Process parameter estimation in controlling emission of a non-particulate pollutant into the air
First Claim
1. A parameter value estimator for a process primarily performed to control emission of a particular non-particulate pollutant into the air, the process having multiple process parameters (MPPs) including a parameter representing an amount of the particular non-particulate pollutant emitted, comprising:
- one of a neural network process model and a non-neural network process model representing a relationship between one of the MPPs, other than the parameter representing the amount of the emitted particular non-particulate pollutant, and one or more of the other MPPs; and
a processor configured with the logic to estimate a value of the one MPP based on a value of each of the one or more other MPPs and the one model;
wherein the one MPP is either (i) a pH level of matter applied in the process to absorb the particular nonparticulate pollutant and thereby control its emission into the air, (ii) a purity of a by-product produced in performing the process, (iii) an amount of oxygen dissolved in matter applied in the process to absorb the particular non-particulate pollutant and thereby control its emission into the air, (iv) an amount of ammonia applied in the process to absorb the particular non-particulate pollutant that is emitted into the air with the particular non-particulate pollutant that is not absorbed, or (v) an amount of applied ammonia in exhausted reduced NOx flue gas, the particular non-particulate pollutant being NOx, and the one or more other MPPs include an amount of the applied ammonia.
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Abstract
A parameter value estimator is provided for a process performed primarily to control emission of a particular non-particulate pollutant, such as NOx and SO2, into the air. The process has multiple process parameters (MPPs) including a parameter representing an amount of the particular non-particulate pollutant emitted. The parameter value estimator includes either a neural network process model or a non-neural network process model. In either case the model represents a relationship between one of the MPPs, other than the parameter representing the amount of the emitted particular non-particulate pollutant, and one or more other of the MPPs. Also included is a processor configured with the logic, e.g. programmed software, to estimate a value of the one MPP based on a value of each of the one or more other MPPs and the one model.
76 Citations
21 Claims
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1. A parameter value estimator for a process primarily performed to control emission of a particular non-particulate pollutant into the air, the process having multiple process parameters (MPPs) including a parameter representing an amount of the particular non-particulate pollutant emitted, comprising:
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one of a neural network process model and a non-neural network process model representing a relationship between one of the MPPs, other than the parameter representing the amount of the emitted particular non-particulate pollutant, and one or more of the other MPPs; and a processor configured with the logic to estimate a value of the one MPP based on a value of each of the one or more other MPPs and the one model; wherein the one MPP is either (i) a pH level of matter applied in the process to absorb the particular nonparticulate pollutant and thereby control its emission into the air, (ii) a purity of a by-product produced in performing the process, (iii) an amount of oxygen dissolved in matter applied in the process to absorb the particular non-particulate pollutant and thereby control its emission into the air, (iv) an amount of ammonia applied in the process to absorb the particular non-particulate pollutant that is emitted into the air with the particular non-particulate pollutant that is not absorbed, or (v) an amount of applied ammonia in exhausted reduced NOx flue gas, the particular non-particulate pollutant being NOx, and the one or more other MPPs include an amount of the applied ammonia. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. An article of manufacture for estimating a parameter value for a process performed primarily to control emission of a particular non-particulate pollutant into the air, the process having multiple process parameters (MPPs) including a parameter representing an amount of the particular non-particulate pollutant emitted, comprising:
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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; detemine a value of each of one or more of the MPPs; and estimate a value of another one of the MPPs, other than the parameter representing the amount of the emitted particular non-particulate pollutant, based on (i) the determined value of each of the one or more MPPs and (ii) one of a neural network process model and a non-neural network process model representing a relationship between the one other MPP and the one or more MPPs; wherein the one other MPP is either (i) a pH level of matter applied in the process to absorb the particular non-particulate pollutant and thereby control its emission into the air, (ii) a purity of a by-product produced in performing the process, (iii) an amount of oxygen dissolved in matter applied in the process to absorb the particular non-particulate pollutant and thereby control its emission into the air, (iv) an amount of ammonia applied in the process to absorb the particular non-particulate pollutant that is emitted into the air with the particular non-particulate pollutant that is not absorbed, or (v) an amount of applied ammonia in exhausted reduced NOx flue gas, the particular non-particulate pollutant being NOx, and the one or more MPPs include an amount of the applied ammonia. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21)
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Specification