CN109190715B - β ray dust concentration detecting method based on multi-feature fusion - Google Patents
β ray dust concentration detecting method based on multi-feature fusion Download PDFInfo
- Publication number
- CN109190715B CN109190715B CN201811219228.4A CN201811219228A CN109190715B CN 109190715 B CN109190715 B CN 109190715B CN 201811219228 A CN201811219228 A CN 201811219228A CN 109190715 B CN109190715 B CN 109190715B
- Authority
- CN
- China
- Prior art keywords
- value
- transmitted intensity
- dust concentration
- indicate
- ray
- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/253—Fusion techniques of extracted features
Abstract
The invention discloses a kind of β ray dust concentration detecting methods based on multi-feature fusion, comprising the following steps: S1: building detects computing platform based on Beta-ray dust concentration；S2: the standard deviation value of β transmitted intensity fluctuation data is extracted；S3: the envelope mean value of β transmitted intensity fluctuation data is extracted；S4: fusion standard deviation value and envelope mean value calculate dust concentration to obtain area value.Through the invention, a kind of improved β ray dust concentration detecting method has been obtained, β transmitted intensity has been eliminated and fluctuates the influence detected to dust concentration, improve the detection accuracy of dust concentration.
Description
Technical field
The present invention relates to dust concentration detection technique field, in particular to β ray dust concentration based on multi-feature fusion
Detection method.
Background technique
With the development of society, people are increasing to the attention of environment, wherein the Concentration Testing of dust particle is even more
The most important thing directly affects people's lives quality.Dust concentration detecting method mainly has light scattering method, β ray method and oscillation
Sedimentation balance method.The difference of the measuring principle of detection method will cause the error different from of dust concentration detection accuracy.
β ray method is one of the main method of dust in mine Concentration Testing, is applied to quick, portable direct-reading equipment
On, and the precision that the fluctuation of β transmitted intensity can detect dust concentration to equipment has an impact.
Summary of the invention
Aiming at the problem that fluctuation of β transmitted intensity in the prior art, which will cause dust concentration detection, to be reduced, the present invention provides one
Kind β ray dust concentration detecting method based on multi-feature fusion, the signal characteristic by the way that β transmitted intensity to be fluctuated to data carry out
Fusion obtains the area value for demarcating dust concentration, the precision of β ray dust concentration detecting method is improved, to improve dust
The precision of Concentration Testing.
To achieve the goals above, the present invention provides β ray dust concentration detecting method based on multi-feature fusion, including
Following steps:
S1: building detects computing platform based on Beta-ray dust concentration；
S2: the standard deviation value of β transmitted intensity fluctuation data is extracted；
S3: the envelope mean value of β transmitted intensity fluctuation data is extracted；
S4: fusion standard deviation value and envelope mean value calculate dust concentration to obtain area value.
Preferably, the detection computing platform includes: β ray emission source, filter membrane and detector；
β ray emission source, for emitting β ray, and Beta-ray radiation diameter is 10mm；
The filter membrane, a diameter of 40mm, for filtering the dust in sample gas；
The detector, detection diameter is 20mm, for receiving β ray.
Preferably, the calculation formula of the standard deviation value of the β transmitted intensity fluctuation data are as follows:
In formula (1), S indicates that standard deviation value, N indicate the total number of β transmitted intensity value, XiIndicate that i-th of β ray is strong
Angle value,Indicate the average value of N number of β transmitted intensity value.
Preferably, β transmitted intensity described in the step S3 fluctuation data envelope mean value extraction the following steps are included:
S3-1: the envelope up and down of building β transmitted intensity fluctuation data；
S3-2: the envelope mean value of the envelope up and down of β transmitted intensity fluctuation data is calculated；
S3-3: the envelope mean value of β transmitted intensity is calculated；
Preferably, the calculation formula of the envelope mean value of the β transmitted intensity are as follows:
In formula (2), T indicates the envelope mean value of β transmitted intensity, C1And C2Respectively indicate β transmitted intensity fluctuation envelope mean value
The arithmetic mean of instantaneous value of first data and the second data, σ1And σ2Respectively indicate β transmitted intensity fluctuation the first data of envelope mean value and the
The standard error of two data.
Preferably, in the S4, it is calculated by the following formula dust concentration:
In formula (3), ρΔmIndicate dust concentration, μmIndicate that mass-absorption coefficient, V indicate sample air volume, Gi(x) β is indicated
Transmitted intensity fluctuates the area value of data, and r indicates filter membrane radius.
Preferably, the calculation formula of the area value of the β transmitted intensity fluctuation data are as follows:
In formula (4), Gi(x) indicate that the area value of β transmitted intensity fluctuation data, ∫ indicate integral function, ni(x) the is indicated
The envelope Mean curve of i node, mi(x) the standard deviation value curve of i-th of node, x are indicatedi+1Indicate i+1 node.
In conclusion by adopting the above-described technical solution, compared with prior art, the present invention at least has beneficial below
Effect:
The present invention by fusion β transmitted intensity fluctuate data signal characteristic obtain area value, have high-resolution and
The good linearity, the present invention demarcates dust concentration using the area value of β transmitted intensity fluctuation data, for eliminating β transmitted intensity wave
The dynamic influence detected to dust concentration, dust concentration detection accuracy improve 6.3% or so.
Detailed description of the invention:
Fig. 1 is a kind of β ray dust concentration detection side based on multi-feature fusion according to exemplary embodiment of the present
Method flow diagram.
Fig. 2 is to be based on β ray dust concentration detection platform structural schematic diagram according to one kind of exemplary embodiment of the present.
Fig. 3 is the curve of cyclical fluctuations schematic diagram of β transmitted intensity value.
Fig. 4 is the relationship that different dusts concentration fluctuates that data standard deviation normalizes numerical value with corresponding β transmitted intensity
Schematic diagram.
Fig. 5 is the curve of cyclical fluctuations of β transmitted intensity value and the contrast schematic diagram of envelope Mean curve.
Fig. 6 is that different dusts concentration is shown with the relationship that corresponding β transmitted intensity fluctuates data area value normalization numerical value
It is intended to.
Specific embodiment
Below with reference to embodiment and specific embodiment, the present invention is described in further detail.But this should not be understood
It is all that this is belonged to based on the technology that the content of present invention is realized for the scope of the above subject matter of the present invention is limited to the following embodiments
The range of invention.
Fig. 1 is a kind of β ray dust concentration detecting method based on multi-feature fusion of exemplary embodiment of the present, tool
Body the following steps are included:
S1: building detects computing platform based on Beta-ray dust concentration.
In the present invention, Fig. 2 is the exemplary diagram based on Beta-ray dust concentration detection computing platform of building.The calculating
Platform includes β ray emission source 1, filter membrane 2 and detector 3.
β ray emission source 1, for emitting β ray；Beta-ray radiation diameter is 10mm.
The filter membrane 2, for filtering the dust in sample gas；The diameter of filter membrane 2 is 40mm, this structure is for guaranteeing β ray
Whole penetrate, reduce the error of calculating.
The detector 3, detection diameter are 20mm；After β ray penetrates filter membrane 2, can be emitted on detector 3 from
And TTL pulse signal is excited, detector 3 counts the TTL pulse in 1 second, for characterizing β transmitted intensity fluctuation data
Value；In the present embodiment, the distance between β ray emission source 1 and detector 3 are set as 1cm.
In the present embodiment, when β ray emission source 1 does not emit β ray, the detector 3 is to TTL pulse signal
It counts, then the count value in 1s is 1 or 0, and showing the detector 3, there is no drift fluctuations.
S2: the standard deviation value of β transmitted intensity fluctuation data is extracted.
In the present embodiment, the present invention is based on the dense based on Beta-ray dust concentration detection computing platform acquisition dust of building
The β transmitted intensity value of degree；Filter membrane 2 is penetrated when β ray emission source 1 emits β ray, reaches detector 3 to excite TTL pulse to believe
Number, detector 3 counts pulse signal, and the period of pulse count signal is that the step-by-step counting in 1 second, i.e., 1 second is penetrated for β
Line intensity value.The step-by-step counting that the present invention is carried out continuously N seconds (such as 180 seconds) obtains N number of β transmitted intensity value, and collection is combined into X=
{X1, X2…XN}.As can be seen from Figure 3 there is fluctuation in β transmitted intensity value in the detection process, therefore the present invention calculates and extracts β ray
The standard deviation value S of strength fluctuation data, for demarcating dust concentration.
The extraction calculation formula of standard deviation value S is following formula:
In formula (1), N indicates the total number of β transmitted intensity value, XiIndicate i-th of β transmitted intensity value,Indicate that N number of β is penetrated
The average value of line intensity value.
In the present embodiment, the present invention detects the different powder of computing platform acquisition based on Beta-ray dust concentration by building
The standard deviation value S of the β transmitted intensity fluctuation data of dust concentration；Standard deviation value S is normalized in the present invention, is used for
Intuitively indicate relationship of the different dusts concentration corresponding thereto between standard deviation value S.As can be seen from Figure 4, standard deviation value S
The linearity that curve has had, therefore the standard deviation value of present invention extraction β transmitted intensity fluctuation data is dense for demarcating dust
Degree.
S3: the envelope mean value of β transmitted intensity fluctuation data is extracted.
In the present embodiment, the present invention need to extract the envelope mean value of β transmitted intensity fluctuation, and the envelope mean value is for reducing powder
The calibration resolution of the fluctuation of β transmitted intensity and raising dust concentration in dust concentration detection process.
S3-1: the envelope up and down of building β transmitted intensity fluctuation data.
In the present embodiment, β transmitted intensity signal is twice continuously differentiable function f (x), and section is divided into n+1 node:
x1<x2<···<xn+1, xn+1Indicate (n+1)th node, therefore n-2 cubic spline functions S can be obtained in the present inventioni
(x)；The present invention calculates separately n-2 cubic spline functions Si(x), the maximum e of β transmitted intensity fluctuation data is obtainedmax
(x) and minimum emin(x), to construct the envelope up and down of β transmitted intensity fluctuation data.
Cubic spline functions Si(x) expression formula is following formula:
In formula (2), mi=S " (xi) indicate Si(x) second derivative, hi=xi+1-xiIt is an intermediate computations variable,
Xi+1Indicate i+1 node, f (xi) indicate XiThe function of node.
S3-2: the envelope mean value of the envelope up and down of β transmitted intensity fluctuation data is calculated.
In the present embodiment, the present invention fluctuates the maximum e of data according to β transmitted intensitymax(x) and minimum emin(x), may be used
Obtain the envelope mean value of upper and lower envelope.The β transmitted intensity curve of cyclical fluctuations 4 can with the comparison of envelope Mean curve 5 from Fig. 5
Out, the fluctuation of envelope Mean curve 5 is less than the fluctuation of the β transmitted intensity curve of cyclical fluctuations 4, therefore the present invention is strong using β ray
The envelope mean value of degree demarcates dust concentration.
The envelope mean value computation formula of upper and lower envelope is following formula:
In formula (3), eavg(x) the envelope mean value of envelope up and down, e are indicatedmax(x) and emin(x) packet up and down is respectively indicated
The maximum and minimum of winding thread.
S3-3: the envelope mean value of β transmitted intensity is calculated.
In the present embodiment, the data in the Mean curve of obtained envelope up and down are divided into the first data and by the present invention
Two data calculate the arithmetic mean of instantaneous value C of the first data1With standard error σ1, calculate the arithmetic mean of instantaneous value C of the second data2And standard
Error σ2, finally obtain the envelope mean value T of β transmitted intensity fluctuation data.
S4: fusion standard deviation value and envelope mean value calculate dust concentration to obtain area value.
The standard deviation value S and envelope mean value T of β transmitted intensity fluctuation data are fused to basic β ray powder by the present invention
In dust concentration detection method, for obtaining, a kind of linearity is good, β ray dust concentration detection improvement method of high resolution.
In the present embodiment, the curve of the standard deviation value S of β transmitted intensity fluctuation data of the invention is m (x), and envelope is equal
The curve of value T is n (x), according to spline interpolation principle, [0, xi+1] section is divided into i+1 node: 0=x1<x2<···<xi+1,
xi+1Indicate i+1 node, then the set of two curves is denoted as m (x)={ m respectively1(x), m2(x) ... mi(x) }, n (x)=
{n1(x), n2(x) ... ni(x) }, i >=1 and be positive integer；The present invention is based on merge basic principle for standard deviation value S and envelope
Mean value T is merged, the area value G between calculated curve m (x) and n (x)i(x).Place is normalized to area value in the present invention
Reason is convenient for the intuitive corresponding relationship for showing different dusts concentration and area value.As can be seen from Figure 6, standard deviation value S and packet are merged
The area value G of network mean value Ti(x) linearity having had, for demarcating dust concentration.
In formula (5), Gi(x) indicate that the area value of β transmitted intensity fluctuation data, ∫ indicate integral function, ni(x) the is indicated
The envelope Mean curve of i node, mi(x) the standard deviation value curve of i-th of node, x are indicatedi+1Indicate i+1 node.
1., table implementation different dusts concentration and standard deviation value, envelope mean value, the relationship of area value
As can be known from Table 1, when demarcating dust concentration, area value comparison with standard deviation and envelope mean value are with higher
Resolution ratio.
In the present embodiment, the present invention will be according to obtained area value Gi(x) dust concentration ρ is calculatedΔm, calculation formula is following
Formula:
In formula (6), ρΔmIndicate dust concentration, μmIndicate that mass-absorption coefficient, V indicate sample air volume, Gi(x) β is indicated
Transmitted intensity fluctuates the area value of data, and r indicates filter membrane radius.
Claims (4)
1. β ray dust concentration detecting method based on multi-feature fusion, which comprises the following steps:
S1: building detects computing platform based on Beta-ray dust concentration；
S2: the standard deviation value of β transmitted intensity fluctuation data is extracted；
S3: the envelope mean value of β transmitted intensity fluctuation data is extracted；
S3-1: the envelope up and down of building β transmitted intensity fluctuation data；
S3-2: the envelope mean value of the envelope up and down of β transmitted intensity fluctuation data is calculated；
S3-3: the envelope mean value of β transmitted intensity is calculated；
The calculation formula of the envelope mean value of the β transmitted intensity are as follows:
In formula (1), T indicates the envelope mean value of β transmitted intensity, C1And C2Respectively indicate β transmitted intensity fluctuation envelope mean value first
The arithmetic mean of instantaneous value of data and the second data, σ1And σ2Respectively indicate β transmitted intensity fluctuation the first data of envelope mean value and the second number
According to standard error；
S4: fusion standard deviation value and envelope mean value calculate dust concentration to obtain area value.
2. β ray dust concentration detecting method based on multi-feature fusion as described in claim 1, which is characterized in that described
In S2, the calculation formula of the standard deviation value of the β transmitted intensity fluctuation data are as follows:
In formula (2), S indicates that standard deviation value, N indicate the total number of β transmitted intensity value, XiIndicate i-th of β transmitted intensity value,Indicate the average value of N number of β transmitted intensity value.
3. β ray dust concentration detecting method based on multi-feature fusion as described in claim 1, which is characterized in that described
In S4, it is calculated by the following formula dust concentration:
In formula (3), ρΔmIndicate dust concentration, μmIndicate that mass-absorption coefficient, V indicate sample air volume, Gi(x) β ray is indicated
The area value of strength fluctuation data, r indicate filter membrane radius.
4. β ray dust concentration detecting method based on multi-feature fusion as claimed in claim 1 or 3, which is characterized in that institute
State the calculation formula of the area value of β transmitted intensity fluctuation data are as follows:
In formula (4), Gi(x) indicate that the area value of β transmitted intensity fluctuation data, ∫ indicate integral function, ni(x) it indicates i-th
The envelope Mean curve of node, mi(x) the standard deviation value curve of i-th of node, x are indicatedi+1Indicate i+1 node.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811219228.4A CN109190715B (en) | 2018-10-19 | 2018-10-19 | β ray dust concentration detecting method based on multi-feature fusion |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811219228.4A CN109190715B (en) | 2018-10-19 | 2018-10-19 | β ray dust concentration detecting method based on multi-feature fusion |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109190715A CN109190715A (en) | 2019-01-11 |
| CN109190715B true CN109190715B (en) | 2019-10-18 |
Family
ID=64945672
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811219228.4A Active CN109190715B (en) | 2018-10-19 | 2018-10-19 | β ray dust concentration detecting method based on multi-feature fusion |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109190715B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111323353B (en) * | 2020-04-13 | 2021-03-16 | 中煤科工集团重庆研究院有限公司 | Dust concentration detection system and method based on multi-sensing multi-source data fusion |
| CN113405961B (en) * | 2021-06-21 | 2022-10-14 | 中煤科工集团重庆研究院有限公司 | Dust concentration detection method based on multi-angle light scattering |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101806727A (en) * | 2010-03-02 | 2010-08-18 | 东南大学 | Method and device for measuring sulfur content in coal by ultraviolet absorption spectroscopy |
| CN108211527A (en) * | 2018-01-29 | 2018-06-29 | 付崇沛 | The pre- grading plant and method of high concentrate dust |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100491957C (en) * | 2003-04-16 | 2009-05-27 | 株式会社崛场制作所 | Filtering membrane for trapping granular substance and sampler using same and analyzer for granular substance |
| CN203053899U (en) * | 2012-12-29 | 2013-07-10 | 聚光科技(杭州)股份有限公司 | Detection device of particles and elements |
| CN108645767B (en) * | 2018-05-02 | 2019-08-30 | 华中科技大学 | The method for coupling light scattering and beta-ray measurement coal-fired flue-gas particulate matter quality concentration |
-
2018
- 2018-10-19 CN CN201811219228.4A patent/CN109190715B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101806727A (en) * | 2010-03-02 | 2010-08-18 | 东南大学 | Method and device for measuring sulfur content in coal by ultraviolet absorption spectroscopy |
| CN108211527A (en) * | 2018-01-29 | 2018-06-29 | 付崇沛 | The pre- grading plant and method of high concentrate dust |
Non-Patent Citations (2)
| Title |
|---|
| 基于β射线吸收法的PM2.5连续自动监测的关键技术研究;左健等;《仪表技术与传感器》;20170131(第1期);全文 * |
| 电荷感应法粉尘浓度检测技术;陈建阁;《煤炭学报》;20150331;第40卷(第3期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109190715A (en) | 2019-01-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103675886B (en) | scintillation detector gain control | |
| CN109190715B (en) | β ray dust concentration detecting method based on multi-feature fusion | |
| US7456405B1 (en) | Portable radiation monitor methods and apparatus | |
| KR101730891B1 (en) | Real time continuous radon detector | |
| CN104570047B (en) | Gamma spectroscopy tool is from spectrum-stabilizing device and method | |
| US9417334B2 (en) | Radiation measuring instrument | |
| CN204789249U (en) | High accuracy beta penetrates device of line method on line measurement atmospheric particulates concentration | |
| Jie et al. | Energy calibration of a BC501A liquid scintillator using a γ-γ coincidence technique | |
| CN103176203A (en) | Detector and method for detecting gamma ray and neutron ray synchronously by using same | |
| US8946648B2 (en) | Dual range digital nuclear spectrometer | |
| CN203561610U (en) | Self-calibrated expiration nitrogen monoxide analyzer | |
| CN109781752A (en) | For detecting the enhancing of X-ray digital imagery and quantitative identification method of sleeve grouting defect | |
| Lipka et al. | Resonator for charge measurement at REGAE | |
| US8294894B2 (en) | Particle counter | |
| CN102841366B (en) | Method and system for detecting discrimination threshold of pulse-amplitude discriminator | |
| WO2021120697A1 (en) | Pulse radiation detection circuit and apparatus | |
| Yang et al. | Performance analysis of natural γ-ray coal seam thickness sensor and its application in automatic adjustment of shearer’s arms | |
| JPH03123881A (en) | Method and apparatus for analyzing gamma ray nuclide | |
| Sutton et al. | Proton-proton scattering at 437 MeV | |
| CN113805219A (en) | Radionuclides60Co detection method and detection system | |
| CN111413726B (en) | Radon measuring instrument and calibration method thereof | |
| CN204479045U (en) | A kind of power transmission and transforming equipment corrosion-inhibiting coating gauge strips electrical measurement | |
| CN209783740U (en) | Photon counting device | |
| CN113376679A (en) | Vehicle channel type nuclear security system and device | |
| Holt et al. | An Investigation of (d, p) Stripping Reactions I: Apparatus and Results for Aluminium |
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 |