Advanced Instrumentation and Computer I/O Design

Defined Accuracy Decision, Control, and Process Applications

Patrick H. Garrett

• Publisher: Wiley-IEEE Press
• Year: 2013
• Print ISBN: 9781118317082
• eBook ISBN: 9781118504796
• Edition: 2
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

Written by an expert in the field of instrumentation and measurement device design, this book employs comprehensive electronic device and circuit specifications to design custom defined-accuracy instrumentation and computer interfacing systems with definitive accountability to assist critical applications.

Advanced Instrumentation and Computer I/O Design, Second Edition begins by developing an understanding of sensor-amplifier-filter signal conditioning design methods, enabled by device and system mathematical models, to achieve conditioned signal accuracies of interest and follow-on computer data conversion and reconstruction functions. Providing complete automated system design analyses that employ the Analysis Suite computer-assisted engineering spreadsheet, the book then expands these performance accountability methods—coordinated with versatile and evolving hierarchical subprocesses and control architectures—to overcome difficult contemporary process automation challenges combining both quantitative and qualitative methods. It then concludes with a taxonomy of computer interfaces and standards including telemetry, virtual, and analytical instrumentation.

Advanced Instrumentation and Computer I/O Design, Second Edition offers:

• Updated chapters incorporating the latest electronic devices and system applications
• Improved accuracy of the design models between their theoretical derivations and actual measured results
• End-of-chapter problems based on actual industry, laboratory, and aerospace system designs
• Multiple real-world case studies performed for technology enterprises
• Instrumentation Analysis Suite for computer I/O system design
• A separate solutions manual

Written for international engineering practitioners who design and implement industrial process control systems, laboratory instrumentation, medical electronics, telecommunications, and embedded computer systems, this book will also prove useful for upper-undergraduate and graduate-level electrical engineering students.

CHAPTER 1

Thermal, Mechanical, Quantum, and Analytical Sensors

1-0 INTRODUCTION

Automated laboratory systems, manufacturing process controls, analytical instrumentation, and aerospace systems all would have diminished capabilities without the availability of contemporary computer-integrated data systems with multisensor information structures. This text accordingly develops supporting error models that enable a unified performance evaluation for the design and analysis of linear and digital instrumentation systems with the goal of compatibility of integration with enterprise quality requirements. These methods then serve as a quantitative framework supporting the design of high-performance automation systems.

This chapter specifically describes the front-end electrical sensor devices for a broad range of applications from industrial processes to scientific measurements. Examples include environmental sensors for temperature, pressure, level, and flow; optical sensors for measurements beyond apparatus boundaries, including spectrometers for chemical analytes; and material and biomedical assays sensed by microwave microscopy. It is notable that owing to advancements in higher attribution sensors they are increasingly being substituted for process models in many applications.

1-1 INSTRUMENTATION ERROR INTERPRETATION

Measured and modeled electronic device, circuit, and system error parameters are defined in this text for combination into a quantitative end-to-end instrumentation performance representation for computer-centered measurement and control systems. It is therefore axiomatic that the integration and optimization of these systems may be achieved by design realizations that provide total error minimization. Total error is graphically described in Figure 1-1, and analytically expressed by Equation (1-1), as a composite of mean error contributions (barred quantities) plus the root-sum-square (RSS) of systematic and random uncertainties. Total error thus constitutes the deviation of a sensor-based measurement from its absolute true value, which is traceable to a standard value harbored by the National Institute of Standards and Technology (NIST). This error is traditionally expressed as 0–100% of full scale (%FS), where the RSS component represents a one-standard-deviation confidence interval, and accuracy is defined as the complement of error (100% − ε_total). Figure 1-2 illustrates generic sensor elements and the definitions describe relevant terms:

Figure 1-1. Instrumentation error interpretation.

Figure 1-2. Generic sensor elements.

Accuracy:	The closeness with which a measurement approaches the true value of a measurand, usually expressed as a percent of full scale
Error:	The deviation of a measurement from the true value of a measurand, usually expressed as a percent of full scale
Tolerance:	Allowable deviation about a reference of interest
Precision:	An expression of a measurement over some span described by the number of significant figures available

(1-1)

Resolution:	An expression of the smallest quantity to which a quantity can be represented
Span:	An expression of the extent of a measurement between any two limits
Range:	An expression of the total extent of measurement values
Linearity:	Variation in the error of a measurement with respect to a specified span of the measurand
Repeatability:	Variation in the performance of the same measurement
Stability:	Variation in a measurement value with respect to a specified time interval

Technology has advanced significantly as a consequence of sensor development. Sensor nonlinearity is a common source of error that can be minimized by means of multipoint calibration. Practical implementation often requires the synthesis of a linearized sensor that achieves the best asymptotic approximation to the true value over a measurement range of interest.

The cubic function of Equation (1-2) is an effective linearizing equation demonstrated over the full 700°C range of a commonly applied Type-J thermocouple, which is tabulated in Table 1-1. Solution of the A and B coefficients at judiciously spaced temperature values defines the linearizing equation with a 0°C intercept. Evaluation at linearized 100°C intervals throughout the thermocouple range reveals temperature values nominally within 1°C of their true temperatures, which correspond to typical errors of 0.25%FS. It is also useful to express the average of discrete errors over the sensor range, obtaining a mean error value of

FS for the Type-J thermocouple. This example illustrates a design goal proffered throughout this text of not exceeding one-tenth percent error for any contributing system component. Extended polynomials permit further reduction in linearized sensor error while incurring increased computational burden, where a fifth-order equation can beneficially provide linearization to 0.1 °C, corresponding to

FS mean error.

Table 1-1. Sensor cubic linearization

(1-2)

Coefficient for 10.779 mV at 200°C:

Coefficient for 27.393 mV at 500°C:

1-2 TEMPERATURE SENSORS

Thermocouples are widely used temperature sensors because of their ruggedness and broad temperature range. Two dissimilar metals are used in the Seebeck-effect temperature-to-emf junction with transfer relationships described by Figure 1-3. Proper operation requires the use of a thermocouple reference junction in series with the measurement junction to polarize the direction of current flow and maximize the measurement emf. Omission of the reference junction introduces an uncertainty evident as a lack of measurement repeatability equal to the ambient temperature.

Figure 1-3. Temperature–millivolt graph for thermocouples.

(Courtesy Omega Engineering, Inc., an Omega Group Company.)

An electronic reference junction that does not require an isolated supply can be realized with an Analog Devices AD590 temperature sensor as shown in Figure 4-5. This reference junction usually is attached to an input terminal barrier strip in order to track the thermocouple-to-copper circuit connection thermally. The error signal is ...

Table of contents

• Cover
• Half Title page
• Title page
• Copyright page
• Preface
• Chapter 1: Thermal, Mechanical, Quantum, and Analytical Sensors
• Chapter 2: Instrumentation Amplifiers and Parameter Errors
• Chapter 3: Filters for Measurement Signals
• Chapter 4: Signal Conditioning Design and Instrumentation Errors
• Chapter 5: Data Converstion Devices and Parameters
• Chapter 6: Sampled Data and Reconstruction with Intersample Error
• Chapter 7: Instrumentation Analysis Suite, Error Propagation, Sensor Fusion, and Interfaces
• Chapter 8: Instrumented Processes Decision and Control
• Chapter 9: Process Automation Applications
• Index