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Types of errors
There are three main types of errors in measurement systems:
1) Gross errors are caused by human mistakes when using instruments, calculating measurements, or recording data.
2) Systematic errors occur due to faults in measuring devices and can include zero errors, observational errors from wrong readings, and environmental errors from changes in temperature or humidity.
3) Random errors are caused by sudden changes in experimental conditions from unknown causes and can include noise, resulting in measurements that need to be analyzed statistically.
Errors in measurement
The document discusses different types of errors that can occur in measurement. It describes gross errors, systematic errors like instrumental errors and environmental errors, and random errors. It also defines key terms used to analyze errors like limit of reading, greatest possible error, and discusses analyzing measurement data using statistical methods like the mean, standard deviation, variance and histograms. Measurement errors can occur due to issues like parallax, calibration, limits of the measuring device, and are analyzed statistically.
Physics 1.2b Errors and Uncertainties
This document discusses uncertainties and errors in physical measurements. It explains that there are two types of errors - random errors which are unpredictable, and systematic errors caused by imperfect measuring equipment. Random errors can be reduced by repeating measurements, while systematic errors are reduced by calibrating equipment. Accuracy refers to how close a measurement is to the true value, while precision refers to how close repeated measurements are. The number of significant figures reported in a result should not exceed the least precise value used. The document also discusses determining and expressing uncertainties in measurements, and how to combine uncertainties when performing calculations or graphing data.
Measurement and error
This document provides an overview of the DEE1012 measurement course. It outlines the course learning outcomes, which are to apply measurement principles and solve problems using measuring operations and theorems. The document then details several topics that will be covered in the course, including the measurement process, elements of a measurement system, types of errors, measurement terminology, characteristics of measurement, and standards used in measurement. Examples are provided to illustrate key concepts. References are listed at the end.
Measurement Errors and Standards
This document discusses measurement errors and standards. It defines key terms related to measurement accuracy and precision. Accuracy is the closeness of a measurement to the true value, while precision refers to the consistency of repeated measurements. Errors can be absolute or relative. Systematic errors are due to instrument flaws, while random errors have unknown causes. The document also discusses limiting/guarantee errors, which specify the maximum allowed deviation from a component's rated value. Resolution refers to the smallest detectable change in a measurement. Sensitivity is the change in output per unit change in input.
Absolute relative error
Absolute and relative error are two types of error that scientists should be familiar with. Absolute error is the physical error in a measurement, while relative error gives an indication of how good a measurement is relative to the size of the thing being measured. Absolute error is calculated as the amount of error, while relative error is calculated as the absolute error divided by the value of the thing measured. This allows comparisons of accuracy between measurements even if the absolute error is the same.
Physical measurement and error analysis
This document discusses physical measurement and errors in measurement. It defines key terms like measurement, units, observations, and least count. It describes the International System of Units (SI) as the modern metric system. It also discusses different types of errors like absolute error and relative error. Systematic errors can be corrected while random errors are reduced by taking multiple measurements. Accuracy refers to systematic errors while precision describes random errors. The document outlines methods to calculate propagation of errors and statistical treatment of error values.
Chapter 1(5)Measurement and Error
This document discusses terminology and concepts related to measurement and error. It defines true value, accuracy, and precision. There are two types of errors - determinate (systematic) errors which have a known cause, and indeterminate (random) errors which cannot be determined. Accuracy refers to closeness to the true value while precision refers to reproducibility. The standard deviation allows for more variation in a sample compared to the population. When combining uncertainties from multiple measurements, relative uncertainties should be summed for multiplication and division, while absolute uncertainties are summed for addition and subtraction. Significant figures refer to the reliable digits in a measurement and rules govern how many are retained in calculations.
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Types of errors
There are three main types of errors in measurement systems:
1) Gross errors are caused by human mistakes when using instruments, calculating measurements, or recording data.
2) Systematic errors occur due to faults in measuring devices and can include zero errors, observational errors from wrong readings, and environmental errors from changes in temperature or humidity.
3) Random errors are caused by sudden changes in experimental conditions from unknown causes and can include noise, resulting in measurements that need to be analyzed statistically.
Errors in measurement
The document discusses different types of errors that can occur in measurement. It describes gross errors, systematic errors like instrumental errors and environmental errors, and random errors. It also defines key terms used to analyze errors like limit of reading, greatest possible error, and discusses analyzing measurement data using statistical methods like the mean, standard deviation, variance and histograms. Measurement errors can occur due to issues like parallax, calibration, limits of the measuring device, and are analyzed statistically.
Physics 1.2b Errors and Uncertainties
This document discusses uncertainties and errors in physical measurements. It explains that there are two types of errors - random errors which are unpredictable, and systematic errors caused by imperfect measuring equipment. Random errors can be reduced by repeating measurements, while systematic errors are reduced by calibrating equipment. Accuracy refers to how close a measurement is to the true value, while precision refers to how close repeated measurements are. The number of significant figures reported in a result should not exceed the least precise value used. The document also discusses determining and expressing uncertainties in measurements, and how to combine uncertainties when performing calculations or graphing data.
Measurement and error
This document provides an overview of the DEE1012 measurement course. It outlines the course learning outcomes, which are to apply measurement principles and solve problems using measuring operations and theorems. The document then details several topics that will be covered in the course, including the measurement process, elements of a measurement system, types of errors, measurement terminology, characteristics of measurement, and standards used in measurement. Examples are provided to illustrate key concepts. References are listed at the end.
Measurement Errors and Standards
This document discusses measurement errors and standards. It defines key terms related to measurement accuracy and precision. Accuracy is the closeness of a measurement to the true value, while precision refers to the consistency of repeated measurements. Errors can be absolute or relative. Systematic errors are due to instrument flaws, while random errors have unknown causes. The document also discusses limiting/guarantee errors, which specify the maximum allowed deviation from a component's rated value. Resolution refers to the smallest detectable change in a measurement. Sensitivity is the change in output per unit change in input.
Absolute relative error
Absolute and relative error are two types of error that scientists should be familiar with. Absolute error is the physical error in a measurement, while relative error gives an indication of how good a measurement is relative to the size of the thing being measured. Absolute error is calculated as the amount of error, while relative error is calculated as the absolute error divided by the value of the thing measured. This allows comparisons of accuracy between measurements even if the absolute error is the same.
Physical measurement and error analysis
This document discusses physical measurement and errors in measurement. It defines key terms like measurement, units, observations, and least count. It describes the International System of Units (SI) as the modern metric system. It also discusses different types of errors like absolute error and relative error. Systematic errors can be corrected while random errors are reduced by taking multiple measurements. Accuracy refers to systematic errors while precision describes random errors. The document outlines methods to calculate propagation of errors and statistical treatment of error values.
Chapter 1(5)Measurement and Error
This document discusses terminology and concepts related to measurement and error. It defines true value, accuracy, and precision. There are two types of errors - determinate (systematic) errors which have a known cause, and indeterminate (random) errors which cannot be determined. Accuracy refers to closeness to the true value while precision refers to reproducibility. The standard deviation allows for more variation in a sample compared to the population. When combining uncertainties from multiple measurements, relative uncertainties should be summed for multiplication and division, while absolute uncertainties are summed for addition and subtraction. Significant figures refer to the reliable digits in a measurement and rules govern how many are retained in calculations.
Error analytical
This document discusses experimental errors in scientific measurements. It defines experimental error as the difference between a measured value and the true value. Experimental errors can be classified as systematic errors or random errors. Systematic errors affect accuracy and can result from faulty instruments, while random errors affect precision and arise from unpredictable fluctuations. The document also discusses ways to quantify and describe experimental errors, including percent error, percent difference, mean, and significant figures. Understanding experimental errors is important for analyzing measurement uncertainties and improving experimental design.
1 measurement and error
The document discusses measurement errors and standards. It defines key terms like instruments, measurements, standards, and different types of errors. It explains absolute and relative errors, accuracy, precision and resolution. It discusses sources of errors like gross errors, systematic errors from instruments and environment, and random errors. Finally, it categorizes measurement standards into international, primary, secondary and working standards based on their accuracy and purpose.
Topic 2 error & uncertainty- part 3
This document discusses errors and uncertainty in measurement. It defines error as the difference between an individual measurement and the true value. Errors can be random or systematic. Sources of error include the measuring instrument, the item being measured, the measurement process, and environmental factors. There are two types of uncertainty - type A which is evaluated statistically from repeated measurements, and type B which is evaluated from other sources like specifications or published data. Calculating uncertainty involves identifying sources of uncertainty, estimating individual uncertainties, and combining them to obtain an overall measurement uncertainty.
Diploma sem 2 applied science physics-unit 1-chap 2 error s
This document discusses various types of errors that can occur in measurements. It describes instrumental error, observer error, and procedural error as the three main sources of uncertainty. It also defines accuracy as a measure of how close a measurement is to the accepted value, while precision refers to the closeness of repeated measurements. The document provides examples of calculating percentage error, relative error, and discusses significant figures when taking measurements.
Instrumentation & Measurement: Error and Its Types
There are three main types of errors in measurement: gross errors due to human mistakes, systematic errors due to issues with instruments or environment, and random errors due to unknown causes. When quantities are calculated from multiple measurements, the total error is determined by combining the individual errors based on the calculation - for addition/subtraction it is the sum of the absolute errors, for multiplication/division it is the sum of the percentage errors, and for powers it is the power multiplied by the percentage error. Proper instrument selection, calibration, and accounting for errors can help reduce systematic and random errors.
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This document discusses measurement and data processing. It describes random uncertainties and systematic errors, and distinguishes between precision and accuracy. It explains that random uncertainties can be reduced by taking multiple measurements, while systematic errors must be corrected before an investigation. Precision refers to the closeness of repeated measurements, while accuracy refers to how close measurements are to the true value. The document also covers uncertainty ranges, significant figures, absolute and percentage uncertainties, and how uncertainties are treated in calculations. It provides examples of plotting graphs and determining the line of best fit.
Errors and uncertainties
This is a lecture note on Error and its propagation. This slide can be very much useful for As level physics students. It is totally different from the presentation. I would like to name it as slides of lecture notes on Error(uncertainty), difference on precision and accuracy, difference on two types of error (systematic and random errors). Believe me it will help you to enhance your knowledge on Uncertainty and its propagarion.
Errors and uncertainties
This document discusses different types of errors in experimental measurements and calculations. It describes random errors, which vary unpredictably, and systematic errors, which are consistent biases. Random errors can be reduced by taking more trials, while systematic errors must be accounted for. Mistakes are distinguished from errors. Significant figures rules for measurements and calculations are explained. The concepts of uncertainty, including limits of reading, degrees of uncertainty, absolute and relative uncertainty, and uncertainty propagation through calculations, are introduced.
Measurement & Error
I split the presentation for the unit into two, as I added so many slides to help with student questions and misconceptions. This one focuses on mathematical aspects of the unit.
errors of measurement and systematic errors
This document discusses measurement errors and uncertainty. It defines measurement as assigning a number and unit to a property using an instrument. Error is the difference between the measured value and true value. There are two main types of error: random error, which varies unpredictably, and systematic error, which remains constant or varies predictably. Sources of error include the measuring instrument and technique used. Uncertainty is the doubt about a measurement and is quantified with an interval and confidence level, such as 20 cm ±1 cm at 95% confidence. Uncertainty is important for tasks like calibration where it must be reported.
Accuracy, Precision Measurement
Accuracy refers to how close a measurement is to the true value, while precision refers to the reproducibility of measurements. Accuracy is determined by calculating percentage error compared to the accepted value. Precision depends on the number of significant figures in a measurement as determined by the measuring tool. Random and systematic errors can affect accuracy, while random errors affect precision. The uncertainty of a measurement combines its precision and accuracy errors and is reported with the mean value and at a given confidence level, typically 95%. Propagation of error calculations allow determining the total uncertainty when a value depends on multiple measurements.
Error in measurement
Errors and uncertainties are inherent in the process of making any measurement and in the instrument with which the measurement are made.
Errors and uncertainty
All physical measurements have an associated uncertainty that reflects errors involved. There are two types of errors - random errors which are out of the measurer's control and can be reduced through repeat readings, and systematic errors from instruments which can be reduced through calibration. The uncertainty is the smallest division on the instrument for systematic errors, and for random errors it can be determined from the range of repeat readings.
Measurement errors, Statistical Analysis, Uncertainty
The Presentation covers Measurement Errors and types, Gross error, systematic error, absolute error and relative error, accuracy, precision, resolution and significant figures, Measurement error combination, basics of statistical analysis, uncertainty, Gaussian Curve, Meaning of Ranges
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Measurements and estimations involve uncertainty that arises from imprecision, random errors, and systematic errors. Numbers can be categorized as exact or approximate, with approximations involving uncertainty. Uncertainty must be expressed either implicitly by careful rounding or explicitly using ranges. Significant digits indicate the precision of measurements and estimations, and implied uncertainty ranges can be determined from them. When combining approximate values, answers must be rounded or expressed as ranges consistent with the least precise input to properly account for accumulated uncertainties.
Introduction to measurement uncertainty
This document provides an introduction to uncertainty measurements. It explains that there is always uncertainty involved when taking measurements as values can vary depending on factors like how, when and where something is measured. It describes the two main sources of uncertainty as random errors which are unpredictable, and systematic errors which are constant. The document then outlines the process for calculating uncertainty which involves taking multiple readings to determine standard deviation and uncertainty (Type A), and combining various uncertainty components from calibration certificates and manufacturers alongside sensitivity coefficients to determine combined and expanded uncertainty using a normal distribution with 95% confidence (Type B). It emphasizes that the process is the same for measurements in decibels or real numbers but the calculations are different.
Errors in measurement
This document discusses errors in measurement and different types of errors. It explains that there are five main elements that can cause errors: standards, work pieces, instruments, persons, and environment. There are three types of errors: systematic errors, which occur due to imperfections and are of fixed magnitude; random errors, which occur irregularly; and statistical analysis can be used to analyze random errors through calculations of mean, range, deviation, and standard deviation. Systematic errors include instrumental errors from faulty instruments, environmental errors from external conditions, and observational errors from human factors like parallax.
Measurement And Error
There are two main types of errors in measurement: systematic errors, which always produce results in the same direction, and random errors, which occur unpredictably due to various factors. The accuracy of a measurement indicates how close it is to the accepted value, while the precision refers to the agreement between multiple measurements of the same quantity. Taking the average of repeated measurements reduces the impact of random errors, but the uncertainty in any measurement must be reported using plus-and-minus values to indicate the possible variance.
Measurement
The document discusses various concepts related to measurement and error including:
- Defining accuracy as closeness to the true value and precision as reproducibility of measurements.
- Types of errors such as determinate/systematic errors which can be corrected and indeterminate/random errors which average out with multiple trials.
- Assessing total error by treating a reference standard as a sample and calculating differences from the reference value.
- Expressing accuracy and precision using terms like mean, percent error, range, standard deviation, and percent coefficient of variation.
Errors and uncertainties in physics
Every measurement has uncertainty that arises from limitations in measuring devices, techniques, and the inherent variability in what is being measured. There are several types of uncertainty: absolute uncertainty is the value given directly by the measurement; fractional and percent uncertainties relate the absolute uncertainty to the measured value. The proper method for determining the combined uncertainty when calculations are performed on measurements depends on whether values are added, subtracted, multiplied, divided, or raised to a power. Accounting accurately for uncertainty is crucial for scientific validity.
instrumentation electrical engineering Lecture 1.2.pptx
The document discusses secondary instruments used for measurement. It defines secondary instruments as those that must be calibrated by comparison with an absolute instrument or another calibrated secondary instrument. Secondary instruments are further classified as indicating, integrating, and recording instruments. Indicating instruments show the magnitude of a quantity, integrating instruments measure total quantity or energy over time, and recording instruments provide a continuous record of a quantity's variation over a period of time through pen tracings. The document also discusses concepts such as precision, accuracy, resolution uncertainty, types of errors including gross, systematic, and random, and the loading effect.
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This document discusses the functional elements, static and dynamic characteristics, and errors in measurement instruments. It describes the key components of instruments including sensing elements, variable conversion/manipulation elements, and data presentation/transmission elements. Static characteristics like accuracy, sensitivity, linearity, and resolution do not vary with time, while dynamic characteristics like speed of response and measuring lag do vary with time. Errors can be gross, systematic including due to instruments and environment, or random. Statistical analysis is used to evaluate random errors in measurement data. Calibration against standards is important to ensure instrument accuracy.
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Error analytical
This document discusses experimental errors in scientific measurements. It defines experimental error as the difference between a measured value and the true value. Experimental errors can be classified as systematic errors or random errors. Systematic errors affect accuracy and can result from faulty instruments, while random errors affect precision and arise from unpredictable fluctuations. The document also discusses ways to quantify and describe experimental errors, including percent error, percent difference, mean, and significant figures. Understanding experimental errors is important for analyzing measurement uncertainties and improving experimental design.
1 measurement and error
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This document discusses errors and uncertainty in measurement. It defines error as the difference between an individual measurement and the true value. Errors can be random or systematic. Sources of error include the measuring instrument, the item being measured, the measurement process, and environmental factors. There are two types of uncertainty - type A which is evaluated statistically from repeated measurements, and type B which is evaluated from other sources like specifications or published data. Calculating uncertainty involves identifying sources of uncertainty, estimating individual uncertainties, and combining them to obtain an overall measurement uncertainty.
Diploma sem 2 applied science physics-unit 1-chap 2 error s
This document discusses various types of errors that can occur in measurements. It describes instrumental error, observer error, and procedural error as the three main sources of uncertainty. It also defines accuracy as a measure of how close a measurement is to the accepted value, while precision refers to the closeness of repeated measurements. The document provides examples of calculating percentage error, relative error, and discusses significant figures when taking measurements.
Instrumentation & Measurement: Error and Its Types
There are three main types of errors in measurement: gross errors due to human mistakes, systematic errors due to issues with instruments or environment, and random errors due to unknown causes. When quantities are calculated from multiple measurements, the total error is determined by combining the individual errors based on the calculation - for addition/subtraction it is the sum of the absolute errors, for multiplication/division it is the sum of the percentage errors, and for powers it is the power multiplied by the percentage error. Proper instrument selection, calibration, and accounting for errors can help reduce systematic and random errors.
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This document discusses measurement and data processing. It describes random uncertainties and systematic errors, and distinguishes between precision and accuracy. It explains that random uncertainties can be reduced by taking multiple measurements, while systematic errors must be corrected before an investigation. Precision refers to the closeness of repeated measurements, while accuracy refers to how close measurements are to the true value. The document also covers uncertainty ranges, significant figures, absolute and percentage uncertainties, and how uncertainties are treated in calculations. It provides examples of plotting graphs and determining the line of best fit.
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This is a lecture note on Error and its propagation. This slide can be very much useful for As level physics students. It is totally different from the presentation. I would like to name it as slides of lecture notes on Error(uncertainty), difference on precision and accuracy, difference on two types of error (systematic and random errors). Believe me it will help you to enhance your knowledge on Uncertainty and its propagarion.
Errors and uncertainties
This document discusses different types of errors in experimental measurements and calculations. It describes random errors, which vary unpredictably, and systematic errors, which are consistent biases. Random errors can be reduced by taking more trials, while systematic errors must be accounted for. Mistakes are distinguished from errors. Significant figures rules for measurements and calculations are explained. The concepts of uncertainty, including limits of reading, degrees of uncertainty, absolute and relative uncertainty, and uncertainty propagation through calculations, are introduced.
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I split the presentation for the unit into two, as I added so many slides to help with student questions and misconceptions. This one focuses on mathematical aspects of the unit.
errors of measurement and systematic errors
This document discusses measurement errors and uncertainty. It defines measurement as assigning a number and unit to a property using an instrument. Error is the difference between the measured value and true value. There are two main types of error: random error, which varies unpredictably, and systematic error, which remains constant or varies predictably. Sources of error include the measuring instrument and technique used. Uncertainty is the doubt about a measurement and is quantified with an interval and confidence level, such as 20 cm ±1 cm at 95% confidence. Uncertainty is important for tasks like calibration where it must be reported.
Accuracy, Precision Measurement
Accuracy refers to how close a measurement is to the true value, while precision refers to the reproducibility of measurements. Accuracy is determined by calculating percentage error compared to the accepted value. Precision depends on the number of significant figures in a measurement as determined by the measuring tool. Random and systematic errors can affect accuracy, while random errors affect precision. The uncertainty of a measurement combines its precision and accuracy errors and is reported with the mean value and at a given confidence level, typically 95%. Propagation of error calculations allow determining the total uncertainty when a value depends on multiple measurements.
Error in measurement
Errors and uncertainties are inherent in the process of making any measurement and in the instrument with which the measurement are made.
Errors and uncertainty
All physical measurements have an associated uncertainty that reflects errors involved. There are two types of errors - random errors which are out of the measurer's control and can be reduced through repeat readings, and systematic errors from instruments which can be reduced through calibration. The uncertainty is the smallest division on the instrument for systematic errors, and for random errors it can be determined from the range of repeat readings.
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Measurements and estimations involve uncertainty that arises from imprecision, random errors, and systematic errors. Numbers can be categorized as exact or approximate, with approximations involving uncertainty. Uncertainty must be expressed either implicitly by careful rounding or explicitly using ranges. Significant digits indicate the precision of measurements and estimations, and implied uncertainty ranges can be determined from them. When combining approximate values, answers must be rounded or expressed as ranges consistent with the least precise input to properly account for accumulated uncertainties.
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This document provides an introduction to uncertainty measurements. It explains that there is always uncertainty involved when taking measurements as values can vary depending on factors like how, when and where something is measured. It describes the two main sources of uncertainty as random errors which are unpredictable, and systematic errors which are constant. The document then outlines the process for calculating uncertainty which involves taking multiple readings to determine standard deviation and uncertainty (Type A), and combining various uncertainty components from calibration certificates and manufacturers alongside sensitivity coefficients to determine combined and expanded uncertainty using a normal distribution with 95% confidence (Type B). It emphasizes that the process is the same for measurements in decibels or real numbers but the calculations are different.
Errors in measurement
This document discusses errors in measurement and different types of errors. It explains that there are five main elements that can cause errors: standards, work pieces, instruments, persons, and environment. There are three types of errors: systematic errors, which occur due to imperfections and are of fixed magnitude; random errors, which occur irregularly; and statistical analysis can be used to analyze random errors through calculations of mean, range, deviation, and standard deviation. Systematic errors include instrumental errors from faulty instruments, environmental errors from external conditions, and observational errors from human factors like parallax.
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There are two main types of errors in measurement: systematic errors, which always produce results in the same direction, and random errors, which occur unpredictably due to various factors. The accuracy of a measurement indicates how close it is to the accepted value, while the precision refers to the agreement between multiple measurements of the same quantity. Taking the average of repeated measurements reduces the impact of random errors, but the uncertainty in any measurement must be reported using plus-and-minus values to indicate the possible variance.
Measurement
The document discusses various concepts related to measurement and error including:
- Defining accuracy as closeness to the true value and precision as reproducibility of measurements.
- Types of errors such as determinate/systematic errors which can be corrected and indeterminate/random errors which average out with multiple trials.
- Assessing total error by treating a reference standard as a sample and calculating differences from the reference value.
- Expressing accuracy and precision using terms like mean, percent error, range, standard deviation, and percent coefficient of variation.
Errors and uncertainties in physics
Every measurement has uncertainty that arises from limitations in measuring devices, techniques, and the inherent variability in what is being measured. There are several types of uncertainty: absolute uncertainty is the value given directly by the measurement; fractional and percent uncertainties relate the absolute uncertainty to the measured value. The proper method for determining the combined uncertainty when calculations are performed on measurements depends on whether values are added, subtracted, multiplied, divided, or raised to a power. Accounting accurately for uncertainty is crucial for scientific validity.
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Errors
- 2. • Gross Errors • Random Errors • Systematic Errors – Instrumental Errors – Environmental – Observational
- 3. • Instrumental Errors: • Due to inherent shortcomings in the instrument: Due to mechanical structure, construction, calibration or operation of instruments. • Due to misuse of instruments: Failure to adjust zero of instruments, poor initial adjustments, using leads of too high resistance. • Due to loading effects of instruments:
- 4. Environmental Errors: • Errors due to temperature effect, humidity, dust, external magnetic or electrostatic field. Corrective measures: • Try to keep the conditions constant. • Use material which is immune to these effects. • Using techniques which eliminates these effects. • use air conditioner • sealing certain component in the instruments • use magnetic shields
- 5. Observational error - introduce by the observer - most common : parallax error and estimation error (while reading the scale) • Eg: an observer who tend to hold his head too far to the left, while reading the position of the needle on the scale.
- 6. Random Errors • Random errors in experimental measurements are caused by unknown and unpredictable changes in the experiment. • These changes may occur in the measuring instruments or in the environmental conditions. Examples of causes of random errors are: • electronic noise in the circuit of an electrical instrument, • irregular changes in the heat loss rate from a solar collector due to changes in the wind.
- 7. • Look at this ammeter: • What can you say?
- 8. • Look at this voltmeter: • Zero errors What is the first thing to do? • Use a screwdriver here to adjust the pointer.
- 9. • A spring balance: Zero errors • Over a period of time, the spring may weaken, and so the pointer
- 10. Dynamic Characteristics The dynamic characteristics of a measurement system are: 1)Speed of response 2)Fidelity 3)Lag 4)Dynamic error
- 11. Speed of response It is defined as the rapidity with which an instrument, responds to the changes in the measured quantity. • It shows how active and fast the system is. • Speed measuring instruments:-
- 12. Fidelity It is defined as the degree to which a measurement system is capable of faithfully reproducing the changes in input, without any dynamic error.
- 13. Measuring lag Every system requires its own time to respond to the changes in input. This time is called as lag. • It is defined as the retardation or delay, in the response of a system to the changes in the input. • The lags are of two types: 1. Retardation lag: • As soon as there is a changes in the measured quantity, the measurement system begins to respond. 2. Time delay: • The response of the measurement system starts after a dead time, once the input is applied. They cause dynamic error.
- 14. Dynamic error • It is the difference between the true value of the quantity that is to be measured, changing with time and the measured value, if no static error is assumed.