Pi unit-1

Course Information

  • Course Title: CHC 3090: Process Instrumentation

  • Degree Program: 3rd Year B.Tech. Chemical Engineering

  • Semester: V (Autumn Semester: 2019 - 20)

Course Objectives

  • Develop understanding of process instrumentation basics and instrument functioning.

Course Assessments

  • Course Work: Home assignments, tutorials, and quizzes (15%)

  • Mid-Semester Exam: 1 hour (25%)

  • End-Semester Exam: 2 hours (60%)

Syllabus Overview

  • Unit 1: Measurement basics, Classification and Characteristics of measuring instruments.

  • Unit 2: Measurement system components, Transducers/sensors, Data acquisition, D/A and A/D converters.

  • Unit 3: Process instruments for measurement: pressure, flow, temperature, level, density, viscosity, humidity.

  • Unit 4: Measurements of solids, liquids, gases, Instrumental methods of analysis, P&ID, Instrumentation in modern plants.

Text and Reference Books

  • Textbooks:

    • Eckman, D. P., Industrial Instrumentation, John Wiley, 1966.

    • Bolton, W., Instrumentation & Process Measurements, Orient Longmans, 1991.

  • Reference Books:

    • Andrew, W.G., Applied Instrumentation in Process Industries, Vol. I and II, Gulf Publishing, 1993.

    • Morris, A.J., Measurement and Instrumentation Principles, 3rd Ed., Butterworth & Heinmann, 2001.

    • Johnson, C.B., Process Control Instrumentation Technology, 8th Ed., Prentice Hall of India, 2005.

    • Willard, H.H. et al., Instrumental Methods of Analysis, 6th Ed., CBS Publishers, 1986.

    • Gregory S. Patience, Experimental Methods and Instrumentation for Chemical Engineers, 2nd Ed., Elsevier.

Introduction to Process Instrumentation

  • Definition: Study of measurement of process parameters/variables and their control.

  • Applications:

    • Aerospace Industry

    • Power Plants

    • Automobile Industry

    • Process Industry

    • Laboratory

    • Weather Forecasting

    • Medical Instruments

    • Communication

Benefits of Process Instrumentation

  • Consistency: Reduces variability of equipment and ensures reliability of operation.

  • Quality Improvement: Maintains proper ratios of reactants, temperature/pressure regulation, and output monitoring.

  • Safety: Controls process conditions to avoid incidents and hazards.

Measurement Importance in Chemical Industry

  • Significance: Measurements provide numerical values critical for assessing:

    • Reactor and separator conditions

    • Flow rates

    • Product composition

  • Fundamental Purpose: Obtain numerical values to improve product quality/effectiveness of production.

  • Focus on economically attractive, safe, and sustainable chemical processing.

Functional Elements of Measurement System

  • Basic Functional Element:

    • Transducer: Converts input signals into a suitable form for processing.

    • Signal Conditioning Element: Processes transducer output into a suitable format.

    • Data Presentation Element: Provides quantitative measurements of the variable.

  • Auxiliary Functional Elements:

    • Calibration Element: For built-in calibration.

    • Feedback Element: Controls variations of the measured quantity.

    • Microprocessor Element: Facilitates data manipulation and interpretation.

Characteristics of Measuring Instruments

Static Characteristics

  1. Accuracy: Closeness of measurements to true values.

  2. Precision: Reproducibility of measurements within set tolerances.

  3. Resolution: Smallest detectable change in measurement.

  4. Reliability: Ability to perform assigned functions over time.

  5. Maintainability: Ease of repair and restoration after failures.

Dynamic Characteristics

  1. Speed of Response: Measure of how quickly an instrument reacts to input changes.

  2. Measuring Lag: Delay in output response to changes in input.

  3. Fidelity: Instrument's ability to accurately reproduce input changes.

  4. Dynamic Error: Difference between true value and indicated value during rapid changes.

Uncertainty Analysis

  • Definition: Technique to analyze derived quantities based on uncertainty from measurements.

  • Types:

    1. External Estimate of Uncertainty (UE)

    2. Internal Estimate of Uncertainty (UI)

  • Process: Involves statistical analysis of data to estimate true values and associated uncertainties.

Problems & Examples

  1. Zero Drift and Sensitivity Drift: Calculating changes in measuring instruments under different conditions.

  2. First Order Instruments: Assessing input frequency and output signal parameters to determine dynamic characteristics.