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CN-121977235-A - Automatic adjusting method of intelligent range hood and intelligent range hood

CN121977235ACN 121977235 ACN121977235 ACN 121977235ACN-121977235-A

Abstract

The application relates to an automatic adjusting method of an intelligent range hood and the intelligent range hood, wherein the method comprises the steps of collecting an air pressure fluctuation signal in a cooking area; the method comprises the steps of carrying out feature extraction of at least a time domain dimension, a frequency domain dimension and a change gradient dimension on an air pressure fluctuation signal to obtain air pressure fluctuation features, judging the type of a cooking action based on the air pressure fluctuation features, and generating a corresponding automatic adjustment instruction based on the type of the cooking action. The technical problem that the existing automatic adjusting method cannot accurately sense the change of aerodynamic parameters in a cooking area, so that the automatic adjusting accuracy of the intelligent range hood is poor is solved.

Inventors

  • HE LIBO

Assignees

  • 宁波方太厨具有限公司

Dates

Publication Date
20260505
Application Date
20260105

Claims (10)

  1. 1. An intelligent automatic adjusting method for a range hood is characterized by comprising the following steps: Collecting an air pressure fluctuation signal in a cooking area; Performing feature extraction of at least a time domain dimension, a frequency domain dimension and a variation gradient dimension on the air pressure fluctuation signal to obtain air pressure fluctuation features; determining a type of cooking action based on the air pressure fluctuation feature; And generating a corresponding automatic adjustment instruction based on the type of the cooking action.
  2. 2. The method of claim 1, wherein the acquiring the air pressure fluctuation signal in the cooking area comprises: defining the cooking area; collecting an original air pressure signal in the cooking area; and performing filtering processing on the original air pressure signal to obtain the air pressure fluctuation signal.
  3. 3. The method of claim 1, wherein performing feature extraction of at least a time domain dimension, a frequency domain dimension, and a varying gradient dimension on the barometric pressure fluctuation signal to obtain barometric pressure fluctuation features comprises: Performing feature extraction of a time domain dimension on the air pressure fluctuation signal, including calculating a pulse width of the air pressure fluctuation signal based on a preset time domain judgment condition; Performing feature extraction of frequency domain dimensions on the air pressure fluctuation signal, wherein the feature extraction comprises the steps of calculating signal energy of the air pressure fluctuation signal in a preset frequency band based on a preset frequency domain judging condition; Performing feature extraction of a variation gradient dimension on the air pressure fluctuation signal, including calculating a pressure variation rate of the air pressure fluctuation signal based on a preset variation gradient determination condition; Wherein the air pressure fluctuation feature includes at least the pulse width, the signal energy, and the pressure change rate.
  4. 4. A method according to claim 3, wherein said calculating the pulse width of the air pressure fluctuation signal based on a preset time domain decision condition comprises: extracting the pressure variation and attenuation coefficient of the air pressure fluctuation signal; When the pressure variation is smaller than a preset pressure variation threshold value and the attenuation coefficient is larger than a preset attenuation coefficient threshold value, extracting a pulse starting point and a pulse ending point of the air pressure fluctuation signal; a pulse width of the air pressure fluctuation signal is calculated based on the pulse start point and the pulse end point.
  5. 5. The method of claim 3, wherein calculating the signal energy of the air pressure fluctuation signal within a predetermined frequency band based on a predetermined frequency domain decision condition comprises: the energy duty ratio parameter of the air pressure fluctuation signal is obtained based on the signal energy; calculating the standard deviation of the frequency distribution of the air pressure fluctuation signal in the preset frequency band, and obtaining the frequency stability parameter of the air pressure fluctuation signal based on the standard deviation of the frequency distribution; and outputting the signal energy when the energy duty ratio parameter is larger than a preset energy duty ratio threshold and the frequency stability parameter is smaller than a preset frequency stability threshold.
  6. 6. The method of claim 5, wherein said deriving an energy duty cycle parameter of said air pressure fluctuation signal based on said signal energy comprises: calculating the total signal energy of the air pressure fluctuation signal in the full frequency band; and obtaining an energy duty ratio parameter of the air pressure fluctuation signal based on the signal energy and the total signal energy.
  7. 7. The method according to claim 3, wherein calculating the pressure change rate of the air pressure fluctuation signal based on a preset change gradient determination condition includes: Calculating the attenuation slope and the peak time of the air pressure fluctuation signal; and when the attenuation slope is larger than a preset attenuation slope threshold value and the peak time is smaller than a preset peak time threshold value, calculating the pressure change rate of the air pressure fluctuation signal.
  8. 8. A method according to claim 3, wherein said performing a cooking action decision based on said air pressure fluctuation feature comprises: when the pulse width is greater than a first threshold, determining a first cooking action; Determining a second cooking action when the signal energy is greater than a second threshold; and when the pressure change rate is greater than a third threshold value, determining a third cooking action.
  9. 9. The method of claim 8, wherein the generating the corresponding automatic adjustment instruction based on the type of cooking action comprises: establishing a mapping relation between the type of the cooking action and the original adjusting instruction; Based on the mapping relationship, corresponding original adjustment instructions are automatically matched for the first cooking action, the second cooking action or the third cooking action.
  10. 10. An intelligent range hood, characterized by comprising: the sensor is arranged in the cooking area and is used for acquiring an air pressure fluctuation signal in the cooking area; an intelligent regulation module for implementing the steps of the method of any one of claims 1 to 9 based on the acquired air pressure fluctuation signal.

Description

Automatic adjusting method of intelligent range hood and intelligent range hood Technical Field The application relates to the field of automatic adjustment of intelligent range hoods, in particular to an automatic adjustment method of an intelligent range hood and the intelligent range hood. Background The range hood is core electrical equipment in a cooking environment, and can timely remove oil smoke and steam generated in a cooking process so as to ensure indoor air quality and user health. With the development of technology, the user's demand for range hoods has turned from basic functions to an intelligent experience, which is expected to be able to automatically identify specific cooking actions occurring in different cooking phases and to accurately and rapidly adjust the fan air volume based on the identified action type. The existing automatic adjustment method generally detects macroscopic parameters in a cooking scene and automatically adjusts the intelligent range hood based on the macroscopic parameters. However, there is a significant delay in its automatic adjustment, since the change in macroscopic parameters generally lags behind the cooking operation itself. This also makes it impossible to effectively distinguish between the physical features corresponding to different cooking actions, thus identifying misalignments for a particular cooking action. Therefore, the existing method is poor in real-time performance and control accuracy of automatic adjustment. Aiming at the technical problem that the existing automatic adjusting method cannot accurately sense the change of aerodynamic parameters in a cooking area, thereby causing the poor automatic adjusting accuracy of the intelligent range hood, no effective solution is proposed at present. Disclosure of Invention The embodiment of the application provides an intelligent automatic adjusting method of a range hood and the intelligent range hood, which are used for solving the technical problem that the existing automatic adjusting method cannot accurately sense the change of aerodynamic parameters in a cooking area, so that the automatic adjusting accuracy of the intelligent range hood is poor. In a first aspect, in an embodiment of the present application, there is provided an automatic adjustment method for an intelligent range hood, including the steps of: Collecting an air pressure fluctuation signal in a cooking area; Performing feature extraction of at least a time domain dimension, a frequency domain dimension and a variation gradient dimension on the air pressure fluctuation signal to obtain air pressure fluctuation features; determining a type of cooking action based on the air pressure fluctuation feature; And generating a corresponding automatic adjustment instruction based on the type of the cooking action. In some of these embodiments, the acquiring the air pressure fluctuation signal in the cooking area includes: defining the cooking area; collecting an original air pressure signal in the cooking area; and performing filtering processing on the original air pressure signal to obtain the air pressure fluctuation signal. In some of these embodiments, the performing feature extraction on the air pressure fluctuation signal in at least a time domain dimension, a frequency domain dimension, and a varying gradient dimension to obtain an air pressure fluctuation feature includes: Performing feature extraction of a time domain dimension on the air pressure fluctuation signal, including calculating a pulse width of the air pressure fluctuation signal based on a preset time domain judgment condition; Performing feature extraction of frequency domain dimensions on the air pressure fluctuation signal, wherein the feature extraction comprises the steps of calculating signal energy of the air pressure fluctuation signal in a preset frequency band based on a preset frequency domain judging condition; Performing feature extraction of a variation gradient dimension on the air pressure fluctuation signal, including calculating a pressure variation rate of the air pressure fluctuation signal based on a preset variation gradient determination condition; Wherein the air pressure fluctuation feature includes at least the pulse width, the signal energy, and the pressure change rate. In some further embodiments, the calculating the pulse width of the air pressure fluctuation signal based on a preset time domain decision condition includes: extracting the pressure variation and attenuation coefficient of the air pressure fluctuation signal; When the pressure variation is smaller than a preset pressure variation threshold value and the attenuation coefficient is larger than a preset attenuation coefficient threshold value, extracting a pulse starting point and a pulse ending point of the air pressure fluctuation signal; a pulse width of the air pressure fluctuation signal is calculated based on the pulse start point and the pulse end point. In some fur