Online intelligent detection method and detection system for dry concentration in fluid

Abstract

The invention discloses an online intelligent detection method and detection system for dry concentration in fluid. The method comprises the steps that the range of the fly ash concentration is determined, the concentration range is divided into a plurality of type value points based on an arithmetic progression, and a concentration arithmetic progression is generated; correspondingly collecting unit volume weight data of fly ash on the production line pipeline under the concentration based on each type value point; constructing a calibration curve based on the type value points and the unit volume weight of the fly ash; during production, a mixed solute sample of a production line pipeline is extracted, the unit volume weight of fly ash is calculated on line, and the fly ash concentration of a production line is determined based on the calibration curve. The invention aims to provide an on-line intelligent detection method and a detection system for dry concentration in a fluid, and adopts a technical method of obtaining the concentration by pre-experiment to obtain unit volume weight-concentration calibration curve + on-line detection of the unit volume weight of the fluid and comparison of the concentration curve.

Description

Technical Field

[0001] The present invention relates to the technical field of online intelligent detection, and particularly to an online intelligent detection method and detection system for the dry matter concentration in a fluid. Background Art

[0002] Industrial waste gas, especially the high-temperature flue gas discharged from the petrochemical industry, contains various toxic gases, metal compounds and dust, collectively referred to as "fly ash". One of the treatment measures for "fly ash" is to "cool and absorb fly ash with water, and then add a certain amount of other materials to form a pollution-free new building material fluid". This treatment process requires online detection of the "fly ash" concentration in the above-mentioned fluid in order to accurately add fillers and form an accurate formula. It is very difficult to directly detect the fly ash concentration. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide an online intelligent detection method and detection system for the dry matter concentration in a fluid, adopting the technical method of "obtaining the unit volume weight-concentration calibration curve through preliminary experiments + online detecting the unit volume weight of the fluid + comparing with the concentration curve to obtain the concentration".

[0004] According to one aspect of the present invention, there is provided an online intelligent detection method for the dry matter concentration in a fluid, the method comprising: Determine the range of fly ash concentration, divide the concentration range into several type value points based on an arithmetic progression, and generate a concentration arithmetic progression; Based on each type value point, correspondingly collect the unit volume weight data of fly ash on the production line pipeline at this concentration; Construct a calibration curve based on the type value point and the unit volume weight of fly ash; During production, extract a mixed solute sample from the production line pipeline, calculate the unit volume weight of fly ash online, and determine the fly ash concentration of the production line based on this calibration curve.

[0005] In the above technical solution, first, determine the measurement range of fly ash concentration to clarify the object and target of subsequent detection work and ensure the pertinence of the detection process. Based on the division method of an arithmetic progression, divide the concentration range into several type value points. This method is simple, regular, easy to operate and calculate, and can generate a regular concentration arithmetic progression, providing a clear framework for subsequent data collection and calibration curve construction. For each type value point, collect the data of the unit volume weight of fly ash at the corresponding concentration to ensure the accurate correspondence between the data and the concentration point, providing reliable data support for the construction of the calibration curve. By collecting data on the production line pipeline, directly obtain the data of the unit volume weight of fly ash in the actual production process to ensure the practicality and representativeness of the data. Use the type value point data and the unit volume weight data of fly ash to construct a calibration curve, establish a quantitative relationship between fly ash concentration and unit volume weight, and provide a theoretical basis for on-line detection. The calibration curve visually displays the relationship between the two in graphical form, facilitating analysis and judgment by researchers and operators. The real-time on-line detection system can extract samples in real time during the production process, calculate the unit volume weight of fly ash on-line, and obtain fly ash concentration information in a timely manner, providing timely and accurate data support for the control and adjustment of the production process.

[0006] In some embodiments, based on each type value point, correspondingly collect the unit volume weight of fly ash on the production line pipeline at this concentration, specifically including: For each type value point, weigh the fly ash weight at the corresponding concentration to establish a sequence of fly ash weight calibration points; Before the fly ash is sucked and treated into the production line pipeline, weigh the weight of the fluid, construct a weight concentration sequence of fly ash-fluid mixture, and record the volume at the corresponding concentration; Calculate the unit volume weight of fly ash at each concentration point based on the fluid weight and volume.

[0007] In the above technical solution, by accurately weighing the fly ash weight of each type value point, accurate fly ash weight data can be obtained, providing a reliable basis for the subsequent construction of the calibration curve. Establishing a sequence of fly ash weight calibration points helps to systematically manage and analyze data, ensuring the integrity and continuity of the data. At the same time, by weighing the fluid weight and recording the volume at the corresponding concentration, a weight concentration sequence of fly ash-fluid mixture can be constructed. This data correlation method can more comprehensively reflect the actual distribution of fly ash in the fluid. In addition, recording volume data can be used to calculate the unit volume weight, thus more accurately reflecting the concentration distribution of fly ash in the fluid. Based on the data of fluid weight and volume, the unit volume weight of fly ash at each concentration point can be calculated, and then a quantitative relationship between fly ash concentration and unit volume weight can be established.

[0008] In some embodiments, the calibration curve is obtained through regression analysis.

[0009] In the above technical solution, through regression analysis, detailed statistical processing and analysis can be performed on the data, so as to obtain more accurate calibration curve parameters. Compared with some simple methods, regression analysis can better consider the fluctuations and errors in the data. By principles such as the least squares method, the curve is made to be as close as possible to all data points, thereby improving the accuracy and precision of the calibration curve, and further improving the accuracy of fly ash concentration detection.

[0010] In some embodiments, a calibration curve is constructed based on the profile points and the unit volume weight of fly ash. After that, it further includes: According to the extracted mixed fluid sample, measure the sample weight and volume respectively, and calculate the unit volume weight of fly ash; Obtain a preliminary concentration based on the unit volume weight of fly ash, calculate the error based on the comparison between the preliminary concentration and the profile points. If the error is greater than the preset threshold, use the interpolation optimization method to optimize the calibration curve.

[0011] In the above technical solution, by extracting a mixed fluid sample, measuring the sample weight and volume, calculating the unit volume weight of fly ash, and comparing it with the profile points, the error of the calibration curve can be discovered and corrected in a timely manner. This dynamic adjustment mechanism can ensure the accuracy and adaptability of the calibration curve, and improve the reliability and precision of fly ash concentration detection.

[0012] According to another aspect of the present invention, there is provided an on-line intelligent detection system for the dry matter concentration in a fluid. Based on the above method, the system includes: A data acquisition device, which is used to extract a mixed solute sample from the production line pipeline during production, calculate the unit volume weight of fly ash online, and determine the fly ash concentration of the production line based on this calibration curve; A data analysis device, which is used to determine the range of fly ash concentration, divide the concentration range into several profile points based on an arithmetic progression to generate a concentration arithmetic progression; based on each profile point, collect the unit volume weight data of fly ash on the production line pipeline at this concentration correspondingly; construct a calibration curve based on the profile points and the unit volume weight of fly ash.

[0013] In the above technical solution, this system relies on the above devices, and the specific advantages are detailed in the above text.

[0014] In some embodiments, the data acquisition device includes a branch pipeline arranged on one side of the production line pipeline. The branch pipeline is sequentially provided with a first solenoid valve, a flow sensor, a volume sensor, a weight sensor, a counter, a delivery pump, and a second solenoid valve along the flow direction of the fluid.

[0015] In the above technical solution, the data acquisition device realizes a highly automated and integrated data acquisition system by setting a branch pipeline on one side of the production line pipeline and sequentially arranging a first solenoid valve, a flow sensor, a volume sensor, a weight sensor, a counter, a delivery pump, and a second solenoid valve along the flow direction of the fluid. This design can collect key data of the fluid in real time, providing reliable data support for the online detection of fly ash concentration. At the same time, through precise control and integrated design, the reliability and stability of the system are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 is a schematic flowchart of an embodiment of the online intelligent detection method for the dry matter concentration in a fluid of the present invention; Figure 2 is a schematic diagram of an embodiment of the online intelligent detection system for the dry matter concentration in a fluid of the present invention; Figure 3 is a schematic structural diagram of an embodiment of the online intelligent detection system for the dry matter concentration in a fluid of the present invention; Figure 4 is a schematic structural diagram of the data acquisition device in an embodiment of the online intelligent detection system for the dry matter concentration in a fluid of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will further describe the present invention in detail with reference to the drawings and embodiments. It should be particularly noted that the following embodiments are only used to illustrate the present invention, but do not limit the scope of the present invention. Similarly, the following embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0019] The present invention provides an online intelligent detection method and detection system for the dry matter concentration in a fluid, adopting a technical method of "obtaining a unit volume weight-concentration calibration curve through pre-experiment + online detecting the unit volume weight of the fluid + comparing with the concentration curve to obtain the concentration".

[0020] Embodiment 1 Please refer to Figure 1 , an online intelligent detection method for the dry matter concentration in a fluid, the method comprising: S1. Determine the range of fly ash concentration, divide the concentration range into several type value points based on an arithmetic progression, and generate a concentration arithmetic progression. S2. Based on each type value point, collect the unit volume weight data of fly ash on the production line pipeline corresponding to this concentration. S3. Construct a calibration curve based on the type value points and the unit volume weight of fly ash. S4. During production, extract a mixed solute sample from the production line pipeline, calculate the unit volume weight of fly ash online, and determine the fly ash concentration of the production line based on this calibration curve.

[0021] In this embodiment, first, determine the measurement range of fly ash concentration to clarify the object and target of subsequent detection work and ensure the pertinence of the detection process. Based on the division method of arithmetic progression, divide the concentration range into several type value points. This method is simple, regular, easy to operate and calculate, and can generate a regular concentration arithmetic progression, providing a clear framework for subsequent data collection and calibration curve construction. For each type value point, collect the unit volume weight data of fly ash corresponding to the concentration to ensure the accurate correspondence between the data and the concentration point, providing reliable data support for the construction of the calibration curve. By collecting data on the production line pipeline, directly obtain the unit volume weight data of fly ash in the actual production process to ensure the practicality and representativeness of the data. Use the type value point data and the unit volume weight data of fly ash to construct a calibration curve, establish a quantitative relationship between fly ash concentration and unit volume weight, and provide a theoretical basis for on-line detection. The calibration curve visually displays the relationship between the two in graphical form, facilitating analysis and judgment by researchers and operators. The real-time on-line detection system can extract samples in real time during production, calculate the unit volume weight of fly ash online, and obtain fly ash concentration information in a timely manner, providing timely and accurate data support for the control and adjustment of the production process.

[0022] In this embodiment, S2. Based on each type value point, collect the unit volume weight of fly ash on the production line pipeline corresponding to this concentration, specifically including: S21. For each type value point, weigh the fly ash weight corresponding to the concentration and establish a fly ash weight calibration point sequence. S22. Before the fly ash is sucked and processed into the production line pipeline, weigh the weight of the fluid, construct a weight concentration sequence of fly ash-fluid mixture, and record the volume corresponding to the concentration. S23. Calculate the unit volume weight of fly ash at each concentration point based on the fluid weight and volume.

[0023] In this embodiment, by accurately weighing the fly ash weight at each profile point, accurate fly ash weight data can be obtained, providing a reliable basis for the construction of the subsequent calibration curve. Establishing a sequence of fly ash weight calibration points helps to systematically manage and analyze data, ensuring the integrity and continuity of the data. At the same time, by weighing the weight of the fluid and recording the volume at the corresponding concentration, a weight concentration sequence of the fly ash-fluid mixture can be constructed. This data correlation method can more comprehensively reflect the actual distribution of fly ash in the fluid. In addition, recording volume data can be used to calculate the weight per unit volume, thus more accurately reflecting the concentration distribution of fly ash in the fluid. Based on the data of the fluid weight and volume, the fly ash weight per unit volume at each concentration point can be calculated, and then a quantitative relationship between the fly ash concentration and the weight per unit volume can be established.

[0024] In this embodiment, the calibration curve is obtained through regression analysis. Through regression analysis, detailed statistical processing and analysis of the data can be carried out, so as to obtain more accurate calibration curve parameters. Compared with some simple methods, regression analysis can better consider the fluctuations and errors in the data. By principles such as the least squares method, the curve is made to be as close as possible to all data points, thereby improving the accuracy and precision of the calibration curve, and further improving the accuracy of fly ash concentration detection.

[0025] In this embodiment, S3. Based on the profile points and the fly ash weight per unit volume, a calibration curve is constructed, and then it further includes: S31. According to the extracted mixed fluid sample, measure the sample weight and volume respectively, and calculate the fly ash weight per unit volume; S32. Obtain a preliminary concentration based on the fly ash weight per unit volume, calculate the error based on the comparison between the preliminary concentration and the profile points. If the error is greater than the preset threshold, use the interpolation optimization method to optimize the calibration curve. Preferably, use the Newton interpolation algorithm.

[0026] In this embodiment, by extracting a mixed fluid sample, measuring the sample weight and volume, calculating the fly ash weight per unit volume, and comparing it with the profile points, the error of the calibration curve can be detected and corrected in a timely manner. This dynamic adjustment mechanism can ensure the accuracy and adaptability of the calibration curve, and improve the reliability and precision of fly ash concentration detection. Specifically: This embodiment uses the concentration range as the estimated value, and the implementation range ; 1. Online sampling Not less than 5 times and take the average value.

[0027] 2. Match with the calibration curve to obtain the initial value; If the measured concentration value , and the ideal value , there is a certain error, take the detection norm accuracy of the two.

[0028] In the formula, —— A relatively small positive number, given according to the detection accuracy requirements.

[0029] When the above formula holds, it is considered that the test accuracy meets the requirements.

[0030]

[0031] In the formula, represents the qualified measurement value passing the error test, that is, when the above formula holds, is confirmed as the effective value, and is denoted as .

[0032] 3. Perform Newton interpolation between two type value points containing the expected concentration to obtain a more accurate interpolation function (calibration curve); 4. Substitute the random on-line sampled unit volume weight value into the interpolation function to obtain the high-precision final solution as the finally measured result.

[0033]

[0034] In the formula, represents the high-precision final solution, that is, the final solution optimized by steps 3 and 4, with the highest precision, and is used for the output of the final result.

[0035] 5. Comparison of interpolation methods 5.1 Linear interpolation Suppose there are two type value points in space z0(x0, y0, z0), z1(x1, y1, z1), and take a real number , then:

[0036] If the interpolation range is known, any value can be obtained between the two type value points; if the error is non-linear, the error of the linear interpolation result is relatively large.

[0037] 5.2 Polynomial interpolation - Lagrangian interpolation For the function There are n + 1 type value points, x0, x1, x2,......, x n , function series , k = 0, 1, 2.......,n, then:

[0038] If the interpolation error is non-linear, the interpolation function has a high precision - the Lagrangian interpolation has a high precision, but it needs to be recalculated when adding more profile points.

[0039] 5.3 Newton Interpolation For the function There are n+1 profile points, x0, x1, x2,......,x n , the function series , k = 0, 1, 2......., n .

[0040] The function is

[0041] When adding more profile points, the previous calculations are still valid. Comparing linear interpolation and polynomial interpolation, Newton interpolation not only ensures high precision, but also has a simple and practical algorithm. The comparison of actual operations, the Newton interpolation between profile points dp5 and dp6 and the comparison of the effects with linear interpolation and polynomial interpolation: Table 1 Partial Results and Precision Comparison of On-line Detection of Dry Matter Concentration

[0042] To better explain the embodiments of the present invention, the following will be further elaborated: The first step: Take dry fly ash, accurately weigh it, and at the same time, according to the possible concentration range and detection precision requirements, determine the tolerance, design and obtain an arithmetic progression of fly ash weights. Let the possible minimum concentration be , the possible maximum concentration be , divided into groups, then the common difference of the arithmetic progression is:

[0043] Its concentration sequence is , and the arithmetic progression of fly ash weights corresponding to the concentration is .

[0044] The second step: Take the arithmetic progression of weights in the fluid before the fly ash is sucked and processed into the production line pipeline:

[0045] The third step, calculate the weight concentration and record the corresponding volume sequence at the same time:

[0046]

[0047] In the formula, —— The volume of the mixed working fluid containing fly ash and other substances, which is the volume occupied after adding fly ash to the working fluid without fly ash.

[0048] Step 4: Calculate the unit volume weight sequence , and list the corresponding concentrations simultaneously. The volume of the mixed working fluid containing fly ash and other substances.

[0049] Table 2 Unit Volume Weight - Concentration Table

[0050] Obtain the unit volume weight - concentration data within a sufficient concentration range and with sufficient precision and store them in the database.

[0051] Step 5: Through regression analysis, obtain the unit volume weight - concentration equation:

[0052] In the formula, —— The fly ash concentration in the fluid; —— The weight per unit volume of the fluid; —— Two coefficients determined by regression analysis.

[0053] Step 6: Obtain a certain volume of actual fluid from the production line and accurately weigh it with a weight sensor to obtain the weight per unit volume: ; Step 7: Repeat Step 6 three times and take the average value ; Step 8: Through accurate measurement of the weight of the standard volume (measure three times and take the average value), obtain the weight measurement per unit volume; Step 9: Compare the concentration curve corresponding to the weight per unit volume and display the concentration result; Step 10: Pump the obtained production line fluid back to the production line; So far, the accurate detection of the concentration comes from the production line that generates fly ash and the production line that conducts pollution - free treatment of fly ash; the extracted mixed dry matter and the tested fluid are all sent back to the production line.

[0054] Operating conditions: In the production line for treating fly ash to form pollution - free new building materials with a fluid, its production process is to online detect the fly ash concentration in the fluid, and then add materials A, B, and C according to the formula to form a new fluid that meets the requirements and enters the post - treatment process.

[0055] Taking the concentration range of 7% - 13% as an example, appropriately expand the coverage range. Take 5% - 15% and conduct design calculations. Divide it into 30 equal parts to form 30 profile points, that is, 30 type - value points, and the interval between adjacent two points is , such precision is generally sufficient in engineering. The arithmetic progression of concentration is (%): . The corresponding unit volume weight series is (kg / L) .

[0056] V. Specific implementation plan for detection (1) Linear regression analysis (or least squares) to determine k and b , and obtain the regression equation:

[0057]

[0058]

[0059]

[0060] In the formula, —— Fly ash concentration; —— Weight of the fluid per unit volume.

[0061] (2) Online inspection 1) Sampling: Randomly extract 3 - 5 fluids at certain time intervals or at different sections of the production line, with a volume of L i Each sample is not less than 1 liter (volume unit).

[0062] 2) Measurement, precise weighing , and a precision electronic scale can be used to measure the mass of the fluid and take its average value. Considering , then: (15) Calculate the specific gravity (density) - unit volume weight: (16) 3) Compare the regression equation to determine the fly ash density: (17) (3) Add materials A, B, and C in proportion according to the formula and fly ash concentration.

[0063] Example Two Please refer to Figure 2 , an on-line intelligent detection system for the dry matter concentration in a fluid. Based on the method described in Example One, the system includes: A data acquisition device, which is used to extract samples of the mixed solute from the production line pipeline during production, calculate the unit volume weight of fly ash online, and determine the fly ash concentration of the production line based on this calibration curve; A data analysis device is used to determine the range of fly ash concentration, divide the concentration range into several type value points based on an arithmetic progression, and generate a concentration arithmetic progression; collect the unit volume weight data of fly ash on the production line pipeline at each type value point; and construct a calibration curve based on the type value point and the unit volume weight of fly ash.

[0064] A data processing device is used to measure the weight and volume of a mixed fluid sample respectively according to the extracted mixed fluid sample, and calculate the unit volume weight of fly ash; obtain a preliminary concentration based on the unit volume weight of fly ash, calculate the norm accuracy by comparing the preliminary concentration with the type value point, and if the norm accuracy is greater than a preset threshold, optimize the calibration curve using the interpolation optimization method.

[0065] In this embodiment, the system relies on the above device, and the specific advantages are detailed above.

[0066] In this embodiment, please refer to Figure 3 , the data acquisition device includes a branch pipeline arranged on one side of the production line pipeline. The branch pipeline is sequentially provided with a first solenoid valve, a flow sensor, a volume sensor, a weight sensor, a counter, a delivery pump, and a second solenoid valve along the fluid flow direction. By setting a branch pipeline on one side of the production line pipeline and sequentially arranging a first solenoid valve, a flow sensor, a volume sensor, a weight sensor, a counter, a delivery pump, and a second solenoid valve along the fluid flow direction, the data acquisition device realizes a highly automated and integrated data acquisition system. This design can collect key data of the fluid in real time, provide reliable data support for the on-line detection of fly ash concentration, and improve the reliability and stability of the system through precise control and integrated design. Specifically: To determine the fly ash concentration, relying solely on a flow pump and a proportional pump cannot effectively solve the problem. The present invention uses the concept of concentration, adopts weight concentration, collects fly ash, and weighs it precisely , and also precisely weighs water or fluid without fly ash , to prefabricate a precise concentration:

[0067] At the same time, obtain the volume of the mixed working fluid corresponding to this concentration and weight , so as to obtain the refined weight per unit volume:

[0068] Make a series according to an arithmetic progression Yes, measure the volume and weight of the working fluid online, obtain the actual weight per unit volume of the production line, and further obtain the corresponding concentration.

[0069] Please refer to Figure 3, on the production line, directly intercept a certain volume of the working fluid and accurately weigh it to obtain the weight per unit volume. To obtain accurate results, the online measurement of a certain concentration value can be increased from averaging 3 measurements to 5 measurements. The corresponding calculation is as follows:

[0070] The weight per unit volume of the production line is:

[0071] An online weighing load cell is used, and the online volume calculation can be done by the following method.

[0072] Select a liquid level photoelectric sensing float; set the vertical movement of the float in the designed container to form; when the liquid level rises to a specified height such as 3L (volume), the light shines on the float, and a signal is obtained - the production line working fluid stops flowing into the detection system, and the PLC controller instructs the solenoid valve 1 to act - lock. The logic diagrams of Example 1 and Example 2 are as Figure 4 shown.

[0073] The above are only some embodiments of the present invention, and thus do not limit the protection scope of the present invention. Any equivalent device or equivalent process transformation made using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall similarly be included in the patent protection scope of the present invention.

Claims

1. An online intelligent detection method for dry matter concentration in a fluid, characterized in that: The method comprises: Determine the range of fly ash concentration, divide the concentration range into several type value points based on the arithmetic progression, and generate the concentration arithmetic progression; Based on each value point, the fly ash unit volume weight data on the production line pipeline at the corresponding concentration is collected; A calibration curve is constructed based on the type value points and the unit volume weight of fly ash; During production, mixed solute samples are drawn from the production line pipeline, the unit volume weight of fly ash is calculated online, and the fly ash concentration of the production line is determined based on the calibration curve.

2. The method for online intelligent detection of dry matter concentration in a fluid as claimed in claim 1, characterized in that: Based on each value point, the unit volume weight of fly ash collected on the production line pipeline at the corresponding concentration includes: For each type value point, weigh the fly ash at the corresponding concentration and establish a fly ash weight calibration point sequence; Before the fly ash is vacuumed and processed into the production line pipeline, the fluid weight is weighed, the weight concentration sequence of the fly ash-fluid mixture is constructed, and the volume at the corresponding concentration is recorded; The unit volume weight of fly ash at each concentration point is calculated based on the fluid weight and volume.

3. The method for online intelligent detection of dry matter concentration in a fluid as claimed in claim 1, characterized in that: The calibration curve is obtained by regression analysis.

4. The method for online intelligent detection of dry matter concentration in a fluid as claimed in claim 1, characterized in that: The calibration curve is constructed based on the type value point and the unit volume weight of fly ash, followed by: According to the mixed fluid samples drawn, the sample weight and volume are measured respectively, and the unit volume weight of fly ash is calculated; A preliminary concentration is obtained based on the unit volume weight of the fly ash, and the norm accuracy is calculated based on the comparison between the preliminary concentration and the type value point. If the norm accuracy is greater than a preset threshold, the interpolation optimization method is used to optimize the calibration curve.

5. An online intelligent detection system for dry matter concentration in fluid, characterized in that: Based on the method according to any one of claims 1 to 4, the system comprises: A data acquisition device is used to extract mixed solute samples from the production line pipeline during production, calculate the unit volume weight of fly ash online, and determine the fly ash concentration of the production line based on the calibration curve; The data analysis device is used to determine the range of fly ash concentration, divide the concentration range into a number of type value points based on an arithmetic progression, and generate a concentration arithmetic progression; based on each type value point, correspondingly collect the unit volume weight data of fly ash on the production line pipeline at the concentration; and construct a calibration curve based on the type value points and the unit volume weight of fly ash.

6. An online intelligent detection system for dry matter concentration in fluid as claimed in claim 5, characterized in that: The data acquisition device includes a branch pipeline arranged on one side of the production line pipeline, and the branch pipeline is provided with a first solenoid valve, a flow sensor, a volume sensor, a weight sensor, a counter, a delivery pump, and a second solenoid valve in sequence along the flow direction of the fluid.

7. An online intelligent detection system for dry matter concentration in fluid as claimed in claim 5, characterized in that: Based on each type value point, the unit volume weight of fly ash collected on the production line pipeline at the corresponding concentration specifically includes: For each type value point, weigh the fly ash at the corresponding concentration and establish a fly ash weight calibration point sequence; Before the fly ash is vacuumed and processed into the production line pipeline, the fluid weight is weighed, the weight concentration sequence of the fly ash-fluid mixture is constructed, and the volume at the corresponding concentration is recorded; The unit volume weight of fly ash at each concentration point is calculated based on the fluid weight and volume.

8. An online intelligent detection system for dry matter concentration in fluid as claimed in claim 5, characterized in that: The calibration curve is obtained by regression analysis.

9. The on-line intelligent detection system for dry matter concentration in fluid as claimed in claim 5, characterized in that: The system further comprises: a data processing device; The device is used to measure the weight and volume of the sample according to the extracted mixed fluid sample, and calculate the unit volume weight of the fly ash; A preliminary concentration is obtained based on the unit volume weight of the fly ash, and the norm accuracy is calculated based on the comparison between the preliminary concentration and the type value point. If the norm accuracy is greater than a preset threshold, the interpolation optimization method is used to optimize the calibration curve.

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