CN105512804A - Emulsion flow setting method taking cost integrated control as target in cold continuous rolling process - Google Patents

Abstract

The invention discloses an emulsion flow setting method taking cost integrated control as a target in a cold continuous rolling process. The emulsion flow setting method mainly comprises the steps of: 1, collecting field parameters; 2, collecting friction characteristic parameters of a unit; 3, collecting cost parameters of the unit; 4, defining relevant parameters; 5, setting an initial value and an initial optimization step size; 6, calculating outlet and inlet speeds, a reduction ratio, pass reduction and an equivalent tension influence coefficient of an ith rack; 7, calculating a dynamic viscosity coefficient, lubricant film thickness, a friction coefficient, a rolling force, a working roll flattening radius, an external friction force influence coefficient, a forward slip value, a rolling torque, a slipping factor, a slip damage index and a rolling power of the ith rack; 8, calculating sum of power consumption of all racks in the unit; 9, constructing a unit production cost control target functional expression; 10, and outputting an optimal emulsion flow. The emulsion flow setting method sets a reasonable target value for emulsion flow control, effectively reduces enterprise cost, and increases enterprise revenue.

Description

The emulsion flow set method that cold continuous rolling process is target with cost Comprehensive Control

Technical field

The invention belongs to metallurgical cold rolling field, particularly a kind of emulsion flow set method of applicable cold continuous rolling process.

Background technology

In recent years, due to the great demand of the industries such as household electrical appliance, automobile, electronics, space flight, domestic and international cold rolled sheet manufacture is made to obtain fast development.In the past, in cold rolled sheet production run, the on-the-spot focus paid close attention to mainly concentrates on the control of the quality index such as plate shape, thickness of slab, surface imperfection.But along with the fierceness day by day of steel industry competition, the downslide of the overall rate of profit of steel industry, the cost control problem in cold rolled sheet production run is put in the status of equal importance with quality control.Because for iron and steel enterprise, under the condition of market economy, no matter how high product quality is, if its production cost is close to even having exceeded product price, ton steel benefit is close to zero or be negative, this product is also do not have vital, can not long-term production go down.The power consumption of ton steel is the sizable part of unit production cost accounting, simultaneously, in cold continuous rolling process, emulsion belongs to consumables, and the change of emulsion flow also just means the change of emulsion integrated cost (mainly comprising cost and cost for wastewater treatment two parts of emulsion itself).The control of current emulsion flow and calculate main foundation and qualifications is rolling temperature, heat slid wound and skidding, and for comprising rolling temperature, the composite factor of heat slid wound and skidding controls to rarely have document, will cause like this meeting under the conditions such as rolling temperature, heat slid wound and skidding, the flow control scope of emulsion is accurate not enough, cause the waste of emulsion, increase production cost.Therefore, the optimization of emulsion flow, while the above-mentioned factor of consideration, also must be carried out under the prerequisite considering emulsion integrated cost, can not occur the situation that the income that reduction electric power consumption per ton steel brings increases lower than emulsion integrated cost.

Summary of the invention

For tandem mills scene occur in order to reduce electric power consumption per ton steel, cause occurring, because electric power consumption per ton steel reduces the problem that the income brought increases lower than emulsion integrated cost, the invention provides a kind of emulsion flow set method that cold continuous rolling process is target with cost Comprehensive Control.The present invention is mainly by rational mathematical modeling, and the cost on simulation cold continuous rolling production line produces, and from the angle of cost control, sets the rational desired value of emulsion flow control.

The present invention includes the following step performed by computing machine:

A) collect on-site parameters, comprising: unit i-th frame gateway thickness h _i, h _i-1, unit i-th gantry motor efficiency eta _i, unit i-th breast roller radius R _i, unit strip width B, unit strip density ρ, Young modulus E, Poisson ratio v, unit i-th frame average deformation drag K _mi, unit i-th frame emulsion maximum flow Q _imax, unit emulsion total flow maximal value Q _max, tension force T before and after unit i-th frame band steel _i, T _i-1, rolling milimeter number L after unit i-th frame work roll changing _i, the maximum draught pressure P of unit i-th frame _imax, the maximum slip factor ψ of unit i-th frame _imax, the maximum slip injury index of unit i-th frame the maximum rolling power W of unit i-th frame _imax, unit Final Stand Rolling speed V _n, wherein parameter i is machine set frame numbering, and n is the total frame number of unit;

B) collect unit friction coefficient, comprising: the i-th frame fluid friction influence coefficient a _i, the i-th frame dry friction influence coefficient b _i, the i-th frame friction factor damped expoential B _{ξ i}, the i-th frame concentration of emulsion used influence coefficient k _ci, emulsion viscosity compressibility coefficient θ, the i-th frame working roll and belt steel surface Longitudinal Surface Roughness carry emulsion strength factor k secretly _rgi, the i-th frame impression rate K _rsi, the i-th frame working roll initial roughness Ra _r0i, the i-th frame working roll roughness attenuation coefficient B _li, kinetic viscosity parameter a under emulsion atmospheric pressure ₁, b ₁, the i-th breast roller linear resonance surface velocity V _ri, the i-th frame emulsion contacts with the strip face A _i, the i-th frame band steel nip angle α _i, emulsion specific heat capacity c _m, emulsion density p _breast, emulsion initial temperature t ₀, the temperature t after the i-th frame emulsion temperature rise _i, the i-th frame coefficient of heat transfer and emulsion discharge relation linear coefficient k _3i, the i-th frame coefficient of heat transfer and emulsion discharge relation index c _3i, emulsion Flux Loss coefficient k _4i;

C) gathering machine group cost parameter, comprising: the cost ξ of every kilowatt-hour of power consumption _d, milling train expends the integrated cost ξ of often liter of emulsion _r;

D) X={Q is made ₁, Q ₂, Q ₃, Q ₄, Q ₅be unit n=5 frame emulsion flow separately, define flow iterative process parameter j and initialization j=0;

E) initial value X ₀={ Q ₁₀, Q ₂₀, Q ₃₀, Q ₄₀, Q ₅₀, initial optimization step delta X ₀={ Δ Q ₁₀, Δ Q ₂₀, Δ Q ₃₀, Δ Q ₄₀, Δ Q ₅₀;

F) X=X is calculated ₀+ j Δ X ₀;

G) judge $\left\{\begin{array}{c}\underset{i=1}{\overset{n}{\Σ}}\left(Q_i\right)\≤Q_{max}\\ Q_i\≤Q_{imax}\end{array}\right.$ If set up, then proceed to step h); If be false, adjustment X ₀with Δ X, reset j=0, and proceed to step f);

H) i=1 is made;

I) the i-th frame gateway speed is calculated i-th frame reduction ratio i-th frame passage absolute draft amount Δ h _i=h _i-1-h _i, the i-th frame equivalence tension force influence coefficient ξ _i'=0.3T _i+ 0.7T _i-1;

J) the i-th frame coefficient of kinetic viscosity is calculated

K) the i-th frame oil film thickness is calculated

${\mathrm{\ξ}}_i=\frac{h_{i-1}+h_i}{2h_{i-1}}\·k_{ci}\·\frac{3{\mathrm{\θ\η}}_i(V_{ri}+V_{i-1})}{{\mathrm{\α}}_i\[1-e^{-\mathrm{\θ}(K_{mi}-T_{i-1})}\]}-k_{rgi}\·(1+K_{rsi})\·{\mathrm{Ra}}_{r0i}\·e^{-B_{Li}\·L_i};$

L) friction factor of the i-th frame is calculated

M) calculate the i-th frame roll-force, the following step performed by computing machine can be adopted:

M1) initial general rolling force P is defined _i', roll-force control accuracy δ, accurate general rolling force P _i;

M2) P is made _i'=1000 (t), δ=10 ^-10;

M3) elastic compression of rolled piece and the working roll elastic flattening radius of elastic recovery are considered in calculating

${R^{\′}}_i=R_i\[1+\frac{16(1-v^2){P_i}^{\′}}{\mathrm{\π}EB(\sqrt{{\mathrm{\Δh}}_i+\frac{1-v^2}{E}{h}_i(K_{mi}-T_i)}+\sqrt{\frac{1-v^2}{E}{h}_i(K_{mi}-T_i)})}\];$

M4) external friction power influence coefficient is calculated $Q_{G_i}=1.08-1.02r_i+1.79r_i\·{\mathrm{\μ}}_i\sqrt{\frac{{R^{\′}}_i}{h_{i-1}}};$

M5) computational plasticity distorted area roll-force

M6) entrance elastic compression district roll-force is calculated

M7) outlet elastic compression district roll-force is calculated

M8) general rolling force P is calculated _i=P _pi+ P _e1i+ P _e2i;

M9) judge | P _i-P _i' |≤δ, if set up, proceeds to step m10); Be false, then make P _i'=P _i, and proceed to step m3);

M10) general rolling force P is exported _i;

N) the i-th frame working roll elastic flattening radius is calculated

I-th frame external friction power influence coefficient $Q_{G_i}=1.08-1.02r_i+1.79r_i\·{\mathrm{\μ}}_i\sqrt{\frac{{R^{\′}}_i}{h_i}},$

The advancing slip value of i-th frame $f_{si}=(1-\frac{h_i}{2{R_i}^{\′}})\frac{{\mathrm{\Δh}}_i}{4h_i}{\[1-\frac{1}{2{\mathrm{\μ}}_i}\left(\sqrt{\frac{{\mathrm{\Δh}}_i}{{R_i}^{\′}}-\frac{{\mathrm{Bh}}_i{T}_i-{\mathrm{Bh}}_{i-1}{T}_{i-1}}{P_i}}\right)\]}^2,$

I-th frame roll torque $N_i=B\[(k_{mi}-{{\mathrm{\ξ}}_i}^{\′})R_i{\mathrm{\Δh}}_i{Q}_{G_i}+T_{i-1}{R}_i{h}_{i-1}-T_i{R}_i{h}_i\]\×\frac{1}{1000};$

0) slip factor of the i-th frame is calculated and slip injury index

P) the i-th frame rolling power is calculated

Q) judge set up? if set up, then proceed to step r); Be false, then make j=j+1, proceed to step f);

R) i=i+1 is made, judge i≤n? if set up, then proceed to step I); Be false, then proceed to step s);

S) unit all frame power consumptions summation is calculated

T) tectonic unit's volume cost Controlling object function formula

U) do you judge that Powell condition is set up? if set up, then proceed to step v); Be false, adjust X ₀with Δ X, reset j=0, and repeat above-mentioned steps f) to step t), until Powell condition is set up;

V) X={Q that G (X) gets minimum value is exported ₁, Q ₂, Q ₃, Q ₄, Q ₅optimum solution, G (X) is now the minimum specific yield cost of unit.

When unit normally runs, equaling or infinite approach { Q of each frame emulsion flow must be ensured ₁, Q ₂, Q ₃, Q ₄, Q ₅, with this target, unit emulsion flow is optimized, effectively can reduces enterprise cost, for enterprise brings benefit.

The present invention compared with prior art tool has the following advantages:

1, by rational mathematical modeling, the cost on simulation cold continuous rolling production line produces, and from the angle of cost control, sets the rational desired value of emulsion flow control, effectively reduces enterprise cost, for enterprise brings benefit.

2, can prevent because unit emulsion flow set is improper, cause band steel to skid or sliding injury and rolling power and roll-force exceed limit value, the emulsion flow integrated optimization and setting taking cost control as target for cold continuous rolling production line provides foundation.

Accompanying drawing explanation

Fig. 1 is total computing block diagram of the present invention.

Fig. 2 is tube rolling simulation block diagram of the present invention.

Embodiment

Embodiment 1

According to the total computing block diagram of emulsion flow set method that the cold continuous rolling process shown in Fig. 1 is target with cost Comprehensive Control, first, in step (a), collect on-site parameters, comprising: five frame inlet/outlet thickness h _i-1, h _i(mm) { (2.50,1.85), (1.85,1.16), (1.16,0.82), (0.82,0.56), (0.56,0.45) }, five breast roller radius Rs _i(mm) { 265,237,249,266,264}, five gantry motor efficiency eta _i{ 0.85,0.84,0.86,0.85,0.87}, strip density ρ=7850 (kg/m ³), five frame strip width B _i=1020 (mm), Young modulus E=210GPa, Poisson ratio v=0.3, five frame average deformation drag K _mi(Mpa) { 373,475,541,576,612}, five frame maximum emulsion flow Q _imax(L/min) { 4500,4500,4500,4500,4500}, the maximum total flow Q of unit emulsion _max(L/min)=22500, five frame band steel inlet/outlet tension force T _i-1, T _i(Mpa) { (49,160), (160,170), (170,170), (170,180), (180,69) }, rolling milimeter number L after five frame work roll changings _i(Km) 150,220,240,263,263}, five maximum draught pressure P of frame _imax(t) { 1500,1480,1470,1490,1480}, five maximum slip factor ψ of frame _imax{ 0.5,0.45,0.47,0.47,0.49}, five maximum slip injury index of frame five maximum rolling power W of frame _imax(KW) { 2500,3800,3800,3800,3800}, tandem mills end gantry speed V ₅=1520 (m/min), wherein parameter i is tandem mills frame numbering, and n=5 is the total frame number of tandem mills;

Subsequently, in step (b), collect unit and to rub special characterisitic parameter, comprising: the i-th frame fluid friction influence coefficient a _i={ 0.0126,0.0121,0.0122,0.0127,0.0131}, the i-th frame dry friction influence coefficient b _i={ 0.1416,0.1421,0.1430,0.1408,0.1425}, the i-th frame friction factor damped expoential B _{ξ i}={ the-2.4297 ,-2.4287 ,-2.4305 ,-2.4308 ,-2.4312}, i-th frame concentration of emulsion used influence coefficient k _ci={ 1.9 × 10 ^-5, 1.7 × 10 ^-5, 1.7 × 10 ^-5, 1.8 × 10 ^-5, 2.0 × 10 ^-5, emulsion viscosity compressibility coefficient θ=0.05, the i-th frame working roll and belt steel surface Longitudinal Surface Roughness carry emulsion strength factor k secretly _rgi={ 0.09,0.11,0.12,0.14,0.13}, the i-th frame impression rate K _rsi={ 0.029,0.031,0.032,0.034,0.036}, the i-th frame working roll initial roughness Ra _r0i={ 1.25,0.93,0.61,0.51,3.21}, the i-th frame working roll roughness attenuation coefficient B _li={-0.00244 ,-0.00233 ,-0.00232 ,-0.00234 ,-0.00225}, kinetic viscosity parameter a under emulsion atmospheric pressure ₁=51, b ₁=0.012, i-th breast roller linear resonance surface velocity (m/min) V _ri={ 362.13,577.53,816.99,1196.31,1488.74}, the i-th frame emulsion contacts with the strip face (m ²) A _i=1.02, i-th frame band steel nip angle α _i={ 0.050,0.053,0.036,0.031,0.020}, emulsion specific heat capacity c _m=2.0kJ/ (kg DEG C), emulsion density p _breast=0.89kg/L, emulsion initial temperature t ₀=20 DEG C, temperature (DEG C) t after the i-th frame emulsion temperature rise _i={ 52,51,49,50,53}, the i-th frame coefficient of heat transfer and emulsion discharge relation linear coefficient k _3i=={ 0.63,0.61,0.58,0.58,0.55}, the i-th frame coefficient of heat transfer and emulsion discharge relation index c _3i={ 0.648,0.648,0.648,0.648,0.648}, emulsion Flux Loss coefficient k _4i{ 0.7,0.6,0.7,0.7,0.8};

Subsequently, in step (c), collect unit efficiency parameter, comprising: the cost ξ of every kilowatt-hour of power consumption _d=1 yuan/kilowatt hour, milling train expends the integrated cost ξ of often liter of emulsion _r=0.05 yuan/liter;

Subsequently, in step (d), make X={Q ₁, Q ₂, Q ₃, Q ₄, Q ₅be unit 5 frames emulsion flow separately, define flow iterative process parameter j and initialization j=0;

Subsequently, in step (e), initial value X ₀={ 2000,2200,2200,2300,2400}, initial optimization step delta X ₀={ 50,50,50,50,50};

Subsequently, in step (f), calculate X=X ₀+ j Δ X ₀={ 2000,2200,2200,2300,2400};

Subsequently, in step (g), obvious inequality $\left\{\begin{array}{c}11100\≤22500\\ Q_i\≤4500\end{array}\right.$ Set up, proceed to step (h);

Subsequently, in step (h), make i=1;

Subsequently, in step (i), calculate the 1st rack outlet speed V _i=243.24 (m/min), V _i=180.00 (m/min) and reduction ratio r _i=0.26, passage absolute draft amount Δ h _i=0.65 and equivalent tension force influence coefficient ξ _i'=82.3;

Subsequently, in step (j), calculate the 1st frame coefficient of kinetic viscosity η _i=27.5;

Subsequently, in step (k), calculate the 1st frame oil film thickness ξ _i=0.51um;

Subsequently, in step (l), calculate the 1st frame coefficientoffrictionμ _i=0.052;

Subsequently, as shown in Figure 2, in step (m), the i-th frame roll-force is calculated:

M1) initial general rolling force P is defined _i', roll-force control accuracy δ, accurate general rolling force P _i;

M2) P is made _i'=1000 (t), δ=10 ^-10;

M3) calculate consider the elastic compression of rolled piece and elastic recovery working roll elastic flattening radius R ' _i=270.13;

M4) external friction power influence coefficient is calculated

M5) computational plasticity distorted area roll-force P _pi=424.98 (t);

M6) entrance elastic compression district roll-force P is calculated _e1i=406.45 (t);

M7) outlet elastic compression district roll-force P is calculated _e2i=327.65 (t);

M8) general rolling force P is calculated _i=1159.08 (t);

M9) obvious | P _i-P _i' |=159.08≤δ is false, then make P _i'=P _i=1159.08 (t), and proceed to step m3);

M10) the 1st frame roll-force P is exported _i=1354.3 (t);

Subsequently, in step (n), calculating the 1st frame working roll elastic flattening radius R ' _i=276.66, external friction power influence coefficient advancing slip value f _si=0.021 and roll torque N _i=6.67 × 10 ³nm;

Subsequently, in step (o), calculate the 1st frame slip factor ψ _i=0.31 and slip injury index

Subsequently, in step (p), calculate the 1st frame rolling power W _i=2045KW;

Subsequently, in step (q), obvious inequality $\left\{\begin{array}{c}1354.3\≤1500\\ 0.31\≤0.5\\ 0.80\≤0.82\\ 2045\≤2500\end{array}\right.$ Set up, proceed to step (r);

Subsequently, in step (r), make i=i+1=2, obvious 2≤5, then proceed to step (i);

Subsequently, in step (s), calculate unit all frame power consumptions summation F _j=178.34 (kilowatt hour/tons);

Subsequently, in step (t), unit of account volume cost Controlling object function formula G _j(X)=279.62 (yuan/ton);

Subsequently, in step (u), because Powell condition is false, be then false, adjust X ₀with Δ X, reset j=0, and repeat above-mentioned steps (f) to step (t), until Powell condition is set up;

Subsequently, in step (v), export the X={3050 that G (X)=225.34 (yuan/ton) gets minimum value, 3450,3500,3600,3900} optimum solution, G (X) is now the minimum specific yield cost of unit.

When then unit normally runs, must ensure each frame emulsion flow equal or infinite approach { 3050,3450,3500,3600,3900} is optimized unit emulsion flow with this target, effectively can reduces enterprise cost, for enterprise brings benefit.

Embodiment 2

First, in step (a), collect on-site parameters, comprising: five frame inlet/outlet thickness h _i-1, h _i(mm) { (1.82,1.15), (1.15,0.81), (0.81,0.55), (0.55,0.40), (0.40,0.25) }, five breast roller radius Rs _i(mm) { 265,250,250,250,250}, five gantry motor efficiency eta _i{ 0.90,0.89,0.89,0.85,0.88}, strip density ρ=7850 (kg/m ³), tandem mills i-th frame emulsion flow Q _i(L/min) { 3000,3400,3600,3800,4200}, five frame strip width B _i=1800 (mm), Young modulus E=210GPa, Poisson ratio v=0.3, five frame average deformation drag K _mi(Mpa) { 392,485,561,596,652}, five frame maximum emulsion flow Q _imax(L/min) { 4200,4300,4300,4300,4500}, the maximum total flow Q of unit emulsion _max(L/min)=21600, five frame band steel inlet/outlet tension force T _i-1, T _i(Mpa) { (51,176), (176,176), (176,150), (150,176), (176,68) }, rolling milimeter number L after five frame work roll changings _i(Km) { 160,150,150,160,170}, five maximum draught pressure P of frame _imax(t) { 1500,1500,1500,1500,1500}, five maximum slip factor ψ of frame _imax=0.43, five maximum slip injury index of frame five maximum rolling power W of frame _imax(KW) { 2500,3800,3800,3800,3800}, tandem mills Final Stand Rolling speed V ₅=1680 (m/min), wherein parameter i is tandem mills frame numbering, and n=5 is the total frame number of tandem mills;

Subsequently, in step (b), collect unit and to rub special characterisitic parameter, comprising: the i-th frame fluid friction influence coefficient a _i={ 0.0127,0.0122,0.0123,0.0128,0.0132}, the i-th frame dry friction influence coefficient b _i={ 0.1536,0.1521,0.1520,0.1538,0.1535}, the i-th frame friction factor damped expoential B _{ξ i}={ the-2.5497 ,-2.5487 ,-2.5405 ,-2.5408 ,-2.5412}, i-th frame concentration of emulsion used influence coefficient k _ci={ 2.1 × 10 ^-5, 1.9 × 10 ^-5, 1.8 × 10 ^-5, 1.9 × 10 ^-5, 2.0 × 10 ^-5, emulsion viscosity compressibility coefficient θ=0.05, the i-th frame working roll and belt steel surface Longitudinal Surface Roughness carry emulsion strength factor k secretly _rgi={ 0.09,0.11,0.12,0.14,0.13}, the i-th frame impression rate K _rsi={ 0.029,0.031,0.032,0.034,0.036}, the i-th frame working roll initial roughness Ra _r0i={ 1.15,0.83,0.51,0.52,2.81}, the i-th frame working roll roughness attenuation coefficient B _li={-0.00244 ,-0.00233 ,-0.00232 ,-0.00234 ,-0.00225}, kinetic viscosity parameter a under emulsion atmospheric pressure ₁=51, b ₁=0.012, i-th breast roller linear resonance surface velocity (m/min) V _ri={ 354,502,740,1017,1627}, the i-th frame emulsion contacts with the strip face (m ²) A _i=1.80, i-th frame band steel nip angle α _i={ 0.050,0.037,0.032,0.024,0.021}, emulsion specific heat capacity c _m=2.0kJ/ (kg DEG C), emulsion density p _breast=0.89kg/L, emulsion initial temperature t ₀=20 DEG C, temperature (DEG C) t after the i-th frame emulsion temperature rise _i={ 55,52,51,52,56}, the i-th frame coefficient of heat transfer and emulsion discharge relation linear coefficient k _3i=={ 0.73,0.71,0.68,0.68,0.65}, the i-th frame coefficient of heat transfer and emulsion discharge relation index c _3i={ 0.648,0.648,0.648,0.648,0.648}, emulsion Flux Loss coefficient k _4i{ 0.8,0.7,0.6,0.6,0.9};

Subsequently, in step (c), collect unit efficiency parameter, comprising: the cost ξ of every kilowatt-hour of power consumption _d=1 yuan/kilowatt hour, milling train expends the integrated cost ξ of often liter of emulsion _r=0.05 yuan/liter;

Subsequently, in step (d), make X={Q ₁, Q ₂, Q ₃, Q ₄, Q ₅be unit 5 frames emulsion flow separately, define flow iterative process parameter j and initialization j=0;

Subsequently, in step (e), initial value X ₀={ 2100,2300,2300,2400,2500}, initial optimization step delta X ₀={ 50,50,50,50,50};

Subsequently, in step (f), calculate X=X ₀+ j Δ X ₀={ 2100,2300,2300,2400,2500};

Subsequently, in step (g), obvious inequality $\left\{\begin{array}{c}11600\≤21600\\ Q_i\≤Q_{imax}\end{array}\right.$ Set up, proceed to step (h);

Subsequently, in step (h), make i=1;

Subsequently, in step (i), calculate the 1st rack outlet speed V _i=239.24 (m/min), V _i=151.17 (m/min) and reduction ratio r _i=0.37, passage absolute draft amount Δ h _i=0.67 and equivalent tension force influence coefficient ξ _i'=88.5;

Subsequently, in step (j), calculate the 1st frame coefficient of kinetic viscosity η _i=25.3;

Subsequently, in step (k), calculate the 1st frame oil film thickness ξ _i=0.48um;

Subsequently, in step (l), calculate the 1st frame coefficientoffrictionμ _i=0.049;

Subsequently, as shown in Figure 2, in step (m), the i-th frame roll-force is calculated:

M1) initial general rolling force P is defined _i', roll-force control accuracy δ, accurate general rolling force P _i;

M2) P is made _i'=1000 (t), δ=10 ^-10;

M3) calculate consider the elastic compression of rolled piece and elastic recovery working roll elastic flattening radius R ' _i=271.95;

M4) external friction power influence coefficient is calculated

M5) computational plasticity distorted area roll-force P _pi=449.08 (t);

M6) entrance elastic compression district roll-force P is calculated _e1i=431.45 (t);

M7) outlet elastic compression district roll-force P is calculated _e2i=354.15 (t);

M8) general rolling force P is calculated _i=1234.68 (t);

M9) obvious | P _i-P _i' |=234.68≤δ is false, then make P _i'=P _i=1234.68 (t), and proceed to step m3);

M10) the 1st frame roll-force P is exported _i=1389.5 (t);

Subsequently, in step (n), calculating the 1st frame working roll elastic flattening radius R ' _i=277.3, external friction power influence coefficient advancing slip value f _si=0.032 and roll torque N _i=7.52 × 10 ³nm;

Subsequently, in step (o), calculate the 1st frame slip factor ψ _i=0.41 and slip injury index

Subsequently, in step (p), calculate the 1st frame rolling power W _i=2243KW;

Subsequently, in step (q), obvious inequality $\left\{\begin{array}{c}1389.5\≤1500\\ 0.41\≤0.43\\ 0.76\≤0.82\\ 2243\≤2500\end{array}\right.$ Set up, proceed to step (r);

Subsequently, in step (r), make i=i+1=2, obvious 2≤5, then proceed to step (i);

Subsequently, in step (s), calculate unit all frame power consumptions summation F _j=214.42 (kilowatt hour/tons);

Subsequently, in step (t), unit of account volume cost Controlling object function formula G _j(X)=312.15 (yuan/ton);

Subsequently, in step (u), because Powell condition is false, be then false, adjust X ₀with Δ X, reset j=0, and repeat above-mentioned steps (f) to step (t), until Powell condition is set up;

Subsequently, in step (v), export the X={3000 that G (X)=284.57 (yuan/ton) gets minimum value, 3200,3300,3450,3800} optimum solution, G (X) is now the minimum specific yield cost of unit.

When then unit normally runs, must ensure each frame emulsion flow equal or infinite approach { 3000,3200,3300,3450,3800} is optimized unit emulsion flow with this target, effectively can reduces enterprise cost, for enterprise brings benefit.

Claims (1)

1. in cold continuous rolling process with the emulsion flow set method that cost Comprehensive Control is target, it is characterized in that: it comprises the following step performed by computing machine:

A) collect on-site parameters, comprising: unit i-th frame gateway thickness h _i, h _i-1, unit i-th gantry motor efficiency eta _i, unit i-th breast roller radius R _i, unit strip width B, unit strip density ρ, Young modulus E, Poisson ratio v, unit i-th frame average deformation drag K _mi, unit i-th frame emulsion maximum flow Q _imax, unit emulsion total flow maximal value Q _max, tension force T before and after unit i-th frame band steel _i, T _i-1, rolling milimeter number L after unit i-th frame work roll changing _i, the maximum draught pressure P of unit i-th frame _imax, the maximum slip factor ψ of unit i-th frame _imax, the maximum slip injury index of unit i-th frame the maximum rolling power W of unit i-th frame _imax, unit Final Stand Rolling speed V _n, wherein parameter i is machine set frame numbering, and n is the total frame number of unit;

B) collect unit friction coefficient, comprising: the i-th frame fluid friction influence coefficient a _i, the i-th frame dry friction influence coefficient b _i, the i-th frame friction factor damped expoential B _{ξ i}, the i-th frame concentration of emulsion used influence coefficient k _ci, emulsion viscosity compressibility coefficient θ, the i-th frame working roll and belt steel surface Longitudinal Surface Roughness carry emulsion strength factor k secretly _rgi, the i-th frame impression rate K _rsi, the i-th frame working roll initial roughness Ra _r0i, the i-th frame working roll roughness attenuation coefficient B _li, kinetic viscosity parameter a under emulsion atmospheric pressure ₁, b ₁, the i-th breast roller linear resonance surface velocity V _ri, the i-th frame emulsion contacts with the strip face A _i, the i-th frame band steel nip angle α _i, emulsion specific heat capacity c _m, emulsion density p _breast, emulsion initial temperature t ₀, the temperature t after the i-th frame emulsion temperature rise _i, the i-th frame coefficient of heat transfer and emulsion discharge relation linear coefficient k _3i, the i-th frame coefficient of heat transfer and emulsion discharge relation index c _3i, emulsion Flux Loss coefficient k _4i;

C) gathering machine group cost parameter, comprising: the cost ξ of every kilowatt-hour of power consumption _d, milling train expends the integrated cost ξ of often liter of emulsion _r;

D) X={Q is made ₁, Q ₂, Q ₃, Q ₄, Q ₅be unit n=5 frame emulsion flow separately, define flow iterative process parameter j and initialization j=0;

E) initial value X ₀={ Q ₁₀, Q ₂₀, Q ₃₀, Q ₄₀, Q ₅₀, initial optimization step delta X ₀={ Δ Q ₁₀, Δ Q ₂₀, Δ Q ₃₀, Δ Q ₄₀, Δ Q ₅₀;

F) X=X is calculated ₀+ j Δ X ₀;

G) judge $\left\{\begin{array}{c}\underset{i=1}{\overset{n}{\Σ}}\left(Q_i\right)\≤Q_{max}\\ Q_i\≤Q_{imax}\end{array}\right.$ If set up, then proceed to step h); If be false, adjustment X ₀with Δ X, reset j=0, and proceed to step f);

H) i=1 is made;

I) the i-th frame gateway speed is calculated i-th frame reduction ratio i-th frame passage absolute draft amount Δ h _i=h _i-1-h _i, the i-th frame equivalence tension force influence coefficient ξ _i'=0.3T _i+ 0.7T _i-1;

J) the i-th frame coefficient of kinetic viscosity is calculated

K) the i-th frame oil film thickness is calculated

${\mathrm{\ξ}}_i=\frac{h_{i-1}+h_i}{2h_{i-1}}\·k_{ci}\·\frac{3{\mathrm{\θ\η}}_i\left(V_{ri}+V_{i-1}\right)}{{\mathrm{\α}}_i\[1-e^{-\mathrm{\θ}\left(K_{mi}-T_{i-1}\right)}\]}-k_{rgi}\·\left(1+K_{rsi}\right)\·{\mathrm{Ra}}_{r0i}\·e^{-B_{Li}\·L_i};$

L) friction factor of the i-th frame is calculated

M) calculate the i-th frame roll-force, adopt the following step performed by computing machine:

M1) initial general rolling force P is defined _i', roll-force control accuracy δ, accurate general rolling force P _i;

M2) P is made _i'=1000 (t), δ=10 ^-10;

M3) elastic compression of rolled piece and the working roll elastic flattening radius of elastic recovery are considered in calculating

${R^{\′}}_i=R_i\[1+\frac{16(1-v^2){P_i}^{\′}}{\mathrm{\π}EB(\sqrt{{\mathrm{\Δh}}_i+\frac{1-v^2}{E}{h}_i(K_{mi}-T_i)}+\sqrt{\frac{1-v^2}{E}{h}_i(K_{mi}-T_i)})}\];$

M4) external friction power influence coefficient is calculated $Q_{G_i}=1.08-1.02r_i+1.79r_i\·{\mathrm{\μ}}_i\sqrt{\frac{{R^{\′}}_i}{h_{i-1}}};$

M5) computational plasticity distorted area roll-force

M6) entrance elastic compression district roll-force is calculated

M7) outlet elastic compression district roll-force is calculated

M8) general rolling force P is calculated _i=P _pi+ P _e1i+ P _e2i;

M9) judge | P _i-P _i' |≤δ, if set up, proceeds to step m10); Be false, then make P _i'=P _i, and proceed to step m3);

M10) general rolling force P is exported _i;

N) the i-th frame working roll elastic flattening radius is calculated

I-th frame external friction power influence coefficient $Q_{G_i}=1.08-1.02r_i+1.79r_i\·{\mathrm{\μ}}_i\sqrt{\frac{{R^{\′}}_i}{h_i}},$

The advancing slip value of i-th frame $f_{si}=\left(1-\frac{h_i}{2{R_i}^{\′}}\right)\frac{{\mathrm{\Δh}}_i}{4h_i}{\[1-\frac{1}{2{\mathrm{\μ}}_i}\left(\sqrt{\frac{{\mathrm{\Δh}}_i}{{R_i}^{\′}}}-\frac{{\mathrm{Bh}}_i{T}_i-{\mathrm{Bh}}_{i-1}{T}_{i-1}}{P_i}\right)\]}^2,$

I-th frame roll torque $N_i=B\[(k_{mi}-{{\mathrm{\ξ}}_i}^{\′})R_i{\mathrm{\Δh}}_i{Q}_{G_i}+T_{i-1}{R}_i{h}_{i-1}-T_i{R}_i{h}_i\]\×\frac{1}{1000};$

O) slip factor of the i-th frame is calculated and slip injury index

P) the i-th frame rolling power is calculated

Q) judge set up? if set up, then proceed to step r); Be false, then make j=j+1, proceed to step f);

R) i=i+1 is made, judge i≤n? if set up, then proceed to step I); Be false, then proceed to step s);

S) unit all frame power consumptions summation is calculated

T) tectonic unit's volume cost Controlling object function formula

U) do you judge that Powell condition is set up? if set up, then proceed to step v); Be false, adjust X ₀with Δ X, reset j=0, and repeat above-mentioned steps f) to step t), until Powell condition is set up;

V) X={Q that G (X) gets minimum value is exported ₁, Q ₂, Q ₃, Q ₄, Q ₅optimum solution, G (X) is now the minimum specific yield cost of unit.