A method and device for quickly detecting equivalent mud content of concrete aggregate

Abstract

The invention relates to the technical field of concrete aggregate detection, and specifically provides a method and a device for rapid detection of equivalent mud content of concrete aggregate. The invention determines the spectral absorption rate of mud powder with specific mineral composition and chemical composition to methylene blue by a spectral absorption method, and uses the spectral absorption rate as a calibration value to determine the equivalent of mud powder in actual aggregate equivalent to standard mud powder. The spectral absorption detection method avoids the subjective error caused by naked eye observation, and the accurate value of the equivalent mud content detected can also be used as a basis for adjusting the mix ratio due to the use of aggregates with different mud contents to produce concrete. At the same time, spectral absorption, edge computing, the Internet of Things, artificial intelligence, concrete materials and other related technologies are applied, and optical detection and Internet of Things big data technology are integrated to realize rapid detection of equivalent mud content of concrete aggregate and predictive control and adjustment of the influence of harmful clay particle content in aggregate on concrete working performance.

Description

Technical Field

[0001] The invention belongs to the technical field of concrete aggregate detection, and particularly relates to a method and a device for quickly detecting equivalent mud content of concrete aggregate. Background Art

[0002] Both coarse and fine aggregates (sand and gravel) used in concrete contain microparticles, which generally refer to particles with a particle size of less than or equal to 75μm, which is roughly equivalent to the particle size range of cement, mineral admixtures and other powders, but its properties are different from those of powders and do not have hydration. Microparticles are composed of stone powder and mud powder. Stone powder is a fine particle formed by weathering or crushing of primary minerals (rocks), which has little adverse effect on the properties of concrete mixtures, and its filling property has a certain improvement effect on the performance of concrete mixtures; mud powder is a secondary mineral (clay minerals and oxide minerals formed by chemical or biological action of primary minerals) particles, which has a great adverse effect on the properties of concrete mixtures. The greater the mud content of aggregates, the greater the amount of admixtures used in concrete production, the greater the slump loss, and significantly affects the performance of concrete mixtures; the greater the mud content of aggregates, the more water is used for concrete mixing, the greater the risk of concrete hardening and cracking, and the lower the strength and durability of concrete after hardening.

[0003] Concrete is the most widely used and largest amount of engineering material in civil engineering. The proportion of sand and gravel in concrete is the largest, generally 70%~80%. Due to the large demand for concrete materials in engineering construction, sand and gravel resources, especially natural sand resources, are becoming increasingly scarce, and the quality of natural sand is also getting worse. The most noteworthy is its high mud powder content. In order to solve the problem of scarce natural sand resources, solid waste resources such as machine-made sand or tailings and recycled sand have been widely used in concrete production. The biggest problem to be solved in the rational and effective use of these resources is still the detection and control of mud powder content. In order to reduce the mud content of machine-made sand, water washing and other processes are generally used, which consumes a lot of water resources. When the sand is washed too clean, the encapsulation and cohesion of the slurry will deteriorate, affecting the performance of the concrete mixture. Therefore, the detection and control of mud content in fine aggregate is the most concerned technical and quality problem in the concrete and mortar industry.

[0004] Clay minerals in clay and clayey rocks are mainly hydrated layered silicate minerals with fine crystal particles and chemical components mainly composed of aluminum, magnesium and iron. Clay minerals have a layered structure, swelling properties, interlayer and surface adsorption of polycarboxylic acid admixtures, and strong affinity for organic matter. Therefore, the adsorption of free water and polycarboxylic acid admixtures by clay minerals is the main reason for the loss of fluidity of concrete mixtures. The more typical clay minerals are montmorillonite, illite and kaolin. In the laboratory, the adsorption of free water and polycarboxylic acid admixtures by typical clay minerals can be quantitatively studied to establish the relationship between the content of typical clay minerals and the performance of concrete mixtures. However, the composition of clay minerals in sand and gravel aggregates is relatively complex and varies with their sources. They are mixed minerals with large fluctuations in the content of multiple minerals. Therefore, in actual concrete production, detecting and analyzing the content of variable mixed clay minerals in aggregates and their influence has become a technical problem for aggregate quality detection and monitoring.

[0005] At present, the national standard usually adopts the MB value method to determine the stone powder content of fine aggregate (sand). The main test steps are to take a sand test sample and pour it into distilled water, stirring it continuously to make a mud powder suspension, and then drip a standard methylene blue solution into the suspension in a single amount of 5 mL multiple times (depending on the test situation, each drip should be stirred for 1 minute before testing). Until the suspension can show a color halo on the filter paper that lasts for more than 5 minutes, record the total volume of methylene blue solution added at this time, and calculate the MB value according to the formula.

[0006] Existing invention 1: CN116559162B - A method for quickly determining the MB value of sand material based on image recognition technology, which combines image recognition technology to establish a mapping between the color of the methylene blue halo on the filter paper and the spectral absorbance and concentration of methylene blue measured by a spectrophotometer, and directly quantitatively determines the residual amount of methylene blue in the sample suspension by image color recognition. This test method does not change the process of testing the MB value by titration, so the detection process of a single sample is not much different from the traditional method, the detection efficiency is slow, and the detection accuracy of the MB value is low.

[0007] Existing invention 2: CN113848185B-A sand MB value testing system and method, using a laser emitter and a light intensity sensor, through different light intensities passing through different test samples, to detect the sand MB value, simplifying the MB value testing process, shortening the test time, and changing the original test method that relies on the test results of the test personnel's subjective judgment with the naked eye. Since the test principle is based on the change of light intensity, there is a certain error in the test, and the final test result is still the sand MB value, which is not quantified into mud content data. This indicator cannot effectively characterize the adsorption size of harmful clay particles in the sand, and cannot provide targeted guidance for the adjustment and control of the mix ratio and working performance in the concrete production process.

[0008] Patent CN111721893B proposes a method for determining the composition and content of clay minerals contained in mud powder in sand. By determining the MB value of test sand containing different amounts of stone powder and mud powder, the dynamic influence relationship between stone powder, mud powder and MB value is established with the same linear regression equation. By drawing a linear regression curve and combining chemical analysis and testing technology, the clay mineral composition contained in the mud powder in the sand sample to be tested can be qualitatively determined. On this basis, quantitative calculation is performed in combination with the regression equation. Compared with the existing technology, this method can more accurately and rigorously obtain the composition and content of clay minerals contained in the mud. Patent CN217112099U proposes a detection device for the MB value of machine-made sand, including a control console, a reaction chamber, a stirring blade, a motor, a titration mechanism, a liquid outlet pipe, etc., which is an optimization and improvement of the original titration method for detecting MB value. Patent CN215005004U proposes a test device for automatically detecting the MB value of machine-made sand, including a bracket and a cup body placed on the bracket, a stirring mechanism is provided in the cup body, a filter paper placement table is provided on the bracket, a color halo recognition camera is located above the filter paper placement table, a methylene blue solution storage device for quantitatively supplying liquid to the cup body, and a liquid collection mechanism hand for taking liquid from the cup body and dropping it on the filter paper on the filter paper placement table, which can realize automatic detection of the MB value of machine-made sand.

[0009] Most of this series of patents and methods have only optimized and improved the traditional method of detecting MB value to improve detection efficiency and accuracy, or optimized the traditional detection method process, but none of them has achieved the quantification of the content of harmful clay minerals in concrete aggregates, the characterization and predictive analysis of the impact of clay particles in aggregates on the working performance of concrete, and none of them has built a real-time dynamic analysis device and its system based on the Internet of Things consisting of spectral absorption detection equipment, data processing and analysis terminals, and digital intelligence middle platforms. Summary of the invention

[0010] In view of the deficiencies in the prior art, the present invention aims to provide a method and device for quickly detecting the equivalent mud content of concrete aggregates, so as to solve the problems raised in the above-mentioned background technology.

[0011] To achieve the above object, the present invention provides the following technical solution: a method for quickly detecting the equivalent mud content of concrete aggregate, comprising the following steps:

[0012] Step 1: Select mud powder standard samples: Select representative materials as standard mud powder, and use their equivalent values ​​to represent the content of mud powder in different regions and with different mineral components;

[0013] Step 2: Define equivalent mud content: divide primary mineral stone powder into two categories: siliceous stone powder and calcareous stone powder, and divide secondary mineral mud powder into three categories: kaolin, montmorillonite, and illite. Then select mud powder with universal mineral composition and chemical composition as standard mud powder, and use its equivalent value to represent the size and influence of the adsorption of fine particles in different fine aggregates. The formula model is as follows:

[0014]

[0015] In the formula, Equivalent mud content (%); is the mineral composition coefficient of siliceous stone powder; is the mineral composition coefficient of calcareous stone powder; is the mineral composition coefficient of kaolin; is the mineral composition coefficient of illite; is the mineral composition coefficient of montmorillonite; is the content of siliceous stone powder (%); is the content of calcareous stone powder (%); is the kaolin content (%); is illite content (%); is the montmorillonite content (%);

[0016] Step 3: Establish a spectral absorption rate relationship model: Pass the spectrum with a wavelength of 610nm through the methylene blue solution, at this time the spectral absorption rate is A0, mix the standard mud powder and the methylene blue solution evenly, and filter the mixed suspension, pass the spectrum with a wavelength of 610nm through the standard mud powder filtered solution, at this time the spectral absorption rate is ;

[0017]

[0018] In the formula, Spectral absorbance; Incident light intensity; Transmitted light intensity; Molar absorptivity (L·mol -1 cm -1 ); Substance concentration (mol·L -1 ); Liquid layer thickness (cm);

[0019] The photoelectric sensor is used to convert the spectral absorbance signal into an electrical signal to test the spectral absorbance data of standard mud powder filtrate with different contents and the benchmark methylene blue solution;

[0020] The relationship between the photoelectric signals of the standard mud powder sample filtrate solution and the reference methylene blue solution was obtained in the experiment. The correlation model R 2It can reach 97.4%. The simplified model of the relationship between standard mud powder content and photoelectric signal is:

[0021]

[0022] In the formula, Equivalent mud content (%); Spectral absorption coefficient; Spectral absorbance; Spectral absorption constant;

[0023] Step 4: Use the detection device to detect the equivalent mud content of the fine aggregate to be tested: first, dry the fine aggregate to be tested to constant weight, screen out particles larger than 2.36 mm, take 20g of the fine aggregate to be tested and add it to 30mL of 0.5‰ concentration of methylene blue solution, mix evenly to make a suspension, filter the suspension with a 0.22μm filter, take 0.6g of the filtered solution, and dilute it to 30mL with distilled water, add the diluted solution to the test solution vessel for testing, put the reference solution and the test solution into the host test box respectively for testing, and after the equipment data is processed and analyzed, the equivalent mud content data is displayed on the display and automatically uploaded to the digital intelligence center;

[0024] Step 5: Data upload to the digital intelligence center: After a quick test by the detection device, the data is analyzed by edge computing module and IoT signal transmission module and uploaded to the cloud. Data is downloaded from the cloud to the digital intelligence center for display. At the same time, the data is stored for quality analysis and combined with the concrete working performance data for correlation iterative learning to complete the detection.

[0025] Preferably, the standard mud powder minerals are divided into non-clay minerals and clay minerals, wherein the non-clay minerals include: quartz 10.1%, potassium feldspar 14.3%, plagioclase 30.4%, mica 39.3%, and amphibole 2.3%; the clay minerals include: kaolinite 0.2%, illite 2.1%, montmorillonite 1.2%, and chlorite 0.1%. The main chemical components and percentages of the standard mud powder are as follows: O is 44.42%, Si is 24.48%, Al is 13.97%, C is 8.26%, Mg is 0.91%, Na is 1.20%, Fe is 3.30%, and Ca is 1.96%.

[0026] A rapid detection device for equivalent mud content of concrete aggregates, comprising a mounting base plate and a housing, wherein a light source, a test solution vessel, a 610nm filter glass, a photoelectric sensor and a power supply module are fixedly mounted on the top of the mounting base plate from right to left in sequence, and an edge computing module and an Internet of Things signal transmission module are also arranged on the top of the mounting base plate;

[0027] The shell is fixedly connected to the mounting base plate, a light-shielding closed sliding cover is movably provided on one side of the shell and directly above the test solution vessel, a control panel is also provided on the front surface of the shell, and a display, a test switch button, a networking switch button and a WiFi data transmission indicator light are sequentially provided on the control panel.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. The spectrum absorption principle is used to replace manual naked eye observation, which improves the efficiency and accuracy of clay particle detection in concrete aggregates;

[0030] 2. Define standard mud powder, complete the calibration of standard mud powder mineral and chemical composition, and use equivalent mud content instead of traditional MB value as a technical indicator to characterize the adsorption and influence of clay particles in concrete aggregate;

[0031] 3. Define the relationship between the standard mud powder equivalent mud content and two primary minerals (siliceous stone powder, calcareous stone powder) and three secondary minerals (kaolin, illite, montmorillonite), and use the equivalent mud content value to characterize the complex and diverse mineral composition in fine aggregate and its influence on concrete performance;

[0032] 4. Establish a relationship model between equivalent mud content and spectral absorbance, and quickly obtain the equivalent mud content data of aggregate through spectral detection;

[0033] 5. Utilize IoT edge computing technology and big data technology to upload the test results of equivalent mud content of concrete aggregate to the digital intelligence platform. This can not only save and record the test data, but also serve as a basis for adjusting the concrete production mix ratio, thereby comprehensively improving the concrete quality control capabilities and reducing concrete quality fluctuations. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is an internal structure diagram of a device for quickly detecting equivalent mud content of concrete aggregates according to the present invention;

[0035] Figure 2 This is an external structural diagram of a device for quickly detecting equivalent mud content of concrete aggregates according to the present invention;

[0036] Figure 3 A flow chart for establishing the model in step 3 of the method of the present invention;

[0037] Figure 4 This is a flow chart for detecting the equivalent mud content of fine aggregate in step 4 of the method of the present invention;

[0038] Figure 5 This is the flow chart of uploading the equivalent mud content to the digital intelligence platform in step 5 of the method of the present invention.

[0039] Figure 1 and Figure 2 In: 1. Installation base plate; 2. Housing; 3. Control panel; 4. Light source; 5. Test solution container; 6. 610nm filter glass; 7. Photoelectric sensor; 8. Power supply module; 9. Edge computing module and IoT signal transmission module; 10. Shading closed slide cover; 11. Display; 12. Test switch button; 13. Network switch button; 14. WiFi data transmission indicator light. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below through embodiments and in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0041] Refer to the following Figure 1-Figure 5 A method and device for quickly detecting equivalent mud content of concrete aggregate provided in one embodiment of the present application will be described.

[0042] like Figure 1-2 As shown: Combining spectral absorption technology, photoelectric signal conversion technology, edge computing technology, concrete production technology and Internet of Things technology, the present invention designs a rapid detection device for equivalent mud content of concrete aggregate, including a mounting base plate 1 and a housing 2, a light source 4, a test solution container 5, a 610nm filter glass 6, a photoelectric sensor 7 and a power supply module 8 are fixedly installed on the top of the mounting base plate 1 from right to left in sequence, and an edge computing module and an Internet of Things signal transmission module 9 are also provided on the top of the mounting base plate 1;

[0043] The shell 2 is fixedly connected to the mounting base plate 1, and a light-shielding closed sliding cover 10 is movably provided on one side of the shell 2 and directly above the test solution container 5. A control panel 3 is also provided on the front surface of the shell 2, and a display 11, a test switch button 12, a network switch button 13 and a WiFi data transmission indicator light 14 are sequentially provided on the control panel 3. The above device integrates spectral absorption measurement, equivalent mud content analysis and calculation, and electronic screen display.

[0044] A method for quickly detecting the equivalent mud content of concrete aggregate comprises the following steps:

[0045] Step 1: Select mud powder standard samples: First, select representative materials as standard mud powder. Standard mud powder is universal and can represent the content of mud powder with different mineral components in different regions by its equivalent value. The mineral composition of standard mud powder is shown in Table 1, and the relative content of chemical composition is shown in Table 2:

[0046] Table 1 Standard mud powder mineral composition

[0047]

[0048] Table 2 Main chemical components of standard mud powder / %

[0049] ;

[0050] Step 2: Define equivalent mud content: Fine particles smaller than 75 μm in concrete aggregate have a great influence on the performance of concrete. The mineral composition of these fine particles is very complex, including primary minerals such as quartz, mica, and calcite, as well as secondary minerals such as kaolin, montmorillonite, illite, and chlorite. The MB value method currently used can only qualitatively evaluate whether the fine particles below 75 μm in concrete fine aggregate are mainly primary minerals or secondary minerals, and their specific content and influence cannot be known. In fact, there are significant differences in the adsorption of fine particles of different mineral components. According to the different adsorption of particles, the present invention divides the primary mineral stone powder into two categories: siliceous stone powder (mainly quartz) and calcareous stone powder (mainly limestone), and divides the secondary mineral mud powder into three categories: kaolin, montmorillonite, and illite. Then, mud powder with universal mineral composition and chemical composition is selected as standard mud powder, and its equivalent value represents the size of the adsorption of fine particles in different fine aggregates and its influence. The formula model is as follows:

[0051]

[0052] In the formula, Equivalent mud content (%); is the mineral composition coefficient of siliceous stone powder; is the mineral composition coefficient of calcareous stone powder; is the mineral composition coefficient of kaolin; is the mineral composition coefficient of illite; is the mineral composition coefficient of montmorillonite; is the content of siliceous stone powder (%); is the content of calcareous stone powder (%); is the kaolin content (%); is illite content (%); is the montmorillonite content (%);

[0053] Step 3: Establish a spectral absorbance relationship model: Specifically, establish a spectral absorbance relationship model (Clay-Model) between the benchmark methylene blue solution and the standard mud powder sample filtered solution: Methylene blue is an azo-type cationic industrial colored dye that is easily soluble in water. The aqueous solution of methylene blue is blue, and its colored ions are positively charged. When the spectrum with a wavelength of 610nm passes through the methylene blue solution, its spectrum will be partially absorbed. At this time, the spectral absorbance is A0. After the standard mud powder and the methylene blue solution are evenly mixed, the methylene blue colored ions will be adsorbed by the clay particles in the standard mud powder. The mixed suspension is filtered and the spectrum with a wavelength of 610nm is passed through the standard mud powder filtered solution. At this time, the spectral absorbance is A. According to Lambert-Beer's law:

[0054]

[0055] In the formula, Spectral absorbance; Incident light intensity; Transmitted light intensity; Molar absorptivity (L·mol -1 cm -1 ); Substance concentration (mol·L -1 ); Liquid layer thickness (cm);

[0056] Spectral absorbance The value of is affected by the clay particle content. When the clay particle content is high, the concentration of colored ions in the filtered solution decreases and the spectral absorbance The photoelectric sensor is used to convert the spectral absorbance signal into an electrical signal to test the spectral absorbance data of standard mud powder filtrate with different contents and the benchmark methylene blue solution. The flow chart is as follows Figure 3 As shown;

[0057] The relationship between the photoelectric signals of the standard mud powder sample filtrate solution and the reference methylene blue solution was obtained in the experiment. The correlation model R 2 It can reach 97.4%. The simplified model of the relationship between standard mud powder content and photoelectric signal is:

[0058]

[0059] In the formula, Equivalent mud content (%); Spectral absorption coefficient; Spectral absorbance; Spectral absorption constant;

[0060] Step 4: Use the detection device to test the equivalent mud content of the fine aggregate to be tested: the test personnel first dry the fine aggregate to be tested to constant weight, screen out particles larger than 2.36mm, take 20g of the fine aggregate to be tested and add it to 30mL of 0.5‰ concentration of methylene blue solution, mix them evenly to make a suspension, filter the suspension with a 0.22μm filter, take 0.6g of the filtered solution, and dilute it to 30mL with distilled water. Add the diluted solution to the test solution vessel for testing, put the reference solution and the test solution into the host test box respectively for testing. After the equipment data is processed and analyzed, the equivalent mud content data is displayed on the display and automatically uploaded to the digital intelligence center. The flow chart is as follows Figure 4 As shown;

[0061] Step 5: Upload data to the digital intelligence platform: Figure 5As shown, after a quick test by the detection device, edge computing analysis is performed through the edge computing module and the IoT signal transmission module, and the data is uploaded to the cloud. The data is downloaded from the cloud to the digital intelligence platform for display. At the same time, the data is stored for quality analysis, and the correlation iterative learning is performed in combination with the concrete working performance data to complete the detection.

[0062] Combined with the above embodiments, the working process of a method and device for rapid detection of equivalent mud content of concrete aggregates of the present application is summarized as follows:

[0063] In response to the problems existing in the existing technologies and inventions, combined with the two core technical problems of concrete aggregate mud content detection and its influence on the working performance of concrete that urgently need to be optimized in the current civil engineering materials field, the present invention applies spectral absorption, edge computing, Internet of Things, artificial intelligence, concrete materials and other related technologies, and integrates optical detection and Internet of Things big data technology. It solves the current difficult problems of low efficiency and inaccuracy in concrete aggregate mud content detection, and the test results cannot be used as a basis for adjusting the concrete production mix ratio in the production process. It realizes the rapid detection of the equivalent mud content of concrete aggregate and the predictive control and adjustment of the influence of harmful clay particle content in aggregate on the working performance of concrete.

[0064] First, the test method is innovated based on the principle of spectral absorption. A 610nm wavelength spectrum is selected. After the 610nm wavelength spectrum is irradiated through the test solution, part of the spectrum is absorbed, and the spectral signal is received by the photoelectric sensor and transmitted to the edge computing device. The spectral absorbance value of the sample can be calculated by the edge computing device and compared with the benchmark 5‰ concentration of methylene blue solution, so as to obtain the spectral absorbance ratio of the test sample.

[0065] Afterwards, standard clay powder was selected to establish an equivalent clay content model (Clay-Model). In view of the complex and diverse mineral composition and chemical composition of clay particles in concrete aggregates, representative standard clay powder was selected as the standard test material, and the spectral absorbance values ​​of standard clay powder solutions with different contents and benchmark methylene blue solutions were tested to establish a correlation model (Clay-Model). The equivalent clay content of standard clay powder is used to characterize the content of two typical primary minerals and three typical secondary minerals. According to the spectral absorbance photoelectric signal conversion data of different test samples, the equivalent clay content model is used to uniformly convert the fine particle content in any natural sand, machine-made sand or reclaimed sand into the standard clay powder equivalent clay content value.

[0066] Finally, after obtaining the data on the equivalent mud content of different concrete aggregates, it is transmitted to the digital intelligence platform through the Internet of Things information technology to store and analyze the concrete aggregate detection data, providing data support for concrete production mix adjustment and working performance quality control.

[0067] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should be included in the scope of the claims of the present invention.

Claims

1. A method for rapid detection of equivalent mud content of concrete aggregate, characterized in that: The following steps are involved: Step 1: Select mud powder standard sample and define equivalent mud content: divide primary mineral stone powder into two categories: siliceous stone powder and calcareous stone powder, and divide secondary mineral mud powder into three categories: kaolin, montmorillonite and illite. Then select mud powder with universal mineral composition and chemical composition as standard mud powder, and use its equivalent value to represent the adsorption of fine particles in different fine aggregates. The formula model is as follows: In the formula, Equivalent mud content, %; is the mineral composition coefficient of siliceous stone powder; is the mineral composition coefficient of calcareous stone powder; is the mineral composition coefficient of kaolin; is the mineral composition coefficient of illite; is the mineral composition coefficient of montmorillonite; is the content of siliceous stone powder, %; is the content of calcareous stone powder, %; is the kaolin content, %; is illite content, %; is the montmorillonite content, %; Step 2: Establish a spectral absorbance relationship model: pass the spectrum with a wavelength of 610nm through the reference methylene blue solution, at this time the spectral absorbance is A0, uniformly mix the standard mud powder and the reference methylene blue solution, and filter the mixed suspension, pass the spectrum with a wavelength of 610nm through the standard mud powder filtered solution, at this time the spectral absorbance is A, and obtain the spectral absorbance relationship model between the reference methylene blue solution and the standard mud powder sample filtered solution according to the Lambert-Beer law; The photoelectric sensor is used to convert the spectral absorbance signal into an electrical signal, and the spectral absorbance data of standard mud powder filtrate with different contents and the reference methylene blue solution are tested; The relationship between the photoelectric signals of the standard mud powder sample filtrate solution and the reference methylene blue solution was obtained in the experiment. The correlation model R 2 It can reach 97.4%. The simplified model of the relationship between standard mud powder content and photoelectric signal is: In the formula, Equivalent mud content, %; Spectral absorption coefficient; Spectral absorbance; Spectral absorption constant; Step 3: Use the detection device to detect the equivalent mud content of the fine aggregate to be tested: first, dry the fine aggregate to be tested to constant weight, screen out particles larger than 2.36 mm, take 20g of the fine aggregate to be tested and add it to 30mL of 0.5‰ concentration of methylene blue solution, mix evenly to make a suspension, filter the suspension with a 0.22μm filter, take 0.6g of the filtered solution, and dilute it to 30mL with distilled water, add the diluted solution to the test solution vessel for testing, put the reference methylene blue solution and the test solution into the host test box respectively for testing, after the equipment data is processed and analyzed, the equivalent mud content data is displayed on the display and automatically uploaded to the digital intelligence center; Step 4: Data upload to the digital intelligence center: After a quick test by the detection device, the data is analyzed by edge computing module and IoT signal transmission module and uploaded to the cloud. Data is downloaded from the cloud to the digital intelligence center for display. At the same time, the data is stored for quality analysis and combined with the concrete working performance data for correlation iterative learning to complete the detection.

2. The method according to claim 1, characterized in that: Standard mud powder minerals are divided into non-clay minerals and clay minerals, among which non-clay minerals include: quartz 10.1%, potassium feldspar 14.3%, plagioclase 30.4%, mica 39.3%, amphibole 2.3%; clay minerals include: kaolinite 0.2%, illite 2.1%, montmorillonite 1.2%, chlorite 0.1%. The main chemical components and percentages of standard mud powder are as follows: O is 44.42%, Si is 24.48%, Al is 13.97%, C is 8.26%, Mg is 0.91%, Na is 1.20%, Fe is 3.30%, and Ca is 1.96%.

3. A device for rapid detection of concrete aggregate equivalent mud content, using the method for rapid detection of concrete aggregate equivalent mud content according to claim 1, characterized in that: It includes a mounting base plate and a housing, wherein a light source, a test solution vessel, a 610nm filter glass, a photoelectric sensor and a power supply module are fixedly mounted on the top of the mounting base plate from right to left in sequence, and an edge computing module and an Internet of Things signal transmission module are also arranged on the top of the mounting base plate; The shell is fixedly connected to the mounting base plate, a light-shielding closed sliding cover is movably provided on one side of the shell and directly above the test solution vessel, a control panel is also provided on the front surface of the shell, and a display, a test switch button, a networking switch button and a WiFi data transmission indicator light are sequentially provided on the control panel.

Images