Smart sensors and MEMS intelligent devices and microsystems for industrial applications

Smart Sensors and MEMS: Intelligent Devices and Microsystems for Industrial Applications, Second Edition highlights new, important developments in the field, including the latest on magnetic sensors, temperature sensors and microreaction chambers. The book outlines the industrial applications for sm...

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Detalles Bibliográficos
Otros Autores:	Nihtianov, S, author (author), Nihtianov, Stoyan, editor (editor), Luque, Antonio, editor
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Duxford, England : Woodhead Publishing 2018.
Edición:	Second edition
Colección:	Woodhead Publishing series in electronic and optical materials.
Materias:	Detectors > Industrial applications. Microelectromechanical systems > Industrial applications.
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627774706719

Tabla de Contenidos:

Front Cover
Smart Sensors and MEMS
Related titles
Smart Sensors and MEMS
Copyright
Contents
List of Contributors
1 - What makes sensor devices and microsystems "intelligent" or "smart"?
1.1 Introduction
1.2 Interpretation of terms related to sensors
1.2.1 About the term "sensor"
1.2.2 Definitions of key terms related to devices with elements of artificial intelligence
1.3 Key trends in the development of sensors (sensor devices) and microelectromechanical systems
1.3.1 The method of analogy
1.3.2 Complication of organisms and sensors as a tendency of evolution
1.3.3 Features and forms of intelligence
1.4 Suggestions for improving terminology in the field of sensors and microelectromechanical systems
1.5 Conclusion
Acknowledgment
References
2 - Interfacing sensors to microcontrollers: a direct approach
2.1 Introduction
2.2 Sensors
2.2.1 Resistive sensors
2.2.1.1 Single resistive sensor
2.2.1.2 Differential resistive sensor
2.2.1.3 Bridge-type resistive sensor
2.2.2 Capacitive sensors
2.2.2.1 Single capacitive sensor
2.2.2.2 Lossy capacitive sensor
2.2.2.3 Differential capacitive sensor
2.2.2.4 Bridge-type capacitive sensor
2.3 Microcontrollers
2.3.1 General description
2.3.2 Time-interval measurement
2.4 Interface circuits
2.4.1 Operating principle
2.4.2 Circuits for resistive sensors
2.4.2.1 Single resistive sensor
2.4.2.2 Differential resistive sensor
2.4.2.3 Bridge-type resistive sensor
2.4.3 Circuits for capacitive sensors
2.4.3.1 Single capacitive sensor
2.4.3.2 Lossy capacitive sensor
2.4.3.3 Differential capacitive sensor
2.4.3.4 Bridge-type capacitive sensor
2.5 Applications
2.5.1 Temperature measurement
2.5.2 Position measurement
2.5.3 Magnetic field measurement.
2.5.4 Relative humidity measurement
2.5.5 Tilt measurement
2.5.6 Other applications
2.6 Future trends
Sources of further information and advice
References
3 - Smart temperature sensors and temperature sensor systems
3.1 Introduction
3.2 Measuring temperature, temperature differences, and temperature changes in industrial applications
3.3 Temperature-sensing elements
3.3.1 Introduction
3.3.2 Temperature sensor characteristics of bipolar junction transistors
3.3.3 ΔVBE temperature sensors
3.3.4 Bipolar junction transistors in complementary metal-oxide semiconductor (CMOS) technology
3.4 Basic concepts of smart temperature sensors
3.4.1 Architectures of smart temperature sensor systems
3.4.2 Temperature sensors with a duty-cycle-modulated (DEM) output
3.5 Methods to improve the accuracy of CMOS smart temperature-sensor systems
3.5.1 Dynamic element matching
3.5.2 Chopping
3.6 Principles of BJT-based smart temperature sensors with DCM
3.7 Signal processing of duty cycle modulated signals
3.7.1 Three methods of averaging
3.7.1.1 First type of averaging: best accuracy at any speed
3.7.1.2 Second type of averaging: simplest method
3.7.1.3 Third method of averaging: best accuracy at intermediate and low speeds
3.8 Fabrication and test results
3.8.1 Fabrication
3.8.2 Accuracy over temperature range and supply voltage range
3.8.3 Noise
3.8.4 Packaging shift and long-term stability
3.8.5 Performance summary
3.8.6 Simple systems with digital and analog signal processing
3.9 Summary
References
4 - Capacitive sensors for displacement measurement in the subnanometer range
4.1 Introduction
4.2 Challenges for subnanometer displacement measurement with capacitive sensors
4.3 Offset capacitance cancellation technique.
4.4 Capacitance-to-digital converter with offset capacitance cancellation and calibration functions
4.5 Conclusion
References
5 - Integrated inductive displacement sensors for harsh industrial environments
5.1 Why inductive displacement sensors?
5.2 Principle of operation and practical limitations for eddy-current sensors
5.2.1 Sensor operation principle
5.2.2 Limitations of eddy-current sensors
5.2.2.1 Skin effect
5.2.2.2 Parasitic effects
5.2.2.3 Limited sensing coil quality factor
5.2.2.4 Frequency dependence
5.3 Design requirements in precision industrial applications
5.4 State-of-the-art eddy-current sensor interfaces
5.4.1 Utilizing external switched-capacitor oscillator and LC resonator
5.4.2 Relaxation oscillator-based interface
5.5 Eddy-current sensor interfaces with LC oscillator and ratiometric measurement
5.5.1 Precision peak detection-based eddy-current sensor interface
5.5.2 Trade-offs in mixer-based interfaces
5.5.3 Synchronous detection-based eddy-current sensor interface
5.5.3.1 Sensor interface for mm-range displacement measurement
5.5.3.2 Sensor interface for μm-range displacement measurement
5.6 Summary and design perspectives
Appendix
5.A Sensing coil design aspects
5.A.1 Inductance
5.A.2 Quality factor
5.A.3 Self-resonance frequency
References
6 - Magnetic sensors and industrial sensing applications
6.1 Introduction
6.1.1 Hall effect
6.1.2 Magnetoresistance effect
6.1.2.1 Electron spin
6.1.3 Giant magnetoresistance
6.1.4 Tunneling magnetoresistance
6.1.5 MR/Hall effect-based angle sensors
6.1.6 Through-shaft magnetic angle sensor
6.1.6.1 Variable reluctance-Hall effect-based angle sensor
6.1.6.2 Signal conditioning circuit and sensor calibration
6.2 Conclusions
References.
7 - Advanced silicon radiation detectors in the vacuum ultraviolet and the extreme ultraviolet spectral range
7.1 Introductory overview
7.2 Challenges for radiation detection in the VUV and EUV spectral ranges
7.3 Device solutions for radiation detection in the VUV and EUV spectral ranges
7.4 Methods of radiometric investigation and characterization
7.5 Spectral responsivity and radiation hardness of VUV and EUV radiation detectors
7.6 Future trends
References
8 - Advanced interfaces for resistive sensors
8.1 Introduction
8.2 Resistive sensors
8.2.1 Examples of resistive sensors
8.2.1.1 Resistive temperature detectors
8.2.1.2 Light-dependent resistors
8.2.1.3 Resistive gas sensors
8.2.1.4 Strain gauges
8.2.1.5 Potentiometers
8.2.2 Parasitic capacitance
8.3 Voltamperometric resistance estimation
8.3.1 Implementation in smart sensors
8.3.2 Parasitic capacitance issues
8.3.3 Calibration procedures
8.4 Resistance-to-time conversion methods
8.4.1 Oscillator-based systems
8.4.1.1 Parasitic capacitance issues
8.4.1.2 The problem of long measuring times
8.4.2 Systems with constant sensor excitation voltage
8.4.2.1 Long measuring time problem
8.4.2.2 Direct ramp slope estimation
8.4.2.3 Parasitic capacitance estimation
8.5 Industrial-related aspects
8.6 Conclusion and future trends
References
9 - Reconfigurable ultrasonic smart sensor platform for nondestructive evaluation and imaging applications
9.1 Introduction
9.2 Fundamentals of ultrasonic sensing and pulse-echo measurements
9.3 Reconfigurable ultrasonic smart sensor platform design
9.3.1 System features and user interface
9.3.2 System response and real-time operational requirements
9.3.3 Reconfigurable ultrasonic smart sensor platform architecture.
9.3.4 Analog-to-digital converter to field-programmable gate array interface
9.4 Algorithms used in evaluation of reconfigurable ultrasonic smart sensor platform
9.4.1 Coherent averaging
9.4.2 Split-spectrum processing
9.4.3 Chirplet signal decomposition
9.5 Hardware realization of ultrasonic imaging algorithms using reconfigurable ultrasonic smart sensor platform
9.5.1 Averaging implementation
9.5.2 Split-spectrum processing implementation
9.5.3 Chirplet signal decomposition implementation
9.5.4 Resource usage and timing constraints
9.6 Future trends
9.7 Conclusion
9.8 Sources of further information and advice
References
10 - Advanced optical incremental sensors: encoders and interferometers
10.1 Introduction
10.2 Displacement interferometers
10.2.1 Basics of displacement interferometry
10.2.1.1 Homodyne interferometers (detection)
10.2.1.2 Heterodyne interferometers (detection)
10.2.1.3 Signals
10.2.2 Interferometer concepts
10.2.2.1 Linear interferometer
10.2.2.2 Plane mirror interferometer
10.2.3 Phase detection and interpolation
10.3 Sources of error and compensation methods
10.3.1 Setup dependent error sources
10.3.1.1 Cosine error
10.3.1.2 Abbe error
10.3.1.3 Dead path error
10.3.1.4 Target uniformity
10.3.1.5 Mechanical stability
10.3.2 Instrument dependent error sources
10.3.2.1 (Split) frequency
10.3.2.2 Beam walk-off
10.3.2.3 Electronics and data age
10.3.2.4 Periodic deviation
10.3.3 Environment dependent error sources
10.3.3.1 Thermal effects on the interferometer
10.3.3.2 Refractive index of air
10.4 Optical encoders
10.4.1 Imaging incremental encoder
10.4.2 Interferential encoders
10.4.2.1 Diffraction physics
10.4.2.2 Sensitivities
10.4.2.3 Schematic setups
10.4.2.4 Phase detection.
10.4.2.5 Tilt sensitivity.

Smart sensors and MEMS intelligent devices and microsystems for industrial applications

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