CN112858075A - Method for detecting kneading effect of multi-component raw materials - Google Patents

Method for detecting kneading effect of multi-component raw materials Download PDF

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CN112858075A
CN112858075A CN202110172020.7A CN202110172020A CN112858075A CN 112858075 A CN112858075 A CN 112858075A CN 202110172020 A CN202110172020 A CN 202110172020A CN 112858075 A CN112858075 A CN 112858075A
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戴波
魏进超
刘克俭
李小龙
卢兴福
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Zhongye Changtian International Engineering Co Ltd
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Abstract

The invention relates to the technical field of material kneading processes, in particular to a method for detecting the kneading effect of a multi-component raw material. The method for detecting the kneading effect of the multi-component raw materials comprises the following steps: determining the mass fractions of the kneaded materials with different grades of particle sizes according to the particle size distribution and the particle size of the kneaded materials; and determining the kneading mass ratio of the kneaded materials according to the mass fractions of the kneaded materials with different grade granularities. The method can simply and quickly judge the blending degree of the kneaded material so as to judge the kneading quality of the kneaded material, provides a detection means for fine control of the multicomponent raw material kneading production and evaluation of the kneading process, and can provide reference and reference for product quality stability and process improvement. The method provided by the invention is used for detecting the kneading process of the multi-component raw materials for preparing the activated carbon, the distribution condition of the coal tar in the kneaded materials can be accurately known, and further, the stability of the strength of the activated carbon is guaranteed.

Description

Method for detecting kneading effect of multi-component raw materials
Technical Field
The invention belongs to the technical field of material kneading processes, and particularly relates to a method for detecting the kneading effect of a multi-component raw material.
Background
In the field of flue gas treatment in the metallurgical steel industry, the flue gas purification effect of the desulfurization and denitrification activated carbon (namely large-particle activated carbon) process treatment is outstanding, and particularly in the steel industry flue gas purification treatment, the technology can be widely applied due to the characteristics of larger treatment capacity, excellent purification effect, cyclic utilization of the activated carbon and the like. The active carbon industry for flue gas purification at present develops comparatively rapidly, and the active carbon demand continues to increase.
The raw materials for preparing the activated carbon generally comprise various coals, coke powder, coal tar and the like, and the coal tar is an important lubricant and binder in the preparation of the activated carbon and plays a role in forming and strengthening the strength in the activated carbon. However, with the increase of the yield, the quality of the activated carbon is uneven, and particularly in the aspect of activated carbon strength, the strength difference of activated carbon products of the same manufacturer is large, so that the flue gas purification effect is influenced.
It was found that one of the reasons for the remarkable difference in strength is caused by uneven stirring of the raw materials of the respective components, particularly the coal tar added, during the kneading process for the preparation of the activated carbon. Therefore, the evaluation of the blending degree of the materials obtained in the kneading process is very important for improving the strength and the quality of the activated carbon.
However, in the raw materials for preparing the activated carbon, more than 90% of elements of coal and coal tar are C, and the colors are black; the granularity of the coal is small, the coal with the granularity smaller than-200 (smaller than 0.074mm) accounts for more than 90 percent, and the maximum granularity does not exceed 0.2 mm; in addition, the proportion of the coal tar in the raw materials is low and only accounts for 10-20%. Due to the factors, the distribution condition of each component in the material obtained after the kneading process, especially the distribution condition of coal tar, is difficult to distinguish by naked eyes or an element detection method, so that the uniform mixing degree of the raw materials for preparing the activated carbon is difficult to accurately evaluate.
Therefore, how to detect the blending degree of coal tar in the material obtained in the kneading step becomes a problem to be solved in the prior art.
Disclosure of Invention
The first aspect of the invention provides a method for detecting the kneading effect of multi-component raw materials. The method can simply and quickly judge the blending degree of the kneaded material so as to judge the kneading quality (kneading effect), provides a detection means for fine control of the multicomponent raw material kneading production and evaluation of the kneading process, and can provide reference and reference for product quality stability and process improvement. Particularly, the detection method is used for detecting the kneading process of the multi-component raw materials for preparing the activated carbon, and the distribution condition of the coal tar in the kneaded materials can be accurately known by the method, so that the stability of the strength of the activated carbon is ensured.
The method for detecting the kneading effect of the multi-component raw materials comprises the following steps: determining the mass fractions of the kneaded materials with different grades of particle sizes according to the particle size distribution and the particle size of the kneaded materials; and determining the kneading mass ratio of the kneaded materials according to the mass fractions of the kneaded materials with different grade granularities.
The coal tar is a black or black brown viscous liquid with irritant odor generated during coal dry distillation, and is still in a liquid state at normal temperature. After the kneading process is deeply researched, the viscosity of the coal tar is high, the coal tar is easily distributed unevenly in the raw materials, the coal tar is concentrated in partial areas, large aggregates are easily generated and a large amount of coal dust particles are wrapped, so that the particle size difference of the kneaded materials is obvious, the strength and the uniformity of the finished product active carbon particles are influenced, and the stability of the flue gas purification effect cannot be ensured; even the recycling service life of the activated carbon is influenced due to unqualified strength of part of the activated carbon, and the operation cost of flue gas purification is increased.
Meanwhile, the invention also discovers that if the mixed materials for preparing the activated carbon are effectively and uniformly mixed, the mixed materials are regarded as coal tar which is consistent everywhere, the coal tar is scattered and uniformly distributed in the coal dust particles and mutually bonded with the coal dust particles to form particles with small and uniform particle size. Theoretically, after kneading the multicomponent raw materials, the particles of the mutually cohesive materials are more uniform in particle size and the smaller the particle size, the better.
Aiming at the discovery of the important physical property, the invention provides a method for detecting the kneading effect by detecting the particle size distribution and the particle size of the kneaded material, thereby solving the problem that the mixing uniformity of the coal tar in the multi-component raw material for the existing activated carbon is difficult to detect.
In the present invention, the particle size distribution and the particle size of the kneaded material are measured by screening treatment of different particle size grades. Researches show that different granularity grades are selected, the screening effect is different, and corresponding detection results are also different. In order to improve the detection accuracy and avoid increasing detection components and operation load, the invention limits the granularity grade to be at least 3 grades; preferably 6 grades, thereby improving the accuracy, shortening the detection time and simplifying the detection operation.
The specific particle size grade gradient may be determined according to the type of kneaded material or the actual production requirements. Taking the activated carbon for desulfurization and denitrification as an example, the particle size grades can be 1mm, 3mm and 5 mm; or the granularity grades are 0.5mm, 1mm, 2mm, 3mm, 4mm and 5mm, preferably the latter, the detection result is more accurate, but the former has higher efficiency and is suitable for rapid detection.
The screening mode of the invention can adopt manual screening or automatic screening. However, automatic screening is preferred to avoid human error and to improve detection accuracy. The invention also optimizes the screening condition of automatic screening, and is more favorable for improving the accuracy of the detection result by reasonably controlling the screening operation parameters. Through verification, the automatic screening operation conditions in the invention are as follows: shaking for 280-320 times/min, amplitude of 8-15 mm, and sieving time of 120-200 s.
The screening according to the invention can be carried out using equipment customary in the art, such as vibrating screens.
In the vibrating screen machine, the test screens are arranged on the vibrating screen machine from top to bottom according to the sequence of the screen holes from large to small, as shown in figure 1. After uniformly screening according to certain swing parameters, weighing the mass (accurate to 0.01g) of the materials in each screen layer and the chassis in sequence.
The invention also provides a study of the test sieves used for said screening, the dimensions of which are related to the sample size of the kneaded mass. Through experimental verification, the specification of the test sieve used for sieving is as follows: the diameter is 200, the sieve holes are square holes and are in accordance with the GB/T6003.1-2012; meanwhile, the sampling amount of the kneaded material is controlled to be about 50g, so that the accuracy of a detection result is improved, and meanwhile, the detection cost can be reasonably controlled.
Further research of the invention finds that the kneaded material is dried before screening, and the coal tar is solidified and hardened along with the evaporation of moisture, so that the particle structure of the material is more stable and is not easy to break, the subsequent particle size classification is more accurate, and the screening error caused by breaking of particles during screening can be greatly reduced.
Preferably, the drying conditions are: the temperature is 100 ℃ and 105 ℃, and the time is 1-3h, preferably 2 h. Under the condition, the problem that particles burst due to excessive drying is avoided while the material is hardened, and the testing accuracy is influenced.
In the detection method, the mass fraction of the kneaded material is calculated by the following formula:
Figure BDA0002938999710000041
wherein i-grade particle size;
Mi-mass fraction,%, of kneaded mass corresponding to i-grade particle size;
mi-mass of kneaded mass corresponding to i-grade particle size, g;
m- -total mass of kneaded material of all grade sizes, g.
In the detection method, the mass proportion of the kneaded material is calculated by the following formula:
P(%)=∑(Mi×λi) (1-2)
in the formula, P represents the mass percentage of the kneaded material;
Mi-mass fraction,%, of kneaded mass corresponding to i-grade particle size;
λi-the weight factor of the kneaded mass for the i-grade particle size.
Theoretically, after the multi-component raw materials are kneaded, if the particle diameters of the mutually bonded materials are more uniform, the better the particle diameters are, the smaller the particle diameters are, the better the particle diameters are, therefore, the coefficient weighting is carried out on the kneaded materials with different grades of particle sizes, the smaller the particle diameter is, the higher the weight is, and the larger the particle diameter is, the smaller the weight is.
The determination of the weighting coefficients can be adjusted according to actual production and operating conditions.
Taking the activated carbon for desulfurization and denitrification as an example, when 3 grades of sieves are adopted, 4 grain size materials are formed: less than 1mm, 1-3mm, 3-5mm, more than 5 mm; the corresponding weighting factors are set to 1, 0.8, 0.6, 0.4, respectively. When 6 grades of screening are used, 7 grain size materials are formed: less than 0.5mm, 0.5-1mm, 1-2mm, 2-3mm, 3-4mm, 4-5mm, > 5 mm; the corresponding weight coefficients are set to 1, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, respectively. Through the reasonable setting of the weight coefficient, the accuracy of the detection result is improved.
The invention has the following beneficial effects:
the invention utilizes the characteristics of the kneaded materials, measures the particle distribution condition of the kneaded materials in a multi-level screening mode, calculates the corresponding kneading mass ratio according to the screening result, and detects the kneading effect according to the kneading mass ratio. The method provides a detection means for fine control of the multi-component raw material kneading production and evaluation of the kneading process, and also provides reference and reference for stable product quality and process improvement.
Drawings
Figure 1 is a schematic diagram of vibratory screening.
In the figure: 1. a chassis; 2. 0.5mm sieve; 3.1 mm sieve; 4. 2mm sieve, 5mm, 3mm sieve; 6. 4mm sieve; 7. 5mm sieve; 8. a vibrating screen machine.
Detailed Description
The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Each of the components in the following examples is commercially available.
Example 1
This example provides a method for detecting kneading effect of multi-component raw materials for preparing activated carbon, which includes the following steps:
(1) sampling:
sampling materials obtained by 4 different kneading procedures, wherein the samples comprise a sample 1, a sample 2, a sample 3 and a sample 4, and each sample is 500 g; drying;
(2) automatic screening:
screening by adopting a vibrating screen machine. The process parameters of the vibrating screen machine are as follows: shaking for 300 times/min with amplitude of 12mm, and sieving time of 170 s.
The test sieve is arranged on the vibrating screen machine from top to bottom according to the sequence of the sieve holes from large to small, as shown in figure 1. After uniformly screening according to certain swing parameters, weighing the mass (accurate to 0.01g) of the materials in each screen layer and the chassis in sequence.
The sieve holes of the test sieve are 0.5mm, 1mm, 2mm, 3mm, 4mm and 5 mm; the diameter of the test sieve is phi 200, and the sieve holes are square holes, which meets the regulation of GB/T6003.1-2012.
(3) Calculating the mass fraction of the granularity:
calculated according to equation (1-1):
Figure BDA0002938999710000051
wherein i-grade particle size;
Mi-mass fraction,%, of kneaded mass corresponding to i-grade particle size;
mi-mass of kneaded mass corresponding to i-grade particle size, g;
m- -total mass of kneaded material of all grade sizes, g.
(4) Calculating the mass ratio of kneading:
P(%)=∑(Mi×λi) (1-2)
in the formula, P represents the mass percentage of the kneaded material;
Mi-mass fraction,%, of kneaded mass corresponding to i-grade particle size;
λi-the weight factor of the kneaded mass for the i-grade particle size.
The results are as follows.
TABLE 1 evaluation of kneading quality
Figure BDA0002938999710000061
As can be seen from the above table, the particle size distribution of sample 4 is most concentrated and the particle size is small, mainly in the range of < 0.5mm, so that the kneading quality is the highest for sample 4 compared to samples 1-3. The particle size distribution of the particles of sample 1 is not concentrated, the proportion is higher than 5mm, 2-3mm, 1-2mm and the like, and the corresponding kneading quality is relatively worst.
Example 2
This example provides a method for detecting kneading effect of multi-component raw materials for preparing activated carbon, which includes the following steps:
(1) sampling:
the same material as in example 1 was sampled to obtain 5 to 8 samples each 50 g; drying;
(2) manual screening:
screening samples 5-8 separately; the sieve holes of the test sieve for sieving are 1mm, 3mm and 5 mm; the diameter of the test sieve is phi 200, and the sieve holes are square holes, which meets the regulation of GB/T6003.1-2012.
(3) Calculating the mass fraction of the granularity:
calculated according to equation (1-1):
Figure BDA0002938999710000071
wherein i-grade particle size;
Mi-mass fraction,%, of kneaded mass corresponding to i-grade particle size;
mi-mass of kneaded mass corresponding to i-grade particle size, g;
m- -total mass of kneaded material of all grade sizes, g.
(4) Calculating the mass ratio of kneading:
P(%)=∑(Mi×λi) (1-2)
in the formula, P represents the mass percentage of the kneaded material;
Mi- -mass fraction of kneaded material corresponding to i-grade particle size,%;
λi-the weight factor of the kneaded mass for the i-grade particle size.
The results are as follows.
TABLE 2 evaluation of kneading quality
Figure BDA0002938999710000072
As can be seen from the above table, the particle size distribution of sample 8 is most concentrated and the particle size is small, mainly in the range of < 1mm, so that the kneading quality is the highest for sample 8 compared to samples 5-7. The particle size distribution of sample 6 was not concentrated, and was higher at > 5mm and 3-5mm, and the corresponding kneading quality was relatively worst.
Example 3
The test was carried out in the same manner as in example 1 except that the sample was not dried.
Test results show that a small part of particles are crushed in the screening process, so that the detection accuracy is reduced.
According to the test results, the kneading quality of the materials in the preparation process of the activated carbon can be quantitatively evaluated by adopting the detection method disclosed by the invention, so that the production is guided.
Although the invention has been described in detail hereinabove with respect to a general description and specific embodiments thereof, it will be apparent to those skilled in the art that modifications or improvements may be made thereto based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.

Claims (10)

1. A method for detecting the kneading effect of multi-component raw materials is characterized by comprising the following steps: determining the mass fractions of the kneaded materials with different grades of particle sizes according to the particle size distribution and the particle size of the kneaded materials; and determining the kneading mass ratio of the kneaded materials according to the mass fractions of the kneaded materials with different grade granularities.
2. The method for detecting kneading effects of multicomponent raw materials according to claim 1, wherein the particle size distribution and particle size of the kneaded material are measured by screening treatment of different particle size grades; the granularity level is at least 3 levels, preferably 6 levels.
3. The method for detecting kneading effect of multicomponent raw materials according to claim 2, wherein when the particle size classification is 3 classifications, the particle size classification is 1mm, 3mm, 5 mm.
4. The method for detecting the kneading effect of multi-component materials according to claim 2, wherein the particle size grades are 0.5mm, 1mm, 2mm, 3mm, 4mm, and 5mm when the particle size grade is 6 grades.
5. The method for detecting the kneading effect of multicomponent raw materials according to any one of claims 2 to 4, wherein the screening is performed by manual screening or automatic screening;
the operating conditions of the automatic screening are as follows: shaking for 280-320 times/min, amplitude of 8-15 mm, and sieving time of 120-200 s.
6. The method for detecting the kneading effect of multicomponent raw materials according to claim 5, wherein the specification of a test sieve used for the sieving is: the diameter is 200 and the sieve holes are square holes.
7. The method for detecting the kneading effect of multicomponent raw materials according to any one of claims 2 to 4, wherein the kneaded material is subjected to a drying treatment before being sieved;
preferably, the drying conditions are: the temperature is 100 ℃ and 105 ℃, and the time is 1-3 h.
8. The method for detecting kneading effect of multicomponent raw materials according to any one of claims 1 to 4 and 6, wherein the mass fraction of the kneaded material is calculated by the following formula:
Figure FDA0002938999700000011
wherein i-grade particle size;
Mi-mass fraction,%, of kneaded mass corresponding to i-grade particle size;
mi-mass of kneaded mass corresponding to i-grade particle size, g;
m- -total mass of kneaded material of all grade sizes, g.
9. The method for detecting kneading effect of multicomponent raw materials according to claim 8, wherein the mass ratio of the kneaded material is calculated by the following formula:
P(%)=∑(Mi×λi) (1-2)
in the formula, P represents the mass percentage of the kneaded material;
Mi-mass fraction,%, of kneaded mass corresponding to i-grade particle size;
λi-the weight factor of the kneaded mass for the i-grade particle size.
10. The method for detecting kneading effects of multicomponent raw materials according to claim 9, wherein as the kneaded material, an activated carbon preparation material:
when the granularity grade is 3 grades, the weight coefficients are 1, 0.8, 0.6 and 0.4;
when the granularity grade is 6 grades, the weight coefficients are 1, 0.8, 0.7, 0.6, 0.5, 0.4 and 0.3.
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Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5222605A (en) * 1992-01-08 1993-06-29 Rotex, Inc. Automatic particle size analyzer using stacked sieves
US20090091755A1 (en) * 2005-05-02 2009-04-09 Intelligent Pharmaceutics Ltd Oy Measuring method and system for measuring particle size and shape of powdery or grain like particles
CN103398918A (en) * 2013-07-29 2013-11-20 重庆大学 Method and device for testing thermal property of semicokes generated by cracking of block coal
CN103558250A (en) * 2013-10-14 2014-02-05 中国石油化工股份有限公司 Determination method for kneading and uniform mixing of materials
CN106940284A (en) * 2017-05-24 2017-07-11 张建平 A kind of dispersability of titanium dioxide detection method
CN206862834U (en) * 2017-07-12 2018-01-09 北京北化高科新技术股份有限公司 A kind of plastic grain evenness test device
CN110208266A (en) * 2019-06-20 2019-09-06 长沙理工大学 A kind of reclaimed asphalt mixture uniformity evaluating method
CN110672473A (en) * 2018-07-03 2020-01-10 上海梅山钢铁股份有限公司 Method for evaluating grain size distribution segregation of material in bin
CN111175449A (en) * 2020-01-03 2020-05-19 中南大学 Method for evaluating mixing uniformity of strong mixing reinforced iron ore sintering raw materials
CN112044723A (en) * 2020-07-13 2020-12-08 中南大学 Method for evaluating state of railway dirty track bed

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5222605A (en) * 1992-01-08 1993-06-29 Rotex, Inc. Automatic particle size analyzer using stacked sieves
US20090091755A1 (en) * 2005-05-02 2009-04-09 Intelligent Pharmaceutics Ltd Oy Measuring method and system for measuring particle size and shape of powdery or grain like particles
CN103398918A (en) * 2013-07-29 2013-11-20 重庆大学 Method and device for testing thermal property of semicokes generated by cracking of block coal
CN103558250A (en) * 2013-10-14 2014-02-05 中国石油化工股份有限公司 Determination method for kneading and uniform mixing of materials
CN106940284A (en) * 2017-05-24 2017-07-11 张建平 A kind of dispersability of titanium dioxide detection method
CN206862834U (en) * 2017-07-12 2018-01-09 北京北化高科新技术股份有限公司 A kind of plastic grain evenness test device
CN110672473A (en) * 2018-07-03 2020-01-10 上海梅山钢铁股份有限公司 Method for evaluating grain size distribution segregation of material in bin
CN110208266A (en) * 2019-06-20 2019-09-06 长沙理工大学 A kind of reclaimed asphalt mixture uniformity evaluating method
CN111175449A (en) * 2020-01-03 2020-05-19 中南大学 Method for evaluating mixing uniformity of strong mixing reinforced iron ore sintering raw materials
CN112044723A (en) * 2020-07-13 2020-12-08 中南大学 Method for evaluating state of railway dirty track bed

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
王国环 等: "PE-HD/炭黑在捏合块元件内分散混合的数值模拟研究", 《中国塑料》 *

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