CN-121978997-A - Multi-dimensional sensing, adjusting and optimizing method and system for kitchen electric environment parameters

CN121978997ACN 121978997 ACN121978997 ACN 121978997ACN-121978997-A

Abstract

The invention provides a kitchen electric environment parameter multidimensional sensing and adjusting optimization method and system, which relate to the field of kitchen oil smoke control and comprise the steps of collecting cooking heat source temperature and behavior data, identifying cooking state characteristics, combining the relation between the rising speed of oil smoke particles and the air flow speed to generate oil smoke movement space-time prediction information, dividing a cooking area into a plurality of control blocks, adopting a gradient air pressure control strategy to form a block air flow control scheme, adjusting air flow parameters to establish a protective air field when an oil smoke diffusion trend is detected, and recording control effects to generate optimal configuration information. The invention can accurately predict the oil smoke diffusion path, realize multi-region cooperative control and improve the oil smoke trapping efficiency.

Inventors

YAO GUOXIANG
LU JIESHENG
YUE MING
YAO YUNJUN
WEN YONG
YAN GUOWEI
SHAO LINGLING
ZHANG HAINAN
MAO JIANGUO
WANG HONGXING
Gu Luorong

Assignees

宁波舜韵电子有限公司

Dates

Publication Date: 20260505
Application Date: 20251219

Claims (10)

1. The multidimensional sensing and adjusting optimizing method for the kitchen electric environment parameters is characterized by comprising the following steps: Collecting cooking heat source temperature and cooking behavior data; Identifying cooking state characteristics according to a fluctuation rule of cooking heat source temperature and a displacement track of cooking behavior, and generating space-time prediction information of oil smoke movement by combining a ratio relation between the rising speed of oil smoke particles and peripheral air flow speed; based on space-time prediction information, dividing a cooking area into a plurality of control blocks, and calculating air flow guiding parameters of each control block by adopting a gradient air pressure control strategy to form a block air flow control scheme; Collecting oil smoke movement data of each control block, and when an oil smoke diffusion trend is detected, adjusting air flow parameters of adjacent control blocks according to a block air flow control scheme to establish a protective air field; recording the control effect of the protection gas field on the oil smoke, extracting the corresponding relation between the gas flow parameters and the control effect, generating optimal block gas flow configuration information, and controlling the operation of the environment regulating equipment according to the optimal block gas flow configuration information.
2. The method of claim 1, wherein identifying cooking state characteristics based on a law of fluctuation of a cooking heat source temperature and a displacement trajectory of a cooking behavior, and generating spatiotemporal prediction information of a cooking fume movement in combination with a ratio relationship of a rising speed of a cooking fume particle to a peripheral air flow speed comprises: collecting temperature data of a cooking heat source, calculating the temperature change rate of adjacent sampling points, acquiring a temperature fluctuation curve, and determining the fluctuation rule of the temperature of the cooking heat source according to the change frequency and the peak amplitude of the temperature change rate; Acquiring space position coordinates of the cooking utensil, calculating the instantaneous speed and the instantaneous acceleration of the position coordinates, and determining a displacement track of the cooking behavior according to the combined change of the speed direction and the acceleration direction; carrying out time domain fusion on the mutation points of the fluctuation rule and the motion components of the displacement track, and identifying the cooking state characteristics based on the temperature gradient before and after the mutation points and the variation trend of the motion components; collecting peripheral airflow speed at the moment corresponding to the cooking state characteristics, and calculating the rising speed of the oil smoke particles by combining the convection effect of the temperature field to obtain the ratio relation between the rising speed of the oil smoke particles and the peripheral airflow speed; And generating space-time prediction information of the lampblack movement according to the fluctuation rule of the cooking state characteristics, the displacement track and the gradient distribution of the ratio relation in space.
3. The method of claim 1, wherein dividing the cooking area into a plurality of control blocks based on the spatiotemporal predictive information, calculating air flow direction parameters for each control block using a gradient air pressure control strategy, forming a block air flow control scheme comprises: based on space-time prediction information, dividing the cooking area into a plurality of control blocks by adopting a dynamic clustering mode, and calculating a temperature gradient and an air pressure gradient according to the residence time and the diffusion speed of the oil smoke particles in each block; Collecting oil smoke concentration data of each control block, calculating the oil smoke diffusion direction and the oil smoke diffusion rate by combining the change trend of the temperature gradient, and determining the oil smoke movement track based on the spatial distribution of the air pressure gradient; According to the oil smoke movement track, high-low pressure alternating air pressure steps are established between adjacent control blocks, the air inlet and outlet flow rate of each control block is calculated, and a pressure gradient coefficient is determined based on the ratio of the air inlet and outlet flow rate; and calculating air flow guiding parameters of each control block according to the pressure gradient coefficient, adjusting the running state of the air supply equipment to construct a directional air flow channel, adjusting the air pressure step when detecting that the oil smoke diffusion exceeds a preset diffusion range, and recording the adjusting effect of the air pressure step to form a block air flow control scheme.
4. The method of claim 1, wherein creating alternating high and low pressure air pressure steps between adjacent control blocks according to the soot motion profile, calculating the in and out air flow rate for each control block, and determining the pressure gradient coefficient based on the ratio of the in and out air flow rates comprises: Acquiring the oil smoke movement track and the position information of the adjacent control blocks, calculating the space distance between the control blocks, establishing a pressure transfer function according to the space distance, and generating a reference air pressure value and an initial pressure increment of each control block; Based on the reference air pressure value and the initial pressure increment, constructing air pressure steps with high and low pressure alternation between adjacent control blocks, calculating the pressure attenuation coefficient of the air pressure steps, and forming an initial air pressure step structure according to the pressure attenuation coefficient; Collecting the air inlet and outlet flow of each control block under the initial air pressure ladder structure, calculating the ratio of the air inlet and outlet flow, judging the air flow accumulation state of each block according to the ratio of the air inlet and outlet flow, and calculating the air flow adjustment coefficient based on the air flow accumulation state; acquiring oil smoke concentration data of each control block, calculating a pressure correction quantity by combining an air flow adjusting coefficient, and dynamically adjusting the pressure increment in the air pressure step according to the pressure correction quantity to generate an adjusted air pressure step; Based on the adjusted air pressure steps, constructing a multi-objective optimization function by taking air flow balance, system energy consumption and air flow speed as optimization targets, and solving the multi-objective optimization function to obtain a pressure gradient coefficient.
5. The method of claim 1, wherein collecting soot movement data for each control block, and adjusting airflow parameters for adjacent control blocks according to a block airflow control scheme when soot diffusion trends are detected, and establishing a protective airflow field comprises: acquiring oil smoke motion data of each control block through an oil smoke concentration sensor array, calculating concentration gradients and change rates of adjacent sampling points based on air flow guide parameters in a block air flow control scheme, establishing oil smoke motion feature vectors by combining the oil smoke motion data, and detecting oil smoke diffusion trends based on feature vector analysis; according to the block airflow control scheme, calculating an air pressure transfer coefficient based on the detected oil smoke diffusion trend, and setting the pressure value of each control block and the pressure gradient value between adjacent control blocks according to the air pressure transfer coefficient; Acquiring airflow parameters of each control block, calculating airflow field characteristics in the control block by combining the airflow guiding parameters, and generating airflow parameter adjustment amounts of adjacent control blocks based on the airflow field characteristics; And adjusting the air supply and exhaust parameters of the adjacent control blocks according to the air flow parameter adjustment quantity, updating the pressure gradient values among the blocks in real time, and resetting the pressure values and the pressure gradient values of each control block according to the adjusted air supply and exhaust parameters when the characteristics of the air flow field of the blocks exceed the preset protection values, so as to establish the protection air field.
6. The method of claim 5, wherein collecting airflow parameters for each control block, calculating airflow field characteristics within the control block in combination with the airflow direction parameters, and generating airflow parameter adjustments for adjacent control blocks based on the airflow field characteristics comprises: Acquiring air flow parameters of each control block, wherein the air flow parameters comprise wind speed data and pressure data; Determining the air flow movement direction according to the air speed data, determining a pressure change value according to the pressure data, comparing the air flow movement direction with the air flow guiding parameters to obtain air flow movement deviation, and calculating the air flow field characteristics in the control block based on the air flow movement deviation and the pressure change value; and calculating the air flow motion association degree between the adjacent control blocks based on the air flow field characteristics, determining the air supply and exhaust adjustment requirements of the adjacent control blocks according to the air flow motion association degree, and generating the air flow parameter adjustment quantity of the adjacent control blocks.
7. The method of claim 1, wherein recording the control effect of the protective gas field on the oil smoke, extracting the correspondence between the gas flow parameters and the control effect, generating the optimal block gas flow configuration information, and controlling the operation of the environmental conditioning equipment according to the optimal block gas flow configuration information comprises: Collecting oil smoke concentration data of the boundary of the protective gas field, calculating spatial distribution and time variation values of the oil smoke concentration data, determining boundary breaking points according to the spatial distribution, calculating oil smoke diffusion intensity according to the time variation values, and combining the boundary breaking points and the oil smoke diffusion intensity to generate control effect data of the protective gas field; Establishing a corresponding relation between the air flow parameters of each control block and the control effect data, extracting an air flow parameter combination when the control effect data is optimal, and generating optimal block air flow configuration information; and adjusting the running state of the environment adjusting equipment according to the optimal block airflow configuration information, collecting the adjusted control effect data, and updating the airflow configuration information when the control effect data is reduced.
8. A system for multidimensional sensing and conditioning optimization of kitchen electrical environmental parameters, for implementing the method according to any of the previous claims 1-7, characterized in that it comprises: a first unit for collecting cooking heat source temperature and cooking behavior data; The second unit is used for identifying cooking state characteristics according to the fluctuation rule of the temperature of the cooking heat source and the displacement track of the cooking behavior, and generating space-time prediction information of the oil smoke movement by combining the ratio relation of the rising speed of the oil smoke particles and the peripheral air flow speed; A third unit for dividing the cooking area into a plurality of control blocks based on the space-time prediction information, and calculating air flow guiding parameters of each control block by adopting a gradient air pressure control strategy to form a block air flow control scheme; a fourth unit for collecting the oil smoke movement data of each control block, when detecting the oil smoke diffusion trend, adjusting the air flow parameters of the adjacent control blocks according to the block air flow control scheme, and establishing a protective air field; and the fifth unit is used for recording the control effect of the protection gas field on the oil smoke, extracting the corresponding relation between the gas flow parameters and the control effect, generating optimal block gas flow configuration information, and controlling the operation of the environment regulating equipment according to the optimal block gas flow configuration information.
9. An electronic device, comprising: A processor; A memory for storing processor-executable instructions; Wherein the processor is configured to invoke the instructions stored in the memory to perform the method of any of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 7.

Description

Multi-dimensional sensing, adjusting and optimizing method and system for kitchen electric environment parameters Technical Field The invention relates to a kitchen fume control technology, in particular to a kitchen electric environment parameter multidimensional sensing and adjusting optimization method and system. Background Along with the improvement of the living standard of people, the health and the comfort of the kitchen environment are more and more emphasized. The oil smoke generated in the cooking process not only can influence the indoor air quality, but also can harm the health of human bodies. Traditional kitchen fume extractor mainly relies on the mode of fan suction to handle the oil smoke, but this kind of mode often has the low, the noise big scheduling problem of efficiency. In recent years, intelligent kitchen electric technology is rapidly developed, and multi-disciplinary knowledge such as sensor technology, airflow dynamics, artificial intelligence and the like is applied to kitchen environment management in a fusion manner, so that the intelligent kitchen electric technology becomes an important trend of industry development. The intelligent range hood in the current market has begun to adopt technologies such as temperature sensing and wind speed adjustment, and attempts to realize accurate trapping and treatment of oil smoke. However, the prior art lacks accurate perceptibility of dynamic characteristics of a cooking process, most devices judge the cooking state only through single or limited parameters, and the time point and the spatial distribution characteristics of oil smoke generation cannot be accurately predicted, so that oil smoke is not captured timely or energy is wasted. Traditional kitchen electrical equipment adopts the mode of the even suction and exhaust of full region to handle the oil smoke, has neglected the inhomogeneous of oil smoke diffusion in the kitchen space, can't implement accurate control to the oil smoke concentration difference in different regions, causes partial regional oil smoke to handle inadequately and other regional excessive problem of handling. The existing kitchen electric control system lacks an adaptive learning optimization mechanism, cannot continuously adjust and optimize a control strategy according to an actual control effect, lacks pertinence to cooking fume control under different cooking habits and different cooking environments, and is difficult to achieve optimal energy efficiency and control effect balance. Disclosure of Invention The embodiment of the invention provides a kitchen electrical environment parameter multidimensional sensing and adjusting optimization method and system, which can solve the problems in the prior art. In a first aspect of the embodiment of the present invention, a method for multidimensional sensing and adjustment optimization of kitchen electrical environmental parameters is provided, including: Collecting cooking heat source temperature and cooking behavior data; Identifying cooking state characteristics according to a fluctuation rule of cooking heat source temperature and a displacement track of cooking behavior, and generating space-time prediction information of oil smoke movement by combining a ratio relation between the rising speed of oil smoke particles and peripheral air flow speed; based on space-time prediction information, dividing a cooking area into a plurality of control blocks, and calculating air flow guiding parameters of each control block by adopting a gradient air pressure control strategy to form a block air flow control scheme; Collecting oil smoke movement data of each control block, and when an oil smoke diffusion trend is detected, adjusting air flow parameters of adjacent control blocks according to a block air flow control scheme to establish a protective air field; recording the control effect of the protection gas field on the oil smoke, extracting the corresponding relation between the gas flow parameters and the control effect, generating optimal block gas flow configuration information, and controlling the operation of the environment regulating equipment according to the optimal block gas flow configuration information. Identifying cooking state characteristics according to a fluctuation rule of cooking heat source temperature and a displacement track of cooking behaviors, and generating space-time prediction information of oil smoke movement by combining a ratio relation between the rising speed of oil smoke particles and peripheral air flow speed comprises: collecting temperature data of a cooking heat source, calculating the temperature change rate of adjacent sampling points, acquiring a temperature fluctuation curve, and determining the fluctuation rule of the temperature of the cooking heat source according to the change frequency and the peak amplitude of the temperature change rate; Acquiring space position coordinates of the cooking utensil, calculating th