CN103308516A - Quantitative measurement method for limpidity of emulsified diesel oil - Google Patents

Abstract

The invention discloses a quantitative measurement method for limpidity of emulsified diesel oil. The quantitative measurement method comprises the following steps of: acquiring a gray level image of an oil product; calculating the difference between each row of pixel value and a last row of pixel value in the gray level image of the oil product, so as to obtain a run error figure D of the gray level image f of the oil product; calculating and accumulating a run error figure P; carrying out binaryzation on the accumulated run error figure P, so as to obtain a binaryzation image B of the accumulated run error figure P; extracting possible calibration lines; detecting calibration line regions; calculating a pixel mean value fb of a calibration line region Bf; calculating the pixel mean value of an oil product background region Bg in an oil product image f; and calculating a diversity factor FD. According to the quantitative measurement method disclosed by the invention, a computer is utilized for automatically analyzing and processing the acquired oil product image and finally obtaining a difference value between the pixel mean value of the calibration line region and the pixel mean value of the oil product background region, and by utilizing the difference value as the diversity factor, the limpidity of the oil product can be fast and quantitatively determined. According to the quantitative measurement method, the calculation is simple,the run time is short, and real-time systems can be facilitated.

Description

The clear thoroughly method for quantitative measuring of property of diesel oil emulsification

Technical field

The present invention relates to the clear thoroughly property method for quantitatively determining of a kind of diesel oil emulsification.

Background technology

Along with the economic fast and stable development of China, urbanization and industrialized development process will further be accelerated, each field then increases greatly to the demand of petroleum resources, yet, the growth rate of China oil production is received the restriction of several factors, be significantly less than the growth rate to the oil consumption demand, severe Energy situation will further aggravate the risk of China's oil supply, cause the future period China's oil will face very severe situation safely, so exploitation and the power-saving technology of new forms of energy are most important to China.Micro emulsion diesel fuel reduces diesel consumption as diesel engine and improves a kind of new technology of emission, has effect of micro-explosion, can realize that secondary-atomizing forms more small particle, so that diesel oil can be fully burned, it can increase fuel economy can reduce environmental pollution again, and its application prospect is very wide.

Want the performance of the standby diesel oil emulsification of weight, need to carry out the tests such as power, economy and free Acceleration Smoke, in addition, the clear thoroughly property of the oil product of preparation also is its an important measurement index.At present, mainly as follows for the decision method of the clear thoroughly property of oil product: after oil product prepares, leave standstill a period of time, by the researchist by visual inspection after, provide in appearance whether saturating clearly qualitative conclusion from oil product; When subjective judgement person not simultaneously, the conclusion that provides also has difference, and also can't provide the clear thoroughly quantitative judgement of degree of oil product, thereby, study a kind of method of diesel oil emulsification quantitative measurement, clear property is particularly important thoroughly for judging quickly and accurately oil product.

Summary of the invention

For the defective that exists in the above-mentioned prior art or deficiency, the object of the invention is to, provide a kind of diesel oil emulsification the clear thoroughly method for quantitatively determining of property, the method at first utilizes camera to gather the oil product image, and with oil product image input computing machine, utilize oil product automated image analysis, the processing of computing machine to collecting, finally obtain the difference of the pixel average of the pixel average in calibration line district and oil product background area, with this difference as diversity factor, diversity factor is as the clear thoroughly judgment basis of property quality of oil product, can fast quantification judges the clear thoroughly property of oil product.Calculating of the present invention is simple, working time is short, is adapted at adopting in the real-time system.

In order to achieve the above object, the present invention adopts following technical solution:

The clear thoroughly method for quantitative measuring of property of a kind of diesel oil emulsification is characterized in that, specifically may further comprise the steps:

Step 1: the diesel oil emulsification sample to be measured that will prepare is poured in the clear glass graduated cylinder of not being with scale, draw a black calibration line at a plain pape middle part, take the paper that is decorated with calibration line as background, the graduated cylinder that diesel oil emulsification is housed is carried out the collection of the gray level image of oil product, the black calibration line is remained on the middle part of shooting area during camera as far as possible;

Step 2: with the gray level image f input computing machine of the oil product that collects, the gray level image f size of oil product is M * N, and f (x, y) represents the gray-scale value of pixel (x, y), 1≤x≤M, and 1≤y≤N, x and y are integer; Calculate pixel value poor of every row and its lastrow of the gray level image f of oil product, obtain the poor figure of the row D of the gray level image f of oil product:

$D(x,y)=\left\{\begin{array}{ccc}0& ,& x=\mathrm{1,1}\&le;y\&le;N\\ f(x,y)-f(x-1,y)& ,& 1<x\&le;M,1\&le;y\&le;N\end{array}\right.$ (formula 1);

Wherein, the pixel value f's (x-1, y) of the pixel value f (x, y) of D (x, y) expression pixel (x, y) and its lastrow pixel (x-1, y) is poor;

Step 3: calculate the cumulative poor figure P that goes, namely from the poor accumulated value of scheming D of the capable row of the first row to the x:

$P(x,y)=\left|\underset{i=1}{\overset{x}{\mathrm{\&Sigma;}}}D(i,y)\right|$ (formula 2);

Wherein, the cumulative capable difference of P (x, y) expression pixel (x, y), 1≤x≤M, 1≤y≤N, x and y are integer;

Step 4: the binaryzation of the poor figure of cumulative row P:

Cumulative row difference among the poor figure P of the cumulative row that obtains is thought possible calibration line district greater than the connected region of threshold value T, possible calibration line district all is labeled as 1, other zone all is labeled as 0, namely obtain the binary image B of the poor figure of cumulative row P:

$B(x,y)=\left\{\begin{array}{ccc}1& ,& P(x,y)>T\\ 0& ,& P(x,y)\&le;T\end{array}\right.$ (formula 3);

Wherein, the mark value of B (x, y) expression pixel (x, y); T is threshold value, for 0 ?255 gray level image, T gets 5～15;

Step 5: extract possible calibration line:

To among the binary image B all every trades scanning of advancing, if the x of binary image B capable in, mark value B (x, y) is that the number of 1 pixel satisfies Then think x capable be possible calibration line, then the mark value B (x, y) of all pixels that the x of binary image B is capable all is set to 1, otherwise the mark value B (x, y) of these all pixels of row all is set to 0, wherein, α is constant and 0≤α≤1;

Step 6: the calibration line district is detected:

At first, the mark value of pixel is 1 connected region among the mark binary image B; Secondly, calculate the pixel count of each connected region; At last, the connected region of pixel count maximum is designated as calibration line district Bf, the All Ranges beyond the calibration line district Bf is designated as oil product background area Bg;

Step 7: utilize formula 4 to calculate the pixel average fb of calibration line district Bf:

$\mathrm{fb}=\frac{1}{\mathrm{nBf}}\underset{(x,y)\&Element;\mathrm{Bf}}{\mathrm{\&Sigma;}}f(x,y)$ (formula 4);

Wherein, nBf is the number of pixels of calibration line district Bf;

Step 8: the pixel average ff that calculates oil product background area Bg among the oil product image f:

$\mathrm{ff}=\frac{1}{\mathrm{nBg}}\underset{(x,y)\&Element;\mathrm{Bf}}{\mathrm{\&Sigma;}}f(x,y)$ (formula 5);

Wherein, nBg is the number of pixels of oil product background area Bg;

Step S9: utilize formula 6 to calculate the diversity factor FD of the pixel average of oil product background area Bg and calibration line district Bf:

FD=ff-fb (formula 6).

Further, the black calibration line width in the described step 1 be 1mm ?3mm.

Compare with the clear thoroughly method of property of existing manual observation judgement oil product, method advantage of the present invention is as follows:

1, overcomes the clear thoroughly defective of property of the qualitative observation oil product of traditional artificial naked eyes, got rid of the inconsistency of subjective judgement; Realize the clear thoroughly property of the single oil product of quantitative measurement.

Leave standstill when 2, need not length.In the classic method, oil product prepares the rear time of repose that usually needs about 1-15 days, and method of the present invention only need wait bubble collapse to get final product.

3, thickness, flatness and the status requirement to the shooting environmental of oil product and calibration line is not high.Shooting environmental can make up easily on the one hand; Only require that for calibration line bottom and top that it is not positioned at picture get final product on the other hand.

4, the clear thoroughly property quantitative measurement that the method not only can single oil product also can be used for the clear thoroughly property comparative analysis of a plurality of oil products.

5, simple to operate, travelling speed is fast, for 300 * 200 the oil product image that gathers among the embodiment, at intel cpu2.4GHz, in the computing machine of the internal memory of 1GB, utilize matlab software to carry out emulation, the used time is less than 0.05S, as seen, the method travelling speed is fast.

The present invention is described in further detail below in conjunction with the drawings and specific embodiments.

Description of drawings

Fig. 1 is the clear thoroughly process flow diagram of the method for quantitative measuring of property of diesel oil emulsification of the present invention.

Fig. 2 is the gray level image of each oil product of gathering in the embodiments of the invention, and wherein, Fig. 2 (a) is oil product 1, and Fig. 2 (b) is oil product 2, and Fig. 2 (c) is oil product 3, and Fig. 2 (d) is oil product 4.

Fig. 3 is the result that step S6 calibration line district is detected.The oil product calibration line district Bf of white portion among the figure for detecting, the gray area among the figure is the background area Bg of the oil product of detection.

Embodiment

With reference to Fig. 1, the clear thoroughly method for quantitative measuring of property of diesel oil emulsification of the present invention specifically may further comprise the steps:

Step S1: with diesel oil emulsification sample 30ml to be measured ?40ml pour in the clear glass graduated cylinder of not being with scale; Draw at plain pape middle part a wide 1mm ?the black calibration line of 3mm; As background the graduated cylinder that diesel oil emulsification is housed is carried out the collection of the gray level image of oil product take the paper that is decorated with calibration line; During concrete operations, glass cylinder also can change makees oval vial.The diameter of glass cylinder or oval vial minor axis get 20 ?40mm, the bottle wall thickness be 1 ?2mm.The parameter of glass cylinder among the embodiment: specification is 50ml, and overall height is 195 ± 10mm, and the cylinder external diameter is 25mm.Under white background, lamp environment, take, obtain the gray level image f of oil product; Distance between shooting background and glass cylinder be 30 ?50mm.

Step S2: with the gray level image f input computing machine of the oil product that collects, the gray level image f size of oil product is M * N, f (x, y) expression pixel (x, y) pixel value, because f is the gray level image of oil product, thereby, pixel value f (x, y) also be the gray-scale value of pixel (x, y), i.e. 1≤x≤M, 1≤y≤N, x and y are integer.Calculate pixel value poor of every row and its lastrow of the gray level image f of oil product, obtain the poor figure of the row D of the gray level image f of oil product:

$D(x,y)=\left\{\begin{array}{ccc}0& ,& x=\mathrm{1,1}\&le;y\&le;N\\ f(x,y)-f(x-1,y)& ,& 1<x\&le;M,1\&le;y\&le;N\end{array}\right.$ (formula 1)

Wherein, the pixel value f's (x-1, y) of the pixel value f (x, y) of D (x, y) expression pixel (x, y) and its lastrow pixel (x-1, y) is poor.

Step S3: calculate the poor figure of cumulative row P, namely

$P(x,y)=\left|\underset{i=1}{\overset{x}{\mathrm{\&Sigma;}}}D(i,y)\right|$ (formula 2)

Wherein, the cumulative capable difference of P (x, y) expression pixel (x, y), at once among the poor figure D from the 1st row D (1, y) cumulative to the capable D (x, y) of x, 1≤x≤M, 1≤y≤N, x and y are integer;

Step S4: the binaryzation of the poor figure of cumulative row P:

Cumulative row difference among the poor figure P of the cumulative row that obtains is thought possible calibration line district greater than the connected region of threshold value T, possible calibration line district all is labeled as 1, other zone all is labeled as 0, namely obtain the binary image B of the poor figure of cumulative row P:

$B(x,y)=\left\{\begin{array}{ccc}1& ,& P(x,y)>T\\ 0& ,& P(x,y)\&le;T\end{array}\right.$ (formula 3)

Wherein, the mark value of B (x, y) expression pixel (x, y); T is threshold value, for 0 ?255 gray level image, T gets 5～15 usually, gets 8 in the present embodiment.

Step S5: extract possible calibration line:

To all every trades scannings of advancing among the binary image B of the poor figure of cumulative row P, if the x of binary image B capable in, mark value B (x, y) is that the number of 1 pixel satisfies

Then think x capable be possible calibration line, then the mark value B (x, y) of all pixels that the x of binary image B is capable all is set to 1, otherwise the mark value B (x, y) of these all pixels of row all is set to 0, wherein, α is constant and 0≤α≤1.

Step S6: the calibration line district is detected:

At first, the mark value of pixel is 1 connected region among the mark binary image B; Secondly, calculate the pixel count of each connected region; At last, the connected region of pixel count maximum is designated as calibration line district Bf, the All Ranges beyond the calibration line district Bf is designated as oil product background area Bg.

Step S7: the pixel average of calculating the calibration line district:

Utilize formula 4 to calculate the pixel average fb of calibration line district Bf:

$\mathrm{fb}=\frac{1}{\mathrm{nBf}}\underset{(x,y)\&Element;\mathrm{Bf}}{\mathrm{\&Sigma;}}f(x,y)$ (formula 4)

Wherein, nBf is the number of pixels of calibration line district Bf.

Step S8: the pixel average of calculating the oil product background area:

Calculate the pixel average ff of oil product background area Bg among the oil product image f:

$\mathrm{ff}=\frac{1}{\mathrm{nBg}}\underset{(x,y)\&Element;\mathrm{Bf}}{\mathrm{\&Sigma;}}f(x,y)$ (formula 5)

Wherein, nBg is the number of pixels of oil product background area Bg.

Step S9: calculated difference degree FD:

Utilize formula 6 to calculate the diversity factor FD of the pixel average of oil product background area Bg and calibration line district Bf.Diversity factor FD is used for judging the clear thoroughly property of emulsification oil product to be measured, and diversity factor is larger, and the clear thoroughly property of oil product is just better, otherwise then the clear thoroughly property of oil product is just poorer.

FD=ff-fb (formula 6)

Embodiment:

The inventor is according to above technical scheme of the present invention, four kinds of diesel oil emulsification samples to be measured have been carried out image acquisition, obtain oil product image as shown in Figure 2, size is 300 * 200, and with they input computing machines, utilize computing machine respectively four oil product images to be carried out analyzing and processing, obtain measurement result as shown in table 1.

The quantitative measurement result of four oil product image samples of table 1

As can be seen from Table 1, the diversity factor of oil product 1 is maximum, is 57.8795, and the clear saturating property of this oil product is best; The diversity factor of oil product 2 is taken second place, and is 25.5342; The diversity factor of oil product 3 is 9.0795; The diversity factor of oil product 4 is minimum, is 0, illustrates that the clear saturating property of this oil product is the poorest; Oil product 1 reduces gradually to the diversity factor FD of oil product 4, obtains the conclusion that oil product 1 to the clear thoroughly property of oil product of oil product 4 dies down gradually.Simultaneously, this conclusion has obtained checking from the gray level image of the oil product of Fig. 2, obviously finds out from Fig. 2, and oil product 1 to the clear thoroughly property of oil product of oil product 4 dies down gradually, and this proves absolutely that also the clear thoroughly property method for quantitatively determining of diesel oil emulsification that the present invention proposes is effective.

Claims (2)

1. the clear thoroughly method for quantitative measuring of property of diesel oil emulsification is characterized in that, specifically may further comprise the steps:

Step 1: diesel oil emulsification sample to be measured is poured in the clear glass graduated cylinder of not being with scale, drawn a black calibration line at a plain pape middle part, as background the graduated cylinder that diesel oil emulsification is housed is carried out the collection of the gray level image of oil product take the paper that is decorated with calibration line;

Step 2: with the gray level image f input computing machine of the oil product that collects, the gray level image f size of oil product is M * N, and f (x, y) represents the gray-scale value of pixel (x, y), 1≤x≤M, and 1≤y≤N, x and y are integer; Calculate pixel value poor of every row and its lastrow of the gray level image f of oil product, obtain the poor figure of the row D of the gray level image f of oil product:

$D(x,y)=\left\{\begin{array}{ccc}0& ,& x=\mathrm{1,1}\&le;y\&le;N\\ f(x,y)-f(x-1,y)& ,& 1<x\&le;M,1\&le;y\&le;N\end{array}\right.$ (formula 1);

Wherein, the pixel value f's (x-1, y) of the pixel value f (x, y) of D (x, y) expression pixel (x, y) and its lastrow pixel (x-1, y) is poor;

Step 3: calculate the poor figure of cumulative row P:

$P(x,y)=\left|\underset{i=1}{\overset{x}{\mathrm{\&Sigma;}}}D(i,y)\right|$ (formula 2);

Wherein, the cumulative capable difference of P (x, y) expression pixel (x, y), 1≤x≤M, 1≤y≤N, x and y are integer;

Step 4: the binaryzation of the poor figure of cumulative row P:

Cumulative row difference among the poor figure P of the cumulative row that obtains is thought possible calibration line district greater than the connected region of threshold value T, possible calibration line district all is labeled as 1, other zone all is labeled as 0, namely obtain the binary image B of the poor figure of cumulative row P:

$B(x,y)=\left\{\begin{array}{ccc}1& ,& P(x,y)>T\\ 0& ,& P(x,y)\&le;T\end{array}\right.$ (formula 3);

Wherein, the mark value of B (x, y) expression pixel (x, y); T is threshold value, for 0 ?255 gray level image, T gets 5～15;

Step 5: extract possible calibration line:

To all every trades scannings of advancing among the binary image B of the poor figure of cumulative row P, if the x of binary image B capable in, mark value B (x, y) is that the number of 1 pixel satisfies

Then think x capable be possible calibration line, then the mark value B (x, y) of all pixels that the x of binary image B is capable all is set to 1, otherwise the mark value B (x, y) of these all pixels of row all is set to 0, wherein, α is constant and 0≤α≤1;

Step 6: the calibration line district is detected:

At first, the mark value of pixel is 1 connected region among the mark binary image B; Secondly, calculate the pixel count of each connected region; At last, the connected region of pixel count maximum is designated as calibration line district Bf, the All Ranges beyond the calibration line district Bf is designated as oil product background area Bg;

Step 7: utilize formula 4 to calculate the pixel average fb of calibration line district Bf:

$\mathrm{fb}=\frac{1}{\mathrm{nBf}}\underset{(x,y)\&Element;\mathrm{Bf}}{\mathrm{\&Sigma;}}f(x,y)$ (formula 4);

Wherein, nBf is the number of pixels of calibration line district Bf;

Step 8: the pixel average ff that calculates oil product background area Bg among the oil product image f:

$\mathrm{ff}=\frac{1}{\mathrm{nBg}}\underset{(x,y)\&Element;\mathrm{Bf}}{\mathrm{\&Sigma;}}f(x,y)$ (formula 5);

Wherein, nBg is the number of pixels of oil product background area Bg;

Step S9: utilize formula 6 to calculate the diversity factor FD of the pixel average of oil product background area Bg and calibration line district Bf:

FD=ff-fb (formula 6).

2. the clear thoroughly method for quantitative measuring of property of diesel oil emulsification as claimed in claim 1 is characterized in that, the black calibration line width in the described step 1 be 1mm ?3mm.

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