CN107132315A - Signal recognition method, device and volatile organic matter detection device - Google Patents
Signal recognition method, device and volatile organic matter detection device Download PDFInfo
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- CN107132315A CN107132315A CN201710340937.7A CN201710340937A CN107132315A CN 107132315 A CN107132315 A CN 107132315A CN 201710340937 A CN201710340937 A CN 201710340937A CN 107132315 A CN107132315 A CN 107132315A
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Abstract
The embodiment of the present invention provides signal recognition method, device and volatile organic matter detection device, is related to air pollutants monitoring technical field.Volatile organic matter detection device is used to carry out on-line checking to VOCs, volatile organic matter detection device is stored with the application program of signal recognition method and device, VOCs pollutants can be acquired, pass through the response of gas sensor array, the signal of response is pre-processed, sampled, feature extraction, identification and calculate, the species and corresponding concentration of contained gas in VOCs are obtained, spraying process VOCs pollutants can be rapidly and accurately monitored.Effective Monitoring Data can be not only provided for environmental monitoring, and theoretic support can be provided to improve spraying coating process and technology.
Description
Technical field
The present invention relates to air pollutants monitoring technical field, in particular to a kind of signal recognition method, device and
Volatile organic matter detection device.
Background technology
In recent years, China's air quality deteriorates seriously, and zonal haze weather and ozone pollution event frequently occur, and wave
The long-term a large amount of discharges of hair property organic matter (volatile organic compounds, VOCs) are one of principal elements.According to system
VOCs in meter, city is mainly derived from the discharge of stationary source waste gas, accounts for the 55.5% of whole anthropogenic discharge source.Due to depositing
In the diversification of the enterprise product structure of coating process, coating material species, come in every shape, the technique used in coating process
It is different, cause VOCs discharge link and discharge characteristics also to have nothing in common with each other, also lack (particularly medium and small to apply to application enterprise now
Fill enterprise, such as metal product industry) the effective monitoring of VOCs pollutions, cause most of enterprise VOCs that there is coating process to discharge
Less than effective control.
VOCs, which is determined, two kinds of common methods, and a kind of is the off-line checking method based on gas-chromatography, and another is base
In the on-line monitoring method of electrochemical sensor.Monitoring currently for stationary source VOCs is returned to live hand sampling
Based on lab analysis, gas-chromatography or GC-MS method method are VOCs standard detecting methods generally acknowledged at present, and it can be right
Groups of contaminants is into being analyzed comprehensively, to pollutant concentration accurate quantification, but its instrument and equipment is expensive, and testing cost is high,
Professional is needed to operate, it is impossible to meet the requirement of Site Detection, and off-line method poor in timeliness, it is impossible to reflect gas in time
Change in concentration situation, sample loss and cross pollution are easily caused in sampling, sample storage, transportation, test process is cumbersome, into
This is higher.The sensor, method of on-line monitoring can do quantitative analysis using single sensor to a certain compositions of VOCs, such as
Hydrogen flameionization detection method (FID), VOCs total amounts can be determined based on optic ionized sensor (PID) method, but only determined
VOCs total amounts can not reflect the emission behaviour of pollution from coatings thing completely.
The content of the invention
In view of this, the embodiment of the present invention provides a kind of signal recognition method, device and volatile organic matter detection device,
To improve above mentioned problem.
The embodiment of the present invention provides a kind of signal recognition method, applied to volatile organic matter detection device, the volatilization
Property organic matter detection device include gas sensor array, methods described includes：The letter responded to the gas sensor array
Number sampled；Feature extraction is carried out to the signal of sampling；The signal after extraction is known using artificial neural network algorithm
Not；Data processing is carried out to the signal identified, the species and concentration of corresponding volatile organic matter is obtained.
Further, the step of signal of described pair of sampling carries out feature extraction also includes：Utilize PCA pair
The signal of sampling carries out feature extraction, and decomposites the independent element in multi channel signals using independent component analysis method, goes forward side by side
Row Feature Selection.
Further, methods described also includes：The species and concentration of the volatile organic matter are recorded.
Further, methods described also includes：By the volatilization of the concentration of the volatile organic matter calculated and correspondence species
Property organic matter preset concentration compare, if the concentration of the volatile organic matter calculated be more than correspondence species volatility it is organic
The preset concentration of thing, sends alarm command.
The embodiment of the present invention also provides a kind of signal identification device, described to wave applied to volatile organic matter detection device
Hair property organic matter detection device includes gas sensor array, and described device includes：Sampling module, for the gas sensing
The signal of device array response is sampled；Characteristic extracting module, feature extraction is carried out for the signal to sampling；Pattern-recognition mould
Block, for the signal after extraction to be identified using artificial neural network algorithm；Computing module, for the signal to identifying
Data processing is carried out, the species and concentration of corresponding volatile organic matter is obtained.
Further, the characteristic extracting module is additionally operable to put forward the signal progress feature of sampling using PCA
Take, and decomposite using independent component analysis method the independent element in multi channel signals, and carry out Feature Selection.
Further, the signal identification device also includes logging modle, for by the species of the volatile organic matter
Recorded with concentration.
Further, the signal identification device also includes contrast module and alarm module, and the contrast module is used for will
The preset concentration of the concentration of the volatile organic matter calculated and the volatile organic matter of correspondence species is compared；The alarm mould
If block is used for the preset concentration of volatile organic matter of the concentration more than correspondence species of the volatile organic matter calculated, report is sent
Alert instruction.
The embodiment of the present invention also provides a kind of volatile organic matter detection device, the volatile organic matter detection device bag
Gas sensor array is included, the gas sensor array is configured to detect volatile organic matter；Processor；Storage
Device；And signal identification device；The signal identification device is configured to store in the memory, and including it is one or more by
The functional module of the computing device, the signal identification device includes：Sampling module, for gas sensor battle array
The signal of row response is sampled；Characteristic extracting module, feature extraction is carried out for the signal to sampling；Pattern recognition module,
For the signal after extraction to be identified using artificial neural network algorithm；Computing module, for entering to the signal identified
Row data processing, obtains the species and concentration of corresponding volatile organic matter.
Further, the equipment also includes：Data acquisition circuit, the data acquisition circuit is connected to the gas and passed
Between sensor array and the processor, the data acquisition circuit is configured to the mould for sending the gas sensor array
Intend signal and be converted into data signal；Alarm, is configured to respond to the alarm command of the processor, sends alarm sound；Collection
Into control unit, the alarm command of the processor is configured to respond to, starting volatility organic matter processing system is controlled.
Compared with prior art, volatile organic matter detection device provided in an embodiment of the present invention is used to carry out VOCs
Line detects, volatile organic matter detection device is stored with the application program of signal recognition method and device, can be to VOCs pollutants
Be acquired, by the response of gas sensor array, the signal of response is pre-processed, sampled, feature extraction, identification and
Calculate, obtain the species and corresponding concentration of contained gas in VOCs, can rapidly and accurately monitor spraying process VOCs pollutions
Thing.Effective Monitoring Data can be not only provided for environmental monitoring, and theory can be provided to improve spraying coating process and technology
On support.
To enable the above objects, features and advantages of the present invention to become apparent, preferred embodiment cited below particularly, and coordinate
Appended accompanying drawing, is described in detail below.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be attached to what is used required in embodiment
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore is not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
The structured flowchart for the volatile organic matter detection device that Fig. 1 provides for first embodiment of the invention.
The high-level schematic functional block diagram for the signal identification device that Fig. 2 provides for first embodiment of the invention.
The fundamental diagram for the volatile organic matter detection device that Fig. 3 provides for first embodiment of the invention.
The flow chart for the signal recognition method that Fig. 4 provides for second embodiment of the invention.
Icon：100- volatile organic matter detection devices；101- memories；102- storage controls；103- processors；
104- Peripheral Interfaces；105- display units；106- gas sensor arrays；107- data acquisition circuits；108- alarms；109-
Integrated control unit；200- signal identification devices；201- sampling modules；202- characteristic extracting modules；203- pattern recognition modules；
204- computing modules；205- logging modles；206- contrast modules；207- alarm modules；300- chambers.
Embodiment
Below in conjunction with accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.Generally exist
The component of the embodiment of the present invention described and illustrated in accompanying drawing can be arranged and designed with a variety of configurations herein.Cause
This, the detailed description of the embodiments of the invention to providing in the accompanying drawings is not intended to limit claimed invention below
Scope, but it is merely representative of the selected embodiment of the present invention.Based on embodiments of the invention, those skilled in the art are not doing
The every other embodiment obtained on the premise of going out creative work, belongs to the scope of protection of the invention.
It should be noted that：Similar label and letter represents similar terms in following accompanying drawing, therefore, once a certain Xiang Yi
It is defined in individual accompanying drawing, then it further need not be defined and explained in subsequent accompanying drawing.Meanwhile, the present invention's
In description, term " first ", " second " etc. are only used for distinguishing description, and it is not intended that indicating or implying relative importance.
First embodiment
Fig. 1 is refer to, is the structured flowchart for the volatile organic matter detection device 100 that first embodiment of the invention is provided.
Volatile organic matter detection device 100 provided in an embodiment of the present invention be used in spraying operation to volatile organic matter
The composition and content of (volatile organic compounds, VOCs) are detected, to prevent and administer VOCs pollutions.Often
The VOCs seen includes benzene, toluene, ethylbenzene, dimethylbenzene, methanol, ethanol, acetone, isopropanol, preferably benzene homologues.
The volatile organic matter detection device 100 includes multiple hardware and software feature modules, volatile organic matter inspection
Measurement equipment 100 can carry Android (Android) system, IOS (iPhone operating system) system, Windows
Phone systems, Windows systems etc., running environment is provided for multiple software function modules.It is described in the embodiment of the present invention
Signal identification is the application program (Application, APP) being installed in volatile organic matter detection device 100.The volatilization
Property organic matter detection device 100 also to include memory 101, storage control 102, processor 103, Peripheral Interface 104, display single
Member 105, gas sensor array 106, data acquisition circuit 107, alarm 108 and integrated control unit 109.
The memory 101, storage control 102, processor 103, Peripheral Interface 104, display unit 105, gas are passed
Sensor array 106, data acquisition circuit 107, alarm 108 and integrated control unit 109, each element each other directly or
Ground connection is electrically connected with, to realize the transmission or interaction of data.For example, these elements can pass through one or more communication each other
Bus or signal wire, which are realized, to be electrically connected with.The signal identification device 200 can be with software or firmware including at least one
(firmware) form is stored in the memory 101 or is solidificated in the behaviour of the volatile organic matter detection device 100
Make the software function module in system (operating system, OS).The processor 103 is used to perform in memory 101
The executable module of storage, for example, software function module or computer program that the signal identification device 200 includes.
Signal recognition method that memory 101 can be used in storage software program and module, such as embodiment of the present invention and
Corresponding programmed instruction/the module of device.The processor 103 is used to perform the executable module stored in the memory 101,
Such as software function module and computer program included by signal identification device 200.
Memory 101 may include high speed random access memory, may also include nonvolatile memory, such as one or more magnetic
Property storage device, flash memory or other non-volatile solid state memories.Processor 103 and other possible components are to storage
The access of device 101 can be carried out under the control of storage control 104.
Processor 103 is probably a kind of IC chip, the disposal ability with signal.Above-mentioned processor 103 can
To be general processor, including central processing unit (Central Processing Unit, abbreviation CPU), network processing unit
(Network Processor, abbreviation NP) etc.；Can also be digital signal processor (DSP), application specific integrated circuit (ASIC),
It is ready-made programmable gate array (FPGA) or other PLDs, discrete gate or transistor logic, discrete hard
Part component.It can realize or perform disclosed each method, step and the logic diagram in the embodiment of the present invention.General processor
Can be microprocessor or the processor 103 can also be any conventional processor etc..
Various input/output devices are coupled to processor 103 and memory 101 by the Peripheral Interface 104.At some
In embodiment, Peripheral Interface 104, processor 103 and storage control 102 can be realized in one single chip.Other one
In a little examples, they can be realized by independent chip respectively.
Display unit 105 provides an interactive interface (example between the volatile organic matter detection device 100 and user
Such as user interface) or for display image data give user reference.In the present embodiment, the display unit 105 can be with
It is liquid crystal display or touch control display.Preferably, the display unit 105 can be used for display volatile organic matter detection device
100 VOCs detected composition and each component content numerical value.
The gas sensor array 106 can include TGS series sensors, PID photoions sensor and electrochemistry and pass
Sensor.It is preferred that, the gas sensor array 106 is by 7 TGS series sensors, 1 PID photoions sensor and 2 electricity
Chemical sensor is constituted.The gas sensor array 106 has sensitiveness to VOCs, is capable of detecting when the chemical combination that VOCs contains
Thing, and gas sensor array 106 electrically connects with data acquisition circuit 107, and gas sensor array 106 detects VOCs
Afterwards, the signal of response is analog signal, by the analog signal transmission of response to data acquisition circuit 107.
The data acquisition circuit 107 can include multiple capture cards, such as may include A/D capture cards.Also there is signal
The function of pretreatment, can include filter circuit, can be filtered the data signal of conversion and denoising.Pass through Peripheral Interface
104 send the data signal of collection to processor 103, are handled by processor 103.
The alarm 108 is used for the control instruction that answer processor 103 is sent, and sends in alarm, the present embodiment, described
Alarm 108 is audible-visual annunciator.
The integrated control unit 109 is used for the alarm command for responding the processor 103, and control starting volatility is organic
Thing processing system, the TREATMENT OF VOCs system can be handled indoor VOCs pollutants.
Fig. 2 is refer to, is the high-level schematic functional block diagram for the signal identification device 200 that first embodiment of the invention is provided.Institute
Stating signal identification device 200 includes sampling module 201, characteristic extracting module 202, pattern recognition module 203 and computing module
204。
The sampling module 201, for being sampled to the signal that the gas sensor array 106 is responded.This implementation
In example, the signal that gas sensor array 106 is responded is after the pretreatment of data acquisition circuit 107, the pre- place of 201 pairs of sampling module
Signal after reason is acquired.To respond the analog signal produced after corresponding sensitive gas by gas sensor array 106, then
By data acquisition circuit 107 handle after data signal, the signal as sampled.
The characteristic extracting module 202, feature extraction is carried out for the signal to sampling.In the present embodiment, using it is main into
Point analytic approach carries out feature extraction to the signal of sampling, and decomposites using independent component analysis method the independence in multi channel signals
Composition, and carry out Feature Selection.Principal component analysis is also referred to as principal component analysis, it is intended to using the thought of dimensionality reduction, multi objective is converted
For a few overall target (i.e. principal component), wherein each principal component can reflect the most information of original variable, and
Information contained is not repeated mutually；Independent component analysis refers to recover independent source signal from independent source mixed signal, is a kind of
The method of blind source separating.
The pattern recognition module 203, for the signal after extraction to be identified using artificial neural network algorithm.Patrol
The thinking for collecting property refers to the process of be made inferences according to logic rules, and information is first melted into concept, and symbolically by it, so
Afterwards, reasoning from logic is carried out according to symbolic operation in a serial mode, this process can be write as serial instruction, allow computer to hold
OK, as artificial neural network algorithm.
The computing module 204, for carrying out data processing to the signal identified, obtains corresponding volatile organic matter
Species and concentration.It is preferred that, corresponding data processing method can be transferred in memory 101 to knowledge according to user instruction
The signal not gone out carries out data processing, obtains the species and concentration of corresponding volatile organic matter.For example, can be in different temperatures
Different data processing methods or pattern are selected under state.
The signal identification device 200 also includes logging modle 205, contrast module 206 and alarm module 207.The note
Record module 205 is used to be recorded the species and concentration of the volatile organic matter, and by the volatile organic matter of record
Species and concentration storage are into memory 101.Signal identification device 200 can also according to storage VOCs species and concentration with
And X-Y scheme is set up at the time of correspondence, can be that spraying coating process and technology provide theoretic support.
The volatility that the contrast module 206 is used for the concentration and correspondence species for the volatile organic matter that will be calculated is organic
The preset concentration of thing is compared；If the concentration that the alarm module 207 is used for the volatile organic matter calculated is more than correspondence kind
The preset concentration of the volatile organic matter of class, sends alarm command, and control alarm 108 sends alarm sound.
Fig. 3 is refer to, is the operation principle for the volatile organic matter detection device 100 that first embodiment of the invention is provided
Figure.The volatile organic matter detection device 100, which can include VOCs sampling units, sensor array detection unit, signal, to be known
Other device 200 and integrated control unit 109.
The VOCs sampling units are used to carry out gas collecting, can be including the air inlet pipe being sequentially connected, condenser, filtering
Device, drier, aspiration pump and flowmeter.Sensor array detection unit is used for signal sampling and Signal Pretreatment, including experiment
Case 300, the gas sensor array 106 in chamber 300, the heating power supply being connected with gas sensor array 106,
Working power and data acquisition circuit 107.
When VOCs is after air inlet pipe enters chamber 300,106 pairs of gas sensor array in chamber 300 is adopted
The gas of collection carries out signal sampling, and the analog signal of sampling is sent to data acquisition circuit 107 and passed through by gas sensor array 106
Cross after analog-to-digital conversion, filtering, denoising and send to processor, the signal identification being stored in memory 101 is performed by processor 103
Device 200 carries out signal identification, calculated, and finally obtains various species and corresponding concentration in VOCs.
Second embodiment
Fig. 4 is refer to, is the flow chart for the signal recognition method that second embodiment of the invention is provided.The present invention second is implemented
The signal recognition method that example is provided comprises the following steps：
Step S101, samples to the signal that the gas sensor array 106 is responded.
Specifically, the signal that gas sensor array 106 is responded is after the pretreatment of data acquisition circuit 107, mould of sampling
Block 201 is acquired to pretreated signal.By gas sensor array 106 respond corresponding sensitive gas after produce
Analog signal, then by data acquisition circuit 107 handle after data signal, the signal as sampled.
In the embodiment of the present invention, the step S101 can be performed by sampling module 201.
Step S102, feature extraction is carried out to the signal of sampling.
Feature extraction is carried out to the signal of sampling using PCA, and decomposited using independent component analysis method many
Independent element in channel signal, and carry out Feature Selection.Principal component analysis is also referred to as principal component analysis, it is intended to utilize the think of of dimensionality reduction
Think, multi objective is converted into a few overall target (i.e. principal component), wherein each principal component can reflect original variable
Most information, and information contained do not repeat mutually；Independent component analysis refers to recover independence from independent source mixed signal
Source signal, be a kind of method of blind source separating.
In the embodiment of the present invention, the step S102 can be performed by characteristic extracting module 202.
Step 103, the signal after extraction is identified using artificial neural network algorithm.
In the embodiment of the present invention, the step S103 can be performed by pattern recognition module 203.
Step 104, data processing is carried out to the signal that identifies, obtains the species of corresponding volatile organic matter and dense
Degree.
In the embodiment of the present invention, the step S104 can be performed by computing module 204.
Step 105, the species and concentration of the volatile organic matter are recorded.
In the embodiment of the present invention, the step S105 can be performed by logging modle 205.Logging modle 205 is waved described
The species and concentration of hair property organic matter are recorded, and the species of the volatile organic matter of record and concentration storage are arrived into memory
In 101.
Step 106, whether the VOCs calculated concentration is more than preset concentration
The preset concentration of the concentration of the volatile organic matter calculated and the volatile organic matter of correspondence species is compared,
If the concentration of the volatile organic matter calculated is less than or equal to the preset concentration of the volatile organic matter of correspondence species, tie
Beam；If the concentration of the volatile organic matter calculated is more than the preset concentration of the volatile organic matter of correspondence species, step is performed
Rapid S107.
In the embodiment of the present invention, the step S106 can be performed by contrast module 206.
Step 107, alarm command is sent.The alarm command can control alarm 108 to send alarm sound, can be with
The integrated starting volatility organic matter processing system of control unit 109 is stated in control, and the TREATMENT OF VOCs system can be right
Indoor VOCs pollutants are handled.
In the embodiment of the present invention, the step S107 can be performed by alarm module 207.
In summary, volatile organic matter detection device provided in an embodiment of the present invention is used to examine VOCs online
Survey, volatile organic matter detection device is stored with the application program of signal recognition method and device, and VOCs pollutants can be carried out
Collection, by the response of gas sensor array, the signal of response is pre-processed, sampled, feature extraction, identification and count
Calculate, obtain the species and corresponding concentration of contained gas in VOCs, can rapidly and accurately monitor spraying process VOCs pollutants.
Effective Monitoring Data can be not only provided for environmental monitoring, and can provide theoretic to improve spraying coating process and technology
Support.
In several embodiments provided herein, it should be understood that disclosed apparatus and method, it can also pass through
Other modes are realized.Device embodiment described above is only schematical, for example, flow chart and block diagram in accompanying drawing
Show according to the device of multiple embodiments of the present invention, the architectural framework in the cards of method and computer program product,
Function and operation.At this point, each square frame in flow chart or block diagram can represent the one of a module, program segment or code
Part a, part for the module, program segment or code is used to realize holding for defined logic function comprising one or more
Row instruction.It should also be noted that in some implementations as replacement, the function of being marked in square frame can also with different from
The order marked in accompanying drawing occurs.For example, two continuous square frames can essentially be performed substantially in parallel, they are sometimes
It can perform in the opposite order, this is depending on involved function.It is also noted that every in block diagram and/or flow chart
The combination of individual square frame and block diagram and/or the square frame in flow chart, can use the special base for performing defined function or action
Realize, or can be realized with the combination of specialized hardware and computer instruction in the system of hardware.
In addition, each functional module in each embodiment of the invention can integrate to form an independent portion
Point or modules individualism, can also two or more modules be integrated to form an independent part.
If the function is realized using in the form of software function module and is used as independent production marketing or in use, can be with
It is stored in a computer read/write memory medium.Understood based on such, technical scheme is substantially in other words
The part contributed to prior art or the part of the technical scheme can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, including some instructions are to cause a computer equipment (can be individual
People's computer, server, or network equipment etc.) perform all or part of step of each of the invention embodiment methods described.
And foregoing storage medium includes：USB flash disk, mobile hard disk, read-only storage (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with the medium of store program codes.Need
Illustrate, herein, such as first and second or the like relational terms be used merely to by an entity or operation with
Another entity or operation make a distinction, and not necessarily require or imply between these entities or operation there is any this reality
The relation or order on border.Moreover, term " comprising ", "comprising" or its any other variant are intended to the bag of nonexcludability
Contain, so that process, method, article or equipment including a series of key elements are not only including those key elements, but also including
Other key elements being not expressly set out, or also include for this process, method, article or the intrinsic key element of equipment.
In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that including the key element
Process, method, article or equipment in also there is other identical element.
The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.Within the spirit and principles of the invention, that is made any repaiies
Change, equivalent substitution, improvement etc., should be included in the scope of the protection.It should be noted that：Similar label and letter exists
Similar terms is represented in following accompanying drawing, therefore, once being defined in a certain Xiang Yi accompanying drawing, is then not required in subsequent accompanying drawing
It is further defined and explained.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all be contained
Cover within protection scope of the present invention.Therefore, protection scope of the present invention should be defined by scope of the claims.
Claims (10)
1. a kind of signal recognition method, applied to volatile organic matter detection device, the volatile organic matter detection device bag
Include gas sensor array, it is characterised in that methods described includes：
The signal that the gas sensor array is responded is sampled；
Feature extraction is carried out to the signal of sampling；
The signal after extraction is identified using artificial neural network algorithm；
Data processing is carried out to the signal identified, the species and concentration of corresponding volatile organic matter is obtained.
2. signal recognition method according to claim 1, it is characterised in that the signal of described pair of sampling carries out feature extraction
The step of also include：Feature extraction is carried out to the signal of sampling using PCA, and utilizes independent component analysis method point
The independent element in multi channel signals is solved, and carries out Feature Selection.
3. signal recognition method according to claim 1, it is characterised in that methods described also includes：By the volatility
The species and concentration of organic matter are recorded.
4. signal recognition method according to claim 1, it is characterised in that methods described also includes：By waving for calculating
The preset concentration of the concentration of hair property organic matter and the volatile organic matter of correspondence species is compared, if the volatility calculated is organic
The concentration of thing is more than the preset concentration of the volatile organic matter of correspondence species, sends alarm command.
5. a kind of signal identification device, applied to volatile organic matter detection device, the volatile organic matter detection device bag
Include gas sensor array, it is characterised in that described device includes：
Sampling module, for being sampled to the signal that the gas sensor array is responded；
Characteristic extracting module, feature extraction is carried out for the signal to sampling；
Pattern recognition module, for the signal after extraction to be identified using artificial neural network algorithm；
Computing module, for carrying out data processing to the signal that identifies, obtains the species of corresponding volatile organic matter and dense
Degree.
6. signal identification device according to claim 5, it is characterised in that the characteristic extracting module is additionally operable to utilize master
Componential analysis carries out feature extraction to the signal of sampling, and is decomposited using independent component analysis method only in multi channel signals
Vertical composition, and carry out Feature Selection.
7. signal identification device according to claim 5, it is characterised in that the signal identification device also includes record mould
Block, for the species and concentration of the volatile organic matter to be recorded.
8. signal identification device according to claim 5, it is characterised in that the signal identification device also includes contrast mould
Block and alarm module, the contrast module are used to have the volatility of the concentration of the volatile organic matter calculated and correspondence species
The preset concentration of machine thing is compared；
If the alarm module is used for volatile organic matter of the concentration more than correspondence species of the volatile organic matter calculated
Preset concentration, sends alarm command.
9. a kind of volatile organic matter detection device, it is characterised in that the volatile organic matter detection device is passed including gas
Sensor array, the gas sensor array is configured to detect volatile organic matter；
Processor；
Memory；And
Signal identification device；
The signal identification device is configured to store in the memory, and including one or more by the computing device
Functional module, the signal identification device includes：
Sampling module, for being sampled to the signal that the gas sensor array is responded；
Characteristic extracting module, feature extraction is carried out for the signal to sampling；
Pattern recognition module, for the signal after extraction to be identified using artificial neural network algorithm；
Computing module, for carrying out data processing to the signal that identifies, obtains the species of corresponding volatile organic matter and dense
Degree.
10. volatile organic matter detection device according to claim 9, it is characterised in that the equipment also includes：
Data acquisition circuit, the data acquisition circuit is connected between the gas sensor array and the processor, institute
Data acquisition circuit is stated to be configured to the analog signal that the gas sensor array is sent being converted into data signal；
Alarm, is configured to respond to the alarm command of the processor, sends alarm sound；
Integrated control unit, is configured to respond to the alarm command of the processor, controls starting volatility organic matter processing system
System.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111157584A (en) * | 2020-01-07 | 2020-05-15 | 广东博智林机器人有限公司 | Alcohol content detection method, device and detection equipment |
| CN111398377A (en) * | 2020-04-16 | 2020-07-10 | 北方工业大学 | Gas environment monitoring system and method for rail transit station |
| CN113517039A (en) * | 2020-04-10 | 2021-10-19 | 中国石油化工股份有限公司 | Method and system for identifying production device based on VOCs components |
| CN116718733A (en) * | 2023-06-28 | 2023-09-08 | 中国海洋大学 | Volatile organic compound concentration calculation method, system, electronic equipment and medium |
| CN116718733B (en) * | 2023-06-28 | 2024-05-31 | 中国海洋大学 | Volatile organic compound concentration calculation method, system, electronic equipment and medium |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1588030A (en) * | 2004-07-09 | 2005-03-02 | 大连理工大学 | Portable gas detection analyzer with temperature and humidity compensation function |
| CN101614625A (en) * | 2008-06-27 | 2009-12-30 | 同方威视技术股份有限公司 | Detect the gate-type pedestrian safety inspection device and the method for contraband goodss such as drugs, explosive |
| CN101788656A (en) * | 2010-01-29 | 2010-07-28 | 东南大学 | Method for recognizing function response signal under function nuclear magnetic resonance scan |
| CN101819177A (en) * | 2010-04-23 | 2010-09-01 | 王海宝 | Ambient air quality monitoring system |
| CN102192927A (en) * | 2010-11-05 | 2011-09-21 | 重庆大学 | Air-quality monitoring system based on electronic nose technique, and monitoring method thereof |
| CN202093008U (en) * | 2011-05-17 | 2011-12-28 | 中国人民解放军76349部队 | Intelligent noxious gas detector |
| CN203439256U (en) * | 2013-09-06 | 2014-02-19 | 中科宇图天下科技有限公司 | Multi-rotor-wing unmanned aerial vehicle for monitoring and tracing pollution gas |
| CN103728348A (en) * | 2013-12-02 | 2014-04-16 | 江苏大学 | Electronic nose for detecting indoor air quality |
| CN103745466A (en) * | 2014-01-06 | 2014-04-23 | 北京工业大学 | Image quality evaluation method based on independent component analysis |
| CN104636314A (en) * | 2015-01-30 | 2015-05-20 | 太原科技大学 | Single channel chaotic signal blind source separation method |
| CN104792826A (en) * | 2015-03-23 | 2015-07-22 | 中国农业大学 | System and method for detecting milk freshness based on electronic nose |
| CN105067768A (en) * | 2015-07-30 | 2015-11-18 | 安徽中杰信息科技有限公司 | Multi-component mixed gas quantitative recognition system for dangerous chemical detection |
| CN105738434A (en) * | 2016-02-01 | 2016-07-06 | 清华大学深圳研究生院 | Diabetes diagnostic system for detecting respiratory gases based on electronic nose |
-
2017
- 2017-05-12 CN CN201710340937.7A patent/CN107132315A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1588030A (en) * | 2004-07-09 | 2005-03-02 | 大连理工大学 | Portable gas detection analyzer with temperature and humidity compensation function |
| CN101614625A (en) * | 2008-06-27 | 2009-12-30 | 同方威视技术股份有限公司 | Detect the gate-type pedestrian safety inspection device and the method for contraband goodss such as drugs, explosive |
| CN101788656A (en) * | 2010-01-29 | 2010-07-28 | 东南大学 | Method for recognizing function response signal under function nuclear magnetic resonance scan |
| CN101819177A (en) * | 2010-04-23 | 2010-09-01 | 王海宝 | Ambient air quality monitoring system |
| CN102192927A (en) * | 2010-11-05 | 2011-09-21 | 重庆大学 | Air-quality monitoring system based on electronic nose technique, and monitoring method thereof |
| CN202093008U (en) * | 2011-05-17 | 2011-12-28 | 中国人民解放军76349部队 | Intelligent noxious gas detector |
| CN203439256U (en) * | 2013-09-06 | 2014-02-19 | 中科宇图天下科技有限公司 | Multi-rotor-wing unmanned aerial vehicle for monitoring and tracing pollution gas |
| CN103728348A (en) * | 2013-12-02 | 2014-04-16 | 江苏大学 | Electronic nose for detecting indoor air quality |
| CN103745466A (en) * | 2014-01-06 | 2014-04-23 | 北京工业大学 | Image quality evaluation method based on independent component analysis |
| CN104636314A (en) * | 2015-01-30 | 2015-05-20 | 太原科技大学 | Single channel chaotic signal blind source separation method |
| CN104792826A (en) * | 2015-03-23 | 2015-07-22 | 中国农业大学 | System and method for detecting milk freshness based on electronic nose |
| CN105067768A (en) * | 2015-07-30 | 2015-11-18 | 安徽中杰信息科技有限公司 | Multi-component mixed gas quantitative recognition system for dangerous chemical detection |
| CN105738434A (en) * | 2016-02-01 | 2016-07-06 | 清华大学深圳研究生院 | Diabetes diagnostic system for detecting respiratory gases based on electronic nose |
Non-Patent Citations (1)
| Title |
|---|
| 王化祥: "《现代传感技术及应用》", 30 June 2016 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111157584A (en) * | 2020-01-07 | 2020-05-15 | 广东博智林机器人有限公司 | Alcohol content detection method, device and detection equipment |
| CN113517039A (en) * | 2020-04-10 | 2021-10-19 | 中国石油化工股份有限公司 | Method and system for identifying production device based on VOCs components |
| CN111398377A (en) * | 2020-04-16 | 2020-07-10 | 北方工业大学 | Gas environment monitoring system and method for rail transit station |
| CN116718733A (en) * | 2023-06-28 | 2023-09-08 | 中国海洋大学 | Volatile organic compound concentration calculation method, system, electronic equipment and medium |
| CN116718733B (en) * | 2023-06-28 | 2024-05-31 | 中国海洋大学 | Volatile organic compound concentration calculation method, system, electronic equipment and medium |
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