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| موضوع: كتاب Computational Surface and Roundness Metrology الإثنين 05 سبتمبر 2016, 9:27 pm | |
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أخوانى فى الله أحضرت لكم كتاب Computational Surface and Roundness Metrology Bala Muralikrishnan, Jay Raja
ويتناول الموضوعات الأتية :
Contents Notation xix 1 Introduction 1 1.1 Surface and Roundness Metrology 1 1.2 Scope and Objectives 1 1.3 Organization 3 References 4 Part I Filtering 2 A Brief History of Filtering 7 2.1 Introduction 7 2.2 Electrical Filters 7 2.3 Digital Filters 8 2.4 The Envelope Method 8 2.5 The Gaussian Filter 8 2.6 Overlap of Measurement Techniques 9 2.7 Recent Advances in Filtering 9 2.8 Summary 10 References 10 3 Filtering in the Frequency Domain 13 3.1 Surface Wavelengths 13 3.2 Fourier Transform, Discrete Fourier Transform, and Fast Fourier Transform 14 3.3 Filtering in the Frequency Domain 16 3.4 Wrap-Around Effect 19 3.5 Amplitude Transmission and Phase Characteristics 19 3.6 Summary 20 Exercises 20 References 21 xixii Contents 4 Filtering in the Time Domain 23 4.1 Filtering as an Averaging Process 23 4.2 Relationship Between Frequency-Domain and Time-Domain Filtering 26 4.3 Filtering Profiles: Putting It All Together 27 4.4 Summary 29 Exercises 30 References 31 5 Gaussian Filter 33 5.1 Introduction 33 5.2 High-Pass and Low-Pass Filters 35 5.3 Roughness, Waviness, and Form Using the Gaussian Filter 35 5.4 Effect of Cutoff 36 5.5 Phase Characteristics 36 5.6 Summary 37 Exercises 37 References 38 6 The 2RC Filter 39 6.1 Introduction 39 6.2 The 2RC High-Pass Filter 39 6.3 More on the 2RC Filter 42 6.4 Comparison of the 2RC and Gaussian Filters 44 6.5 Summary 44 Exercises 45 References 46 7 Filtering Roundness Profiles 47 7.1 Introduction 47 7.2 Gaussian Filter for Roundness 47 7.3 Amplitude Transmission Characteristics 49 7.4 Filtering Roundness Profiles in the Time Domain 50 7.5 Circular Convolution in the Frequency Domain 50 7.6 Summary 52 Exercises 52 References 53 8 Filtering 3D Surfaces 55 8.1 Areal Surface Texture Analysis 55 8.2 2D Convolution 55 8.3 Gaussian Filter in 3D 56 8.4 A Note on Indices 56 8.5 Frequency-Domain Filtering in 3D 59 8.6 Summary 62 Exercises 62 References 63Contents xiii Part II Advanced Filtering 9 Gaussian Regression Filters 67 9.1 Introduction 67 9.2 Zero-Order Gaussian Regression Filter 68 9.3 Second-Order Gaussian Regression Filter 71 9.4 3D Zero-Order Gaussian Regression Filter 73 9.5 3D Second-Order Gaussian Regression Filter 74 9.6 Summary 75 Exercises 75 References 76 10 Spline Filter 77 10.1 Introduction 77 10.2 Amplitude Transmission Characteristics 78 10.3 Implementation of the Non-periodic Spline Filter 79 10.4 Implementation of the Periodic Spline Filter 82 10.5 Summary 86 Exercises 86 References 86 11 Robust Filters 87 11.1 Rk Filter 87 11.2 Robust Gaussian Regression Filter 90 11.3 Summary 91 Exercises 92 References 92 12 Envelope and Morphological Filters 93 12.1 Envelope Filters 93 12.2 Stylus Tip Convolution 94 12.3 Morphological Filters 96 12.4 A Word on the Fundamentals 98 12.5 3D Morphological Filtering 98 12.6 Summary 100 Exercises 100 References 101 13 Multi-scale Filtering 103 13.1 Introduction 103 13.2 Alternate Sequence Filters or Scale Space Analysis 103 13.3 Wavelet-Based Filters 107 13.4 Summary 109 Exercises 110 References 111xiv Contents Part III Fitting 14 Introduction to Fitting Substitute Geometry 115 14.1 Introduction 115 14.2 Fitting Criteria 116 14.3 Solution Methodologies 117 References 118 15 Least-Squares Best-Fit Line and Plane 121 15.1 Introduction 121 15.2 Closed-Form Solution for LS Best-Fit Line 121 15.3 Matrix Formulation 122 15.4 Centroid as a Point on the LS Line 123 15.5 Normal LS in Parametric Form 124 15.6 Lagrange Multiplier Method 126 15.7 Back to the LS Line 127 15.8 LS Best-Fit Plane 128 15.9 Summary 129 Exercises 129 References 130 16 Non-linear Least-Squares I: Introduction 131 16.1 Introduction 131 16.2 Formulating the Circle in a Plane Problem 131 16.3 The Steepest Descent Algorithm 132 16.4 The Gauss–Newton Algorithm 134 16.5 The Levenberg–Marquardt Algorithm 136 16.6 Summary 137 Exercises 138 References 138 17 Non-linear Least-Squares II: Circle, Sphere, and Cylinder 139 17.1 Introduction 139 17.2 Initial Estimates for Center and Radius of Circle 139 17.3 Best-Fit Sphere 142 17.4 Best-Fit Cylinder 143 17.5 Summary 144 Exercises 144 References 144 18 Fitting Radius-Suppressed Circle Data 145 18.1 Introduction 145 18.2 The Limaçon Approximation 145 18.3 LS Best-Fit Circle 146 18.4 LS Best-Fit Cylinder 148 18.5 Errors in the Limaçon Approximation 149Contents xv 18.6 Summary 150 Exercises 151 References 151 19 Exchange Algorithms for Minimum Zone 153 19.1 Introduction 153 19.2 Exchange Algorithms 153 19.3 Exchange Algorithm for Line 154 19.4 Exchange Algorithm for Plane 157 19.5 Exchange Algorithm for Circle 159 19.6 Summary 162 Exercises 163 References 163 20 Reference Circle-Fitting Using Linear Programming Simplex 165 20.1 Introduction 165 20.2 LP Simplex 165 20.3 Formulating the MI Problem 167 20.4 Formulating the MC Problem 171 20.5 Duality 172 20.6 LP and Exchange Algorithms 174 20.7 Exchange Algorithms for MI and MC Circles 176 20.8 Summary 176 Exercises 176 References 177 Part IV Parameterization 21 Surface Finish Parameters I: Amplitude, Spacing, Hybrid, and Shape 181 21.1 Introduction 181 21.2 Amplitude Parameters 181 21.3 Spacing Parameters 183 21.4 Hybrid and Shape Parameters 186 21.5 Summary 188 Exercises 189 References 190 22 Surface Finish Parameters II: Autocorrelation, Power Spectral Density, Bearing Area 191 22.1 Autocovariance and Autocorrelation Function 191 22.2 Power Spectral Density 193 22.3 Amplitude Density Function and Bearing Area Curve 195 22.4 Summary 198 Exercises 199 References 199xvi Contents 23 3D Surface Texture Parameters 201 23.1 Introduction 201 23.2 Amplitude and Shape Parameters 201 23.3 AACV, APSD, and BAC for 3D Surfaces 202 23.4 Spacing and Hybrid Parameters 205 23.5 Summary 206 Exercises 206 References 206 Part V Errors and Uncertainty 24 Uncertainty Considerations 209 24.1 Introduction 209 24.2 Random and Systematic Components 209 24.3 Uncertainty Modeling 210 24.4 Uncertainty Propagation 210 24.5 Systematic Errors: an Example 210 References 211 25 Uncertainty Propagation in Computations 213 25.1 Introduction 213 25.2 Intervals at Some Level of Confidence 214 25.3 The Central Limit Theorem 215 25.4 Limitations of GUM 217 25.5 The Monte Carlo Method 217 25.6 Filtering Surface Profiles 218 25.7 Fitting Substitute Geometry 221 25.8 Summary 223 Exercises 224 References 224 26 Error Separation Techniques in Roundness Metrology 225 26.1 Introduction 225 26.2 Full Reversal 225 26.3 Two-Position Method 226 26.4 Two-Probe Method 229 26.5 Three-Probe FFT Method 229 26.6 Three-Probe Sequential Method 231 26.7 Three-Position FFT Method 233 26.8 Error Separation by Solving Linear Equations 234 26.9 Uncertainty Propagation 236 26.10 Summary 236 Exercises 236 References 237Contents xvii 27 Other Relevant Topics 239 27.1 Introduction 239 27.2 Parameter Extraction 239 27.3 Tools for Correlation and Diagnostics 240 27.4 Challenges 241 References 241 Answers to Selected Exercises 243 Index
أتمنى أن تستفيدوا منه وأن ينال إعجابكم رابط تنزيل كتاب Computational Surface and Roundness Metrology- Bala Muralikrishnan, Jay Raja
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