CN114354589A - Permanganate index automatic analyzer based on image recognition and analysis method - Google Patents
Permanganate index automatic analyzer based on image recognition and analysis method Download PDFInfo
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Abstract
The invention belongs to the technical field of water quality detection, and particularly relates to an automatic permanganate index analyzer and an analysis method based on image recognition. The automatic analyzer comprises a digestion pipe, a condensation pipe, an image acquisition module, a stirring motor and a data processing module. The method comprises the steps of S1, adding a sample, an oxidant and a catalyst, and digesting to obtain a digestion solution; s2, adding a reducing agent into the digestion solution; s3, performing high-index titration on the digestion solution; s4, collecting a color image of the digestion solution in the titration process; s5, extracting pixel points in the color image, and dividing the colors of the pixel points into chromaticity, saturation and brightness and recording; s6, calculating and judging a titration end point; and S7, measuring the permanganate index of the digestion solution after the titration is finished. The invention has the characteristics of cost saving, strong anti-interference capability and high detection accuracy.
Description
Technical Field
The invention belongs to the technical field of water quality detection, and particularly relates to an automatic permanganate index analyzer and an analysis method based on image recognition.
Background
Permanganate index is a common parameter for surface water stations, and potentiometric and colorimetric methods are generally used.
The potentiometric titration has the advantages of accurate measurement value and strong anti-interference capability; the disadvantages are large waste liquid amount and high cost.
The colorimetric method has the advantages of small waste liquid amount; the defects are that the anti-interference capability is weak, and the digestion tube is easy to scale.
Through the research of the titration method, the whole process of titration is a process of changing colorless into purple, and the color is obviously changed. Therefore, an image identification mode in the field of artificial intelligence is introduced into the titration process, and the end point is judged through the change of the color depth so as to achieve the purpose of measurement.
Therefore, it is very important to design an automatic permanganate index analyzer and an analysis method based on image recognition, which have the advantages of cost saving, strong anti-interference capability and high detection accuracy.
For example, chinese patent document No. CN202011456468.3 describes an online automatic monitoring instrument for permanganate index based on visual identification system, which comprises a measurement body, a sampling quantitative body and an image processing body, wherein the measurement body comprises a digestion reaction bottle, a digestion reaction bracket, an electric heating wire and a water valve component device, the sampling quantitative body comprises a special sampling tube, an infrared quantitative sensor, a water valve set and a peristaltic pump component, the image sampling processing body comprises an industrial color camera, an RGB color sensor and an upper computer AI analysis processing unit, the online automatic monitoring instrument transfers the reagent and the power unit to the measurement body unit for mixing reaction through a water sample link formed by the valve set unit passing through the quantitative unit and then the valve set unit in sequence according to the instruction given by the central control processor, after the camera takes a picture, the picture is transmitted to an AI processing unit of an upper computer through an RGB color sensor, and the result is obtained by analyzing the linearity of color calibration and comparing the colors. Although the measurement accuracy and resolution of the instrument can be greatly improved, the machine error of the original titration method can be effectively reduced, and the measurement stability of the instrument is improved, the visual identification only considers the color difference to realize the online automatic monitoring of the permanganate index, and the measurement accuracy is not limited by the multi-aspect parameters.
Disclosure of Invention
The invention provides an automatic permanganate index analyzer and an automatic permanganate index analysis method based on image recognition, which are cost-saving, strong in anti-interference capability and high in detection accuracy, and aims to solve the problem that the existing detection mode for permanganate indexes in water cannot give consideration to both cost and anti-interference capability in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme:
permanganate index autoanalyzer based on image recognition comprises:
the digestion tube is used for digesting the sample to form digestion liquid;
the condensing pipe is communicated with the digestion pipe and is used for condensing and refluxing the hot steam;
the image acquisition module is used for acquiring a color image of the digestion liquid in the titration process;
the stirring motor is used for stirring the digestion liquid in the digestion pipe;
and the data processing module is used for extracting pixel points in the color image, dividing the colors of the pixel points into chromaticity, saturation and brightness and recording the chromaticity, the saturation and the brightness.
Preferably, the image acquisition module comprises a camera mounting bracket, a camera fixed on the camera mounting bracket and white light lamps fixed on two sides of the camera; the camera and the positive white light lamp are both opposite to the side wall of the digestion tube.
Preferably, a digestion tube bracket is arranged outside the digestion tube.
The invention also provides an automatic permanganate index analysis method based on image recognition, which comprises the following steps:
s1, adding the sample, the oxidant and the catalyst into the digestion pipe in sequence, and digesting to obtain a digestion solution;
s2, adding a reducing agent into the digestion solution;
s3, adding potassium permanganate into the digestion solution to perform high-index titration;
s4, collecting a color image of the digestion solution after each drop of potassium permanganate in the titration process;
s5, extracting pixel points in the color image, dividing the colors of the pixel points into chromaticity, saturation and brightness, and recording the variation of the chromaticity, saturation and brightness of the digestion solution in the titration process;
s6, calculating according to the change of the chroma, saturation and brightness of the digestion solution in the titration process and judging the titration end point;
and S7, measuring the permanganate index of the digestion solution after the titration is finished.
Preferably, the step S4 includes the steps of setting the chromaticity as a, the saturation as B, the brightness as C, the number of drops as D, and the cumulative titration volume as V:
s41, recording the initial chroma A of the digestion solution to be titrated before titration0Initial saturation B0Initial brightness C0；
S42, brightness C0When the concentration is more than 0.8, the titration is started; when the brightness does not satisfy C0If the condition is more than 0.8, the error brightness is insufficient.
Preferably, step S6 includes the steps of:
s61, continuously titrating potassium permanganate, and obtaining the chroma A of the digestion solution after titrating the ith dropiFirst satisfies Ai-A0When the concentration is more than 0.3, ending the titration;
s62, let Δ Ai＝Ai-Ai-1(i＞1)，ΔVi＝Vi-Vi-1(i＞1)；
S63, setting Δ a/Δ V to G, setting the average value of cumulative titration volumes V to H,
then Δ Gi＝Gi-Gi-1(i＞2)，ΔHi＝Hi-Hi-1(i＞2)；
S64, let Δ Ai＝Ai-Ai-1(i＞1)，ΔVi＝Vi-Vi-1(i＞1)；
S65, making delta A/delta V equal to E, making the average value of the average value H of the cumulative titration volume V equal to F,
when E isi*Ei+1<When 0, then (E)i，Fi)，(Ei+1，Fi+1)
The cumulative titration volume at the titration endpoint was:
preferably, step S6 further includes the steps of:
s66, taking Delta AmaxAnd Δ BminCorresponding Δ Ai；
When Δ Ai＝ΔAi+1＝ΔAi+2＝ΔAmaxWhen, take Δ Ai+1The corresponding volume is the cumulative titration volume at the titration end point;
when Δ Ai＝ΔAi+1＝ΔAmaxWhen it is, take Ai、ΔAi+1The median of the corresponding volumes is the cumulative titration volume at the end of the titration.
Preferably, the permanganate index automatic analysis method based on image recognition further comprises the following steps: s8, discharging the digestion solution in the digestion tube and cleaning the liquid flow path.
Compared with the prior art, the invention has the beneficial effects that: (1) the invention introduces an image recognition mode in the field of artificial intelligence into the titration process, and judges the end point through the change of the color depth so as to achieve the purpose of measurement; (2) the invention has the characteristics of cost saving, strong anti-interference capability and high detection accuracy.
Drawings
FIG. 1 is a schematic diagram of a permanganate index autoanalyzer according to the present invention based on image recognition;
FIG. 2 is a flow chart of the digestion solution preparation and titration process of the present invention;
FIG. 3 is a linear relationship diagram of the number of drops and the chromaticity in the titration process of the permanganate index automatic analysis method based on image recognition according to the present invention;
fig. 4 is a flow diagram of an application of the permanganate index autoanalyzer based on image recognition in the present invention.
In the figure: stirring motor 1, clear up a tub support 2, camera 3, positive white light lamp 4, clear up pipe 5, camera installing support 6, condenser pipe 7.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention, the following description will explain the embodiments of the present invention with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
Example 1:
the permanganate index automatic analyzer based on image recognition as shown in fig. 1 comprises:
the digestion tube 5 is used for digesting the sample to form digestion liquid;
the condensing pipe 7 is communicated with the digestion pipe and is used for condensing and refluxing the hot steam;
the image acquisition module is used for acquiring a color image of the digestion liquid in the titration process;
the stirring motor 1 is used for stirring digestion liquid in the digestion pipe;
and the data processing module is used for extracting pixel points in the color image, dividing the colors of the pixel points into chromaticity, saturation and brightness and recording the chromaticity, the saturation and the brightness.
The image acquisition module comprises a camera mounting bracket 6, a camera 3 fixed on the camera mounting bracket and white light lamps fixed on two sides of the camera; the camera and the positive white light lamp are both opposite to the side wall of the digestion tube.
Furthermore, a digestion tube bracket 2 is arranged outside the digestion tube.
Fig. 4 shows a specific application of the permanganate index automatic analyzer based on image recognition in the present invention. In fig. 4, a control valve and a waste liquid pump are also adopted at the liquid outlet end of the digestion pipe.
Based on embodiment 1, as shown in fig. 2, the permanganate index automatic analysis method based on image recognition comprises the following steps:
s1, adding the sample, the oxidant and the catalyst into the digestion pipe in sequence, and digesting to obtain a digestion solution;
s2, adding a reducing agent into the digestion solution;
s3, adding potassium permanganate into the digestion solution to perform high-index titration;
s4, collecting a color image of the digestion solution after each drop of potassium permanganate in the titration process;
s5, extracting pixel points in the color image, dividing the colors of the pixel points into chromaticity, saturation and brightness, and recording the variation of the chromaticity, saturation and brightness of the digestion solution in the titration process;
s6, calculating according to the change of the chroma, saturation and brightness of the digestion solution in the titration process and judging the titration end point;
s7, measuring the permanganate index of the digestion solution after the titration is finished;
s8, discharging the digestion solution in the digestion tube and cleaning the liquid flow path.
Because the high-concentration refers to the process that the reducing agent in the digestion solution is gradually consumed up along with the continuous addition of the potassium permanganate in the titration process, and the solution is gradually changed into pink purple and purple from colorless. The end point is judged by color when the laboratory is manually titrated. At this time, the color is used as the main judgment basis.
According to the actual situation, a part of specific pixel points of the image collected by the camera are extracted, and the color is divided into the chromaticity, the saturation and the brightness.
The chroma is used for representing the change degree of the color; the saturation characterizes the approximate position of the end point; the brightness is used to determine whether the light source is good or bad.
In the titration process, the chroma, saturation and brightness of the digestion solution are recorded for each drop.
Meanwhile, a linear relationship between the number of drops and the chromaticity is established, and the end point is the point where the slope of the curve changes the most, as shown in fig. 3.
Further, setting the chroma as a, the saturation as B, the brightness as C, the number of drops as D, and the cumulative titration volume as V, the step S4 includes the following steps:
s41, recording the initial chroma A of the digestion solution to be titrated before titration0Initial saturation B0Initial brightness C0；
S42, brightness C0When the concentration is more than 0.8, the titration is started; when the brightness does not satisfy C0If the condition is more than 0.8, the error brightness is insufficient.
Further, step S6 includes the following steps:
s61, continuously titrating potassium permanganate, and obtaining the chroma A of the digestion solution after titrating the ith dropiFirst satisfies Ai-A0When the concentration is more than 0.3, ending the titration;
taking the titration drop number as an example of 13 drops, the software records the data as in table 1 below:
table 1 table of the change of the chroma, saturation and brightness of the digestion solution during the titration.
S62, let Δ Ai＝Ai-Ai-1(i＞1)，ΔVi＝Vi-Vi-1(i > 1), the data as in Table 2 below were obtained:
TABLE 2 TABLE 1 corresponding first derivative table
S63, setting Δ a/Δ V to G, setting the average value of cumulative titration volumes V to H,
then Δ Gi＝Gi-Gi-1(i＞2)，ΔHi＝Hi-Hi-1(i > 2) obtaining the data as in Table 3 below;
TABLE 3 TABLE 1 corresponding second derivative table
| Numbering | ΔH | ΔG | ΔG/ | H average | |
| 2 | 10 | 0 | 0 | 10 | |
| 3 | 10 | 0 | 0 | 20 | |
| 4 | 10 | 0 | 0 | 30 | |
| 5 | 10 | 0 | 0 | 40 | |
| 6 | 10 | 0 | 0 | 50 | |
| 7 | 10 | 0 | 0 | 60 | |
| 8 | 10 | 0 | 0 | 70 | |
| 9 | 10 | 0 | 0 | 80 | |
| 10 | 10 | 0.008 | 0.0008 | 90 | |
| 11 | 10 | 0.014 | 0.0014 | 100 | |
| 12 | 10 | -0.016 | -0.0016 | 110 | |
| 13 | 10 | -0.004 | -0.0004 | 120 |
S64, let Δ Ai＝Ai-Ai-1(i＞1)，ΔVi＝Vi-Vi-1(i＞1)；
S65, making delta A/delta V equal to E, making the average value of the average value H of the cumulative titration volume V equal to F,
when E isi*Ei+1<When 0, then (E)i，Fi)，(Ei+1，Fi+1)
The cumulative titration volume at the titration endpoint was:
lowest degree of saturationThe value indicating the color change, the calculated VnShould be at the minimum value of saturation BminAnd Bmin+1Between the corresponding volumes. By means of this check, the error is further reduced.
For special cases, even if V is calculatednAnd not within the verification range.
E.g. some fluctuation of data, resulting in Ei*Ei+1<0 appears in advance. Improved boosting of the algorithm is needed.
For fluctuations in data, resulting in Ei*Ei+1<0, and further, step S6 further includes the following steps:
s66, taking Delta AmaxAnd Δ BminCorresponding Δ AiThe data records are shown in tables 4 and 5 below:
TABLE 4A derivative table
| Numbering | ΔV | ΔA | ΔA/ΔV | V average |
| i-1 | 10 | 0.08 | 0.008 | 95 |
| i | 10 | 0.22 | 0.022 | 105 |
| i+1 | 10 | 0.06 | 0.006 | 115 |
TABLE 5 second derivative table
| Numbering | ΔH | ΔG | ΔG/ΔH | H |
| i | ||||
| 10 | 0.014 | 0.0014 | 100 | |
| i+1 | 10 | -0.016 | -0.0016 | 110 |
When Δ Ai＝ΔAi+1＝ΔAi+2＝ΔAmaxWhen, take Δ Ai+1The corresponding volume is the cumulative titration volume at the titration end point;
when Δ Ai＝ΔAi+1＝ΔAmaxWhen it is, take Ai、ΔAi+1The median of the corresponding volumes is the cumulative titration volume at the end of the titration.
The invention introduces an image recognition mode in the field of artificial intelligence into the titration process, and judges the end point through the change of the color depth so as to achieve the purpose of measurement; the invention has the characteristics of cost saving, strong anti-interference capability and high detection accuracy.
The foregoing has outlined rather broadly the preferred embodiments and principles of the present invention and it will be appreciated that those skilled in the art may devise variations of the present invention that are within the spirit and scope of the appended claims.
Claims (8)
1. Permanganate index autoanalyzer based on image recognition is characterized by comprising:
the digestion tube is used for digesting the sample to form digestion liquid;
the condensing pipe is communicated with the digestion pipe and is used for condensing and refluxing the hot steam;
the image acquisition module is used for acquiring a color image of the digestion liquid in the titration process;
the stirring motor is used for stirring the digestion liquid in the digestion pipe;
and the data processing module is used for extracting pixel points in the color image, dividing the colors of the pixel points into chromaticity, saturation and brightness and recording the chromaticity, the saturation and the brightness.
2. The automatic permanganate index analyzer based on image recognition according to claim 1, wherein the image acquisition module comprises a camera mounting bracket, a camera fixed on the camera mounting bracket and a white light lamp fixed on two sides of the camera; the camera and the positive white light lamp are both opposite to the side wall of the digestion tube.
3. The automatic permanganate index analyzer according to claim 1, wherein a digestion tube support is further arranged outside the digestion tube.
4. The permanganate index automatic analysis method based on image recognition is characterized by comprising the following steps of:
s1, adding the sample, the oxidant and the catalyst into the digestion pipe in sequence, and digesting to obtain a digestion solution;
s2, adding a reducing agent into the digestion solution;
s3, adding potassium permanganate into the digestion solution to perform high-index titration;
s4, collecting a color image of the digestion solution after each drop of potassium permanganate in the titration process;
s5, extracting pixel points in the color image, dividing the colors of the pixel points into chromaticity, saturation and brightness, and recording the variation of the chromaticity, saturation and brightness of the digestion solution in the titration process;
s6, calculating according to the change of the chroma, saturation and brightness of the digestion solution in the titration process and judging the titration end point;
and S7, measuring the permanganate index of the digestion solution after the titration is finished.
5. The automatic permanganate index analysis method according to claim 4, wherein the chroma is A, the saturation is B, the brightness is C, the number of drops is D, the cumulative titration volume is V, and the step S4 comprises the following steps:
s41, recording the initial chroma A of the digestion solution to be titrated before titration0Initial saturation B0Initial brightness C0；
S42, brightness C0When the concentration is more than 0.8, the titration is started; when the brightness does not satisfy C0When the brightness is greater than 0.8, the error-reporting brightness is insufficient。
6. The automatic permanganate index analysis method according to claim 5, wherein the step S6 comprises the following steps:
s61, continuously titrating potassium permanganate, and obtaining the chroma A of the digestion solution after titrating the ith dropiFirst satisfies Ai-A0When the concentration is more than 0.3, ending the titration;
s62, let Δ Ai＝Ai-Ai-1(i＞1)，ΔVi＝Vi-Vi-1(i＞1)；
S63, when Δ a/Δ V is G and the average value of cumulative titration volumes V is H, Δ Gi＝Gi-Gi-1(i＞2)，ΔHi＝Hi-Hi-1(i＞2)；
S64, let Δ Ai＝Ai-Ai-1(i＞1)，ΔVi＝Vi-Vi-1(i＞1)；
S65, making delta A/delta V equal to E, accumulating the average value of the average value H of the titration volume V equal to F, and when E isi*Ei+1<When 0, then (E)i，Fi)，(Ei+1，Fi+1)
The cumulative titration volume at the titration endpoint was:
7. the automatic permanganate index analysis method according to claim 6, wherein the step S6 further comprises the following steps:
s66, taking Delta AmaxAnd Δ BminCorresponding Δ Ai；
When Δ Ai＝ΔAi+1＝ΔAi+2＝ΔAmaxWhen, take Δ Ai+1The corresponding volume is the cumulative titration volume at the titration end point;
when Δ Ai＝ΔAi+1＝ΔAmaxWhen it is, take Ai、ΔAi+1The median of the corresponding volumes is the cumulative titration volume at the end of the titration.
8. The automatic permanganate index analysis method according to claim 4, further comprising the following steps:
s8, discharging the digestion solution in the digestion tube and cleaning the liquid flow path.
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