CN109061101A - Thickener underflow concentration, mud layer height, internal mine amount hard measurement device and method - Google Patents
Thickener underflow concentration, mud layer height, internal mine amount hard measurement device and method Download PDFInfo
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- 239000002562 thickening agent Substances 0.000 title claims abstract description 162
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000005259 measurement Methods 0.000 title claims abstract description 30
- 229910000831 Steel Inorganic materials 0.000 claims description 27
- 239000010959 steel Substances 0.000 claims description 27
- 230000008569 process Effects 0.000 claims description 15
- 239000007788 liquid Substances 0.000 claims description 8
- 239000011159 matrix material Substances 0.000 claims description 8
- 239000002002 slurry Substances 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 5
- 230000007246 mechanism Effects 0.000 claims description 4
- 239000012141 concentrate Substances 0.000 claims description 3
- 238000009826 distribution Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 101100134058 Caenorhabditis elegans nth-1 gene Proteins 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 8
- 238000012423 maintenance Methods 0.000 abstract description 7
- 238000003723 Smelting Methods 0.000 abstract description 2
- 230000000149 penetrating effect Effects 0.000 abstract 1
- 238000001514 detection method Methods 0.000 description 8
- 230000000694 effects Effects 0.000 description 6
- 230000005855 radiation Effects 0.000 description 6
- 229910052500 inorganic mineral Inorganic materials 0.000 description 5
- 239000011707 mineral Substances 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 238000009434 installation Methods 0.000 description 4
- 230000008719 thickening Effects 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 239000008394 flocculating agent Substances 0.000 description 2
- 238000009854 hydrometallurgy Methods 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 238000005272 metallurgy Methods 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- 238000011144 upstream manufacturing Methods 0.000 description 2
- CWYNVVGOOAEACU-UHFFFAOYSA-N Fe2+ Chemical compound [Fe+2] CWYNVVGOOAEACU-UHFFFAOYSA-N 0.000 description 1
- 238000005299 abrasion Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
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- 238000011143 downstream manufacturing Methods 0.000 description 1
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- 230000003203 everyday effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 230000002285 radioactive effect Effects 0.000 description 1
- 238000005406 washing Methods 0.000 description 1
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- G—PHYSICS
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Abstract
The present invention proposes a kind of thickener underflow concentration, mud layer height, internal mine amount hard measurement device and method, belongs to smelting field of selecting, including N number of pressure sensor, cable, wirerope and counterweight.N number of pressure sensor is used to measure the pressure of the ore pulp to be tested of different height in concentrator, lateral Hoisting Position of the wirerope on concentrator walking frame is determined according to the lateral position that n-th pressure sensor is located at, according to acquisition thickener underflow concentration value and N number of pressure sensor pressure data, fitting modeling, for measuring the underflow density of concentrator, the mud layer height, internal mine amount of ore pulp to be tested.The at low cost, install convenient of the present invention, there is no penetrating source problem, and maintenance period is long, easy to maintain.By applying at the scene, and with offline concentration Testing value, mud layer height measurements, enter mine amount and compare, illustrate that the measurement accuracy of the invention can satisfy production scene demand.
Description
Technical Field
The invention belongs to the field of concentration and metallurgy, and particularly relates to a soft measuring device and method for underflow concentration, mud layer height and internal ore quantity of a thickener of the thickener.
Background
With the rapid development of the country and the continuous promotion of the industrialization and urbanization processes, mineral resources are continuously developed and utilized, and high-grade ores are gradually reduced. The industry is increasingly faced with the problem of recovering mineral resources from poor, fine and miscellaneous ores, and the supply of mineral resources is under unprecedented pressure. The hydrometallurgical process has the advantages of capability of treating low-grade complex ores, high production efficiency, low emission and the like, and has increasingly wide application in the field of non-ferrous metal smelting. The thickener is typical solid-liquid separation equipment, is widely applied to a hydrometallurgy process, is an important process in a mineral separation production flow, plays a role in washing and thickening ore pulp, improves the concentration of the ore pulp, and has a certain function of adjusting the influence of production disturbance of an upstream process on a downstream process. Through the development of many years, from the flocculating agent that does not have at first adds to there being the flocculating agent to add, again to high-efficient thickener, deep cone thickener, the dense effect constantly promotes, still lacks the detection to the secret key variable of thickener, more can't accurately know the inside running state of thickener, mainly includes following two aspects: firstly, the underflow concentration of the thickener is difficult to detect, a ray concentration meter is mostly adopted for detecting the concentration of the ore pulp at present, and the application of a radiation source is more and more difficult due to the fact that the country pays more and more attention to the environmental protection problem; secondly, due to the problems that the mechanism of the thickening process is complex, the internal state is invisible and the like, the internal operation state of the thickener is lack of understanding, and the height of a mud layer and the internal ore amount of the thickener are difficult to detect. The thickener is a key device in mineral dressing metallurgy, but has the problem that key variables cannot be detected, so that the thickener cannot reach the optimal running state. At present, most of the underflow concentration of the thickener is detected by adopting a ray concentration meter, but the ray concentration meter has the defects of difficult examination and approval of a radiation source, difficult maintenance and the like.
Due to the lack of detection means and the incapability of detecting key variables, the underflow concentration of the thickener cannot be further improved, so that the process function of the process cannot be effectively exerted, and the production of upstream and downstream lines is interfered. The soft measurement method and the device for the underflow concentration, the mud layer height and the internal ore amount of the thickener can realize the soft measurement of the underflow concentration, the mud layer height and the internal ore amount, have low cost, convenient installation and small maintenance amount, not only solve the problem of detecting the key variable of the thickener, but also lay the foundation for the subsequent realization of the optimized control of the thickener.
Disclosure of Invention
The invention aims to solve the problem that the underflow concentration, the mud layer height and the internal ore amount of a thickener are difficult to detect, and the soft measuring device of the thickener is arranged inside the thickener, so that the underflow concentration, the mud layer height and the internal ore amount of the thickener are measured by using a soft measuring method, and workers can use the system to ensure the running safety of the thickener and simultaneously guide the production of a thickening process. Compared with the traditional radioactive concentration meter, the device can not only realize the detection of the concentration of the underflow, but also measure the internal information of the thickener, does not need a radiation source, is convenient to install and convenient to maintain.
The device for measuring the underflow concentration, the mud layer height and the internal ore quantity of the thickener comprises N pressure sensors, a cable, a steel cable and a balance weight;
the N pressure sensors are connected with cables, the cables are fixed on steel cables, one ends of the steel cables are fixed on a walking frame of the thickener, and the other ends of the steel cables are connected with a balance weight;
the N pressure sensors are used for measuring the pressure of ore pulp to be tested at different heights in the thickener, the number N of the pressure sensors is more than or equal to 3, the first pressure sensor is arranged on the interface of the slurry and the water of the ore pulp to be tested, the Nth pressure sensor is positioned at an ore outlet, and the N-2 pressure sensors in the middle are evenly distributed between the first pressure sensor and the Nth pressure sensor;
the cable is used for transmitting signals of the pressure sensor and is fixed on the steel cable, so that the pressure sensor is kept vertical in the rotating process of the thickener, and the pressure sensors are distributed at the same vertical position in the thickener according to different heights;
the steel cable is connected with the balance weight and used for keeping the vertical position of the steel cable unchanged in the rotation process of the thickener, and the transverse hoisting position of the steel cable on the running frame of the thickener is determined according to the transverse position of the Nth pressure sensor;
n pressure sensors measure to-be-tested ore pulp pressure modeling data to be P'1,P'2…,P'NThe real-time pressure to be tested is PS1,PS2…,PSNThe length of the cable is consistent with the height of the N pressure sensors and is h1,h2…,hNThe total height of the thickener is H, and the concentration value of the bottom flow of the thickener is C'UFThe height h of the mud layer and the internal ore amount M of the thickener.
Wherein the pressure difference between two adjacent pressure sensors should be more than 10 times of the maximum error of the sensors.
The method for soft measurement by using the soft measuring device for the underflow concentration, the mud layer height and the internal ore quantity of the thickener comprises the following steps:
step 1: collecting offline thickener underflow concentration value C'UFAnd recording pressure modeling data P 'of N pressure sensors at the same time'1,P'2…,P'NCollecting k groups of data as a group of data;
step 2: preprocessing the sampled data, removing outliers, and if the ith pressure value P of the jth group of datai' (j) standard deviation exceeding 3 sigmaiThat is, the outlier, all data of the jth group, σ, are removediThe total standard deviation of the sampling data of the ith pressure sensor is expressed by the formula (1);
wherein k is the data of k groups collected in the step 1,is the average value of k sets of pressure data, P, of the ith pressure sensori' (j) is the pressure value collected by the ith pressure sensor in the jth group of data;
there were m sets of data after treatment:
wherein, PN(m) is the pressure value of the nth pressure sensor in the mth group, and c (m) is the concentration value of the underflow obtained by offline measurement in the mth group;
step 3, identifying underflow concentration, mud layer height and internal ore quantity models of the thickener, wherein the identifying specifically comprises ①, ② and ③:
① identifying the underflow concentration model of the thickener, the concrete steps are shown in (a), (b), (c) and (d):
(a) the pressure difference Δ P of each of the 2 pressure sensors is obtained from the data obtained in step 2, as shown in the following equation (4),
wherein,a matrix with the expression that the delta P is m rows and N-1 columns; delta PNN-1(m) represents a pressure difference between the nth sensor and the (N-1) th sensor of the mth group;
(b) determining the average density of the slurry between each 2 pressure sensors from the pressure difference Δ PAs shown in the following equation (5):
wherein,to representIs a matrix of m rows and N-1 columns, g is 9.8N/kg, and Δ h is Δ h21,Δh32,…,ΔhNN-1The diagonal matrix Δ h formed is diag (Δ h)21,Δh32,…,ΔhNN-1) Wherein, Δ hNN-1Is the height difference between the pressure sensor N and the pressure sensor N-1, Δ hNN-1＝hN-hN-1；
(c) From the average density of the pulpThe average concentration of the ore pulp between every two pressure sensors is obtainedThe following formula (6):
wherein,to representIs a matrix of m rows and N-1 columns, p0The density of the concentrate is constant;
(d) from the average concentrationThe concentration value of the underflow of the thickener pretreated in the step 2Identifying a thickener underflow concentration model wherein the input is the average concentration of the slurry between every 2 pressure sensorsThe output is the underflow concentration C measured off-lineUFAnd identifying the functional relation between the average pulp concentration and the underflow concentration among every 2 pressure sensors by using a least square fitting and polynomial fitting method and taking the identification error as the principle, wherein the functional relation is as shown in the following formula (7):
② identifying the mud layer height model, which comprises the following steps:
(a) the knowledge of the mechanism of the thickener shows that the concentration distribution in the thickener is a power function, as shown in formula (8):
wherein, b1,b2,b3H is the distance between the measuring point and the liquid level of the thickener, and C (h) is the concentration at the depth h;
(b) identifying function parameters b1,b2,b3：
The parameter identification data is: concentration dataDepth dataWherein,the average concentration between the Nth pressure sensor and the N-1 th pressure sensor is obtained by the equation (6) CUFIs the concentration of the bottom flow of the thickener,the depth from the middle position of the Nth pressure sensor and the Nth-1 th pressure sensor to the liquid level is H, and the depth from the bottom of the thickener to the liquid level is also the total depth of the thickener; from concentration data CdAnd depth data hdAnd fitting the parameter b of the formula (8) by using a nonlinear fitting method1,b2,b3Wherein, in the formula (8), C (h) is represented by concentration data CdAs parameter identification data, h is represented by depth data hdAs parameter identification data;
(c) calculating the height of a mud layer of the thickener:
and (5) rewriting the formula (8) to obtain a mud layer height formula of the thickener, as shown in the formula (9):
by identifying parameter b in ② (b)1,b2,b3And a formula (9), when the concentration value of the corresponding height in the thickener is given manually, the positions of different concentrations in the thickener are obtained, namely the height of the mud layer of the thickener is obtained;
③ internal ore size model of thickener:
the internal ore quantity soft measurement model has the following calculation formula:
wherein, S (h) ═ r2(h) R (h) is the relation between the depth h and the radius of the thickener at the depth h, and is obtained according to the size of the thickener; h is the total height of the thickener; rho0C (h) is the ore pulp concentration of depth h, the height h of a mud layer of the thickener is obtained in step ②, and the ore pulp concentration C (h) of corresponding depth is obtained according to the formula (8);
and 4, step 4: calculating the underflow concentration, the height of a mud layer and the internal ore amount of the ore pulp thickener to be detected:
(a) calculating the underflow concentration real-time value of the thickener:
detecting real-time pressure P of ore pulp to be detected through pressure sensorS1,PS2…,PSNCalculating the underflow concentration real-time value of the thickener according to the formulas (4), (5), (6) and (7);
(b) identifying the parameters of the mud layer height model and calculating the mud layer height:
from real-time pressure data PS1,PS2…,PSNAnd equations (4), (5) and (6) to obtain the average concentration between the two pressure sensors, identifying the real-time model parameters of the height of the mud layer according to step ② (b), manually giving the concentration value of the corresponding height in the thickener, and obtaining the height of the mud layer of the thickener according to equation (9);
(c) calculating the internal ore amount:
calculating the pulp concentration C (h) according to the height value of the thickener mud layer in the step 4(b) and a formula (8), wherein a function parameter b in the formula (8)1,b2,b3And (c) substituting the calculated ore pulp concentration C (h) into a formula (10) by using the mud layer height real-time model parameters identified in the step 4(b) to obtain internal ore volume data.
The beneficial effects are as follows:
the soft measuring device and method for the underflow concentration, the mud layer height and the internal ore amount of the thickener not only solve the problem of detecting the underflow concentration of the thickener, but also realize the detection of the mud layer height and the internal ore amount of the thickener. The invention has low cost, the equipment mainly comprises a pressure sensor, a steel cable and a counterweight, and the cost is greatly reduced compared with other concentration detection equipment; the installation is convenient and fast, the whole structure of the device is simple, the installation can be finished only by determining the installation height, fixing the pressure sensor on the steel cable and then fixing the steel cable on the walking frame; the device has no problem of a radiation source, does not need the examination and approval of the radiation source, and does not need to manage the radiation source in the using process; the device has the advantages that the maintenance period is long, the maintenance is convenient, the part needing to be maintained is mainly the pressure sensor, the ore pulp in the thickener flows slowly, the abrasion to the pressure sensor is small, the maintenance period is 6 months on the installed detection equipment, and only the sensor needs to be replaced during the maintenance, and the device is simple in structure and convenient to maintain. The method is applied on site and compared with sampling data, a mud layer height measurement value and an ore entering amount, and the measurement precision of the method can meet the requirements of a production site.
Drawings
FIG. 1 is a schematic view of the mounting location of a pressure sensor in a thickener;
FIG. 2 is a comparison of a soft measurement of underflow concentration and an offline concentration measurement of a thickener;
FIG. 3 is a comparison of the mud layer height soft measurement value and the actual mud layer height value;
FIG. 4 is a comparison of soft measurements of the amount of ore in the thickener with the sampled values;
FIG. 5 is a flow chart of a soft measurement method for underflow concentration, mud layer height and internal ore amount of a thickener.
In the figure, 1 is a running frame of a thickener, 2 is a pressure sensor 1, 3 is a pressure sensor N-1, 4 is a pressure sensor N, 5 is a steel cable, 6 is a cable, and 7 is a counterweight.
Detailed Description
The soft measuring device and method for the underflow concentration, the mud bed height and the internal ore amount of the thickener are described in detail by aiming at the attached drawings:
the device for measuring the underflow concentration, the mud layer height and the internal ore quantity of the thickener comprises N pressure sensors (2) (3) (4), a cable (6), a steel cable (5) and a counterweight (7) as shown in figure 1;
the N pressure sensors (2), (3) and (4) are connected with a cable (6), the cable (6) is fixed on a steel cable (5), one end of the steel cable (5) is fixed on the walking frame (1) of the thickener, and the other end of the steel cable is connected with a counterweight (7);
the N pressure sensors (2), (3) and (4) are used for measuring the pressure of ore pulp to be tested at different heights in the thickener, the number N of the pressure sensors is more than or equal to 3, the first pressure sensor (2) is arranged on a muddy water interface of the ore pulp to be tested, the Nth pressure sensor (4) is positioned at an ore outlet, and the N-2 pressure sensors (3) in the middle are evenly distributed between the first pressure sensor (2) and the Nth pressure sensor (4);
the cable (6) is used for transmitting signals of the pressure sensor and is fixed on the steel cable (5), so that the pressure sensor is kept vertical in the rotating process of the thickener, and the pressure sensors are distributed at the same vertical position in the thickener according to different heights;
the steel cable (5) is connected with the counterweight (7) and used for keeping the vertical position unchanged in the rotation process of the thickener, and the transverse hoisting position of the steel cable (5) on the running frame (1) of the thickener is determined according to the transverse position of the Nth pressure sensor (4);
n pressure sensors (2) (3) (4) measure pulp pressure modeling data to be tested to be P'1,P'2…,P'NThe real-time pressure to be tested is PS1,PS2…,PSNThe length of the cable (6) is consistent with the height of the N pressure sensors (2), (3) and (4), and is h1,h2…,hNThe total height of the thickener is H, and the concentration value of the bottom flow of the thickener is C'UFThe height h of the mud layer and the internal ore amount M of the thickener.
Wherein the pressure difference between two adjacent pressure sensors should be more than 10 times of the maximum error of the sensors.
The measured value of the pressure sensor is sent to an AB433F4 analog quantity wireless transmission module through a cable, the wireless transmission module transmits the measured value of the pressure to an upper computer, the upper computer is a Lenovo think centre computer, a Windows 7 operating system is adopted, MATLAB 2010a is algorithm software, algorithms for soft measurement of underflow concentration, mud bed height and internal ore quantity of the thickener are compiled, the pressure value is detected in real time, the underflow concentration, the mud bed height and the internal ore quantity value are calculated through the algorithms, a display interface is compiled through C #2008 programming software, and the real-time calculated value is displayed through a display screen.
2, the method of the soft measuring device for the underflow concentration, the mud bed height and the internal ore amount of the thickener, as shown in fig. 5, comprises the following steps:
step 1 and step 2: collecting a underflow concentration value of a thickener, recording pressure data of N pressure sensors, preprocessing the sampled data, and removing outliers;
a total of 200 sets of data were collected by manual sampling, 20 of which were selected to illustrate the modeling process, e.g., data with outliers removed. The number N of the pressure sensors is 3;
wherein, the pressure data P is shown in Table 1:
table 1: pressure data P obtained by 3 pressure sensors
| P1(kPa) | P2(kPa) | P3(kPa) |
| 31.4 | 38.9 | 48.1 |
| 31.4 | 38.7 | 47.8 |
| 31.4 | 38.8 | 48.1 |
| 31.3 | 38.7 | 47.7 |
| 31.1 | 38.3 | 45.8 |
| 31.0 | 38.2 | 45.7 |
| 31.1 | 38.3 | 45.8 |
| 31.0 | 38.1 | 45.4 |
| 31.1 | 38.5 | 46.3 |
| 31.1 | 38.6 | 46.2 |
| 31.8 | 37.9 | 44.4 |
| 31.8 | 37.6 | 44.3 |
| 31.8 | 37.8 | 44 |
| 32.2 | 39.1 | 47 |
| 32.1 | 38.7 | 46.2 |
| 32.1 | 38.7 | 46.2 |
| 32.1 | 38.8 | 45.8 |
| 32.1 | 38.7 | 46 |
| 31.7 | 37.3 | 43.7 |
| 31.7 | 37.2 | 43.7 |
Wherein the corresponding underflow concentration C is determined by an off-line concentration pot methodUFAs shown in table 2, at this time, the underflow concentration is the underflow concentration value obtained while the pressure sensor transmits the pressure value;
TABLE 2 underflow concentration values determined by the offline concentration pot method
Step 3, identifying underflow concentration, mud layer height and internal ore quantity models of the thickener, wherein the identifying specifically comprises ①, ② and ③:
① identifying the underflow concentration model of the thickener, the concrete steps are shown as (a), (b), (c) and (d), (a) calculating the pressure difference delta P of each 2 pressure sensors according to the data obtained in step 2, as shown in Table 3:
TABLE 3 pressure differential Δ P per 2 pressure sensors
| P2-P1(kPa) | P3-P2(kPa) |
| 7.5 | 9.2 |
| 7.3 | 9.1 |
| 7.4 | 9.3 |
| 7.4 | 9 |
| 7.2 | 7.5 |
| 7.2 | 7.5 |
| 7.2 | 7.5 |
| 7.1 | 7.3 |
| 7.4 | 7.8 |
| 7.5 | 7.6 |
| 6.1 | 6.5 |
| 5.8 | 6.7 |
| 6.0 | 6.2 |
| 6.9 | 7.9 |
| 6.6 | 7.5 |
| 6.6 | 7.5 |
| 6.7 | 7 |
| 6.6 | 7.3 |
| 5.6 | 6.4 |
| 5.5 | 6.5 |
(b) Determining the average density of the slurry between each 2 pressure sensors from the pressure difference Δ PSolving for average Density by equation (5)Wherein g is 9.8N/kg, height h of the pressure sensor 113.3m, height h of the pressure sensor 22Is 3.8m, the height h of the pressure sensor 33At 4.3m, Δ h ═ diag (0.5m ), and the results are shown in table 4:
TABLE 4 average DensityCalculation results
(c) From the average density of the pulpThe average concentration of the ore pulp between every two pressure sensors is obtainedSolving the average concentration of pulp between each 2 pressure sensors by equation (6)Where ρ is0＝4.27kg/m3The calculation results are shown in table 5:
TABLE 5 average pulp concentration between 2 pressure sensorsCalculation results
(d) From the average concentrationThe concentration value C of the underflow of the thickener pretreated in the step 2UFIdentifying a bottom flow concentration model of the thickener, wherein in order to accurately obtain 200 groups of data of the model, a polynomial fitting method is adopted to obtain:
② identifying the mud layer height model, which comprises the following steps:
(a) the knowledge of the mechanism of the thickener shows that the concentration distribution in the thickener is a power function, as shown in formula (8):
wherein, b1,b2,b3H is the distance between the measuring point and the liquid level of the thickener, and C (h) is the concentration at the depth h;
(b) identifying function parameters b1,b2,b3：
Take the first set of data as an example, namelyThe content of the carbon dioxide is 0.452,0.610, the height of the mud layer is identified, and C is obtained from the underflow concentration value in the first row of the table 2UFIf not 0.773, therefore, take Cd＝[0.452,0.610,0.773]T；
Height h of pressure sensor 113.3m, height h of the pressure sensor 22Is 3.8m, the height h of the pressure sensor 33Is 4.3m, so hd＝[3.55,4.05,5.3]TIdentifying the parameter in equation (8), b, by a non-linear fitting method1＝-37.92,b2＝-3.55,b30.88 yield c (h) -37.92h-3.55+0.88；
(c) Calculating the height of the mud layer of the thickener,
when the concentration is selected to be 0.4 as the height of the mud layer, C (h) is 0.4, and the formula is substituted to obtain h which is 3.42 m;
③ internal ore size model of thickener:
from the thickener dimension map, the method can be used to determine
Adding C (h) to-37.92 h-3.55+0.88，ρ0＝4.27kg/m3H is 5.3, s (H) and formula (10), the internal ore content of the thickener is: and M is 104 tons.
And 4, step 4: the method comprises the following steps of calculating the underflow concentration, the height of a mud layer and the internal ore amount of the ore pulp thickener to be detected:
(a) calculating the underflow concentration real-time value of the thickener:
the real-time pressure of the ore pulp to be detected is detected to be P1 ═ 32.1kPa, P2 ═ 38.7kPa, P3 ═ 46.2kPa through the pressure sensor, and the pressure difference of each 2 sensors is calculated according to the formula (4): Δ P ═ 6.67.5;
calculated from equation (5) where g is 9.8N/kg and Δ h is diag (0.5m )
Calculated from equation (6)
Substitute it into formulaObtaining the underflow concentration CUF＝0.530。
(b) Identifying the parameters of the mud layer height model and calculating the mud layer height:
from real-time pressure data PS1,PS2…,PSNAnd (4), (5) and (6) calculating the average concentration between the two pressure sensors, identifying the real-time model parameter of the height of the mud layer according to the step ② (b), and obtaining Cd＝[0.3340.4530.530]T；
The height of the pressure sensor 1 is 3.3m, the height of the pressure sensor 2 is 3.8m, the height of the pressure sensor 3 is 4.3m, and the bottom height of the thickener is 5.3m, so hd＝[3.55,4.05,5.3]T；
Identification of parameter b in equation (8) by nonlinear fitting method1＝-508.52,b2＝-6.13,b30.55 yield c (h) -508.52h-6.13+0.55, and then obtaining a mud layer height real-time model as follows:
when C (h) is given by manpower and 0.4 is given, the formula is substituted, and h is 3.77m
(c) Calculating the internal ore amount:
calculating the pulp concentration C (h), C (h) -508.52h according to the height value of the thickener mud layer in the step 4(b) and the formula (8)-6.13+0.55, wherein the function parameter b in equation (8)1,b2,b3And (c) substituting the calculated ore pulp concentration C (h) into a formula (10) by using the mud layer height real-time model parameters identified in the step 4(b) to obtain internal ore volume data. From the thickener dimension map, the method can be used to determine
Where ρ is0＝4.27kg/m3H5.3, mixing C (H) with-508.52H-6.13+0.55 for formula (10) to give M ═ 58 tons
3, the practical application effect of the thickener underflow concentration, mud layer height and internal ore amount soft measuring device is illustrated through three aspects:
(1) soft measurement effect of underflow concentration:
after the device is applied on site, underflow ore pulp is sampled every day, concentration values are detected, the underflow concentration is compared with soft-measurement underflow concentration, and a comparison effect graph of the underflow concentration soft-measurement and offline concentration detection values of a thickener in figure 2 can be seen from the graph: the soft measurement value of the underflow concentration is very close to the off-line concentration detection value (concentration pot method), and the average relative error is 2.83 percent through calculation.
(2) Mud layer height soft measurement effect:
the mud layer height can be measured by inserting a pipe into the thickener, measuring the mud layer height of the thickener by the method on site, and counting the mud layer height corresponding to the soft measurement at the moment, as shown in fig. 3.
As can be seen from the graph, the soft measurement value of the mud layer height is consistent with the mud layer height variation trend measured through the pipe, the average relative error is calculated to be 5.1%, and the requirements of a production field are met.
(3) Soft measurement effect of inside ore deposit:
because there is no way to directly measure the true value of the internal ore amount of the thickener, the accuracy of the internal ore amount soft measurement can be only checked by an indirect method. Counting the ore quantity M of the thickener every dayINThe amount of ore M flowing out of the bottom of the thickener every dayUFInternal amount of ore M at the beginning0Internal mine mass M at the endendThe 4 values satisfy the following relationship:
MIN＝MUF+(M0-Mend) (11)
wherein M isINThe ore amount of the thickener is added in one day, QIN,CINThe ore feeding flow and the ore feeding concentration of the thickener can be respectively detected by an electromagnetic flowmeter and a ray concentration meter, and the measurement is accurate. MOUTIs a thickener 1Amount of mined material in the day, QUF,CUFThe underflow flow of the thickener and the underflow concentration value of the thickener are measured by the soft sensor, and the underflow flow of the thickener is detected by an electromagnetic flowmeter; m0，MendThe amount of ore in the thickener at the beginning of the day and the amount of ore in the thickener at the end of the day can be obtained by the equation (11). The statistics of the daily concentrate output over a period of time are shown in figure 4.
As can be seen from FIG. 4, the average relative error between the ore loading amount of the thickener and the change value and the average relative error between the ore removal amount of the thickener and the change value of the internal ore amount of the thickener are 5.7%, the change trends are consistent, and the internal ore amount soft measurement value can reflect the change situation of the ore amount of the thickener through an indirect way.
Claims (3)
1. The device for measuring underflow concentration, mud layer height and internal ore quantity of the thickener is characterized by comprising N pressure sensors, a cable, a steel cable and a balance weight;
the N pressure sensors are connected with cables, the cables are fixed on steel cables, one ends of the steel cables are fixed on a walking frame of the thickener, and the other ends of the steel cables are connected with a balance weight;
the N pressure sensors are used for measuring the pressure of ore pulp to be tested at different heights in the thickener, the number N of the pressure sensors is more than or equal to 3, the first pressure sensor is arranged on the interface of the slurry and the water of the ore pulp to be tested, the Nth pressure sensor is positioned at an ore outlet, and the N-2 pressure sensors in the middle are evenly distributed between the first pressure sensor and the Nth pressure sensor;
the cable is used for transmitting signals of the pressure sensor and is fixed on the steel cable, so that the pressure sensor is kept vertical in the rotating process of the thickener, and the pressure sensors are distributed at the same vertical position in the thickener according to different heights;
the steel cable is connected with the balance weight and used for keeping the vertical position of the steel cable unchanged in the rotation process of the thickener, and the transverse hoisting position of the steel cable on the running frame of the thickener is determined according to the transverse position of the Nth pressure sensor;
n pressure sensors measure to-be-tested ore pulp pressure modeling data to be P'1,P'2…,P'NThe real-time pressure to be tested is PS1,PS2…,PSNThe length of the cable is consistent with the height of the N pressure sensors and is h1,h2…,hNThe total height of the thickener is H, and the concentration value of the bottom flow of the thickener is C'UFThe height h of the mud layer and the internal ore amount M of the thickener.
2. The thickener underflow concentration, mud bed height and internal ore amount soft measuring device according to claim 1, which is characterized in that: the pressure difference between two adjacent pressure sensors should be more than 10 times the maximum error of the sensors.
3. The method for soft measurement by using the thickener underflow concentration, mud bed height and internal ore amount soft measurement device as claimed in claim 1 is characterized by comprising the following steps:
step 1: collecting offline test thickener underflow concentration value C'UFAnd recording the pressure modeling data P 'of the N pressure sensors at the same time'1,P'2…,P'NCollecting k groups of data as a group of data;
step 2: preprocessing the sampling data, removing outliers, and if the ith pressure value P 'of the jth group of data'i(j) Standard deviation exceeding 3 sigmaiI.e. outlier, the jth group is removedAll data, σiThe total standard deviation of the sampling data of the ith pressure sensor is expressed by the formula (1);
wherein k is the data of k groups collected in the step 1,is the average value, P ', of the k sets of pressure data of the ith pressure sensor'i(j) The pressure value collected by the ith pressure sensor is the jth group of data;
there were m sets of data after treatment:
wherein, PN(m) is the pressure value of the nth pressure sensor in the mth group, and c (m) is the concentration value of the underflow obtained by offline measurement in the mth group;
step 3, identifying underflow concentration, mud layer height and internal ore quantity models of the thickener, wherein the identifying specifically comprises ①, ② and ③:
① identifying the underflow concentration model of the thickener, the concrete steps are shown in (a), (b), (c) and (d):
(a) the pressure difference Δ P of each of the 2 pressure sensors is obtained from the data obtained in step 2, as shown in the following equation (4),
wherein,a matrix with the expression that the delta P is m rows and N-1 columns; delta PNN-1(m) denotes the mth group of nth transmissionsPressure differential between the sensor and the (N-1) th sensor;
(b) determining the average density of the slurry between each 2 pressure sensors from the pressure difference Δ PAs shown in the following equation (5):
wherein,to representIs a matrix of m rows and N-1 columns, g is 9.8N/kg, and Δ h is Δ h21,Δh32,…,ΔhNN-1The diagonal matrix Δ h formed is diag (Δ h)21,Δh32,…,ΔhNN-1) Wherein, Δ hNN-1Is the height difference between the pressure sensor N and the pressure sensor N-1, Δ hNN-1＝hN-hN-1；
(c) From the average density of the pulpThe average concentration of the ore pulp between every two pressure sensors is obtainedThe following formula (6):
wherein,to representIs a matrix of m rows and N-1 columns, p0The density of the concentrate is constant;
(d) from the average concentrationThe concentration value of the underflow of the thickener pretreated in the step 2Identifying a thickener underflow concentration model wherein the input is the average concentration of the slurry between every 2 pressure sensorsThe output is the underflow concentration C of an off-line testUFAnd identifying the functional relation between the average pulp concentration and the underflow concentration among every 2 pressure sensors by using a least square fitting and polynomial fitting method and taking the identification error as the principle, wherein the functional relation is as shown in the following formula (7):
② identifying the mud layer height model, which comprises the following steps:
(a) the knowledge of the mechanism of the thickener shows that the concentration distribution in the thickener is a power function, as shown in formula (8):
wherein, b1,b2,b3H is the distance between the measuring point and the liquid level of the thickener, and C (h) is the concentration at the depth h;
(b) identifying function parameters b1,b2,b3：
The parameter identification data is: concentration dataDepth dataWherein,the average concentration between the Nth pressure sensor and the N-1 th pressure sensor is obtained by the equation (6) CUFIs the concentration of the bottom flow of the thickener,the depth from the middle position of the Nth pressure sensor and the Nth-1 th pressure sensor to the liquid level is H, and the depth from the bottom of the thickener to the liquid level is also the total depth of the thickener; from concentration data CdAnd depth data hdAnd fitting the parameter b of the formula (8) by using a nonlinear fitting method1,b2,b3Wherein, in the formula (8), C (h) is represented by concentration data CdAs parameter identification data, h is represented by depth data hdAs parameter identification data;
(c) calculating the height of a mud layer of the thickener:
and (5) rewriting the formula (8) to obtain a mud layer height formula of the thickener, as shown in the formula (9):
by identifying parameter b in ② (b)1,b2,b3And a formula (9), when the concentration value of the corresponding height in the thickener is given manually, the positions of different concentrations in the thickener are obtained, namely the height of the mud layer of the thickener is obtained;
③ internal ore size model of thickener:
the internal ore quantity soft measurement model has the following calculation formula:
wherein，S(h)＝πr2(h) R (h) is the relation between the depth h and the radius of the thickener at the depth h, and is obtained according to the size of the thickener; h is the total height of the thickener; rho0C (h) is the ore pulp concentration of depth h, the height h of a mud layer of the thickener is obtained in step ②, and the ore pulp concentration C (h) of corresponding depth is obtained according to the formula (8);
and 4, step 4: calculating the underflow concentration, the height of a mud layer and the internal ore amount of the ore pulp thickener to be detected:
(a) calculating the underflow concentration real-time value of the thickener:
detecting real-time pressure P of ore pulp to be detected through pressure sensorS1,PS2…,PSNCalculating the underflow concentration real-time value of the thickener according to the formulas (4), (5), (6) and (7);
(b) identifying the parameters of the mud layer height model and calculating the mud layer height:
from real-time pressure data PS1,PS2…,PSNAnd (4), (5) and (6) calculating the average concentration between the two pressure sensors, identifying the real-time model parameters of the height of the mud layer according to the step ② (b), manually giving the concentration value of the corresponding height in the thickener, and calculating the height of the mud layer of the thickener according to the formula (9);
(c) calculating the internal ore amount:
calculating the pulp concentration C (h) according to the height value of the thickener mud layer in the step 4(b) and a formula (8), wherein a function parameter b in the formula (8)1,b2,b3And (c) substituting the calculated ore pulp concentration C (h) into a formula (10) by using the mud layer height real-time model parameters identified in the step 4(b) to obtain internal ore volume data.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110119671A (en) * | 2019-03-26 | 2019-08-13 | 中国海洋大学 | Underwater cognitive method based on artificial side line visual image |
| CN110276128A (en) * | 2019-06-21 | 2019-09-24 | 东北大学 | A kind of thickener underflow concentration prediction method based on DAJYPLS algorithm |
| CN112945344A (en) * | 2021-03-03 | 2021-06-11 | 北矿机电科技有限责任公司 | Paste thickener material layer position online detection method and device |
| CN112985506A (en) * | 2021-03-05 | 2021-06-18 | 北京科技大学 | Method for mutual calculation of mud layer height and mud layer pressure of deep cone thickener |
| CN113281099A (en) * | 2021-06-02 | 2021-08-20 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | Rotation type sampling device suitable for concentrated pond |
| CN113295838A (en) * | 2021-06-02 | 2021-08-24 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | Rotary-cut drainage type concentration detection assembly of concentration tank based on interference rectification and detection device with rotary-cut drainage type concentration detection assembly |
| CN113599863A (en) * | 2021-08-13 | 2021-11-05 | 山东科技大学 | Early warning type anti-blocking method for column type rake-free paste thickener |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060122071A1 (en) * | 2004-12-08 | 2006-06-08 | Hallbiurton Energy Services, Inc. | Oilwell sealant compositions comprising alkali swellable latex |
| CN101251396A (en) * | 2008-04-02 | 2008-08-27 | 罗放明 | Energy-saving grinder swirler closed-loop system and control method |
| CN102527098A (en) * | 2010-12-29 | 2012-07-04 | 中国瑞林工程技术有限公司 | Self-growth inoculating crystal circulating and precipitating system and processing method |
| US20120211421A1 (en) * | 2010-05-14 | 2012-08-23 | Kyle Self | Systems and methods for processing co2 |
| WO2012110284A2 (en) * | 2011-01-26 | 2012-08-23 | Abb Research Ltd | Froth flotation control |
| KR20130036686A (en) * | 2011-10-04 | 2013-04-12 | 금오공과대학교 산학협력단 | Gas injection type automated sample concentration |
| CN107144304A (en) * | 2017-06-05 | 2017-09-08 | 东北大学 | Real-time pressure and granule density measurement apparatus and method in iron ore suspension roaster |
| CN107796476A (en) * | 2017-11-13 | 2018-03-13 | 山东科技大学 | It is a kind of to be used for the device and method of material position and measurement of concetration in concentrator |
-
2018
- 2018-06-29 CN CN201810693030.3A patent/CN109061101B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060122071A1 (en) * | 2004-12-08 | 2006-06-08 | Hallbiurton Energy Services, Inc. | Oilwell sealant compositions comprising alkali swellable latex |
| CN101251396A (en) * | 2008-04-02 | 2008-08-27 | 罗放明 | Energy-saving grinder swirler closed-loop system and control method |
| US20120211421A1 (en) * | 2010-05-14 | 2012-08-23 | Kyle Self | Systems and methods for processing co2 |
| CN102527098A (en) * | 2010-12-29 | 2012-07-04 | 中国瑞林工程技术有限公司 | Self-growth inoculating crystal circulating and precipitating system and processing method |
| WO2012110284A2 (en) * | 2011-01-26 | 2012-08-23 | Abb Research Ltd | Froth flotation control |
| KR20130036686A (en) * | 2011-10-04 | 2013-04-12 | 금오공과대학교 산학협력단 | Gas injection type automated sample concentration |
| CN107144304A (en) * | 2017-06-05 | 2017-09-08 | 东北大学 | Real-time pressure and granule density measurement apparatus and method in iron ore suspension roaster |
| CN107796476A (en) * | 2017-11-13 | 2018-03-13 | 山东科技大学 | It is a kind of to be used for the device and method of material position and measurement of concetration in concentrator |
Non-Patent Citations (1)
| Title |
|---|
| 王旭等: "浓缩生产过程优化控制系统的研究与应用", 《有色金属（选矿部分）》 * |
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| CN110276128A (en) * | 2019-06-21 | 2019-09-24 | 东北大学 | A kind of thickener underflow concentration prediction method based on DAJYPLS algorithm |
| CN110276128B (en) * | 2019-06-21 | 2023-04-07 | 东北大学 | Underflow concentration prediction method of thickener based on DAJYPLS algorithm |
| CN112945344A (en) * | 2021-03-03 | 2021-06-11 | 北矿机电科技有限责任公司 | Paste thickener material layer position online detection method and device |
| CN112985506A (en) * | 2021-03-05 | 2021-06-18 | 北京科技大学 | Method for mutual calculation of mud layer height and mud layer pressure of deep cone thickener |
| CN112985506B (en) * | 2021-03-05 | 2023-03-17 | 北京科技大学 | Method for mutual calculation of mud layer height and mud layer pressure of deep cone thickener |
| CN113281099A (en) * | 2021-06-02 | 2021-08-20 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | Rotation type sampling device suitable for concentrated pond |
| CN113295838A (en) * | 2021-06-02 | 2021-08-24 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | Rotary-cut drainage type concentration detection assembly of concentration tank based on interference rectification and detection device with rotary-cut drainage type concentration detection assembly |
| CN113295838B (en) * | 2021-06-02 | 2023-03-21 | 安徽理工大学环境友好材料与职业健康研究院(芜湖) | Rotary-cut drainage type concentration detection assembly of concentration tank based on interference rectification and detection device with rotary-cut drainage type concentration detection assembly |
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| CN113599863B (en) * | 2021-08-13 | 2022-07-12 | 山东科技大学 | Early warning type anti-blocking method for column type rake-free paste thickener |
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