APC process control when process parameters are inaccurately measured
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G05B-013/02
G05B-021/00
G06F-017/00
G06F-019/00
G01N-031/00
B01D-050/00
B01D-053/34
B01D-053/56
B01D-053/86
B01D-053/50
C01B-021/00
F01N-003/00
출원번호
UP-0002439
(2004-12-03)
등록번호
US-7698004
(2010-05-20)
발명자
/ 주소
Boyden, Scott A.
Piche, Stephen
출원인 / 주소
ALSTOM Technology Ltd.
대리인 / 주소
Antonelli, Terry, Stout & Kraus, LLP.
인용정보
피인용 횟수 :
14인용 특허 :
44
초록▼
A controller is provided for directing control of a process performed to control an amount of a pollutant emitted into the air. The process has multiple process parameters (MPPs) The controller includes either a neural network process model or a non-neural network process model. Whichever type model
A controller is provided for directing control of a process performed to control an amount of a pollutant emitted into the air. The process has multiple process parameters (MPPs) The controller includes either a neural network process model or a non-neural network process model. Whichever type model is included, it will represent a relationship between one of the MPPs and other of the MPPs. The controller also includes a control processor having the logic to determine the validity of a measured value of the one MPP based on the one model. The control processor directs control of the process in accordance with the measured value of the one MPP only if the measured value of the one MPP is determined to be valid. On the other hand, if the measured value is determined to be invalid, the control processor may direct control of the process in accordance with an estimated value of the one MPP.
대표청구항▼
We claim: 1. A controller for directing control of a process, having multiple process parameters (MPPs), performed to control an amount of a pollutant emitted into the air, comprising: one of a neural network process model and a non-neural network process model, the one model representing a relatio
We claim: 1. A controller for directing control of a process, having multiple process parameters (MPPs), performed to control an amount of a pollutant emitted into the air, comprising: one of a neural network process model and a non-neural network process model, the one model representing a relationship between one of the MPPs and other of the MPPs; a control processor configured with the logic to determine validity of a measured value of the one MPP based on the one model, and to direct control of the process in accordance with the measured value of the one MPP, only if the measured value of the one MPP is determined to be valid; and an estimator configured with logic to estimate the value of the one MPP based on actual values of the other MPPs and the one model; wherein the control processor determines the validity of the measured value of the one MPP based on the one model by comparing the estimated value of the one MPP with the measured value of the one MPP and, if the measured value of the one MPP is determined to be invalid, directs control of the process in accordance with an estimated value of the one MPP; wherein the process is a wet flue gas desulfurization (WFGD) process which applies a reactant to remove SO2 from SO2 laden wet flue gas, and exhausts desulfurized flue gas; wherein the one MPP is a pH level of the applied reactant; wherein the one model represents a relationship between the pH level of the applied reactant and the other MPPs; wherein the estimator estimates the value of the pH level of the applied reactant based on the actual values of the other MPPs and the one model; and wherein the control processor compares the estimated value of the pH level of the applied reactant with the measured value of the pH level of the applied reactant, to determine the validity of the measured value of the pH level of the applied reactant, and (i) if the measured value of the pH level of the applied reactant is determined to be valid, directs control of the WFDG process in accordance with the measured value of the pH level of the applied reactant, and (ii) if the measured value of the pH level of the applied reactant is determined to be invalid, directs control of the WFGD process in accordance with the estimated value of the pH level of the applied reactant. 2. The controller according to claim 1, wherein: the reactant is a limestone slurry; the other MPPs include an amount of the SO2 in the SO2 laden flue gas and an amount of the SO2 in the exhausted desulfurized flue gas; the one model represents a relationship between the pH level of the applied limestone slurry and the SO2 in the SO2 laden flue gas and the SO2 in the exhausted desulfurized flue gas; and the estimator estimates the value of the pH level of the applied limestone slurry based on the actual amount of SO2 in the SO2 laden flue gas and the actual amount of SO2 in the exhausted desulfurized flue gas, and on the one model. 3. A controller for directing control of a process, having multiple process parameters (MPPs), performed to control an amount of a pollutant emitted into the air, comprising: one of a neural network process model and a non-neural network process model, the one model representing a relationship between one of the MPPs and other of the MPPs; a control processor configured with the logic to determine validity of a measured value of the one MPP based on the one model, and to direct control of the process in accordance with the measured value of the one MPP, only if the measured value of the one MPP is determined to be valid; and an estimator configured with logic to estimate the value of the one MPP based on actual values of the other MPPs and the one model; wherein the control processor determines the validity of the measured value of the one MPP based on the one model by comparing the estimated value of the one MPP with the measured value of the one MPP and, if the measured value of the one MPP is determined to be invalid, directs control of the process in accordance with an estimated value of the one MPP; wherein the process is a selective catalytic reduction (SCR) process which applies a reactant to remove NOx from NOx laden flue gas, and exhausts reduced NOx flue gas; wherein the one MPP is an amount of the applied reactant; wherein the one model represents a relationship between the amount of applied reactant and the other MPPs; wherein the estimator estimates the value of the amount of applied reactant based on the actual values of the other MPPs and the one model; and wherein the control processor compares the estimated value of the amount of applied reactant with the measured value of the amount of applied reactant, to determine the validity of the measured value of the amount of applied reactant, and (i) if the measured value of the amount of applied reactant is determined to be valid, directs control of the SCR process in accordance with the measured value of the amount of applied reactant, and (ii) if the measured value of the amount of applied reactant is determined to be invalid, directs control of the SCR process in accordance with the estimated value of the amount of applied reactant. 4. The controller according to claim 3, wherein: the reactant is ammonia; the other MPPs include an amount of the NOx in the NOx laden flue gas and an amount of the NOx in the exhausted reduced NOx flue gas; the one model represents a relationship between the amount of the applied ammonia and the NOx in the NOx laden flue gas and the NOx in the exhausted reduced NOx flue gas; and the estimator estimates the value of the amount of the applied ammonia based on the actual amount of NOx in the NOx laden flue gas and the actual amount of NOx in the exhausted reduced NOx flue gas, and on the one model. 5. An article of manufacture for directing control of a process, having multiple process parameters (MPPs), performed to control an amount of a pollutant emitted into the air, comprising: computer readable storage media; and logic stored on the storage media, wherein the stored logic is configured to be readable by one or more computers and thereby cause the one or more computers to operate so as to: determine validity of a measured value of one of the MPPs based on one of a neural network process model and a non-neural network process model, the one model representing a relationship between the one MPP and other of the MPPs; direct control of the process in accordance with the measured value of the one MPP, only if the measured value of the one MPP is determined to be valid; estimate a value of the one MPP based on actual values of the other MPPs and the one model; compare the estimated value of the one MPP with the measured value of the one MPP; and if the measured value of the one MPP is determined to be invalid, direct control of the process in accordance with the estimated value of the one MPP; wherein the validity of the measured value of the one MPP is determined based also on the comparison of the estimated value of the one MPP with the measured value of the one MPP; wherein the process is a wet flue gas desulfurization (WFGD) process which applies a reactant to remove SO2 from SO2 laden wet flue gas, and exhausts desulfurized flue gas; wherein the one MPP is a pH level of the applied reactant; wherein the one model represents a relationship between the pH level of the applied reactant and the other MPPs; wherein the value of the pH level of the applied reactant is estimated based on the actual values of the other MPPs and the one model; wherein the estimated value of the pH level of the applied reactant is compared with the measured value of the pH level of the applied reactant, to determine the validity of the measured value of the pH level of the applied reactant; wherein if the measured value of the pH level of the applied reactant is determined to be valid, control of the WFDG process is directed in accordance with the measured value of the pH level of the applied reactant; and wherein if the measured value of the pH level of the applied reactant is determined to be invalid, control of the WFGD process is directed in accordance with the estimated value of the pH level of the applied reactant. 6. The article of manufacture according to claim 5, wherein: the reactant is a limestone slurry; the other MPPs include an amount of the SO2 in the SO2 laden flue gas and an amount of the SO2 in the exhausted desulfurized flue gas; the one model represents a relationship between the pH level of the applied limestone slurry and the SO2 in the SO2 laden flue gas and the SO2 in the exhausted desulfurized flue gas; and the value of the pH level of the applied limestone slurry is estimated based on the actual amount of SO2 in the SO2 laden flue gas and the actual amount of SO2 in the exhausted desulfurized flue gas, and on the one model. 7. An article of manufacture for directing control of a process, having multiple process parameters (MPPs), performed to control an amount of a pollutant emitted into the air, comprising: computer readable storage media; and logic stored on the storage media, wherein the stored logic is configured to be readable by one or more computers and thereby cause the one or more computers to operate so as to: determine validity of a measured value of one of the MPPs based on one of a neural network process model and a non-neural network process model, the one model representing a relationship between the one MPP and other of the MPPs; direct control of the process in accordance with the measured value of the one MPP, only if the measured value of the one MPP is determined to be valid; estimate a value of the one MPP based on actual values of the other MPPs and the one model; compare the estimated value of the one MPP with the measured value of the one MPP; and if the measured value of the one MPP is determined to be invalid, direct control of the process in accordance with the estimated value of the one MPP; wherein the validity of the measured value of the one MPP is determined based also on the comparison of the estimated value of the one MPP with the measured value of the one MPP; wherein the process is a selective catalytic reduction (SCR) process which applies a reactant to remove NOx from NOx laden flue gas, and exhausts reduced NOx flue gas; wherein the one MPP is an amount of the applied reactant; wherein the one model represents a relationship between the amount of applied reactant and the other MPPs; wherein the value of the amount of applied reactant is estimated based on the actual values of the other MPPs and the one model; and wherein the estimated value of the amount of applied reactant is compared with the measured value of the amount of applied reactant, to determine the validity of the measured value of the amount of applied reactant; wherein if the measured value of the amount of applied reactant is determined to be valid, control of the SCR process is directed in accordance with the measured value of the amount of applied reactant; and wherein if the measured value of the amount of applied reactant is determined to be invalid, control of the SCR process is directed in accordance with the estimated value of the amount of applied reactant. 8. The article of manufacture according to claim 7, wherein: the reactant is ammonia; the other MPPs include an amount of the NOx in the NOx laden flue gas and an amount of the NOx in the exhausted reduced NOx flue gas; the one model represents a relationship between the amount of the applied ammonia and the NOx in the NOx laden flue gas and the NOx in the exhausted reduced NOx flue gas; and the value of the amount of the applied ammonia is estimated based on the actual amount of NOx in the NOx laden flue gas and the actual amount of NOx in the exhausted reduced NOx flue gas, and on the one model. 9. A wet flue gas desulfurizing system, comprising: a wet flue gas desulfurizer configured (i) to receive SO2 laden wet flue gas, (ii) to apply limestone slurry to remove SO2 from the received SO2 laden wet flue gas, and (iii) to exhaust desulfurized flue gas; a pH sensor to measure a pH level of the applied limestone slurry; one of a neural network process model and a non-neural network process model, the one model representing a relationship between the pH level of the applied limestone slurry and an amount of the SO2 in the received SO2 laden wet flue gas and an amount of the SO2 in the exhausted desulfurized flue gas; and a control processor configured with the logic to determine validity of the measured pH level of the applied limestone slurry based on the one model, and to direct control of the process in accordance with the measured pH level of the applied limestone slurry only if the measured pH level of the applied limestone slurry is determined to be valid. 10. The system of claim 9, wherein the sensor is a first sensor, and further comprising: a second sensor to measure an actual amount of the SO2 in the received SO2 laden wet flue gas values; and a third sensor configured to measure an actual amount of the SO2 in the exhausted desulfurized flue gas; a virtual analyzer having the logic to estimate the pH level of the applied limestone slurry based on the measured amount of SO2 in the received SO2 laden wet flue gas, the measured amount of SO2 in the exhausted desulfurized flue gas and the one model; and a feed back loop configured to transmit the measured pH level of the applied limestone slurry, the measured amount of SO2 in the received SO2 laden wet flue gas, and the measured amount of SO2 in the exhausted desulfurized flue gas, to the virtual analyzer in real time; wherein the virtual analyzer estimates the pH level of the applied limestone slurry based on the transmitted measured amounts of SO2 in the received SO2 laden wet flue gas and in the exhausted desulfurized flue gas, in real time; wherein the control processor is further configured with the logic to compare the estimated pH level of the applied limestone slurry with the measured pH level of the applied limestone slurry, to determine the validity of the measured pH level of the applied limestone slurry based on the comparison and, if the measured pH level of the applied limestone slurry is determined to be invalid, to direct control of the process in accordance with the estimated pH level of the applied limestone slurry. 11. A selective catalytic reduction system, comprising: selective catalytic reducer configured (i) to receive NOx laden flue gas, (ii) to apply ammonia to remove NOx from the received NOx laden flue gas, and (iii) to exhaust reduced NOx flue gas; an ammonia sensor to measure an amount of ammonia in the exhausted reduced NOx flue gas; one of a neural network process model and a non-neural network process model, the one model representing a relationship between the amount of the ammonia in the exhausted reduced NOx flue gas and an amount of NOx in the received NOx laden flue gas and an amount of NOx in the exhausted reduced NOx flue gas; and a control processor having the logic to determine validity of the measured amount of ammonia in the exhausted reduced NOx flue gas based on the one model, and to direct control of the process in accordance with the measured amount of ammonia in the exhausted reduced NOx flue gas only if the measured amount of ammonia in the exhausted reduced NOx flue gas is determined to be valid. 12. The system of claim 11, wherein the sensor is a first sensor, and further comprising: a second sensor to measure an actual amount of the NOx in the received NOx laden flue gas; and a third sensor configured to measure an actual amount of the NOx in the exhausted reduced NOx flue gas; a virtual analyzer having the logic to estimate the amount of ammonia in the exhausted reduced NOx flue gas based on the measured amount of NOx in the received NOx laden flue gas and the measured amount of NOx in the exhausted reduced NOx flue gas, and on the one model; and a feed back loop configured to transmit the measured amount of NOx in the received NOx laden flue gas, and the measured amount of NOx in the exhausted reduced NOx flue gas, to the virtual analyzer in real time; wherein the virtual analyzer estimates the amount of ammonia in the exhausted reduced NOx flue gas based on the transmitted measured amounts of NOx in the received NOx laden flue gas and in the exhausted reduced NOx flue gas, in real time; wherein the control processor is further configured with the logic to compare the estimated amount of ammonia in the exhausted reduced NOx flue gas with the measured amount of ammonia in the exhausted reduced NOx flue gas, to determine the validity of the measured amount of ammonia in the exhausted reduced NOx flue gas based on the comparison and, if the measured amount of ammonia in the exhausted reduced NOx flue gas is determined to be invalid, to direct control of the process in accordance with the estimated amount of ammonia in the exhausted reduced NOx flue gas.
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