An extractor hood and an intelligent control method thereof

Abstract

The application discloses an extractor hood and an intelligent control method thereof. The extractor hood comprises an air inlet assembly, a fan box body arranged above a ceiling of a kitchen, and a fan arranged in the fan box body. The fan box body is hung to a floor of a top of the kitchen. The extractor hood further comprises a microphone array for collecting sound in a channel through which oil fume passes, at least two acceleration sensors for collecting vibration of the fan box body, a secondary loudspeaker for emitting reverse sound waves according to the sound collected by the microphone array, and an electromagnetic actuator for generating reverse vibration according to the vibration of the fan box body collected by the acceleration sensors.

Description

Technical Field

[0001] This invention relates to an oil fume purification device, and more particularly to a range hood and an intelligent control method for the range hood. Background Technology

[0002] Range hoods have become an indispensable kitchen appliance in modern homes. Installed above the stove, they quickly remove and exhaust the waste from the stove and the harmful fumes produced during cooking.

[0003] As users become increasingly focused on user experience, range hoods and cooktops are now paying more attention to noise reduction and concealed design during cooking, leading to the popularity of products with ceiling-mounted fan housings in recent years. On one hand, users of ceiling-mounted (split-type) products are generally more sensitive to noise. While these products reduce noise by housing the fan housing within the kitchen ceiling, making the perceived noise level slightly lower than that of a standard integrated range hood, the ceiling primarily isolates high-frequency noise (because higher frequencies have weaker penetration through obstacles), leaving mid-to-low frequencies unisolated. This alters the overall frequency response, resulting in a slightly strange sound compared to standard products. Therefore, some of these products are incorporating active noise cancellation measures to reduce low-frequency noise and further improve the user experience, as disclosed in Chinese patent applications 202220778031.X and 202220778038.1.

[0004] However, range hoods typically use multi-blade centrifugal fans with 48-80 blades, resulting in two key characteristics: 1) a higher blade passing frequency (BPF) compared to ordinary fans (5-18 blades); and 2) noise energy radiated by the impeller shifts towards mid-to-high frequencies, falling within the range most sensitive to human hearing (rather than the low-frequency band below 500Hz, which is easier to reduce with traditional active noise cancellation). Furthermore, traditional broadband noise reduction algorithms cannot accurately capture the harmonic groups generated by these densely packed blades, and the distance between the noise source of a traditional range hood and the human ear is too close, making it difficult for the reverse sound waves to cancel out slightly higher frequency noise. Therefore, ordinary active noise cancellation solutions are often ineffective in kitchen environments.

[0005] Furthermore, the actuators (microphones) used in traditional active noise cancellation are large and occupy valuable fluid channel space. Moreover, as diaphragm structures, they are easily contaminated by oil and require frequent maintenance or cleaning, further increasing the after-sales costs for users. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing a range hood that improves noise reduction, provides a more comfortable and convenient cooking experience, and enhances adaptability to different scenarios.

[0007] The second technical problem to be solved by the present invention is to provide an intelligent control method for the above-mentioned range hood.

[0008] The technical solution adopted by the present invention to solve the first technical problem mentioned above is: a range hood, including an air intake component, a fan housing installed above the ceiling of the kitchen, and a fan installed inside the fan housing, wherein the fan housing is hung on the floor slab of the kitchen interior. The range hood also includes: Microphone array, used to collect sound from the passage through which cooking fumes pass; Accelerometers, used to collect vibrations of the fan housing, are provided in at least two configurations. Secondary loudspeakers are used to emit anti-phase sound waves based on the sound collected by the microphone array; and An electromagnetic actuator is used to generate reverse vibration based on the vibration of the fan housing collected by an acceleration sensor.

[0009] By setting up two types of active noise-reducing actuators (secondary speakers and electromagnetic actuators) to work together, the noise reduction effect is improved, providing a more comfortable and convenient cooking experience and enhancing scene adaptability.

[0010] Preferably, to make the sound collection more comprehensive, the microphone array includes a first microphone disposed near the smoke inlet of the air intake assembly, a second microphone disposed at the air outlet of the fan, and a third and fourth microphone disposed on the inner wall of the fan housing, respectively.

[0011] Preferably, to improve the accuracy of vibration acquisition and damping, the fan housing is attached to the floor slab via hooks, and the hooks are locked to the floor slab by screws. The acceleration sensor is located at the connection between the hooks and the fan housing, and the electromagnetic actuator is integrated into the screw.

[0012] Preferably, to improve the comprehensiveness and uniformity of vibration reduction, the hooks are arranged at the four corners of the top of the fan housing, and the acceleration sensor and electromagnetic actuator each have four corresponding hooks.

[0013] Preferably, to improve the comprehensiveness and uniformity of active noise cancellation, there are four secondary speakers, which are respectively disposed on the front, back, left and right inner walls of the fan housing.

[0014] Furthermore, to facilitate the control and driving of the actuator, the range hood also includes a controller capable of receiving signals collected by a microphone array and an accelerometer, a speaker drive circuit that controls a secondary speaker according to the control signal output by the controller, and an actuator drive circuit that controls an electromagnetic actuator according to the control signal output by the controller.

[0015] The technical solution adopted by the present invention to solve the second technical problem mentioned above is: an intelligent control method for a range hood, using the range hood described above, characterized in that: the intelligent control method includes the following steps: 1) The range hood is started, and the fan runs at a preset speed, proceeding to step 2); 2) Initialize the microphone array, accelerometer, secondary speaker, and electromagnetic actuator; 3) Determine whether the fan is running. If yes, proceed to step 4). If no, it means that it is currently in standby mode. 4) Raw signal acquisition: Sound pressure signals are collected using a microphone array. ,in The microphones in the microphone array are numbered; vibration signals are collected using an accelerometer. ,in The sequence number of each accelerometer sensor is used to acquire the motor speed signal of the fan. ; 5) Feature frequency extraction: Extract the following three feature frequencies respectively: 5.1) Fundamental frequency : in, This refers to the number of blades in the wind turbine. 5.2) Dominant Acoustic Mode Frequency Extraction: Extraction of sound pressure signals from microphone arrays After sequentially performing frame segmentation, windowing preprocessing, and FFT processing, the spectral amplitude is calculated. Finally, the dominant mode frequencies are extracted. , The sound pressure pressure weights are determined by the pre-calibrated spatial position coefficients of each microphone. 5.3) Vibration resonance peak frequency extraction: Extraction of vibration signals collected by each accelerometer. The process involves sequentially performing frame segmentation, windowing preprocessing, and FFT processing. Then, the octave band energy is calculated, and finally, the center frequency corresponding to the frequency band with the most concentrated vibration energy is extracted as the resonant frequency. ; 6) Synthesize reference signal : in, , , The coefficients are pre-calibrated and satisfy... > , The sampling period; 7) Based on the reference signal Calculate the initial control signal and : in For calculation The coefficients of the FIR filter at that time, , coefficient, The order of the FIR filter. For FIR filter tap index; 8) Acoustic-vibration co-optimization: in, for The inverse matrix, for , The coupling matrix; This yields the final drive signal. and , Used to drive secondary speakers Used to drive electromagnetic actuators; 9) Acquire error signals , ; Spatially weighted average sound pressure level for each microphone: This represents the real-time sound pressure level of the m-th microphone. , The secondary path impulse response is measured in advance; The method of obtaining it is as follows: First, the acceleration signals acquired by each acceleration sensor are converted into velocity signals: Then, filtering is performed; Next, the effective value (RMS) is calculated: Finally, perform a spatial average: ; in, The sampling period; 10) Update the weights: in, To converge the step size, ; in, Set the convergence step size for AVC; 11) Update the coupling matrix: The learning rate for the coupling matrix is ​​then used, and we return to step 3.

[0016] By capturing the three-dimensional sound field distribution inside the fan housing in real time using a distributed microphone array, and simultaneously monitoring the vibration transmission path of the housing using an accelerometer, a composite reference signal is generated using sound-vibration feature fusion technology. This signal drives the secondary speaker array to emit anti-phase sound waves to cancel aerodynamic noise. At the same time, the electromagnetic actuator is controlled to generate reverse vibration to suppress structural sound transmission. Through online compensation using a sound pressure-vibration coupling matrix, the problem of insufficient low-frequency noise suppression (<200Hz, 8.2dB difference) and control inaccuracy caused by oil accumulation in traditional solutions in enclosed ceiling spaces can be solved, thus improving the noise reduction experience under all operating conditions during cooking.

[0017] Preferably, to avoid misjudgment due to random impact interference, in step 5), the calculation of octave band energy in the vibration resonance peak frequency extraction is performed by dividing the low-frequency band into 1 / 3 octave band sub-bands and calculating the vibration energy of each band. :

[0018] This yields the resonance peak.

[0019]

[0020] in, The average energy across the entire frequency band. This is the threshold coefficient.

[0021] Preferably, in step 7), .

[0022] Compared with existing technologies, the advantages of this invention are as follows: By setting two types of active noise reduction actuators (secondary speakers and electromagnetic actuators), they work together to improve the noise reduction effect, providing a more comfortable and convenient cooking experience and enhancing scene adaptability; the three-dimensional sound field distribution inside the fan housing is captured in real time by a distributed microphone array, and the vibration transmission path of the housing is monitored simultaneously using an accelerometer. A composite reference signal is generated using sound-vibration feature fusion technology to drive the secondary speaker array to emit anti-phase sound waves to cancel aerodynamic noise. At the same time, the electromagnetic actuator is controlled to generate reverse vibration to suppress structural sound transmission. Through online compensation of the sound pressure-vibration coupling matrix, the problems of insufficient low-frequency noise suppression (<200Hz difference of 8.2dB) and control inaccuracy caused by oil accumulation in traditional solutions in enclosed ceiling spaces can be solved, thus improving the noise reduction experience under all working conditions during cooking. Attached Figure Description

[0023] Figure 1 This is a front view of the range hood in use after installation, according to an embodiment of the present invention.

[0024] Figure 2 This is a side view of the range hood in its installed and usable state according to an embodiment of the present invention;

[0025] Figure 3 This is a cross-sectional side view of a range hood according to an embodiment of the present invention;

[0026] Figure 4 for Figure 1 A magnified schematic diagram of part I;

[0027] Figure 5 This is a hardware principle block diagram of a range hood according to an embodiment of the present invention;

[0028] Figure 6 This is a flowchart of the active noise reduction control method for a range hood according to an embodiment of the present invention;

[0029] Figure 7 This is a flowchart of the feature frequency extraction process in the active noise reduction method for a range hood according to an embodiment of the present invention. Detailed Implementation

[0030] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0031] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Since the embodiments disclosed in this invention can be arranged in different directions, these terms indicating direction are only for illustration and should not be regarded as limitations. For example, "upper" and "lower" are not necessarily limited to directions opposite to or consistent with the direction of gravity. In addition, features defined with "first" and "second" may explicitly or implicitly include one or more of such features.

[0032] See Figures 1-4 A range hood includes an air inlet assembly 1, a fan housing 2 mounted above a suspended ceiling 100 in the kitchen, a fan 3 housed within the fan housing 2, a connecting duct 4 connecting the air inlet assembly 1 and the fan housing 2, and an air outlet mask 5 mounted at the air outlet of the fan 3. The air inlet assembly 1 includes a smoke inlet 11. The air inlet assembly 1 can be flush with a wall cabinet 200 below the suspended ceiling 100, can be exposed below the wall cabinet 200, or can only be exposed below the wall cabinet 200 during operation. The connecting duct 4 can be a flexible hose to allow adjustment of the position of the fan housing 2 and the air inlet assembly 1 during installation.

[0033] The fan housing 2 is hung on the floor slab 300 at the top of the room. It is fixed to the fan housing 2 and the floor slab 300 respectively by hooks 21. The hooks 21 and the floor slab 300 are locked together by screws 22 to achieve the hanging. How to hoist it is the prior art in this field and will not be described in detail here. For reference, please refer to the applicant's Chinese patent application number 202221537478.4.

[0034] The range hood also includes a microphone array, an accelerometer 7, a secondary speaker 8, and an electromagnetic actuator 9. The microphone array is distributed to collect sound from the passage through which the cooking fumes pass. It includes a first microphone 61 located near the smoke inlet 11 of the air inlet assembly 1, a second microphone 62 located at the air outlet of the fan 3, a third microphone 63 located on the inner wall of the fan housing 2, and a fourth microphone 64 located on the inner wall of the fan housing 2. The first microphone 61 can be located within a panel assembly 12 at the bottom front end of the air inlet assembly 1; this panel assembly 12 is typically used for button control, etc. The second microphone 62 can be located inside the fan 3 or within the air outlet mask 5. The third microphone 63 is located on the front inner wall of the fan housing 2, and the fourth microphone 64 is located on the rear inner wall of the fan housing 2. Thus, the four microphones form a spatial collection layout. Preferably, the third microphone 63 and the fourth microphone 64 are located at the center of their respective inner walls of the fan housing 2. The electromagnetic actuator 9 is integrated into the screw 22.

[0035] The aforementioned accelerometer 7 has at least two components; in this embodiment, there are four, respectively disposed at the mounting points (connection points of hooks 21 and fan housing 21) at the four corners of the top of the fan housing 2. There are also four secondary speakers 8, respectively disposed on the front, back, left, and right inner walls of the fan housing 2. The output of the secondary speakers 8 can cover 100Hz~1kHz. Since the fan housing 2 is a cuboid, the number of accelerometer 7 and secondary speakers 8 is four.

[0036] The range hood's built-in controller can receive signals from the microphone array and accelerometer 7 and perform calculations to control the secondary speaker 8 and electromagnetic actuator 9.

[0037] See Figure 5 The microphone array can capture the three-dimensional sound field distribution inside the fan housing 2 in real time, and the accelerometer 7 can simultaneously monitor the vibration transmission path of the fan housing 2. The signals collected by the signal acquisition modules of the microphone array and the accelerometer 7 are transmitted to the controller 10 of the range hood. The controller 10 can be an independently set device or it can be built into the range hood. The controller 10 is preferably a multi-modal collaborative controller. The controller 10 may include an ANC (Active Noise Control) algorithm processor 101 and an AVC (Active Vibration Control) algorithm processor 102. The range hood may also include a speaker drive circuit 103 and an actuator drive circuit 104. The corresponding ANC algorithm processor 101 of the controller 10 calculates the control signal and outputs it to the speaker drive circuit 103, and the corresponding AVC algorithm processor 102 outputs it to the actuator drive circuit 104, so as to control the secondary speaker 8 and the electromagnetic actuator 9 to perform corresponding actions respectively.

[0038] Therefore, this invention uses sound-vibration feature fusion technology to generate a composite reference signal, which drives the secondary speaker array 8 to emit anti-phase sound waves to cancel aerodynamic noise, while controlling the electromagnetic actuator 8 to generate reverse vibration to suppress structural sound transmission; through online compensation of the sound pressure-vibration coupling matrix, it solves the problems of insufficient low-frequency noise suppression (<200Hz difference of 8.2dB) and control inaccuracy caused by oil accumulation in traditional solutions in enclosed ceiling spaces, thus improving the noise reduction experience under all working conditions during cooking.

[0039] Specifically, the intelligent control method for active noise reduction of the range hood of the present invention is described in [reference needed]. Figure 6 It includes the following steps:

[0040] 1) The range hood starts, and fan 3 runs at the preset speed. It is determined whether the user has selected intelligent monitoring. If yes, proceed to step 2). If no, it enters manual mode. This judgment can also be skipped and the process can directly proceed to step 2.

[0041] 2) Initialize each sensor and actuator, namely the microphone array, accelerometer 7, secondary speaker 8 and electromagnetic actuator 9.

[0042] 3) Determine if fan 3 is running. If yes, proceed to step 4). If no, it means that it is currently in standby mode.

[0043] 4) Raw signal acquisition

[0044] Sound pressure signals are collected using a microphone array. ,in That is, they correspond to four spatial positions respectively. The first microphone 61 can be recorded as number 1. The second microphone, number 62, is designated as number 2. The third microphone, number 63, is designated as number 3. The fourth microphone, 64, is designated as number 4. The sampling time is [value]. This sound pressure level reflects the three-dimensional distribution of airborne noise.

[0045] Vibration signals are collected using accelerometer 7. ,in That is, each corresponding to one of the four fulcrums. The sampling time represents the signal, which reflects the energy transfer path of structural vibration.

[0046] Motor speed signal of fan 3 The PSMS or BLDC motor drive modules commonly used in range hoods have their own speed information, so this speed information can be obtained directly. This signal provides the characteristics of the fundamental frequency source of the aerodynamic noise of the range hood. If the motor itself does not have this information, some existing methods can be used to detect the motor speed, such as the back EMF method or using an encoder. These are conventional technologies and will not be elaborated on here.

[0047] 5) Feature frequency extraction

[0048] Combination Figure 7 In this step, the following three feature frequencies are extracted respectively:

[0049] 5.1) Fundamental frequency calculation: The fundamental frequency of the discrete noise generated by the periodic cutting of airflow by the blades of fan 3. (Unit: Hz) is:

[0050]

[0051] Since the fan 3 of a range hood is mostly a multi-blade centrifugal fan, the number of blades in the fan 3 is... Generally, there are 48 to 80 pieces, such as when N , hour, This frequency is within the range that the human ear is sensitive to;

[0052] 5.2) Dominant acoustic mode frequencies, represented by weighted summation to identify the strongest standing wave frequency within the fan housing 2: First, the sound pressure signal collected by the microphone array... The signal is divided into frames (frame length can be selected as needed), and then preprocessed by windowing, such as using a Hanning window (the Hanning window can also be replaced by a Hamming window, Blackman window, Kaiser window, etc.). The Hanning window balances frequency resolution and amplitude accuracy in noise spectrum analysis and is a common choice for acoustic signal processing. After FFT processing, the spectral amplitude is calculated. (Microphone array spectral amplitude), and finally extract the dominant mode frequency. , The sound pressure level weights of the spatial position coefficients of each microphone are pre-calibrated under standard operating conditions, such as the microphone near the smoke inlet at position 11. The sound pressure level is 0.4 (near the noise source, where the sound pressure amplitude is highest), at the air outlet. The noise level is 0.3 (critical area of ​​airflow noise at the air outlet), at two locations on the inner wall of the fan housing 2. , The values ​​are 0.2 (lower weight, monitoring the standing wave of the wind turbine casing 2); Preferred, , , , In this step, from acquiring the sound pressure signal to obtaining the spectral amplitude, it is basically the same as the existing signal processing method.

[0053] 5.3) Vibration resonance peak frequency extraction, which is achieved by finding the center frequency corresponding to the frequency band where the vibration energy is most concentrated, calculated by integration, as the resonance peak: First, the vibration signals collected by each acceleration sensor 7 are analyzed. The process involves framing (frame length can be selected as needed), followed by windowing preprocessing, such as Hanning windowing, and then FFT processing. The octave band energy is then calculated, and finally, the center frequency corresponding to the frequency band with the highest concentration of vibration energy is extracted as the resonant frequency. ;

[0054] After FFT processing, the octave band energy is calculated first to avoid misjudgment due to random impact interference. Specifically, the low-frequency band (e.g., 0~500Hz) is divided into 1 / 3 octave band sub-bands (15 in total), and the vibration energy of each band is calculated. :

[0055] The parameters in the above formulas are explained in the table below:

[0056]

[0057] Table 1: Explanation of symbols in the vibration energy calculation formula

[0058] also, It is the first The starting frequency of each frequency band, in Hz, for example, when When =3 (center frequency 100Hz), ; It is a frequency determined by 1 / 3 octave band, and the unit is Hz. For example, when the center frequency is 100Hz, .

[0059] Therefore, by using fixed-ratio bandwidth analysis, the vibration frequency response characteristics of the ceiling structure can be adapted, avoiding the problem of insufficient low-frequency resolution in equal-bandwidth analysis.

[0060] This yields the resonance peak (satisfying) And the center frequency of the sub-band with the highest energy)

[0061]

[0062] in, The average energy across the entire frequency band. It is the energy arithmetic average (dynamic value); This is a threshold coefficient, an empirically determined value calibrated in advance under standard operating conditions, preferably 1.5~2.0, with an even more preferred value of 1.8 (excluding background noise). Here it is used as a function variable to represent the first... The individual carries vibrational energy, which depends on the dynamic value obtained from measured vibration. It also satisfies the following relationship: .

[0063] See Table 2 below:

[0064]

[0065] Table 2: Center Frequency and Corresponding Vibration Energy Example

[0066] To ensure the above resonance peak Its real-time nature allows for updates at intervals, such as every 200ms. (To meet the requirements for responding to changes in fan speed).

[0067] Existing methods in this field typically only use the peak value of the FFT spectrum to detect the fundamental frequency (e.g., 100Hz), ignoring harmonic components and spatial coupling effects, resulting in poor phase mismatch between the out-of-phase acoustic wave and noise. See Table 3 below:

[0068]

[0069] Table 3: Comparison of Existing Methods and the Method of the Present Invention

[0070] Laboratory tests showed that when the fan speed of the fan 3 changed abruptly (800rpm→1200rpm), the traditional method had a misjudgment rate of 42%, while the misjudgment rate of the present invention was <5%.

[0071] 6) Synthesize reference signal :

[0072]

[0073] This yields signals that integrate the fundamental frequency, acoustic modes, and vibration resonance peak characteristics of the aerodynamic noise generated by the rotating blades. This represents the discrete index of the data after FFT transformation. , , These are coefficients calibrated in advance through a noise energy ratio experiment. Sampling period. Due to the fundamental frequency As the largest source of noise energy, therefore The maximum coefficient value is 1.0, representing the acoustic mode. Due to the amplification effect of the fan housing 2, this is the secondary dominant noise, while the resonance peak... The contribution of structural sound transmission is smaller than that of acoustic modes, therefore > Preferred , More preferably, ,

[0074] 7) Based on the reference signal The ANC algorithm processor 101 calculates the initial control signal. The AVC algorithm processor 102 calculates the initial control signal to drive the secondary speaker 8. , for use in controlling electromagnetic actuator 9.

[0075] Specifically, the ANC algorithm processor 101 can use the FxLMS algorithm (Filter-x Least Mean Square algorithm) for calculation:

[0076]

[0077] This is a typical discrete-time adaptive FIR filter. The coefficients of the FIR filter (delay is...) The time-varying weights (time-varying weights), their initial values In LMS-type algorithms (such as FxLMS), it is standard practice to initialize the weights to zero vectors. In engineering, this can prevent transient oscillations caused by random initial values ​​when the system starts up.

[0078] The AVC algorithm processor 102 can use the LMS-VC algorithm (variable convergence factor least mean square algorithm) for calculation:

[0079]

[0080] This is a typical discrete-time adaptive FIR filter, where As a vibration reference signal, From base frequency And its second harmonic synthesis (harmonic coefficients are calibrated through vibration spectrum analysis), These are the coefficients of the FIR filter (delay is...). The time-varying weights (time-varying weights) determine the generation of control forces to counteract vibrations. Time, from the past Vibration reference signal at each moment The initial value of the "proportion" or "gain" it accounts for. This also conforms to the norms of control theory. The FIR filter order (number of taps) is dynamically adjusted according to the main frequency to satisfy... , To accommodate the increased vibration bandwidth caused by oil contamination, the frequency range is 32-64, with 48 being preferred, to cover 1-2 cycles of the dominant vibration frequency (80-200Hz). This value determines the controller's time memory depth. : ( (sampling period), example: when , → Memory depth 4.8ms; This is the tap index for the FIR filter. This allows us to iterate through all historical sampling points.

[0081] 8) Acoustic-vibration co-optimization:

[0082]

[0083] in, for The inverse matrix, for , The coupling matrix (convolution expansion matrix) is obtained from this; thus, the final driving signal is derived. and They respectively drive the secondary speaker 8 and the electromagnetic actuator 9;

[0084] Initial value:

[0085] The initial value is the identity matrix, ensuring that the value is obtained in the first iteration. , This indicates that the sound pressure control and vibration control are assumed to be independent when the system is started.

[0086] 9) Acquire error signals , ;

[0087]

[0088] For ANC residuals, Spatially weighted average sound pressure level for the four microphones:

[0089]

[0090] For the first Real-time sound pressure level of each microphone, and the theoretical sound pressure contribution of each speaker at the corresponding microphone position: Calculate the convolution; from this, we obtain The residuals obtained through spatial weighted averaging can resist local oil pollution interference and reduce the error by 60%. The pre-measured secondary path impulse response (pre-system identification) represents the acoustic transfer characteristics from the secondary speaker 8 to the microphone, which can be identified by existing technology. White noise is played through the speaker, the microphone response is measured, and the transfer function is fitted using the LMS algorithm, such as the offline calibration technology in patent CN212570385U.

[0091] For AVC residuals, specifically, the method for obtaining them is as follows:

[0092] First, the acceleration signals acquired by each accelerometer 7 are converted into velocity signals:

[0093]

[0094] Then, filtering is performed, such as bandpass filtering: 20~500Hz (4th order Butterworth);

[0095] Next, the effective value (RMS) is calculated (the RMS value of the velocity signal can more accurately characterize the vibration energy because...). )):

[0096] Finally, a spatial average is calculated over the four points:

[0097] .

[0098] The residuals obtained through the above method can improve the characterization accuracy by 3 times.

[0099] 10) Update the weights:

[0100]

[0101] in : Convergence step size (adaptive adjustment), with a value range of To control the speed of weight updates, it can be based on Amplitude dynamic adjustment: Increase when noise is high. Accelerate convergence, or conversely, reduce it to avoid overshoot.

[0102] Other parameters are shown in Table 4 below:

[0103] Table 4: Meaning of parameters for active noise control

[0104] Then, the weights are updated adaptively and iteratively generated using the LMS algorithm. ;in, This is the convergence step size for AVC, which can be a fixed value of 0.0005. If it is too large, it will cause system oscillation; if it is too small, it will cause slow convergence.

[0105] 11) Update the coupling matrix:

[0106] Minimize the objective function:

[0107] When the fan housing 2 vibrates strongly ( Increase), automatically enhance the output of electromagnetic actuator 9, when air noise is prominent ( Increase the output of the loudspeaker (prioritize optimizing the loudspeaker output). The coefficient 0.7 / 0.3 is calibrated based on the noise characteristics of the range hood (primarily airborne sound).

[0108] And thus, the coupling matrix is ​​updated:

[0109]

[0110] The learning rate for the coupling matrix can be experimentally calibrated in advance, and the preferred range of values ​​is [value range missing]. A more preferred value is 0.002; then return to step 3).

[0111] When the range hood is running, the rotation of fan 3 generates fundamental frequency noise ( ), forming a standing wave resonance above the 100mm ceiling. ), and transmit structural vibrations through the mounting supports of the fan housing 2. Existing solutions are typically only for... Noise reduction, and by using the method of this invention, 1) spatial sound field weighted fusion, can accurately capture resonant frequencies. 2) Vibration energy integration can identify the dominant structural noise. 3) A three-band synthesized reference signal is used to fully cover the noise source; 4) Acoustic-vibration co-optimization → blocks the "air → structure" noise coupling path. This achieves full-path noise suppression and solves the low-frequency noise amplification problem unique to the fan housing 2. See Table 5 below for details:

[0112]

[0113] Table 5: Comparison of the advantages of the method of the present invention and existing solutions.

Claims

1. A range hood, comprising an air intake assembly (1), a fan housing (2) disposed above a ceiling (100) in a kitchen, and a fan (3) disposed within the fan housing (2), wherein the fan housing (2) is suspended from the floor slab (300) at the top of the kitchen interior. Its features are: The range hood also includes: Microphone array, used to collect sound from the passage through which cooking fumes pass; An accelerometer (7) is used to collect vibrations of the fan housing (2), and has at least two. Secondary loudspeaker (8) for emitting antiphase sound waves based on sound collected by the microphone array; and An electromagnetic actuator (9) is used to generate reverse vibration based on the vibration of the fan housing (2) collected by the acceleration sensor (7).

2. The range hood according to claim 1, characterized in that: The microphone array includes a first microphone (61) located at the smoke inlet (11) near the air inlet assembly (1), a second microphone (62) located at the air outlet of the fan (3), and a third microphone (63) and a fourth microphone (64) respectively located on the inner wall of the fan housing (2).

3. The range hood according to claim 1 or 2, characterized in that: The fan housing (2) is attached to the floor slab (300) by a hook (21). The hook (21) and the floor slab (300) are locked together by a screw (22). The acceleration sensor (7) is located at the connection between the hook (21) and the fan housing (2). The electromagnetic actuator (9) is integrated into the screw (22).

4. The range hood according to claim 3, characterized in that: The hooks (21) are arranged at the four corners of the top of the fan housing (2), and the acceleration sensor (7) and the electromagnetic actuator (9) each have four corresponding ones.

5. The range hood according to claim 1 or 2, characterized in that: There are four secondary loudspeakers (8), which are respectively installed on the front, back, left and right inner walls of the fan housing (2).

6. The range hood according to claim 1 or 2, characterized in that: The range hood also includes a controller (10) capable of receiving signals collected by a microphone array and an accelerometer (7), a speaker drive circuit (103) that controls a secondary speaker (8) according to the control signal output by the controller (10), and an actuator drive circuit (104) that controls an electromagnetic actuator (9) according to the control signal output by the controller (10).

7. A smart control method for a range hood, using a range hood as described in any one of claims 1 to 6, characterized in that: The intelligent control method includes the following steps: 1) The range hood is started, and the fan (3) runs at the preset speed, proceeding to step 2); 2) Initialize the microphone array, accelerometer (7), secondary speaker (8) and electromagnetic actuator (9); 3) Determine whether the fan (3) is running. If yes, proceed to step 4). If no, it means that it is currently in standby mode. 4) Raw signal acquisition: Sound pressure signals are collected using a microphone array. ,in The serial number of each microphone in the microphone array; vibration signals are collected by an accelerometer (7). ,in The serial numbers of each acceleration sensor (7) are used; the motor speed signal of the fan (3) is obtained. ; 5) Feature frequency extraction: Extract the following three feature frequencies respectively: 5.1) Fundamental frequency : in, The number of blades of the fan (3); 5.2) Acoustic dominant mode frequency extraction: Extraction of sound pressure signals acquired by the microphone array After sequentially performing frame segmentation, windowing preprocessing, and FFT processing, the spectral amplitude is calculated. Finally, the dominant mode frequencies are extracted. , Sound pressure weights for the pre-calibrated spatial position coefficients of each microphone; 5.3) Extraction of vibration resonance peak frequency: Extraction of vibration signals collected by each acceleration sensor (7) The process involves sequentially performing frame segmentation, windowing preprocessing, and FFT processing. Then, the octave band energy is calculated, and finally, the center frequency corresponding to the frequency band with the most concentrated vibration energy is extracted as the resonant frequency. ; 6) Synthesize reference signal : in, , , The coefficients are pre-calibrated and satisfy... > , The sampling period; 7) Based on the reference signal Calculate the initial control signal and : in , For calculation The coefficients of the FIR filter at that time, , The coefficients of the FIR filter, The order of the FIR filter. For FIR filter tap index; 8) Acoustic-vibration co-optimization: in, for The inverse matrix, for , The coupling matrix; This yields the final drive signal. and , Used to drive the secondary speaker (8), Used to drive electromagnetic actuator (9); 9) Acquire error signals , ; Spatially weighted average sound pressure level for each microphone: This represents the real-time sound pressure level of the m-th microphone. , The secondary path impulse response is measured in advance; The method of obtaining it is as follows: First, the acceleration signals acquired by each accelerometer 7 are converted into velocity signals: Then, filtering is performed; Next, the effective value (RMS) is calculated: Finally, perform a spatial average: ； in, The sampling period; 10) Update the weights: in, For active noise control convergence step size, ; in, To determine the convergence step size for active vibration control; 11) Update the coupling matrix: The learning rate for the coupling matrix is ​​then used, and we return to step 3.

8. The intelligent control method for a range hood according to claim 7, characterized in that: In step 5), the calculation of octave band energy in the vibration resonance peak frequency extraction is performed by dividing the low-frequency band into 1 / 3 octave band sub-bands and calculating the vibration energy of each band. : in, It is the first The starting frequency of each frequency band Subband bandwidth; This yields the resonance peak. in, The average energy across the entire frequency band. This is the threshold coefficient.

9. The intelligent control method for a range hood according to claim 7, characterized in that: In step 7), .

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