic signature features.
[0035] Step 202: Determine the antiphase acoustic wave signal based on the noise acoustic signature characteristics; Based on the noise segment corresponding to each noise voiceprint feature, generate an anti-phase sound wave signal with a phase difference of 180° and the same frequency.
[0036] In an optional embodiment of the present invention, the step of determining the antiphase acoustic signal based on the noise acoustic signature features includes: Sub-step S2021: Synthesize an inverted waveform candidate set based on the noise voiceprint features; To generate inverted acoustic signals, we can first fit a candidate set of inverted waveforms based on the spectral variation trend of noise acoustic signature characteristics. The candidate set of inverted waveforms contains multiple inverted waveforms.
[0037] Sub-step S2022: In the candidate set of inverted waveforms, determine the target inverted waveform that matches the spectrum of the noise acoustic signature. The spectrum of the noise soundprint feature is matched with each inverted waveform in the candidate set of inverted waveforms. For example, the spectral matching degree between the noise soundprint feature spectrum and each inverted waveform in the candidate set of inverted waveforms can be calculated. The inverted waveform with the highest spectral matching degree with the noise soundprint feature in the candidate set of inverted waveforms is determined as the target inverted waveform.
[0038] Sub-step S2023: Determine the anti-phase acoustic signal based on the target anti-phase waveform.
[0039] The corresponding inverted acoustic signal is generated based on the target inverted waveform.
[0040] The generation of antiphase acoustic signals can be achieved using adversarial networks (ANNs). In an AAN, the generator network synthesizes a candidate set of antiphase waveforms based on the noise time-frequency spectrum, while the discriminator network evaluates the spectral matching degree between the waveform and the real noise. Its output serves as gradient feedback to guide the generator in optimizing the waveform. Through iterative adversarial training, high-fidelity antiphase acoustic signals are generated. The adversarial training mechanism continuously improves the spectral matching degree of the generated antiphase acoustic signals, achieving high-fidelity noise reduction and further enhancing the noise reduction effect.
[0041] Step 203: Locate the sound source of the original noise signal and determine the noise distribution heatmap; Sound source localization algorithms can be used to locate the sound source of the original noise signal and determine a noise distribution heatmap. The noise distribution heatmap reflects the distribution changes of the noise source in real time. The noise distribution heatmap can be a three-dimensional or two-dimensional noise distribution heatmap. For the sound source localization algorithm, techniques such as beamforming based on time delay estimation or based on arrival intensity difference can be used; this embodiment of the invention does not specifically limit the specific methods employed.
[0042] In an optional embodiment of the present invention, the step of locating the sound source of the original noise signal and determining the noise distribution heatmap includes: Sub-step S2031: Locate the sound source of the original noise signal to determine the location of the sound source; A coordinate system can be established using the bottom corner of the range hood as the coordinate center. Under this coordinate system, the original noise signal can be located based on the sound source localization algorithm, and the coordinate position of the sound source can be determined as the sound source location.
[0043] Sub-step S2032: Determine the energy frequency band of the original noise signal; Furthermore, the energy frequency band of the original noise signal is determined based on parameters such as the amplitude of the original noise signal in the frequency domain.
[0044] Sub-step S2033: Combine the sound source location and the energy frequency band to determine the noise distribution heat map.
[0045] By combining energy frequency bands at the location of the sound source, each sound source is labeled, forming a noise distribution heat map.
[0046] For example, the two-dimensional or three-dimensional coordinates corresponding to the sound source location can be calculated using the time delay estimation (TDOA) of the raw noise signal from the microphone array. Secondly, the energy frequency bands (such as spectral energy density) of the raw noise signal are mapped onto a spatial coordinate system to form a noise distribution heatmap. Finally, combined with the time-frequency domain analysis results, different colors are used to represent the noise energy of different frequency bands (e.g., red represents high-energy frequency bands, and blue represents low-energy frequency bands). For instance, motor vibration noise might appear as a high-frequency red heatmap in the impeller area, while airflow noise in the duct forms a broadband yellow heatmap on the surface of the air outlet volute. Sudden abnormal noises manifest as instantaneous high-energy points. The heatmap is dynamically updated, reflecting the real-time distribution changes of the noise source.
[0047] Step 204: In the noise distribution heatmap, determine the location of the noise target corresponding to the noise soundprint characteristics; In the noise distribution heatmap, the location of the noise target is determined based on the noise soundprint characteristics, thus enabling noise reduction at the corresponding target location.
[0048] Step 205: Output the anti-phase acoustic wave signal at the noise target location; It can output an anti-phase acoustic signal at the noise target location, thereby achieving noise reduction.
[0049] In an optional embodiment of the present invention, the step of outputting the anti-phase acoustic signal at the noise target location includes: Sub-step S2051: Determine the target loudspeaker among multiple loudspeakers based on the noise target location; First, based on the location of the noise target, the loudspeaker that can cover and eliminate the noise at that location can be identified as the target loudspeaker.
[0050] Sub-step S2052: Output the anti-phase acoustic wave signal based on the loudspeaker.
[0051] The speaker outputs an anti-phase sound wave signal for noise reduction.
[0052] For example, to address motor fundamental frequency harmonics (low-frequency noise), the system activates a low-frequency speaker array at the impeller center guard plate, generating an anti-phase sound wave opposite to the fundamental frequency to cancel it out. For broadband wind noise, the system activates a full-band speaker array on the surface of the air outlet volute, covering both high and low frequency noise. For sudden foreign object impact noise, the system triggers a pulsed speaker inside the air inlet guide shroud, generating a millisecond-level anti-phase sound wave to suppress transient noise. The allocation process dynamically decides based on real-time noise classification results and spatial positioning data, or it can use a deep learning model to determine the noise type and then call the corresponding speaker control strategy for output.
[0053] Step 206: Perform frequency domain transformation on the noise acoustic signature features to determine the energy mutation trend; The noise signature characteristics of the original noise can be transformed in the frequency domain. Based on the changing trends of various characteristics in the frequency domain, the energy mutation trend can be determined. For example, in motor vibration harmonic analysis: the harmonic components of the motor speed signal are extracted by Fourier transform, and the harmonic distortion rate (such as the ratio of fundamental frequency to subharmonic energy) is calculated as the energy mutation trend to determine the degree of bearing wear. In blade aerodynamic sound energy analysis: the time-frequency characteristics of blade aerodynamic noise are extracted by wavelet transform or short-time Fourier transform, and the energy mutation trend of turbulence is analyzed.
[0054] Step 207: Determine the fault level based on the energy mutation trend; The mechanical health status of the operating components of a range hood is determined by analyzing different energy mutation trends, thereby identifying the corresponding fault level. For example, the wear level of bearings and the risk of impeller imbalance can be predicted using health decay curves to determine the mechanical health status. Health decay curves can be constructed based on historical data and real-time characteristics (e.g., using exponential decay models or machine learning regression models) to quantify the degree of mechanical wear. For instance, when the harmonic distortion rate of bearing wear exceeds 15%, the health status drops to a moderate risk; a sudden increase in blade turbulent energy exceeding 20 dB indicates a risk of impeller imbalance.
[0055] Step 208: Perform maintenance based on the fault level.
[0056] Different maintenance procedures are applied to different fault levels, enabling timely and effective maintenance of the range hood and improving its reliability. For example, when a minor fault level is detected, maintenance suggestions are pushed to the user; when a fault level with moderate wear is identified, the fan speed is automatically reduced and a yellow warning light is activated; when a fault level with severe fault characteristics is detected, the fan power supply is immediately cut off and a red alarm is triggered.
[0057] Furthermore, an environmentally adaptive control chain can be established for the range hood. A door magnetic sensor can be installed on the kitchen door; triggering the sensor activates a noise reduction response, executing the aforementioned noise reduction steps to suppress sudden noise introduced by opening and closing the door. The range hood can also have a built-in rhythm model, activating an active noise reduction mode during peak cooking times and executing the aforementioned noise reduction steps. During low-activity periods, it switches to a low-noise energy-saving state. The speaker array output power is reduced to a minimum, only minimizing and canceling basic operating noise (such as weak motor vibration), while unnecessary noise reduction modules are turned off to reduce energy consumption. The range hood's operating status is visually indicated by a ring-shaped breathing light: a solid green light indicates normal operation, a blue breathing light indicates low-noise mode, and a flashing red light warns of system malfunction. Maintenance notifications are simultaneously pushed via a mobile app.
[0058] This invention embodiment involves setting a triangular sound field monitoring topology at the duct location of a range hood. This topology is used to collect the raw noise signal during range hood operation. The raw noise signal is separated in the time domain, and overlapping portions in the time domain are separated in the frequency domain to determine noise signature characteristics. Based on these characteristics, an inverse sound wave signal is determined. The raw noise signal is used to locate the source and determine a noise distribution heatmap. In the noise distribution heatmap, the noise target location corresponding to the noise signature characteristics is determined. The inverse sound wave signal is output at the noise target location. The noise signature characteristics are then frequency-domain converted to determine an energy mutation trend. Based on this energy mutation trend, a fault level is determined. Maintenance is then performed based on the fault level. By employing a triangular sound field monitoring topology, the noise source localization accuracy can be maximized within the limited space of the range hood's duct, acquiring complete and precise raw noise signals. Time-frequency domain separation is then performed on the raw noise signal to achieve time-frequency decoupling, separating even noise superimposed in the time domain. This identifies the noise signature characteristics of the raw noise signal, enabling component quantization and significantly improving noise source separation accuracy. Furthermore, the noise signature characteristics provide precise input for generating the inverted sound wave signal, making the waveform of the inverted sound wave signal more closely match the original noise signal, improving noise reduction efficiency. Finally, the noise distribution heatmap based on physical location and component quantization work together to output the inverted sound wave signal at the noise target location, maximizing the resistance of the inverted sound wave signal to the original noise signal and improving the active noise reduction effect of the range hood. Moreover, the detected sound components determine the wear state of the corresponding noise-generating components, identifying different fault levels based on different wear states and requiring different maintenance procedures. This allows for timely detection of faults in critical components, providing early warnings, improving noise reduction stability under complex operating conditions, and reducing equipment maintenance costs.
[0059] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.
[0060] Reference Figure 5 The diagram illustrates a structural block diagram of an embodiment of a noise reduction device for a range hood according to the present invention. A triangular sound field monitoring topology is installed at the air duct position of the range hood. The triangular sound field monitoring topology is used to collect the original noise signal during the operation of the range hood. The noise reduction device for the range hood may specifically include the following modules: The separation module 501 is used to separate the original noise signal in the time domain and separate the overlapping parts in the time domain in the frequency domain to determine the noise soundprint characteristics. Inverting module 502 is used to determine the inverted acoustic wave signal based on the noise acoustic signature characteristics; Distribution module 503 is used to locate the sound source of the original noise signal and determine the noise distribution heat map; The positioning module 504 is used to determine the location of the noise target corresponding to the noise soundprint feature in the noise distribution heat map; The noise reduction module 505 is used to output the anti-phase acoustic wave signal at the noise target location.
[0061] In an optional embodiment of the present invention, the separation module 501 includes: An extraction submodule is used to extract the acoustic feature parameters of the original noise signal; The classification submodule is used to classify the acoustic feature parameters and determine the noise type; The separation submodule is used to separate the components of the original noise signal based on the noise type and determine the noise voiceprint characteristics.
[0062] In an optional embodiment of the present invention, the noise types include motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise, and the classification submodule includes: The acoustic characteristic parameters are compared with preset acoustic reference characteristics to determine whether they are one of the following: motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, or pulse abnormal noise.
[0063] In an optional embodiment of the present invention, the inverting module 502 includes: The synthesis submodule is used to synthesize a candidate set of inverted waveforms based on the noise acoustic features; A matching submodule is used to determine, in the candidate set of inverted waveforms, a target inverted waveform that is spectrally matched with the noise acoustic signature features; The inverting submodule is used to determine the inverted acoustic signal based on the target inverted waveform.
[0064] In an optional embodiment of the present invention, the positioning module 504 includes: The positioning submodule is used to locate the sound source of the original noise signal and determine the location of the sound source. An energy determination submodule is used to determine the energy frequency band of the original noise signal; The heat map determination submodule is used to determine the noise distribution heat map by combining the sound source location and the energy frequency band.
[0065] In an optional embodiment of the present invention, the range hood is provided with multiple speakers, and the noise reduction module 505 includes: A target loudspeaker determination submodule is used to determine the target loudspeaker among multiple loudspeakers based on the location of the noise target; The output submodule is used to output the anti-phase acoustic wave signal based on the speaker.
[0066] In an optional embodiment of the present invention, the device further includes: The conversion module is used to perform frequency domain conversion on the noise acoustic features to determine the energy change trend; The fault module is used to determine the fault level based on the energy mutation trend; The maintenance module is used to perform maintenance based on the fault level.
[0067] In an optional embodiment of the present invention, the triangular sound field monitoring topology includes: The first set of anti-oil microphone arrays is installed inside the air inlet guide hood of the range hood; the second set of anti-oil microphone arrays is installed on the impeller center guard plate of the range hood; and the third set of anti-oil microphone arrays is installed on the surface of the air outlet volute of the range hood.
[0068] In an optional embodiment of the present invention, the surfaces of the first group of oil-resistant microphone arrays, the second group of oil-resistant microphone arrays and the third group of oil-resistant microphone arrays are provided with an oleophobic coating.
[0069] This invention provides an embodiment of a triangular sound field monitoring topology installed at the duct location of a range hood. This topology is used to collect the original noise signal during the operation of the range hood, separate the original noise signal in the time domain, and separate overlapping portions in the time domain in the frequency domain to determine noise signature characteristics. Based on these noise signature characteristics, an inverse sound wave signal is determined. The original noise signal is then used to locate the sound source and determine a noise distribution heatmap. Within the noise distribution heatmap, the noise target location corresponding to the noise signature characteristics is determined. Finally, the inverse sound wave signal is output at the noise target location. By employing a triangular sound field monitoring topology, the noise source localization accuracy can be maximized within the limited space of the range hood's duct, acquiring complete and accurate original noise signals. Then, time-frequency domain separation is performed on the original noise signal to achieve time-frequency decoupling, separating even noise superimposed in the time domain. This identifies the noise signature characteristics of the original noise signal, enabling component quantization and significantly improving noise source separation accuracy. Furthermore, the noise signature characteristics provide precise input for generating the anti-phase sound wave signal, making the waveform of the anti-phase sound wave signal more closely match the original noise signal, thus improving noise reduction efficiency. Finally, the noise distribution heatmap based on physical location and component quantization jointly outputs the anti-phase sound wave signal at the noise target location, allowing the anti-phase sound wave signal to resist the original noise signal to the greatest extent, improving the active noise reduction effect of the range hood.
[0070] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.
[0071] Reference Figure 6 This invention also provides a range hood, comprising: A processor 601 and a memory 602 are provided. The memory 602 stores a computer program executable by the processor 601. When the range hood is in operation, the processor 601 executes the computer program to implement the range hood noise reduction method as described in any embodiment of the present invention. A triangular sound field monitoring topology is provided at the air duct position of the range hood. The triangular sound field monitoring topology is used to collect the original noise signal of the range hood during operation. The range hood noise reduction method includes: The original noise signal is separated in the time domain, and the overlapping parts in the time domain are separated in the frequency domain to determine the noise acoustic features; The antiphase acoustic signal is determined based on the noise acoustic signature characteristics. The original noise signal is used to locate the sound source and determine the noise distribution heatmap; In the noise distribution heatmap, the location of the noise target corresponding to the noise acoustic signature is determined; The anti-phase acoustic signal is output at the noise target location.
[0072] Optionally, the step of separating the original noise signal in the time domain and separating the overlapping parts in the time domain in the frequency domain to determine the noise acoustic signature features includes: Extract the acoustic feature parameters of the original noise signal; The acoustic feature parameters are classified to determine the noise type; Based on the noise type, the original noise signal is component-separated to determine the noise voiceprint characteristics.
[0073] Optionally, the noise types include motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise. The classification of the acoustic characteristic parameters to determine the noise type includes: The acoustic characteristic parameters are compared with preset acoustic reference characteristics to determine whether they are one of the following: motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, or pulse abnormal noise.
[0074] Optionally, the step of determining the antiphase acoustic signal based on the noise acoustic signature features includes: Based on the aforementioned noise acoustic signature features, a candidate set of inverted waveforms is synthesized; In the candidate set of inverted waveforms, a target inverted waveform that matches the spectrum of the noise acoustic signature is determined; The antiphase acoustic signal is determined based on the target antiphase waveform.
[0075] Optionally, the step of locating the sound source of the original noise signal and determining the noise distribution heatmap includes: The original noise signal is subjected to sound source localization to determine the location of the sound source; Determine the energy frequency band of the original noise signal; By combining the location of the sound source and the energy frequency band, a noise distribution heatmap is determined.
[0076] Optionally, the range hood is equipped with multiple speakers, and the step of outputting the anti-phase sound wave signal at the noise target location includes: The target loudspeaker is determined from among multiple loudspeakers based on the location of the noise target; The speaker outputs the anti-phase sound wave signal.
[0077] Optionally, the method further includes: The noise acoustic signature features are frequency domain transformed to determine the energy mutation trend; The fault level is determined based on the energy mutation trend; Maintenance procedures are performed based on the fault level.
[0078] Optionally, the triangular sound field monitoring topology includes: The first set of anti-oil microphone arrays is installed inside the air inlet guide hood of the range hood; the second set of anti-oil microphone arrays is installed on the impeller center guard plate of the range hood; and the third set of anti-oil microphone arrays is installed on the surface of the air outlet volute of the range hood.
[0079] Optionally, the surfaces of the first group of oil-resistant microphone arrays, the second group of oil-resistant microphone arrays, and the third group of oil-resistant microphone arrays are provided with an oleophobic coating.
[0080] This invention provides an embodiment of a triangular sound field monitoring topology installed at the duct location of a range hood. This topology is used to collect the original noise signal during the operation of the range hood, separate the original noise signal in the time domain, and separate overlapping portions in the time domain in the frequency domain to determine noise signature characteristics. Based on these noise signature characteristics, an inverse sound wave signal is determined. The original noise signal is then used to locate the sound source and determine a noise distribution heatmap. Within the noise distribution heatmap, the noise target location corresponding to the noise signature characteristics is determined. Finally, the inverse sound wave signal is output at the noise target location. By employing a triangular sound field monitoring topology, the noise source localization accuracy can be maximized within the limited space of the range hood's duct, acquiring complete and accurate original noise signals. Then, time-frequency domain separation is performed on the original noise signal to achieve time-frequency decoupling, separating even noise superimposed in the time domain. This identifies the noise signature characteristics of the original noise signal, enabling component quantization and significantly improving noise source separation accuracy. Furthermore, the noise signature characteristics provide precise input for generating the anti-phase sound wave signal, making the waveform of the anti-phase sound wave signal more closely match the original noise signal, thus improving noise reduction efficiency. Finally, the noise distribution heatmap based on physical location and component quantization jointly outputs the anti-phase sound wave signal at the noise target location, allowing the anti-phase sound wave signal to resist the original noise signal to the greatest extent, improving the active noise reduction effect of the range hood.
[0081] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.
[0082] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.
[0083] Reference Figure 7 This invention also provides a computer-readable storage medium 701, on which a computer program is stored. When the computer program is run by a processor, it executes the range hood noise reduction method as described in any one of the embodiments of this invention. A triangular sound field monitoring topology is provided at the duct position of the range hood. The triangular sound field monitoring topology is used to collect the original noise signal during the operation of the range hood. The range hood noise reduction method includes: The original noise signal is separated in the time domain, and the overlapping parts in the time domain are separated in the frequency domain to determine the noise acoustic features; The antiphase acoustic signal is determined based on the noise acoustic signature characteristics. The original noise signal is used to locate the sound source and determine the noise distribution heatmap; In the noise distribution heatmap, the location of the noise target corresponding to the noise acoustic signature is determined; The anti-phase acoustic signal is output at the noise target location.
[0084] Optionally, the step of separating the original noise signal in the time domain and separating the overlapping parts in the time domain in the frequency domain to determine the noise acoustic signature features includes: Extract the acoustic feature parameters of the original noise signal; The acoustic feature parameters are classified to determine the noise type; Based on the noise type, the original noise signal is component-separated to determine the noise voiceprint characteristics.
[0085] Optionally, the noise types include motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise. The classification of the acoustic characteristic parameters to determine the noise type includes: The acoustic characteristic parameters are compared with preset acoustic reference characteristics to determine whether they are one of the following: motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, or pulse abnormal noise.
[0086] Optionally, the step of determining the antiphase acoustic signal based on the noise acoustic signature features includes: Based on the aforementioned noise acoustic signature features, a candidate set of inverted waveforms is synthesized; In the candidate set of inverted waveforms, a target inverted waveform that matches the spectrum of the noise acoustic signature is determined; The antiphase acoustic signal is determined based on the target antiphase waveform.
[0087] Optionally, the step of locating the sound source of the original noise signal and determining the noise distribution heatmap includes: The original noise signal is subjected to sound source localization to determine the location of the sound source; Determine the energy frequency band of the original noise signal; By combining the location of the sound source and the energy frequency band, a noise distribution heatmap is determined.
[0088] Optionally, the range hood is equipped with multiple speakers, and the step of outputting the anti-phase sound wave signal at the noise target location includes: The target loudspeaker is determined from among multiple loudspeakers based on the location of the noise target; The speaker outputs the anti-phase sound wave signal.
[0089] Optionally, the method further includes: The noise acoustic signature features are frequency domain transformed to determine the energy mutation trend; The fault level is determined based on the energy mutation trend; Maintenance procedures are performed based on the fault level.
[0090] Optionally, the triangular sound field monitoring topology includes: The first set of anti-oil microphone arrays is installed inside the air inlet guide hood of the range hood; the second set of anti-oil microphone arrays is installed on the impeller center guard plate of the range hood; and the third set of anti-oil microphone arrays is installed on the surface of the air outlet volute of the range hood.
[0091] Optionally, the surfaces of the first group of oil-resistant microphone arrays, the second group of oil-resistant microphone arrays, and the third group of oil-resistant microphone arrays are provided with an oleophobic coating.
[0092] This invention provides an embodiment of a triangular sound field monitoring topology installed at the duct location of a range hood. This topology is used to collect the original noise signal during the operation of the range hood, separate the original noise signal in the time domain, and separate overlapping portions in the time domain in the frequency domain to determine noise signature characteristics. Based on these noise signature characteristics, an inverse sound wave signal is determined. The original noise signal is then used to locate the sound source and determine a noise distribution heatmap. Within the noise distribution heatmap, the noise target location corresponding to the noise signature characteristics is determined. Finally, the inverse sound wave signal is output at the noise target location. By employing a triangular sound field monitoring topology, the noise source localization accuracy can be maximized within the limited space of the range hood's duct, acquiring complete and accurate original noise signals. Then, time-frequency domain separation is performed on the original noise signal to achieve time-frequency decoupling, separating even noise superimposed in the time domain. This identifies the noise signature characteristics of the original noise signal, enabling component quantization and significantly improving noise source separation accuracy. Furthermore, the noise signature characteristics provide precise input for generating the anti-phase sound wave signal, making the waveform of the anti-phase sound wave signal more closely match the original noise signal, thus improving noise reduction efficiency. Finally, the noise distribution heatmap based on physical location and component quantization jointly outputs the anti-phase sound wave signal at the noise target location, allowing the anti-phase sound wave signal to resist the original noise signal to the greatest extent, improving the active noise reduction effect of the range hood.
[0093] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.
[0094] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0095] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0096] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0098] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.
[0099] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.
[0100] The above provides a detailed description of a noise reduction method for a range hood, a noise reduction device for a range hood, a range hood, and a computer-readable storage medium provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.
Claims
1. A method for reducing noise in a range hood, characterized in that, A triangular sound field monitoring topology is installed at the air duct position of the range hood. The triangular sound field monitoring topology is used to collect the raw noise signal of the range hood during operation. The method includes: The original noise signal is separated in the time domain, and the overlapping parts in the time domain are separated in the frequency domain to determine the noise acoustic features; The antiphase acoustic signal is determined based on the noise acoustic signature characteristics. The original noise signal is used to locate the sound source and determine the noise distribution heatmap; In the noise distribution heatmap, the location of the noise target corresponding to the noise acoustic signature is determined; The anti-phase acoustic signal is output at the noise target location.
2. The method according to claim 1, characterized in that, The steps of separating the original noise signal in the time domain and separating the overlapping parts in the time domain in the frequency domain to determine the noise acoustic signature characteristics include: Extract the acoustic feature parameters of the original noise signal; The acoustic feature parameters are classified to determine the noise type; Based on the noise type, the original noise signal is component-separated to determine the noise voiceprint characteristics.
3. The method according to claim 2, characterized in that, The noise types include motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, and pulse abnormal noise. The classification of the acoustic characteristic parameters to determine the noise type includes: The acoustic characteristic parameters are compared with preset acoustic reference characteristics to determine whether they are one of the following: motor fundamental frequency harmonic noise, blade aerodynamic noise, broadband wind noise, or pulse abnormal noise.
4. The method according to claim 1, characterized in that, The step of determining the antiphase acoustic signal based on the noise acoustic signature features includes: Based on the aforementioned noise acoustic signature features, a candidate set of inverted waveforms is synthesized; In the candidate set of inverted waveforms, a target inverted waveform that matches the spectrum of the noise acoustic signature is determined; The antiphase acoustic signal is determined based on the target antiphase waveform.
5. The method according to claim 1, characterized in that, The step of locating the sound source of the original noise signal and determining the noise distribution heatmap includes: The original noise signal is subjected to sound source localization to determine the location of the sound source; Determine the energy frequency band of the original noise signal; By combining the location of the sound source and the energy frequency band, a noise distribution heatmap is determined.
6. The method according to claim 1, characterized in that, The range hood is equipped with multiple speakers, and the step of outputting the anti-phase sound wave signal at the noise target location includes: The target loudspeaker is determined from among multiple loudspeakers based on the location of the noise target; The speaker outputs the anti-phase sound wave signal.
7. The method according to claim 1, characterized in that, The method further includes: The noise acoustic signature features are frequency domain transformed to determine the energy mutation trend; The fault level is determined based on the energy mutation trend; Maintenance procedures are performed based on the fault level.
8. The method according to claim 1, characterized in that, The triangular sound field monitoring topology includes: The first set of anti-oil microphone arrays is installed inside the air inlet guide hood of the range hood; the second set of anti-oil microphone arrays is installed on the impeller center guard plate of the range hood; and the third set of anti-oil microphone arrays is installed on the surface of the air outlet volute of the range hood.
9. The method according to claim 8, characterized in that, The surfaces of the first group of oil-resistant microphone arrays, the second group of oil-resistant microphone arrays, and the third group of oil-resistant microphone arrays are provided with an oleophobic coating.
10. A noise reduction device for a range hood, characterized in that, A triangular sound field monitoring topology is installed at the air duct position of the range hood. The triangular sound field monitoring topology is used to collect the raw noise signal of the range hood during operation. The device includes: The separation module is used to separate the original noise signal in the time domain and separate the overlapping parts in the time domain in the frequency domain to determine the noise acoustic features; The inverting module is used to determine the inverted acoustic wave signal based on the noise acoustic signature characteristics; The distribution module is used to locate the sound source of the original noise signal and determine the noise distribution heatmap. The positioning module is used to determine the location of the noise target corresponding to the noise soundprint features in the noise distribution heatmap. A noise reduction module is used to output the anti-phase acoustic wave signal at the noise target location.
11. A range hood, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, it implements the steps of the noise reduction method for a range hood as described in any one of claims 1-9.
12. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when executed by a processor, the computer program implements the steps of the noise reduction method for a range hood as described in any one of claims 1-9.