Flame instability detection and identification of unstable burners in industrial furnaces

Abstract

Systems and method for identifying an unstable subset of burners from among a plurality of burners in a furnace are also disclosed. At least one measurement is obtained from each of the plurality of burners. An instability associated with the furnace is detected. An unstable signal matrix associated with the instability is computed based on the at least one measurement from each of the plurality of burners. An unstable subset of burners is identified based at least in part on the unstable signal matrix.

What is claimed is: 
     
         1 . A method for identifying, in a furnace having a plurality of burners, an unstable subset of burners from among the plurality of burners, the method comprising:
 obtaining at least one measurement from each of a plurality of detectors;   detecting an instability associated with the furnace;   computing, using at least one processor, an unstable signal matrix associated with the instability based on the at least one measurement from each of the plurality of burners; and   identifying the unstable subset of burners based at least in part on the unstable signal matrix.   
     
     
         2 . The method of  claim 1 , wherein obtaining at least one measurement from each of a plurality of detectors comprises obtaining from each of the plurality of detectors a first measurement related to the plurality of burners when the furnace is operating in a stable condition, and obtaining from each of the plurality of detectors a second measurement related to the plurality of burners when the furnace is operating in an unknown state; and
 wherein detecting an instability associated with the furnace comprises:
 determining, based at least in part on the first measurement from each of the plurality of detectors, a stable signal component representation for the furnace; 
 determining, based at least in part on the second measurement from each of the plurality of detectors and the stable signal component representation, an unstable signal component representation for the furnace; and 
 detecting an instability in the furnace based at least in part on the unstable signal component representation and an instability threshold. 
   
     
     
         3 . The method of  claim 2 , wherein the plurality of detectors comprises a plurality of pressure sensors. 
     
     
         4 . The method of  claim 2 , wherein the plurality of detectors comprises a plurality of vibration sensors. 
     
     
         5 . The method of  claim 2 , wherein the plurality of detectors comprises a plurality of video sensors. 
     
     
         6 . The method of  claim 2 , wherein the stable signal component representation for the furnace comprises a stable covariance matrix. 
     
     
         7 . The method of  claim 2 , wherein the unstable signal component representation for the furnace comprises an instability component covariance. 
     
     
         8 . The method of  claim 7 , wherein the instability component covariance is calculated based on a stable covariance matrix and a current covariance matrix. 
     
     
         9 . The method of  claim 8 , wherein the current covariance matrix is calculated based on the stable covariance matrix and a vector of the second measurement from each of the plurality of burners. 
     
     
         10 . The method of  claim 2 , wherein the instability threshold is comapred against a detection test statistic. 
     
     
         11 . The method of  claim 10 , wherein the detection test statistic comprises a Neyman-Pearson detector. 
     
     
         12 . The method of  claim 10 , further comprising computing the detection test statistic based on an inverse of a stable covariance matrix. 
     
     
         13 . The method of  claim 10 , further comprising computing the detection test statistic based on an inverse of a current covariance matrix. 
     
     
         14 . The method of  claim 13 , wherein the inverse of the current covariance matrix is computed via matrix inversion lemma. 
     
     
         15 . The method of  claim 1 , wherein the unstable signal matrix comprises an instability component covariance. 
     
     
         16 . The method of  claim 1 , further comprising using eigenvalue composition of the unstable signal matrix to obtain at least one dominant eigenvector. 
     
     
         17 . The method of  claim 16 , wherein the at least one dominant eigenvector includes three components defining a point on a unit ball. 
     
     
         18 . The method of  claim 17 , further comprising clustering the point with a plurality of other points from a plurality of previous dominant eigenvectors. 
     
     
         19 . The method of  claim 18 , further comprising identifying the unstable subset of burners based on the clustering. 
     
     
         20 . The method of  claim 19 , wherein historical data is used to identifying the unstable subset of burners. 
     
     
         21 . The method of  claim 17 , further comprising recovering a Green's function vector from the at least one dominant eigenvector. 
     
     
         22 . The method of  claim 21 , wherein the at least one dominant eigenvector is normalized to obtain the Green's function vector. 
     
     
         23 . The method of  claim 1 , wherein the unstable subset of burners comprises a single burner. 
     
     
         24 . The method of  claim 1 , wherein the unstable subset of burners comprises a plurality of burners. 
     
     
         25 . The method of  claim 1 , wherein the unstable subset of burners comprises a group of burners containing at least one unstable burner. 
     
     
         26 . A system for identifying, in a furnace having a plurality of burners, an unstable subset of burners from among the plurality of burners, the system comprising:
 a plurality of detectors; and   a processor coupled to the plurality of burners and configured to:
 obtain at least one measurement from each of the plurality of detectors; 
 detect an instability associated with the furnace; 
 compute an unstable signal matrix associated with the instability based on the at least one measurement from each of the plurality of burners; and 
 identify the unstable subset of burners based at least in part on the unstable signal matrix. 
   
     
     
         27 . The system of  claim 26 , configured for use in accordance with any of the methods described in  claims 1  through  25 .