Air quality detection method and intelligent control method of range hood

Abstract

The application relates to an air quality detection method and an intelligent control method of a range hood. The air quality detection method comprises the following steps: initializing an air quality sensor and a temperature sensor; dynamically loading a voltage to the air quality sensor to collect resistance data corresponding to a to-be-identified gas at a characteristic voltage point; reading a current temperature detected by the temperature sensor and performing temperature compensation on the resistance data collected by the air quality sensor to calculate a standard resistance value corresponding to the to-be-identified gas at the characteristic voltage point; calculating characteristic spectrum values of each characteristic voltage point based on the standard resistance value through a characteristic spectrum value model; determining a main pollutant type based on the characteristic spectrum values of each characteristic voltage point; and loading a characteristic response voltage corresponding to the main pollutant type to the air quality sensor based on the determined main pollutant type and collecting a real-time resistance and a real-time temperature to calculate a pollutant concentration.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent kitchens, in particular to an air quality detection method and an intelligent control method of a range hood. BACKGROUND

[0002] With the improvement of people's living standards and the enhancement of health awareness, the influence of kitchen air quality on human health is increasingly concerned. As a key appliance for removing oil fume in the kitchen, the function of the range hood is no longer limited to simply sucking and exhausting oil fume. More and more intelligent range hoods begin to integrate air monitoring functions, such as being equipped with air butler systems, to realize the monitoring of TVOC (total volatile organic compounds), PM2.5 and other pollutants and other odors in the kitchen environment, and automatically adjust the operating state of the range hood to meet the user's demand for a healthy kitchen environment and create a healthier and more comfortable cooking environment. However, the existing air monitoring solutions of the range hood still have many technical defects to be solved:

[0003] Firstly, in terms of sensor function: at present, such air sensors on the market are mostly single-function sensors, which can only detect a certain type of main pollutants and cannot effectively distinguish multiple specific pollutants in the kitchen environment that users are highly concerned about. For example, a common TVOC (total volatile organic compound) sensor can only detect the total amount of volatile organic compounds in the environment, but cannot distinguish from the detection results whether the current main pollutant is oil fume, formaldehyde or gas leakage, etc. Moreover, in actual cooking scenarios, the type of main pollutants will change with different cooking scenarios. Since the single-function sensor has high sensitivity to only one type of pollutant, if the type of main pollutant in the air changes, it cannot identify the new main pollutant or the change. This single detection capability makes it impossible for the user to obtain accurate pollutant information and thus to adjust the air quality adjustment mode in a targeted manner, such as changing the air volume of the range hood or opening the fresh air system, etc.

[0004] Secondly, even if a sensor or sensor array that can respond to multiple gases is used, the back-end identification method usually relies on "preset fixed response mode or threshold comparison", which leads to the fact that this method can only effectively identify the concentration of the to-be-detected gas reaching a certain level or showing "fingerprint" characteristics significantly different from other gases. However, in the complex environment of the kitchen, multiple pollutant gases (such as oil fume, aldehyde or gas, etc.) often "coexist and mix", and their combined effects can easily cause the response mode of the sensor to overlap or distort, significantly reducing the identification accuracy. In addition, this identification mechanism relying on high concentration or obvious characteristics also leads to a lag in system response, making the control action of the range hood not timely enough, affecting the user experience and health protection effect.

[0005] Finally, in terms of cost and practicability, the existing solutions have contradictions and limitations: sensors or arrays with certain multi-gas recognition capabilities are usually high in cost; more importantly, in the harsh environment of kitchens with heavy oil fume, large temperature and humidity changes, the sensors are easily affected by factors such as oil pollution covering and high temperature drift, resulting in shortened service life, reduced detection accuracy, and the need for frequent maintenance or replacement, which increases the user's use cost. While low-cost single-function sensors may have more cost advantages, the fundamental defect of their single function and inability to distinguish the main pollutants in different cooking scenarios still exists. The above makes it difficult for existing solutions to meet the dual needs of accurate monitoring and active protection. SUMMARY

[0006] In view of the above prior art status, an air quality detection method and an intelligent control method of a range hood are provided, which can realize accurate identification and dynamic particle intelligent capture of the main pollutant gas in different cooking scenarios.

[0007] According to an aspect of the present application, the present application provides an air quality detection method, comprising the steps of:

[0008] initializing an air quality sensor and a temperature sensor; dynamically loading a voltage to the air quality sensor to collect resistance data of a to-be-identified gas at a characteristic voltage point through the air quality sensor; reading a current temperature detected by the temperature sensor and performing temperature compensation on the resistance data collected by the air quality sensor to calculate a standard resistance value of the to-be-identified gas at the characteristic voltage point; calculating characteristic spectrum values of each characteristic voltage point based on the standard resistance value through a characteristic spectrum value model; determining a main pollutant type based on the characteristic spectrum values of each characteristic voltage point; and loading a characteristic response voltage corresponding to the main pollutant type to the air quality sensor based on the determined main pollutant type, and collecting a real-time resistance and a real-time temperature to calculate a pollutant concentration.

[0009] In an embodiment of the present application, the step of initializing the air quality sensor and the temperature sensor comprises the steps of:

[0010] preheating the air quality sensor; initializing voltage scanning of the air quality sensor; and initializing configuration of the temperature sensor.

[0011] In an embodiment of the present application, in the step of dynamically loading a voltage to the air quality sensor to collect resistance data of a to-be-identified gas at a characteristic voltage point through the air quality sensor:

[0012] a dynamic step voltage or a dynamic loading of multiple fixed characteristic voltages is used to load the characteristic voltage point V i , and collect the resistance data of the to-be-identified gas at the loaded characteristic voltage point Vi The corresponding resistance under the i-th characteristic voltage point; wherein, i = 1, 2, …, n; and V1< V2< …< Vn. n .

[0013] In an embodiment of the present application, in the step of reading the current temperature detected by the temperature sensor and temperature-compensating the resistance data collected by the air quality sensor to calculate the standard resistance value of the to-be-identified gas corresponding to the characteristic voltage point:

[0014] The standard resistance value of the to-be-identified gas corresponding to each characteristic voltage point is calculated by a temperature compensation model; wherein the temperature compensation model is:

[0015] ; wherein is the standard resistance value after temperature compensation calibration under the characteristic voltage point V i , R0 is the resistance of clean air, is the resistance value collected by the air quality sensor under the characteristic voltage point V i , β is a material constant, T0 is a standard temperature, and T is the current temperature detected by the temperature sensor. Vi

[0016] In an embodiment of the present application, in the step of calculating the characteristic spectrum value of each characteristic voltage point based on the standard resistance value by a characteristic spectrum value model, the characteristic spectrum value model is:

[0017] ; wherein is the characteristic spectrum value under the characteristic voltage point V i , R0 is the resistance of clean air, is the standard resistance value after temperature compensation calibration under the characteristic voltage point V i .

[0018] In an embodiment of the present application, the step of determining the main pollutant type based on the characteristic spectrum value of each characteristic voltage point comprises the steps of:

[0019] constructing a feature vector based on the characteristic spectrum value of each characteristic voltage point; calculating the vector space distance of each type of gas by a classification decision model based on the constructed feature vector; and selecting the minimum value from the vector space distance of each type of gas to determine the gas type corresponding to the minimum value as the main pollutant type;

[0020] wherein the constructed feature vector is: ; wherein, is the constructed feature vector, S V1 is the characteristic spectrum value under the characteristic voltage point V1, S V2 is the characteristic spectrum value under the characteristic voltage point V2, and S​Vn characteristic spectrum value at the characteristic voltage point V n characteristic spectrum value at the characteristic voltage point V

[0021] wherein the classification decision model is:

[0022] , and i≥k; wherein D k is the vector space distance of the kth gas; is the constructed characteristic vector; is the standard vector of the kth gas; S Vi characteristic spectrum value at the characteristic voltage point V i characteristic spectrum value at the characteristic voltage point V k,i is the standard spectrum value of the kth gas at the characteristic voltage point V i characteristic voltage point V

[0023] In an embodiment of the present application, the step of determining the main pollutant type based on the characteristic spectrum value at each characteristic voltage point comprises the steps of:

[0024] comparing the size relationship between the characteristic spectrum values at each characteristic voltage point to obtain a characteristic spectrum value comparison relationship; constructing a matching relationship between the characteristic spectrum value at each voltage point and the main pollutant type; and classifying the main pollutant type of the gas to be identified based on the characteristic spectrum value comparison relationship and the constructed matching relationship.

[0025] In an embodiment of the present application, in the step of loading the characteristic response voltage corresponding to the main pollutant type to the air quality sensor based on the determined main pollutant type, and collecting real-time resistance and real-time temperature to calculate the pollutant concentration, the main pollutant concentration is calculated by a concentration calculation model, wherein the concentration calculation model is:

[0026] ; wherein is the main pollutant concentration, R SV is the real-time resistance collected after the characteristic response voltage V bias corresponding to the main pollutant is loaded, β is a material constant, T V is the real-time temperature collected after the characteristic response voltage V bias corresponding to the main pollutant type is loaded, T0 is a calibration standard temperature, R0 is a clean air resistance, γ is a voltage sensitivity coefficient, and ɑ is a gas sensitivity.

[0027] According to another aspect of the present application, an embodiment of the present application further provides an intelligent control method of a range hood, comprising the steps of:

[0028] The air quality detection method according to any one of the above embodiments, obtaining a main pollutant type and a main pollutant concentration; determining whether the main pollutant concentration is greater than a preset concentration threshold corresponding to the main pollutant type; in response to the main pollutant concentration being greater than the preset concentration threshold, adjusting the working gear and / or working mode of the fan; and in response to the main pollutant concentration being less than or equal to the preset concentration threshold, returning to the step of obtaining the main pollutant type and the main pollutant concentration by the air quality detection method according to any one of the above embodiments.

[0029] In an embodiment of the present application, the step of adjusting the working gear and / or working mode of the fan in response to the main pollutant concentration being greater than the preset concentration threshold comprises the steps of:

[0030] When the main pollutant type is the pollutant generated by frying oil fume or barbecue, the fan is adjusted to high gear and / or to a boost mode; when the main pollutant type is gas leakage, the fan is adjusted to medium gear to actively exhaust air, and a signal is sent to open the door and window; when the main pollutant type is formaldehyde release, the fan is adjusted to low gear to ventilate, and is linked with a fresh air device; and when the main pollutant type is the pollutant generated by volatilization of deposited oil dirt, the fan is adjusted to low gear to ventilate, and a signal is sent to clean the deposited oil dirt.

[0031] In summary, compared with the existing design, the advantages of the present application are that: through the dynamic voltage loading mechanism, the multi-gas response characteristics of the sensor are actively excited, the detection limitations of using a single functional sensor are broken through, and the accurate identification of the main pollutant gas under different cooking scenes can be achieved; at the same time, the active voltage excitation can avoid the delay defect of passive detection. In addition, the air quality detection method of the present application can enable air purification equipment such as a range hood to actively adopt a corresponding control strategy when the main pollutant concentration is in the initial accumulation stage, the response speed is fast, and intelligent net capture of different dynamic particles such as oil fume can be effectively realized, thereby meeting the user's requirement for kitchen air quality monitoring, breaking through the passive smoke removal deficiency of the traditional range hood, and realizing intelligent active protection of the kitchen air. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 An installation schematic diagram of a range hood according to an embodiment of the present application;

[0033] Figure 2 A use scene schematic diagram of a range hood according to the above embodiment of the present application is shown;

[0034] Figure 3 A schematic diagram of a sensor assembly in a range hood according to the above embodiment of the present application is shown;

[0035] Figure 4Fig. 1 shows a schematic diagram of an air quality detection system in a range hood according to an embodiment of the present application;

[0036] Figure 5 Fig. 2 shows a flowchart of an air quality detection method according to an embodiment of the present application;

[0037] Figure 6 Fig. 3 shows a flowchart of an initialization step in the air quality detection method according to an embodiment of the present application;

[0038] Figure 7 Fig. 4 shows an example of a type determination step in the air quality detection method according to an embodiment of the present application;

[0039] Figure 8 Fig. 5 shows another example of a type determination step in the air quality detection method according to an embodiment of the present application;

[0040] Figure 9 Fig. 6 shows a flowchart of an intelligent control method of a range hood according to an embodiment of the present application;

[0041] Figure 10 Fig. 7 shows a flowchart of a fan adjustment step in the intelligent control method of a range hood according to an embodiment of the present application;

[0042] Figure 11 Fig. 8 shows an example of the intelligent control method of a range hood according to an embodiment of the present application;

[0043] Figure 12 Fig. 9 shows another example of the intelligent control method of a range hood according to an embodiment of the present application.

[0044] Main element symbol explanation:

[0045] 1. Range hood main body; 2. Fan; 3. Air quality sensor; 4. Controller; 5. Temperature sensor; 6. Installation compartment; 7. Oil-proof grille; 8. Voltage adjustable driving board; 9. Signal processor.

[0046] The above main element symbol explanation further details the present application in combination with the accompanying drawings and specific embodiments. DETAILED DESCRIPTION

[0047] In order to make the above objectives, features and advantages of the present application more clear and comprehensible, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be practiced in a variety of ways beyond the specific embodiments described herein without departing from the scope of the present application, and it is understood that similar changes in form and substitution of equivalent ones can be made by those skilled in the art without departing from the spirit and scope of the present application, and therefore the present application is not limited to the specific embodiments disclosed below.

[0048] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0049] In addition, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined with "first", "second", etc. can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, such as two, three, etc., unless otherwise explicitly specified and limited.

[0050] In the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting", "fixing" and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements, unless otherwise explicitly limited. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0051] It should be noted that when an element is referred to as "fixed to" or "disposed on" another element, it can be directly on the other element or there can be a mediating element. When an element is referred to as "connected to" another element, it can be directly connected to the other element or there can be a mediating element. The terms "vertical", "horizontal", "up", "down", "left", "right" and similar expressions used herein are for illustrative purposes only and are not the only implementation.

[0052] Considering that the existing solutions are difficult to meet the dual needs of accurate monitoring and active protection, the application creatively provides an air purification device, an air quality detection method, and an intelligent control method of a range hood, which can realize accurate identification and dynamic particle intelligent capture of main pollutant gas in different cooking scenes. It can be understood that the air purification device mentioned in the application can be implemented as a range hood, an air purifier, or a fresh air system, etc. electrical equipment with air purification, ventilation, and other functions. In order to facilitate the understanding of the scheme of the application, the following will take the range hood as an example to display and explain the related technical solutions.

[0053] Specifically, as shown in Figures 1 to 4 One embodiment of the application provides a range hood, which can include a range hood body 1, a fan 2 arranged on the range hood body 1, an air quality sensor 3 mounted on the range hood body 1 and having different response characteristics to different types of gas, a controller 4 communicatively connected to the fan 2 and the air quality sensor 3, and a temperature sensor 5 arranged on the range hood body 1 and communicatively connected to the controller 4. The controller 4 can receive the output signal of the air quality sensor 3 and the current temperature information detected by the temperature sensor 5 to convert the resistance measured at the current temperature into the resistance at the standard temperature.

[0054] More specifically, as shown in Figure 2 and Figure 3 The range hood further includes a mounting bin 6 arranged on the outer wall of the range hood body 1 and an oil-proof screen or oil-proof grille 7 mounted at the opening of the mounting bin 6; the air quality sensor 3 and the temperature sensor 5 are both mounted inside the mounting bin 6 to form a sensor assembly, so as to block oil particles through the oil-proof screen or oil-proof grille 7, avoid contamination of the sensor, improve detection accuracy and prolong the service life of the sensor.

[0055] It is worth noting that the aperture or slit width of the oil-proof screen or oil-proof grille 7 mentioned in the application is between 0.5mm and 3mm, so as to ensure the smooth entry of gas into the mounting bin 6 while blocking large oil particles. Preferably, the oil-proof screen or oil-proof grille 7 has an outer large and inner small gas acceleration channel.

[0056] In particular, the air quality sensor 3 is implemented as a MOS sensor using SnO2-based semiconductor, which has different response characteristics to different types of gas; for example, under voltage driving, it has different resistance response curves for different types of gas. In addition, the temperature sensor 5 can be mounted in a patch type with an accuracy of ±0.5℃. It can be understood that the temperature sensor 5 mentioned in the application is used for temperature compensation, so that the controller 4 converts the resistance measured at the current temperature into the resistance at the standard temperature.

[0057] Optionally, as shown in Figure 4 The range hood further comprises a voltage-adjustable driving board 8 and a signal processor 9; the voltage-adjustable driving board 8 is in electrical signal connection with the air quality sensor 3, the air quality sensor 3 and the temperature sensor 5 are both in electrical signal connection with the signal processor 9, and the voltage-adjustable driving board 8 and the signal processor 9 are both in electrical signal connection with the controller 4 to form an air quality detection system. In this way, the voltage-adjustable driving board 8 can use dynamic bias modulation technology to apply a periodic variable bias voltage between 0.8V and 5V to the air quality sensor 3, so that the air quality sensor 3 realizes multi-gas identification of a single sensor by using the selective response characteristics of metal oxide semiconductors at different voltages; at the same time, the output signals of the air quality sensor 3 and the temperature sensor 5 are first processed by the signal processor 9 and then read by the controller 4; and then the controller 4 classifies and decides the to-be-detected gas according to the read signals, and then controls the working gear or speed of the fan 2 accordingly.

[0058] It is worth mentioning that, according to another aspect of the present application, one embodiment of the present application further provides an air quality detection method which can use feature spectrum values of respective characteristic voltage points to construct a feature vector, and use the feature vector to match a to-be-detected gas to obtain the most matched corresponding gas type.

[0059] Specifically, as shown in Figure 5 The air quality detection method can comprise the following steps:

[0060] S110: initializing an air quality sensor and a temperature sensor;

[0061] S120: dynamically loading a voltage to the air quality sensor to collect resistance data of a to-be-identified gas corresponding to a characteristic voltage point by the air quality sensor;

[0062] S130: reading a current temperature detected by the temperature sensor, and temperature-compensating the resistance data collected by the air quality sensor to calculate a standard resistance value of the to-be-identified gas corresponding to the characteristic voltage point;

[0063] S140: calculating feature spectrum values of respective characteristic voltage points by a feature spectrum value model based on the standard resistance value; and

[0064] S150: determining a main pollutant type based on the feature spectrum values of respective characteristic voltage points.

[0065] More specifically, as shown in Figure 5 The air quality detection method can further comprise the following steps:

[0066] S160: based on the determined main pollutant type, loading a characteristic response voltage corresponding to the main pollutant type to the air quality sensor, and collecting a real-time resistance and a real-time temperature, to calculate a pollutant concentration.

[0067] It is worth noting that, as shown in Figure 6 , step S110 in the air quality detection method of the present application can include steps of:

[0068] S111: preheating the air quality sensor;

[0069] S112: initializing a voltage scan of the air quality sensor; and,

[0070] S113: initializing a configuration of the temperature sensor.

[0071] It can be understood that in step S111: it is determined whether the preheating time of the air quality sensor reaches a preheating threshold value such as 90s, if yes, then step S112 is entered; if no, the air quality sensor continues to be preheated.

[0072] Exemplarily, in one example of the present application, step S120 of the air quality detection method: can load characteristic voltage points V i in a dynamic step voltage manner, and collect resistances corresponding to the loaded characteristic voltage points V i of the to-be-identified gas; wherein i=1, 2, …, n; and V1 n < V2 i i SVi n It can be understood that the starting voltage and the step voltage mentioned in the present application are not limited to the above examples.

[0073] In addition, in another example of the present application, step S120 of the air quality detection method: can also load characteristic voltage points V i in a dynamic manner of loading multiple fixed characteristic voltages, and collect resistances R i corresponding to the loaded characteristic voltage points V n of the to-be-identified gas; wherein i=1, 2, …, n; and V1 i < V2 i SVi n It can be understood that the starting voltage and the step voltage mentioned in the present application are not limited to the above examples.For example, according to the common gas type in the kitchen, five characteristic voltage points V1=1.8V, V2=2.3V, V3=3.0V, V4=3.8V, and V5=4.5V can be selected for loading, and the dwell time of each characteristic voltage point can be set to 200ms. It can be understood that, compared with the step voltage loading mode, the fixed characteristic voltage loading mode only needs to select a specific voltage point for selective excitation, which is beneficial to improve the response speed. In addition, the characteristic voltage points mentioned in the present application can also be other values, and the above are only examples, which will not be described here.

[0074] It is worth noting that the above two voltage scanning modes are different from the passive detection in the prior art, that is, the present application adopts an active dynamic loading voltage point mode for scanning to construct a resistance response curve, which is beneficial to ensure the timeliness of gas detection.

[0075] According to the above embodiment of the present application, in step S130 of the air quality detection method: the standard resistance value of the to-be-identified gas at each characteristic voltage point can be calculated by a temperature compensation model; wherein the temperature compensation model can be but not limited to implemented as:

[0076] ; wherein is the standard resistance value after temperature compensation calibration at the characteristic voltage point V i , is the resistance value collected by the air quality sensor at the characteristic voltage point V i , β is a material constant, T0 is a standard calibration temperature, and T Vi is the current temperature detected by the temperature sensor. It can be understood that the unit of temperature in the temperature compensation model mentioned in the present application is Kelvin K. For example, the standard calibration temperature T0 can be but not limited to set to 298K.

[0077] Optionally, in step S140 of the air quality detection method: the characteristic spectrum value model is implemented as:

[0078] ; wherein is the characteristic spectrum value at the characteristic voltage point V i , is the standard resistance value after temperature compensation calibration at the characteristic voltage point V i .

[0079] It is worth noting that in step S150 of the air quality detection method: the main pollutant type can be determined by calculating the vector space distance and finding the minimum value of the vector space distance; or the main pollutant type can also be determined by directly comparing the size relationship of the characteristic spectrum values of each characteristic voltage point and determining the matching relationship.

[0080] Exemplarily, in one example of the present application, as shown in the figure, Figure 7 step S150 of the air quality detection method can include the steps of:

[0081] S151: constructing a feature vector based on the characteristic spectrum values of each characteristic voltage point;

[0082] S152: calculating the vector space distance of each type of gas by a classification decision model based on the constructed feature vector; and,

[0083] S153: selecting the minimum value from the vector space distance of each type of gas to determine the gas type corresponding to the minimum value as the main pollutant type.

[0084] Optionally, in step S151: the constructed feature vector is implemented as:

[0085] wherein is the constructed feature vector, S V1 is the characteristic spectrum value under the characteristic voltage point V1, S V2 is the characteristic spectrum value under the characteristic voltage point V2, S Vn is the characteristic spectrum value under the characteristic voltage point V n .

[0086] Optionally, in step S152: the classification decision model is implemented as:

[0087] , and i≥k; wherein D k is the vector space distance of the kth type of gas; is the constructed feature vector; is the standard vector of the kth type of gas; S Vi is the characteristic spectrum value under the characteristic voltage point V i ; M k,i is the standard spectrum value of the kth type of gas under the characteristic voltage point V i , which can be obtained by placing the air quality sensor in the kth type of standard gas.

[0088] It is worth noting that in another example of the present application, as shown in the figure, Figure 8 step S150 of the air quality detection method can also include the steps of:

[0089] S151': compare the size relationship between the characteristic spectrum values of each characteristic voltage point to obtain a characteristic spectrum value comparison relationship;

[0090] S152': construct a matching relationship between the characteristic spectrum values of each voltage point and the main pollutant type; and,

[0091] S153': based on the characteristic spectrum value comparison relationship and the constructed matching relationship, classify the main pollutant type of the to-be-identified gas.

[0092] For example, five characteristic voltage points V1=1.8V, V2=2.3V, V3=3.0V, V4=3.8V, and V5=4.5V are selected for loading, and the characteristic spectrum values at the characteristic voltage points are calculated as follows: V1 V2 V3 V4 V5 The matching relationship between the characteristic spectrum values of each voltage point and the main pollutant type is constructed as follows:

[0093] If S V3 > S V2 > S V4 , the main pollutant type is frying oil fume;

[0094] If S V5 > S V1 or S V3 ≈0, the main pollutant type is gas leakage;

[0095] If S V2 > S V3 or the gradient is slowly changing, the main pollutant type is formaldehyde release; here, the slowly changing gradient refers to the characteristic spectrum value S V2 at the characteristic voltage point V2, which does not change much relative to the values corresponding to other characteristic voltage points, which is consistent with the characteristics of slow release of formaldehyde;

[0096] If S V4 / S V3 > 1.5, the main pollutant type is pollution generated by barbecue; and,

[0097] If S V1 > S V2 , S V1 > S V3 , S V1 > S V4 , or S V1 > S V5 , the main pollutant type is pollution generated by volatilization of deposited oil dirt.

[0098] ​​​​It is worth noting that in step S160 of the air quality detection method of the present application, the main pollutant concentration is calculated by a concentration calculation model, which can be but is not limited to being implemented as:

[0099] ; wherein is the main pollutant concentration, R SV is the real-time resistance collected after the characteristic response voltage V bias corresponding to the main pollutant type is loaded, β is a material constant, T V is the real-time temperature collected after the characteristic response voltage V bias corresponding to the main pollutant type is loaded, T0 is a calibration standard temperature, R0 is a clean air resistance, γ is a voltage sensitivity coefficient, and ɑ is a gas sensitivity.

[0100] It can be understood that the main pollutant concentration mentioned in the present application is usually between 1 ppm and 500 ppm; the real-time resistance R SV may be collected by the above-mentioned air quality sensor after the characteristic response voltage V bias corresponding to the main pollutant type is loaded, and its unit is Ω; the material constant β can be calibrated by experiment, and its unit is K; the real-time temperature T V may be collected by the above-mentioned temperature sensor after the characteristic response voltage V bias corresponding to the main pollutant type is loaded, and its unit is K; the calibration standard temperature T0 is preset during experimental calibration and is used for temperature compensation, and is usually between 290 K and 350 K; the clean air resistance R0 can be calibrated by experiment, such as 10 KΩ; the voltage sensitivity coefficient γ can be calibrated by experiment, such as 0.25 V -1 ; the characteristic response voltage V bias corresponding to the main pollutant is a bias voltage, which is usually between 0.8 V and 5 V; the gas sensitivity ɑ can be calibrated by experiment, for example, the gas sensitivity of ethanol is 0.08 ppm -1 .

[0101] According to another aspect of the present application, as shown in Figure 9 , one embodiment of the present application further provides an intelligent control method of a range hood, which can include the steps of:

[0102] S210: obtaining the main pollutant type and the main pollutant concentration by the above-mentioned air quality detection method;

[0103] S220: determining whether the main pollutant concentration is greater than a preset concentration threshold corresponding to the main pollutant type;

[0104] S230: in response to the main pollutant concentration being greater than the preset concentration threshold, adjusting the working gear and / or working mode of the fan; and

[0105] S240: in response to the main pollutant concentration being less than or equal to the preset concentration threshold, returning to the step of obtaining the main pollutant type and the main pollutant concentration by the air quality detection method.

[0106] It is worth noting that the preset concentration threshold mentioned in the present application can be set according to experiments and health protection based on various main pollutant types.

[0107] Optionally, as shown in the present application, the intelligent control method of the range hood comprises the following steps of step S230: Figure 10

[0108] S231: when the main pollutant type is the pollutant generated by frying oil fume or barbecue, adjusting the fan to high gear and / or adjusting the fan to the boost mode;

[0109] S232: when the main pollutant type is gas leakage, adjusting the fan to medium gear to actively exhaust air, and issuing a reminder signal to open the door and window;

[0110] S233: when the main pollutant type is formaldehyde release, adjusting the fan to low gear to ventilate, and cooperating with fresh air equipment; and,

[0111] S234: when the main pollutant type is the pollutant generated by volatilization of deposited oil dirt, adjusting the fan to low gear to ventilate, and issuing a reminder signal to clean the deposited oil dirt.

[0112] It is worth noting that the fan gear and the boost mode are as follows:

[0113] The low gear mentioned in the present application refers to a gear with low speed, such as a speed within 500 RPM, mainly for low-noise ventilation; the medium gear refers to a gear with moderate speed, such as a speed between 500 RPM and 1000 RPM, mainly for non-oil fume cooking ventilation, balancing noise and ventilation efficiency; the high gear refers to a gear with high speed, such as a speed between 1000 RPM and 1500 RPM, mainly for frying and stir-frying oil fume cooking suction and exhaust, and is biased towards oil fume suction; the boost mode refers to a gear with higher speed, such as a speed above 1500 RPM, mainly for the case of short-time sudden large oil fume in the cooking process (such as the moment of putting food into the pot or the process of stir-frying) in the environment with back pressure resistance such as public flue, sacrificing noise to increase speed to improve oil fume exhaust capacity.

[0114] Exemplarily, in the first example of the present application, as shown in Figure 11 ​As shown, the specific process of the intelligent control method for the range hood is as follows: 1) System startup; 2) Sensor preheating; 3) Determine if preheating is complete. If yes, proceed to the next step; otherwise, continue preheating; 4) Initialize voltage scan; 5) Acquire the resistance R of the gas to be identified at the characteristic voltage point. SVi 6) Read the temperature; 7) Perform temperature compensation to obtain the standard resistance value R. compVi 8) Calculate the feature vector; 9) Identify the pollutant with the smallest vector space distance as the primary pollutant; 10) Calculate the concentration of the primary pollutant using the concentration calculation model. ;11) Determine the concentration Is it greater than the corresponding pollutant threshold (i.e., the preset concentration threshold corresponding to the main pollutant type)? If yes, proceed to the next step; otherwise, return to step 4 above. 12) Respond to the corresponding control strategy, such as adjusting the working level and / or working mode of the fan based on the main pollutant type.

[0115] Furthermore, in the second example of this application, such as Figure 12 As shown, the specific process of the intelligent control method for the range hood is as follows: 1) System startup; 2) Sensor preheating; 3) Determine if preheating is complete. If yes, proceed to the next step; otherwise, continue preheating; 4) Initialize voltage scan; 5) Acquire the resistance R of the gas to be identified at the characteristic voltage point. SVi 6) Read the temperature; 7) Perform temperature compensation on each voltage point to obtain the standard resistance value R. compVi 8) Calculate the characteristic spectrum values ​​at each voltage point. 9) Compare the characteristic spectral values ​​S at each voltage point. Vi 10) Determine the type of the main pollutant; 11) Calculate the concentration of the main pollutant using a concentration calculation model. ;11) Determine the concentration Is it greater than the corresponding pollutant threshold (i.e., the preset concentration threshold corresponding to the main pollutant type)? If yes, proceed to the next step; otherwise, return to step 4 above. 12) Respond to the corresponding control strategy, such as adjusting the working level and / or working mode of the fan based on the main pollutant type.

[0116] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0117] The above embodiments only express several implementation ways of the present application, and the description is specific and detailed, but it should not be understood as a limitation to the patent scope. It should be pointed out that, for ordinary skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A method of air quality detection, characterized in that, The method comprises the steps of: initializing an air quality sensor and a temperature sensor; dynamically loading a voltage to the air quality sensor to collect resistance data of a to-be-identified gas at a characteristic voltage point through the air quality sensor; reading a current temperature detected through the temperature sensor and temperature-compensating the resistance data collected through the air quality sensor to calculate a standard resistance value of the to-be-identified gas at the characteristic voltage point; calculating characteristic spectrum values of each characteristic voltage point through a characteristic spectrum value model based on the standard resistance value; determining a main pollutant type based on the characteristic spectrum values of each characteristic voltage point; and loading a characteristic response voltage corresponding to the main pollutant type to the air quality sensor based on the determined main pollutant type and collecting a real-time resistance and a real-time temperature to calculate a pollutant concentration. The step of initializing the air quality sensor and the temperature sensor comprises the steps of:

2. The air quality detection method of claim 1, wherein, preheating the air quality sensor; initializing a voltage scanning of the air quality sensor; and initializing a configuration of the temperature sensor. In the step of dynamically loading the voltage to the air quality sensor to collect the resistance data of the to-be-identified gas at the characteristic voltage point through the air quality sensor:

3. The method of claim 1, wherein, In the step of reading the current temperature detected through the temperature sensor and temperature-compensating the resistance data collected through the air quality sensor to calculate the standard resistance value of the to-be-identified gas at the characteristic voltage point: Adopt the dynamic step voltage or dynamic load multiple fixed characteristic voltage mode to load characteristic voltage point V i And collect the to-be-identified gas at the loaded characteristic voltage point V i Corresponding resistance; wherein, i=1, 2, …, n; and V1 n .

4. The air quality detection method of any one of claims 1 to 3, wherein, the standard resistance value of the to-be-identified gas at each characteristic voltage point is calculated through a temperature compensation model; wherein the temperature compensation model is: In the step of calculating the characteristic spectrum values of each characteristic voltage point through the characteristic spectrum value model based on the standard resistance value: ; wherein is the standard resistance value after temperature compensation calibration at the characteristic voltage point V i , V is the resistance value collected by the air quality sensor at the characteristic voltage point V i , β is a material constant, T0 is the calibration standard temperature, and T Vi is the current temperature detected by the temperature sensor.

5. The air quality detection method of any one of claims 1 to 3, wherein, the step of determining the main pollutant type based on the characteristic spectrum values of each characteristic voltage point comprises the steps of: ; wherein is the characteristic spectral value at the characteristic voltage point V i , R0 is the clean air resistance, is the standard resistance value after temperature compensation calibration at the characteristic voltage point V i .

6. The air quality detection method of any one of claims 1 to 3, wherein, constructing a characteristic vector based on the characteristic spectrum values of each characteristic voltage point; calculating vector space distances of each type of gas through a classification decision model based on the constructed characteristic vector; and selecting a minimum value from the vector space distances of each type of gas to determine a gas type corresponding to the minimum value as the main pollutant type; wherein the classification decision model is: wherein the constructed feature vector is: ; wherein, is the constructed feature vector, S V1 is the feature spectrum value at the feature voltage point V1, S V2 is the feature spectrum value at the feature voltage point V2, S Vn is the feature spectrum value at the feature voltage point V n ; the step of determining the main pollutant type based on the characteristic spectrum values of each characteristic voltage point comprises the steps of: , and i > k; where D k is the vector space distance of the kth gas; is the constructed eigenvector; is the standard eigenvector of the kth gas; S Vi is the eigenvalue at the eigenpotential point V i ; M k,i is the standard eigenvalue of the kth gas at the eigenpotential point V i .

7. The air quality detection method of any one of claims 1-3, wherein, comparing size relationships between the characteristic spectrum values of each characteristic voltage point to obtain a characteristic spectrum value comparison relationship; constructing a matching relationship between each voltage point characteristic spectrum value and the main pollutant type; and classifying the main pollutant type of the to-be-identified gas based on the characteristic spectrum value comparison relationship and the constructed matching relationship. In the step of loading the characteristic response voltage corresponding to the main pollutant type to the air quality sensor based on the determined main pollutant type and collecting the real-time resistance and the real-time temperature to calculate the pollutant concentration, the main pollutant concentration is calculated through a concentration calculation model, wherein the concentration calculation model is: The method comprises the steps of:

8. The air quality detection method of any one of claims 1-3, wherein, obtaining a main pollutant type and a main pollutant concentration through the air quality detection method according to any one of claims 1 to 8. ; wherein is the main pollutant concentration, R SV is the real-time resistance after loading the characteristic response voltage V bias corresponding to the main pollutant, β is a material constant, T V is the real-time temperature after loading the characteristic response voltage V bias corresponding to the main pollutant type, T0 is a calibration standard temperature, R0 is a clean air resistance, γ is a voltage sensitivity coefficient, and ɑ is a gas sensitivity.

9. A method of intelligent control of a range hood, characterized in that, ​ ​ determining whether the main pollutant concentration is greater than a preset concentration threshold corresponding to the main pollutant type; adjusting the working gear and / or working mode of the fan in response to the main pollutant concentration being greater than the preset concentration threshold; and in response to the main pollutant concentration being less than or equal to the preset concentration threshold, returning to the steps of obtaining the main pollutant type and the main pollutant concentration by the air quality detection method according to any one of claims 1 to 8.

10. The intelligent control method of the range hood according to claim 9, characterized in that, The step of adjusting the working gear and / or working mode of the fan in response to the main pollutant concentration being greater than the preset concentration threshold comprises the steps of: when the main pollutant type is the pollutant generated by frying oil fume or barbecue, adjusting the fan to high gear and / or adjusting the fan to a boost mode; when the main pollutant type is gas leakage, adjusting the fan to medium gear to actively exhaust air, and issuing a reminder signal to open doors and windows; when the main pollutant type is formaldehyde release, adjusting the fan to low gear to ventilate, and cooperating with fresh air equipment; and when the main pollutant type is the pollutant generated by volatilization of deposited oil dirt, adjusting the fan to low gear to ventilate, and issuing a reminder signal to clean the deposited oil dirt.

Images