CN110532511A - It is a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method - Google Patents
It is a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method Download PDFInfo
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Abstract
The invention belongs to a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method, to the dust image of several groups normal concentration gradient, carry out the calculating of gray scale-order co-occurrence matrix and rotary inertia, the mathematical model between dust concentration and rotary inertia is constructed, dust concentration is measured by the mathematical model.Change the present invention is based on measurement accuracy vulnerable to global atmosphere light and the interference of atmosphere light scattering effect caused and the interference of dust particles occlusion effect；For the precision for improving visual method powder concentration measurement, this motion proposes the calculation method of gray scale-order co-occurrence matrix and its Characteristic inertia from global face domain textural characteristics；And dust concentration is levied using rotary inertia as indirect scale, the mathematical model between dust concentration and rotary inertia is constructed, realizes the powder concentration measurement of higher precision.
Description
Technical field
The present invention relates to the technical fields of powder concentration measurement method, are related to a kind of based on gray scale-order co-occurrence matrix rotation
The powder concentration measurement method of inertia.
Background technique
Powder concentration measurement method can be divided into off-line measurement and on-line measurement two major classes.Dust concentration off-line measurement method essence
Degree is high, but such method operating process is cumbersome, and face domain measurement ability is limited, realizes that visual analyzing is hindered.Dust concentration
It is fast that on-line measurement method detects speed, but there are measurement accuracy vulnerable to interference, measurement method is complicated and the limitation such as expensive, still needs to
Further research.It will be carried out below to the state of the art of the most similar Videogrammetry (belonging to On-line Measuring Method) of this motion
It illustrates.
Dust particles are under visual apparatus with itself morphological feature, gray feature, scattering signatures etc., vision hair utilization
Measuring system obtains the characteristics of image realization powder concentration measurement that can characterize dust concentration in dust concentration image.
Visual method has the not high characteristic of intuitive, non-contact, easy to operate, cost, additionally being total to vision system
Property, such as TB grades of data storage capacity, it can be realized production scene history big data on-line analysis, it can also be integrated with other sensors
The many kinds of parameters of production process is acquired to complete the detection and monitoring of production scene multi-parameter, this is that other measurement methods do not have
Standby feature.Visual method is advantageously implemented one of industrial automation, and measurement application field technological trend, wide at present
It is general to be used for the fields of measurement such as military affairs, agricultural, but it is few in research achievement of powder concentration measurement field application, just in development
The grade stage.
The powder concentration measurement fado of view-based access control model method utilizes the gray feature or morphological feature of dust image, passes through foundation
Mathematical model between feature and dust concentration, the final on-line measurement for realizing dust concentration.
1) gray feature
Characteristic feature of the gray feature as dust concentration, can be for statistical analysis to dust image from the overall situation, establishes
Functional relation between dust concentration and gray scale, the final real-time measurement for realizing dust concentration.
Grasa G etc. has found that particle phase volume fraction and gray value of image are in logarithmic function relationship, can be realized according to gray value
Powder concentration measurement.Obreg ó n L etc. first calculates the image threshold in light tone region and dark areas, then calculates image averaging gray scale
Difference between value and threshold value constructs the logarithmic model on Grasa model basis for solving dust concentration.
Using gray feature measurement dust concentration can avoid dust image in dust particles overlapping interference, but only consider into
The influence that the occlusion effect of dust forms dust image is penetrated, without considering what atmosphere light scattering effect formed dust image
It influences, continually changing overall situation atmosphere light will affect atmosphere light scattering to influence the gray feature of dust image, measurement essence
Spend the leeway being still improved.
2) morphological feature
Using the morphological feature of dust particles in dust image, such as partial size, surface area, volume, form factor feature, build
Vertical dust concentration and mathematical relationship between it, it can be achieved that dust concentration measurement.
Liu Hongli etc. is by matching dust particles and partial size, form factor, the fractal dimension of standard dust particle to be measured etc.
Form parameter selects approximate test dust particles volume and density as dust particles volume to be measured and density, unit of account body
The quality of all types particulate matter obtains dust concentration in product.Due to dust particles have occlusion effect will lead to measurement accuracy by
To interference.Zhang Chenyu etc. is to improve measurement accuracy, the influence using scattering integral method research grain diameter to measurement accuracy.Experiment
The results show that calculate scattering angle using scattering integral method still can measure dust concentration in the case where not calculating partial size, but
Its measurement error is within 15%.
Dust concentration is characterized using morphological feature, can avoid the light-initiated atmosphere light scattering effect of continually changing global atmosphere
Measurement accuracy is interfered.But dust particles have adhesiveness, and particle overlapping phenomenon can cause occlusion effect to interfere
The extraction of morphological feature influences dust concentration precision.Therefore the measurement of the morphological feature measurement dust concentration of dust particles is utilized
Method, still wait be further improved.
Summary of the invention
The interference of atmosphere light scattering effect for changing the present invention is based on measurement accuracy vulnerable to global atmosphere light and causing, and
The interference of dust particles occlusion effect；For the precision for improving visual method powder concentration measurement, this motion is from global face domain textural characteristics
It sets out, proposes the calculation method of gray scale-order co-occurrence matrix and its Characteristic inertia；And dust is levied using rotary inertia as indirect scale
Concentration constructs the mathematical model between dust concentration and rotary inertia, realizes the powder concentration measurement of higher precision.
The technical solution adopted by the invention is as follows: it is total to carry out gray scale-order to the dust image of several groups normal concentration gradient
The calculating of raw matrix and rotary inertia, constructs the mathematical model between dust concentration and rotary inertia, is surveyed by the mathematical model
Measure dust concentration；The following steps are included:
S1: the dust image of acquisition several groups normal concentration gradient；
S2: gray scale-order co-occurrence matrix is carried out to the dust image of S1 and is calculated, comprising the following steps:
(1) regularization order matrix M is obtained to dust image procossing,
(2) dust image normalizing and quantification treatment are obtained into regularization gray matrix F,
(3) gray scale-order co-occurrence matrix H is established by regularization order matrix M and regularization gray matrix F and gray scale-order is total
The Probability Forms P of raw matrix；
S3: the calculating for bringing the gray scale in S2-order co-occurrence matrix Probability Forms P the rotary inertia of dust image into is public
Formula obtains rotary inertia accumulation and S；
S4: by the rotary inertia acquired in S3 accumulation and S and with the dust graphics standard concentration in S1, be fitted using data
Method establishes the mathematical model c (s) between dust concentration and rotary inertia accumulation and S；
S5: the mathematical model c (s) in S4 is brought in rotary inertia accumulation and S by tested dust image into, obtains tested dust
The dust concentration of image.
Further, rotary inertia is the measurement of inertia when dust is around origin rotation in gray scale-order co-occurrence matrix, is depended on
The Mass Distribution and rotating shaft position of dust itself.
Further, regularization order matrix M are as follows:
Ω (x, y) is the child window that the size centered on the position (x, y) is w in formula, and R () is to seek order operator, and N () is
Normalize operator, LMFor the order quantization level of M, LMLess than or equal to w.
Further, regularization gray matrix F are as follows:
F=N (I) × LI
L in formulaIFor the grey level quantization rank of I, LILess than or equal to gray level 256.
Further, gray scale-order co-occurrence matrix H:
H (i, j) | I (x, y)=i, G (x, y)=j }
In formula, i=0,1,2 ..., LI- 1, j=0,1,2 ..., LM-1.Element H (i, j) in H is regularization regularization order
Meet the pixel sum of gray value i and rank value j in matrix M and dust gray level image F jointly.
Further, gray scale-order co-occurrence matrix Probability Forms P are as follows:
Further, in S3 rotary inertia accumulation sum calculation formula are as follows:
Wherein P (i, j) characterizes dust quality at (i, j), and i and j characterize the vertical and horizontal distance between origin respectively.Powder
Dust concentration is bigger, gray scale-order co-occurrence matrix rotary inertia accumulation and it is bigger.
Further, in S4 dust concentration and rotary inertia accumulation and between mathematical model are as follows:
C (s)=k1s3+k2s2+k3s+k4
Wherein c be dust measurement concentration, s be surveyed dust image rotary inertia accumulate with, k1, k2, k3 and k4 are respectively
Medium coefficient related with dust type, the coefficient of k1, k2, k3 and k4 mathematical model between c and s, for different types of powder
Dirt, the mathematical model between c and s are also different.K1, k2, k3 and k4 are the coefficient for the mathematical model being fitted by data, meeting
Change with dust type and changes.
While dust concentration marking apparatus measures dust normal concentration, gray scale-order of corresponding dust gray level image is calculated
Co-occurrence matrix Probability Forms and its rotary inertia accumulation and.The result shows that being using rotary inertia accumulation and measurement dust concentration
It is feasible.Dust concentration and the gray level in Dust distribution section in gray scale-order co-occurrence matrix are positively correlated, i.e., concentration is bigger,
The gray level of distributed area is bigger；Concentration and rotary inertia are accumulated and are positively correlated, i.e., concentration is bigger, rotary inertia accumulation and
It is bigger.The corresponding rotary inertia accumulation of the dust normal concentration surveyed based on dust concentration marking apparatus and, it is quasi- using data
It is legal, establish dust concentration and rotary inertia accumulation and between mathematical model, and then the dust for calculating tested dust image is dense
Degree.
Beneficial effects of the present invention:
1) measurement accuracy of the invention increases, and relative error narrows down to ± 9%, and reason is to introduce better face
Standard of the domain textural characteristics as dust concentration；
2) measuring range of the invention increases, and is 0.5~1000mg/m3, reason is to be used when model of fit
The dust concentration range for being fitted sample is wider；
3) present invention can avoid the interference of dust particles overlapping in dust image using gray feature measurement dust concentration, together
When consider the influence that is formed to dust image of atmosphere light scattering effect, a kind of higher powder concentration measurement side of measurement accuracy is provided
Method.
Detailed description of the invention
Fig. 1 is algorithm flow chart of the invention.
Specific embodiment
Technical effect in order to further illustrate the present invention is specifically described the present invention below by embodiment.
Embodiment 1
It is a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method, comprising the following steps:
S1: the dust image of acquisition several groups normal concentration gradient；
S2: gray scale-order co-occurrence matrix is carried out to the dust image of S1 and is calculated, gray scale-order co-occurrence matrix probability shape is obtained
Formula；Regularization order matrix M obtained to the carry out operation of dust gray level image I, then by dust gray level image I normalizing and quantification treatment
Regularization gray matrix F is obtained, is obtained in gray scale-order co-occurrence matrix H, H by regularization order matrix M and regularization gray matrix F
Element H (i, j) be to meet the picture of gray value i and rank value j in regularization regularization order matrix M and dust gray level image F jointly
Vegetarian refreshments sum, finally finds out gray scale-order co-occurrence matrix Probability Forms P:
Wherein P (i, j) characterizes dust quality at (i, j), and i and j characterize the vertical and horizontal distance between origin respectively.
Wherein regularization order matrix M:
Ω (x, y) is the child window that the size centered on the position (x, y) is w in formula, and R () is to seek order operator, and N () is
Normalize operator, LMFor the order quantization level of M, LMLess than or equal to w.
Regularization gray matrix F:
F=N (I) × LI
L in formulaIFor the grey level quantization rank of I, LILess than or equal to gray level 256.
Gray scale-order co-occurrence matrix H:
H (i, j) | I (x, y)=i, G (x, y)=j }
In formula, i=0,1,2 ..., LI- 1, j=0,1,2 ..., LM-1。
S3: the rotary inertia of dust image is calculated based on the gray scale in S2-order co-occurrence matrix Probability Forms, is rotated
Inertia accumulation and；The calculation formula of gray scale-order co-occurrence matrix rotary inertia accumulation sum are as follows:
Wherein P (i, j) characterizes dust quality at (i, j), and i and j characterize the vertical and horizontal distance between origin respectively.Turn
Dynamic inertia is the measurement of inertia when dust is around origin rotation in gray scale-order co-occurrence matrix, the Mass Distribution depending on dust itself
And rotating shaft position.Dust concentration is bigger, gray scale-order co-occurrence matrix rotary inertia accumulation and it is bigger.
S4: the corresponding rotary inertia of the normal concentration based on dust image is accumulated and using data fitting method, is established
Dust concentration and rotary inertia accumulation and between mathematical model；
The dust normal concentration of multiple gradients is measured by dust concentration marking apparatus, while calculating corresponding dust gray level image
Gray scale-order co-occurrence matrix and its rotary inertia accumulation and, the results showed that using rotary inertia accumulate and measure dust concentration be
It is feasible.Dust concentration and the gray level in Dust distribution section in gray scale-order co-occurrence matrix are positively correlated, i.e., concentration is bigger,
The gray level of distributed area is bigger；Concentration and rotary inertia are accumulated and are positively correlated, i.e., concentration is bigger, rotary inertia accumulation and
It is bigger.The corresponding rotary inertia accumulation of the dust normal concentration surveyed based on dust concentration marking apparatus and, it is quasi- using data
It is legal, establish dust concentration and rotary inertia accumulation and between mathematical model, the mathematical model are as follows:
C (s)=k1s3+k2s2+k3s+k4
Wherein c be dust measurement concentration, s be surveyed dust image rotary inertia accumulate with, k1, k2, k3 and k4 are respectively
Medium coefficient related with dust type, the coefficient of k1, k2, k3 and k4 mathematical model between c and s, for different types of powder
Dirt, the mathematical model between c and s are also different.K1, k2, k3 and k4 are the coefficient for the mathematical model being fitted by data, meeting
Change with dust type and changes.
S5: carrying out the calculating of gray scale-order co-occurrence matrix and rotary inertia to tested dust image, obtains tested dust image
Rotary inertia accumulation and, the mathematical model in S4 is accumulated and brought into the rotary inertia of tested dust image, measures tested powder
The dust concentration of dirt image.
Established model is utilized to calculate test sample dust concentration, measurement concentration and normal concentration are compared such as 1 institute of table
Show.
1 test sample testing result of table
The corresponding rotary inertia accumulation of the dust normal concentration for the more gradients surveyed based on dust concentration marking apparatus and,
Using data fitting method, establish dust concentration and rotary inertia accumulation and between mathematical model.To tested dust image through ash
The calculating of degree-order co-occurrence matrix and rotary inertia, the rotary inertia for obtaining tested dust image are accumulated and bring the mathematical modulo into
Type measures the dust concentration of tested dust image.
Measurement accuracy of the invention compares Conventional visual method with measuring range and is improved.It can be seen from Table 1 that originally mentioning
For the detection method measurement error of case within ± 9%, measuring range is 0.5~1000mg/m3。
Finally, it should be noted that the above examples are only used to illustrate the technical scheme of the present invention rather than limits, although ginseng
Technical solution of the present invention is described in detail according to preferred embodiment, it will be appreciated by those skilled in the art that can be to this
The technical solution of invention is modified or replaced equivalently, and without departing from the purpose and scope of the invention, should all be covered at this
In the protection scope of invention.
Claims (10)
1. a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method, which is characterized in that normal concentration
The dust image of gradient carries out the calculating of gray scale-order co-occurrence matrix and rotary inertia, constructs between dust concentration and rotary inertia
Mathematical model measures dust concentration by the mathematical model.
2. it is according to claim 1 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, comprising the following steps:
S1: the dust image of acquisition several groups normal concentration gradient；
S2: gray scale-order co-occurrence matrix is carried out to the dust image of S1 and is calculated, comprising the following steps:
(1) regularization order matrix M is obtained to the dust image procossing of S1,
(2) the dust image normalizing and quantification treatment of S1 are obtained into regularization gray matrix F,
(3) gray scale-order co-occurrence matrix H and gray scale-order symbiosis square are established by regularization order matrix M and regularization gray matrix F
The Probability Forms P of battle array；
S3: the gray scale in S2-order co-occurrence matrix Probability Forms P is brought into the calculation formula of the rotary inertia of dust image, is obtained
To rotary inertia accumulation and S；
S4: by data fitting method, establish rotary inertia obtained in S3 accumulation and S and with the dust graphics standard concentration in S1
Between mathematical model c (s)；
S5: the mathematical model c (s) in S4 is brought in rotary inertia accumulation and S by tested dust image into, obtains tested dust image
Dust concentration.
3. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, the rotary inertia is the measurement of inertia when dust is around origin rotation in gray scale-order co-occurrence matrix.
4. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, regularization order matrix M are as follows:
Ω (x, y) is the child window that the size centered on the position (x, y) is w in formula, and R () is to seek order operator, and N () is normalizing
Change operator, LMFor the order quantization level of M, LMLess than or equal to w.
5. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, regularization gray matrix F are as follows:
F=N (I) × LI
L in formulaIFor the grey level quantization rank of I, LILess than or equal to gray level 256.
6. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, gray scale-order co-occurrence matrix H are as follows:
H (i, j) | I (x, y)=i, G (x, y)=j }
In formula, i=0,1,2 ..., LI- 1, j=0,1,2 ..., LM-1。
7. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, the element H (i, j) in H is to meet gray value i jointly in regularization regularization order matrix M and dust gray level image F
With the pixel sum of rank value j.
8. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, gray scale-order co-occurrence matrix Probability Forms P are as follows:
9. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, the calculation formula of rotary inertia accumulation sum in S3 are as follows:
Wherein P (i, j) characterizes dust quality at (i, j), and i and j characterize the vertical and horizontal distance between origin respectively.
10. it is according to claim 2 a kind of based on gray scale-order co-occurrence matrix rotary inertia powder concentration measurement method,
It is characterized in that, in S4 dust concentration and rotary inertia accumulation and between mathematical model are as follows:
C (s)=k1s3+k2s2+k3s+k4
Wherein c is dust measurement concentration, s be tested dust image rotary inertia accumulation and, k1, k2, k3 and k4 are respectively and powder
The related medium coefficient of dirt type.
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| CN114627140A (en) * | 2022-05-16 | 2022-06-14 | 新风光电子科技股份有限公司 | Coal mine ventilator intelligent adjusting method based on high-voltage frequency converter |
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Application publication date: 20191203 |
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| RJ01 | Rejection of invention patent application after publication |