Enhanced method and apparatus for deducing a correct rail weight for use in rail wear analysis of worn railroad rails

Abstract

A system for identifying rail weights applicable to worn railroad rails measured along a railroad track system includes at least one track measurement device for recording at least a portion of a profile shape of the worn rails, and, a data processor running a software implement for accepting recorded data as input data from the at least one track measurement device and for processing the input data against known unworn railroad rail data to facilitate selection and application of the appropriate rail weights equated thereto to the worn railroad rails.

1 . A system for identifying rail weights applicable to worn railroad rails measured along a railroad track system comprising: 
 at least one track measurement device for recording at least a portion of a profile shape of the worn rails; and,    a data processor running a software implement for accepting recorded data as input data from the at least one track measurement device and for processing the input data against known unworn railroad rail data to facilitate selection and application of the appropriate rail weights equated thereto to the worn railroad rails.    
     
     
         2 . The system of  claim 1 , wherein the track measurement device uses image-capturing technology to record track data.  
     
     
         3 . The system of  claim 1 , wherein the track measurement device further includes audio emitting and capturing technology to record track data.  
     
     
         4 . The system of  claim 1 , wherein the appropriate rail weights are identified for use in rail wear measurement of the physical wear subjected to the worn rails.  
     
     
         5 . The system of  claim 1 , wherein the at least one-track measurement device is installed in a track measurement railcar.  
     
     
         6 . The system of  claim 1 , wherein the profile shape of the worn rails is a transverse cross-sectional view of the rail shape.  
     
     
         7 . The system of  claim 1 , wherein the software implement directs rail weight identification and rail wear calculation.  
     
     
         8 . The system of  claim 1 , wherein a profile shape of a rail comprises a set of geometric features applicable and identifiable to parts of the rail profile.  
     
     
         9 . The system of  claim 8 , wherein the geometric features include one of, all of, or a combination of web radius, fillet radius, profile height, head width, web width, or flange angle.  
     
     
         10 . The system of  claim 1 , wherein the unworn rail data comprises profile shapes of unworn rails, each profile including a set of geometric features making up the profile shape, the features applicable and identifiable to parts of the rail profiles.  
     
     
         11 . The system of  claim 10 , wherein the geometric features include one of, all of, or a combination of web radius, fillet radius, profile height, head width, web width, or flange angle.  
     
     
         12 . The system of  claim 4 , further including a data repository for storing calculated rail-wear data results along with geographic information and date and time information.  
     
     
         13 . A software implement for identifying rail weights applicable to worn railroad rails measured along a railroad track system comprising: 
 a feature extractor for extracting geometric features from recorded data of the worn rails; and    a rail weight classifier for comparing the extracted features to the same features of unworn rail shapes and for selecting an appropriate rail weight equated to an unworn rail shape for application to a worn rail.    
     
     
         14 . The software implement of  claim 13 , wherein the feature extractor combines geometric feature data produce a geometric vector.  
     
     
         15 . The software implement of  claim 14 , wherein the rail weight classifier compares the geometric vector against a store of geometric vectors previously created for unworn railroad rails.  
     
     
         16 . The software implement of  claim 13 , wherein the geometric features derive from captured image data.  
     
     
         17 . The software implement of  claim 13 , wherein the geometric features derive from captured audio data.  
     
     
         18 . The software implement of  claim 13 , further comprising a preprocessor for creating X,Y coordinate pairs for feature extraction.  
     
     
         19 . The software implement of  claim 13 , further comprising a post processor for validating identified rail weights applied to worn rails against a set of business rules.  
     
     
         20 . The software implement of  claim 13 , further comprising a rail wear calculator for calculating the correct amount of wear subject to a worn rail compared to an unworn rail of the same identified rail weight.  
     
     
         21 . A method for identifying a correct a rail weight for a worn rail profile given data recorded from the worn rail by a track measurement system including steps of: 
 (a) identifying geometric features of the worn rail profile;    (b) unifying the identified features as a single feature vector;    (c) comparing the single feature vector to one or more similarly constructed feature vectors previously stored for comparison, the previously stored feature vectors representing unworn rail profiles; and    (d) selecting a feature match of that of a worn rail profile to that of an unworn rail profile.    
     
     
         22 . The method of  claim 21 , wherein in step (a), the geometric features of the worn rail profile include one of, all of, or a combination of web radius, fillet radius, profile height, head width, web width, or flange angle.  
     
     
         23 . The method of  claim 21 , wherein in step (a), the geometric features are derived from image data captured from a worn rail.  
     
     
         24 . The method of  claim 21 , wherein in step (a), the geometric features are expressed as a set of X,Y coordinate pairs.  
     
     
         25 . The method of  claim 21 , wherein in step (a), the geometric features are discernible from one another using linear or quadratic discriminant analysis.  
     
     
         26 . The method of  claim 21 , wherein in step (b), the single feature vector contains the data from all of the unified features considered in creating the vector.  
     
     
         27 . The method of  claim 21 , wherein in step (d), if there is no match accomplished to a previously stored feature vector, an indication of match to a rail weight not known to the system is returned.  
     
     
         28 . The method of  claim 21 , wherein in step (a), the identified geometric features are adjusted to correct for a detected angle of cant of the worn rail.  
     
     
         29 . The method of  claim 21 , further including a step (e) upon obtaining a match in step (d) wherein the resulting data of the match is input into a rail wear calculator.  
     
     
         30 . In a system for identifying rail weights applicable to worn railroad rails measured along a railroad track system, a method for correcting a worn rail profile for an angle of cant comprising steps of: 
 (a) detecting the existence of cant attributed to a web portion of the rail profile;    (b) retrieving a sample of any like web portion of an unworn rail aligned to true vertical;    (c) cross-correlating the web portion of the worn rail to the web portion of the unworn rail;    (d) identifying the direction of cant of the worn rail against the unworn rail;    (e) rotating the web portion of the worn rail a number of increments of angle opposite the cant direction; and    (f) accepting as a correction angle, the sum of rotation increments required to obtain a least discrepant match in cross-correlation to the symmetry of the web portion of the unworn rail profile.    
     
     
         31 . The method of  claim 30 , wherein in step (a), the worn rail profile is described by a set of X,Y coordinate pairs.  
     
     
         32 . The method of  claim 30 , wherein in step (a), more than one worn rail profile is considered for cant correction along a same track section.  
     
     
         33 . The method of  claim 30 , wherein in step (b), the sample is retrieved from a repository previously stored unworn rail profiles.  
     
     
         34 . The method of  claim 30 , wherein in step (c), cross-correlation considers vertical symmetry.  
     
     
         35 . The method of  claim 30 , wherein in step (c), cross-correlation considers horizontal symmetry.  
     
     
         36 . The method of  claim 30 , wherein in step (c), cross-correlation is two-dimensional.  
     
     
         37 . The method of  claim 30  further including a step (g) for estimating height of the worn rail profile.  
     
     
         38 . The method of  claim 30 , wherein in step (f), a least discrepant match considers the best equation for a line of symmetry of the worn rail profile considering the minimum distance equalities of like geometric features located on either side of the line of symmetry in cross-correlation.  
     
     
         39 . The method of  claim 21  wherein, in step (d), selection is based on pattern recognition results.  
     
     
         40 . The method of  claim 39  wherein pattern recognition is based on linear or quadratic discriminant techniques and associated rules.  
     
     
         41 . The method of  claim 39  wherein pattern recognition is based on use of a decision tree.  
     
     
         42 . The system of  claim 1  wherein processing includes statistical comparison.  
     
     
         43 . The software implement of  claim 13  wherein the method for comparing is statistical comparison.  
     
     
         44 . The method of  claim 21  wherein in step (c), the method for comparing is statistical comparison.