Instrumentation (and Fundamentals & Process Control) Characteristics Fall 1393 Bonab University
Instrumentation - Course Information Department of Electrical Engineering Instructor: Fariborz Rahimi Lectures: 13-14:30pm (Sat), 8-10am (Sun*) Prerequisites/Useful courses: Signals-Systems, Electrical measurements, Linear control systems Evaluation: • Assignments: 10% • Quizzes: 5% • Midterm 20% • Final Exam 65% References: • “ Measurement and Instrumentation. Theory and Application ” , Alan S. Morris, Reza Langari, 2011 • “ Instrumentation and Control Systems ” , W. Bolton, Elsevier, 2004 • “ Advanced Industrial Control Technology ” , Peng Zhang, Elsevier, 2010 2
Instrumentation - Course Information References: • [1] “ قیقد رازبا یاهمتسیس رد یریگ هزادنا ینابم ” , دار یقت اضردیمح , یتملبس یلع دیس 1392 • [2] “ یتعنص لرتنک یاهشور و لوصا ” یوفص ربکا یلع دیس – یناوضر دمحم – 1388- • [3] “ یتعنص لرتنک ئازجا و لوصا ” , 1379 – ناشوپ زبس تجح دیس • Introduction Video 3
Instrumentation – Course Contents & Summary • Introduction [1-1, A-1&2] • Definitions, Components, Characteristics (Sta-Dyn), Importance, Need/application of instrumentation & control • Measurement & Sensors • Errors & key parameters [1-1, A-2&3] • Sensors categories (variable resistors, transformers, capacitors … ) [1-1, A-2&13] • Conditioning systems (active-passive) [1-2, A-9&10] • Calibrating Measurement systems [A-4] • Measurement systems: • Force/Torque, pressure [1-4, A-15 & 18] • Displacement, Velocity, acceleration [1-5, A-19] • Temperature [1-6, A-14] • Basics of Control Technology [2-1] • Open/closed loop control systems, Components of control loops, Principles/Performance of such systems • Industrial/Process Control [2-2,2-5] • Function and terminology of process control systems, Control algorithms & tuning controllers, proportional/integral/derivative (PID) control laws, PLC controllers (or Micro-controllers) • Correction Elements (Actuators) [3-5] 4
Introduction Introduction • Instrumentation (usually in) Automation field • Process Control • Industrial Control • Components: Data Analysis Recorder Sensor / Signal Amplifier Conditioning Transducer Power Controller Control Supply Command 5
Introduction Introduction • The aim (application): • Engineering Analyses (of a machine, system, process) • A new product optimization • Mathematical/ computer modeling • Analyzing performance/safety • Monitor • Quality control, fault/failure detection (useful for Parameter adjustment) • Process Control (*) • In a feedback loop such information is used for automatic control • Control in process industries refers to the regulation of all aspects of the process (Precise control of level, temperature, pressure and flow) • Components of an instrumentation system: Sensor, Transducer, Transmitter, Actuator, Controller, Interface 6
Introduction Introduction • Why process control is important? Refining, combining, handling, manipulating inputs (raw) to profitably produce end products is: • Precise • Demanding • potentially hazardous process Small changes in a process = a large impact on the end result. Variations in: • Proportions, temperature, flow, turbulence, and many other factors must be carefully and consistently controlled to produce the desired end product with a minimum of raw materials/energy Process control more precise operations =profitability, quality & safety 7
Measurement Instrumentation Systems & Sensors 8
Measurement Instrumentation Systems & Sensors May • Measured numerical value ≠ true value of the variable Measurem ent System Input: Output: True value of a variable Measured value of a variable Errors in measurement: -Temperature of a liquid -The value for temperature, • Unavoidable (but can be reduced) -Pressure, speed, flow, … Pressure, speed, flow,… • Error , Repeatability Error Sources: 1. Gross errors ( هدمع یاطخ ) • Mistake (wrong summation of couple values) • Distraction (23.2 32.2) • Misuse of instruments 2. Systematic errors ( دنمشور ) • Observational/personal errors Parallax error: Angle of observing a scale ( mirror) • • Interpolation error: pointer stays between the divisions of the scale (observer has to estimate) 9
Measurement Instrumentation Systems - Errors & Sensors 2. Systematic errors • Instrumentation errors • Due to inherent shortcomings in the instrument • Due to positioning/levelness • Due to loading effects of the instrument • Environmental errors • due to conditions external to the measuring device (effects of temperature, pressure, humidity, dust or of external electrostatic or magnetic field) 3. Random/Residual errors ( یفداصت ) due to a multitude of small factors which change or fluctuate from one measurement to another. The happenings or disturbances about which we are unaware are lumped together averaging and statistical methods help Error Categories: • Linear (reading is related to true value in a Linear way) • Zero shift error • Non-Linear (don ’ t follow a general trend, affect repeatability) • Hysteresis, dead-zone errors 10
Measurement Instrumentation Systems - Errors & Sensors • Error combination 𝑓 𝑢 2 + 𝑓 𝑡𝑑 2 + 𝑓 𝑏 2 + 𝑓 𝑆 2 (Root Mean Square, RMS) 𝑓 𝑑 = • Calibration: Calibration is the process of comparing the output of a measurement system against standards of known accuracy Output quantity Qo • Key parameters in an instrumentation system: Allowable deviation 1. Sensitivity Q i R Zero shift ∆𝑅𝑝 𝑇 = lim 𝑅𝑗 → 0 Input quantity Qi ∆𝑅𝑗 2. Accuracy (= تحص ) Closeness to the true value 3. Precision (= تقد ) Identifyability, clearity, freedom from Random error 11
Measurement Instrument Types (Passive-Active) & Sensors • Passive: instrument output is produced entirely by the quantity being measured 12
Measurement Instrument Types (Passive-Active) & Sensors • Active: the quantity being measured simply modulates the magnitude of some external power source 13
Measurement Instrument Types (Null-Type and Deflection) & Sensors • Deflection type: the value of the quantity being measured is displayed in terms of the amount of movement of a pointer (pressure gauge) • Null-type (dead-weight gauge): weights are put on top of the piston until the downward force balances the fluid pressure. (Pressure measurement in terms of weight) • A general rule: null-type instruments more accurate than deflection types 14
Measurement Instrument Types (Analogue - Digital) & Sensors • Analogue: output varies continuously as the measured quantity changes. (output can have an infinite number of values within the range, the deflection- type of pressure gauge) • Digital: output varies in discrete steps and so can only have a finite number of values (needed for Microprocessor/computer) 15
Measurement Instrument Types (Indicating - with a Signal Output) & Sensors • Indicating: merely give an audio or visual indication of the magnitude of the physical quantity measured • all null-type instruments • most passive ones • analogue output (liquid-in-glass thermometer) • digital display • With a Signal Output: output in the form of a measurement signal whose magnitude is proportional to the measured quantity (commonly as part of automatic control systems) 16
Measurement Instrument Types (Smart - Non-smart) & Sensors • The advent of the microprocessor has created a new division in instruments between those that do incorporate a microprocessor (smart/intelligent) and those that don ’ t 17
Measurement Instrument Characteristics: A-Static & Sensors • Accuracy - Inaccuracy (Measurement Uncertainty) • how close the output reading is to the correct value • Inaccuracy/uncertainty (more common in practice): the extent to which a reading might be wrong. often quoted as a percentage of the full-scale (f.s.) reading • Example: A pressure gauge, measurement range of 0 – 10 bar has a quoted inaccuracy of ±1.0% f.s. (±1% of full-scale reading). • (a) What is the maximum measurement error expected for this instrument? • (b) What is the likely measurement error expressed as a percentage of the output reading if this pressure gauge is measuring a pressure of 1 bar? • Solution: • (a) 1.0% of the full-scale reading: maximum likely error is 1.0% ± 10 bar = 0.1 bar • (b) The maximum measurement error is a constant value related to the full-scale reading of the instrument. Thus, when measuring a pressure of 1 bar, the maximum possible error of 0.1 bar is 10% of the measurement value 18
Measurement Instrument Characteristics: A-Static & Sensors • Precision/Repeatability/Reproducibility • Degree of freedom from random errors • Large number of readings (the same quantity) by a high-precision instrument spread of readings = very small • Often confused with accuracy • High-precision may have low-accuracy (bias re-calibration) • Repeatability / reproducibility mean approximately the same robots programmed to place components at a particular point on a table 19
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