CN100370117C - Online controlling method for steam turbine rotator equivalent stress safety margin coefficient - Google Patents

Online controlling method for steam turbine rotator equivalent stress safety margin coefficient Download PDF

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CN100370117C
CN100370117C CNB2006100302454A CN200610030245A CN100370117C CN 100370117 C CN100370117 C CN 100370117C CN B2006100302454 A CNB2006100302454 A CN B2006100302454A CN 200610030245 A CN200610030245 A CN 200610030245A CN 100370117 C CN100370117 C CN 100370117C
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steam turbine
equivalent stress
stress
rotor
turbine
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CN1908382A (en
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史进渊
杨宇
邓志成
危奇
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Shanghai Power Equipment Research Institute Co Ltd
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Abstract

The invention relates to an online detecting method on the equivalent stress safe allowance factor of the rotor of turbine, wherein it is characterized in that: it uses artificial nerve network technique to realize the online real-time calculation and online real-time detection and control on said factor; if said factor is lower than preset value, it can control the temperature change rate of main steam, and the load change rate to improve the factor and prolong the service life. If the factor reaches the alarm value, it will alarm, and stop in preset time. The invention can realize quick and accurate online real-time calculation, detection and control.

Description

A kind of online controlling method for steam turbine rotator equivalent stress safety margin coefficient
Technical field
The present invention relates to a kind of online real-time calculating of artificial neural network technology realization steam turbine rotator equivalent stress safety margin coefficient and method of in-service monitoring and control of adopting, be applied to steam turbine rotator equivalent stress safety margin coefficient on line control and turbine rotor life-span online management, belong to the steam turbine technology field.
Background technique
In the process of steam turbine startup, shutdown and load change; inhomogeneous heating of turbine rotor or cooling; turbine rotor is the bigger thermal stress of the even generation of temperature distributing disproportionation radially, causes steam turbine rotator equivalent stress to increase, and the safety margin coefficient of equivalent stress reduces.Smaller equivalent stress safety margin coefficient produces bigger low-cycle fatigue damage to turbine rotor, has shortened the working life of turbine rotor.In order to prolong the working life of turbine rotor, need be at the safety margin coefficient of the equivalent stress of line computation, supervision and control turbine rotor.Heavy wall cylindrical models such as prior art use are in the equivalent stress of line computation turbine rotor, be characterized in that computational speed is fast, can in seconds finish once and calculate, the error that main deficiency is an equivalent stress result of calculation is big, compare with the equivalent stress that actual turbine rotor structure finite element numerical calculation draws, the absolute value that calculates relative error influences the accuracy of steam turbine rotator equivalent stress safety margin coefficient in-service monitoring and control up to 35%.
Summary of the invention
The purpose of this invention is to provide a kind of artificial neural network technology that adopts and realize the method for steam turbine rotator equivalent stress safety margin coefficient, realize online real-time calculating and the in-service monitoring and the control of quick, the high accuracy of steam turbine rotator equivalent stress safety margin coefficient in line computation and in-service monitoring and control.
For realizing above purpose, technological scheme of the present invention provides a kind of online controlling method for steam turbine rotator equivalent stress safety margin coefficient, it is characterized in that, adopts artificial neural network technology, and its method is made up of two flow processs:
First pass: determine the steam turbine rotator equivalent stress correction factor based on artificial neural network
The first step: adopt the simplified model of prior art to calculate rotor outer surface name equivalent stress σ Ne
Adopt the temperature field of the simplified model calculated off-line turbine rotor of prior art, the turbine rotor that center hole is arranged such as is reduced at the heavy wall cylindrical model, the turbine rotor of no center hole is reduced to the equal diameter cylinder model, the temperature field of adopting method of difference to calculate this simplified model; Adopt nominal centrifugal stress, nominal vapor tension stress and the nominal thermal stress of the analytic formula calculating rotor outer surface of prior art, turbine rotor outer surface name equivalent stress σ NeFormula be:
σ ne = ( σ θt + σ θp + σ θth ) 2 + ( σ zth ) 2 - ( σ θt + σ θp + σ θth ) ( σ zth )
In the formula:
σ θ tThe tangential centrifugal stress of-rotor outer surface name
σ θ p-rotor outer surface name vapor tension stress
σ θ thThe tangential thermal stress of-rotor outer surface name
σ Zth-rotor outer surface name is thermal stress axially
Second step: determine transient state equivalent stress correction factor y i
Same roots rotor for the same model steam turbine, set up bidimensional or three-dimensional finite element model according to the practical structures size, the change condition of vapor (steam) temperature, pressure, rotating speed and the power etc. of the given steam turbine identical with step 1, adopt the FEM (finite element) model calculated off-line of prior art, draw the equivalent stress σ of turbine rotor outer surface same area Eqa, for the transient state moment t of steam turbine start-up course, stopping process or load change process i, the rotor outer surface equivalent stress σ that FEM (finite element) model calculates EqaThe rotor surface name equivalent stress σ that calculates divided by simplified model Ne, calculate the equivalent stress correction factor y of rotor outer surface i:
y i=σ eqane
The 3rd step: set up the artificial neural network that calculates equivalent stress correction factor y
Set up three-layer artificial neural network's model, comprise input layer, hidden layer and output layer, input layer is made up of 5 nodes, and 5 physical quantitys of 5 input layer correspondences are: steam turbine main steam pressure P 0, steam turbine main steam temperature t 0, steam turbine working speed n, turbine rotor volume averaging temperature θ mWith the steam turbine transient be the initial moment inner cylinder metal monitor temperature e of start-up course, stopping process and load change process 0Hidden layer is made up of 10 to 20 nodes; Output layer has only a node, the correction factor y of expression steam turbine rotator equivalent stress;
The 4th step: connection weights and the threshold value of determining artificial neural network
The correction factor y of each turbine rotor transient state equivalent stress i, all to one group of steam turbine main steam pressure P should be arranged 0i, steam turbine main steam temperature t 0i, steam turbine working speed n i, turbine rotor volume averaging temperature θ MiInitial moment inner cylinder metal monitor temperature θ with the steam turbine transient 0i, the correction factor y of Q the steam turbine rotator equivalent stress that calculates for a large amount of start-up courses, stopping process and load change process iWith Q group input value, constitute Q group training sample, to Q group input sample data P 0i, t 0i, n i, θ Mi, θ 0iWith Q output value y iAdopt batch algorithms, relative error quadratic sum with network export target value and actual value output is trained as performance function, train the performance function of network to reach given 0.025%, realize the Nonlinear Mapping between input output, just can finish training, can draw and be connected weights, hidden node and the internodal threshold value of weights, hidden node and the threshold value of output layer node of being connected of output layer between this artificial neural network input layer and hidden node;
The 5th step: write the artificial neural network software that calculates the equivalent stress correction factor
By the threshold value that is connected weights and node between the artificial nerve network model that calculates steam turbine rotator equivalent stress correction factor y and its node, adopt the C language compilation to calculate the software for calculation of equivalent stress correction factor y, the parameter that operates in steam turbine monitors on the computer with control;
Second flow process: steam turbine rotator equivalent stress safety margin coefficient is in line computation, supervision and control
The 6th step: adopt the nominal equivalent stress of the online real-time calculating of simplified model
Adopt the simplified model that waits heavy wall cylinder or equal diameter cylinder of prior art, online real-time calculating turbine rotor outer surface name equivalent stress σ Ne
The 7th step: use the online real-time calculating equivalent stress correction factor y of artificial neural network technology
The steam turbine main steam pressure P of Input Online monitoring 0, steam turbine main steam temperature t 0, steam turbine working speed n steam turbine inner casing metal monitor temperature of the initial moment of transient θ 0And the online turbine rotor volume averaging temperature θ that calculates m, use the artificial neural network software that calculates the equivalent stress correction factor, calculate steam turbine rotator equivalent stress correction factor y in real time;
The 8th step: online real-time calculating equivalent stress monitoring value σ Eq
The artificial neural network special-purpose software that uses a computer, the monitoring value σ of online real-time calculating turbine rotor outer surface equivalent stress Eq:
σ eq=y×σ ne
The 9th step: the ultimate stress σ of online real-time calculating turbine rotor material u
The ultimate stress σ of online real-time calculating turbine rotor material u, the ultimate stress σ of turbine rotor material uGet YIELD STRENGTH σ under the working rotor temperature 0.2With 1000 hours rupture strength σ of material work FrMinimum value:
σ u=min{σ 0.2;σ fr}
The tenth step: online real-time calculating steam turbine rotator equivalent stress safety margin coefficient S SA
Online real-time calculating steam turbine rotator equivalent stress safety margin coefficient, steam turbine rotator equivalent stress safety margin coefficient S SAUltimate stress σ for rotor material uWith rotor outer surface equivalent stress monitoring value σ EqDifference with the ultimate stress σ of rotor material uThe ratio:
S SA=(σ ueq)/σ u
The 11 step: the in-service monitoring of steam turbine rotator equivalent stress safety margin coefficient and control
The equivalent stress safety margin coefficient S of online real-time calculating turbine rotor SAAnd with setting value relatively, the supervision of steam turbine rotator equivalent stress safety margin coefficient and control are divided into following three kinds of situations: as if S SA〉=20%, the main steam temperature variance ratio of steam turbine and load changing rate are by the stated number Value Operations of " steam turbine operation rules "; If 0<S SA<20%, reduce the main steam temperature variance ratio and the load changing rate of steam turbine, to increase the margin of safety of steam turbine rotator equivalent stress; If-5%<S SA≤ 0%, the main steam temperature variance ratio and the load change rate of control steam turbine are 0, to increase the margin of safety of steam turbine rotator equivalent stress;
The 12 step: the online warning of steam turbine rotator equivalent stress safety margin coefficient and beat the stress safety margin coefficient S of the online real-time calculating turbine rotor of gate stop-start SA, if-25%<S SA≤-5%, send warning, tripping grinder after 30 minutes; If S SA≤-25%, give the alarm tripping grinder after 1 minute.
The present invention provides a kind of method of the online real-time calculating steam turbine rotator equivalent stress safety margin coefficient of artificial neural network technology and method of equivalent stress safety margin coefficient LINE REAL TIME MONITORING and control of adopting, and can realize online real-time calculating and the LINE REAL TIME MONITORING and the control of steam turbine rotator equivalent stress safety margin coefficient.If steam turbine rotator equivalent stress safety margin coefficient is less than setting value, increase steam turbine rotator equivalent stress safety margin coefficient by the rate of temperature change of online real-time control steam turbine main steam, the load changing rate of steam turbine, to reduce the low-cycle fatigue life damage of turbine rotor.When if steam turbine rotator equivalent stress safety margin coefficient reaches alarming value; send warning; and in the time of setting, shut down; monitor and control steam turbine rotator equivalent stress safety margin coefficient and prolong the high pressure rotor technique effect in working life to reduce the low-cycle fatigue life damage of turbine rotor, to reach.
Advantage of the present invention be realize steam turbine rotator equivalent stress safety margin coefficient fast, online real-time calculating and the in-service monitoring and the control of high accuracy.
Description of drawings
Fig. 1 is an artificial nerve network model of the present invention;
Fig. 2 is the flow chart of method that the present invention adopts;
Fig. 3 is a computer software block diagram of the present invention;
The Changing Pattern of outer surface equivalent stress behind the high pressure rotor governing stage of Fig. 4 cold start process;
The Changing Pattern of outer surface equivalent stress behind the high pressure rotor governing stage of Fig. 5 warm starting process;
The Changing Pattern of outer surface equivalent stress behind the high pressure rotor governing stage of Fig. 6 hot starting, hot start process;
The Changing Pattern of outer surface equivalent stress behind the high pressure rotor governing stage of Fig. 7 very hot startup process;
The Changing Pattern of outer surface equivalent stress safety margin coefficient behind the high pressure rotor governing stage impeller of Fig. 8 cold start process.
Embodiment
As shown in Figure 2, method provided by the invention is made up of two flow processs, and five steps of the first step to the of technical solution of the present invention constitute first flow process, use nerual network technique to determine the correction factor y of steam turbine rotator equivalent stress; The 6th step of technical solution of the present invention constitutes second flow process to the 12 step, the equivalent stress safety margin coefficient of online real-time calculating, supervision and control turbine rotor, and the invention will be further described below in conjunction with drawings and Examples.
Embodiment
It for certain model throttle (steam) temperature 566 ℃ overcritical 600MW turbine high-pressure rotor, adopt the flow chart of artificial nerve network model that the present invention shown in Figure 1 adopts, the method that the invention provides shown in Figure 2 and the software for calculation block diagram of the inventive method shown in Figure 3, the result of calculation of this turbine high-pressure rotor equivalent stress in different start-up courses that calculates is listed in Fig. 4 to Fig. 7.
The first step and the 6th step: the online nominal equivalent stress σ that calculates this fillet position, turbine high-pressure rotor governing stage impeller outer surface in cold start process, warm starting process, hot starting, hot start process, very hot startup process of simplified model that adopts prior art NeIn Fig. 4 to Fig. 7, represent with curve 1.
Second step: adopt the FEM (finite element) model of prior art, calculated off-line draws the equivalent stress σ of this fillet position, turbine high-pressure rotor governing stage impeller outer surface in cold start process, warm starting process, hot starting, hot start process, very hot startup process EqaIn Fig. 4 to Fig. 7, represent with curve 3.In Fig. 4 to Fig. 7, the equivalent stress value σ of the corresponding curve 3 of same abscissa EqaNominal equivalent stress value σ with curve 1 NeCompare, draw a series of equivalent stress correction factor y i
The 3rd step: set up three-layer artificial neural network's model as shown in Figure 1, comprise input layer, hidden layer and output layer.Input layer is made up of 5 nodes, and 5 physical quantitys of 5 input layer correspondences are: steam turbine main steam pressure P 0, steam turbine main steam temperature t 0, steam turbine working speed n, turbine rotor volume averaging temperature θ mInitial moment inner cylinder metal monitor temperature θ with steam turbine transient (start-up course, stopping process and load change process) 0Hidden layer is made up of 10 to 20 nodes; Output layer has only a node, the correction factor y of expression steam turbine rotator equivalent stress.
The 4th step and the 5th step: to artificial nerve network model shown in Figure 1, adopt batch algorithms, through the study and the training of artificial neural network, determine the connection weights and the threshold value of artificial neural network, and write the artificial neural network software that calculates equivalent stress correction factor y.
The 7th step and the 8th step: use artificial neural network technology at line computation equivalent stress correction factor y, by formula σ Eq=y * σ NeThe equivalent stress correction value σ at online this fillet position, steam turbine high pressure rotor governing stage impeller outer surface that calculates EqCurve 2 expressions in Fig. 4 to Fig. 7.
The 9th step: this high pressure rotor adopts CrMoV material, its yield limit σ 0.2With the pass of operating temperature t be: σ 0.2=544.963-0.295t (MPa), its rupture strength σ Fr=10 c, c=[23 * (273+t)-3.4498 * 10 4]/(-6.5356 * 10 3)
The tenth step: outer surface fillet position equivalent stress safety margin coefficient S in the cold start process behind this turbine high-pressure rotor governing stage impeller of line computation SAChange curve as shown in Figure 8.
The 11 step and the 12 step: at this turbine high-pressure rotator equivalent stress safety margin coefficient S SAAmong Fig. 8 of Changing Pattern, A district S SA〉=20%, the main steam temperature variance ratio of steam turbine and load changing rate are by the stated number Value Operations of " steam turbine operation rules "; B district 0<S SA<20%, reduce the main steam temperature variance ratio and the load changing rate of steam turbine, to increase the margin of safety of steam turbine rotator equivalent stress; C district-5%<S SA≤ 0%, the main steam temperature variance ratio and the load change rate of control steam turbine are 0, to increase the margin of safety of steam turbine rotator equivalent stress; D district-25%<S SA≤-5%, send warning, tripping grinder after 30 minutes; E district S SA≤-25%, give the alarm tripping grinder after 1 minute.
Know that from Fig. 4 the result compares with the finite element calculated off-line, adopt and the invention provides method that the scope of the relative error of turbine high-pressure rotor outer surface cold start process equivalent stress is 0.005% to 3.583% in line computation.Know that from Fig. 5 the result compares with the finite element calculated off-line, adopt and the invention provides method that the scope of the relative error of turbine high-pressure rotor outer surface warm starting process equivalent stress is 0.038% to 1.360% in line computation.Know that from Fig. 6 the result compares with the finite element calculated off-line, adopt and the invention provides method in line computation,, the scope of the relative error of turbine high-pressure rotor outer surface hot starting, hot start process equivalent stress is 0.001% to 1.078%.Know that from Fig. 7 the result compares with the finite element calculated off-line, adopt and the invention provides method in line computation,, the scope of the relative error of turbine high-pressure rotor outer surface very hot startup process maximum equivalent is 0.004% to 1.536%.
Use the equivalent stress of equal diameter cylinder simplified model at line computation turbine high-pressure rotor, the result compares with the finite element calculated off-line, and the scope of the relative error of steam turbine start-up course mesohigh rotor outer surface equivalent stress is-35%~11%.Use the on-line calculation method of steam turbine rotator equivalent stress provided by the invention, the result compares with the finite element calculated off-line, steam turbine start-up course mesohigh rotor outer surface equivalent stress calculate relative error less than 4%.The simplified model that steam turbine rotator equivalent stress provided by the invention adopts artificial neural network technology to be about in the relative error of line computation to use prior art has reached raising steam turbine rotator equivalent stress and the equivalent stress safety margin coefficient technique effect in the line computation accuracy 1/9 of the relative error of line computation; Use technology provided by the invention at the steam turbine rotator equivalent stress safety margin coefficient of line computation and control the main steam temperature variance ratio of steam turbine of start-up course, stopping process and load change process of steam turbine and the load changing rate of steam turbine; can be implemented in the equivalent stress safety margin coefficient that line calculated, monitors and controlled turbine rotor in real time; realized the increase steam turbine rotator equivalent stress safety margin coefficient; reduce the low-cycle fatigue life damage of turbine rotor, reached the technique effect in prolongation turbine rotor working life.

Claims (1)

1. an online controlling method for steam turbine rotator equivalent stress safety margin coefficient is characterized in that, adopts artificial neural network technology, and its method is made up of two flow processs:
First pass: determine the steam turbine rotator equivalent stress correction factor based on artificial neural network
The first step: adopt the simplified model of prior art to calculate rotor outer surface name equivalent stress σ Ne
Adopt the temperature field of the simplified model calculated off-line turbine rotor of prior art, the turbine rotor that center hole is arranged such as is reduced at the heavy wall cylindrical model, the turbine rotor of no center hole is reduced to the equal diameter cylinder model, the temperature field of adopting method of difference to calculate this simplified model; Adopt nominal centrifugal stress, nominal vapor tension stress and the nominal thermal stress of the analytic formula calculating rotor outer surface of prior art, turbine rotor outer surface name equivalent stress σ NeFormula be:
σ ne = ( σ θt + σ θp + σ θth ) 2 + ( σ zth ) 2 - ( σ θt + σ θp + σ θth ) ( σ zth )
In the formula:
σ θ tThe tangential centrifugal stress of-rotor outer surface name
σ θ p-rotor outer surface name vapor tension stress
σ θ thThe tangential thermal stress of-rotor outer surface name
σ Zth-rotor outer surface name is thermal stress axially
Second step: determine transient state equivalent stress correction factor y i
Same roots rotor for the same model steam turbine, set up bidimensional or three-dimensional finite element model according to the practical structures size, the change condition of vapor (steam) temperature, pressure, rotating speed and the power etc. of the given steam turbine identical with step 1, adopt the FEM (finite element) model calculated off-line of prior art, draw the equivalent stress σ of turbine rotor outer surface same area Eqa, for the transient state moment t of steam turbine start-up course, stopping process or load change process i, the rotor outer surface equivalent stress σ that FEM (finite element) model calculates EqaThe rotor surface name equivalent stress σ that calculates divided by simplified model Ne, calculate the equivalent stress correction factor y of rotor outer surface i:
y i=σ eqane
The 3rd step: set up the artificial neural network that calculates equivalent stress correction factor y
Set up three-layer artificial neural network's model, comprise input layer, hidden layer and output layer, input layer is made up of 5 nodes, and 5 physical quantitys of 5 input layer correspondences are: steam turbine main steam pressure P 0, steam turbine main steam temperature t 0, steam turbine working speed n, turbine rotor volume averaging temperature θ mWith the steam turbine transient be the initial moment inner cylinder metal monitor temperature θ of start-up course, stopping process and load change process 0Hidden layer is made up of 10 to 20 nodes; Output layer has only a node, the correction factor y of expression steam turbine rotator equivalent stress;
The 4th step: connection weights and the threshold value of determining artificial neural network
The correction factor y of each turbine rotor transient state equivalent stress i, all to one group of steam turbine main steam pressure P should be arranged 0i, steam turbine main steam temperature t 0i, steam turbine working speed n i, turbine rotor volume averaging temperature θ MiInitial moment inner cylinder metal monitor temperature θ with the steam turbine transient 0i, the correction factor y of Q the steam turbine rotator equivalent stress that calculates for a large amount of start-up courses, stopping process and load change process iWith Q group input value, constitute Q group training sample, to Q group input sample data P 0i, t 0i, n i, θ Mi, θ 0iWith Q output value y iAdopt batch algorithms, relative error quadratic sum with network export target value and actual value output is trained as performance function, train the performance function of network to reach given 0.025%, realize the Nonlinear Mapping between input output, just can finish training, can draw and be connected weights, hidden node and the internodal threshold value of weights, hidden node and the threshold value of output layer node of being connected of output layer between this artificial neural network input layer and hidden node;
The 5th step: write the artificial neural network software that calculates the equivalent stress correction factor
By the threshold value that is connected weights and node between the artificial nerve network model that calculates steam turbine rotator equivalent stress correction factor y and its node, adopt the C language compilation to calculate the software for calculation of equivalent stress correction factor y, the parameter that operates in steam turbine monitors on the computer with control;
Second flow process: steam turbine rotator equivalent stress safety margin coefficient is in line computation, supervision and control
The 6th step: adopt the nominal equivalent stress of the online real-time calculating of simplified model
Adopt the simplified model that waits heavy wall cylinder or equal diameter cylinder of prior art, online real-time calculating turbine rotor outer surface name equivalent stress σ Ne:
The 7th step: use the online real-time calculating equivalent stress correction factor y of artificial neural network technology
The steam turbine main steam pressure P of Input Online monitoring 0, steam turbine main steam temperature t 0, steam turbine working speed n steam turbine inner casing metal monitor temperature of the initial moment of transient θ 0And the online turbine rotor volume averaging temperature θ that calculates m, use the artificial neural network software that calculates the equivalent stress correction factor, calculate steam turbine rotator equivalent stress correction factor y in real time;
The 8th step: online real-time calculating equivalent stress monitoring value σ Eq
The artificial neural network special-purpose software that uses a computer, the monitoring value σ of online real-time calculating turbine rotor outer surface equivalent stress Eq:
σ eq=y×σ ne
The 9th step: the ultimate stress σ of online real-time calculating turbine rotor material u
The ultimate stress σ of online real-time calculating turbine rotor material u, the ultimate stress σ of turbine rotor material uGet YIELD STRENGTH σ under the working rotor temperature 0.2With 1000 hours rupture strength σ of material work FrMinimum value:
σ u=min{σ 0.2;σ fr}
The tenth step: online real-time calculating steam turbine rotator equivalent stress safety margin coefficient S SA
Online real-time calculating steam turbine rotator equivalent stress safety margin coefficient, steam turbine rotator equivalent stress safety margin coefficient S SAUltimate stress σ for rotor material uWith rotor outer surface equivalent stress monitoring value σ EqDifference with the ultimate stress σ of rotor material uThe ratio:
S SA=(σ ueq)/σ u
The 11 step: the in-service monitoring of steam turbine rotator equivalent stress safety margin coefficient and control
The equivalent stress safety margin coefficient S of online real-time calculating turbine rotor SAAnd with setting value relatively, the supervision of steam turbine rotator equivalent stress safety margin coefficient and control are divided into following three kinds of situations: as if S SA〉=20%, the main steam temperature variance ratio of steam turbine and load changing rate are by the stated number Value Operations of " steam turbine operation rules "; If 0<S SA<20%, reduce the main steam temperature variance ratio and the load changing rate of steam turbine, to increase the margin of safety of steam turbine rotator equivalent stress; If-5%<S SA≤ 0%, the main steam temperature variance ratio and the load change rate of control steam turbine are 0, to increase the margin of safety of steam turbine rotator equivalent stress;
The 12 step: the online warning of steam turbine rotator equivalent stress safety margin coefficient and beat the stress safety margin coefficient S of the online real-time calculating turbine rotor of gate stop-start SA, if-25%<S SA≤-5%, send warning, tripping grinder after 30 minutes; If S SA≤-25%, give the alarm tripping grinder after 1 minute.
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