Preparation method of dust for testing dynamic filtering performance of filter material

Abstract

The invention discloses a preparation method of dust for testing the dynamic filtering performance of a filter material. The method comprises the following steps: firstly, freeze-drying high-purity pseudo-boehmite (99.9% grade) at the temperature of 40 DEG C below zero to 15 DEG C below zero; performing graded grinding by adopting a planetary ball mill to obtain powder with three characteristic particle size distributions (D / D / D); a linear weighted proportioning model (target powder = a * D + b * D + c * D) is constructed based on an Excel VBA program, and + / -5% error control of measured data of mixed dust D, D and D and target working conditions (cement / thermal power / steel plant) is realized through nonlinear programming operation; finally, a V-shaped mixer is adopted for mixing for 20-40 min under the charging amount of 40%-60%, and the uniformity CV is smaller than or equal to 5%. The pore volume (0.3-0.8 cm / g), the particle density (2.3-2.8 g / cm) and the particle size distribution of the obtained dust for testing are similar to those of real industrial dust, a high-fidelity simulation environment can be provided for dynamic filtering performance testing of a filter material of a bag type dust collector, and the accuracy of dynamic dust removal efficiency evaluation of the filter material is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of testing the filtration performance of filter materials for bag filters, and particularly to a method for preparing dust for testing the dynamic filtration performance of filter materials. Background Art

[0002] China attaches great importance to the pollution and treatment of dust, and further improves the pollutant discharge standards for related industries. For example, the "Emission Standards for Air Pollutants from Thermal Power Plants" and the "Emission Standards for Air Pollutants from Cement Industry" have increased the particulate matter emission standard from 30 mg / m 3 to 10 mg / m 3 , and the "New Emission Standards for Air Pollutants from Steelmaking Industry and Iron and Steel Sintering and Pelletizing Industry" will increase the implementation standard from 50 mg / m 3 to 30 mg / m 3 . Moreover, in specific areas, the emission of particulate matter will implement more stringent quota standards or even ultra-low emission standards.

[0003] As one of the efficient dust removal technologies for highly efficient removal of particulate matter and significantly reducing industrial soot emissions, bag filter is an important environmental protection technology and equipment for solving air pollution. Bag filters have a dust removal efficiency as high as 99.99%, and the dust emission concentration is controlled below 10 mg / m 3 , and can even reach 5 mg / m 3 . These characteristics make bag filters more and more widely used in the field of industrial dust removal. As the core component of bag filters, filter materials determine the performance of the equipment. Therefore, scientific research personnel pay more attention to the research on the performance of filter materials for bag filters.

[0004] The dynamic filtration performance test platform for filter materials of bag filters is a test device for simulating actual working conditions in the laboratory to test the dynamic filtration performance of filter materials. However, there are significant differences between the industrial dust discharged under actual working conditions and the physical properties of the dust source α-Al2O3 specified in the "Technical Requirements for Bag Filters" (GB / T 6719-2009). Therefore, there are large differences between the dynamic filtration performance test of filter materials and the actual working conditions. Developing simulated test dust for different working conditions is of great significance for evaluating the true filtration performance of filter materials for bag filters. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method for preparing dust for testing the dynamic filtration performance of filter materials. The dust prepared by this method is closer to the industrial dust discharged under actual working conditions than the dust source α-Al2O3 specified in the "Technical Requirements for Bag Filters" (GB / T 6719-2009), so as to provide more scientific and accurate test data for the dynamic filtration performance test of filter materials for bag filters.

[0006] To achieve the above object, the present invention adopts the following technical solutions: A method for preparing dust for testing the dynamic filtration performance of filter media, comprising the following steps:

[0007] Step a: Pretreatment: Freeze-dry the pseudo-boehmite raw material powder with a purity ≥ 99.9%, control the freezing temperature at -40°C to -15°C, the vacuum pressure at 15 - 35 Pa, and the pretreatment time at 1 - 3 h to obtain the pretreated raw material;

[0008] Step b: Classification and grinding: Rapidly put the pretreated raw material into a planetary ball mill at a low temperature state, and the feeding process does not exceed 60 s. Start the planetary ball mill to classify and crush the pretreated raw material to obtain 3 kinds of particulate dust with different particle size distributions and label them as F-1, F-2, and F-3;

[0009] Step c: Ratio optimization: Based on the industrial dust particle size distribution data of the target working conditions, establish a multi-component ingredient optimization model through the Excel VBA program; the model adopts a linear weighting formula: target powder = a·D1 + b·D2 + c·D3, with the constraint condition a + b + c = 1. Continuously assign values to a from 0 to 1 with a step size of 0.01. After assigning a value to a, continuously assign a value to b, and the assignment method is b = 1 - a with a step size of -0.01, and c = 1 - a - b; continuously perform calculations, accumulate the variances and continuously record them in the corresponding cells, and record the minimum variance sum in the best ratio cell; where D1, D2, and D3 respectively represent the characteristic particle size distribution vectors of F-1, F-2, and F-3;

[0010] Step d: Mixing process: Use a V-type mixer to mix the classified products according to the optimized ratio, with a mixing time of 5 - 15 min, control to the diffusion mixing stage, and the mixing uniformity CV ≤ 5%;

[0011] In a preferred embodiment, the characteristic particle size D of F-1 50 = 1μm ± 0.5μm, the characteristic particle size D of F-2 50 = 10μm ± 2μm, the characteristic particle size D of F-3 50 = 20μm ± 3μm.

[0012] In a preferred embodiment, the crystal structure of the pseudo-boehmite raw material powder is amorphous or pseudo-boehmite phase, with a pore volume of 0.3 - 0.8 cm 3 / g, a particle density of 2.3 - 2.8 g / cm 3 , and the pseudo-boehmite is one of the alcohol-aluminum method, the neutralization method, and the carbonization method.

[0013] In a preferred embodiment, the tank body and grinding balls of the planetary ball mill should be made of one of silicon carbide, zirconia, agate, corundum, and stainless steel.

[0014] In a preferred embodiment, the revolution speed of the grinding speed of the planetary ball mill is 100 - 800 rpm, and the rotation speed is 300 - 600 rpm; the grinding time should be controlled within 20 - 40 min, and there should be an intermittent break of 1 min every 5 min of grinding; the mass ratio of grinding balls to materials should be 4:1 to 6:1; the loading amount is controlled at 40 - 50%.

[0015] In a preferred embodiment, the Excel VBA program is implemented through the following steps: 1) Read the data matrix of the particle size distribution of each powder; 2) Construct the target cell containing the squared error function; 3) Call the Solver tool for non - linear programming operations; 4) Output the mixing ratio coefficient that satisfies the minimum mean square error.

[0016] In a preferred embodiment, the loading coefficient of the V - type mixer is 40 - 60%, the mixing speed is 12 - 15 rpm, and the mixing stops when the coefficient of variation ≤ 5%.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The dust used for testing the dynamic filtration performance of the filter material prepared by the present invention is closer to the industrial dust discharged under actual working conditions than the dust source α - Al2O3 test dust (particle density is 3.56 - 4.00 cm 3 / g) specified in the "Technical Requirements for Bag Filters" (GB / T 6719 - 2009), having the simulation effect of the actual working conditions, thus providing more scientific and accurate test data for the test of the dynamic filtration performance of the filter material for bag filters. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of the change in the residual resistance of the filter material in the first 30 cycles of the preferred embodiment of the present invention;

[0019] Figure 2 Schematic diagram of the change in the residual resistance during the aging process of the filter material in the preferred embodiment of the present invention;

[0020] Figure 3 Schematic diagram of the change in the residual resistance of the filter material in the first 30 cycles of the preferred embodiment of the present invention;

[0021] Figure 4 Schematic diagram of the change in the residual resistance during the aging process of the filter material in the preferred embodiment of the present invention;

[0022] Figure 5 Schematic diagram of the constant - pressure pulse jet of the filter material in the last 30 cycles of the preferred embodiment of the present invention;

[0023] Figure 6 Schematic diagram of the change in the filtration cycle of the filter material in the last 30 cycles of the preferred embodiment of the present invention;

[0024] Figure 7Schematic diagram of the change in residual resistance during filtration in the 30th cycle of the filter material in the preferred embodiment of the present invention;

[0025] Figure 8 Schematic diagram of the actual operation interface of the VBA program in the preferred embodiment of the present invention;

[0026] Figure 9 Program calculation result diagram of Case 1 in the preferred embodiment of the present invention;

[0027] Figure 10 Program calculation result diagram of Case 2 in the preferred embodiment of the present invention;

[0028] Figure 11 Schematic diagram of the Excel VBA program flow in the preferred embodiment of the present invention. Detailed implementation manners

[0029] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0030] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0031] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary implementation manners according to the present application; as used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0032] A filter material dynamic filtration test dust for the preparation of pseudo-boehmite and a preparation method according to the present invention, referring to Figures 1-11 comprises the following steps:

[0033] Step 1, pretreatment of pseudo-boehmite

[0034] Freeze-dry the pseudo-boehmite raw material powder with a purity > 99.9%, control the freezing temperature to be -40°C to -15°C, the vacuum pressure to be 15 - 35 Pa, and the pretreatment time to be 3 h to obtain the pretreated raw material. In order to keep the pseudo-boehmite in a dry state for easy crushing by the grinder and to make the material in a highly fluid state for easy feeding of the grinder.

[0035] The pseudo-boehmite adopts one of the alcohol-aluminum method, the neutralization method, and the carbonization method

[0036] Step 2, classification grinding of pseudo-boehmite;

[0037] The pretreated raw materials are classified and pulverized by a planetary ball mill. The pretreated raw materials are quickly put into the planetary ball mill at a low temperature (< -15°C), and the feeding process should not exceed 60 s. The tank body and grinding balls of the planetary ball mill should be made of one of silicon carbide, zirconia, agate, corundum, and stainless steel. The revolution speed of the grinding speed is 100 - 800 rpm, and the rotation speed is 300 - 600 rpm. The grinding time should be controlled within 20 - 40 min, and there should be an intermittent period of 1 min every 5 min of grinding. The mass ratio of grinding balls to materials should be 4:1 to 6:1. The loading amount is controlled at 40 - 50%. Finally, three kinds of particulate powders with different particle size distributions are obtained and marked as F-1, F-2, and F-3;

[0038] Step 3: Optimization of the ratio of pseudo-boehmite;

[0039] Based on the industrial dust particle size distribution data of the target working conditions (such as the flue gas dust of dust collectors in cement plants, thermal power plants, steel plants, etc.), a multi-component batching optimization model is established through an Excel VBA program. The model uses the linear weighted formula target powder = a·D1 + b·D2 + c·D3 (constraint condition a + b + c = 1) to continuously assign values to a from 0 to 1 with a step size of 0.01. After a is assigned, b is also continuously assigned, and the assignment method is b = 1 - a with a step size of -0.01, and c = 1 - a - b. Continuous calculations are carried out, and the variances are accumulated and continuously recorded in the corresponding cells. The best ratio cell records the smallest accumulated variance sum and records it. Among them, D1, D2, and D3 respectively represent the characteristic particle size distribution vectors of F-1, F-2, and F-3;

[0040] Step 4: Mixing of different classified pseudo-boehmite;

[0041] Use a V-type mixer to mix the classified products according to the optimized ratio. The mixing time is 5 - 15 min, and it is controlled to the diffusion mixing stage (mixing uniformity CV ≤ 5%).

[0042] The Excel VBA program code is as follows:

[0043] Sub Fitting()

[0044] stepper = 0.01 'The matching accuracy is one percentage forward each time

[0045] Cells(14, 9) = 9999999 'Setting the start variance sum to 9999999 for the start condition allows the program to proceed smoothly

[0046] For a = 0 To 1 Step 0.01 'Take a as the variable, b and c as the following variables

[0047] For b = 1 - a To 0 Step -0.01 'After a is determined, b is the variable and c is the following variable

[0048] c = 1 - a - b

[0049] For i = 2 To 51

[0050] Cells(i, 7) = a * Cells(i, 2) + b * Cells(i, 3) + (1 - a - b) * Cells(i, 4) 'Real - time particle size distribution

[0051] Cells(i, 8) = Cells(i, 7) - Cells(i, 5) 'Variance change

[0052] Cells(52, 2) = a 'Real - time scale changes

[0053] Cells(52, 3) = b

[0054] Cells(52, 4) = c

[0055] Cells(i, 9) = Cells(i, 8) * Cells(i, 8)

[0056] Cells(52, 9) = 0

[0057] Cells(52, 9) = Application.Sum(Cells(2, 9).Resize(51, 1)) 'Variance sum

[0058] Next i

[0059] If Cells(53,9)>Cells(52,9) Then 'Set the criteria to find the smallest variance and its corresponding proportion

[0060] Cells(53,9) = Cells(52,9)

[0061] Cells(53,2) = Cells(52,2)

[0062] Cells(53,3) = Cells(52,3)

[0063] Cells(53,4) = Cells(52,4)

[0064] Else: Cells(53,9) = Cells(53,9)

[0065] Cells(53,2) = Cells(53,2)

[0066] Cells(53,3) = Cells(53,3)

[0067] Cells(53,4) = Cells(53,4)

[0068] End If

[0069] Next b

[0070] Next a

[0071] For x = 2 To 51

[0072] Cells(x,10) = Cells(53,2) * Cells(x,2) + Cells(53,3) * Cells(x,3) + Cells(53,4) * Cells(x,4)

[0073] 'The optimal particle size distribution is calculated at the end of the cycle

[0074] Next

[0075] End Sub

[0076] Implementation Case One

[0077] A dust for dynamic filtration test of filter media prepared from pseudo-boehmite and its preparation method. The main raw material is pseudo-boehmite prepared by the alcohol-aluminum method with a purity of ≥99.9%, and the D50 of the No. 1 raw powder is 17 μm, and the D50 of the target dust (working condition dust) is 7 μm. After drying the raw powder in an environment with a vacuum pressure drop of 20 Pa at -40°C for 3 hours, the powder is put into a ball mill at a low temperature. The tank body and balls of the planetary ball mill are made of agate material. The revolution speed of the grinding speed is 800 rpm, the rotation speed is 600 rpm, the grinding time is 40 min, and there is an intermittent period of 1 min every 5 min of grinding; the mass ratio of the grinding balls to the material should be 6:1, and the loading amount is controlled at 50%. Finally, the D50 of F-1 is 4.6 μm, the D50 of F-2 is 5.7 μm, and the D50 of F-3 is 8.8 μm. 50 D50 = 17 μm, and the target dust (working condition dust) D50 50 = 7 μm. After drying the raw powder in an environment with a vacuum pressure drop of 20 Pa at -40°C for 3 hours, the powder is put into a ball mill at a low temperature. The tank body and balls of the planetary ball mill are made of agate material. The revolution speed of the grinding speed is 800 rpm, the rotation speed is 600 rpm, the grinding time is 40 min, and there is an intermittent period of 1 min every 5 min of grinding; the mass ratio of the grinding balls to the material should be 6:1, and the loading amount is controlled at 50%. Finally, the D50 of F-1 is 4.6 μm, the D50 of F-2 is 5.7 μm, and the D50 of F-3 is 8.8 μm. 50 D50 = 4.6 μm, the D50 of F-2 50 = 5.7 μm, the D50 of F-3 50 = 8.8 μm.

[0078] The test dust prepared by the present invention uses pseudo-boehmite with a purity > 99.9%. Through the Excel VBA program, the proportion is continuously assigned values, and the program calculation is as Figure 9 shown. Finally, the optimal mixing ratio is shown in Table 2 as F-1:F-2:F-3 = 0.35:0.01:0.64, and the total variance sum is 267.32. According to the calculation results, the dust with different particle size fractions is mixed for 10 min (CV = 3.1%) using a material mixer. The difference in the characteristic particle size D10 between the prepared powder and the target dust is only 0.47 μm, the difference in D50 is 0.24 μm, and the difference in D90 is 0.54 μm.

[0079] Table 1

[0080]

[0081] Table 2

[0082]

[0083] Implementation Case Two

[0084] A dust for dynamic filtration test of filter media prepared from pseudo-boehmite and its preparation method. The main raw material is pseudo-boehmite prepared by the neutralization method with a purity > 99.9%. The D50 of the No. 2 raw powder is 16 μm, and the D50 of the target dust (working condition dust) is 7 μm. After drying the raw material powder in an environment with a vacuum pressure drop of 35 Pa at -15°C for 3 hours, the powder is put into a ball mill at a low temperature. The tank body and balls of the planetary ball mill are made of agate material. The revolution speed of the grinding speed is 800 rpm, the rotation speed is 600 rpm, the grinding time is 40 min, and there is an intermittent period of 1 min every 5 min of grinding; the mass ratio of the grinding balls to the material should be 6:1. Finally, the D50 of F-1 50= 5.1 μm, D of F-2 50 = 8.1 μm, D of F-3 50 = 9.7 μm.

[0085] Table 3

[0086]

[0087] The test dust prepared by pseudoboehmite with a purity > 99.9% in the present invention is used to continuously assign values to the ratio through the Excel VBA program. The program calculation is as Figure 10 shown. The final optimal mixing ratio is shown in Table 4 as F-1:F-2:F-3 = 0.26:0.58:0.16, and the total variance sum is 14.43. According to the calculation results, the dust with different particle size classifications is mixed for 10 min (CV = 4.5%) using a material mixer. The characteristic particle sizes D10, D50, and D90 of the prepared powder and the target dust differ by only 0.08 μm, 0.08 μm, and 0.7 μm respectively

[0088] Table 4

[0089]

[0090] Figures 1-7 It is a comparison chart of the dynamic filtration tests of the same filter material for the dust source α-aluminum oxide test dust in the current standard "Technical Requirements for Bag Filters" (GB / T 6719—2009) and the dusts prepared in Case One and Case Two of the implementation cases. The test time of the α-aluminum oxide test dust in the clean stage and the stable stage is approximately three times that of Case One and Case Two of the implementation cases. The particle density of Case One and Case Two of the implementation cases is closer to that of industrial dust. Moreover, in the aging stage, the use of the α-aluminum oxide test dust in the current standard does not cause the dust deposition inside the filter material to reach saturation, and it is impossible to simulate the long-term use condition of the filter material under the working conditions. The use of the prepared powder can effectively shorten the experimental time cycle and improve the operation efficiency of the experimental equipment. Using the prepared powder for laboratory dynamic filtration tests, the results are more consistent with the results of the long-term use of the filter material under actual working conditions.

Claims

1. A method for preparing dust for testing the dynamic filtration performance of filter media, characterized in that It includes the following steps: Step a: Pretreatment: Freeze-dry the pseudo-boehmite raw material powder with a purity of ≥99.9%, control the freezing temperature at -40°C to -15°C, the vacuum pressure at 15 - 35 Pa, and the pretreatment time at 1 - 3 h to obtain the pretreated raw material; Step b: Graded grinding: Rapidly put the pretreated raw material into a planetary ball mill at a low temperature state, and the feeding process should not exceed 60 s. Start the planetary ball mill to carry out graded crushing on the pretreated raw material to obtain three kinds of particulate dust with different particle size distributions and label them as F-1, F-2, and F-3; Step c: Ratio optimization: Based on the industrial dust particle size distribution data of the target working condition, establish a multi-component proportioning optimization model through the Excel VBA program; the model uses a linear weighted formula: target powder = a·D1 + b·D2 + c·D3, with the constraint condition a + b + c = 1. Continuously assign values to a starting from 0 to 1 with a step size of 0.

01. After assigning a value to a, continuously assign a value to b, and the assignment method is b = 1 - a with a step size of -0.01, and c = 1 - a - b; continuously perform calculations, accumulate the variances and continuously record them in the corresponding cells, and record the minimum variance accumulation sum in the best ratio cell; where D1, D2, and D3 respectively represent the characteristic particle size distribution vectors of F-1, F-2, and F-3; Step d: Mixing process: Use a V-type mixer to mix the classified products according to the optimized ratio, with the mixing time of 5 - 15 min, control it to the diffusion mixing stage, and the mixing uniformity CV ≤ 5%; 2. The preparation method of the dust for testing the dynamic filtration performance of a filter medium according to claim 1, wherein: F-1 characteristic particle size D 50 = 1 μm ± 0.5 μm, F-2 characteristic particle size D 50 = 10 μm ± 2 μm, F-3 characteristic particle size D 50 = 20 μm ± 3 μm.

3. The preparation method of the dust for testing the dynamic filtration performance of a filter medium according to claim 1, wherein: The crystal structure of the pseudo-boehmite raw material powder is amorphous or pseudo-boehmite phase, with a pore volume of 0.3 - 0.8 cm 3 / g and a particle density of 2.3 - 2.8 g / cm 3 . The pseudo-boehmite is prepared by one of the methods of alcohol-aluminum method, neutralization method, and carbonization method.

4. The preparation method of dust for testing the dynamic filtration performance of filter media according to claim 1, characterized in that: The tank body and grinding balls of the planetary ball mill should be made of one of silicon carbide, zirconia, agate, corundum, and stainless steel.

5. The preparation method of dust for testing the dynamic filtration performance of filter media according to claim 4, characterized in that: The revolution speed of the grinding rotation speed of the planetary ball mill is 100 - 800 rpm, and the rotation speed of self-rotation is 300 - 600 rpm; the grinding time should be controlled within 20 - 40 min, and there should be an intermittent period of 1 min every 5 min of grinding; the mass ratio of grinding balls to materials should be 4:1 to 6:1; the loading amount is controlled at 40 - 50%.

6. The preparation method of dust for testing the dynamic filtration performance of filter media according to claim 1, characterized in that The Excel VBA program is implemented through the following steps: 1) Read the data matrix of the particle size distribution of each powder; 2) Construct the target cell containing the squared error function; 3) Call the Solver tool to perform non-linear programming operations; 4) Output the mixing ratio coefficients that meet the minimum mean square error.

7. The preparation method of dust for testing the dynamic filtration performance of filter media according to claim 1, characterized in that The loading coefficient of the V-type mixer is 40 - 60%, the mixing speed is 12 - 15 rpm, and stop mixing when the coefficient of variation ≤ 5%.

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