CN106546697B - A kind of on-line prediction method of bauxite flotation process mash acid alkalinity - Google Patents
A kind of on-line prediction method of bauxite flotation process mash acid alkalinity Download PDFInfo
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Abstract
A kind of bauxite flotation process mash acid alkalinity on-line prediction method, existing for bauxite flotation mash acid alkalinity regulator addition point to pH value test point makes pH value control lag compared with large dead time, and the problem that pH value manual detection efficiency is low, the present invention initially set up ore alkali consumption regression model caused by ore is reacted with alkali；It is hydrolyzed in water further according to the alkali not reacted with ore, and influence of the alkaline recirculated water to hydrolysising balance, establishes pH value mechanism prediction model；Error compensation model is established according to the error time sequence that pH value measured value and mechanism model predicted value are constituted；Error compensation direction is modified based on Expert Rules according to operating condition variation, mechanism model is compensated using revised offset to obtain mash acid alkalinity predicted value.The present invention is used for the prediction of actual production process mash acid alkalinity, and root-mean-square error 0.0935, maximum relative error 2.83%, 90% test sample relative error is within ± 2%.
Description
Technical field
The present invention relates to a kind of on-line prediction methods of bauxite flotation process mash acid alkalinity.
Background technique
Liquor of Ore Dressing Bayer process alumina producing enables a large amount of low-grade bauxite in China for visiing by ore concentration of bauxite
The production of ear method, is greatly saved production energy consumption, reduces discharge.The target of ore concentration of bauxite is in the premise for guaranteeing concentrate grade
Under, the rate of recovery of aluminium is improved as far as possible, and the rate of recovery directly determines the utilization rate of ore.
Ore concentration of bauxite uses foam flotation method, by adding flotation medicine in the ore pulp that the mineral grain ground is constituted
Agent adjusts the surface nature of mineral grain, and air is passed through in ore pulp, forms bubble, valuable mineral particle is made to be attached to bubble
Surface forms froth bed with bubble floating, recycles foam enrichment valuable mineral, and gangue mineral stays and drains in water from slot bottom.Bubble
Foam floatation process is related to the physical-chemical reaction of a series of complex, and there are many influence factor, wherein the pH value of flotation pulp (is used
PH value indicates) it is a very crucial variable, mash acid alkalinity directly affects the activity of the composition of ore pulp ion, floating agent
And the floatability of mineral, decide that can floating agent effectively be ionized into required ion, thus any mineral only have
Best flotation effect can be just obtained under suitable acidity and alkalinity environment.But in the actual production process, for grinding aid, pH
It is worth regulator (Na2CO3Solution) it is added in ore before grinding machine, the ability after ore grinding and two-stage classification and two buffer tanks
The test point of pH value is reached, and the detection of pH value is obtained by artificial offline chemical examination, and manually adjusts the additional amount of pH regulator,
This lag is so that the control lag of pH value, reagent consumption be big, fluctuation of operating conditions is frequent, and worker's heavy workload large labor intensity.
Therefore, mash acid alkalinity in real time and accurately predict, be of great significance to the efficiency for improving ore concentration of bauxite process.
Currently, the modeling method based on data such as neural network, support vector machine, the modeling method based on mechanism, and
Mixed method based on data and mechanism is all used for the prediction of process variable, and achieves good effect.Meanwhile though pH value
Amount all critically important in numerous production processes, but during ore concentration of bauxite, pH regulator in addition to occur in water hydrolysis other than,
Some can react with ore and is consumed；Meanwhile the water used in grinding process is largely flotation
Recirculated water, pH value itself are strong basicity, increase the complexity of floatation process pH adjusting.So far, to bauxite flotation process
And some other floatation process, all there is no from pH adjuster additive amount, working condition and pH adjuster and ore and
The research that the reaction angle of water predicts pH value.PH value prediction based on foam characteristics is inherently the hard measurement of pH value, nothing
Method is for solving pH value control lag issues caused by stopping during grind grading because of ore pulp.And the control of floatation process pH
It is still completely dependent on artificial experience, without effective On-Line Control Method.
It is that pH value control is solved based on PREDICTIVE CONTROL for this purpose, how to be predicted according to real-time working condition mash acid alkalinity
The basis of lag issues suffers from economic and technical index, the mitigation labor intensity of workers of raising floatation process particularly significant
Meaning.
Summary of the invention
The object of the present invention is to provide a kind of on-line prediction methods of bauxite flotation process mash acid alkalinity.
The principle of the present invention is：In floatation process determine mash acid alkalinity process mainly include the hydrolysis of alkali in water and
Mineral are reacted with alkali.It is primarily based on experiment and industrial production data and ore and pH value adjustment is established using multilinear fitting method
Agent Na2CO3The regression model of ore alkali consumption caused by alkali reacts：
O=b0+b1X1+b2X2+b3c+b4pHw (1)
In formula, o (g ton mine) indicates that alkali reacts the alkali number being consumed, X with 1 ton of mineral1For aluminum oxide in raw ore
Percentage composition, X2For the percentage composition of silica in raw ore, c (g ton mine) is the additional amount of sodium carbonate in 1 ton of mineral,
pHwFor the pH value of recirculated water, b0,...,b4For regression parameter.
Generating hydrolysis in water further according to the alkali not reacted with ore makes ore pulp in alkalinity, meanwhile, consider alkaline recirculated water
Addition influence the hydrolysis of alkali, write out the equilibrium equation of hydroxide ion according to hydrolysis mechanism, establish the mechanism of pH value
Prediction model.
PH adjuster (Na in floatation process2CO3Solution) mass concentration be denoted as w (g/L), flow is denoted as L (L/min)；
Discharge quantity flow is denoted as F (ton/hour)；The flow of recirculated water is denoted as Q between pH adjuster addition point and pH value test point1
(L/min), pH value pHwIt indicates, the flow of new water is denoted as Q2(L/min), then in recirculated water hydroxide ion concentration (mol/
L) it is：
It is indicated in the hydroxide ion concentration of pH value test point with x (mol/L), in water according to the alkali not reacted with ore
One-stage hydrolysis is generated, is had according to hydrolysising balance：
Solution formula (3)：
In formula, k1For Na2CO3The one-stage hydrolysis equilibrium constant, value be 1.8 × 10-4, c1For the alkali not reacted with mineral
It is dissolved in the water of all additions alkali concentration (mol/L) of equal value later, calculation method is：
In formula, 106 be the molal weight (g/mol) of sodium carbonate, and 60 for being scaled g/h for unit g/min.
According to hydroxide ion concentration total in solution, can acquire mash acid alkalinity mechanism model prediction value expression is：
pr=14+lg (x+c2) (6)
In formula, prFor mechanism model predicted value.
The history error time sequence foundation constituted according to mash acid alkalinity measured value with mechanism model predicted value is based on
The Error Compensated Prediction model of autoregressive moving average obtains the error compensation value of subsequent time.
The actual measurement sample value of bauxite flotation mash acid alkalinity is denoted as rt(t=1,2 ..., n), the mechanism mould at corresponding moment
Type predicted value is prt(t=1,2 ..., n), the two subtracts each other to obtain error et=rt-prt, remember that its error time sequence is { e1,
e2,...,et,...,en}；According to error time sequence { e1,e2,...,et,...,en, it establishes and is based on autoregressive moving average
Error Compensated Prediction model：
In formula, ε is the error term of model,And θj(j=1,2 ..., q) it is undetermined coefficient.Using
Unit root test method carries out stationarity identification to the time series of modeling, is then stationary sequence there is no unit root, there are lists
Position root illustrates the sequence non-stationary, and non-stationary series are first carried out with difference processing and is used further to model；Based on auto-correlation function (ACF)
Model is carried out to determine rank with the Method of determining the optimum of partial autocorrelation function (PACF), according to the hangover of ACF and PACF and truncation come
It determines model order, that is, determines the value of p and q, the sequence when the ACF of time series and PACF is respectively provided with p rank and q rank hangover property
It is classified as ARMA (p, q) sequence；According to history error sequence, parameter is recognized to obtain using least square method And θj(j=1,2 ..., q).
When ore properties are more stable, the variation of process operating condition is the main cause for causing pH value to change, meanwhile, because ARMA error is pre-
It is only related with the error amount at preceding several moment to survey model, cannot reflect the unexpected fluctuation of operating condition, makes the compensation of error time sequence can
Can there is a problem of with should actually compensate it is contrary, and experienced worker working condition variation it is more apparent when total energy standard
Really judge the change direction of pH value.Therefore, when operating condition changes greatly, Expert Rules are established according to operating condition variation and Heuristics
Error in judgement compensation direction, Expert Rules compensation direction withIt is used when direction is consistentDirectly mechanism model is compensated, no
It is subject to Expert Rules compensation direction when consistent, offset usesAbsolute value, to realize the prediction of mash acid alkalinity.
Rule of thumb, Na2CO3Flow increment, discharge quantity increment, inflow increment, the fluctuation of pH in Circulating Water increment is to mine
What material consumption alkali number generated is affected, therefore according to the situation of change of this tittle, establishes Expert Rules to determine error compensation side
To variable quantity of the incremental representation current sample time variable relative to previous hour sampling instant, with Δ βtTon indicates t moment
Relative to the discharge quantity increment of previous sampling instant, Δ ptIndicate that t moment increases relative to the pH in Circulating Water of previous sampling instant
Amount, Δ mtG ton mine indicates the mineral facies per ton of t moment for the Na in the mineral per ton of previous sampling instant2CO3Additional amount
Increment, Δ ωtTon indicates recirculated water and new water total increment of the t moment relative to previous sampling instant, ktIndicate the expert of t moment
Rule output, 1 and 0, which respectively corresponds pH value, increases and subtracts, and obtaining error compensation rule is：
IF Δβt>=3.4, THEN kt=1；
IF Δβt<=-4.7, THEN kt=0；
IF -4.7<Δβt<3.4AND Δpt<=-0.21, THEN kt=1；
IF -4.7<Δβt<3.4AND Δpt>=0.23, THEN kt=0；
IF -4.7<Δβt<3.4AND -0.21<Δpt<0.23AND Δmt<=-100, THEN kt=1；
IF -4.7<Δβt<3.4AND -0.21<Δpt<0.23AND Δmt>=100, THEN kt=0；
IF -4.7<Δβt<3.4AND 0.21<Δpt<0.23AND -100<Δmt<100AND
Δωt>=12,
THEN kt=1；
IF -4.7<Δβt<3.4AND 0.21<Δpt<0.23AND -100<Δmt<100AND
Δωt<=-6, THEN kt=0；
ELSE ktWithDirection is consistent.
Mechanism model predicted value is compensated with revised error prediction value to obtain the predicted value of mash acid alkalinity, is counted
Calculating formula is：
When being predicted using this programme mash acid alkalinity, real-time monitoring bauxite Milling classification process adds new water, circulation
Water, alkali number and mine-supplying quantity information analyze tcrude ore composition information in real time, ore alkali consumption are acquired according to formula (1), according to formula
(8) mash acid alkalinity mechanism model predicted value is acquired, calculates error compensation value according to formula (7), and determine and miss according to Expert Rules
Poor compensation direction obtains the final predicted value of model by formula (8), realizes the on-line prediction of mash acid alkalinity.Beneficial effect of the invention
Fruit is：Alkali caused by the present invention reacts ore with alkali is consumed by designing the simple experiment progress quantification of one kind and modeling,
And then utilize the Error Compensated Prediction model based on autoregressive moving average and the error compensation adjustment in direction based on Expert Rules
Method carries out online compensation to mechanism model, predicts the pH value of ore pulp solution, adapts to the variation of working condition, can be effectively
It is 0.0935 using the root-mean-square error that this method is predicted, maximum relative error is applied to actual production process
2.83%.
Detailed description of the invention
Fig. 1 is the prediction model structure of mash acid alkalinity；
Fig. 2 is prediction result of the modelling by mechanism to mash acid alkalinity；
Fig. 3 is the Error Compensated Prediction result based on autoregressive moving-average model and Expert Rules；
Fig. 4 is the final prediction result of mash acid alkalinity.
The present invention is described in further detail with reference to the accompanying drawings and detailed description.
Specific embodiment
As shown in Figure 1, the present invention using based on industrial production data ore alkali consumption regression model, be based on flotation solution
The mechanism model of the principles of chemistry and Error Compensated Prediction model realization based on autoregressive moving average are to flotation pulp soda acid
The prediction of degree.It does case using 285 groups of continuous production data of certain ore concentration of bauxite factory herein and is analyzed and (do not include improper work
Data under condition), wherein preceding 215 groups of data are used for parameter identification, rear 70 groups of data are used for compliance test result.
1. ore alkali consumption regression model
Ore is reacted with alkali can consume a part of alkali, to prevent the alkali being added in ore pulp from being completely used for adjusting ore pulp
PH value；Meanwhile it is because more comprising diaspore, chlorite, iron ore, titanium ore, illite etc. in diaspore ore
Kind mineral, ingredient is sufficiently complex, and the effect of ore and alkali is also sufficiently complex, design and grind grading actual production process condition
(including slurry fineness, concentration and temperature) experiment close as far as possible determines that ore reacts the alkali number of consumption with alkali.Experimentation is：
Acquisition actual production is first crushed with ore, is then ground to (- 200 mesh identical as the slurry fineness of flotation is entered in actual production
Content is 85% or more), a certain amount of ore (500g) is weighed, in ore plus water forms ore pulp (concentration 45%), adds simultaneously
Enter different alkali numbers (2200g/t mine, 2500g/t mine, 2800g/t mine), and keeps solution temperature and actual production slurry temperature
Close to (38 DEG C), every 1 pH value of detection in 5 minutes, until 1 hour after alkali addition, note pH value is Pn(n=1,2 ...,
12)。
It is 20 minutes according to actual production lag time, alkali number needed for pH value when calculating according to the following formula reaction 20 minutes
o2(g ton mine)：
In formula, k1For the one-stage hydrolysis equilibrium constant of alkali, value is 1.8 × 10-4, V is calculated to obtain according to pulp densityWaterFor
0.61 liter.
Remember that the alkali number being initially added is o1(g ton mine), then ore reacts the alkali number consumed with alkali and is：
oh=o1-o2 (2)
Caused by being reacted according to ore of the above-mentioned experiment acquisition under corresponding with actual production grind grading condition with alkali
Quantity of alkali consumption data.
Acquisition actual production Jia Shui corresponding with experiment ore plus alkali and composition of ores data, based on these experiments and work
The fitting of industry creation data acquires ore alkali consumption regression model.
The chemical component of ore pulp is detected, and compares discovery with raw ore chemical component, bauxite it is main at
It is some before and after grind grading to generate variation at branch in point, and have some components unchangeds, wherein aluminium oxide, silica and water meeting
It is reacted with alkali, has the potassium oxide of part and sodium oxide molybdena that can be dissolved in water, but the content of potassium oxide and sodium oxide molybdena is very small, so can
Not consider, separately it is believed that di-iron trioxide, titanium oxide with magnesia is not soluble in water does not also react with alkali, calcium oxide is dissolved in aquatic
At calcium hydroxide precipitation.Meanwhile caustic dosage is more, the alkali number that ore consumes is also more, and the addition of the recirculated water in alkalinity
It is equivalent to the addition of more polybase；Therefore, it in the case where not considering other chemical reactions, is obtained according to experiment and actual production data
Regression equation to ore alkali consumption is：
O=25.917+0.0947X1-0.107X2+0.36c-1.91pHw(R2=0.867) (3)
O (g ton mine) indicates that alkali reacts the alkali number being consumed, X with 1 ton of mineral in formula1For aluminum oxide in raw ore
Percentage composition, X2For the percentage composition of silica in raw ore, c (g ton mine) is the additional amount of sodium carbonate in 1 ton of mineral, pHw
For the pH value of recirculated water.
2. mash acid alkalinity mechanism prediction model
Alkali is added after ore pulp, and a part is chemically reacted with certain ingredients in bauxite, complete according to another part
Portion generates one-stage hydrolysis in water and is calculated.And since the addition of recirculated water makes ore pulp in alkalinity, the hydrolysis of alkali is influenced, thus
Hydrolysising balance establishes the mechanism prediction model of pH value.
Remember pH adjuster (Na in floatation process2CO3Solution) mass concentration be w (g/L), flow be L (L/min)；It is short
The average discharge quantity flow of (20 minutes) is F (ton/hour) in time；It is followed between pH adjuster addition point and pH value test point
The flow of ring water is Q1(L/min), pH value pHwIt indicates, the flow of new water is Q2(L/min), hydroxide ion in recirculated water
Concentration (mol/L) be：
One-stage hydrolysis is all generated in water according to the alkali not reacted with ore, is remembered dense in pH value test point hydroxide ion
Degree is x (mol/L), is had according to hydrolysising balance：
Solution formula (5) can obtain：
In formula, k1For the one-stage hydrolysis equilibrium constant of alkali, value is 1.8 × 10-4,c1For the alkali soluble do not reacted with mineral in
Equivalent concentration (mol/L) after the water of all additions, calculation method are：
In formula, 106 be the molal weight (g/mol) of sodium carbonate, and 60 for being scaled g/h. for unit g/min
According to hydroxide ion concentration total in solution, can acquire mash acid alkalinity mechanism model prediction value expression is：
pr=14+lg (x+c2) (8)
In formula, prFor mechanism model predicted value.
Mash acid alkalinity mechanism model prediction effect is as shown in Figure 2, wherein root-mean-square error 0.1488, it is maximum opposite
Error is 3.28%.
3. the error time sequence prediction based on autoregressive moving-average model compensates
Mash acid alkalinity measured value has certain correlation with the error time sequence that mechanism model predicted value is constituted,
Error time sequence is predicted using autoregressive moving-average model thus.Using the error time sequence of preceding 215 groups of data
Column are modeled, and wherein time series corresponding to the measured value of mash acid alkalinity is rt(t=1,2 ..., n), each time point institute
Corresponding mechanism model predicted value isThe two subtracts each other to obtain corresponding error
Remember that its error time sequence is { e1,e2,...,et,...,en}。
According to error time sequence { e1,e2,...,et,...,en, establish the error compensation based on autoregressive moving average
Prediction model：
In formula, ε is the error term of model,And θj(j=1,2 ..., q) it is undetermined coefficient.Using
Unit root test method carries out stationary test to error time sequence and obtains that unit root, the time are not present in error time sequence
Sequence meets the stationarity condition of sequence；Rank side is determined using based on auto-correlation function (ACF) and partial autocorrelation function (PACF)
Method carries out model to determine rank, and the auto-correlation function of error time sequence is the hangover of 6 ranks, and partial autocorrelation function is the hangover of 1 rank, therefore from
Regression order is 6, and sliding average order is 1, i.e. p=6, q=1.Parameter is recognized to obtain using least square methodAnd θj(j=1 ..., q), finally obtaining Error Compensated Prediction model is：
4. the error compensation adjustment in direction based on Expert Rules
Mechanism model reflects OH caused by the hydrolysis of alkali and the addition of recirculated water in floatation process-Change the shadow to pH value
It rings.With the proviso that chemistry of Flotation ambient stable.But entire floatation process is extremely complex, alkali a part and the mine being added in ore pulp
Stone reaction, another part generate hydrolysis, and the additional amount of alkali and the discharge quantity of ore directly affect the alkali number for generating hydrolysis, new water and
The additional amount of recirculated water and the OH in recirculated water-Concentration can influence slurry pH.When ore properties are more stable, process work
Condition variation is the main cause for causing pH value to change, meanwhile, because ARMA error prediction model is only related with the error amount at preceding several moment,
The unexpected fluctuation that cannot reflect operating condition asks the compensation of error time sequence there may be contrary with what should actually be compensated
Topic, and the change direction of experienced worker total energy accurate judgement pH value when working condition changes more apparent.Therefore, according to work
Condition variation and Heuristics establish Expert Rules error in judgement compensation direction, Expert Rules compensation direction withWhen direction is consistent
Directly mechanism model is compensated, is subject to Expert Rules compensation direction when inconsistent, offset usesAbsolute value, from
And realize the prediction of mash acid alkalinity.
Rule of thumb, Na2CO3The fluctuation of increment, discharge quantity increment, inflow increment, pH in Circulating Water increment consumes mineral
What alkali number generated is affected, therefore according to the situation of change of this tittle, establishes Expert Rules to determine error compensation direction, increases
Amount indicates variable quantity of the current sample time variable relative to previous hour sampling instant, with Δ βtTon indicates that t moment is opposite
In the discharge quantity increment of previous sampling instant, Δ ptIndicate pH in Circulating Water increment of the t moment relative to previous sampling instant, Δ
mtG ton mine indicates the mineral facies per ton of t moment for the Na in the mineral per ton of previous sampling instant2CO3Additional amount increment,
ΔωtTon indicates recirculated water and new water total increment of the t moment relative to previous sampling instant, ktIndicate that the Expert Rules of t moment are defeated
Out, it 1 and 0 respectively corresponds pH value increasing and subtracts, obtaining error compensation rule is：
IF Δβt>=3.4, THEN kt=1；
IF Δβt<=-4.7, THEN kt=0；
IF -4.7<Δβt<3.4AND Δpt<=-0.21, THEN kt=1；
IF -4.7<Δβt<3.4AND Δpt>=0.23, THEN kt=0；
IF -4.7<Δβt<3.4AND -0.21<Δpt<0.23AND Δmt<=-100, THEN kt=1；
IF -4.7<Δβt<3.4AND -0.21<Δpt<0.23AND Δmt>=100, THEN kt=0；
IF -4.7<Δβt<3.4AND 0.21<Δpt<0.23AND -100<Δmt<100AND
Δωt>=12,
THEN kt=1；
IF -4.7<Δβt<3.4AND 0.21<Δpt<0.23AND -100<Δmt<100AND
Δωt<=-6, THEN kt=0；
ELSE ktWithDirection is consistent.
It is with the predicted value that revised error prediction value compensates to obtain mash acid alkalinity to mechanism model：
When predicting using this programme mash acid alkalinity, ore alkali consumption is acquired according to formula (3), further according to anti-not with ore
The alkali answered hydrolyzes in water, mash acid alkalinity mechanism model predicted value is acquired by formula (8), according to the actual measurement of mash acid alkalinity
The history error time sequence that value and mechanism model value are constituted establishes Error Compensated Prediction model and obtains error compensation value such as formula
(10) shown in, error compensation direction is corrected based on Expert Rules, the two direction directly compensates mechanism model when consistent, no
It is subject to Expert Rules compensation direction when consistent, i.e., mechanism model predicted value is compensated to obtain mash acid alkalinity by formula (11)
Predicted value.
It is as shown in Figure 4 to factory's continuous production 3 days mash acid alkalinity prediction results.Wherein, root-mean-square error is
0.0935,90% test sample relative error shows that prediction model has degree of precision, can satisfy reality in ± 2%
Production requirement.On-line checking is provided for production as a result, improving the real-time of detection and alleviating the labor intensity of worker.
Claims (1)
1. a kind of on-line prediction method of bauxite flotation process mash acid alkalinity, it is characterised in that first establish ore and pH value tune
Whole dose of Na2CO3Ore alkali consumption regression model caused by reaction：
O=b0+b1X1+b2X2+b3c+b4pHw (1)
In formula, o g tons of mine indicates that alkali reacts the alkali number being consumed, X with 1 ton of mineral1For the percentage of aluminum oxide in raw ore
Content, X2For the percentage composition of silica in raw ore, c g tons of mine is the additional amount of alkali in 1 ton of mineral, pHwFor recirculated water
PH value, b0,...,b4For regression parameter；
It generates ionization hydrolysis in water further according to the alkali not reacted with ore, and considers that the addition of alkaline recirculated water influences ore pulp acid
Basicity establishes pH value mechanism prediction model, pH adjuster Na in floatation process according to hydrolysis2CO3The quality of solution is dense
Degree is denoted as wg/L, and flow is denoted as LL/min；Discharge quantity flow is denoted as F ton/hours；PH adjuster addition point and pH value detect
The flow of recirculated water is denoted as Q between point1L/min, pH value pHwIt indicates, the flow of new water is denoted as Q2L/min, hydrogen in recirculated water
The concentration mol/L of oxygen radical ion is：
It is indicated in the hydroxide ion concentration of pH value test point with xmol/L, generates one in water according to the alkali not reacted with ore
Grade hydrolysis, has according to hydrolysising balance：
Solution formula (3)：
In formula, k1For Na2CO3The one-stage hydrolysis equilibrium constant, value be 1.8 × 10-4, c1For the alkali soluble do not reacted with mineral in
Alkali concentration mol/L of equal value, calculation method are after the water of all additions：
In formula, 106 be the molal weight g/mol of sodium carbonate, and 60 for being scaled g/h for unit g/min；
According to hydroxide ion concentration total in ore pulp solution, acquiring mash acid alkalinity mechanism model prediction value expression is：
pr=14+lg (x+c2) (6)
In formula, prFor mechanism model predicted value；
It is established according to the error time sequence that mash acid alkalinity measured value and mechanism model predicted value are constituted sliding based on autoregression
Move average error time sequence compensation model；
The actual measurement sample value for remembering bauxite flotation mash acid alkalinity is rt, t=1,2 ..., n, each time point corresponding mechanism model
Predicted value isT=1,2 ..., n, the two subtract each other to obtain corresponding error beAccording to error time sequence
{e1,e2,...,et,...,en, establish autoregressive moving average error compensation model：
In formula, ε is the error term of model,And θj, j=1,2 ..., q are undetermined coefficient, using unit root
Method of inspection carries out stationarity identification to time series, using the Method of determining the optimum based on auto-correlation function and partial autocorrelation function to mould
Type carries out determining rank, that is, determines that the value of p and q is recognized to obtain using least square method according to history error sequence to parameterAnd θj, j=1,2 ..., q；
Expert Rules error in judgement compensation direction is established according to operating condition variation and Heuristics, with incremental representation current sample time
Variable quantity of certain variable relative to previous hour sampling instant, with Δ βtTon indicates the blanking of the relatively previous sampling instant of t moment
Measure increment, Δ ptIndicate the pH in Circulating Water increment of the relatively previous sampling instant of t moment, Δ mtG ton mine indicates the every of t moment
Ton mineral facies are to the Na in the mineral per ton of previous sampling instant2CO3Additional amount increment, Δ ωtTon indicates that t moment is relatively previous
The recirculated water of sampling instant and new water total increment, ktIndicate t moment Expert Rules output, 1 and 0 respectively correspond pH value increase and
Subtract, obtaining error compensation rule is：
If Δ βt>=3.4, then kt=1；
If Δ βt<=-4.7, then kt=0；
If -4.7<Δβt<3.4 and Δ pt<=-0.21, then kt=1；
If -4.7<Δβt<3.4 and Δ pt>=0.23, then kt=0；
If -4.7<Δβt<3.4 and -0.21<Δpt<0.23 and Δ mt<=-100, then kt=1；
If -4.7<Δβt<3.4 and -0.21<Δpt<0.23 and Δ mt>=100, then kt=0；
If -4.7<Δβt<3.4 and 0.21<Δpt<0.23 and -100<Δmt<100 and Δ ωt>=12,
Then kt=1；
If -4.7<Δβt<3.4 and 0.21<Δpt<0.23 and -100<Δmt<100 and Δ ωt<=-6, then kt=0；
Otherwise ktWithDirection is consistent；
Positive compensation or negative compensation according to offset rule determination, Expert Rules compensation direction withIt is used when direction is consistentDirectly
It connects and mechanism model is compensated, be then subject to Expert Rules compensation direction when inconsistent, offset usesAbsolute value, use
Revised error prediction value compensates mechanism model predicted value to obtain the predicted value of mash acid alkalinity, obtains final predicted value
For：
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201610968376.0A CN106546697B (en) | 2016-10-28 | 2016-10-28 | A kind of on-line prediction method of bauxite flotation process mash acid alkalinity |
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