CN107015023B - A kind of smell source three-dimensional detection method - Google Patents
A kind of smell source three-dimensional detection method Download PDFInfo
- Publication number
- CN107015023B CN107015023B CN201710173931.5A CN201710173931A CN107015023B CN 107015023 B CN107015023 B CN 107015023B CN 201710173931 A CN201710173931 A CN 201710173931A CN 107015023 B CN107015023 B CN 107015023B
- Authority
- CN
- China
- Prior art keywords
- smell
- modulus maximum
- similitude
- maximum line
- sensors
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P13/00—Indicating or recording presence, absence, or direction, of movement
- G01P13/02—Indicating direction only, e.g. by weather vane
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Investigating Or Analyzing Materials By The Use Of Fluid Adsorption Or Reactions (AREA)
- Investigating Or Analyzing Materials By The Use Of Electric Means (AREA)
Abstract
The present invention relates to a kind of smell source three-dimensional detection methods, and four smell sensors are arranged on tetrahedral four vertex, the method is as follows: the smell of four pieces of sensor acquisition a period of times, output voltage time series.The voltage time sequence exported is subjected to continuous wavelet transform, obtains the fluctuation signal under multiple scales.The modulus maximum for extracting each scale fluctuation signal, establishes Modulus maximum line.The similitude for defining Modulus maximum line in conjunction with three kinds of similitudes and is subject to respective weights and obtains final global similitude, and weight is set according to the significance degree of every difference, to identify that the same smell reaches or leave event.According to the similitude of Modulus maximum line, each Modulus maximum line of four sensors is matched, by the highest modulus maximum lines matching of global similitude at one group, reaches or leave the response of event to find them to same smell.
Description
Technical field
The present invention relates to a kind of smell source direction detection device and methods, can especially detect the three-dimensional side in smell source
To.
Background technique
With the development of industrialization, more and more Hazardous Chemical Substances are directly or indirectly applied in production and living, but
During use, production, storage or transport toxic gas, the incident of leakage Shi Youfa as caused by artificial or objective factor
It is raw.The leakage of toxic gas seriously threatens the life security of the people, the property safety and economic development of society.Therefore fast
Speed, accurately and reliably find unknown leakage source position in advance to the later period it is reasonable dispose and rescue it is most important.
Currently, odor source detection method mainly includes two kinds of normal forms, wherein widely used method is passed from smell
The azimuth information that odor source is excavated in the time series of sensor and wind measuring device utilizes wind information backstepping when detecting smell
Smell source orientation out.This method relies on wind direction information, needs anemometry, and the usual volume of high-precision anemobiagraph and
Weight is larger, there is certain requirement to application.
Second of normal form is then that hiding odor source azimuth information is excavated from the Time-space serial of multiple smell sensors.
Due to not needing anemometry, the robot that this normal form is more suitable for portable equipment and requires to size or load-carrying
(such as microrobot, rotor wing unmanned aerial vehicle etc.).Ishida devises mechanical smell compass to indicate odor source direction
{Nakamoto T,Ishida H,Moriizumi T.An odor compass for localizing an odor
source[J].Sensorsand Actuators B:Chemical,1996,35(1):32–36.}{Ishida H,
Kobayashi A,Nakamoto T,et al.Three-dimensional odor compass[J].Robotics
AndAutomation, IEEE Transactions on, 1999,15 (2): 251-257. }, this compass is by 4 semiconductor smells
The components such as sensor, fan and motor composition, compass probe constantly rotation adjustment posture is to keep 4 pieces of smell sensor response letters
Number balance, compass probe instruction direction be smell source direction.But the device for mechanical component is more, it is difficult to accomplish small-sized
Change, there is also problems easy to damage easy to aging.In addition, the method needs servo motor slowly to drive sensor group to traverse respectively
The efficiency in a direction, the judgement of smell orientation is lower.
Meng Qinghao has invented a kind of gas detection apparatus and method { patent that can indicate odor source direction
CN201410605741.2 }, and propose a kind of corresponding odor source orientation judgment method Wei Y.-T., Meng Q.-H.,
Jing Y.-Q.,et al.A Portable Odor-Tracing Instrument[J].IEEE Transactions on
Instrumentation&Measurement,2016,65(3):631-642.}.The method uses difference of Gaussian
(Different of Gaussian, DoG) handles the Time-space serial of 3 smell sensors being mounted equidistant two-by-two, establishes sensing
The DoG scale space of device variable signal, later therefrom extraction time difference information and by the way that smell source direction is calculated.
But the method adjustable parameter is more, and parameter adjustment relies on experience, and method performance is to parameter sensitivity, and equipment uses too busy to get away people
Work decision not can avoid toxic gas potential hazard caused by operator.In addition, this device and method can only detect smell
The horizontal two-dimension direction in source, can not know the elevation information in smell source.
Meng Qinghao has invented a kind of detection method { patent for odor source direction instruction in three-dimensional environment
CN201610815146.0 }, smell sensor is installed on the vertex of regular polygon by this method, keeps 12 sensors uniform
Be distributed on a spherical surface.The concentration value for monitoring sensor output, then thinks that the sensor is detected higher than given threshold
Smell packet is recorded after second sensor, 3rd sensor detect smell packet as first sensor and detects smell
The time difference of packet;If different sensors odor detection event time interval is less than 200ms, and the odorousness that the latter detects
It is lower than previous, then meet sensor with packet condition;The last three-dimensional according to the time difference calculating smell packet for detecting smell packet
Source direction.But there are following two points deficiencies for the method: 1) judging that same packet condition directly uses sensor concentration value, without simultaneous interpretation
The baseline differences of sensor are bigger, and are used every time with using the factors such as time, sensor life-time, environment constantly to change
It is required to calibration sensor base line before;2) when sensor distance is closer, common metal oxide sensor is not easy point
The concentration difference of former and later two sensors is discerned, and increasing sensor distance can be such that detection device volume increases, and influence portability.
Summary of the invention
The present invention provides one kind and does not depend on wind information, and adjustable parameter is few, insensitive to adjustable parameter, does not depend on artificial determine
Plan, the fast and quasi- smell source three-dimensional detection method of detection speed.In addition, this method is suitable for portable equipment, environment is supervised
The odor detection for surveying automatic Weather Station, ground robot, rotor wing unmanned aerial vehicle etc., can especially equip lesser miniature to volume and load-carrying
In robot.Technical scheme is as follows:
Four smell sensors are arranged in tetrahedral four by a kind of smell source three-dimensional detection method, this method
On vertex, detection method is as follows:
[1] primary voltage of the higher output of odorousness is lower, the smell of four pieces of sensor acquisition a period of times, output electricity
Press time series.
[2] to each smell sensor, the voltage time sequence exported is subjected to continuous wavelet transform, obtains multiple rulers
The lower fluctuation signal of degree, negative value indicates the arrival of smell in transformed fluctuation signal, and the corresponding smell of positive value leaves, and fluctuation is believed
Number minimum correspond to the maximum aggregation rate of smell, maximum corresponds to the maximum dissipation rate of smell.
[3] modulus maximum for extracting each scale fluctuation signal, establishes Modulus maximum line, minimum in Modulus maximum line
Value line corresponds to smell arrival event, and maximum line corresponds to smell and leaves event.
[5] in terms of three define Modulus maximum line similitude: 1) modulus maximum with scale variation tendency;2) extreme value
Point corresponds to the time with the variation tendency of scale;3) out to out that Modulus maximum line extends;For maximum line l1, l2, the above two
Similitude χw(l1,l2) and χt(l1,l2) calculated by Pearson correlation coefficient;The similitude of the third party, that is, out to out similitude
χs(l1,l2)=1- | N1-N2|/Ns, wherein N1, N2For maximum line l1, l2The out to out extended to;
In conjunction with three kinds of similitudes and it is subject to respective weights and obtains final global similitude, weight is according to the aobvious of every difference
Work degree setting, to identify that the same smell reaches or leave event.
[6] according to the similitude of Modulus maximum line, each Modulus maximum line of four sensors is matched, by global phase
Like the highest modulus maximum lines matching of property at one group, the response of event is reached or left to find them to same smell.
[7] according to the response time difference that four sensors reached or left event to the same smell be calculated smell come
Source orientation.
[8] multiple smell source orientation is detected using the method for step [1] to [7], seeks vector sum as final gas
Taste source direction.
The main advantages of the present invention and characteristic be embodied in following aspects:
1. this method directly detects the space time information comprising olfactory flow characteristic with sensor few as far as possible.Four pieces of sensings
The disposing way of device provides the optimal case of smell source detection, in the same of the odiferous information that detection comes from all directions diffusion
When, avoid the redundancy of information.
2. the method does not depend on wind information compared to traditional gas detection method, it is not necessarily to wind speed measuring device.It is reducing
While cost, for the method using more flexible, application is more extensive, is especially more suitable for micro-robot or unmanned plane etc. to load-carrying
The smell required searches equipment.
3. this method eliminates the influence of different odor sensor base line difference, do not need to be calibrated before the use.
4. the method reaches/leaves the time difference of four sensors according to smell to calculate in a direction estimation
To the direction of odor source, wherein using Modulus maximum line thought carry out sensor response signal matching, improve matching at
Power, so that the method calculates quickly and precision is higher.
5. the adjustable parameter in the method is less, and method performance is insensitive to parameter, and method performance and stability are able to
It ensures.
6. this method avoids manual decision on the temporald eixis of smell source, make in hazardous environment in conjunction with robot
Industry can avoid toxic gas health hazard caused by operator.
Detailed description of the invention
Fig. 1 is the main view of smell source three-dimensional detection device of the invention.
Fig. 2 is the hardware composite structural diagram of detection device.
Fig. 3 is smell source direction reasoning algorithm flow chart of the invention.
Specific embodiment
Core sensing element of the present invention is made of four pieces of gas sensors of same model, uses bracket and support
Bar support, forms positive tetrahedron structure, carries out type selecting according under test gas in practice.
Smell source direction inference method of the invention is as follows:
[1] odiferous information is acquired after sensor preheating, the voltage time sequence sampled sends microprocessor to, in real time
It calculates smell source orientation, calculates that result is sent to portable device, robot etc. using universal serial bus.
[2] in an algorithm cycle period, continuous wavelet transform is carried out to original time series, is obtained under multiple scales
Fluctuation signal.Wavelet function uses Gauss first derivative.In order to generate equally distributed modulus maximum, scale, which uses, to be referred to
Number function is calculated.Due to the circuit design of gas sensor, the primary voltage of the higher output of odorousness is lower, therefore becomes
Negative value indicates the arrival of smell in signal after changing, and the corresponding smell of positive value leaves, and minimum corresponds to the maximum aggregation speed of smell
Rate, and maximum corresponds to the maximum dissipation rate of smell.
[4] modulus maximum of each scale fluctuation signal is linked to be Modulus maximum line.Considering each magnitude signal decaying
In the case where, two extreme value sizes and corresponding moment immediate extreme point are connected on same Modulus maximum line.
[5] according to the similitude of Modulus maximum line, each Modulus maximum line of four sensors is matched, to find it
Same smell is reached/is left the response of event.This method defines the similitude of Modulus maximum line: 1) mould in terms of three
Maximum with scale variation tendency;2) extreme point corresponds to the time with the variation tendency of scale;3) Modulus maximum line extends most
Large scale.For maximum line l1, l2, the above two similitude χw(l1,l2) and χt(l1,l2) calculated by Pearson correlation coefficient.
The calculation method of out to out similitude is as follows:
χs(l1,l2)=1- | N1-N2|/Ns (1)
Wherein N1, N2For maximum line l1, l2The out to out extended to.In conjunction with three kinds of similitudes and it is subject to respective weights
Obtain final similitude.Weight is set according to the significance degree of every difference.Global phase is obtained in conjunction with four Modulus maximum lines
Like property, by the highest modulus maximum lines matching of similitude at one group, thus identify the same smell reach/leave event.
[6] according to the response time difference that four sensors reached/left event to the same smell be calculated smell come
Source directionCalculation method is as follows:
1. establishing dimensional Cartesian coordinates system using tetrahedron central point as co-ordinate zero point, tetrahedral all ribs are expressed as
Vector.
It is minimum in respective Modulus maximum line 2. four sensors reach/leave the response time of event to same smell
Extreme point on scale corresponds to the time.Due to the tetrahedron arrangement mode of sensor, six time differences at most can only be there are two being
Zero, it participates in calculating in order to avoid being equal to the time difference of zero, when finding out maximum three time differences of mould in six time differences composition
Between difference vector:
T=[Δ ti Δtj Δtk]T (2)
3. rib vector corresponding with the time difference is formed matrix:
4. establishing equation group:
5. solution obtains current rate v and olfactory flow directionThen smell source direction
[7] period, return step [2] are executed in next algorithm.
[8] multiple smell source orientation is detected, seeks vector sum as final odor source direction.
Claims (1)
1. a kind of smell source three-dimensional detection method, four smell sensors are arranged in tetrahedral four tops by this method
On point, detection method is as follows:
[1] primary voltage of the higher output of odorousness is lower, the smell of four pieces of sensors acquisition a period of time, when output voltage
Between sequence;
[2] to each smell sensor, the voltage time sequence exported is subjected to continuous wavelet transform, is obtained under multiple scales
Fluctuation signal, negative value indicates the arrival of smell in transformed fluctuation signal, and the corresponding smell of positive value leaves, fluctuation signal
Minimum corresponds to the maximum aggregation rate of smell, and maximum corresponds to the maximum dissipation rate of smell;
[3] modulus maximum for extracting each scale fluctuation signal, establishes Modulus maximum line, in Modulus maximum line, minimum line
Corresponding smell arrival event, maximum line correspond to smell and leave event;
[5] in terms of three define Modulus maximum line similitude: 1) modulus maximum with scale variation tendency;2) extreme point pair
With the variation tendency of scale between seasonable;3) out to out that Modulus maximum line extends;For maximum line l1, l2, the above two phase
Like property χw(l1,l2) and χt(l1,l2) calculated by Pearson correlation coefficient;The similitude of the third party, that is, out to out similitude χs
(l1,l2)=1- | N1-N2|/Ns, wherein N1, N2For maximum line l1, l2The out to out extended to;
In conjunction with three kinds of similitudes and it is subject to respective weights and obtains final global similitude, weight is according to the significant journey of every difference
Degree setting, to identify that the same smell reaches or leave event;
[6] according to the similitude of Modulus maximum line, each Modulus maximum line of four sensors is matched, by global similitude
Highest modulus maximum lines matching reaches or leaves the response of event to find them to same smell at one group;
[7] smell source side is calculated according to the response time difference that four sensors reached or left event to the same smell
Position;
[8] multiple smell source orientation is detected using the method for step [1] to [7], seeks vector sum as final odor source
Direction.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710173931.5A CN107015023B (en) | 2017-03-22 | 2017-03-22 | A kind of smell source three-dimensional detection method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710173931.5A CN107015023B (en) | 2017-03-22 | 2017-03-22 | A kind of smell source three-dimensional detection method |
Publications (2)
Publication Number | Publication Date |
---|---|
CN107015023A CN107015023A (en) | 2017-08-04 |
CN107015023B true CN107015023B (en) | 2019-06-14 |
Family
ID=59439881
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710173931.5A Active CN107015023B (en) | 2017-03-22 | 2017-03-22 | A kind of smell source three-dimensional detection method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN107015023B (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111492234A (en) * | 2018-11-09 | 2020-08-04 | 广东美的白色家电技术创新中心有限公司 | Movable electric device |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101344513A (en) * | 2008-08-26 | 2009-01-14 | 天津大学 | Method for robot searching scent source in time-varying flow field environment |
CN102135530A (en) * | 2010-12-28 | 2011-07-27 | 天津市环境保护科学研究院 | Intelligent rotary-disk random-steering exhausting method |
JP4976792B2 (en) * | 2006-09-14 | 2012-07-18 | 東プレ株式会社 | Centrifugal fan impeller |
CN104360018A (en) * | 2014-10-31 | 2015-02-18 | 天津大学 | Portable gas detection device and method capable of indicating direction of gas source |
CN106295575A (en) * | 2016-08-10 | 2017-01-04 | 天津大学 | A kind of Electronic Nose pre-method of calibration of sampled data based on response curve derivative characteristic |
CN106442879A (en) * | 2016-09-10 | 2017-02-22 | 天津大学 | Detection method for indicating direction of odor source in three-dimensional environment |
CN106444827A (en) * | 2016-09-13 | 2017-02-22 | 武汉科技大学 | Rotor type air-ground integrated amphibious active olfaction robot and odor detection method thereof |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7755360B1 (en) * | 2005-10-24 | 2010-07-13 | Seektech, Inc. | Portable locator system with jamming reduction |
US20160376001A1 (en) * | 2014-06-01 | 2016-12-29 | Robin Felix | Vehicle including a tetrahedral body or chassis |
-
2017
- 2017-03-22 CN CN201710173931.5A patent/CN107015023B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP4976792B2 (en) * | 2006-09-14 | 2012-07-18 | 東プレ株式会社 | Centrifugal fan impeller |
CN101344513A (en) * | 2008-08-26 | 2009-01-14 | 天津大学 | Method for robot searching scent source in time-varying flow field environment |
CN102135530A (en) * | 2010-12-28 | 2011-07-27 | 天津市环境保护科学研究院 | Intelligent rotary-disk random-steering exhausting method |
CN104360018A (en) * | 2014-10-31 | 2015-02-18 | 天津大学 | Portable gas detection device and method capable of indicating direction of gas source |
CN106295575A (en) * | 2016-08-10 | 2017-01-04 | 天津大学 | A kind of Electronic Nose pre-method of calibration of sampled data based on response curve derivative characteristic |
CN106442879A (en) * | 2016-09-10 | 2017-02-22 | 天津大学 | Detection method for indicating direction of odor source in three-dimensional environment |
CN106444827A (en) * | 2016-09-13 | 2017-02-22 | 武汉科技大学 | Rotor type air-ground integrated amphibious active olfaction robot and odor detection method thereof |
Non-Patent Citations (2)
Title |
---|
《Three-Dimensional Odor Compass》;Hiroshi Ishida;《RoboticsandAutomation》;19991231;第15卷(第2期);全文 |
《基于无线传感器网络的气体泄漏源定位机器人设计》;程磊;《传感器与微系统》;20150220;第34卷(第2期);全文 |
Also Published As
Publication number | Publication date |
---|---|
CN107015023A (en) | 2017-08-04 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN101907448B (en) | Depth measurement method based on binocular three-dimensional vision | |
CN105016208B (en) | A kind of two-electron atom bridge crane panning angle measuring devices and methods therefor | |
CN102192927B (en) | Air-quality monitoring system based on electronic nose technique, and monitoring method thereof | |
CN106125548A (en) | Industrial robot kinetic parameters discrimination method | |
CN104299247B (en) | A kind of video target tracking method based on adaptive measuring matrix | |
CN108008099B (en) | Pollution source positioning method | |
CN202443108U (en) | Electric tool switch comprehensive tester | |
CN106442879A (en) | Detection method for indicating direction of odor source in three-dimensional environment | |
CN108844702A (en) | The measuring method of Bridge Influence Line when vehicle at the uniform velocity passes through | |
CN106352879B (en) | A kind of position and orientation estimation method that the UWB positioning based on figure optimization is merged with encoder | |
CN104165742A (en) | Cross spectral function-based operational modal analysis experiment method and apparatus | |
CN107015023B (en) | A kind of smell source three-dimensional detection method | |
CN103633903A (en) | Self-detection method for positions of rotors of switched reluctance motors | |
CN106777893A (en) | A kind of method for recognizing city space multi-pollutant source using removable contamination detector | |
CN102072779A (en) | Rotor-groove harmonic analysis based method for identifying temperature of sensorless rotor for submersible motor | |
CN117590989B (en) | Motor rotating speed online estimation device and method based on neural network | |
CN107681937A (en) | A kind of ultrahigh speed permagnetic synchronous motor speed observation procedure based on neutral net | |
CN116256026B (en) | Health monitoring system of multidimensional splice welding structure under dynamic service working condition | |
CN109753631A (en) | It is a kind of that algorithm is speculated based on the air quality of Active Learning and Kriging regression | |
CN103020598B (en) | A kind ofly carry out knowledge method for distinguishing for attitude variation when people being completed to specific action | |
KR102192141B1 (en) | Apparatus for orientation mapping of multi-axis vibration sensor measurment and Driving mathod thereof | |
CN112893180A (en) | Object touch classification method and system considering friction coefficient abnormal value elimination | |
CN2638074Y (en) | Intelligent three-dimensional magnetic field detector | |
CN107547024B (en) | No speed sensor of no bearing PMSM | |
CN103051275A (en) | Construction method of flux linkage observing device of electric automobile induction motor |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |