Particle size measurement method for siliceous slag synthesis

Abstract

The present invention relates to the field of particle size measurement technology, and specifically to a particle size measurement method applied to siliceous slag synthesis, the method comprising: sampling several times from the same batch of crushed siliceous slag, detecting the ultrasonic power data, average particle size, particle size range and distribution curve of each sample; based on the average particle size difference and particle size range difference between the sampled samples, dividing all the sampled samples into several similar particle size groups; based on the probability distribution difference of the distribution curve between different sampled samples in the same particle size group, the power data difference, and the collinearity characteristics between the power data, determining the particle size measurement results of the same batch of crushed siliceous slag. The present application aims to screen the sampled samples by analyzing the particle size distribution and particle agglomeration phenomenon in the crushed siliceous slag, so as to improve the data accuracy of the particle size measurement results.

Description

Technical Field

[0001] The invention relates to the technical field of particle size measurement, and in particular to a particle size measurement method applied to siliceous slag synthesis. Background Art

[0002] At present, the discharge of various solid waste residues is large and the utilization rate is low, which brings many serious problems. Large amounts of solid waste residues that are accumulated and poorly managed are prone to cause geological disasters such as slag pile collapse; some waste residues contain heavy metals and mineral processing agents, and long-term accumulation will pollute water resources and destroy the ecosystem. However, solid waste residues also have utilization value. For example, siliceous slag is mainly composed of compounds formed by the combination of silicon, calcium and other chemical elements. It is formed during the metallurgical process and usually contains alumina and alkali. The ingredients make it have certain chemical activity and can play an important role in industrial production. It contains iron between 7-8%, aluminum about 8%, calcium about 12%, and moisture content maintained at about 6%. It has a certain hardness and is suitable for use as an abrasive or filling material in industrial applications.

[0003] In the process of recycling siliceous slag, it is very important to use a laser particle size analyzer to measure the particle size. Accurately measuring the particle size and distribution of siliceous slag has a key impact on its subsequent processing, utilization and performance. For example, during the processing, the particle size results can be used to optimize process parameters, improve processing efficiency and product quality; it is helpful to deeply study the performance of siliceous slag and provide a theoretical basis for the development of high value-added products; it can also achieve strict control of product quality.

[0004] However, in the current measurement of siliceous slag particle size, there are differences in the size and shape of siliceous slag particles sampled from different batches, and their distribution in the dispersion is different, which affects the accuracy of the particle size measurement results and leads to low precision in the siliceous slag particle size measurement. Specifically, ultrasonic stirring has the limitation of local uneven dispersion causing particle agglomeration, which in turn affects the particle dispersion effect and the accuracy of particle size measurement. Summary of the invention

[0005] In order to solve the above technical problems, the present application provides a particle size measurement method applied to siliceous slag synthesis to solve the existing problems.

[0006] The particle size measurement method applied to siliceous slag synthesis in the present application adopts the following technical scheme:

[0007] One embodiment of the present application provides a particle size measurement method applied to siliceous slag synthesis, the method comprising the following steps:

[0008] Take several samples from the same batch of crushed siliceous slag and test the ultrasonic power data, average particle size, particle size range and distribution curve of each sample;

[0009] Based on the differences in average particle sizes and particle size ranges among the sampled samples, the particle size characteristic difference values ​​among the sampled samples are determined; and all the sampled samples are divided into a number of similar particle size groups using the particle size characteristic difference values;

[0010] Based on the probability distribution differences of the distribution curves between different sampling samples in the same particle size group, the power data differences, and the collinearity characteristics between the power data, the difference value of the particle agglomeration effect of each sampling sample in the same particle size group is determined;

[0011] Using the difference values ​​of all the samples in the same particle size group due to the influence of particle agglomeration, the standard samples for particle size determination are screened;

[0012] The particle size measurement data of the particle size measurement standard sample in the same particle size group with the largest number of sampling samples shall be taken as the particle size measurement result of the siliceous slag after crushing in the same batch.

[0013] Preferably, the distribution curve is obtained by detecting each sample using a laser particle size analyzer.

[0014] Preferably, the particle size range difference is the intersection-over-intersection ratio of the particle size ranges between the sampled samples.

[0015] Preferably, the particle size characteristic difference value is obtained by reversely fusing the average particle size difference and the particle size range difference.

[0016] Preferably, the method for dividing the similar particle size groups is: taking the particle size characteristic difference value as the clustering distance between the corresponding sampled samples, clustering all the sampled samples to obtain a number of clusters, which are respectively recorded as similar particle size groups.

[0017] Preferably, the method for determining the difference value affected by particle agglomeration includes:

[0018] For any sample in the same particle size group, the probability distribution difference and power data difference of the distribution curve between any sample and each remaining sample in the same particle size group are forward fused;

[0019] Calculate the average level of the fusion results between any sample and all other samples in the same particle size group;

[0020] Calculate the variance expansion factor between any sample and all other samples in the same particle size group;

[0021] The average level and variance expansion factor of the fusion results are reversely fused to obtain the difference value of any sample affected by particle agglomeration.

[0022] Preferably, the variance expansion factor is calculated as follows:

[0023] Taking a sequence composed of power data of any of the sampling samples as a target sequence;

[0024] Sequences composed of power data of other remaining sampled samples in the same particle size group as any sampled sample are respectively used as control sequences;

[0025] Calculate the variance expansion factor for the target sequence and all reference sequences.

[0026] Preferably, the reverse fusion method of the difference value of any sampling sample affected by particle agglomeration is further determined as the ratio of the average level of the fusion result and the variance expansion factor.

[0027] Preferably, the probability distribution difference is determined by a KL divergence value between distribution curves.

[0028] Preferably, the screening process of the particle size determination standard sample includes:

[0029] Normalize the difference values ​​of all the samples in the same particle size group due to the influence of particle agglomeration;

[0030] When the normalized result of the difference value of the sample sample affected by particle agglomeration is less than or equal to the preset secondary screening threshold, the sample sample is used as a standard sample for particle size determination.

[0031] This application has at least the following beneficial effects:

[0032] The present application proposes a method for measuring the particle size of siliceous slag. Considering that in the traditional siliceous slag particle size measurement process, the measurement result is determined only through a small number of sampling samples, and the measurement process does not consider the influence of the same particle size distribution and particle agglomeration on the particle size measurement error, which leads to poor stability of the siliceous slag particle size measurement process result, affecting the accuracy of the subsequent production process optimized according to the feedback measured particle size; in response to the above problems, the present application considers that the sampling selection of crushed siliceous slag in the siliceous slag recovery production process and the particle agglomeration in the measurement process will affect the particle size measurement results of the same batch, and therefore the crushed siliceous slag is sampled multiple times, and the ultrasonic dispersion parameter data and particle size measurement result data of each sampling are obtained, and the sampled samples are screened once based on the average particle size difference and the particle size range difference. The beneficial effect is that it is convenient to reduce the influence of sampling errors on the measurement results in the subsequent period, and at the same time, the particle size difference and particle size range characteristics are comprehensively considered to improve the subsequent The influence of particle agglomeration caused by ultrasonic dispersion stability on particle size determination; based on the primary screening results of the sampling samples, a relative analysis of the ultrasonic dispersion parameters and particle size distribution differences is performed on each group of sampling samples after screening, and the difference value of the influence of particle agglomeration on the particle size determination of each sample after the primary screening is obtained, and then a secondary screening is performed based on the difference value. The beneficial effect lies in considering the particle size distribution differences between sampling samples with similar average particle size and particle size range, the stable characteristics of ultrasonic stirring parameters during the determination process, and the consistency differences when the stability differences of the ultrasonic dispersion process of different sampling samples are large, reducing the influence of particle agglomeration on the crushing particle size determination results of the same batch of siliceous slag during the determination process, improving the accuracy of the particle size determination results, and optimizing the subsequent screening, dehydration and drying, dust removal, aging and batching, mixing production steps, thereby effectively stabilizing the component content of the produced polymer siliceous slag. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 A schematic diagram of a process for recycling siliceous slag provided in one embodiment of the present application;

[0035] Figure 2 A flow chart of a particle size measurement method for siliceous slag synthesis provided in one embodiment of the present application;

[0036] Figure 3 A schematic diagram of distribution curves of three different sampling samples measured by a laser particle size analyzer provided in one embodiment of the present application;

[0037] Figure 4 A flow chart of a screening process for screening out a particle size determination standard sample from all sampled samples provided in one embodiment of the present application;

[0038] Figure 5 A schematic diagram of the clustering results of all sampled samples provided in one embodiment of the present application;

[0039] Figure 6 A flow chart of a method for determining a difference value affected by particle agglomeration provided in accordance with an embodiment of the present application. DETAILED DESCRIPTION

[0040] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the particle size measurement method applied to siliceous slag synthesis proposed in the present application, its specific implementation method, structure, characteristics and effects are described in detail as follows in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0042] The specific scheme of the particle size measurement method applied to siliceous slag synthesis provided by the present application is described in detail below in conjunction with the accompanying drawings.

[0043] The particle size measurement of the siliceous slag pre-analyzed in this application is an important step in the crushing and screening link in the siliceous slag recovery production process. The data from the particle size measurement can provide important reference data for the batching and mixing steps in the subsequent production. The siliceous slag recovery production process ultimately obtains polymer siliceous slag with stable component content, a particle size of 5 cm and a moisture content of 6%.

[0044] In the embodiment of the present application, the process of recycling siliceous slag is as shown in the attached Figure 1 As shown, specifically including:

[0045] S1, raw material crushing.

[0046] In this embodiment, the raw materials used in the recycling and production process of the composite production material siliceous slag in industrial production are mainly steel slag, filter residue, coal slag, and white mud; the main chemical components of the raw materials are: silicon dioxide, magnesium oxide, calcium oxide, aluminum oxide, and iron oxide. In the recycling process, the siliceous slag raw material is crushed by a jaw crusher to reduce its size for subsequent processing.

[0047] S2, particle size determination and sieving.

[0048] Sampling is performed in the crushed siliceous slag raw material, and the sampled samples are subjected to particle size measurement; specifically, the siliceous slag is screened using a laser particle sizer. The laser particle sizer wet sample pool is filled with dispersion liquid, the siliceous slag is placed in the dispersion liquid, and after ultrasonic stirring and mixing by an ultrasonic processor, the laser particle sizer irradiates the laser beam on the particles in the dispersion liquid to obtain the particle size measurement result of the siliceous slag, and then the siliceous slag is screened using a vibrating screen according to the particle size of the siliceous slag; wherein the vibration amplitude is 2-8 mm, the vibration frequency is 1000-2000 times / minute, and the vibration time is 10-20 minutes.

[0049] It should be noted that the precise determination of siliceous slag particle size is one of the key links in the recycling of siliceous slag. The data such as the particle size distribution of siliceous slag particles obtained through advanced measurement technology can provide a scientific basis for the raw material crushing link, assist in determining the appropriate crushing parameters, and effectively control the particle size during the product production stage, thereby playing a key role in ensuring and improving the overall siliceous slag production quality.

[0050] However, in the recycling production process of siliceous slag raw materials, the traditional particle size measurement method does not fully consider the sampling differences of different batches of siliceous slag raw materials and the influence of the dispersion state in the dispersion liquid on the measurement results during the measurement process, resulting in large deviations in subsequent production feedback and control. Therefore, this application collects and analyzes the measurement parameters in the siliceous slag particle size measurement process.

[0051] In the embodiment of the present application, a flow chart of the method for measuring the synthetic particle size of siliceous slag is shown in the attached figure. Figure 2 As shown, the specific analysis steps include:

[0052] In the first step, several samples are taken from the same batch of crushed siliceous slag to detect the ultrasonic power data, average particle size, particle size range and distribution curve of each sample.

[0053] The same batch of siliceous slag raw materials after vibration crushing were sampled, and the number of sampled samples was 100. For each sampled sample, ultrasonic power data, average particle size, particle size range and distribution curve were obtained by ultrasonic processor and laser particle size analyzer respectively. Among them, ultrasonic power data is real-time collected data, and the time interval for collecting data is 1s. In other embodiments of the embodiment of the present application, the time interval can be set by itself. The sequence composed of the collected ultrasonic power data in ascending time order is used as the power data sequence in the particle size determination process.

[0054] In the embodiment of the present application, the schematic diagram of the distribution curve of three different samples measured by the laser particle size analyzer is shown in the attached figure. Figure 3 shown.

[0055] exist Figure 3 In the figure, 1, 2 and 3 respectively represent the distribution curves of three different samples measured by a laser particle size analyzer. In this embodiment, three distribution curves of three samples are taken as examples. Figure 3 An example is given in . Figure 3 The horizontal axis is the particle size, in mm, and the vertical axis is the weight percentage, which is used to indicate the weight percentage of particles of a certain particle size in the sample to which they belong.

[0056] So far, the relevant data of the particle size measurement of several sampling samples obtained from the same batch of crushed siliceous slag are obtained by the above method.

[0057] The second step is to select the particle size determination standard samples from all the sampled samples based on the differences in the relevant data between the sampled samples.

[0058] Normally, after the same batch of siliceous slag raw materials are crushed, there are differences in the particle sizes of the siliceous slag in different sampling samples, but the differences are small. Due to the different particle size distributions of siliceous slag after crushing in different regions, there are differences in the dispersion states of the sampling samples with different crushing degrees during the sampling and testing process. Even if different sampling samples actually have the same particle size measurement results, the particles may agglomerate after dispersion due to differences in the shape and size of the crushed particles, resulting in a large deviation in the particle size measurement results of the siliceous slag.

[0059] Therefore, in response to the above problems, the present application obtains the relevant data of each sampling sample in the process of particle size measurement through the first step, performs preliminary correlation feature analysis based on the analysis of the relevant data of each sampling sample in the measurement process, and compares the dispersion feature differences of the sampling samples based on the results of the correlation feature analysis, and obtains accurate samples for siliceous slag particle size measurement based on the analysis results.

[0060] In the embodiment of the present application, the screening process flow chart of screening out the particle size determination standard sample from all the sampled samples is as shown in the attached figure. Figure 4 As shown, the specific screening process is as follows:

[0061] A1. Based on the differences in average particle size and particle size range between the sampled samples, the particle size characteristic difference values ​​between the sampled samples are determined; and all the sampled samples are divided into several similar particle size groups using the particle size characteristic difference values.

[0062] Since the particle size measurement between different sampling samples may be affected by the uniformity of ultrasonic stirring and the differences in particle characteristics of the sampling samples, the difference characteristics of the particle size measurement between different sampling samples are analyzed.

[0063] Specifically, for any sample in the siliceous slag production process, the difference w in average particle size between any sample and each other sample is calculated. The larger the difference w, the larger the average difference in particle size determination between different sample. The difference m in particle size range between any sample and each other sample is calculated. The larger the difference m in particle size range, the closer the overall range of particle size of siliceous slag between different sample.

[0064] Preferably, in this embodiment, the difference w is specifically the absolute value of the difference in average particle size between any sample and each other sample. The particle size range difference m is the intersection-combination ratio of the particle size range between any sample and each other sample.

[0065] In other implementations of the embodiments of the present application, the reverse fusion result of the overlapping part and the non-overlapping part of the particle size range between any sample and each other sample can also be used as the particle size range difference m.

[0066] It can be understood that reverse fusion is a fusion method such as subtraction and division between data. The specific reverse fusion method is determined by the implementer according to the actual situation, and this application does not impose any special restrictions.

[0067] Therefore, the sampled samples in the process of siliceous slag particle size determination can be preliminarily divided by the particle size difference and particle size range variation between different sampled samples. Specifically, the particle size characteristic difference value d between any sampled sample and each other sampled sample in the process of siliceous slag particle size determination is calculated as follows:

[0068] Preferably, the difference w is reversely fused with the particle size range difference m to obtain a particle size characteristic difference value d between any sample and each other sample.

[0069] Specifically, in one implementation of the present application, the specific calculation relationship of the particle size characteristic difference value d is: The larger the calculated particle size characteristic difference value, that is, the larger the average particle size difference between the two samples, the smaller the overlap between their particle size ranges, indicating that the particle size characteristic difference between different samples of the same batch of siliceous slag after crushing is larger. The denominator is added with 0.01 to eliminate the situation where the denominator is zero. In other implementation methods, this value is also set by itself.

[0070] Furthermore, all sampled samples are taken as input, the particle size characteristic difference values ​​between the sampled samples are taken as the cluster distance, that is, the sample distance between the sampled samples, and the average value of the particle size characteristic difference values ​​between all sampled samples is taken as the threshold for dividing the clusters, and the clustering results of all sampled samples are obtained by using the agglomerative hierarchical clustering algorithm. The clustering results contain several clusters, which are respectively recorded as similar particle size groups. Among them, the agglomerative hierarchical clustering algorithm is a well-known technology and will not be repeated here. In other implementations of the embodiments of the present application, other suitable clustering algorithms, such as split hierarchical clustering, can also be used.

[0071] It should be understood that the sampling samples within each similar particle size group have similar particle size characteristics and their particle size ranges are also relatively the same, that is, the several similar particle size groups obtained by division are preliminary divisions of the sampling samples to avoid the influence of subsequent screening sampling samples on the analysis of particle size measurement results in the batch of crushed siliceous slag.

[0072] In the embodiment of the present application, the schematic diagram of the clustering results of all sampled samples is as follows: Figure 5 shown.

[0073] exist Figure 5 In the figure, the horizontal axis is the sample number of the sampled sample, and the vertical axis is the sample distance between different sampled samples, that is, the particle size characteristic difference value; wherein the particle size characteristic difference value between different sampled samples is used as the judgment result of the similarity between the samples, that is, as the clustering distance between the sampled samples. The specific implementation process of the agglomerative hierarchical clustering algorithm is a technology well known to those skilled in the art and will not be repeated here. Figure 5 Each solid line in the figure represents the average value of the particle size characteristic difference values ​​between all the sampled samples in the corresponding cluster, and the dotted line represents the cluster division threshold. The purpose is to use all clusters corresponding to the average value less than the division threshold as the final clustering result of the clustering algorithm.

[0074] It should be noted that the purpose of clustering by calculating the particle size characteristic difference values ​​between different sampling samples is to make a preliminary division of the sampling samples by comprehensively considering the average particle size differences and particle size variation range differences of different sampling samples, so as to avoid the influence of particle size range changes on the particle characteristic analysis of particle size measurement, and improve the accuracy of subsequent analysis of the influence of particle agglomeration on the measurement results during the particle size measurement process.

[0075] A2, based on the probability distribution differences of the distribution curves between different sampling samples in the same particle size group, the power data differences, and the collinearity characteristics between the power data, determine the difference value of the particle agglomeration effect of each sampling sample in the same particle size group.

[0076] After the above preliminary division, the particle size characteristic change curve and the stability of particle uniform dispersion parameters during the measurement process of the divided samples were analyzed to comprehensively evaluate their impact on the particle size measurement results.

[0077] Specifically, considering the differences in particle size distribution between sampling samples with similar average particle sizes and particle size ranges, as well as the stable characteristics of ultrasonic stirring parameters during the measurement process, the particle size measurement process of the sampling samples was further screened.

[0078] For any similar particle size group, the probability distribution difference c of the distribution curve of each sampled sample and each other sampled sample in the similar particle size group is calculated. The larger the probability distribution difference c, the larger the difference in particle size distribution between different sampled samples in the sampled sample group with similar particle size variation range and particle size mean difference. During the measurement process, due to the greater influence of ultrasonic dispersion stability, the more likely it is that agglomeration occurs, causing a large measurement error. In this embodiment, the KL divergence value is used to calculate the probability distribution difference between the distribution curves. The calculation process of the KL divergence value is a well-known technology and will not be repeated here. In other embodiments of the present application embodiment, the chi-square distance can also be used instead of the KL divergence value to calculate the probability distribution difference between the distribution curves.

[0079] Furthermore, in order to accurately analyze whether the ultrasonic dispersion stability causes large differences in the dispersion uniformity of the particle size sampling samples during the siliceous slag particle size measurement process, thereby causing particle agglomeration and resulting in large errors in the particle size measurement data, the embodiment of the present application analyzes the differences in parameter stability characteristics of the ultrasonic dispersion process between different sampling samples, and compares the differences in particle size measurement data.

[0080] Specifically, for any similar particle size group, the power data difference t corresponding to each sampled sample and each other sampled sample in the similar particle size group is calculated. The larger the power data difference t, the larger the power data difference t, indicating that different sampled samples in the particle size determination process have larger differences in the power data of the dispersed distribution of the particle size. Among them, in the embodiment of the present application, the DTW distance is used to calculate the distance between the power data sequences corresponding to the sampled samples, and the distance is used as the power data difference t. The calculation process of the DTW distance is a well-known technology and will not be repeated here. In other implementation methods of the embodiment of the present application, the Euclidean distance and the inverse of the Pearson correlation coefficient can also be used to calculate the distance between the power data sequences.

[0081] Secondly, when the stability of the ultrasonic dispersion process of different samples is greatly different, there may be consistency differences, which in turn affects the judgment result of the determination results of the sampled samples after the initial division being affected by the ultrasonic dispersion stability. Therefore, the collinearity characteristics between any sampled sample and all other sampled samples in the same particle size group can be considered to characterize the consistency difference of the ultrasonic dispersion stability between any sampled sample and all other sampled samples.

[0082] Accordingly, the present embodiment uses the power data sequence of any sampling sample in the same particle size group as the target sequence, and the power data sequences of other remaining sampling samples in the same particle size group are respectively used as control sequences, and the target sequence and all control sequences are used as input to calculate the variance expansion factor z of the target sequence. The larger the variance expansion factor is, the more significant the collinearity characteristics between the target sequence and other control sequences are, and the smaller the possibility of the influence of ultrasonic dispersion stability in the sampling sample determination process is. Wherein, the calculation process of the variance expansion factor is a known technology and is no longer repeated. In other embodiments of the present application embodiment, the conditional index method can also be used to calculate the collinearity characteristics between the target sequence and each control sequence.

[0083] Therefore, based on the analysis of the differences in ultrasonic dispersion stability and particle size distribution between the samples in the same particle size group after the above preliminary division, the difference value s due to the influence of particle agglomeration in the particle size determination process was calculated.

[0084] Specifically, for any sampling sample in the same particle size group, the probability distribution difference and power data difference of the distribution curve between any sampling sample and each remaining sampling sample in the same particle size group are forward fused; the average level of the fusion result between any sampling sample and all the remaining sampling samples in the same particle size group is calculated; the variance expansion factor between any sampling sample and all the remaining sampling samples in the same particle size group is calculated; the average level and variance expansion factor of the fusion result are reversely fused to obtain the difference value of any sampling sample affected by particle agglomeration.

[0085] It can be understood that forward fusion is a fusion method such as addition and multiplication between data. The specific forward fusion method is determined by the implementer according to the actual situation, and this application does not impose any special restrictions.

[0086] Preferably, in one embodiment of the present application, the first x The difference value of the sample size affected by particle agglomeration The specific calculation formula is: ; In the formula, Indicates the first x The difference value of the sampled samples is affected by particle agglomeration; Indicates the first x and i The probability distribution difference of the distribution curve between the sampling samples, Indicates the first x and i The power data difference corresponding to the sampling samples; Indicates the first x The variance expansion factor of the sample; n Describes the number of samples drawn from the same particle size group.

[0087] It should be understood that the greater the calculated difference in the effect of particle agglomeration on the sampled samples during the particle size determination process, the greater the possibility that the sampled samples will be affected by ultrasonic dispersion and particle agglomeration caused by differences in sampled particle crushing during the particle size determination process, and there may be larger errors in the particle size determination.

[0088] In the embodiment of the present application, a flow chart of a method for determining a difference value affected by particle agglomeration is shown in the attached figure. Figure 6 shown.

[0089] A3, using the difference values ​​of all the samples in the same particle size group due to the influence of particle agglomeration, screen the standard samples for particle size determination.

[0090] After the above analysis, after the preliminary division of all the sampling samples, a relative analysis of the ultrasonic dispersion parameters and particle size distribution differences in the measurement process of the sampling samples in each similar particle size group was carried out, and then the sampling samples after the preliminary division were screened for the second time to reduce the impact of the particle agglomeration phenomenon on the particle size measurement results of the same batch of siliceous slag during the measurement process.

[0091] Specifically, for each similar particle size group, the difference values ​​of the influence of particle agglomeration of all sampled samples in the similar particle size group during the particle size measurement process are normalized. This embodiment adopts the Z-score normalization algorithm to obtain the normalized results of all the difference values. In other implementations of the embodiments of the present application, the minimum and maximum normalization algorithm may also be used.

[0092] Because the particle size range and particle size distribution of the siliceous slag samples after crushing are usually small, the difference in the particle size determination data of different samples is small when the ultrasonic dispersion stability is good and the particle agglomeration phenomenon has little effect, so the secondary screening threshold for particle size determination after crushing of siliceous slag is set. It is 0.3. Since the particle size measurement accuracy is different in different particle size measurement scenarios, the implementer can set the secondary screening threshold according to the actual accuracy requirements.

[0093] The normalized result of the difference value of particle agglomeration effect in the particle size determination process of all sampled samples in each particle size group is less than or equal to The sampled samples are used as standard samples for particle size determination.

[0094] The third step is to use the particle size measurement data of the particle size measurement standard samples in the same particle size group with the largest number of sample samples as the particle size measurement results of the siliceous slag after crushing in the same batch.

[0095] After sampling and measuring the particle size of the crushed siliceous slag particles, a secondary screening was carried out on the influence of particle agglomeration caused by sampling error and ultrasonic dispersion error in the measurement process on the measurement results. Because under normal circumstances, the particle size measurement data after crushing are close, the influence of sampling error on particle size measurement is removed through a first screening; and the influence of agglomeration phenomenon caused by ultrasonic dispersion stability on measurement error is removed through a secondary screening.

[0096] Specifically, for the same type of particle size groups, the particle size measurement data of the particle size measurement standard samples in the same type of particle size group with the largest number of sampling samples are used as the result of particle size measurement after crushing of the same batch of siliceous slag. The results are fed back and stored to provide accurate data for the subsequent optimization and adjustment of siliceous slag crushing parameters and siliceous slag ingredients, mixed sample production process and production quality.

[0097] After the above steps S1 and S2, the measurement of the particle size after crushing in the siliceous slag recovery production process is completed, so as to provide accurate particle size data for the siliceous slag particle size crushing parameters, production process batching and mixing in subsequent production, and thus obtain a siliceous slag recovery production product with stable component content.

[0098] Furthermore, a subsequent process of the siliceous slag raw material is performed so that the siliceous slag obtained subsequently has the property of stable component content; the specific processing flow is as follows:

[0099] S3, dehydration and drying.

[0100] A centrifugal dehydrator is used to separate the water from the sieved siliceous slag through the centrifugal force generated by high-speed rotation, wherein the speed of the centrifugal dehydrator is 2500-3000 rpm. The dehydrated siliceous slag is then sent to a rotary dryer, which uses hot air to heat it to evaporate the water and achieve the purpose of drying; wherein the drying temperature is 120-200°C and the drying time is 4-8h.

[0101] The purpose of dehydration and drying by the above method in this application is:

[0102] (1) Centrifugal dehydration and drying can effectively remove moisture from siliceous slag and reduce the fluctuation of moisture content. Stable moisture content helps to ensure that the composition ratio of siliceous slag remains relatively stable during subsequent use or processing. This makes the performance of siliceous slag more reliable and predictable, and it can better play its specific role whether it is used in building materials, industrial production or other fields.

[0103] (2) Dehydration and drying can prevent changes in composition caused by excessive moisture content. Excessive moisture may trigger chemical reactions or microbial activities, thereby affecting the composition of the siliceous slag. After dehydration and drying, this risk is greatly reduced, ensuring that the composition of the siliceous slag is in a stable state. At the same time, dry siliceous slag is also easier to store and transport, and will not cause problems such as agglomeration and deterioration due to the presence of moisture, further ensuring the stability of its composition content.

[0104] S4, dust removal.

[0105] A bag filter is used to treat the dusty gas in the dried siliceous slag particles. The bag filter uses the filtering principle to efficiently intercept the dust particles in the dusty gas through the filter bag inside it. During the filtering process, the dusty gas enters from the air inlet of the dust collector, and after being evenly distributed by the guide plate, it flows to the filter bag. When the dust particles come into contact with the filter bag, they are intercepted on the outer surface of the bag, and the purified gas passes through the filter bag and is discharged from the air outlet of the dust collector to achieve standard emissions.

[0106] The purpose of the above processing in this application is to:

[0107] (1) By effectively removing dust particles from dusty gas, the interference of foreign impurities on the composition of siliceous slag can be reduced. Dust particles may contain different chemical components. If they are not removed, they may mix into the siliceous slag and affect the stability of its original composition content.

[0108] (2) After dust removal, the siliceous slag is purer, and its composition ratio can be more accurately controlled during subsequent use or processing, thereby improving the quality stability of the product. In addition, removing dust particles can also reduce the risk of component loss caused by dust flying during storage and transportation of siliceous slag.

[0109] S5, enter the semi-finished product warehouse.

[0110] The siliceous slag after dehydration, drying and dust removal is stored in the semi-finished product warehouse, waiting for the ingredients to age. The purpose of storing the materials after crushing, screening, dehydration, drying and dust removal in the semi-finished product warehouse in this application is:

[0111] (1) After being crushed, dehydrated, dried and dusted, the materials are stored in the semi-finished product warehouse to avoid the influence of external environmental factors on the material composition. For example, humid air, rainwater, etc. are prevented from causing the materials to absorb moisture again, thereby affecting the stability of their component content.

[0112] (2) In the semi-finished product warehouse, the materials are in relatively stable environmental conditions, which can make the various components more evenly distributed and reduce the fluctuation of components. This is crucial to ensure the stability of the content of recycled products.

[0113] S6, Aging and Ingredients.

[0114] According to the product requirements, siliceous slag of different particle sizes is selected from the semi-finished product warehouse for batching. Specifically, the particle size of the siliceous slag in the semi-finished product warehouse is analyzed, and the proportion of siliceous slag of different particle sizes is accurately calculated according to the performance indicators and component requirements required by the product. The siliceous slag of different particle sizes with a determined proportion is taken out and mixed through the conveying equipment and metering device. The prepared materials are then placed in the aging area for aging treatment for 7-21 days.

[0115] Specifically, in the batching step, the siliceous slag in the semi-finished product warehouse is stored in a particle size classification manner, the required composition and particle size distribution are analyzed in combination with the product performance requirements, and an intelligent batching system is introduced to accurately batch the ingredients. In the aging step, the temperature and humidity of the aging environment are strictly controlled, the materials are turned over regularly, and the composition changes and performance tests are monitored, so that the aging time and environmental conditions can be adjusted when necessary to make physical and chemical changes inside the materials, and the composition is more uniform, thereby improving product quality.

[0116] The purpose of aging and batching is to achieve uniformity of ingredients, eliminate internal stress, and improve the completeness of chemical reactions; thereby improving product quality stability, meeting the needs of different products, while optimizing the production process, reducing waste of raw materials, and improving resource utilization and production efficiency.

[0117] S7, mixing and feeding into silo.

[0118] The aged and batched materials are mixed in a powerful mixer. With high-speed rotating stirring blades and a special mixing structure, the powerful mixer can quickly and evenly mix the materials at a stirring speed of 60-120r / min and a mixing time of 45-60min.

[0119] Furthermore, prepare a suitable silo and ensure that it is clean and well sealed. Select suitable conveying equipment to convey the mixed materials from the powerful mixer to the silo, control the conveying speed and flow rate, ensure that the materials are evenly distributed in the silo, and obtain polymer siliceous slag after uniform mixing. After the feeding is completed, seal the silo and make good marks and records.

[0120] The purpose of mixing and feeding in this application is to improve the uniformity of ingredients, eliminate minor ingredient differences, and ensure that the product ingredients are highly uniform at the micro level to provide a stable material basis for subsequent production. Further, the product quality is improved, making the product more stable and reliable in performance and appearance, such as playing a positive role in the construction and industrial fields.

[0121] S8, production packaging.

[0122] The materials in the finished product warehouse are batched and packaged, and the polymer siliceous slag after batching and packaging is sampled. The components of the sampled materials are determined by X-ray fluorescence spectrometer. The specific component determination results are shown in Table 1. It can be seen that the component content of the produced polymer siliceous slag is relatively stable.

[0123] Table 1

[0124]

[0125] In the recycling and production process of siliceous slag, the present application uses a laser particle size analyzer to measure the particle size of the crushed siliceous slag. Since there may be sampling errors and particle agglomeration in the collection process, the embodiment of the present application performs multiple sampling on the crushed siliceous slag, and performs primary particle size difference and particle size range screening, as well as secondary ultrasonic dispersion particle agglomeration effect difference and particle size distribution difference screening, to reduce the influence of sampling errors and particle agglomeration on the particle size measurement results of the crushed siliceous slag, and then the siliceous slag is packaged and produced through dehydration and drying, dust removal, batching and mixing steps to obtain polymer siliceous slag with stable component content.

[0126] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0127] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the sentence "including one..." does not exclude the existence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items.

[0128] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art not invented by the present application.

[0129] It will be appreciated that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A particle size measurement method for siliceous slag synthesis, characterized in that: The method comprises the following steps: Take several samples from the same batch of crushed siliceous slag and test the ultrasonic power data, average particle size, particle size range and distribution curve of each sample; Based on the differences in average particle sizes and particle size ranges among the sampled samples, the particle size characteristic difference values ​​among the sampled samples are determined; and all the sampled samples are divided into a number of similar particle size groups using the particle size characteristic difference values; Based on the probability distribution differences of the distribution curves between different sampling samples in the same particle size group, the power data differences, and the collinearity characteristics between the power data, the difference value of the particle agglomeration effect of each sampling sample in the same particle size group is determined; Using the difference values ​​of all the samples in the same particle size group due to the influence of particle agglomeration, the standard samples for particle size determination are screened; The particle size measurement data of the particle size measurement standard sample in the same particle size group with the largest number of sampled samples shall be used as the particle size measurement result of the siliceous slag after crushing in the same batch; The particle size characteristic difference value is obtained by reverse fusion of the average particle size difference and the particle size range difference; The method for determining the difference value affected by particle agglomeration includes: For any sample in the same particle size group, the probability distribution difference and power data difference of the distribution curve between any sample and each remaining sample in the same particle size group are forward fused; Calculate the average level of the fusion results between any sample and all other samples in the same particle size group; Calculate the variance expansion factor between any sample and all other samples in the same particle size group; The average level and variance expansion factor of the fusion results are reversely fused to obtain the difference value of any sample affected by particle agglomeration; The reverse fusion method of the difference value of any sampling sample affected by particle agglomeration is further determined as the ratio of the average level of the fusion result and the variance expansion factor.

2. The particle size measurement method for siliceous slag synthesis according to claim 1, characterized in that: The distribution curve is obtained by detecting each sample by a laser particle size analyzer.

3. The particle size measurement method for siliceous slag synthesis according to claim 1, characterized in that: The particle size range difference is the intersection-over-intersection ratio of the particle size ranges between the sampled samples.

4. The particle size measurement method for siliceous slag synthesis according to claim 1, characterized in that: The method for dividing the similar particle size groups is as follows: taking the particle size characteristic difference value as the clustering distance between the corresponding sampled samples, clustering all the sampled samples to obtain a number of clusters, which are respectively recorded as similar particle size groups.

5. The particle size measurement method for siliceous slag synthesis according to claim 1, characterized in that: The calculation method of the variance expansion factor is: Taking a sequence composed of power data of any of the sampling samples as a target sequence; Sequences composed of power data of other remaining sampled samples in the same particle size group as any sampled sample are respectively used as control sequences; Calculate the variance expansion factor for the target sequence and all reference sequences.

6. The particle size measurement method for siliceous slag synthesis according to claim 1, characterized in that: The probability distribution difference is determined by the KL divergence value between the distribution curves.

7. The particle size measurement method for siliceous slag synthesis according to claim 1, characterized in that: The screening process of the particle size determination standard sample includes: Normalize the difference values ​​of all the samples in the same particle size group due to the influence of particle agglomeration; When the normalized result of the difference value of the sample sample affected by particle agglomeration is less than or equal to the preset secondary screening threshold, the sample sample is used as a standard sample for particle size determination.

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