Sensor Systems

Fundamentals and Applications

Clarence W. de Silva

• Publisher: CRC Press
• Year: 2016
• Print ISBN: 9781498716246
• eBook ISBN: 9781498716277
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Civil Engineering
• Index: Technology & Engineering

This book covers sensors and multiple sensor systems, including sensor networks and multi-sensor data fusion. It presents the physics and principles of operation and discusses sensor selection, ratings and performance specifications, necessary hardware and software for integration into an engineering system and signal processing and data analysis. Additionally, it discusses parameter estimation, decision making and practical applications. Even though the book has all the features of a course textbook, it also contains a wealth of practical information on the subject.

1

Sensor Systems in Engineering

Chapter Objectives

• Role of Sensors and Sensor Systems

• Importance of Estimation in Sensing

• Innovative Sensor Technologies

• Scenarios of Engineering Application

• Human Sensory System

• Sensors in Mechatronic Engineering

• Sensing in Control Systems

• Instrumentation Process

• Application Examples

• Organization of the Book

1.1 Role of Sensors and Sensor Systems

Sensors

Sensors (e.g., semiconductor strain gauges, tachometers, RTD temperature sensors, cameras, piezoelectric accelerometers) are needed to measure (i.e., sense) unknown signals and parameters of an engineering system and its environment. Essentially, sensors are needed to monitor and “learn” about the system and possible interactions with its surroundings. This knowledge will be useful not only in operating or controlling the system but also for many other purposes such as

1. Process monitoring

2. Experimental modeling (i.e., model identification)

3. Product testing and qualification

4. Product quality assessment

5. Fault prediction, detection, and diagnosis

6. Advisory/warning generation

7. Surveillance

FIGURE 1.1
Sensors in an automobile.

A common application of sensors is in automobiles where a vast variety of sensors are used in the powertrain, driving assistance, safety and comfort, and so on, as presented in Figure 1.1. Some examples of commercially available sensors are given here.

Motion sensors: Potentiometer, differential transformer (LVDT), magnetostrictive (temposonic) displacement sensor, magnetic induction proximity sensor, tachometer, resolver, synchro, gyro, piezoelectric accelerometer, laser ranger, and ultrasound ranger

Force/torque sensors: Semiconductor strain-gauge and motor current sensor

Fluid flow sensors: Coriolis flow meter, pitot tube, rotameter, and orifice flow meter

Pressure sensors: Manometer, Bourdon tube, and diaphragm type

Temperature sensors: Thermocouple, thermistor, and resistance temperature detector (RTD)

Sensor Systems

A “sensor system” may mean

1. A system of multiple sensors, including sensor network and sensor/data fusion (when one sensor may not be adequate for the particular application)

2. A sensor and accessories that will be necessary in implementing it in a practical application (e.g., signal processing, data acquisition, data transmission/communication)

FIGURE 1.2
Sensors and other components in a feedback control system.

Several examples of sensor systems in both of these categories will be introduced in this chapter and further studied in subsequent chapters.

This book concerns both individual sensors and sensor systems. It will present the physics and the principles of operation, ratings and performance specification, selection, necessary hardware and software for integration into an engineering system, signal processing and data analysis, parameter estimation and decision making, and practical applications related to sensors and sensor systems.

Use in a Control System

Sensors and sensor systems are indispensable in a control system. A control system is a dynamic system that contains a controller as an integral part. The purpose of the controller is to generate control signals, which will drive the process (or plant) that is being controlled in a desired manner (i.e., according to some performance specifications; see Chapter 5), using various control devices. Specifically in a feedback control system, the control signals are generated based on the sensed response signals of the plant. Sensors and other main components in a feedback control system are schematically shown in Figure 1.2.

1.1.1 Importance of Estimation in Sensing

The measurement from a sensor may not provide the true value of the required parameter or variable for two main reasons:

1. The required quantity is not directly measured and has to be computed from the measured value (or values) using a suitable “model.”

2. The sensor (or even the sensing process) is not perfect and will introduce “measurement error.”

Hence, sensing may be viewed as a problem of estimation (see Chapter 7), where the “true value” of the measured quantity is “estimated” using the measured data. Two main categories of error, “model error” and “measurement error,” enter into the process of estimation and will affect the accuracy of the result. The model error arises from the relationship between quantity of interest and the quantity that is measured (or the model of the system). Unknown (and random) input disturbances may also be treated under model error. The measurement error will arise from the sensor and the sensing process (e.g., how the sensor is mounted and how the data are collected, communicated, and recorded). It is clear that estimation (of parameters and signals) is an important step of sensing. Many methods are available for estimation. Some of them are presented in the book (e.g., least squares, maximum likelihood, Kalman filter, extended Kalman filter, unscented Kalman filter; see Chapter 7).

1.1.2 Innovative Sensor Technologies

Apart from conventional sensors, many types of innovative and advanced sensors are being developed (see Chapters 10 through 12). Several types are listed as follows:

1. Microminiature and embedded sensors (those based on integrated circuit [IC] technologies and microelectromechanical system [MEMS] technologies, with integrated signal processing, control, and other hardware; sensors may be integral with the system components)

2. Intelligent sensors (built-in information preprocessing, reasoning, and inferencing to provide high-level knowledge-based decision making; multisensor fusion to provide more reliable and accurate results)

3. Networked sensors (multiple sensor nodes [SNs] communicate with each other in a distributed sensing setup; there can be significant geographic separation between SNs; the node connection may be wired or wireless; typically an SN contains one or more sensors, a microcontroller, and signal conditioning hardware)

4. Hierarchical sensory architectures (low-level sensory information is preprocessed to meet higher level requirements), for example, in hierarchical control, each control layer is serviced by a corresponding sensor layer

1.2 Application Scenarios

Sensors and transducers are necessary to acquire output signals (process responses) for system monitoring; fault prediction, detection, and diagnosis; generation of warnings and advisories; feedback control; and supervisory control and to measure input signals for experimental modeling (system identification) and feedforward control and for a variety of other purposes. Since many different types and levels of signals are present in a dynamic system, signal modification (including signal conditioning and signal conversion; see Chapters 3 and 4) is indeed a crucial function associated with sensing. In particular, signal modification is an important consideration in component interfacing. It is clear that the subject of system instrumentation should deal with sensors, transducers, signal modification, and component interconnection. In particular, the subject should address the identification of the necessary system components with respect to type, functions, operation and interaction, and proper selection and interfacing of these components for various applications. Parameter selection (including component sizing and system tuning) is an important step as well. Design is a necessary part of system instrumentation, for it is design that enables us to build a system that meets the performance requirements—starting, perhaps, with a few basic components such as sensors, actuators, controllers, compensators, and signal modification devices.

Engineers, particularly mechatronic engineers, should be able to identify or select components, particularly sensors, actuators, controllers, and interface hardware for a system, to model and analyze individual components and the overall integrated system, and to choose proper parameter values for the components (i.e., component sizing and system tuning) for the system to perform the intended functions in accordance with some specifications.

Instrumentation (sensors, actuators, signal acquisition and modification, controllers, and accessories and their integration into a process) is applicable in branches of engineering. Typically, instrumentation is applicable in process monitoring; fault prediction, detection, and diagnosis; testing; and control, in practically every engineering system. Some branches of engineering and typical application situations are listed as follows:

Aeronautical and aerospace engineering: Aircraft and spacecraft

Civil engineering: Monitoring of civil engineering structures (bridges, buildings, etc.)

Chemical engineering: Monitoring and control of chemical processes and plants

Electrical and computer engineering: Development of electronic and computer-integrated devices, hard drives, etc., sensor-embedded systems, and control and monitoring of electrical and computer systems

Materials engineering: Material synthesis processes and material testing

Mechanical engineering: Vehicles and transit systems, robots, manufacturing plants, industrial plants, power generation systems, jet engines, oil and gas extraction, transportation, and refining

Mining and mineral engineering: Mining machinery and processes and raw material processing

Nuclear engineering: Monitoring and control of nuclear reactors and testing and qualification of components

We have highlighted the automotive example as a valuable application scenario for sensors and sensor systems. Several applications and their use of sensors are noted in Table 1.1. Some important areas of application are indicated here.

As noted before, transportation is a broad area where sensors have numerous applications. In ground transportation in particular, automobiles, trains, and automated transit systems use airbag deployment systems, antilock braking systems (ABS), cruise control systems, active suspension systems, and various devices for monitoring, toll collection, navigation, warning, and control in intelligent vehicular highway systems. All these devices use sensors and sensor systems. In air transportation, modern aircraft designs with advanced materials, structures, electronics, and control benefit from sophisticated sensors. Flight simulators, flight control systems, navigation systems, landing gear mechanisms, traveler/driver comfort aids, and the like use sensors and sensor systems primarily for monitoring and control.

TABLE 1.1
Sensors Used in Some Common Engineering Applications

Process	Typical Sensors
Aircraft	Displacement, speed, acceleration, elevation, heading, force pressure, temperature, fluid flow, voltage, current, global positioning system (GPS)
Automobile	Displacement, speed, force, pressure, temperature, fluid flow, fluid level, vision, voltage, current, GPS, radar, sonar
Home heating system	Temperature, pressure, fluid flow
Milling machine	Displacement, speed, force, acoustics, temperature, voltage, curr...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Preface
• Acknowledgments
• Author
• 1. Sensor Systems in Engineering
• 2. Component Interconnection
• 3. Amplifiers and Filters
• 4. Signal Conversion Methods
• 5. Performance Specification and Rating Parameters
• 6. Bandwidth, Sampling, and Error Propagation
• 7. Estimation from Measurements
• 8. Analog Motion Sensors
• 9. Effort Sensors
• 10. Miscellaneous Sensors
• 11. Digital Transducers
• 12. Microelectromechanical Systems and Multisensor Systems
• Appendix A: Laboratory Exercises
• Appendix B: Projects and Case Studies
• Appendix C: Probability and Statistics
• Appendix D: Reliability Considerations for Multicomponent Devices
• Answers to Numerical Problems
• Units and Conversions (Approximate)
• Index