Intelligent control method of range hood, range hood and intelligent kitchen system

Abstract

This application relates to an intelligent control method for a range hood, a range hood itself, and an intelligent kitchen system. The method generates a modulation drive signal using a carrier signal, the characteristic frequency signal of a target LED bead, and an initial modulation depth. An initial PWM drive signal is generated based on the modulation drive signal to control the LED lights on the range hood. A photoelectric detection signal is obtained by a photoelectric sensor detecting the light emitted by the LED lights. The photoelectric detection signal is cross-correlated and demodulated based on the characteristic frequency signal to obtain the measured amplitude corresponding to the cross-correlation function. An attenuation coefficient is calculated based on the measured amplitude and the initial amplitude. The attenuation coefficient is used to compensate the initial PWM drive signal to obtain a target PWM drive signal, which adjusts the LED light emission. This method solves the problem of insufficient reliability in LED light decay compensation adjustment for range hoods, enabling online detection and compensation of light decay during range hood operation, improving the intelligence of the range hood, and providing a better lighting experience.

Description

Technical Field

[0001] This application relates to the field of kitchen appliance technology, and in particular to an intelligent control method for a range hood, a range hood, and an intelligent kitchen system. Background Technology

[0002] With continuous technological advancements, kitchen appliances are gradually integrating more intelligent functions. As one of the indispensable core appliances in the modern kitchen, range hoods still have much room for improvement in enhancing the cooking experience. Take the LED lights commonly equipped on range hoods as an example; their main function is to provide sufficient and clear lighting for the cooking area. However, LED light sources have obvious light decay characteristics—as usage time increases, their brightness gradually decreases, and the color temperature may also shift. This change in light effect not only interferes with the user's accurate judgment of the color and doneness of food but may also exacerbate visual fatigue, affecting the overall cooking experience.

[0003] Currently, the industry typically uses preset fixed compensation curves to compensate for LED light decay. However, factors such as usage frequency, ambient temperature, and number of switching cycles all affect the actual decay rate and extent of LEDs. Fixed compensation strategies are difficult to accurately match the decay state of LEDs in actual use, easily leading to undercompensation or overcompensation, and failing to achieve fine-grained, adaptive luminous efficacy control.

[0004] Therefore, there is currently no effective solution to the problem of insufficient reliability in the LED light decay compensation adjustment of existing range hood technologies. Summary of the Invention

[0005] This embodiment provides an intelligent control method for a range hood, a range hood, and an intelligent kitchen system to solve the problem of insufficient reliability in the LED light decay compensation adjustment of range hoods in related technologies.

[0006] Firstly, this embodiment provides an intelligent control method for a range hood, the method comprising:

[0007] Based on the preset carrier signal, the characteristic frequency signal of the target LED bead, and the initial modulation depth, a modulation drive signal is generated; based on the modulation drive signal, an initial PWM drive signal is generated to control the LED lights on the range hood to emit light.

[0008] Acquire a photoelectric detection signal; the photoelectric detection signal is obtained by a photoelectric sensor detecting the light emitted by the LED.

[0009] Based on the characteristic frequency signal, the photoelectric detection signal is cross-correlation demodulated to obtain the cross-correlation function, and the amplitude of the cross-correlation function is extracted to obtain the measured amplitude.

[0010] Based on the measured amplitude and the preset initial amplitude, the attenuation coefficient is calculated;

[0011] Based on the attenuation coefficient, the initial PWM drive signal is compensated to obtain the target PWM drive signal, which is used to adjust the LED light emission.

[0012] In some embodiments, based on the attenuation coefficient, the initial PWM drive signal is compensated to obtain a target PWM drive signal to adjust the LED's illumination, including:

[0013] Determine whether the attenuation coefficient is less than the attenuation threshold; the attenuation threshold is a value less than 1.

[0014] If the attenuation coefficient is less than the attenuation threshold, a replacement prompt message will be output.

[0015] If the attenuation coefficient is greater than the attenuation threshold, the initial PWM drive signal is compensated based on the attenuation coefficient to obtain the target PWM drive signal, so as to adjust the LED light emission.

[0016] In some embodiments, the method further includes:

[0017] The oil fume concentration parameter is calculated based on the attenuation coefficient corresponding to the LED bead group of each color light.

[0018] Based on the oil fume concentration parameters and the preset concentration threshold, the fan speed of the range hood is adjusted.

[0019] In some embodiments, the method further includes:

[0020] When the LED light is off, the photoelectric sensor is controlled to collect ambient light signals;

[0021] Spectral analysis was performed on the ambient light signal to obtain the average spectral amplitude, target frequency amplitude, and interference frequency amplitude.

[0022] Based on the average spectral amplitude, the target frequency amplitude, and the interference frequency amplitude, a joint determination is made as to whether a flame marker exists.

[0023] If the flame indicator persists for more than a certain period of time, the range hood fan will remain on.

[0024] If the flame indicator is not detected within the second time period, the photoelectric sensor is controlled to enter the energy-saving mode, and the range hood fan is controlled to turn off.

[0025] In some embodiments, the attenuation coefficient is calculated based on the measured amplitude and a preset initial amplitude, including:

[0026] Based on the measured amplitude, the initial modulation depth is dynamically updated to obtain the updated modulation depth;

[0027] Based on the updated modulation depth, the modulation drive signal, the photoelectric detection signal, and the measured amplitude are updated sequentially until the measured amplitude is within a preset standard range. Then, the latest updated modulation depth is determined as the current modulation depth.

[0028] The attenuation coefficient is calculated based on the preset initial amplitude, the latest measured amplitude, the current modulation depth, and the initial modulation depth.

[0029] In some embodiments, the initial modulation depth is dynamically updated based on the measured amplitude to obtain the updated modulation depth, including:

[0030] If the measured amplitude is less than the first standard threshold, the modulation depth is increased to obtain the updated modulation depth;

[0031] If the measured amplitude is greater than the second standard threshold, the modulation depth is reduced to obtain the updated modulation depth.

[0032] In some embodiments, the method further includes:

[0033] Based on the latest current modulation depth, initial modulation depth, current driving voltage, rated driving voltage, current measured current, and set current, the fault status of the LED lamp is jointly determined; wherein, the current driving voltage is the sampled value of the LED lamp driving voltage, and the current measured current is calculated based on the target PWM driving signal.

[0034] In some embodiments, the method further includes:

[0035] The aging coefficient of the LED lamp, the current modulation depth, and the preset failure threshold are obtained to predict the remaining lifespan of the LED lamp.

[0036] The aging coefficient is obtained by fitting the aging model based on historical data of the current modulation depth and the initial modulation depth.

[0037] Secondly, this embodiment provides a range hood, including: a photoelectric sensor, an LED light, a fan drive circuit, and a controller;

[0038] The controller is connected to the photoelectric sensor, the LED light, and the fan drive circuit respectively, and is used to implement the steps of the method described in any one of the first aspects.

[0039] Thirdly, this application also provides an intelligent kitchen system, including: a range hood, a cooktop, and a controller;

[0040] The range hood includes a photoelectric sensor, an LED light, and a fan drive circuit; the photoelectric sensor, the LED light, and the fan drive circuit are respectively connected to the controller;

[0041] The controller is also connected to the stove and is used to implement the steps of the method described in any one of the first aspects.

[0042] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0043] Compared with related technologies, the intelligent control method for a range hood, the range hood itself, and the intelligent kitchen system provided in this embodiment generate a modulation drive signal based on a preset carrier signal, the characteristic frequency signal of the target LED bead, and an initial modulation depth; based on the modulation drive signal, an initial PWM drive signal is generated to control the LED lights on the range hood to emit light; a photoelectric detection signal is acquired; the photoelectric detection signal is obtained by a photoelectric sensor detecting the light emitted by the LED lights; based on the characteristic frequency signal, the photoelectric detection signal is cross-correlated and demodulated to obtain a cross-correlation function, and the amplitude of the cross-correlation function is extracted to obtain a measured amplitude; based on the measured amplitude and the preset initial amplitude, an attenuation coefficient is calculated; based on the attenuation coefficient, the initial PWM drive signal is compensated to obtain a target PWM drive signal to adjust the LED light emission, thus solving the problem of insufficient reliability in LED light decay compensation adjustment of range hoods. This allows for online detection of LED light decay during range hood operation and pre-adjustment compensation, achieving intelligent control of the LED lights and providing a better cooking lighting experience.

[0044] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0045] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0046] Figure 1 This is a schematic diagram of the installation of LED lights on the range hood in an embodiment of this application;

[0047] Figure 2 This is a flowchart illustrating the intelligent control method for a range hood in an embodiment of this application;

[0048] Figure 3 This is a schematic diagram of the process for dynamically adjusting the modulation depth in a preferred embodiment of this application;

[0049] Figure 4 This is a schematic diagram of the intelligent control process for LED lights and fans in a preferred embodiment of this application;

[0050] Figure 5 This is a schematic diagram of the intelligent control process based on flame detection in a preferred embodiment of this application;

[0051] Figure 6 This is a flowchart illustrating the LED lamp fault prediction process in a preferred embodiment of this application.

[0052] Figure 7 This is a structural block diagram of the range hood in the embodiments of this application.

[0053] Figure labels: 100, range hood; 110, LED light; 120, photoelectric sensor; 200, oil fume cloud. Detailed Implementation

[0054] To better understand the purpose, technical solution, and advantages of this application, the application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0055] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these” used in this application do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to these processes, methods, products, or devices. Words such as “connected,” “linked,” and “coupled” used in this application are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. Normally, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," "third," etc., used in this application are merely to distinguish similar objects and do not represent a specific order of objects.

[0056] Because fixed compensation strategies struggle to accurately match the decay state of LEDs in actual use, they can easily lead to insufficient or excessive compensation, failing to achieve precise and adaptive light efficiency control and affecting normal cooking. To address this issue, this embodiment provides an intelligent control method for a range hood. This method is applied to a range hood equipped with an LED light for illumination and a photoelectric sensor positioned opposite the LED light. The photoelectric sensor collects the light emitted by the LED light when it is turned on, such as... Figure 1 As shown, the LED light 110 and the photoelectric sensor 120 are mounted opposite each other on the smoke collection hood 130 of the range hood 100. The light emitted by the LED light 110 can penetrate the smoke cloud 200 during cooking and shine onto the photoelectric sensor 120. Furthermore, the photoelectric sensor 120 can also be configured to collect ambient light signals of the cooking area (at least including the stove and cookware area) when the LED light 110 is off. Figure 2 This is a flowchart illustrating the intelligent control method for the range hood in this embodiment. Figure 2 As shown, the process of this method includes:

[0057] Step S210: Based on the preset carrier signal, the characteristic frequency signal of the target LED bead, and the initial modulation depth, a modulation drive signal is generated; based on the modulation drive signal, an initial PWM drive signal is generated to control the LED lights on the range hood to emit light.

[0058] Specifically, this embodiment uses a modulated drive signal to control the range hood's light emission. The method for synthesizing the modulated drive signal includes: defining a carrier signal and a characteristic frequency signal of the target LED bead, wherein the carrier signal can be a high-frequency square wave, f c =1kHz, 50% duty cycle, can avoid visible flicker; LED lights typically use LEDs of different colors, such as cool white CW LEDs, warm white CW LEDs, or other colored LEDs, to define low-frequency sine waves with different characteristic frequencies to distinguish different LEDs, for example f cw =23kHz, f ww =19kHz. Set the initial modulation depth, such as m cw0 =0.3,m ww0 =0.3. The modulation drive current I is synthesized based on the preset carrier signal and the characteristic frequency signal of the target LED. drive,s (t) can be represented as:

[0059] ;

[0060] Where 's' represents the target LED type (CW or CW or others), and 'I' represents the target LED type. 0,s f represents the reference drive current (mA) of the corresponding target LED chip. s The m represents the characteristic frequency corresponding to the target LED bead. sThe initial modulation depth is indicated (preferably between 0.2 and 0.5), and rect represents the square wave function (high level 1, low level 0).

[0061] Step S220: Obtain photoelectric detection signal; the photoelectric detection signal is obtained by the photoelectric sensor detecting the light emitted by the LED.

[0062] Specifically, the photoelectric detection signal V output by the photoelectric sensor det (t) is represented as:

[0063] ;

[0064] Among them, A s Represents the initial amplitude, sin(2πf) s t) represents the signal term, β represents ambient light sensitivity (mV / lx), and E amb γ(t) represents ambient light, and γ(t) represents circuit noise.

[0065] Step S230: Based on the characteristic frequency signal, perform cross-correlation demodulation on the photoelectric detection signal to obtain the cross-correlation function, and extract the amplitude of the cross-correlation function to obtain the measured amplitude.

[0066] Specifically, a reference signal r is generated based on the characteristic frequency signal of the target LED. s (t):

[0067] ;

[0068] Cross-correlation function R s (t) is represented as:

[0069] ;

[0070] Where T represents the integration period (taken as 5 / f) s , such as f s For a 19Hz signal, T = 5 / 19 ≈ 0.26s); τ is the time offset used to traverse all possible alignment positions of the signal, with a range of 0 ≤ τ ≤ 1 / f. s (Covering one complete signal cycle), step size: Δτ = 1 / (f s ×N), where N is the number of sampling points, preferably N=100.

[0071] The reference signal is an ideal copy of the target signal, and signal separation is achieved through frequency locking (frequency division multiplexing principle). The correlation peak of the signal is found by scanning τ, and the position of the peak reflects the phase difference of the actual signal.

[0072] Extract the measured amplitude A meas :

[0073] .

[0074] Step S240: Calculate the attenuation coefficient based on the measured amplitude and the preset initial amplitude.

[0075] Specifically, the preset initial amplitude is taken from the factory calibration value of the new LED light. The attenuation coefficient can be the ratio of the measured amplitude to the initial amplitude; or, based on the current photoelectric detection signal acquisition results, the modulation depth of the modulation drive signal is dynamically adjusted to improve the reliability of signal acquisition, and the photoelectric detection signal is reacquired to obtain the latest measured amplitude and initial amplitude. The attenuation coefficient is calculated based on the ratio of the measured amplitude to the initial amplitude and the ratio of the initial modulation depth to the current modulation depth.

[0076] Step S250: Based on the attenuation coefficient, compensate the initial PWM drive signal to obtain the target PWM drive signal, so as to adjust the LED light emission.

[0077] Specifically, the target PWM drive signal = initial PWM drive signal ÷ attenuation coefficient. Based on this, the light emission compensation of each LED group can be achieved.

[0078] In this embodiment, a modulation drive signal is generated based on a preset carrier signal, the characteristic frequency signal of the target LED bead, and an initial modulation depth. An initial PWM drive signal is then generated based on the modulation drive signal to control the LED lights on the range hood. A photoelectric detection signal is acquired; this signal is obtained by a photoelectric sensor detecting the light emitted by the LED lights. Based on the characteristic frequency signal, the photoelectric detection signal is cross-correlated and demodulated to obtain the measured amplitude corresponding to the cross-correlation function. Based on the measured amplitude and the initial amplitude, an attenuation coefficient is calculated. Based on the attenuation coefficient, the initial PWM drive signal is compensated to obtain the target PWM drive signal, which adjusts the LED light emission. This solves the problem of insufficient reliability in LED light decay compensation adjustment for range hoods. It allows for online detection of LED light decay during range hood operation and pre-adjustment compensation, achieving intelligent control of the LED lights and providing a better cooking lighting experience.

[0079] In some embodiments, step S240 above, which calculates the attenuation coefficient based on the measured amplitude and the preset initial amplitude, specifically includes the following steps:

[0080] Step S241: Determine whether the measured amplitude is within the preset standard range. If the measured amplitude is within the preset standard range, proceed to step S242; if the measured amplitude is not within the preset standard range, proceed to subsequent steps S243 to S245.

[0081] Step S242: Determine the initial modulation depth as the current modulation depth, and calculate the attenuation coefficient based on the measured amplitude and the initial amplitude.

[0082] Specifically, if the measured amplitude is within the preset standard range, it indicates that the measured result is normal and usable, and the current initial modulation depth can be maintained. Without changing the modulation depth, the attenuation coefficient can be obtained based on the measured amplitude and the initial amplitude. The standard range can be configured as [first standard threshold, second standard threshold], for example [0.15, 0.3]. When A... meas When A > 0.3V, the modulation depth needs to be reduced to prevent amplifier saturation. meas When the signal-to-noise ratio is less than 0.15, the modulation depth needs to be increased to improve the signal-to-noise ratio.

[0083] Step S243: Based on the measured amplitude, dynamically update the initial modulation depth to obtain the updated modulation depth.

[0084] For details, see Figure 3 Based on preset adjustment rules, the initial modulation depth is dynamically updated: if the measured amplitude A meas If the amplitude is less than the first standard threshold (e.g., 0.15), the initial modulation depth is increased to obtain the updated modulation depth; if the measured amplitude A meas If the initial modulation depth is greater than the second standard threshold (e.g., 0.3), then the initial modulation depth is reduced to obtain the updated modulation depth.

[0085] Step S244: Based on the updated modulation depth, sequentially update the modulation drive signal, photoelectric detection signal, and measured amplitude until the measured amplitude is within the preset standard range, then determine the latest updated modulation depth as the current modulation depth.

[0086] Specifically, based on the updated modulation depth, the modulation drive signal is resynthesized; based on the modulation drive signal, the LED light is controlled to emit light, and the light emitted by the LED light is detected by an electrical sensor to obtain an updated photoelectric detection signal; based on the updated photoelectric detection signal, the measured amplitude corresponding to the cross-correlation function is calculated, and the relationship between the latest measured amplitude and the first standard threshold and the second standard threshold is evaluated until the measured amplitude is greater than the first standard threshold and less than the second standard threshold. Then, the dynamic adjustment of the modulation depth ends and the current modulation depth is obtained. Otherwise, the above-mentioned updated modulation depth is updated again using the adjustment rules, and step S244 is repeated.

[0087] For example, the modulation depth adjustment rule is as follows:

[0088] ;

[0089] Among them, A meas The measured amplitude is represented by m, and the modulation depth before dynamic update is represented by m. new This indicates the modulation depth after dynamic updates.

[0090] Step S245: Calculate the attenuation coefficient based on the preset initial amplitude, the latest measured amplitude, the current modulation depth, and the initial modulation depth.

[0091] For example, the attenuation coefficient k s The calculation formula is:

[0092] ;

[0093] Among them, A meas A represents the measured amplitude. s The initial amplitude is represented by m0 (taken from the factory calibration value of a new lamp), the initial modulation depth is represented by m0 (taken from the factory calibration value of a new lamp), and the current modulation depth is represented by m.

[0094] In this embodiment, the measured amplitude is adjusted in real time based on the adjustment depth, and the ratio of the amplitude is dynamically corrected based on the change ratio of the adjustment depth to obtain a more accurate attenuation coefficient.

[0095] In some embodiments, step S250 above, which compensates the initial PWM drive signal based on the attenuation coefficient to obtain the target PWM drive signal for adjusting the LED illumination, includes:

[0096] Step S251: Determine whether the attenuation coefficient is less than the attenuation threshold; the attenuation threshold is a value less than 1.

[0097] Step S252: If the attenuation coefficient is less than the attenuation threshold, output a replacement prompt message.

[0098] Step S253: If the attenuation coefficient is greater than the attenuation threshold, the initial PWM drive signal is compensated based on the attenuation coefficient to obtain the target PWM drive signal, so as to adjust the LED light emission.

[0099] For details, see Figure 4 You can set an attenuation threshold, such as k. a =0.7, k a This is an empirical value, but it can also be set separately for different color temperatures of LEDs and products. When k... s <k a If the degradation is too high, it is determined that the aging is severe, and replacement is prompted. If the degradation threshold has not been reached, compensation is performed. Taking cool white CW LED groups and warm white WW LED groups as examples, the target PWM drive signal for the cool white CW LED group is... cw =PWM0 cw / k cw The target PWM drive signal for the warm white CW LED group ww =PWM0 ww / k ww , where PWM0 cw and PWM0ww These represent the initial PWM drive signals for the two LED groups, respectively.

[0100] In some embodiments, the intelligent control method for the range hood further includes:

[0101] Step S310: Calculate the oil fume concentration parameter based on the attenuation coefficients corresponding to the LED bead groups of each color light. The attenuation coefficients corresponding to the LED bead groups of each color light include, but are not limited to, the attenuation coefficient k for cool white light. cw Warm white light attenuation coefficient k ww .

[0102] Step S320: Adjust the fan speed of the range hood based on the oil fume concentration parameters and the preset concentration threshold.

[0103] Specifically, the principle of oil fume concentration monitoring is as follows: oil fume particles increase the difference in light intensity between cool white (cw) and warm white (ww) light (based on the principle of dual-wavelength scattering difference). The formula for calculating concentration c is as follows:

[0104] ;

[0105] Where G represents the concentration coefficient, which can be pre-calibrated, for example, G = 20 mg / m³. 3 ;k cw k is the attenuation coefficient of the cool white light LED chip. ww The attenuation coefficient of the warm white light LED.

[0106] See Figure 4 The concentration c can be combined with the threshold corresponding to different types of range hoods. If the concentration is higher than the threshold, the corresponding fan speed can be increased; otherwise, the current speed is maintained, thus realizing fan linkage and improving the intelligent control of the range hood.

[0107] In some embodiments, the intelligent control method for the range hood further includes:

[0108] Step S410: When the LED light is off, control the photoelectric sensor to collect the ambient light signal.

[0109] Specifically, the brightness and color of a burning flame fluctuate over time, especially around 100Hz (corresponding to the flame pulsation frequency of most gas stoves). The flame flicker frequency is determined by combustion dynamics (turbulent combustion instability).

[0110] ;

[0111] Where f represents the flame pulsation frequency (90-110Hz), D represents the burner orifice diameter (typically 5mm), and U represents the gas flow velocity (2-4m / s). This pulsation originates from the periodic vortex shedding in the fuel-air mixing zone.

[0112] Therefore, existing photoelectric sensors (without adding new hardware) can be used to collect ambient light signals during the LED modulation gap (e.g., when the LED gap is closed), with a sampling rate ≥500Hz (meeting the Nyquist criterion).

[0113] Step S420: Perform spectrum analysis on the ambient light signal to obtain the average spectrum amplitude, target frequency amplitude, and interference frequency amplitude.

[0114] For details, see Figure 5 The initial ambient light signal was filtered using a bandpass filter, retaining 80-120Hz, to obtain the target ambient light signal V. flame (t). For V flame Perform an FFT transformation on (t), for example, calculate the FFT every 0.5s to obtain F(k). Extract the 100Hz amplitude A. 100 =|F(k 100 The amplitude at 50Hz is used as the target frequency. 50 The amplitude of the interference frequency is taken as the value. All spectral amplitudes within the frequency range of 20-200Hz are collected, and their arithmetic mean is calculated to obtain the average spectral amplitude A. avg .

[0115] Step S430: Based on the average spectral amplitude, target frequency amplitude, and interference frequency amplitude, jointly determine whether a flame symbol exists.

[0116] Specifically, the flame detection algorithm is as follows:

[0117] ;

[0118] K1 and K2 are empirical thresholds that can be determined based on specific product conditions, for example, K1=3.0 and K2=2.5. This dual-threshold anti-false-judgment mechanism can effectively prevent interference from other industrial frequency lighting factors in the kitchen.

[0119] In step S440, if the flame indicator persists for more than a first time interval ta, the range hood fan is kept on. Further, within the smart kitchen, the stove's action signal is acquired. If the flame indicator persists for less than the first time interval, it is determined whether the stove has a shutdown action signal. If so, the range hood fan enters a delayed shutdown state and continues to monitor the flame indicator. If the stove does not send a shutdown action signal, a reminder signal is generated to alert the user if soup has overflowed, causing the flame to extinguish, and the gas valve is closed, while simultaneously outputting an audible and visual alarm signal.

[0120] In step S450, if no flame indicator is detected within the second time tb, the photoelectric sensor is controlled to enter the energy-saving mode, and the range hood fan is controlled to turn off.

[0121] Traditional flame detectors (UV / IR sensors) are expensive and susceptible to oil fume contamination. This embodiment utilizes the characteristic optical pulsation of flames (100Hz) to achieve flame detection by analyzing the spectral characteristics of the ambient light channel. It reuses existing photoelectric sensors without incurring additional costs, and the dual-threshold anti-false-judgment mechanism improves the accuracy of judgment.

[0122] In some embodiments, the intelligent control method for the range hood further includes:

[0123] Step S510: Based on the latest current modulation depth, initial modulation depth, current driving voltage, rated driving voltage, current measured current, and set current, jointly determine the fault status of the LED lamp; wherein, the current driving voltage is the sampled value of the LED lamp driving voltage, and the current measured current is calculated based on the target PWM driving signal.

[0124] In some of these embodiments, see Figure 6 Based on the latest current modulation depth, initial modulation depth, current drive voltage, rated drive voltage, current measured current, and set current, the parameter change rate is calculated:

[0125] Based on the current driving voltage V CC and rated drive voltage V CC0 The voltage drift of the LED lamp, ΔV, is calculated to be |V CC / V CC0 -1|.

[0126] Based on the current measured current I meas and set current I set The current drift ΔI = |I meas / I set -1|.

[0127] Based on the latest current modulation depth m s and initial modulation depth m s,ref Calculate the modulation depth drift Δm = |m| that reflects the driving system relative to the initial state. s / m s,ref -1|.

[0128] Determine whether the modulation depth drift Δm is greater than the first safety threshold (e.g., 0.1), the voltage drift ΔV is greater than the second safety threshold (e.g., 0.05), and the current drift ΔI is greater than the third threshold (e.g., 0.1). If any of the above conditions are met, a fault is predicted, and the health index is calculated. Otherwise, the condition is predicted to be safe.

[0129] The formula for calculating the health index H is as follows:

[0130] ;

[0131] Where, m s,ref Indicates the initial modulation depth, m s V represents the current modulation depth. CC This indicates the current driving voltage (sampled value of the LED driving voltage detected by the ADC), V CC0 Indicates the rated drive voltage (power supply design nominal value, such as 12V), I meas I represents the current measured current (calculated based on the current PWM duty cycle). set This indicates the set current (the configured target current).

[0132] The fault type of an LED lamp is determined by combining voltage drift ΔV, current drift ΔI, modulation depth drift Δm, and health index H. For details, see [link to relevant documentation]. Figure 6 If Δm is greater than the first drift threshold (e.g., 0.2), ΔV is greater than the first power supply threshold (e.g., 0.1), and H is less than the first health threshold (e.g., 0.85), and all three conditions are met simultaneously, it indicates a decrease in power supply capacity, and is therefore determined to be power supply aging. If Δm is greater than the second drift threshold (e.g., 0.3), ΔV is less than the second power supply threshold (e.g., 0.05), and H is less than the second health threshold (e.g., 0.9), and all three conditions are met simultaneously, it indicates a decrease in LED luminous efficacy, and is therefore determined to be LED lamp degradation. If Δm is greater than the third drift threshold (e.g., 0.1), H is greater than the third health threshold (e.g., 1.15), and ΔI is greater than the current threshold (0.15), and all three conditions are met simultaneously, it indicates abnormal current feedback and deterioration of the current-limiting resistor value, and is therefore determined to be resistor deterioration.

[0133] Furthermore, different control strategies can be adopted for the different fault types mentioned above, and the fault log can be updated. For power supply aging faults, the LED lights can be controlled to operate at reduced power and a "Power Abnormality" prompt can be issued; for LED light attenuation faults, compensation can be increased and a "LED Bead Aging" prompt can be issued; for resistor deterioration faults, the current can be calibrated and a "Circuit Abnormality" prompt can be issued.

[0134] Traditional power supply detection relies on additional sensors (current / voltage probes). This embodiment uses modulation depth parameters as fault indicators to establish a multi-parameter fusion diagnostic model, which can accurately distinguish multiple types of faults and effectively monitor anomalies.

[0135] In some of these embodiments, see Figure 6 The intelligent control method of this range hood also includes:

[0136] Step S520: Obtain the aging coefficient, current modulation depth, and preset failure threshold of the LED lamp to predict the remaining lifespan of the LED lamp; wherein, the aging coefficient is obtained by fitting the aging model based on historical data of the current modulation depth and the initial modulation depth.

[0137] Specifically, establish an aging model m s (t):

[0138] ;

[0139] Where β represents the natural aging factor (which can be taken as 0.0001 / hour), α represents the accelerated aging factor (which can be calibrated based on historical data), K represents the fault amplitude (which can be calibrated based on historical data), m0 represents the initial modulation depth, and m s This indicates the modulation depth corresponding to an LED light malfunction.

[0140] The failure threshold m given by the experimental calibration limit (e.g., the value corresponding to 30% light decay, calibrated in advance), the current m s And using aging factors β and α, calculate the remaining lifespan:

[0141] .

[0142] In this embodiment, by fusing multiple parameters, the remaining lifespan of the LED lamp is quantitatively estimated, thereby achieving the effect of predictive maintenance.

[0143] This embodiment provides a range hood, see [link / reference] Figure 7 The range hood includes: a photoelectric sensor, an LED light, a fan drive circuit, and a controller. The controller is connected to the photoelectric sensor, the LED light, and the fan drive circuit, respectively, and is used to implement the steps of the intelligent control method for the range hood in any of the above embodiments.

[0144] In this embodiment, the problem of insufficient intelligent control of the range hood is solved, thereby providing a better cooking experience.

[0145] This application also provides an intelligent kitchen system, including: a range hood, a cooktop, and a controller; the range hood includes a photoelectric sensor, an LED light, and a fan drive circuit; the photoelectric sensor, the LED light, and the fan drive circuit are respectively connected to the controller; the controller is also connected to the cooktop, for implementing the steps of the intelligent control method for the range hood in any of the above embodiments.

[0146] In this embodiment, the problem of insufficient intelligent control of the range hood is solved, thereby providing a better cooking experience.

[0147] It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. All other embodiments derived by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0148] Obviously, the accompanying drawings are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application.

[0149] The term "embodiment" in this application refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply that it is mutually exclusive with or independent of other embodiments. It will be clearly or implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0150] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. A smart control method for a range hood, characterized in that, The method includes: Based on the preset carrier signal, the characteristic frequency signal of the target LED bead, and the initial modulation depth, a modulation drive signal is generated; based on the modulation drive signal, an initial PWM drive signal is generated to control the LED lights on the range hood to emit light. Acquire a photoelectric detection signal; the photoelectric detection signal is obtained by a photoelectric sensor detecting the light emitted by the LED. Based on the characteristic frequency signal, the photoelectric detection signal is cross-correlation demodulated to obtain the cross-correlation function, and the amplitude of the cross-correlation function is extracted to obtain the measured amplitude. Based on the measured amplitude and the preset initial amplitude, the attenuation coefficient is calculated; Based on the attenuation coefficient, the initial PWM drive signal is compensated to obtain the target PWM drive signal, which is used to adjust the LED light emission.

2. The intelligent control method for a range hood according to claim 1, characterized in that, Based on the attenuation coefficient, the initial PWM drive signal is compensated to obtain the target PWM drive signal, which is used to adjust the LED's illumination, including: Determine whether the attenuation coefficient is less than the attenuation threshold; the attenuation threshold is a value less than 1. If the attenuation coefficient is less than the attenuation threshold, a replacement prompt message will be output. If the attenuation coefficient is greater than the attenuation threshold, the initial PWM drive signal is compensated based on the attenuation coefficient to obtain the target PWM drive signal, so as to adjust the LED light emission.

3. The intelligent control method for a range hood according to claim 1, characterized in that, The method further includes: The oil fume concentration parameter is calculated based on the attenuation coefficient corresponding to the LED bead group of each color light. Based on the oil fume concentration parameters and the preset concentration threshold, the fan speed of the range hood is adjusted.

4. The intelligent control method for a range hood according to claim 1, characterized in that, The method further includes: When the LED light is off, the photoelectric sensor is controlled to collect ambient light signals; Spectral analysis was performed on the ambient light signal to obtain the average spectral amplitude, target frequency amplitude, and interference frequency amplitude. Based on the average spectral amplitude, the target frequency amplitude, and the interference frequency amplitude, a joint determination is made as to whether a flame marker exists. If the flame indicator persists for more than a certain period of time, the range hood fan will remain on. If the flame indicator is not detected within the second time period, the photoelectric sensor is controlled to enter the energy-saving mode, and the range hood fan is controlled to turn off.

5. The intelligent control method for a range hood according to claim 1, characterized in that, Based on the measured amplitude and the preset initial amplitude, the attenuation coefficient is calculated, including: Based on the measured amplitude, the initial modulation depth is dynamically updated to obtain the updated modulation depth; Based on the updated modulation depth, the modulation drive signal, the photoelectric detection signal, and the measured amplitude are updated sequentially until the measured amplitude is within a preset standard range. Then, the latest updated modulation depth is determined as the current modulation depth. The attenuation coefficient is calculated based on the preset initial amplitude, the latest measured amplitude, the current modulation depth, and the initial modulation depth.

6. The intelligent control method for a range hood according to claim 5, characterized in that, Based on the measured amplitude, the initial modulation depth is dynamically updated to obtain the updated modulation depth, including: If the measured amplitude is less than the first standard threshold, the modulation depth is increased to obtain the updated modulation depth; If the measured amplitude is greater than the second standard threshold, the modulation depth is reduced to obtain the updated modulation depth.

7. The intelligent control method for a range hood according to claim 5, characterized in that, The method further includes: Based on the latest current modulation depth, initial modulation depth, current driving voltage, rated driving voltage, current measured current, and set current, the fault status of the LED lamp is jointly determined; wherein, the current driving voltage is the sampled value of the LED lamp driving voltage, and the current measured current is calculated based on the target PWM driving signal.

8. The intelligent control method for a range hood according to claim 6, characterized in that, The method further includes: The aging coefficient of the LED lamp, the current modulation depth, and the preset failure threshold are obtained to predict the remaining lifespan of the LED lamp. The aging coefficient is obtained by fitting the aging model based on historical data of the current modulation depth and the initial modulation depth.

9. A range hood, characterized in that, include: Photoelectric sensors, LED lights, fan drive circuits, and controllers; The controller is connected to the photoelectric sensor, the LED light, and the fan drive circuit respectively, and is used to implement the steps of the method according to any one of claims 1 to 8.

10. An intelligent kitchen system, characterized in that, include: Range hoods, cooktops, and controllers; The range hood includes a photoelectric sensor, an LED light, and a fan drive circuit; The photoelectric sensor, the LED light, and the fan drive circuit are respectively connected to the controller; The controller is also connected to the stove and is used to implement the steps of the method according to any one of claims 1 to 8.

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