Signal Processing and Analysis Techniques for Nuclear Quadrupole Resonance Spectroscopy

✍ Scribed by Cristian Monea · Nicu Bizon

• Year: 2022
• Tongue: English
• Leaves: 190
• Category: Library

✦ Table of Contents

Foreword
Preface
Contents
Abbreviations
1 Introduction
1.1 Context of This Work
1.2 Purpose of This Work
1.3 Structure of This Work
References
2 Methods and Equipment for Signal Acquisition and Analysis for the Detection of Prohibited Substances
2.1 Signal Detection and Estimation Theory
2.2 Techniques for Detecting Prohibited Substances
2.2.1 Trace Detection Techniques
2.2.2 Bulk Detection Techniques
2.3 Conclusions
References
3 Nuclear Quadrupole Resonance Spectroscopy
3.1 The Principle of Nuclear Quadrupole Resonance
3.2 Signal Acquisition Methods Applied in Nuclear Quadrupole Resonance Spectroscopy
3.3 Equipment Used in Nuclear Quadrupole Resonance Spectroscopy
3.4 Conclusions
Appendix
NQR Data for Different Substances
References
4 Signal Processing and Analysis Techniques Applied in Nuclear Quadrupole Resonance
4.1 Classification of the Signal Processing Techniques
4.2 Pre-Processing Techniques
4.2.1 Signal Averaging
4.2.2 Quadrature Detection
4.3 Post-Processing and Analysis Techniques
4.3.1 Single Channel Detection Techniques
4.3.2 Multi-channel Detection Techniques
4.4 Future Research Directions
4.5 Conclusions
Appendix
Signal Processing and Analysis Techniques Classification
Signal Post-Processing and Analysis Techniques Development Timeline
Development of the Post-Processing Techniques
Distribution of the Post-Processing Techniques According to the Type of Detection [1]
References
5 Modeling of Signals Used in Nuclear Quadrupole Resonance Spectroscopy
5.1 Free Induction Decay Models
5.2 Echo Train Models
5.3 Proposal of a New Echo Model
5.4 Noise Models
5.5 Conclusions
References
6 Study of the NQR Signal Processing and Analysis Algorithms
6.1 Description of the Algorithms Chosen for the Analysis
6.2 Proposal of a Multi-criteria Detection Algorithm
6.3 Comparative Analysis of the Signal Processing and Signal Analysis Algorithms
6.3.1 Analysis Procedure and Performance Indicators
6.3.2 Implementation of Comparative Analysis
6.3.3 Comparative Analysis Results
6.4 Conclusions
Appendix
References
7 Analysis of Nuclear Quadrupole Resonance Response Signals
7.1 Description of the Analyzed Signals
7.2 Defining the Signal Features
7.3 Statistical Analysis of Data
7.4 Conclusions
Appendix
Signal Acquisitions in Different Scanning Scenarios
Statistical Analysis of the Data Set
References
8 Development of Signal Analysis Algorithms for NQR Detection
8.1 Selection of the Investigated Algorithms
8.2 Implementation of the Signal Analysis Algorithms
8.3 Training and Evaluation of the Signal Analysis Algorithms
8.4 Optimization of the Proposed Algorithm
8.5 Conclusions
Appendix
Source Code of the Functions Used to Generate the Deep Learning Models
Learning Curves for the Developed Algorithms
AlexNet Model Optimization Results
References
9 Solutions to Improve NQR Detection
9.1 Generalization of the Optimized Algorithm Using Transfer Learning
9.2 Noise Reduction Using Autoencoders
9.3 Conclusions
Appendix
Source Code of the Functions Used to Generate the Autoencoder Models
References
10 Implementation of a Signal Pre-processing, Processing and Analysis System for Nuclear Quadrupole Resonance
10.1 Hardware Implementation of the Detection System
10.2 Software Implementation of the Detection System
10.2.1 Embedded System Firmware
10.2.2 Embedded System Interface
10.2.3 Spincore Module Interface
10.2.4 Database Interface
10.2.5 Interface with External Applications
10.2.6 Application Core
10.2.7 Graphical User Interface
10.2.8 Implementation of the Detection Application
10.3 Evaluation of the Detection System
10.3.1 Evaluation of the Radio Frequency Switch
10.3.2 Detection Limits
10.3.3 Ferrite Core Improvement
10.3.4 Evaluation of the Signal-to-Noise Ratio
10.4 Conclusions
References