NEW06 TraCIM Deliverable D 1.1.1 TraCIM DATABASE Traceability for computationally-intensive metrology TOTAL DOMAIN Domains 7 Applications 20 Aims 79 Length Chemistry Electricity and Magnetism Temperature Mass Radiometry Interdisciplinary metrology AIMS 46 8 5 2 4 1 13 Similar applications No Partner Domain Application Aim 1 NPL Length Surface metrology Profile roughness parameters 2 NPL Length Surface metrology Form removal 3 NPL Length Surface metrology Filtering 4 NPL Length Dimensional Metrology 5 NPL Chemistry Chemometrics 6 7 NPL NPL Chemometrics Chemometrics 8 NPL 9 NPL Chemistry Chemistry Electricity and Magnetism Thermometry 10 NPL Thermometry Temperature 11 NPL 12 NPL 13 NPL 14 NPL 15 NPL Interdisciplinary metrology Interdisciplinary metrology Interdisciplinary metrology Interdisciplinary metrology Interdisciplinary metrology Bundle adjustment Description Priority criterion A = Lest squares, Gauss, Bestfit B = Surface/profile roughness C = Chebyschev fit D = Interlaboratory comparison Selection B Photogrammetry, laser trackers, multilateration, iGPS Principle components analysis/regression Partial least squares Subset selection algorithms Power generation State estimation algorithms Temperature Calibration of PRTs Definition of practical temperature scale Regression Calibration functions Regression Linear least squares Regression Nonlinear least squares Regression Robust regression Uncertainty evaluation LPU/GUM Editors: Vít Zelený, Ivana Linkeová (Czech Metrology Institute) Various uncertainty structures Law of propagation of uncertainty 1/6 NEW06 TraCIM Deliverable D 1.1.1 TraCIM DATABASE Traceability for computationally-intensive metrology Similar applications No Partner Domain Application NPL Interdisciplinary metrology Interdisciplinary metrology Interdisciplinary metrology Mass Uncertainty evaluation Uncertainty evaluation Uncertainty evaluation Mass calibration 20 NPL Mass Calibration of pressure balances 21 PTB Length 22 PTB Length 23 PTB Length 16 NPL 17 NPL 18 NPL 19 Coordinate Metrology Coordinate Metrology Coordinate Metrology Aim Description MCM/GUMS1 Monte Carlo method MCMC Marko chain Monte Carlo Priority criterion Analysis of interlaboratory comparisons Least-squares fit Chebyshev fit Involute gear inspection A = Lest squares, Gauss, Bestfit B = Surface/profile roughness C = Chebyschev fit D = Interlaboratory comparison Selection D Best-Fit for standard elements (2D and 3D) Best-Fit for standard elements (2D and 3D) Profile, helix, pitch SW-manufacturers/end users SW-manufacturers/end users SW-manufacturers/end users SW-manufacturers/end users 24 PTB Length 25 PTB Electricity and Magnetism Surface roughness Surface Metrology parameters HF measuring Calibration algorithms techniques Calculate surface roughness parameters Caclulate HF scattering NMIs, manufacturers parameters Calculation of key comparison reference values, En-values and General metrology NMIS other interesting parameter 26 PTB Interdisciplinary metrology Intercomparison on CMC level BIPM metrology 27 PTB Interdisciplinary metrology Intercomparison on calibration laboratory level Calibration service En-values General metrology calibration services 28 PTB Interdisciplinary metrology all General Noise reduction Spline filter, RC filter, Gausian filter, and other 29 PTB Interdisciplinary metrology 30 CMI Length 31 UM Mass A C B D Mean, standard deviation, regression, etc. Calculate profile characteristics Surface metrology Free-form profile parameters Desire from end-users of free-form surface Recognition of particle position in Flow: PIV-particle Checking SW for flow Desire from an image and vealocity image velocimetry velocity evaluation end-users calculation all General statistics Editors: Vít Zelený, Ivana Linkeová (Czech Metrology Institute) 2/6 NEW06 TraCIM Deliverable D 1.1.1 TraCIM DATABASE Traceability for computationally-intensive metrology Similar applications No Partner Domain Application Aim 32 UM Mass Tension and compression Checking SW for material measurements on priperties evaluation different materials 33 VSL Length Dimensional Metrology Least-squares fit simple geometric elements 34 VSL Length Dimensional Metrology Chebyshev fit simple geometric elements 35 VSL Length Dimensional Metrology Least-squares fit aspheric and free-form lenses 36 VSL Length Dimensional Metrology Chebyshev fit aspheric and free-form lenses 37 VSL Length Dimensional Metrology Least-squares fit gears 38 VSL Length Dimensional Metrology Chebyshev fit gears 39 VSL Length Dimensional Metrology Least-squares fit quadric surfaces 40 VSL Length Dimensional Metrology Chebyshev fit quadric surfaces Editors: Vít Zelený, Ivana Linkeová (Czech Metrology Institute) Description Calculation of material proiperties (tensile strength, compressive strength, plasticity etc.) based on force and extension measurements Calculate parameters of best fit simple geometric elements, with lowest RMS value. Calculate parameters of best fit simple geometric elements, with lowest PV value. Calculate best fit position and orientation of nominal lens form to measurement data, with lowest RMS value. Calculate best fit position and orientation of nominal lens form to measurement data, with lowest PV value. Calculate best fit position and orientation of nominal gear form to measurement data, with lowest RMS value. Calculate best fit position and orientation of nominal gear form to measurement data, with lowest PV value. Calculate best fit position and orientation of nominal surface form to measurement data, with lowest RMS value. Calculate best fit position and orientation of nominal surface form to measurement data, with lowest PV value. Priority criterion A = Lest squares, Gauss, Bestfit B = Surface/profile roughness C = Chebyschev fit D = Interlaboratory comparison Selection Desire from end-users (many different testing machine producers - at least 20) Interest of CMMsoftware manufacturers A Interest of CMMsoftware manufactures C Interest of CMMsoftware manufactures A Interest of CMMsoftware manufactures C Interest of CMMsoftware manufactures A Interest of CMMsoftware manufactures C Interest of CMMsoftware manufactures A Interest of CMMsoftware manufactures C 3/6 NEW06 TraCIM Deliverable D 1.1.1 TraCIM DATABASE Traceability for computationally-intensive metrology Similar applications No Partner Domain Application Aim 41 VSL Length Dimensional Metrology Least-squares fit NURBS surfaces 42 VSL Length Dimensional Metrology Chebyshev fit NURBS surfaces 43 VSL Length 44 VSL Description Calculate best fit position and orientation of nominal surface form to measurement data, with lowest RMS value. Calculate best fit position and orientation of nominal surface form to measurement data, with lowest PV value. Priority criterion A = Lest squares, Gauss, Bestfit B = Surface/profile roughness C = Chebyschev fit D = Interlaboratory comparison Interest of CMMsoftware manufactures A Interest of CMMsoftware manufactures C Dimensional Metrology Calculate best fit of parametrized Interest of CMMLeast-squares fit parameters surface form to measurement quadric surfaces software manufactures data, with lowest RMS value. A Length Dimensional Metrology Chebyshev fit parameters quadric surfaces Calculate best fit of parametrized Interest of CMMsurface form to measurement software manufactures data, with lowest PV value. C 45 VSL Length Surface roughness Surface Metrology parameters 46 VSL Length Surface Metrology Step height 47 VSL Length Surface Metrology Line width 48 VSL Length Surface Metrology Side wall angle 49 VSL Length Surface Metrology Side wall roughness 50 VSL Chemistry Gas Chromatography 51 VSL Chemistry Cavity Ring Down Exponential decay time Spectroscopy Peak area Editors: Vít Zelený, Ivana Linkeová (Czech Metrology Institute) Calculate surface roughness parameters Interest of surface rouhgness measurement device manufacturers (?) Selection B Calculate step height for AFM measurement data Calculate line width for AFM measurement data Calculate side wall angle for AFM measurement data Calculate side wall roughness for AFM measurement data Interest of VSL chemistry department and possibly manufacturers of GCs. Interest of VSL chemistry department Calculate exponential decay time and possibly including uncertainty. manufacturers of gas monitors. Calculate gas chromatograph peak area, based on different definitions of peak area. 4/6 NEW06 TraCIM Deliverable D 1.1.1 TraCIM DATABASE Traceability for computationally-intensive metrology Similar applications No Partner Domain Application Aim Description Priority criterion VSL Chemistry Spectroscopy general 53 VSL Chemistry Calibration curves - Orthogonal distance ODR regression 54 VSL Chemistry Calibration curves Fit polynomial polynomial fit Calculate best fit polynomial (vertical least squares) 55 VSL Electricity and Magnetism Mains frequency Calculate four parameter sine fit NMIs, manufacturers for power and energy meters 56 VSL Electricity and Magnetism Power quality - frequency spectrum Calculate spectrum of mains electrical power 57 VSL Electricity and Magnetism Mains power frequency Power quality frequency spectrum Vector Network Analyzer 58 VSL Radiometry Radiometry color-coordinates, color temperatures 59 VSL Interdisciplinary metrology Flow ISO and AGA norms 60 HEX Length 61 HEX Length 62 HEX Length 63 HEX Length 64 HEX Length Dimensional Metrology Dimensional Metrology Dimensional Metrology Dimensional Metrology Dimensional Metrology Calibration algorithms Verify calculations of VNA calibration Calculate color-coordinates and temperatures, correlated color temperature, color quality indices, etc. Calculate density, calorific value, flow rate, etc. Used in many applications. NMIs, manufacturers NMIs, manufacturers NMIs Flow computer manufacturers Transformation Gauss-Fit for 3D-profiles A Transformation Chebyshev-Fit for 3D-profiles C Max/Min-Deviation Transformation ISO-Element Editors: Vít Zelený, Ivana Linkeová (Czech Metrology Institute) Selection Interest of VSL Calculate best fit of data base chemistry department measurement data to measured and possibly spectrum manufacturers of gas monitors. Calculate best fit curve (line) in Used in many orthogonal distance regression applications. sense. 52 Fit peaks to spectrum A = Lest squares, Gauss, Bestfit B = Surface/profile roughness C = Chebyschev fit D = Interlaboratory comparison Actual-Nominal Comparison for 3D-Profiles Best-Fit for standard elements (2D and 3D) Form calculation for Torus, Sphere, Roundness SW-manufacturers/end users A 5/6 NEW06 TraCIM Deliverable D 1.1.1 TraCIM DATABASE Traceability for computationally-intensive metrology Similar applications No Partner Domain Application 65 Werth Length Dimensional Metrology 66 WHZ Length Coordinate Metrology 67 WHZ Length Coordinate Metrology 68 ZEISS Length 69 ZEISS Length 70 ZEISS Length 71 ZEISS Length 72 ZEISS Length 73 ZEISS Length 74 ZEISS Length 75 ZEISS Length 76 ZEISS Length 77 ZEISS Length 78 ZEISS Length 79 ZEISS Length Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Coordinate Metrology Aim Assignement of standard forms Description Priority criterion A = Lest squares, Gauss, Bestfit B = Surface/profile roughness C = Chebyschev fit D = Interlaboratory comparison Evaluation of the calculation of distances and position of Requiered by customers different standard form elements Parameters of miminum zoneCalculation of contact points and , maximum inscribed- and points with predefined deviations minimum circumscribed elements Form and tolerance Calculation of contact points and assesment for multi points with predefined deviations component features C Circle 3D Orthogonal distance regression Desire from end-users A, C Cone Orthogonal distance regression Desire from end-users A, C Cylinder Orthogonal distance regression Desire from end-users A, C Hexagon 3D Orthogonal distance regression Desire from end-users A, C Plane Orthogonal distance regression Desire from end-users A, C Line 3D Orthogonal distance regression Desire from end-users A, C Rectangle 3D Orthogonal distance regression Desire from end-users A, C Line 3D Orthogonal distance regression Desire from end-users A, C Sphere Orthogonal distance regression Desire from end-users A, C Step cylinder Orthogonal distance regression Desire from end-users A, C Symmetry plane Orthogonal distance regression Desire from end-users A, C Torus Orthogonal distance regression Desire from end-users A, C Editors: Vít Zelený, Ivana Linkeová (Czech Metrology Institute) Selection 6/6
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