510 likes | 776 Views
ENTC 4350. Theories of Measurement. Basics of Measurements. Measurement = assignment of numerals to represent physical properties Two Types of Measurements for Data Qualitative Quantitative. Qualitative Measurements. Qualitative = Non-numerical or verbally descriptive also have 2 types
E N D
ENTC 4350 Theories of Measurement
Basics of Measurements • Measurement = assignment of numerals to represent physical properties • Two Types of Measurements for Data • Qualitative • Quantitative
Qualitative Measurements • Qualitative = Non-numerical or verbally descriptive also have 2 types • Nominal = no order or rank eg. list • Ordinal = allows for ranking but differences between data is meaningless eg. alphabetical list
Quantitative Measurements • Quantitative = Numerical Ranking also have 2 types • Interval = meaningless comparison eg. calendar • Ratio = based on fixed or natural zero point eg. weight, pressure, Kelvin
V1 V2 V3 A2 A1 Definition Decibels • dB = 20 log (Gain) where Gain = Voutput/ Vinput can also be in current or power • Why bother? • Easier math because you can add and subtract db instead of multiplying and dividing
Definition Decibels • A1 = V2/V1 A2 = V3/V2 • Total Gain = A1*A2 = V2/V1 * V3/V2
Definition Decibels • Now if everything was in dB • Total Gain = A1 (dB) + A2 (dB)
Calculation of Gain given dB • dB = 20 Log (output/ input) • Output = input 10dB/20
Decibel example Question • An amplifier has 3 amplifier states and a 1 db attenuator in cascade. Assuming all impedances are matched, what is the overall gain if the amplifiers are 5, 10, 6 dB? Express your answer in dB and nondB form.
Decibel example • Solution: • Gain = 5 dB + 10 dB + 6 dB -1 dB = 20 dB or • 20 dB = 20 log (Gain) • Gain = 1020/20 =10
Variation and Error • Variation caused by small errors in measurement process • Error caused by limitation of machine • Data will exhibit variation where you will see a distribution in data. You can quantify distribution by calculating mean, variance, and standard deviation
Variation and Error • Data will exhibit variation where you will see a distribution in data. • You can quantify distribution by calculating the • mean, • variance, and • standard deviation
MEAN • Mean • where Xi = data point and N = Total number of points • Example data points = 2,3,3,4,3 Mean • Xbar = (2 + 3 + 3 + 4 + 3 ) / 5 = 3
Variance • Variance • Example Variance =[(2-3)2 + ( 3-3) 2 + (3-3)2 + (4 – 3)2 + (3 – 3)2] /5 = 2 / 5 = 0.4
Standard Deviation • Standard Deviation • Example Standard Deviation = (0.4)1/2 • Note with small populations use N-1 instead of N
Root Mean Square (RMS) • RMS used in electrical circuits
Root Mean Square (RMS) • VRMS= RMS value in voltage • T = time interval from t1 to t2 • V(t) = time varying voltage signal • With a sine wave
Voltage Indicators Vp Vrms Vpp Vrms = Vp · .707 (Sine wave)
f = 1/T w = 2 p f Frequency and Period Period, T f1 ( t )
Solving for Vrms: RMS: Root-Mean-Square • RMS is a measure of a signal's average power. • Instantaneous power delivered to aresistor is: P= [v(t)]2/R. • To get average power, integrate and divide by the period:
RMS: Root-Mean-Square • An AC voltage with a given RMS value has the same heating (power) effect as a DC voltage with that same value.
1 1.733 v 1.414 v 1 v 1 v Waveform Vpeak Vrms Sine 1.414 1 Triangle 1.733 1 Square 1 1 DC 1 1 All = 1 WATT RMS: Root-Mean-Square • All the following voltage waveforms have the same RMS value, and should indicate 1.000 VAC on an rms meter:
Three Categories of Measurement • Direct Measurement: • Indirect Measurement: • Null Measurement:
Direct Measurement • Direct Measurement: holding a measurand up to a calibrated standard and comparing them eg. meter stick
Indirect Measurement • Indirect Measurement: Measuring something other than an actual measurement • This is typically done when direct measurement is difficult to obtain or is dangerous. • Example blood pressure can be obtained using a catheter with pressure transducer or can be obtained using Korotkoff Sounds • Neural activity of brain, direct measurement would be implanting of electrodes or use of indirect measurement of MRI
Null Measurement • Null Measurement: Compared calibrated source to an unknown measurand and adjust till one or other until difference is zero • Electrical Potentiometer used in Wheatstone Bridge
Definitions of Factors that Affect Measurements • Error normal random variation not a mistake, • If you have a nonchanging parameter and you measure this repeatedly, the measurement will not always be precisely the same but will cluster around a mean Xo. • The deviation around Xo = error term where you can assume your measurement is Xo as long is deviation is small.
Definitions of Factors that Affect Measurements • Validity = Statement of how well instrument actually measures what it is supposed to measure • Eg. you’re developing a blood pressure sensor with a diaphragm that has a strain gauge. • This instrument is only valid if the deflection of the strain gauge is correlated to blood pressure.
Definitions of Factors that Affect Measurements • Reliability and Repeatability • Reliability statement of a measurement’s consistency of getting the same values of measurand on different trials • Repeatibility getting the same value when exposed to the same stimulus
Definitions of Factors that Affect Measurements continued • Accuracy and Precision: • Accuracy Freedom from error, how close is a measurement to a standard • Precision exactness of successive measurements, has small standard deviations and variance under repeated trials
Xi Xi Xi Xi Xo Xo Xo Xo Definitions of Factors that Affect Measurements continued Good Precision (Sm. Std) Good Accuracy (Xi ~ Xo) Good Precision (Sm. Std) Bad Accuracy (Xi << Xo or Xi >> Xo) Bad Precision (Large. Std) Good Accuracy (Xi ~ Xo) Bad Precision (Large. Std) Bad Accuracy (Xi << Xo or Xi >> Xo) Xi = Where the measurement is supposed to be Xo = Mean of Data
Example of Precision and Accuracy Good Precision (Sm. Std) Bad Accuracy (Xi << Xo or Xi >> Xo) Good Precision (Sm. Std) Good Accuracy (Xi ~ Xo) Bad Precision (Large. Std) Bad Accuracy (Xi << Xo or Xi >> Xo) Bad Precision (Large. Std) Good Accuracy (Xi ~ Xo)
Tactics to Decrease Error on Practical Measurements: • Make Measurements several Times • Make Measurements on Several Instruments • Make successive Measurements on different parts of instruments (different parts of ruler)
Less Resolution More Resolution Definitions of Factors that Affect Measurements cont. • Resolution – Degree to which a measurand can be broken into identifiable adjacent parts ex pictures dpi (dots per square inch)
3 3 2.5 2 2 1.5 1 1 Definitions of Factors that Affect Measurements cont. • Binary Resolution • If you have 8 Bits that will represent 10 V what is the resolution of the system? • Resolution = 10 – 0 / 255 = 39 mV per bit • 8 bits gives you 28 = 256 values or 256 -1 = 255 segments
Error • Measurement Error Deviation between actual value of measurand and indicated value produced by instrument • Categories of Error • Theoretical Error: • Static Error: • Dynamic • Instrument Insertion Error
Theoretical Error: • The difference between the theoretical equation and the simplified math equation.
Static Error: • Errors that are always present even in unchanging system and therefore are not a function of time or frequency. • Reading Static Error: • Environmental Static Error: • Characteristic Static Errors: • Quantization Error:
Reading Static Error: • Misreading of Digital display output • Parallax Reading Error error when not measuring straight on (water in measuring cup). • Interpolation Error Error in estimating correct value • Last Digit Bobble Error Digital display variations when the LSB varies between 2 values .
Environmental Static Error: • Temperature, pressure, electromagnetic fields, and radiation can change output • Eg. electrical components are rated as industrial temperature, temp = -50 to 85C.
Characteristic Static Errors: • Residual error that is not reading or environment • Eg. zero offset, gain error, processing error, linearity error, hysteresis, repeatibility or resolution, or manufacturing deficiencies.
Quantization Error: • Error due to digitization of data and is the value between 2 levels.
Dynamic Error: • When a measurand is changing or is in motion during measurement process • Eg. inertia of mechanical indicating devices during measurement of rapidly changing parameters • Eg. analog meters or frequency, slew rate limitation of instrumentation
Instrument Insertion Error: • Measurement process should not significantly alter phenomenon being measured • Eg. If you are measuring body temp and performing laser surgery the laser will heat the surrounding area and not give an accurate body temperature
Error Contribution Analysis • Error Budget = Analysis to determine allowable error to each individual component to ensure overall error not too high. • Error Calculation =
Error Contribution Analysis • Why not take just summation of the average? • Because noise error can be positive and negative thus canceling and showing less error that what truly exists. • Also need to depict standard deviation because need to denote spread in your data
Operation Definitions • To keep procedure constant so that the results are repeatable. • Example of Standards • ANSI—American National Standard Institute • ITU—International Telecommunication Union • AAMI—Association for the Advancement of Medical Instrumentation • IEEE—Institute for Electrical and Electronic Engineers
Summary • Define and understand how to depict system gain in dB and non dB format • Define 2 Types of Measurement • Calculate Mean, Variance and Standard Deviation • Define 3 categories of Measurement • Explain 5 factors that Affect Measurement