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McMaster University
Civil Engineering

Engineering Experimentation Applications of Engineering Experimentation • Experiments can be separated into 2 categories: 1. Experiments to establish new concepts 2. Experiments to evaluate existing products to determine their maintenance requirements Applications of Engineering Experimentation • Measurements can be separated into 2 categories: 1. Measurement in engineering experimentation: trying to obtain new information 2. Measurement in operational devices: for monitoring and control Measurement in Engineering Experimentation • A simple example: thermometer General Characteristics of Measurement Systems • Goal is to obtain numerical values for certain physical variables (e.g., temperature) • Unknown variables are known as measurands • Measurement system senses the measurand & produces a unique numerical value that describes the measurand Generalized Measurement System • Typically, a measurement system consists of 3 subsystems: 1. Sensing element has a physical characteristic that changes in response to a change in the measurand Generalized Measurement System 2. Signal modification subsystem changes the output of the sensing element to make it more suitable for the indicating or recording device Generalized Measurement System 3. The indicator or recording device can be as simple as a visual reading from a scale to a computerized acquisition system which can record, display and manipulate the data instantaneously V alidity of Measurement • Output of a measurement system must truly represent the actual value of the measurand • Some deviation will exist between the actual value of the measurand & the measurement system output • Deviation must be small enough that the output can be used for its intended purposes • Generally: the smaller the allowable error the more expensive the measurement system Measurement Error • Error = measured value – true value • Experimenter can estimate the uncertainty interval (or simply uncertainty) • Uncertainty is an estimate, with some level of confidence, of the limits of error in the measurement • Example: with 95% confidence, the uncertainty of a voltage measurement is ±1 𝑉 • i.e., the error will be > 1V in < 5% of the time Measurement Error • Errors generally fall into two categories: 1. Systematic errors (a.k.a. fixed or bias errors) 2. Random errors (a.k.a. precision errors) Systematic Errors • Consistent and repeatable • Example: a measurement system may consistently read 10% > than true value • 1 major source is from calibration of the measurement system (calibration errors) • Errors in the calibration process carry into the measurement system • Although many systems are treated as linear, they may in fact be non-linear – assumption leads to calibration errors Systematic Errors • 2 ndmajor source of error results from the use of a measurement system which alters the measurand (loading errors) • Systems that produce significant loading error are called intrusive measurement devices • Example: a thermometer at different temperature than fluid in a beaker • Devices with negligible loading error are called nonintrusive Systematic Errors • 3 source of error results from the system being affected by variables other than the measurand (e.g., spatial error) • Example: wall mounted thermometer used to measure air temperature in a room reads too low if walls are cooler than air Random Errors • Caused by lack of repeatability in the output of the measurement system • Can originate from: • the measurement system itself • the experimental system • the environment Random Errors • Are usually caused by uncontrolled variables in the measurement process • Example: to properly use a temperature sensitive amplifier one has to measure / control the temperature to account for / eliminate system variability Bias & Precision Error • Systematic (bias) error = average of readings – true value • Random (precision) error = reading – average of readings • For error estimates to be reasonable, a large number of readings are req’d to form the avg. Measurement Definitions Range: • A measuring system is designed to operate over a specified range • Describes the values of the measurand to which the measurement system will respond properly – values outside his range will be invalid • Example: a volt meter has a range of ±3𝑉 Measurement Definitions Span: • The difference between the upper and lower values of the range • Example: voltmeter with a range of ±3𝑉 has a span of 6V • Can also refer to output range
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