CN117960139B - Preparation method of filter aid for improving filtering effect of iron concentrate - Google Patents
Preparation method of filter aid for improving filtering effect of iron concentrate Download PDFInfo
- Publication number
- CN117960139B CN117960139B CN202410354295.6A CN202410354295A CN117960139B CN 117960139 B CN117960139 B CN 117960139B CN 202410354295 A CN202410354295 A CN 202410354295A CN 117960139 B CN117960139 B CN 117960139B
- Authority
- CN
- China
- Prior art keywords
- pixel
- sequence
- taking
- heating
- temperature difference
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 title claims abstract description 68
- 229910052742 iron Inorganic materials 0.000 title claims abstract description 34
- 239000012141 concentrate Substances 0.000 title claims abstract description 30
- 238000001914 filtration Methods 0.000 title claims abstract description 29
- 238000002360 preparation method Methods 0.000 title claims abstract description 26
- 230000000694 effects Effects 0.000 title claims abstract description 22
- 238000010438 heat treatment Methods 0.000 claims abstract description 160
- 238000004090 dissolution Methods 0.000 claims abstract description 69
- 238000000034 method Methods 0.000 claims abstract description 53
- HEMHJVSKTPXQMS-UHFFFAOYSA-M Sodium hydroxide Chemical compound [OH-].[Na+] HEMHJVSKTPXQMS-UHFFFAOYSA-M 0.000 claims abstract description 27
- 230000008569 process Effects 0.000 claims abstract description 27
- DPXJVFZANSGRMM-UHFFFAOYSA-N acetic acid;2,3,4,5,6-pentahydroxyhexanal;sodium Chemical compound [Na].CC(O)=O.OCC(O)C(O)C(O)C(O)C=O DPXJVFZANSGRMM-UHFFFAOYSA-N 0.000 claims abstract description 22
- 239000001768 carboxy methyl cellulose Substances 0.000 claims abstract description 22
- 235000019812 sodium carboxymethyl cellulose Nutrition 0.000 claims abstract description 22
- 229920001027 sodium carboxymethylcellulose Polymers 0.000 claims abstract description 22
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims abstract description 16
- 239000008235 industrial water Substances 0.000 claims abstract description 14
- PZNOBXVHZYGUEX-UHFFFAOYSA-N n-prop-2-enylprop-2-en-1-amine;hydrochloride Chemical compound Cl.C=CCNCC=C PZNOBXVHZYGUEX-UHFFFAOYSA-N 0.000 claims abstract description 14
- 239000000047 product Substances 0.000 claims abstract description 13
- 230000001105 regulatory effect Effects 0.000 claims abstract description 13
- 238000009826 distribution Methods 0.000 claims abstract description 12
- 229920000742 Cotton Polymers 0.000 claims abstract description 11
- 229910021578 Iron(III) chloride Inorganic materials 0.000 claims abstract description 11
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- RBTARNINKXHZNM-UHFFFAOYSA-K iron trichloride Chemical compound Cl[Fe](Cl)Cl RBTARNINKXHZNM-UHFFFAOYSA-K 0.000 claims abstract description 11
- 230000008859 change Effects 0.000 claims abstract description 10
- 238000006243 chemical reaction Methods 0.000 claims abstract description 9
- 239000007795 chemical reaction product Substances 0.000 claims abstract description 9
- 238000006266 etherification reaction Methods 0.000 claims abstract description 9
- 229910052757 nitrogen Inorganic materials 0.000 claims abstract description 8
- KUBWXQUHENSKGC-UHFFFAOYSA-N 2-chloroacetic acid;ethanol Chemical compound CCO.OC(=O)CCl KUBWXQUHENSKGC-UHFFFAOYSA-N 0.000 claims abstract description 7
- IDGUHHHQCWSQLU-UHFFFAOYSA-N ethanol;hydrate Chemical compound O.CCO IDGUHHHQCWSQLU-UHFFFAOYSA-N 0.000 claims abstract description 7
- 230000001276 controlling effect Effects 0.000 claims abstract description 6
- 239000000243 solution Substances 0.000 claims description 54
- 230000005855 radiation Effects 0.000 claims description 48
- 150000002500 ions Chemical class 0.000 claims description 37
- 230000005540 biological transmission Effects 0.000 claims description 33
- 238000010668 complexation reaction Methods 0.000 claims description 20
- 238000012546 transfer Methods 0.000 claims description 20
- 230000011218 segmentation Effects 0.000 claims description 15
- 239000013598 vector Substances 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 8
- 239000012456 homogeneous solution Substances 0.000 claims description 7
- 238000005259 measurement Methods 0.000 claims description 5
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 claims description 4
- 238000009825 accumulation Methods 0.000 claims description 4
- 230000001174 ascending effect Effects 0.000 claims description 3
- 230000000536 complexating effect Effects 0.000 claims description 3
- 238000001035 drying Methods 0.000 claims description 3
- 230000003472 neutralizing effect Effects 0.000 claims description 3
- 238000005406 washing Methods 0.000 claims description 3
- 239000007864 aqueous solution Substances 0.000 claims description 2
- 230000001186 cumulative effect Effects 0.000 claims description 2
- NLXLAEXVIDQMFP-UHFFFAOYSA-N Ammonia chloride Chemical compound [NH4+].[Cl-] NLXLAEXVIDQMFP-UHFFFAOYSA-N 0.000 claims 2
- 235000019270 ammonium chloride Nutrition 0.000 claims 1
- 238000005516 engineering process Methods 0.000 description 8
- 239000002994 raw material Substances 0.000 description 8
- 239000012065 filter cake Substances 0.000 description 7
- 230000006870 function Effects 0.000 description 4
- 238000001931 thermography Methods 0.000 description 4
- 238000004062 sedimentation Methods 0.000 description 3
- 239000002002 slurry Substances 0.000 description 3
- 230000002146 bilateral effect Effects 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 2
- 239000000706 filtrate Substances 0.000 description 2
- 239000004615 ingredient Substances 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- ORILYTVJVMAKLC-UHFFFAOYSA-N Adamantane Natural products C1C(C2)CC3CC1CC2C3 ORILYTVJVMAKLC-UHFFFAOYSA-N 0.000 description 1
- QGZKDVFQNNGYKY-UHFFFAOYSA-O Ammonium Chemical compound [NH4+] QGZKDVFQNNGYKY-UHFFFAOYSA-O 0.000 description 1
- DBMJMQXJHONAFJ-UHFFFAOYSA-M Sodium laurylsulphate Chemical compound [Na+].CCCCCCCCCCCCOS([O-])(=O)=O DBMJMQXJHONAFJ-UHFFFAOYSA-M 0.000 description 1
- 229910000831 Steel Inorganic materials 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 229920006318 anionic polymer Polymers 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229920006317 cationic polymer Polymers 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- GVGUFUZHNYFZLC-UHFFFAOYSA-N dodecyl benzenesulfonate;sodium Chemical compound [Na].CCCCCCCCCCCCOS(=O)(=O)C1=CC=CC=C1 GVGUFUZHNYFZLC-UHFFFAOYSA-N 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 239000010419 fine particle Substances 0.000 description 1
- 230000003311 flocculating effect Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000009878 intermolecular interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229920000642 polymer Polymers 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000006403 short-term memory Effects 0.000 description 1
- 229940080264 sodium dodecylbenzenesulfonate Drugs 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 239000004094 surface-active agent Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000002759 z-score normalization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
- G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J20/00—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof
- B01J20/02—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof comprising inorganic material
- B01J20/0203—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof comprising inorganic material comprising compounds of metals not provided for in B01J20/04
- B01J20/0225—Compounds of Fe, Ru, Os, Co, Rh, Ir, Ni, Pd, Pt
- B01J20/0229—Compounds of Fe
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J20/00—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof
- B01J20/02—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof comprising inorganic material
- B01J20/0203—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof comprising inorganic material comprising compounds of metals not provided for in B01J20/04
- B01J20/0274—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof comprising inorganic material comprising compounds of metals not provided for in B01J20/04 characterised by the type of anion
- B01J20/0288—Halides of compounds other than those provided for in B01J20/046
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J20/00—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof
- B01J20/22—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof comprising organic material
- B01J20/24—Naturally occurring macromolecular compounds, e.g. humic acids or their derivatives
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J20/00—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof
- B01J20/22—Solid sorbent compositions or filter aid compositions; Sorbents for chromatography; Processes for preparing, regenerating or reactivating thereof comprising organic material
- B01J20/26—Synthetic macromolecular compounds
- B01J20/262—Synthetic macromolecular compounds obtained otherwise than by reactions only involving carbon to carbon unsaturated bonds, e.g. obtained by polycondensation
Landscapes
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Organic Chemistry (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Engineering & Computer Science (AREA)
- Inorganic Chemistry (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Radiation Pyrometers (AREA)
Abstract
The application relates to the technical field of filter aid preparation, and provides a filter aid preparation method for improving the filtering effect of iron concentrate, which comprises the following steps: crushing cotton fibers, feeding the crushed cotton fibers into a high-pressure kneader, adding sodium hydroxide solution and ethanol water solution, regulating the high-pressure kneader to a vacuum state, inputting nitrogen for alkalization reaction, and adding chloroacetic acid ethanol solution into the alkalization reaction product; regulating the high-pressure kneader again to a vacuum state, inputting nitrogen for etherification reaction, and preparing sodium carboxymethyl cellulose from the products of the etherification reaction; adding industrial water into heating equipment, adding ferric chloride, sodium carboxymethylcellulose and polydimethyl diallyl ammonium chloride, adaptively regulating and controlling heating time based on the change of solution heat conductivity and analysis result of temperature distribution uniformity in the heating process, and adding industrial water after heating and dissolving to obtain a filter aid. According to the application, the heating time in the dissolution process is regulated and controlled in a self-adaptive manner, so that the preparation quality of the filter aid is improved.
Description
Technical Field
The application relates to the technical field of filter aid preparation, in particular to a preparation method of a filter aid for improving the filtering effect of iron concentrate.
Background
Iron ore is a developing raw material of the iron and steel industry, plays a vital role in the history of social industrialized development, and along with the continuous expansion of infrastructure, the demand for iron ore resources is increased, and the filter aid in the iron concentrate dressing process is also put forward a greater demand. The filter aid is a medicament for improving efficiency in solid-liquid separation in the process of filtering iron ore concentrate pulp, and can reduce the moisture content in a filter cake. At present, a disc type vacuum filter, a filter press and the like are adopted for filtering and dewatering of traditional iron concentrates, but the traditional filtering method is to add surfactant filter aids such as sodium dodecyl sulfate, sodium dodecyl benzene sulfonate and the like, so that the water content of the obtained filter cake is higher and is generally more than 10%, and the subsequent process requirements cannot be met.
In the preparation process of the filter aid for improving the filtering effect of the iron ore concentrate, the heating time length has obvious influence on the performance and quality of a final filter aid product, but the problems of a plurality of influence factors in the heating process, complex relation among components of a solution, large interference degree of industrial external environment, easy occurrence of uneven temperature and unstable heating time length in the preparation process of the filter aid and low quality of the filter aid product are solved.
Disclosure of Invention
The application provides a preparation method of a filter aid for improving the filtering effect of iron ore concentrate, which aims to solve the problem that the quality of the filter aid is affected by uneven temperature caused by unstable heating time in the preparation process of the filter aid, and adopts the following technical scheme:
The application relates to a preparation method of a filter aid for improving the filtering effect of iron ore concentrate, which comprises the following steps:
Crushing cotton fibers, feeding the crushed cotton fibers into a high-pressure kneader, adding sodium hydroxide solution and ethanol water solution, regulating the high-pressure kneader to a vacuum state, inputting nitrogen into the high-pressure kneader for alkalization reaction, and adding chloroacetic acid ethanol solution into the alkalization reaction product;
regulating the high-pressure kneader again to a vacuum state, inputting nitrogen into the high-pressure kneader for etherification reaction, and sequentially washing, neutralizing, centrifuging, drying and crushing the etherification reaction product to obtain sodium carboxymethyl cellulose;
Adding industrial water into heating equipment, adding ferric chloride, sodium carboxymethylcellulose and polydimethyl diallyl ammonium chloride, adaptively regulating and controlling heating time based on the change of solution heat conductivity and analysis result of temperature distribution uniformity in the heating process, and adding the industrial water after heating and dissolving until a filter aid with the weight percentage concentration of 5% is obtained.
Preferably, the ratio of the sodium hydroxide solution to the ethanol water solution is as follows: 1.23:1.69.
Preferably, the method for regulating the high-pressure kneader to a vacuum state comprises the following steps: the high-pressure kneader is evacuated to a pressure of-0.08 MPa.
Preferably, the reaction duration of the alkalization reaction is as follows: 45min.
Preferably, the ratio of the ferric chloride, the sodium carboxymethyl cellulose and the polydimethyl diallyl ammonium chloride is as follows: 1:20:29.
Preferably, the temperature of adding the industrial water after heating and dissolving is as follows: the heating temperature was 90℃and the industrial water temperature was 50 ℃.
Preferably, the method for adaptively adjusting and controlling the heating time based on the analysis result of the solution heat conductivity change and the temperature distribution uniformity in the heating process comprises the following steps:
Acquiring a heating dissolution image of each acquisition time in the heating dissolution process of ferric chloride, sodium carboxymethyl cellulose and polydimethyl diallyl ammonium chloride in heating equipment;
Respectively acquiring a spliced transmission sequence, a spliced pixel sequence, a source final transmission sequence and a source final pixel sequence of each pixel based on temperature values of different positions in each heating and dissolving image; the spliced transmission sequence, the spliced pixel sequence, the source terminal transmission sequence and the source terminal pixel sequence are all used as characteristic data sequences of each pixel;
Determining a local temperature conduction excellent index of each pixel based on the change of the temperature conductivity of the solution at each acquisition time and the characteristic data sequence of each pixel in each heating dissolution image;
Taking the extreme difference of the temperature value in a window with a preset size taken by taking each pixel as the center as the local temperature extreme difference of each pixel, taking a vector formed by the local temperature extreme difference, the source point temperature difference radiation intensity, the end point temperature difference radiation intensity and the local temperature conduction excellent index of each pixel as a temperature difference characteristic vector of each pixel, and dividing all pixels into a preset number of temperature difference equipotential classes based on the temperature difference characteristic vector of all pixels in each heating dissolved image by adopting a clustering algorithm;
Determining a temperature difference equipotential histogram of each pixel based on the statistical result of the number of pixels in each temperature difference equipotential class in a window with a preset size taken by each pixel;
Taking four vertex pixels of a window with a preset size taken by each pixel as one corner pixel of each pixel, and taking the sum of the accumulation sum and 0.01 sum of EMD distances between temperature difference equipotential histograms of each pixel and all corner pixels of each pixel as denominators;
taking a natural constant as a base number, taking a calculation result taking the opposite number of variances of all temperature values in a preset size window taken by each pixel as an index as a numerator, and taking the ratio of the numerator to a denominator as a scale factor;
Taking a sequence formed by ordering the number of the pixels in all the temperature difference equipotential classes in a preset size window taken by each pixel according to the sequence numbers of the temperature difference equipotential classes as a temperature difference equipotential number sequence of each pixel, and taking the product of the Herfidal index and the scale factor of the temperature difference equipotential number sequence of each pixel as a local temperature homogeneity index of each pixel;
determining a complexation confidence dissolution index of each heating dissolution image based on a clustering result of the local temperature homogeneity indexes of all pixels in each heating dissolution image;
and inputting the complexation confidence dissolution indexes of the heating dissolution images at all the acquisition moments into an LSTM model according to a heating control sequence of a time sequence composition sequence, and obtaining the heating duration of heating dissolution of the filter aid by using the LSTM model.
Preferably, the method for respectively obtaining the splicing transmission sequence, the splicing pixel sequence, the source final transmission sequence and the source final pixel sequence of each pixel based on the temperature values of different positions in each heating and dissolving image comprises the following steps:
Taking pixels corresponding to a maximum temperature value and a minimum temperature value in a window with preset size as a heat radiation source point and a heat radiation end point respectively;
taking all pixels in a window with a preset size taken by each pixel as one node in a graph, connecting the nodes corresponding to the pixels which are directly adjacent in the window, taking the absolute value of the difference value of the temperature values corresponding to the two nodes on each connecting line as the edge weight of each connecting line, and taking an undirected graph formed by all the pixels in the window with the preset size taken by each pixel as a heating window undirected graph of each pixel;
taking a heating window undirected graph of each pixel as input, taking a node corresponding to a heat radiation source point as a starting point, taking a node corresponding to a pixel in the center of the window as an ending point, acquiring a search path by using a BFS algorithm, and taking a sequence formed by all edge weights and pixels corresponding to all nodes on the search path with the maximum sum of edge weights of connecting lines as a source point transmission sequence and a source point pixel sequence respectively;
Taking a heating window undirected graph of each pixel as input, taking a node corresponding to a pixel in the center of the window as a starting point, taking a node corresponding to a thermal radiation end point as an ending point, acquiring a search path by using a BFS algorithm, and taking all edge weights on the search path with the maximum sum of edge weights through connection and sequences formed by pixels corresponding to all nodes as an end point transmission sequence and an end point pixel sequence respectively;
Taking a heating window undirected graph of each pixel as input, taking a node corresponding to a heat radiation source point as a starting point, taking a node corresponding to a heat radiation end point as an ending point, acquiring a search path by using a BFS algorithm, and taking all edge weights on the search path with the maximum sum of edge weights through connection and sequences formed by pixels corresponding to all nodes as a source terminal transmission sequence and a source terminal pixel sequence respectively;
the sequence obtained by splicing the source point transmission sequence and the end point transmission sequence end to end is used as a splicing transmission sequence of each pixel;
And the sequence obtained by splicing the source point pixel sequence and the end point pixel sequence end to end is used as a spliced pixel sequence of each pixel.
Preferably, the method for determining the local temperature conduction excellent index of each pixel based on the change of the solution temperature conductivity at each acquisition time and the characteristic data sequence of each pixel in each heating dissolution image comprises the following steps:
S1: taking a sequence formed by absolute values of differences between the temperature values of each element in the source point pixel sequence of each pixel and the temperature values of each pixel according to the pixel sequence as a source point temperature difference sequence of each pixel, and performing linear fitting on the source point temperature difference sequence of each pixel to obtain a source point fitting straight line of each pixel;
S2: the Euclidean distance from each element in the source point temperature difference sequence of each pixel to the source point fitting straight line is used as the temperature difference fitting distance of each element, a division threshold value is obtained by utilizing an Ojin threshold value algorithm based on the temperature difference fitting distances of all elements in the source point temperature difference sequence of each pixel, and the element with the temperature difference fitting distance larger than the division threshold value is used as one temperature difference fitting deviation data in the source point temperature difference sequence of each pixel;
S3: determining the temperature difference fitting tolerance of each element in the source point temperature difference sequence of each pixel based on the comparison result of the interval between each element in the source point temperature difference sequence of each pixel and the length of the source point temperature difference sequence;
S4: taking the absolute value of the difference between the temperature difference fitting distance of each temperature difference fitting deviation data in the source point temperature difference sequence of each pixel and the segmentation threshold value as a first difference value, taking the sum of the accumulation result of the ratio of the first difference value to the temperature difference fitting tolerance of each temperature difference fitting deviation data on all the temperature difference fitting deviation data in the source point temperature difference sequence and 0.01 as a denominator, and taking the ratio of the absolute value of the difference value of the temperature values of the first pixel and the second pixel in the source point pixel sequence of each pixel and the denominator as the source point temperature difference radiation intensity of each pixel;
replacing the source point pixel sequence of each pixel with the end point pixel sequence of each pixel, and repeating S1-S4 to obtain the end point temperature difference radiation intensity of each pixel;
Calculating the accumulated result of the absolute value of the difference value between the Euclidean distance between each element and each pixel in the source terminal pixel sequence of each pixel and the preset distance on the source terminal pixel sequence as a molecule; taking the sum of the DTW distance and 0.01 between the source final transfer sequence and the spliced transfer sequence of each pixel as a denominator, and taking the ratio of a numerator to the denominator as a first measurement distance; taking the product of the spliced pixel sequence of each pixel and the number of repeated pixels in the source final pixel sequence of each pixel and the first measurement distance as a local temperature difference radiation path assurance coefficient of each pixel;
And taking the sum of the source point temperature difference radiation intensity, the end point temperature difference radiation intensity and 1 of each pixel as a base number, and taking the calculation result of the local temperature difference radiation path assurance coefficient of each pixel as an index as the local temperature conduction excellent index of each pixel.
Preferably, the method for determining the complexing confidence dissolution index of each heating dissolution image based on the clustering result of the local temperature homogeneity index of all pixels in each heating dissolution image comprises the following steps:
taking the local temperature homogeneity indexes of all pixels in each heating dissolution image as input, and dividing the local temperature homogeneity indexes into a preset number of cluster clusters by adopting a clustering algorithm;
Taking a sequence formed by local temperature homogeneity indexes of all pixels in each cluster according to ascending order as a homogeneity sequence of each cluster;
Taking the average value of the local temperature homogeneity indexes of all pixels in each cluster as a homogeneity representative value of each cluster, taking the homogeneity representative values of all clusters as input, adopting an Ojin threshold algorithm to determine a segmentation threshold value of the homogeneity representative values, taking the cluster with each homogeneity representative value larger than the segmentation threshold value as a suspected ion complex region, and taking the cluster with each homogeneity representative value smaller than or equal to the segmentation threshold value as a suspected pure homogeneous solution region;
adding the sum of the Jacquard coefficient between the homogeneous sequence of each suspected ion complex region and the homogeneous sequence of any suspected pure homogeneous solution region and 0.01 on all suspected pure homogeneous solution regions as denominator;
Taking the ratio of the difference value between the homogeneous representative value and the segmentation threshold value of the homogeneous representative value of each suspected ion complex region and the denominator as the region complexing confidence coefficient of each suspected ion complex region;
Taking the ratio of the number of pixels in each suspected ion complex region to the number of pixels in each heated dissolution image as a duty factor of each suspected ion complex region, and taking the cumulative result of the product of the region complexation confidence coefficient of each suspected ion complex region and the duty factor on all the suspected ion complex regions in each heated dissolution image as the complexation confidence dissolution index of each heated dissolution image.
The beneficial effects of the application are as follows: the application aims to adjust the heating time length of the solution in the heating equipment in real time after the preparation flow of the filter aid is determined, construct the local temperature conduction excellent index of all pixels according to the local temperature radiation phenomenon and the transmission characteristic of the pixels in the heating dissolution image, reflect the heat transmission capability of the pixels in the heating dissolution image, and has the advantages that the non-central pixels far away from the central pixels in the source point pixel sequence are eliminated, the temperature difference is large, the problem of deviation of temperature difference fitting from data is extremely likely, and the calculation error is reduced; based on the local temperature uniformity of pixels in a heating and dissolving image, a complexation confidence dissolving index is constructed, the possibility that the reaction pixels belong to ion complexes is improved, a heating control sequence consisting of the complexation confidence dissolving index is input into an LSTM model to obtain optimal heating time, the problems that influence factors are numerous in the heating and dissolving process, the relation among components of a solution is complex, the heating time is preset to be poor in effect can be avoided, the heating time in the raw material heating and dissolving process in the preparation of a filter aid is adaptively obtained, the influence of the heating time on a filter aid product due to inappropriateness is avoided, and the product quality of the filter aid is improved.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for preparing a filter aid for improving the filtering effect of iron ore concentrate according to an embodiment of the present application;
FIG. 2 is a flow chart of an iron concentrate filtration process according to one embodiment of the present application;
FIG. 3 is a flow chart showing the method for preparing a filter aid for improving the filtering effect of iron ore concentrate according to an embodiment of the present application;
fig. 4 is a schematic diagram of a connection between nodes corresponding to adjacent pixels according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, a flowchart of a method for preparing a filter aid for improving a filtering effect of iron ore concentrate according to an embodiment of the present application is shown, the method includes the following steps:
And S001, determining the preparation flow of the filter aid.
The iron concentrate slurry is buffered through a conveying pipeline and then is input into a distribution tank, a filter aid is added into the distribution tank, the solid-liquid separation efficiency is provided, the filter is connected with the distribution tank for working, under the condition of vacuum negative pressure driving force, solid particles in the ore slurry are adsorbed on the surface of a fan-shaped filtrate piece of the filter, a filter cake with uniform thickness is formed, and then the iron concentrate filter cake is obtained through a scraper. The filtrate in the filter cake is pumped and filtered into a sedimentation tank, the bottom flow after sedimentation is sent into a filter again through a slurry pump for secondary filtration, the overflow is removed from the sedimentation tank, and the process flow of the iron concentrate filtration is shown in figure 2. However, the iron ore concentrate pulp has high viscosity and fine product particles, and the filter medium is easy to be blocked in the filtering process due to the strong dispersion capability of the fine particles, so that the water content in the filter cake is difficult to be effectively reduced, and therefore, the filter aid for improving the filtering effect of the iron ore concentrate is important. The preparation method of the filter aid for improving the filtering effect of the iron concentrate is completed cooperatively by the steps of preparing sodium carboxymethyl cellulose, preparing the filter aid and the like.
1. And (3) preparing sodium carboxymethyl cellulose. The mass ratio of each ingredient is as follows: cotton fiber: sodium hydroxide solution: aqueous ethanol solution: chloroacetic acid ethanol solution = 1:1.23:1.69:1.23.
Step s1: crushing cotton fibers, feeding the crushed cotton fibers into a high-pressure kneader, and adding sodium hydroxide solution and ethanol water solution, wherein the mass fractions of the sodium hydroxide solution and the ethanol water solution are respectively 48% and 95%, and the mass ratios of the cotton fibers, the sodium hydroxide solution and the ethanol water solution are respectively 1:1.23:1.69.
Step s2: vacuumizing the high-pressure kneader to a pressure of-0.08 MPa, inputting nitrogen into the high-pressure kneader to a pressure of 8.5MPa, and performing an alkalization reaction at a temperature of 50 ℃ for 45min to obtain an alkalization reaction product.
Step s3: and adding chloroacetic acid ethanol solution into the alkalization reaction product, wherein the mass fraction of the chloroacetic acid ethanol solution is 80%, and the mass ratio of the cotton fiber to the chloroacetic acid ethanol solution is 1:1.23.
Step s4: vacuumizing the high-pressure kneader again to a pressure of-0.08 MPa, inputting nitrogen into the high-pressure kneader to a pressure of 9MPa and a temperature of 65 ℃, and carrying out etherification reaction for 45min to obtain an etherification reaction product.
Step s5: washing, neutralizing, centrifuging, drying and crushing the etherification reaction product to obtain a finished sodium carboxymethyl cellulose product, and thus, the preparation of sodium carboxymethyl cellulose is completed.
2. And (5) preparing a filter aid. The mass ratio of the ingredients is ferric chloride, sodium carboxymethyl cellulose, polydimethyl diallyl ammonium chloride: industrial water=1:20:29:125.
Step s6: adding enough industrial water into heating equipment, and adding ferric chloride, sodium carboxymethyl cellulose and polydimethyl diallyl ammonium chloride, wherein the mass ratio of the ferric chloride to the sodium carboxymethyl cellulose to the polydimethyl diallyl ammonium chloride to the industrial water is 1:20:29:125, and the heating temperature is 90 ℃ to dissolve the raw materials.
Step s7: after the heating and dissolution are completed, adding 50 ℃ industrial water until a solution with the weight percentage concentration of 5% is obtained, namely the filter aid.
So far, the preparation flow of the filter aid is determined, and the subsequent adjustment of the heating time length is facilitated.
Step S002 determines a local temperature conduction excellent index for each pixel based on the change in the temperature conductivity of the solution at each acquisition time and the characteristic data sequence of each pixel in each heating dissolution image.
In the preparation process of the filter aid, the main raw materials are sodium carboxymethyl cellulose and polydimethyl diallyl ammonium chloride, wherein the sodium carboxymethyl cellulose is an anionic polymer, negative charges can be released in an aqueous solution, and the polydimethyl diallyl ammonium chloride is a cationic polymer with positive charges. When the two polymers are mixed, electrostatic attraction occurs between the negative charge of sodium carboxymethyl cellulose and the positive charge of polydimethyl diallyl ammonium chloride, and ion complexation is formed. When the heating time is too short, the raw materials are insufficiently dissolved, the ion complexation is less, the filter aid can not achieve the expected dispersing and flocculating effects, and the filtration efficiency of the iron concentrate and the quality of a filter cake are affected; when the heating time is too long, the movement of molecules in the solution is accelerated, the collision frequency and energy among the molecules are increased, the mutual attraction force among the molecules is reduced, the viscosity of the solution is reduced, and the heating equipment is damaged and the service life is shortened due to the too high temperature. And during the heating process, the ionic complex formed by sodium carboxymethyl cellulose and polydimethyl diallyl ammonium chloride increases the intermolecular interaction, and the temperature conductivity of the solution may decrease. In addition, during the heating and dissolving process, the raw materials are aggregated to form clusters, so that the temperature distribution of the solution is uneven, and the formation of a temperature gradient is easy to occur. Therefore, the application considers that the heating time length is adjusted based on the analysis result by specifically analyzing the temperature distribution condition in the solution in the heating process of the heating equipment, and the implementation flow of the whole scheme is shown in fig. 3.
Specifically, an endoscopic type furnace high-temperature infrared imager is placed in the heating equipment, and the heating and dissolving process of the raw materials of ferric chloride, sodium carboxymethyl cellulose and polydimethyl diallyl ammonium chloride is sampled and shot to obtain an infrared thermal imaging image of the solution. The time immediately after the heating equipment starts heating for 1min is taken as the first acquisition time, the time interval between two adjacent acquisition times is set to be 0.5s, the total acquisition time length is set to be 1min, and the shooting angle of the high-temperature infrared imager in the endoscopic furnace is overlooking. In order to avoid interference of the industrial complex environment on the infrared thermal imaging images, the infrared thermal imaging images acquired at all acquisition moments are denoised by bilateral filtering, each denoised infrared thermal imaging image is marked as a heating dissolution image, and the bilateral filtering denoising is a known technology, and the specific process is not repeated.
For any one acquisition time, taking a heating dissolution image obtained at the ith acquisition time as an example for analysis, taking an a pixel in the heating dissolution image obtained at the ith acquisition time as a center point, and constructing a heating window with the size of 9*9. Since the temperature is transferred from high temperature to low temperature, traversalThe temperature values of all the pixels in (a) will be/>, respectivelyAnd the pixels corresponding to the maximum value and the minimum value of the medium temperature value are used as heat radiation source points and heat radiation end points. Second, willAll pixels in the picture are taken as one node in the picture, andThe nodes corresponding to the directly adjacent pixels in the row are connected, as shown in fig. 4, the gray block in the figure represents the a-th pixel, the circle containing the gray block is the node corresponding to the a-th pixel, the absolute value of the difference value of the temperature values corresponding to the two nodes on each connection is taken as the edge weight of each connection, and the pixel is represented byAn undirected graph formed by all pixels is used as a heating window undirected graph/>, of the a pixel。
Further, to analyze the uniformity of temperature transfer between the a-th pixel and surrounding pixels, a heated window undirected graph is utilizedAnalysis of the transfer between different temperature values, in particular heating window undirected graphAs input, will/>, respectivelyThe node corresponding to the medium heat radiation source point and the node corresponding to the a pixel are used as a starting point and an ending point in path searching, and a BFS (Breadth FIRST SEARCH) algorithm is utilized to obtain a heating window undirected graphThe search paths are searched, the sum of edge weights passing through the connecting lines on each search path is calculated, and the sequence formed by all edge weights and all pixels corresponding to all nodes on the search path with the largest sum of edge weights passing through the connecting lines is respectively used as a source point transmission sequence and a source point pixel sequence of an a-th pixel; second, heating window undirected graphAs input, the a-th pixel is respectively corresponding to the node,The node corresponding to the medium heat radiation end point is used as a starting point and an ending point in path searching, a search path is obtained by using a BFS algorithm, and all edge weights on the search path with the largest sum of edge weights through connection lines and sequences formed by pixels corresponding to all nodes are respectively used as an end point transmission sequence and an end point pixel sequence of an a pixel; subsequently, the heating window undirected graphAs input, will/>, respectivelyNodes corresponding to heat radiation source points,The node corresponding to the medium heat radiation end point is used as a starting point and an ending point in path searching, and a BFS algorithm is utilized to obtain a heating window undirected graphThe search paths are searched, the sum of edge weights passing through the connecting lines on each search path is calculated, all edge weights on the search path with the largest sum of edge weights passing through the connecting lines and sequences formed by pixels corresponding to all nodes are respectively used as a source final transmission sequence and a source final pixel sequence of an a-th pixel, and BFS algorithm is a known technology, and specific processes are not repeated. And the sequence obtained by splicing the source point transmission sequence and the end point transmission sequence of the a-th pixel end to end is used as a splicing transmission sequence of the a-th pixel; and a sequence obtained by splicing the source point pixel sequence and the end point pixel sequence of the a-th pixel end to end is used as a spliced pixel sequence of the a-th pixel.
Further, the application takes the source point pixel sequence as an example to calculate the absolute value of the difference value between the temperature value of all elements in the source point pixel sequence of the a-th pixel and the temperature value of the pixel a, and takes the sequence formed by the absolute values of all elements in the source point pixel sequence according to the pixel sequence as the source point temperature difference sequence of the a-th pixelSequence source point temperature differenceThe sequence value of the elements in the sequence is respectively used as the abscissa and the ordinate to construct a data space, and a least square fitting algorithm is adopted to obtain a source point temperature difference sequenceThe fitting straight line of the a-th pixel is marked as a source point fitting straight line of the a-th pixel, euclidean distance from each element in the source point temperature difference sequence to the source point fitting straight line is used as a temperature difference fitting distance of each element, the temperature difference fitting distance of all elements in the source point temperature difference sequence is used as input, a division threshold value is obtained by utilizing an Ojin threshold algorithm based on the temperature difference fitting distance of all elements in the source point temperature difference sequence of each pixel, and each element with the temperature difference fitting distance larger than the division threshold value is used as one temperature difference fitting deviation data in the source point temperature difference sequence of the a-th pixel. The least square fitting algorithm and the oxford threshold algorithm are known techniques, and specific processes are not repeated.
Based on the above analysis, a local temperature conduction excellent index was constructed for characterizing the significance of each site temperature transfer phenomenon at each acquisition time in the heating apparatus. Calculating the local temperature conduction excellent index of the a pixel:
In the method, in the process of the invention, Is the source point temperature difference sequenceTemperature difference fitting tolerance of p-th element in (3)/>)Is the source point temperature difference sequenceThe interval between the p-th element and the corresponding element of the a-th pixel is equal to the number of elements between the p-th element and the corresponding element of the a-th pixel, and the size of the interval is equal to the number of elements between the p-th element and the corresponding element of the a-th pixelIs the source point temperature difference sequenceElement number inIs an exponential function based on natural constants;
Is the source point temperature difference radiation intensity of the a-th pixel, D is the absolute value of the difference value of the temperature values of the first and the last two pixels in the source point pixel sequence of the a-th pixel,/> Is the source point temperature difference sequenceTemperature difference fitting distance of p-th element in (1)/>)Is the source point temperature difference sequenceDividing threshold value of fitting distance of middle temperature differenceIs a parameter-adjusting factor for preventing denominator from being 0,The size of (2) is 0.01;
is the local temperature difference radiation path assurance coefficient of the a-th pixel,/> Is the number of repeated pixels in the spliced pixel sequence of the a-th pixel and the source terminal pixel sequence of the a-th pixel, m is the number of elements in the source terminal pixel sequence of the a-th pixel, q is the q-th element in the source terminal pixel sequence of the a-th pixel,Is the Euclidean distance between the q-th element and the a-th pixel,Is a preset distance,Is equal to the heating windowHalf of the diagonal length,、The source final transfer sequence and the splicing transfer sequence of the a-th pixel are respectivelyIs the sequence、The DTW distance between the two is a known technology, and the specific calculation process is not repeated;
Is the local temperature conduction excellent index of the a-th pixel,/> Is the end point temperature difference radiation intensity of the a pixel, and the calculation mode andConsistent, and not described in detail.
Wherein, the source point temperature difference sequence of the a-th pixelThe larger the interval between the p-th element and the corresponding element of the a-th pixel is, the greater the interval between the p-th element and the corresponding element of the a-th pixel isThe larger the value of (c), the smaller the interaction of the temperature transfer of the p-th element on the temperature transfer at the a-th picture element, the less pronounced the trend of temperature difference, should be given a greater tolerance,The purpose of such calculation is to avoid the influence of the deviation data on the temperature transfer, which is processed as a temperature difference fit, due to the larger interval; the more obvious the trend that the temperature of the pixel in the source point temperature difference sequence of the a pixel is reduced, the stronger the linear trend that the source point temperature difference sequence is provided with, the smaller the difference between the temperature difference fitting distance of the temperature difference fitting deviation data in the source point temperature difference sequence and the segmentation threshold value is, the first differenceThe smaller the value ofThe smaller the value of (2) the heating windowThe larger the temperature radiation transfer intensity from the internal heat radiation source point to the a-th pixel, the larger the temperature value difference between the first and the last two pixels in the source point pixel sequence of the a-th pixel, the larger the value of D, and the greater the value ofThe greater the value of (2); in the heating process, a heating windowThe more similar the temperature radiation transfer path passing through the a-th pixel is to the temperature radiation transfer path from the heat radiation source point to the heat radiation end point, the more the spliced pixel sequence of the a-th pixel and the repeated pixel in the source final pixel sequence of the a-th pixel are,The larger the value ofThe smaller the value of (2); the smaller the spatial distance between an element in the sequence of source final pixels and the a-th pixel,The larger the value of (2), the first metric distanceThe larger the value ofThe greater the value of (2); the more remarkable the phenomenon of radiation transmission of temperature at a high temperature point and the phenomenon of temperature transmission to a low temperature point exists at the a-th pixel、The greater the value of (2); i.e.The larger the value of (a), the more obvious the temperature transfer phenomenon is in the local area where the (a) th pixel is located in the heating and dissolving image obtained at the ith acquisition time, and the less likely the (a) th pixel is the pixel forming the ion complex.
So far, the local temperature conduction excellent index of each pixel is obtained and is used for subsequently constructing the temperature difference characteristic vector of each pixel.
Step S003, determining a complex confidence dissolution index for each heating dissolution image based on the clustering result of the local temperature homogeneity index for all pixels in each heating dissolution image.
In the preparation of the filter aid, the temperature of the solution is not uniform due to the aggregation of the raw materials and the influence of the ionic complex, and a temperature gradient is easily formed between the solution and the filter aid in the heating and dissolving process. Meanwhile, the degree of freedom of molecules in the solution is high, the degree of freedom of molecules in the ion complex is low, and in the heating and dissolving process just started, the pure solution part without the ion complex has more temperature gradients, and the solution part with the ion complex has less temperature gradients.
Specifically, a heating window taken by taking the a-th pixel as the center is calculatedThe range of the internal temperature value is used as the local temperature range of the a-th pixel, and a vector formed by the local temperature range, the source point temperature difference radiation intensity, the end point temperature difference radiation intensity and the local temperature conduction excellent index of the a-th pixel is used as a temperature difference characteristic vector of the a-th pixel and is used for reflecting the temperature gradient characteristic of the a-th pixel. According to the steps, the temperature difference feature vector of each pixel in the heating dissolution image obtained at the ith acquisition moment is obtained respectively, Z-score normalization processing is carried out on the temperature difference feature vectors of all the pixels to eliminate the influence of dimension, the normalized result of all the temperature difference feature vectors is used as input, the normalized result of the temperature difference feature vectors is divided into k clusters by adopting a k-shape clustering algorithm, each cluster is used as a temperature difference equipotential class, the number of the temperature difference equipotential class is 1-k, and the pixels in each temperature difference equipotential class have similar temperature gradient characteristics.
Further, statistics heating windowThe number of pixels of each temperature difference equipotential class will heat the windowThe all temperature difference equipotential classes in the picture comprise a sequence formed by the numbers of the pixels according to the sequence from small to large of the numbers of the temperature difference equipotential classes as a sequence of the temperature difference equipotential numbers of the a-th pixel. Secondly, taking the serial numbers of the temperature difference equipotential classes as the abscissa and the pixel number as the ordinate to obtain a heating windowThe statistical histogram of the (a) pixel is recorded as a temperature difference equipotential histogram of the (a) th pixel. Further, the window is heatedThe upper left corner, upper right corner, lower left corner and lower right corner pixels of the picture are all marked as corner pixels of the a-th pixel.
Based on the above analysis, a local temperature homogeneity index is constructed here to characterize the probability that each pixel is an ion complex pixel in the filter aid preparation solution. Calculating the local temperature homogeneity index of the a pixel:
In the method, in the process of the invention, Is the local temperature homogeneity index of the a pixel in the heating dissolution image obtained at the ith acquisition time,Is the Herfidal index of the sequence of the number of the temperature difference equipotential of the a-th pixel,Is a heating windowVariance of all temperature values in/(Is an exponential function based on a natural constant, M is the number of corner pixels of the a-th pixel, j is the j-th corner pixel of the a-th pixel,、The temperature difference equipotential histograms of the a pixel and the j corner pixel are respectively,IsAndEMD (Earth Mover' S DISTANCE) distance,Is a parameter-adjusting factor for preventing denominator from being 0,The EMD distance and the Hefyder index are all known techniques, and the specific process is not repeated.
Wherein the heating windowThe more concentrated the distribution of temperature values inThe smaller the value ofThe greater the value of (2); heating windowThe higher the degree of homogeneity, the more similar the temperature transfer at the corner pixel far from the a-th pixel is to the a-th pixel, the more similar the difference between the temperature radiation transfer phenomenon of the a-th pixel and the corner pixel of the a-th pixel is, the smaller the difference between the temperature difference equipotential histograms of the a-th pixel and the j-th corner pixel is,The smaller the value of (2); i.e.The larger the value of (2) the heating windowThe more uniform the temperature distribution, the more likely the a-th picture element is an ion complex picture element in solution in the heating device.
Further, the local temperature homogeneity indexes of all pixels in the heating dissolution image obtained at the ith acquisition time are used as input, the local temperature homogeneity indexes are divided into k clusters by adopting a k-means algorithm, the local temperature homogeneity indexes among the pixels in each cluster are relatively close, the pixels in each cluster are most likely to be positioned in a region with obvious temperature transmission phenomenon in the heating dissolution image, and the k-means algorithm is a known technology and a specific process is not repeated. In another embodiment, the local temperature homogeneity indexes of all pixels in the heating dissolution image obtained at the ith acquisition time are used as input, the local temperature homogeneity indexes are divided into k clusters by adopting a k-media algorithm, the measurement distance is the difference value between the local temperature homogeneity indexes of two pixels, the number of the clusters is determined by adopting an elbow method, the k clusters are output, the k-media algorithm is a known technology, and the specific process is not repeated.
Secondly, taking a sequence formed by local temperature homogeneity indexes of all pixels in each cluster according to ascending order as a homogeneity sequence of each cluster; and taking the average value of the local temperature homogeneity indexes of all pixels in each cluster as a homogeneity representative value of each cluster. And taking the homogeneous representative values of k clusters as input, determining a segmentation threshold value of the homogeneous representative values by adopting an Ojin threshold algorithm, taking each cluster with the homogeneous representative value larger than the segmentation threshold value as a suspected ion complex region, and taking each cluster with the homogeneous representative value smaller than or equal to the segmentation threshold value as a suspected pure uniform solution region, wherein the Ojin threshold algorithm is a known technology, and the specific process is not repeated.
Based on the above analysis, a complex confidence dissolution index was constructed for characterizing the sufficiency of heating dissolution at each acquisition time in the heating apparatus. Calculating a complexation confidence dissolution index of the heating dissolution image obtained at the ith acquisition time:
In the method, in the process of the invention, Is the region complexation confidence coefficient of the y-th suspected ion complex region,Is the homogeneous representation of the y-th suspected ion complex region,Is a segmentation threshold for homogeneous representative values,Is the number of suspected pure uniform solution areas in the heating and dissolving image obtained at the ith acquisition time, t is the t suspected pure uniform solution area,、The (y) th suspected ion complex region and the (t) th suspected pure homogeneous solution region,Is、Jie Lade coefficient between,Is a parameter-adjusting factor for preventing denominator from being 0,The value of (1) is 0.01, the Jacrad coefficient is a known technology, and the specific process is not repeated;
Is the complexation confidence dissolution index of the heating dissolution image obtained at the ith acquisition time,/> Is the number of suspected ion complex regions in the heated and dissolved image obtained at the ith acquisition time,Is the duty factor of the y-th suspected ion complex region,The size of the (c) is equal to the ratio of the number of pixels in the y-th suspected ion complex region to the number of pixels in the heated and dissolved image obtained at the i-th acquisition time.
Wherein, the more obvious the high homogeneity characteristic of the suspected ion complex region in the heating and dissolving image obtained at the ith acquisition time is, the more the pixel corresponding to the element in the suspected ion complex region accords with the characteristic of the ion complex in the heating and dissolving image, the larger the difference between the suspected ion complex region and the suspected pure uniform solution region is,The larger the value of (c) is,The smaller the value ofThe greater the value of (2); the larger the duty factor of the y-th suspected ion complex region, the larger the effect of the y-th suspected ion complex region on the whole heating dissolution image; i.e.The larger the value of (2), the higher the degree of formation of the ionic complex in the heated and dissolved image, and the more sufficient the heated and dissolved, and at this time, the more excellent the heated and dissolved effect in the filter aid production process, the more unnecessary the long heating period.
So far, the complexation confidence dissolution index of the corresponding heating dissolution image at each acquisition time in the heating process is obtained and is used for obtaining the heating time length in the heating equipment subsequently.
And S004, obtaining a heating control sequence by using the complexation confidence dissolution index of the heating dissolution image at all the acquisition time, and obtaining the heating time length of the filter aid for heating dissolution by using the LSTM model, thereby completing the preparation of the filter aid.
According to the steps, the complexation confidence dissolution index of the heating dissolution image obtained at each acquisition time in the heating process of the heating equipment is obtained respectively, and a sequence formed by the complexation confidence dissolution indexes of the heating dissolution images obtained at all the acquisition times according to the time sequence is used as a heating control sequence of heating dissolution. The heating control sequence for heating and dissolving is used as input, an LSTM (Long Short-Term Memory) model is used for outputting the optimized heating time length at each moment in the preparation process of the filter aid, an optimizer of the model is an Adam optimizer, a loss function is an L1 function, training of a neural network is a known technology, and specific processes are not repeated.
Secondly, after the optimal heating time length of each moment is obtained after the heating equipment starts to heat for 1min, the preparation personnel adjusts in real time according to the optimal heating time length of each moment as the heating time length of the solution in the heating equipment until the filter aid solution with the weight percentage concentration of 5% is obtained. Further, in order to apply the obtained filter aid, when the iron ore concentrate pulp is filtered in the iron ore dressing plant, the iron ore concentrate pulp is prepared into pulp with 65% weight concentration, and the pH value of the pulp is 11.8; the filter aid prepared by the method and the existing filter aid CB are respectively added into two identical ore pulp, wherein the adding proportion is that 0.1mL of the filter aid is added into each 100g of iron concentrate ore pulp, the filter aid is filtered after being uniformly mixed, and the application of the filter aid is completed.
Table 1 comparison of filtration effects
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. The foregoing description of the preferred embodiments of the present invention is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present invention are intended to be included within the scope of the present invention.
Claims (6)
1. A preparation method of a filter aid for improving the filtering effect of iron ore concentrate is characterized by comprising the following steps:
Crushing cotton fibers, feeding the crushed cotton fibers into a high-pressure kneader, adding sodium hydroxide solution and ethanol water solution, regulating the high-pressure kneader to a vacuum state, inputting nitrogen into the high-pressure kneader for alkalization reaction, and adding chloroacetic acid ethanol solution into the alkalization reaction product;
regulating the high-pressure kneader again to a vacuum state, inputting nitrogen into the high-pressure kneader for etherification reaction, and sequentially washing, neutralizing, centrifuging, drying and crushing the etherification reaction product to obtain sodium carboxymethyl cellulose;
Adding industrial water into heating equipment, then adding ferric chloride, sodium carboxymethylcellulose and polydimethyl diallyl ammonium chloride, adaptively regulating and controlling heating time based on the change of solution heat conductivity and analysis result of temperature distribution uniformity in the heating process, and adding the industrial water after heating and dissolving until a filter aid with the weight percentage concentration of 5% is obtained;
the method for adaptively regulating and controlling the heating time based on the analysis result of the heat conductivity change and the temperature distribution uniformity of the solution in the heating process comprises the following steps:
Acquiring a heating dissolution image of each acquisition time in the heating dissolution process of ferric chloride, sodium carboxymethyl cellulose and polydimethyl diallyl ammonium chloride in heating equipment;
Respectively acquiring a spliced transmission sequence, a spliced pixel sequence, a source final transmission sequence and a source final pixel sequence of each pixel based on temperature values of different positions in each heating and dissolving image; the spliced transmission sequence, the spliced pixel sequence, the source terminal transmission sequence and the source terminal pixel sequence are all used as characteristic data sequences of each pixel;
Determining a local temperature conduction excellent index of each pixel based on the change of the temperature conductivity of the solution at each acquisition time and the characteristic data sequence of each pixel in each heating dissolution image;
Taking the extreme difference of the temperature value in a window with a preset size taken by taking each pixel as the center as the local temperature extreme difference of each pixel, taking a vector formed by the local temperature extreme difference, the source point temperature difference radiation intensity, the end point temperature difference radiation intensity and the local temperature conduction excellent index of each pixel as a temperature difference characteristic vector of each pixel, and dividing all pixels into a preset number of temperature difference equipotential classes based on the temperature difference characteristic vector of all pixels in each heating dissolved image by adopting a clustering algorithm;
Determining a temperature difference equipotential histogram of each pixel based on the statistical result of the number of pixels in each temperature difference equipotential class in a window with a preset size taken by each pixel;
Taking four vertex pixels of a window with a preset size taken by each pixel as one corner pixel of each pixel, and taking the sum of the accumulation sum and 0.01 sum of EMD distances between temperature difference equipotential histograms of each pixel and all corner pixels of each pixel as denominators;
taking a natural constant as a base number, taking a calculation result taking the opposite number of variances of all temperature values in a preset size window taken by each pixel as an index as a numerator, and taking the ratio of the numerator to a denominator as a scale factor;
Taking a sequence formed by ordering the number of the pixels in all the temperature difference equipotential classes in a preset size window taken by each pixel according to the sequence numbers of the temperature difference equipotential classes as a temperature difference equipotential number sequence of each pixel, and taking the product of the Herfidal index and the scale factor of the temperature difference equipotential number sequence of each pixel as a local temperature homogeneity index of each pixel;
determining a complexation confidence dissolution index of each heating dissolution image based on a clustering result of the local temperature homogeneity indexes of all pixels in each heating dissolution image;
The complexation confidence dissolution indexes of the heating dissolution images at all the acquisition moments are input into an LSTM model according to a heating control sequence of a sequence formed by time sequences, and the heating duration of heating dissolution of the filter aid is obtained by using the LSTM model;
The method for respectively acquiring the splicing transfer sequence, the splicing pixel sequence, the source final transfer sequence and the source final pixel sequence of each pixel based on the temperature values of different positions in each heating and dissolving image comprises the following steps:
Taking pixels corresponding to a maximum temperature value and a minimum temperature value in a window with preset size as a heat radiation source point and a heat radiation end point respectively;
taking all pixels in a window with a preset size taken by each pixel as one node in a graph, connecting the nodes corresponding to the pixels which are directly adjacent in the window, taking the absolute value of the difference value of the temperature values corresponding to the two nodes on each connecting line as the edge weight of each connecting line, and taking an undirected graph formed by all the pixels in the window with the preset size taken by each pixel as a heating window undirected graph of each pixel;
taking a heating window undirected graph of each pixel as input, taking a node corresponding to a heat radiation source point as a starting point, taking a node corresponding to a pixel in the center of the window as an ending point, acquiring a search path by using a BFS algorithm, and taking a sequence formed by all edge weights and pixels corresponding to all nodes on the search path with the maximum sum of edge weights of connecting lines as a source point transmission sequence and a source point pixel sequence respectively;
Taking a heating window undirected graph of each pixel as input, taking a node corresponding to a pixel in the center of the window as a starting point, taking a node corresponding to a thermal radiation end point as an ending point, acquiring a search path by using a BFS algorithm, and taking all edge weights on the search path with the maximum sum of edge weights through connection and sequences formed by pixels corresponding to all nodes as an end point transmission sequence and an end point pixel sequence respectively;
Taking a heating window undirected graph of each pixel as input, taking a node corresponding to a heat radiation source point as a starting point, taking a node corresponding to a heat radiation end point as an ending point, acquiring a search path by using a BFS algorithm, and taking all edge weights on the search path with the maximum sum of edge weights through connection and sequences formed by pixels corresponding to all nodes as a source terminal transmission sequence and a source terminal pixel sequence respectively;
the sequence obtained by splicing the source point transmission sequence and the end point transmission sequence end to end is used as a splicing transmission sequence of each pixel;
the sequence obtained by splicing the source point pixel sequence and the end point pixel sequence end to end is used as a spliced pixel sequence of each pixel;
The method for determining the local temperature conduction excellent index of each pixel based on the change of the temperature conductivity of the solution at each acquisition time and the characteristic data sequence of each pixel in each heating dissolution image comprises the following steps:
S1: taking a sequence formed by absolute values of differences between the temperature values of each element in the source point pixel sequence of each pixel and the temperature values of each pixel according to the pixel sequence as a source point temperature difference sequence of each pixel, and performing linear fitting on the source point temperature difference sequence of each pixel to obtain a source point fitting straight line of each pixel;
S2: the Euclidean distance from each element in the source point temperature difference sequence of each pixel to the source point fitting straight line is used as the temperature difference fitting distance of each element, a division threshold value is obtained by utilizing an Ojin threshold value algorithm based on the temperature difference fitting distances of all elements in the source point temperature difference sequence of each pixel, and the element with the temperature difference fitting distance larger than the division threshold value is used as one temperature difference fitting deviation data in the source point temperature difference sequence of each pixel;
S3: determining the temperature difference fitting tolerance of each element in the source point temperature difference sequence of each pixel based on the comparison result of the interval between each element in the source point temperature difference sequence of each pixel and the length of the source point temperature difference sequence;
S4: taking the absolute value of the difference between the temperature difference fitting distance of each temperature difference fitting deviation data in the source point temperature difference sequence of each pixel and the segmentation threshold value as a first difference value, taking the sum of the accumulation result of the ratio of the first difference value to the temperature difference fitting tolerance of each temperature difference fitting deviation data on all the temperature difference fitting deviation data in the source point temperature difference sequence and 0.01 as a denominator, and taking the ratio of the absolute value of the difference value of the temperature values of the first pixel and the second pixel in the source point pixel sequence of each pixel and the denominator as the source point temperature difference radiation intensity of each pixel;
replacing the source point pixel sequence of each pixel with the end point pixel sequence of each pixel, and repeating S1-S4 to obtain the end point temperature difference radiation intensity of each pixel;
Calculating the accumulated result of the absolute value of the difference value between the Euclidean distance between each element and each pixel in the source terminal pixel sequence of each pixel and the preset distance on the source terminal pixel sequence as a molecule; taking the sum of the DTW distance and 0.01 between the source final transfer sequence and the spliced transfer sequence of each pixel as a denominator, and taking the ratio of a numerator to the denominator as a first measurement distance; taking the product of the spliced pixel sequence of each pixel and the number of repeated pixels in the source final pixel sequence of each pixel and the first measurement distance as a local temperature difference radiation path assurance coefficient of each pixel;
Taking the sum of the source point temperature difference radiation intensity, the end point temperature difference radiation intensity and 1 of each pixel as a base number, and taking the calculation result of the local temperature difference radiation path assurance coefficient of each pixel as an index as the local temperature conduction excellent index of each pixel;
The method for determining the complexation confidence dissolution index of each heating dissolution image based on the clustering result of the local temperature homogeneity index of all pixels in each heating dissolution image comprises the following steps:
taking the local temperature homogeneity indexes of all pixels in each heating dissolution image as input, and dividing the local temperature homogeneity indexes into a preset number of cluster clusters by adopting a clustering algorithm;
Taking a sequence formed by local temperature homogeneity indexes of all pixels in each cluster according to ascending order as a homogeneity sequence of each cluster;
Taking the average value of the local temperature homogeneity indexes of all pixels in each cluster as a homogeneity representative value of each cluster, taking the homogeneity representative values of all clusters as input, adopting an Ojin threshold algorithm to determine a segmentation threshold value of the homogeneity representative values, taking the cluster with each homogeneity representative value larger than the segmentation threshold value as a suspected ion complex region, and taking the cluster with each homogeneity representative value smaller than or equal to the segmentation threshold value as a suspected pure homogeneous solution region;
adding the sum of the Jacquard coefficient between the homogeneous sequence of each suspected ion complex region and the homogeneous sequence of any suspected pure homogeneous solution region and 0.01 on all suspected pure homogeneous solution regions as denominator;
Taking the ratio of the difference value between the homogeneous representative value and the segmentation threshold value of the homogeneous representative value of each suspected ion complex region and the denominator as the region complexing confidence coefficient of each suspected ion complex region;
Taking the ratio of the number of pixels in each suspected ion complex region to the number of pixels in each heated dissolution image as a duty factor of each suspected ion complex region, and taking the cumulative result of the product of the region complexation confidence coefficient of each suspected ion complex region and the duty factor on all the suspected ion complex regions in each heated dissolution image as the complexation confidence dissolution index of each heated dissolution image.
2. The method for preparing the filter aid for improving the filtering effect of the iron ore concentrate according to claim 1, wherein the mass ratio of the sodium hydroxide solution to the ethanol aqueous solution is as follows: 1.23:1.69.
3. The method for preparing the filter aid for improving the filtering effect of the iron ore concentrate according to claim 1, wherein the method for regulating and controlling the high-pressure kneader to a vacuum state is as follows: the high-pressure kneader is evacuated to a pressure of-0.08 MPa.
4. The method for preparing the filter aid for improving the filtering effect of the iron ore concentrate according to claim 1, wherein the reaction duration of the alkalization reaction is as follows: 45min.
5. The preparation method of the filter aid for improving the filtering effect of the iron ore concentrate according to claim 1, wherein the mass ratio of the ferric chloride, the sodium carboxymethyl cellulose and the polydimethyldiallyl ammonium chloride is as follows: 1:20:29.
6. The method for preparing the filter aid for improving the filtering effect of the iron ore concentrate according to claim 1, wherein the temperature of adding industrial water after heating and dissolving is as follows: the heating temperature was 90℃and the industrial water temperature was 50 ℃.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410354295.6A CN117960139B (en) | 2024-03-27 | 2024-03-27 | Preparation method of filter aid for improving filtering effect of iron concentrate |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410354295.6A CN117960139B (en) | 2024-03-27 | 2024-03-27 | Preparation method of filter aid for improving filtering effect of iron concentrate |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117960139A CN117960139A (en) | 2024-05-03 |
| CN117960139B true CN117960139B (en) | 2024-05-31 |
Family
ID=90863324
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410354295.6A Active CN117960139B (en) | 2024-03-27 | 2024-03-27 | Preparation method of filter aid for improving filtering effect of iron concentrate |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117960139B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118196090B (en) * | 2024-05-16 | 2024-08-20 | 盘锦嘉碳新材料有限公司 | Preparation method of special heat preservation material for graphite negative electrode material |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117753219A (en) * | 2024-01-02 | 2024-03-26 | 深圳市超一环境技术有限公司 | High-performance filter ultrafiltration membrane and preparation method thereof |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11167350B2 (en) * | 2018-04-23 | 2021-11-09 | The Trustees Of Indiana University | Droplet-based microreactors for nanoparticles |
-
2024
- 2024-03-27 CN CN202410354295.6A patent/CN117960139B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117753219A (en) * | 2024-01-02 | 2024-03-26 | 深圳市超一环境技术有限公司 | High-performance filter ultrafiltration membrane and preparation method thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117960139A (en) | 2024-05-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117960139B (en) | Preparation method of filter aid for improving filtering effect of iron concentrate | |
| CN117960020B (en) | Preparation method of filter aid for solid-liquid separation of iron concentrate | |
| Zhu et al. | Lightweight image super-resolution with expectation-maximization attention mechanism | |
| CN115353181B (en) | Intelligent flocculant dosage feeding method for papermaking wastewater | |
| CN112102238B (en) | Method for detecting swelling capacity of starch particles in gelatinization process based on computer vision | |
| CN104504662A (en) | Homomorphic filtering based image processing method and system | |
| CN116091504B8 (en) | Connecting pipe connector quality detection method based on image processing | |
| CN113129236A (en) | Single low-light image enhancement method and system based on Retinex and convolutional neural network | |
| CN113743424B (en) | Quantitative characterization method for dynamic flocculation sedimentation dispersion degree of flocs in dynamic flocculation sedimentation of full tailings | |
| CN115294106B (en) | Method for detecting uniformity of particles in latex solution | |
| Wang et al. | Global aligned structured sparsity learning for efficient image super-resolution | |
| CN108447072B (en) | Image segmentation method and system for crystal particles | |
| CN112419397A (en) | Ore particle size grading method and system based on image and deep neural network | |
| Wu et al. | Experimental analysis of image dehazing algorithms for pelletization process images | |
| CN116703893B (en) | Konjak gel measurement and control method based on machine vision | |
| CN117656243A (en) | Production method of lightweight porous domestic ceramic | |
| CN109308457B (en) | Multi-particle three-dimensional tracking method under high concentration | |
| CN106611418A (en) | Image segmentation algorithm | |
| CN114863313A (en) | Water treatment process monitoring method based on image recognition | |
| Wasson et al. | Full Reference Image Quality Assessment from IQA Datasets: A Review | |
| CN114140347A (en) | Unmanned aerial vehicle aerial image defogging and enhancing method based on dark channel prior | |
| CN110363745A (en) | A kind of bacillus recognition methods, device and the terminal device of fluorescence microscope images | |
| CN112686827A (en) | Image illumination homogenization algorithm improvement method | |
| Yu et al. | Study of image enhancement algorithms in coal mine | |
| CN115578388B (en) | Data processing method for textile production |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |