APC process parameter estimation
First Claim
1. A virtual analyzer for estimating either an attribute of a reactant applied during performance of, or an amount of a reactant exhausted by, a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air, comprising:
- an interface configured to receive signals corresponding to attributes of the MPPs, including (i) if the process is a wet flue gas desulfurization (WFGD) process, a signal corresponding to a measured current pH level of the applied reactant, and (ii) if the process is a selective catalytic reduction (SCR) process, a signal corresponding to a measured current amount of the reactant exhausted by the process;
one of a neural network process model and a non-neural network process model, the one model representing a relationship between either (i) if the process is a WFGD process, the current pH level of the applied reactant and the attributes of the MPPs other than the measured current pH level of the applied reactant or (ii) if the process is the SCR process, the current amount of the reactant exhausted by the process and the attributes of the MPPs other than the measured current amount of the reactant exhausted by the process; and
a processor configured with logic (i) if the process is the WFGD process, to estimate a current pH level of the applied reactant based on the attributes of the MPPs, other than the measured current pH level of the applied reactant, that correspond to the received signals and on the one model, and (ii) if the process is the SCR process, to estimate a current amount of the reactant exhausted by the process based on the attributes of the MPPs, other than the measured current amount of the reactant exhausted by the process, that correspond to the received signals and on the one model.
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Abstract
A virtual analyzer is provided to estimate either an attribute of a reactant applied during performance of, or an amount of a reactant exhausted by, a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air. The virtual analyzer includes an interface which receives signals corresponding to attributes of the MPPs. If the process is a wet flue gas desulfurization (WFGD) process, the signals include a signal corresponding to a measured pH level of the applied reactant. If the process is a selective catalytic reduction (SCR) process, the signals include a signal corresponding to a measured amount of the reactant exhausted by the process.
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Citations
12 Claims
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1. A virtual analyzer for estimating either an attribute of a reactant applied during performance of, or an amount of a reactant exhausted by, a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air, comprising:
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an interface configured to receive signals corresponding to attributes of the MPPs, including (i) if the process is a wet flue gas desulfurization (WFGD) process, a signal corresponding to a measured current pH level of the applied reactant, and (ii) if the process is a selective catalytic reduction (SCR) process, a signal corresponding to a measured current amount of the reactant exhausted by the process; one of a neural network process model and a non-neural network process model, the one model representing a relationship between either (i) if the process is a WFGD process, the current pH level of the applied reactant and the attributes of the MPPs other than the measured current pH level of the applied reactant or (ii) if the process is the SCR process, the current amount of the reactant exhausted by the process and the attributes of the MPPs other than the measured current amount of the reactant exhausted by the process; and a processor configured with logic (i) if the process is the WFGD process, to estimate a current pH level of the applied reactant based on the attributes of the MPPs, other than the measured current pH level of the applied reactant, that correspond to the received signals and on the one model, and (ii) if the process is the SCR process, to estimate a current amount of the reactant exhausted by the process based on the attributes of the MPPs, other than the measured current amount of the reactant exhausted by the process, that correspond to the received signals and on the one model. - View Dependent Claims (2, 4)
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3. A virtual analyzer for estimating either an attribute of a reactant applied during performance of, or an amount of a reactant exhausted by, a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air, comprising:
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an interface configured to receive signals corresponding to attributes of the MPPs, including (i) if the process is a wet flue gas desulfurization (WFGD) process, a signal corresponding to a measured current pH level of the applied reactant, and (ii) if the process is a selective catalytic reduction (SCR) process, a signal corresponding to a measured current amount of the reactant exhausted by the process; one of a neural network process model and a non-neural network process model, the one model representing a relationship between either (i) if the process is a WFGD process, the current pH level of the applied reactant and the attributes of the MPPs other than the measured current pH level of the applied reactant or (ii) if the process is the SCR process, the current amount of the reactant exhausted by the process and the attributes of the MPPs other than the measured current amount of the reactant exhausted by the process; a first processor configured with logic (i) if the process is the WFGD process, to estimate a current pH level of the applied reactant based on the attributes of the MPPs, other than the measured current pH level of the applied reactant, that correspond to the received signals and on the one model, and (ii) if the process is the SCR process, to estimate a current amount of the reactant exhausted by the process based on the attributes of the MPPs, other than the measured current amount of the reactant exhausted by the process, that correspond to the received signals and on the one model; and a second processor configured with logic, (i) if the process is the WFGD process, to compare the estimated current pH level of the applied reactant with the measured current pH level of the applied reactant corresponding to the received signal, and to determine the validity of the measured current pH level based on the comparison, and (ii) if the process is the SCR process, to compare the estimated current amount of reactant exhausted by the process with the measured current amount of reactant exhausted by the process corresponding to the received signal, and to determine the validity of the measured current amount based on the comparison; wherein the first processor estimates the current pH level of the applied reactant or the current amount of the reactant exhausted by the process, in real time during performance of the process; and wherein the second processor compares the estimated current pH level with the measured current pH level of the applied reactant and determines the validity of the measured current pH level, or compares the estimated current amount with the measured current amount of reactant exhausted by the process and determines the validity of the measured current amount, in real time during performance of the process.
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5. A virtual analyzer for estimating either an attribute of a reactant applied during performance of, or an amount of a reactant exhausted by, a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air, comprising:
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an interface configured to receive signals corresponding to attributes of the MPPs, including (i) if the process is a wet flue gas desulfurization (WFGD) process, a signal corresponding to a measured current pH level of the applied reactant, and (ii) if the process is a selective catalytic reduction (SCR) process, a signal corresponding to a measured current amount of the reactant exhausted by the process; one of a neural network process model and a non-neural network process model, the one model representing a relationship between either (i) if the process is a WFGD process, the current pH level of the applied reactant and the attributes of the MPPs other than the measured current pH level of the applied reactant or (ii) if the process is the SCR process, the current amount of the reactant exhausted by the process and the attributes of the MPPs other than the measured current amount of the reactant exhausted by the process; and a processor configured with logic (i) if the process is the WFGD process, to estimate a current pH level of the applied reactant based on the attributes of the MPPs, other than the measured current pH level of the applied reactant, that correspond to the received signals and on the one model, and (ii) if the process is the SCR process, to estimate a current amount of the reactant exhausted by the process based on the attributes of the MPPs, other than the measured current amount of the reactant exhausted by the process, that correspond to the received signals and on the one model; wherein the processor estimates the current pH level of the applied reactant or the current amount of the reactant exhausted by the process, in real time during performance of the process.
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6. A virtual analyzer for estimating an attribute of a reactant applied during performance of a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air, comprising:
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an interface configured to receive signals corresponding to attributes of the MPPs, including a signal corresponding to a measured current pH level of the applied reactant; one of a neural network process model and a non-neural network process model, the one model representing a relationship between the current pH level of the applied reactant and the attributes of the MPPs other than the measured current pH level of the applied reactant; and a processor configured with logic to estimate a current pH level of the applied reactant based on the attributes of the MPPs, other than the measured current pH level of the applied reactant, that correspond to the received signals and on the one model; wherein the reactant is a limestone slurry; wherein the process is a wet flue gas desulfurization (WFGD) process which applies the limestone slurry to remove SO2 from SO2 laden wet flue gas, and exhausts desulfurized flue gas; wherein the attributes of the MPPs include an amount of SO2 in the SO2 laden flue gas and an amount of SO2 in the exhausted desulfurized flue gas; wherein the one model represents a relationship between the pH level of the applied limestone slurry and the amount of SO2 in the SO2 laden flue gas and the amount of SO2 in the exhausted desulfurized flue gas; and wherein the processor estimates the current pH level of the applied limestone slurry based on the amount of SO2 in the SO2 laden flue gas and the amount of SO2 in the exhausted desulfurized flue gas that correspond to the received signals, and on the one model.
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7. A virtual analyzer for estimating an amount of a reactant exhausted by a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air, comprising:
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an interface configured to receive signals corresponding to attributes of the MPPs, including a signal corresponding to a measured current amount of the reactant exhausted by the process; one of a neural network process model and a non-neural network process model, the one model representing a relationship between the current amount of the reactant exhausted by the process and the attributes of the MPPs other than the measured current amount of the reactant exhausted by the process; and a processor configured with logic to estimate a current amount of the reactant exhausted by the process based on the attributes of the MPPs, other than the measured current amount of the reactant exhausted by the process, that correspond to the received signals and on the one model; wherein the reactant is ammonia; wherein the process is a selective catalytic reduction (SCR) process which applies ammonia to remove NOx from NOx laden flue gas and exhausts reduced NOx flue gas; wherein the attributes of the MPPs include an amount of NOx in the NOx laden flue gas and an amount of NOx in the exhausted desulfurized flue gas; wherein the one model represents a relationship between the amount of the ammonia in the exhausted reduced NOx flue gas and the amount of NOx in the NOx laden flue gas and the amount of NOx in the exhausted reduced NOx flue gas; and wherein the processor estimates the current amount of the ammonia in the exhausted reduced NOx flue gas based on the amount of NOx in the NOx laden flue gas and the amount of NOx in the exhausted reduced NOx flue gas that correspond to the received signals, and on the one model.
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8. A virtual analyzer for estimating an attribute of a reactant applied during performance of a process having multiple process parameters (MPPs) that is performed to control an amount of a pollutant emitted into the air, comprising:
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an interface configured to receive signals corresponding to attributes of the MPPs, including a signal corresponding to a measured current pH level of the applied reactant; one of a neural network process model and a non-neural network process model, the one model representing a relationship between the current pH level of the applied reactant and the attributes of the MPPs other than the measured current pH level of the applied reactant; and a processor configured with logic to estimate a current pH level of the applied reactant based on the attributes of the MPPs, other than the measured current pH level of the applied reactant, that correspond to the received signals and on the one model; wherein the one network process model is a dynamic neural or non-neural network process model which represents a relationship over time between the current pH level of the reactant and the applicable other attributes.
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9. A wet flue gas desulfurizing system, comprising:
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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 current 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 current pH level of the applied limestone slurry and an amount of SO2 in the received SO2 laden wet flue gas and an amount of SO2 in the exhausted desulfurized flue gas; a virtual analyzer having the logic to estimate the current pH level of the applied limestone slurry based on an actual amount of SO2 in the received SO2 laden wet flue gas, an actual amount of SO2 in the exhausted desulfurized flue gas and the one model; and a processor having the logic to compare the estimated current pH level of the applied limestone slurry with the measured current pH level of the applied limestone slurry, and to determine the validity of the measured current pH level of the applied limestone slurry based on the comparison. - View Dependent Claims (10)
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11. A selective catalytic reduction system, comprising:
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selective catalytic reducter 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 current 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 current amount of the ammonia in the exhausted reduced NOx flue gas and an actual amount of NOx in the received NOx laden flue gas and an actual amount of NOx in the exhausted reduced NOx flue gas; a virtual analyzer having the logic to estimate the current amount of ammonia in the exhausted reduced NOx flue gas based on the actual amount of NOx in the received NOx laden flue gas and the actual amount of NOx in the exhausted reduced NOx flue gas, and on the one model; and
a processor having the logic to compare the estimated current amount of ammonia in the exhausted reduced NOx flue gas with the measured current amount of ammonia in the exhausted reduced NOx flue gas, and to determine the validity of the measured current amount of ammonia in the exhausted reduced NOx flue gas based on the comparison. - View Dependent Claims (12)
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Specification