CN109884049B - Harmful substance detection device capable of detecting kitchen fume - Google Patents
Harmful substance detection device capable of detecting kitchen fume Download PDFInfo
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Abstract
The utility model provides a harmful substance detection device that can detect kitchen oil smoke, be provided with be used for detecting the temperature sensing module of cooking region in, be used for detecting the particulate matter sensing module of particulate matter concentration in the cooking region oil smoke, be used for calculating the calculation module of the polycyclic aromatic hydrocarbon concentration in cooking region, be used for to the image analysis of cooking region oil smoke and obtain the image acquisition module that produces the oil smoke size and be used for detecting the VOC sensor of the volatile organic compounds concentration in cooking region in real time, temperature sensing module, particulate matter sensing module, VOC sensor and image acquisition module are connected with calculation module electricity respectively. The harmful substance detection device can detect the temperature in a cooking area of a kitchen cooking area, the oil smoke size of the cooking area, the concentration of particles in the oil smoke, the concentration of polycyclic aromatic hydrocarbon and the concentration of volatile organic compounds. The harmful substance detection device is a suspension type, standing type, integrated type or portable type harmful substance detection device. The harmful substance detection device can also carry out health grade classification according to the concentration of volatile organic compounds, the size of oil fume, the concentration of particulate matters and the concentration of polycyclic aromatic hydrocarbons, and send the classified harmful substances to external equipment.
Description
Technical Field
The invention relates to the field of kitchen oil smoke detection, in particular to a harmful substance detection device capable of detecting kitchen oil smoke.
Background
In modern life, a large amount of oil smoke is generated in the cooking process. Research shows that cooking oil fume has complex components, certain inhalation toxicity, immune toxicity and mutagenicity, and certain harm to human health. The fume gas contains various harmful matters, such as polycyclic aromatic hydrocarbon, great amount of granular matters, volatile organic matters, etc. and some polycyclic aromatic hydrocarbon has carcinogenicity, such as benzo [ alpha ] pyrene. Prolonged exposure of the user to the particles also increases the risk of lung cancer. The range hood in the prior art cannot automatically identify the concentration of harmful substances of the oil smoke in the current cooking environment.
Therefore, in order to solve the deficiencies of the prior art, it is necessary to provide a harmful substance detection device capable of detecting kitchen fumes.
Disclosure of Invention
The invention aims to provide a harmful substance detection device capable of detecting kitchen fume, which is used for avoiding the defects of the prior art. The harmful substance detection device capable of detecting kitchen oil smoke can identify the concentration of the polycyclic aromatic hydrocarbon which is the harmful substance of the oil smoke in the front cooking environment.
The above object of the present invention is achieved by the following technical measures:
the utility model provides a harmful substance detection device that can detect kitchen oil smoke is provided with the temperature sensing module that is used for detecting the interior temperature of cooking region, be arranged in detecting the particulate matter sensing module of particulate matter concentration in the cooking region oil smoke, a calculation module that is used for calculating the polycyclic aromatic hydrocarbon concentration in cooking region, an image acquisition module that is used for producing the oil smoke size to cooking region oil smoke image analysis and obtains in real time and a VOC sensor that is used for detecting the volatile organic matter concentration in cooking region, temperature sensing module, particulate matter sensing module, VOC sensor and image acquisition module are connected with calculation module electricity respectively.
The temperature sensing module senses the temperature in the cooking area to obtain a temperature signal, the obtained temperature signal is used as a temperature output signal to be transmitted to the calculating module, the particulate matter sensing assembly collects the concentration of particulate matters in the cooking area oil smoke to obtain a particulate concentration signal and transmits the particulate concentration signal to the calculating module, the VOC sensor collects the concentration of volatile organic matters in the cooking area to obtain a VOC concentration signal and transmits the VOC concentration signal to the calculating module, the image collecting module collects the cooking area oil smoke image to obtain an oil smoke output signal and transmits the oil smoke output signal to the calculating module, and the calculating module receives the temperature output signal, the oil smoke output signal, the VOC concentration signal and the particulate concentration signal respectively and then processes the oil smoke output signal, the VOC concentration signal and the particulate concentration signal to obtain the polycyclic aromatic hydrocarbon concentration of the cooking area in real time.
The harmful substance detection device of the present invention is a suspended type harmful substance detection device, a footed type harmful substance detection device, an integrated type harmful substance detection device, or a portable type harmful substance detection device.
Preferably, the particulate matter sensing assembly comprises a PM2.5 sensor, a PM10 sensor, a PM1.0 sensor, a PM0.1 sensor, a PMA sensor and a dust sensor, wherein the PM10 sensor, the PM2.5 sensor, the PM1.0 sensor, the PM0.1 sensor, the PMA sensor and the dust sensor are respectively electrically connected with the temperature sensing module, the VOC sensor, the calculation module and the image acquisition module.
And the PM10 sensor acquires the concentration of the particulate matters with equivalent diameters smaller than or equal to 10 microns in the cooking area oil smoke to obtain a PM10 concentration signal, and transmits the PM10 concentration signal to the calculation module.
The PM2.5 sensor collects the concentration of particulate matters with equivalent diameters smaller than or equal to 2.5 microns in the cooking area oil smoke to obtain a PM2.5 concentration signal, and the PM2.5 concentration signal is transmitted to the calculation module.
The PM1.0 sensor collects the concentration of particulate matters with equivalent diameters smaller than or equal to 1.0 micron in the cooking area oil smoke to obtain a PM1.0 concentration signal, and the PM1.0 concentration signal is transmitted to the calculation module.
The PM0.1 sensor collects the concentration of particulate matters with equivalent diameters smaller than or equal to 0.1 micron in the cooking area oil smoke to obtain PM0.1 concentration signals, and the PM0.1 concentration signals are transmitted to the calculation module.
And the PMA sensor acquires the concentration of particles with equivalent diameter smaller than or equal to 0.05 micron in the cooking area oil smoke to obtain a PMA concentration signal, and transmits the PMA concentration signal to the calculation module.
The dust sensor acquires the concentration of particles with equivalent diameters of 1-75 microns in the cooking area oil smoke to obtain a dust concentration signal, and the dust concentration signal is transmitted to the calculation module.
Preferably, the calculation module is constructed by mathematical modeling to obtain mathematical relations of temperature, volatile organic compound concentration, oil smoke size and particle concentration in the cooking area and polycyclic aromatic hydrocarbon concentration in harmful gas in the oil smoke.
Preferably, the calculation module is a linear calculation module, a nonlinear calculation module, an exponential calculation module, a power calculation module, a logarithmic calculation module, a neural network-like calculation module, a machine learning calculation module or a deep learning calculation module.
Preferably, the calculation module is also a calculation module for classifying the harmful substances in health grade;
the calculation module carries out health grade division according to the current volatile organic compound concentration, the oil fume size, the particulate matter concentration and the polycyclic aromatic hydrocarbon concentration to obtain a health grade signal.
Preferably, the system is further provided with a signal transmitting module for signal connection with external equipment, and the signal transmitting module is electrically connected with the computing module;
the calculation module carries out health grade division according to the current volatile organic compound concentration, the oil fume size, the particulate matter concentration and the polycyclic aromatic hydrocarbon concentration to obtain a health grade signal, the calculation module sends the health grade signal to the signal transmission module, and the signal transmission module receives the health grade signal and sends the health grade signal to external equipment.
Preferably, the signal connection is a wired signal connection;
the wired signal connection is RS232 signal connection, RS485 signal connection, USB signal connection, GPIB signal connection or CAN signal connection.
Preferably, the signal connection is a wireless signal connection.
Preferably, the wireless signal connection is a WiFi signal connection, a bluetooth signal connection, an NFC signal connection, or a ZIGBee signal connection.
Preferably, the external device is at least one of a range hood, an air purification device, or an exhaust fan.
The invention discloses a harmful substance detection device capable of detecting kitchen oil smoke, which is provided with a temperature sensing module for detecting the temperature in a cooking area, a particulate matter sensing assembly for detecting the concentration of particulate matters in the oil smoke in the cooking area, a calculation module for calculating the concentration of polycyclic aromatic hydrocarbons in the cooking area, an image acquisition module for analyzing the image of the oil smoke in the cooking area and obtaining the size of the generated oil smoke in real time, and a VOC sensor for detecting the concentration of volatile organic matters in the cooking area, wherein the temperature sensing module, the particulate matter sensing assembly, the VOC sensor and the image acquisition module are respectively and electrically connected with the calculation module. The harmful substance detection device can detect the temperature in a cooking area of a kitchen cooking area, the oil smoke size of the cooking area, the concentration of particles in the oil smoke, the concentration of polycyclic aromatic hydrocarbon and the concentration of volatile organic compounds. The harmful substance detection device is a suspension type, standing type, integrated type or portable type harmful substance detection device. The harmful substance detection device can also carry out health grade classification according to the concentration of volatile organic compounds, the size of oil fume, the concentration of particulate matters and the concentration of polycyclic aromatic hydrocarbons, and send the classified harmful substances to external equipment.
Drawings
The invention is further illustrated by the accompanying drawings, which are not to be construed as limiting the invention in any way.
Fig. 1 is a schematic diagram of the working flow of a harmful substance detection device capable of detecting kitchen fumes according to embodiment 1.
Fig. 2 is a schematic diagram of the working flow of a harmful substance detection device capable of detecting kitchen fumes according to embodiment 4.
Detailed Description
The technical scheme of the invention is further described with reference to the following examples.
Example 1.
A harmful substance detection device capable of detecting kitchen oil smoke is provided with a temperature sensing module for detecting temperature in a cooking area, a particulate matter sensing assembly for detecting concentration of particulate matters in the oil smoke in the cooking area, a calculation module for calculating concentration of polycyclic aromatic hydrocarbons in the cooking area, an image acquisition module for analyzing an image of the oil smoke in the cooking area and obtaining the size of the generated oil smoke in real time, and a VOC sensor for detecting concentration of volatile organic matters in the cooking area, wherein the temperature sensing module, the particulate matter sensing assembly, the VOC sensor and the image acquisition module are respectively electrically connected with the calculation module.
The temperature sensing module senses the temperature in the cooking area to obtain a temperature signal, the obtained temperature signal is used as a temperature output signal to be transmitted to the calculating module, the particulate matter sensing assembly collects the concentration of particulate matters in the cooking area oil smoke to obtain a particulate concentration signal and transmits the particulate concentration signal to the calculating module, the VOC sensor collects the concentration of volatile organic matters in the cooking area to obtain a VOC concentration signal and transmits the VOC concentration signal to the calculating module, the image collecting module collects the cooking area oil smoke image to obtain an oil smoke output signal and transmits the oil smoke output signal to the calculating module, and the calculating module receives the temperature output signal, the oil smoke output signal, the VOC concentration signal and the particulate concentration signal respectively and then processes the oil smoke output signal, the VOC concentration signal and the particulate concentration signal to obtain the polycyclic aromatic hydrocarbon concentration of the cooking area in real time.
The harmful substance detection device of the present invention may be: the specific embodiments of the present invention are applicable to a suspended type harmful substance detection device, a stand-alone type harmful substance detection device, an integrated type harmful substance detection device, or a portable type harmful substance detection device, depending on the actual situation. The specific harmful substance detection device of this embodiment is a suspended harmful substance detection device
The suspended harmful substance detection device of the present invention is a harmful substance detection device that can be directly mounted on a wall or other stationary object. It should be noted that, the suspension type harmful substance detection device of the present invention may also be other suspension type harmful substance detection devices, and the protection scope of the present invention is only to realize the suspension assembly mode.
The invention relates to a footed harmful substance detection device, which can be directly placed on a table or other stationary objects such as a cooking bench. It should be noted that, the footed type harmful substance detection device of the present invention may also be other types of footed type harmful substance detection devices, and the protection scope of the present invention is only required to implement the placement mode of the foots.
The integrated harmful substance detection device of the invention is a harmful substance detection device which can be integrated with other equipment, such as an intelligent sound box, a CCTV or a smoke detector. It should be noted that, the integrated harmful substance detection apparatus of the present invention may also be other types of integrated harmful substance detection apparatuses, and the installation mode of the harmful substance detection apparatus of the present invention to be assembled to other devices is only required to be the protection scope of the present invention.
The portable harmful substance detection device of the present invention is a harmful substance detection device that can be carried conveniently and can be used even when it is ready to use. It should be noted that, the portable harmful substance detection apparatus of the present invention may also be other portable harmful substance detection apparatuses, so long as the purpose of portability is achieved, that is, the portable harmful substance detection apparatus falls within the protection scope of the present invention.
The particulate matter sensing assembly comprises a PM2.5 sensor, a PM10 sensor, a PM1.0 sensor, a PM0.1 sensor, a PMA sensor and a dust sensor, wherein the PM10 sensor, the PM2.5 sensor, the PM1.0 sensor, the PM0.1 sensor, the PMA sensor and the dust sensor are respectively electrically connected with the temperature sensing module, the VOC sensor, the calculation module and the image acquisition module.
And the PM10 sensor acquires the concentration of the particulate matters with equivalent diameters smaller than or equal to 10 microns in the cooking area oil smoke to obtain a PM10 concentration signal, and transmits the PM10 concentration signal to the calculation module.
The PM2.5 sensor collects the concentration of particulate matters with equivalent diameters smaller than or equal to 2.5 microns in the cooking area oil smoke to obtain a PM2.5 concentration signal, and the PM2.5 concentration signal is transmitted to the calculation module.
The PM1.0 sensor collects the concentration of particulate matters with equivalent diameters smaller than or equal to 1.0 micron in the cooking area oil smoke to obtain a PM1.0 concentration signal, and the PM1.0 concentration signal is transmitted to the calculation module.
The PM0.1 sensor collects the concentration of particulate matters with equivalent diameters smaller than or equal to 0.1 micron in the cooking area oil smoke to obtain PM0.1 concentration signals, and the PM0.1 concentration signals are transmitted to the calculation module.
And the PMA sensor acquires the concentration of particles with equivalent diameter smaller than or equal to 0.05 micron in the cooking area oil smoke to obtain a PMA concentration signal, and transmits the PMA concentration signal to the calculation module.
The dust sensor acquires the concentration of particles with equivalent diameters of 1-75 microns in the cooking area oil smoke to obtain a dust concentration signal, and the dust concentration signal is transmitted to the calculation module.
The calculation module is a calculation module which is constructed by mathematical modeling and used for obtaining mathematical relations of temperature, volatile organic compound concentration, oil smoke size, particle concentration and polycyclic aromatic hydrocarbon concentration in harmful gas in the oil smoke.
The calculation module is obtained through mathematical modeling, and the mathematical modeling is to collect mathematical relations between factors such as different temperatures, volatile organic compound concentrations, oil smoke sizes, particulate matter concentrations and the like and the concentration of the polycyclic aromatic hydrocarbon in the harmful gas in the oil smoke through experiments. And (3) sampling and detecting according to different experimental conditions to obtain different types of polycyclic aromatic hydrocarbon concentrations, and analyzing and classifying to obtain a mathematical model, so that the calculation module can judge the current different types of polycyclic aromatic hydrocarbon concentrations according to the detection conditions of temperature, volatile organic matter concentration, oil smoke size and particulate matter concentration in the cooking area.
The calculation module is one of a linear calculation module, a nonlinear calculation module, an exponential calculation module, a power calculation module, a logarithmic calculation module, a neural network-like calculation module, a machine learning calculation module or a deep learning calculation module.
The image acquisition module acquires the condition of oil smoke generated in the cooking process in real time, specifically acquires the picture of the corresponding area in real time, processes the current kitchen oil smoke concentration, and transmits the data to the calculation module.
The processing method of the image acquisition module comprises the following steps:
the image acquisition module processes an initial image acquired by the imaging equipment as a basis, the initial image is a gray level image, the acquired initial image is serialized, and the current kitchen oil smoke concentration at the moment when each initial image of the rear frame is positioned is obtained by processing the initial image of the rear frame and the initial image of the front frame in sequence.
Each time the initial image of the back frame and the initial image of the front frame are processed, the current kitchen oil smoke concentration at the moment when the initial image of the back frame is positioned is obtained by the following steps:
(1) Performing frame difference processing on the initial image of the rear frame and the initial image of the front frame to obtain a frame difference image;
(2) Denoising the frame difference image in an open operation mode to obtain a denoised image;
(3) Performing edge detection on the denoising image, and marking a motion region as an initial region of interest;
(4) Carrying out gray average value calculation and region smoothness calculation on an initial region of interest, taking a region meeting the requirements of gray average value and smoothness as a next region of interest, and taking other regions as interference elimination;
(5) And (3) respectively counting the interested areas extracted in the step (4), and obtaining the oil smoke concentration assignment according to the counting result.
In the step (1), the frame difference operation is performed on the acquired initial image to obtain a frame difference image specifically includes:
and the image acquisition module performs difference on the next frame image and the previous frame image according to the sequence of the received initial images to obtain a frame difference image with a high brightness in the dynamic region.
The step (2) is to denoising the frame difference image by adopting open operation to obtain a denoised image, and the method is specifically carried out in the following manner: firstly, carrying out corrosion operation on the frame difference image to eliminate noise points and tiny spines in the image, and breaking narrow connection; and then expanding the corroded image to recover the smoke characteristics in the original frame difference image.
The step (3) is to carry out edge detection on the denoising image, mark a motion area as an initial interested area, and specifically comprises the following steps: detecting and marking the edge of the highlighted area of the frame difference image, and taking the marked area as an initial interested area.
And (4) specifically, carrying out gray average value and region smoothness calculation on each initial region of interest to obtain gray average value and gray smoothness corresponding to each initial region of interest, taking the initial region of interest which simultaneously satisfies that the calculated gray average value is smaller than a gray threshold value and the gray smoothness is smaller than the gray smoothness threshold value as the region of interest, and judging other initial regions of interest as interference regions.
The step (5) is specifically to sum the gray scales of all pixels in each region of interest image to obtain the gray scale value of each region of interest image aiming at the region of interest extracted in the step (4), and then sum the gray scale values of each region of interest image to obtain the oil smoke concentration assignment.
The target area acquired by the imaging device is represented by an area S, and any frame of initial image is the imaging of the corresponding area S.
The initial image is made up of m x n pixels,
the gray values of the pixels of the initial image a of the subsequent frame are represented by a matrix AH, ah= { AH i,j }，ah i,j Representing gray values corresponding to the ith row and the jth column of pixels in the initial image A of the subsequent frame, wherein i is the row where the pixels are located, j is the column where the pixels are located, i is more than or equal to 1 and less than or equal to m, and j is more than or equal to 1 and less than or equal to n; the sub-area where the ith row and jth column pixels are located in the initial image A of the subsequent frame is AS i,j 。
The gray value of the pixel of the previous frame initial image B is represented by a matrix BH, bh= { BH i,j }，bh i,j Representing gray values corresponding to the ith row and the jth column pixels in the initial image B of the previous frame, wherein the subarea where the ith row and the jth column pixels are positioned in the initial image B of the previous frame is BS i,j 。
The pixel gray value of the frame difference image D is represented by a matrix DH, dh= { DH i,j }＝{|ah i,j -bh i,j |}，dh i,j Representing gray values corresponding to the ith row and the jth column pixels in the frame difference image D, wherein the subarea where the ith row and the jth column pixels in the frame difference image D are positioned is DS i,j 。
In the frame difference image, |dh i,j The region of |=0 is black; |dh i,j The region of i+.0 is highlighted.
The step (2) of corroding the frame difference image specifically comprises the following steps:
2-11, arbitrarily defining a convolution kernel theta;
2-12, convolving the convolution kernel theta with the frame difference image; when traversing the frame difference image by the convolution kernel theta, extracting a pixel gray minimum value p of a convolution result in the coverage area of the convolution kernel and a pixel point C overlapped with the center of the convolution kernel;
the gray level of the pixel point C passes through the matrix CH= { C k,q And k, q are the row number and column number of pixel C,
obtaining a minimum value pixel point matrix P of a convolution result obtained in the process of traversing the frame difference image by using a convolution kernel theta, wherein the gray level of the minimum value pixel point matrix P passes through a matrix PH= { P k,q -representation;
2-13, endowing the gray scale of the pixel point matrix P to the pixel point C correspondingly to obtain a corrosion image;
and (3) performing expansion operation on the corrosion image in the step (2), wherein the method specifically comprises the following steps of:
2-21, arbitrarily defining a convolution kernel beta;
2-22, convolving the convolution kernel beta with the corrosion image; when traversing the corrosion image by the convolution kernel beta, extracting a pixel gray maximum value o of a convolution result in the coverage area of the convolution kernel and a pixel point R overlapped with the center of the convolution kernel;
the gray level of the pixel point R passes through the matrix RH= { R l,v And indicates that l and v are the row number and column number of the pixel point R,
obtaining a convolution result maximum pixel point matrix O obtained in the process of traversing the convolution kernel beta through the corrosion image, wherein the gray level of the maximum pixel point matrix O passes through a matrix OH= { O l,v -representation;
and 2-13, endowing the gray scale of the maximum pixel point matrix O with the pixel point R correspondingly to obtain an expanded image, and obtaining the expanded image which is the denoising image.
Wherein the step (3) is performed by the following steps:
3-1, defining a filter Y, wherein the filter is a t matrix, and t is an odd number;
3-2, traversing the filter Y through the denoising image, calculating the gray value of the denoising image of the central pixel point of each position of the filter and the gray values of other pixels in the neighborhood of the central pixel point, and calculating the edge detection value X of the central pixel point of each position of the filter according to the formula (I) z Z is the signature of filter Y as it traverses the denoised image,
f. g is the matrix serial number of the pixel points, f is more than or equal to 1 and less than or equal to t, g is more than or equal to 1 and less than or equal to t, and e is the gray value of the denoising image where the pixel point of the filter at each position is positioned; alpha is a weight coefficient and corresponds to the position of the filter;
3-3, the edge detection value X of the central pixel point of the filter at each position z Subtracting the gray values of other pixels in the neighborhood of the central pixel point, and judging whether the absolute value of the difference value is larger than a threshold delta;
counting a number greater than a threshold, if the number exceeds
Judging the pixel point position of the denoising image corresponding to the central pixel point of the filter as an edge point, and marking;
3-4, traversing the complete denoising image by the filter to obtain all marked edge points, and obtaining a preliminary region of interest.
t is 3.
It should be noted that, the above-mentioned processing method of the image acquisition module is only one of the processing methods provided, and the method that the processing method of the other image acquisition modules can only acquire the output data of the image acquisition module of the cooking area can be applied to the harmful substance detection device capable of detecting kitchen fume of the present invention, and all the methods fall into the protection scope of the present invention.
It should be noted that, the image acquisition module of the present invention adopts the camera to detect the cooking area oil fume, so long as the above functions of the present invention can be implemented, the image acquisition module of the present invention can be used. The calculation module of the present invention calculates the concentration of polycyclic aromatic hydrocarbon in the cooking area through the temperature signal and the oil smoke signal, and the calculation module is a calculator or a module with a calculation function, which can be used as the calculation module of the present invention, and the calculation module of the present invention is a common knowledge of the calculation module in industrial production, and will not be described herein.
The temperature in the cooking area is preferably the temperature of the detected kitchen ware, and can also be the temperature of air, the temperature of lampblack or the temperature of a kitchen range in the cooking area, and the specific implementation mode is determined according to actual conditions. In this embodiment, the detected temperature in the cooking area is the temperature of the kitchen ware.
This can detect harmful substance detection device of kitchen oil smoke is provided with the temperature sensing module that is used for detecting the interior temperature of cooking region, be arranged in detecting the particulate matter sensing module of particulate matter concentration in the cooking region oil smoke, be used for calculating the calculation module of the polycyclic aromatic hydrocarbon concentration in cooking region, be used for to the image analysis of cooking region oil smoke and obtain the image acquisition module that produces the oil smoke size and be used for detecting the volatile organic compounds concentration's of cooking region VOC sensor in real time, temperature sensing module, particulate matter sensing module, VOC sensor and image acquisition module are connected with the calculation module electricity respectively. The harmful substance detection device can detect the temperature in a cooking area of a kitchen cooking area, the oil smoke size of the cooking area, the concentration of particles in the oil smoke, the concentration of polycyclic aromatic hydrocarbon and the concentration of volatile organic compounds.
Example 2.
A harmful substance detecting apparatus capable of detecting kitchen fumes, other features being the same as those of embodiment 1, except that: the calculation formula of the calculation module is shown as a formula (I),
wherein C is Polycyclic aromatic hydrocarbons Is the total concentration of polycyclic aromatic hydrocarbon gas in the cooking areaThe degree, K is the output data of the temperature sensing module, lambda is the output data of the image acquisition module, C is the output data of the particulate matter sensing assembly, C PM10 Output data of PM10 sensor, C PM2.5 Output data of PM2.5 sensor, C PM1.0 Output data of PM1.0 sensor, C PM0.1 Output data of PM0.1 sensor, C PMA Output data of PMA sensor, C Dust C is output data of the dust sensor VOC Is output data of the VOC sensor.
When kappa is E (0 ℃,200 ℃), C is E (0 mug/m) 3 ,3000μg/m 3 )，λ∈(0,300)，C VOC ∈(0mg/m 3 ，5mg/m 3 ) At time C (2-3) ＝70％C Polycyclic aromatic hydrocarbons ,C (4) ＝20％C Polycyclic aromatic hydrocarbons ,C (5-6) ＝10％C Polycyclic aromatic hydrocarbons 。
When kappa is treated with E (200 ℃,240 ℃), C is treated with E (3000 mug/m) 3 ,5000μg/m 3 )，λ∈(300,500)，C VOC ∈(5mg/m 3 ，10mg/m 3 ) At time C (2-3) ＝60％C Polycyclic aromatic hydrocarbons ,C (4) ＝25％C Polycyclic aromatic hydrocarbons ,C (5-6) ＝15％C Polycyclic aromatic hydrocarbons 。
Wherein C is (2-3) Is the concentration of the bi-ring polycyclic aromatic hydrocarbon and the tri-ring polycyclic aromatic hydrocarbon, C (4) Is the concentration of tetracyclic polycyclic aromatic hydrocarbon, C (5-6) Is the concentration of pentacyclic polycyclic aromatic hydrocarbon and hexacyclic polycyclic aromatic hydrocarbon.
For example, when kappa is 100 ℃, C is 1000. Mu.g/m 3 Lambda is 100, C VOC 1mg/m 3 At the time, kappa and C, C are respectively VOC And directly substituting the data value of lambda into the formula to obtain C Polycyclic aromatic hydrocarbons 1106.6 and C Polycyclic aromatic hydrocarbons In pg/m 3 I.e. the concentration of polycyclic aromatic hydrocarbons in the current environment is 1106.6pg/m 3 。C (2-3) Is 774.62pg/m 3 ，C (4) Is 221.32pg/m 3 ，C (5-6) Is 110.66pg/m 3 。
According to the embodiment, the concentration of polycyclic aromatic hydrocarbon in the current cooking area can be obtained by detecting the temperature output signal, the oil smoke output signal, the PM2.5 concentration signal, the PM10 concentration signal, the PM1.0 concentration signal, the PM0.1 concentration signal, the PMA concentration signal, the dust concentration signal and the VOC concentration signal, and the concentrations of the bicyclic polycyclic aromatic hydrocarbon, the tricyclic polycyclic aromatic hydrocarbon, the tetracyclic polycyclic aromatic hydrocarbon, the pentacyclic polycyclic aromatic hydrocarbon and the hexacyclic polycyclic aromatic hydrocarbon in the current environment can be calculated.
Example 3.
A range hood capable of health grading according to the use of food materials, other features being the same as in example 1, except that: the calculation formula of the calculation module is represented by formula (II),
wherein C is Polycyclic aromatic hydrocarbons For the total concentration of polycyclic aromatic hydrocarbon gas in the cooking area, kappa is the output data of the temperature sensing module, lambda is the output data of the image acquisition module, C is the output data of the particulate matter sensing assembly, C PM10 Output data of PM10 sensor, C PM2.5 Output data of PM2.5 sensor, C PM1.0 Output data of PM1.0 sensor, C PM0.1 Output data of PM0.1 sensor, C PMA Output data of PMA sensor, C Dust C is output data of the dust sensor VOC Is output data of the VOC sensor.
When kappa is E (0 ℃,200 ℃), C is E (0 mug/m) 3 ,3000μg/m 3 )，λ∈(0,300)，C VOC ∈(0mg/m 3 ，5mg/m 3 ) At time C (2-3) ＝70％C Polycyclic aromatic hydrocarbons ,C (4) ＝20％C Polycyclic aromatic hydrocarbons ,C (5-6) ＝10％C Polycyclic aromatic hydrocarbons 。
When kappa is treated with E (200 ℃,240 ℃), C is treated with E (3000 mug/m) 3 ,5000μg/m 3 )，λ∈(300,500)，C VOC ∈(5mg/m 3 ，10mg/m 3 ) At time C (2-3) ＝60％C Polycyclic aromatic hydrocarbons ,C (4) ＝25％C Polycyclic aromatic hydrocarbons ,C (5-6) ＝15％C Polycyclic aromatic hydrocarbonHydrocarbons 。
Wherein C is (2-3) Is the concentration of the bi-ring polycyclic aromatic hydrocarbon and the tri-ring polycyclic aromatic hydrocarbon, C (4) Is the concentration of tetracyclic polycyclic aromatic hydrocarbon, C (5-6) Is the concentration of pentacyclic polycyclic aromatic hydrocarbon and hexacyclic polycyclic aromatic hydrocarbon.
For example, when kappa is 100 ℃, C is 1000. Mu.g/m 3 Lambda is 100, C VOC 1mg/m 3 At the time, kappa and C, C are respectively VOC And directly substituting the data value of lambda into the formula to obtain C Polycyclic aromatic hydrocarbons 1101.01 and C Polycyclic aromatic hydrocarbons In pg/m 3 I.e. the concentration of polycyclic aromatic hydrocarbons in the current environment is 1101.01pg/m 3 。C (2-3) Is 770.707pg/m 3 ，C (4) Is 220.202pg/m 3 ，C (5-6) Is 110.101pg/m 3 。
According to the embodiment, the concentration of polycyclic aromatic hydrocarbon in the current cooking area can be obtained by detecting the temperature output signal, the oil smoke output signal, the PM2.5 concentration signal, the PM10 concentration signal, the PM1.0 concentration signal, the PM0.1 concentration signal, the PMA concentration signal, the dust concentration signal and the VOC concentration signal, and the concentrations of the bicyclic polycyclic aromatic hydrocarbon, the tricyclic polycyclic aromatic hydrocarbon, the tetracyclic polycyclic aromatic hydrocarbon, the pentacyclic polycyclic aromatic hydrocarbon and the hexacyclic polycyclic aromatic hydrocarbon in the current environment can be calculated.
Example 4.
As shown in fig. 2, the harmful substance detecting apparatus capable of detecting kitchen fumes has the same other features as those of embodiment 1, except that: the calculation module of the invention is also a calculation module for classifying the health grade of harmful substances.
The embodiment is classified according to the GBT18883-2 indoor air quality standard, and the invention can also be classified according to other quality standards, such as GB3059-2012 and WTO environmental quality standards. The invention can also be divided according to other preset environmental quality values.
The method is specifically as follows:
in the embodiment, the polycyclic aromatic hydrocarbon is graded by dividing the concentration of the polycyclic aromatic hydrocarbon by the average limiting concentration of benzo [ a ] pyrene specified by national standard, as shown in the formula (III):
when epsilon is more than or equal to 0 and less than or equal to 0.5, the grade of the polycyclic aromatic hydrocarbon is judged to be healthy.
When 0.5 < epsilon.ltoreq.1, the polycyclic aromatic hydrocarbon grade is judged to be good.
When epsilon is more than 1 and less than or equal to 5, the grade of the polycyclic aromatic hydrocarbon is judged to be medium.
When 5 < epsilon is less than or equal to 10, the grade of the polycyclic aromatic hydrocarbon is judged to be poor.
When 10 < ε, then the polycyclic aromatic hydrocarbon grade was judged to be severe.
Wherein C is Benzo [ a ]]Pyrene (pyrene) Benzo [ a ] specified for national standard]Average limited concentration of pyrene, and C Benzo [ a ]]Pyrene (pyrene) ＝1ng/m 3 。
It should be noted that, the polycyclic aromatic hydrocarbon grade of the present invention may be divided according to other values of ε, and this embodiment is merely provided as an implementation scheme, and the polycyclic aromatic hydrocarbon grade dividing method according to other polycyclic aromatic hydrocarbon concentrations falls within the protection scope of the present invention.
Health definite value division is carried out on the polycyclic aromatic hydrocarbon grade to obtain the polycyclic aromatic hydrocarbon grade U Polycyclic aromatic hydrocarbons 。
When the grade of polycyclic aromatic hydrocarbon is healthy, then U Polycyclic aromatic hydrocarbons 1.
When the grade of polycyclic aromatic hydrocarbon is good, then U Polycyclic aromatic hydrocarbons 2.
When the polycyclic aromatic hydrocarbon grade is medium, then U Polycyclic aromatic hydrocarbons 3.
When the grade of polycyclic aromatic hydrocarbon is poor, then U Polycyclic aromatic hydrocarbons 4.
When the polycyclic aromatic hydrocarbon grade is severe, then U Polycyclic aromatic hydrocarbons 5.
It should be noted that the polycyclic aromatic hydrocarbon grade of the present invention may correspond to the above, or may correspond to different U's according to different polycyclic aromatic hydrocarbon grades in actual situations Polycyclic aromatic hydrocarbons The value, this example shows only one possibility,corresponding U for various polycyclic aromatic hydrocarbon grades Polycyclic aromatic hydrocarbons The values fall within the scope of the invention.
The calculation module of the invention carries out air quality index assessment according to the output data of the PM10 sensor, the PM2.5 sensor, the PM1.0 sensor, the PM0.1 sensor or the PMA sensor and the selected air quality standard, as shown in a formula (VII);
where M is the current air quality index.
BM Hi Is a high level of the selected air quality criteria and the particulate matter concentration limit corresponding to C.
BM Lo The low value of the particulate matter concentration limit corresponding to C in the air quality standard is selected.
M Hi To select air quality standard medium and BM Hi Corresponding air mass fraction index.
M Lo To select air quality standard medium and BM Lo Corresponding air mass fraction index.
This example illustrates the invention according to table 1 as follows:
table 1, air quality index and PM10 and PM2.5 project concentration limits
For example C, which is currently actually measured PM2.5 ＝425μm/m 3 Searching for the upper and lower values of PM2.5 concentration limit, BM Hi ＝500，BM Lo ＝350。BM Hi The value of (2) corresponds to an air quality index (IAQI) of 500, i.e. M Hi ＝500。BM Lo The value of (2) corresponds to an air quality index (IAQI) of 400, i.e. M Lo =400. Then respectively BM Hi 、BM Lo 、M Hi 、M Lo And C PM2.5 Substituted into formula (VII).
M=475 is obtained.
It should be noted that the present embodiment selects only one air quality standard and C PM2.5 Corresponding numbers, but for different air quality criteria and C PM10 、C PM2.5 、C PM1.0 、C PM0.1 And C PMA And are within the scope of the present invention.
The air quality index is subjected to health constant value division to obtain a particulate matter grade U Particulate matter ；
When M is more than or equal to 0 and less than or equal to 400, U is Particulate matter ＝1；
When M is 400 to 600, U Particulate matter ＝2；
When M is 600 to 700, U is Particulate matter ＝3；
When M is more than 700 and less than or equal to 800, U is Particulate matter ＝4；
When 900 < M, then U Particulate matter ＝5。
It should be noted that the air quality index of the present invention may be divided according to other values of M. This example is merely provided as an implementation, and other methods for classifying particulate matter according to output data of the PM10 sensor, the PM2.5 sensor, the PM1.0 sensor, the PM0.1 sensor, and the PMA sensor fall within the scope of the present invention.
The particulate matter level U corresponding to the air quality index of the invention Particulate matter As shown above, different U can be corresponding to different air quality indexes according to actual conditions Particulate matter The values, in this example, show only one possibility, corresponding to U for each air quality index Particulate matter The values fall within the scope of the invention.
The calculation module of the invention also carries out health constant value division on the output data of the VOC sensor to obtain the volatile organic compound level U VOC 。
Volatilization of the inventionGrade U of organic matter VOC The output data of the VOC sensor is divided into different ranges, and corresponding health fixed values are given to the corresponding ranges.
For example when 0.ltoreq.C VOC ≤0.4mg/m 3 When in use, U VOC ＝1；
When 0.4mg/m 3 ＜C VOC ≤0.6mg/m 3 When in use, U VOC ＝2；
When 0.6mg/m 3 ＜C VOC ≤0.7mg/m 3 When in use, U VOC ＝3；
When 0.7mg/m 3 ＜C VOC ≤0.7mg/m 3 When in use, U VOC ＝4；
When 0.7mg/m 3 ＜C VOC When in use, U VOC ＝5。
Volatile organic compound level U of the present example VOC Is based on the GBT18883-2002 indoor air quality standard, and the average value of the TVOC at 8 hours is 0.6mg/m 3 And divided. Other air quality criteria based or other divisions of the present invention are within the scope of the present invention.
It should be noted that the output data of the VOC sensor of the invention can be divided into health values according to C VOC Is divided by other values of (a). This example is merely an embodiment of providing a volatile organic compound level U based on the output data of other VOC sensors VOC And the method of (2) also falls within the scope of the present invention.
The invention calculates the health grade U by the following method:
1. the calculation module calculates the grade U of polycyclic aromatic hydrocarbon Polycyclic aromatic hydrocarbons Grade U of particulate matter Particulate matter And volatile organic grade U VOC In contrast, the health grade U with the maximum value being the current cooking area is selected, as shown in a formula (VIII),
U＝max(U particulate matter ,U VOC ，U Polycyclic aromatic hydrocarbons ) Formula (VIII).
2. The calculation module calculates the grade U of polycyclic aromatic hydrocarbon Polycyclic aromatic hydrocarbons Grade U of particulate matter Particulate matter And volatile organic compoundsGrade U VOC The health level U of the current cooking area is added, as in formula (ix),
U＝U particulate matter +U VOC +U Polycyclic aromatic hydrocarbons Formula (IX).
3. The calculation module calculates the grade U of polycyclic aromatic hydrocarbon Polycyclic aromatic hydrocarbons Multiplying the polycyclic aromatic hydrocarbon weight factor Q Polycyclic aromatic hydrocarbons Grade U of particulate matter Particulate matter Multiplying by the particulate matter weight factor Q Particulate matter And volatile organic compound level U VOC Multiplied by the volatile organic weight factor Q VOC In contrast, the health grade U with the maximum value of the current cooking area is selected, as shown in formula (X),
U＝max(U particulate matter *Q Particulate matter ,U VOC *Q VOC ，U Polycyclic aromatic hydrocarbons *Q Polycyclic aromatic hydrocarbons ) Formula (X).
4. The calculation module calculates the grade U of polycyclic aromatic hydrocarbon Polycyclic aromatic hydrocarbons Multiplying the polycyclic aromatic hydrocarbon weight factor Q Polycyclic aromatic hydrocarbons Grade U of particulate matter Particulate matter Multiplying by the particulate matter weight factor Q Particulate matter And volatile organic compound level U VOC Multiplied by the volatile organic weight factor Q VOC The health level U of the current cooking area is added, as in formula (xi),
U＝U particulate matter *Q Particulate matter +U VOC *Q VOC +U Polycyclic aromatic hydrocarbons *Q Polycyclic aromatic hydrocarbons Formula (XI).
The health level U calculation of this embodiment is specifically the first one. For example when U Polycyclic aromatic hydrocarbons ＝2，U Particulate matter ＝3、U VOC When=4, the health grade U of the current cooking area is 4. A smaller value for U indicates a healthier, and a larger value for U indicates a less healthier.
It should be noted that the first method may be selected from the 4 methods of the present invention, or the other three methods may be selected according to the actual situation, and the specific embodiment depends on the actual situation. Q for the third method of the invention Particulate matter 0.6, Q Polycyclic aromatic hydrocarbons 1.2, Q VOC 0.6, Q Polycyclic aromatic hydrocarbons 、Q Polycyclic aromatic hydrocarbons And Q Particulate matter Other values are possible, and the specific implementation is according to the actual situation. Q for the fourth method of the invention Particulate matter 0.2, Q Polycyclic aromatic hydrocarbons 0.6, Q VOC 0.2, Q Polycyclic aromatic hydrocarbons 、Q Polycyclic aromatic hydrocarbons And Q Particulate matter Other values are possible, and the specific implementation is according to the actual situation.
The calculation module carries out health grade division according to the current volatile organic compound concentration, the oil fume size, the particulate matter concentration and the polycyclic aromatic hydrocarbon concentration to obtain a health grade signal.
The harmful substance detection device is further provided with a signal transmission module which is used for being in signal connection with external equipment, and the signal transmission module is electrically connected with the calculation module.
The calculation module carries out health grade division according to the current volatile organic compound concentration, the oil fume size, the particulate matter concentration and the polycyclic aromatic hydrocarbon concentration to obtain a health grade signal, the calculation module sends the health grade signal to the signal transmission module, and the signal transmission module receives the health grade signal and sends the health grade signal to external equipment.
The signal connection of the invention can be a wired signal connection or a wireless connection, and the specific implementation mode is dependent on the actual situation. The wired signal connection may be any one of RS232 signal connection, RS485 signal connection, USB signal connection, GPIB signal connection, or CAN signal connection, and the specific implementation manner depends on the actual situation. The wireless signal connection is any one of WiFi signal connection, bluetooth signal connection, NFC signal connection or ZIGBee signal connection, and the specific implementation mode is determined according to practical situations.
The signal connection in this embodiment is a wireless signal connection and is a WiFi signal connection.
The external equipment of the invention is at least one of a range hood, an air purifying device or an exhaust fan. The external equipment range hood of this embodiment.
The signal transmitting module transmits the health grade signal to the range hood, and the external equipment can adjust the air draft assembly according to the health grade, so that the concentration of harmful substances is reduced.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the scope of the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted equally without departing from the spirit and scope of the technical solution of the present invention.
Claims (8)
1. Harmful substance detection device that can detect kitchen oil smoke, its characterized in that: the cooking range oil smoke detection device comprises a temperature sensing module used for detecting the temperature in a cooking range, a particulate matter sensing assembly used for detecting the concentration of particulate matters in cooking range oil smoke, a calculation module used for calculating the concentration of polycyclic aromatic hydrocarbons in the cooking range, an image acquisition module used for analyzing the cooking range oil smoke image and obtaining the generated oil smoke and a VOC sensor used for detecting the concentration of volatile organic matters in the cooking range in real time, wherein the temperature sensing module, the particulate matter sensing assembly, the VOC sensor and the image acquisition module are respectively and electrically connected with the calculation module;
the temperature sensing module senses the temperature in the cooking area to obtain a temperature signal, the obtained temperature signal is used as a temperature output signal to be transmitted to the calculating module, the particulate matter sensing assembly collects the concentration of particulate matters in the cooking area oil smoke to obtain a particulate concentration signal and transmits the particulate concentration signal to the calculating module, the VOC sensor collects the concentration of volatile organic matters in the cooking area to obtain a VOC concentration signal and transmits the VOC concentration signal to the calculating module, the image collecting module collects the cooking area oil smoke image to obtain an oil smoke output signal and transmits the oil smoke output signal to the calculating module, and the calculating module respectively receives the temperature output signal, the oil smoke output signal, the VOC concentration signal and the particulate concentration signal and then processes the oil smoke output signal to obtain the polycyclic aromatic hydrocarbon concentration of the cooking area in real time;
the calculation module is a calculation module which is constructed by mathematical modeling to obtain mathematical relations of temperature, volatile organic compound concentration, oil smoke size, particle concentration and polycyclic aromatic hydrocarbon concentration in harmful gas in the oil smoke;
the particulate matter sensing assembly comprises a PM2.5 sensor, a PM10 sensor, a PM1.0 sensor, a PM0.1 sensor, a PMA sensor and a dust sensor, wherein the PM10 sensor, the PM2.5 sensor, the PM1.0 sensor, the PM0.1 sensor, the PMA sensor and the dust sensor are respectively and electrically connected with the temperature sensing module, the VOC sensor, the calculation module and the image acquisition module;
the PM10 sensor collects the concentration of the particulate matters with equivalent diameters smaller than or equal to 10 microns in the cooking area oil smoke to obtain PM10 concentration signals, and transmits the PM10 concentration signals to the calculation module,
the PM2.5 sensor collects the concentration of particles with equivalent diameter less than or equal to 2.5 microns in the cooking area oil smoke to obtain PM2.5 concentration signals, and transmits the PM2.5 concentration signals to the calculation module,
the PM1.0 sensor collects the concentration of particles with equivalent diameter less than or equal to 1.0 micron in the cooking area oil smoke to obtain PM1.0 concentration signals, and transmits the PM1.0 concentration signals to the calculation module,
the PM0.1 sensor collects the concentration of particles with equivalent diameter less than or equal to 0.1 micron in the cooking area oil smoke to obtain PM0.1 concentration signals, and transmits the PM0.1 concentration signals to the calculation module,
the PMA sensor collects the concentration of particles with equivalent diameter less than or equal to 0.05 micron in the cooking area oil smoke to obtain a PMA concentration signal, and transmits the PMA concentration signal to the calculation module,
the dust sensor acquires the concentration of particles with equivalent diameters of 1-75 microns in the cooking area oil smoke to obtain a dust concentration signal, and the dust concentration signal is transmitted to the calculation module;
the calculation formula of the calculation module is shown as a formula (I),
or alternatively
The calculation formula of the calculation module is represented by formula (II),
wherein C is Polycyclic aromatic hydrocarbons For the total concentration of polycyclic aromatic hydrocarbon gas in the cooking area, kappa is the output data of the temperature sensing module, and lambda is the image acquisitionOutput data of the module, C is output data of the particulate matter sensing assembly, C PM10 Output data of PM10 sensor, C PM2.5 Output data of PM2.5 sensor, C PM1.0 Output data of PM1.0 sensor, C PM0.1 Output data of PM0.1 sensor, C PMA Output data of PMA sensor, C Dust C is output data of the dust sensor VOC Is output data of the VOC sensor.
2. The harmful substance detection apparatus capable of detecting kitchen fumes according to claim 1, wherein: the device is a suspended type harmful substance detection device, a foot-type harmful substance detection device or a portable harmful substance detection device.
3. The harmful substance detection apparatus capable of detecting kitchen fumes according to claim 2, wherein: the computing module is a linear computing module, a nonlinear computing module, an exponential computing module, a power computing module, a logarithmic computing module, a neural network computing module, a machine learning computing module or a deep learning computing module.
4. A harmful substance detection apparatus capable of detecting kitchen fumes according to claim 3, wherein: the calculation module is also used for classifying the health grade of the harmful substances;
the calculation module carries out health grade division according to the current volatile organic compound concentration, the oil fume size, the particulate matter concentration and the polycyclic aromatic hydrocarbon concentration to obtain a health grade signal.
5. The harmful substance detection apparatus capable of detecting kitchen fumes according to claim 4, wherein: the system is also provided with a signal transmitting module for signal connection with external equipment, and the signal transmitting module is electrically connected with the calculating module;
the calculation module carries out health grade division according to the current volatile organic compound concentration, the oil fume size, the particulate matter concentration and the polycyclic aromatic hydrocarbon concentration to obtain a health grade signal, the calculation module sends the health grade signal to the signal transmission module, and the signal transmission module receives the health grade signal and sends the health grade signal to external equipment.
6. The harmful substance detection apparatus capable of detecting kitchen fumes according to claim 5, wherein: the signal connection is a wired signal connection;
the wired signal connection is RS232 signal connection, RS485 signal connection, USB signal connection, GPIB signal connection or CAN signal connection.
7. The harmful substance detection apparatus capable of detecting kitchen fumes according to claim 5, wherein: the signal connection is wireless signal connection;
the wireless signal connection is WiFi signal connection, bluetooth signal connection, NFC signal connection or ZIGBee signal connection.
8. The harmful substance detection apparatus capable of detecting kitchen fumes according to claim 6 or 7, wherein: the external equipment is at least one of a range hood, an air purifying device or an exhaust fan.
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