1. Accuracy refers to how close a measurement is to the actual value, while precision describes the consistency of repeated measurements.
2. Measurement uncertainty comes from systematic errors in instruments and random errors from noise. Total uncertainty is calculated by combining the uncertainties.
3. Improving precision involves averaging measurements to reduce noise, but this may reduce bandwidth. Resolution is the smallest distinguishable difference in values.
The document discusses measurement, calibration, and units of measurement. Some key points:
- Measurement is the first step to control and improvement. If you can't measure something, you can't understand or control it.
- The International System of Units (SI) defines seven base units including the meter, kilogram, second, ampere, kelvin, mole, and candela. Other units are derived from these base units.
- Calibration establishes the relationship between measurement instruments and reference standards under specific conditions. Regular calibration helps ensure accuracy and traceability to national standards.
- Factors like instrument specifications, use, environment, and measurement accuracy needed should be considered when determining calibration frequency.
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.
Alternating current signal
AC means Alternating Current and DC means Direct Current. AC and DC are also used when referring to voltages and electrical signals which are not currents! For example: a 12V AC power supply has an alternating voltage (which will make an alternating current flow).
Generalized Measurement System is a measuring system exists to provide information about the physical value of some variable being measured. In this presentation, generalized measurement system, its elements, classification of instruments, classification of measurement methods, difference between mechanical and electrical measurement systems, input output characteristics are described.
This lecture introduces measurement and instrumentation. It defines measurement and instrumentation, discusses types of measurements and instruments. It reviews units of measurement, standards of measurement, and calibration. Measurement and instrumentation are used in various applications including home appliances, vehicles, and industrial processes to monitor and control parameters and improve operations.
1) The document discusses various standards and units of measurement including fundamental and derived units.
2) It describes different types of standards including international, primary, secondary, working, current, voltage, resistance, capacitance, and time/frequency standards.
3) The key points are that standards define units of measurement and are classified based on their level of accuracy and use from international to working standards used in laboratories.
This document discusses instrumentation and measurement techniques used to gather performance data from programs. It describes:
- Program, binary, dynamic, processor, operating system, and network instrumentation techniques to collect data on software components, hardware usage, and network traffic.
- The Paradyn performance analysis tool, which uses dynamic instrumentation to monitor metrics, store data in histograms and traces, and employs a "Why, Where, When" search model to diagnose potential performance problems in parallel applications.
- How the Performance Consultant module in Paradyn automatically searches the problem space defined by the "Why, Where, When" axes to discover performance issues by evaluating hypotheses tests against collected metrics.
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.
The document discusses measurement, calibration, and units of measurement. Some key points:
- Measurement is the first step to control and improvement. If you can't measure something, you can't understand or control it.
- The International System of Units (SI) defines seven base units including the meter, kilogram, second, ampere, kelvin, mole, and candela. Other units are derived from these base units.
- Calibration establishes the relationship between measurement instruments and reference standards under specific conditions. Regular calibration helps ensure accuracy and traceability to national standards.
- Factors like instrument specifications, use, environment, and measurement accuracy needed should be considered when determining calibration frequency.
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.
Alternating current signal
AC means Alternating Current and DC means Direct Current. AC and DC are also used when referring to voltages and electrical signals which are not currents! For example: a 12V AC power supply has an alternating voltage (which will make an alternating current flow).
Generalized Measurement System is a measuring system exists to provide information about the physical value of some variable being measured. In this presentation, generalized measurement system, its elements, classification of instruments, classification of measurement methods, difference between mechanical and electrical measurement systems, input output characteristics are described.
This lecture introduces measurement and instrumentation. It defines measurement and instrumentation, discusses types of measurements and instruments. It reviews units of measurement, standards of measurement, and calibration. Measurement and instrumentation are used in various applications including home appliances, vehicles, and industrial processes to monitor and control parameters and improve operations.
1) The document discusses various standards and units of measurement including fundamental and derived units.
2) It describes different types of standards including international, primary, secondary, working, current, voltage, resistance, capacitance, and time/frequency standards.
3) The key points are that standards define units of measurement and are classified based on their level of accuracy and use from international to working standards used in laboratories.
This document discusses instrumentation and measurement techniques used to gather performance data from programs. It describes:
- Program, binary, dynamic, processor, operating system, and network instrumentation techniques to collect data on software components, hardware usage, and network traffic.
- The Paradyn performance analysis tool, which uses dynamic instrumentation to monitor metrics, store data in histograms and traces, and employs a "Why, Where, When" search model to diagnose potential performance problems in parallel applications.
- How the Performance Consultant module in Paradyn automatically searches the problem space defined by the "Why, Where, When" axes to discover performance issues by evaluating hypotheses tests against collected metrics.
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.
Measurement errors, Statistical Analysis, UncertaintyDr Naim R Kidwai
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
Systematic and random errors in measurement.pptxLalitKishore18
This document discusses different types of errors that can arise in measurement in physics experiments. It describes systematic errors, which are consistent biases in measurements, and random errors, which cause scattered readings. Systematic errors cannot be reduced by taking multiple readings, but may be reduced by improving techniques. Random errors can be decreased by taking the average of several readings. The document provides examples of different systematic and random errors and how to combine the uncertainties from multiple measurements to determine the total uncertainty.
Thermocouples are temperature measurement devices that produce a voltage when two different conductors contact each other at different temperatures. The voltage is proportional to the temperature difference and relies on the Seebeck effect where a temperature gradient along conductors generates an electric current. Common thermocouple types use different metal combinations like chromel-iron and alumel-constantan wired into a circuit to measure temperature in various applications such as steel production, gas appliances, and vacuum gauges.
Ammeter, voltmeter, wattmeter, power factor meterHome
What is Ammeter, its working principle and its three Ammeter method. What is Voltmeter, working principle and three Voltmeter Method. Watt meter and its working principle.
A transducer is a device that converts one form of energy to another. The document discusses different types of transducers including active and passive transducers. It describes various transducers such as thermocouples, LVDTs, RVDTs, and capacitive transducers. Capacitive transducers can be used to measure variables like pressure, displacement, force, and liquid level by detecting changes in capacitance. The document provides details on the operating principles, advantages, and disadvantages of these transducers.
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.
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.
The instrument which gives output that varies continuously as quantity to be measured is known as analog instrument.
The instrument which gives output that varies in discrete steps and only has finite number of values is known as digital instrument.
The presentation explain principal, working and construction and application of Potentiometer it is useful for senior secondary students of Indian school
Analytical instrumentation provides qualitative and quantitative information about the composition of samples. It comprises four basic elements - a chemical information source, transducers, signal conditioners, and a display system. The document discusses analytical methods, selecting an appropriate method, understanding the measurement process, uses of microcomputers, Beer-Lambert law, spectroscopy, radiation sources, optical fibers, monochromators, and detectors.
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.
The document discusses accuracy and precision in measurement. It defines accuracy as how close a measurement is to the actual value, which depends on the person measuring. Precision refers to how finely tuned or close together measurements are, which depends on the measuring tool. Accuracy and precision are demonstrated through shooting at a target, where accuracy is hitting the bullseye and precision is a tight grouping of shots. Exact numbers come from counting or defined relationships, while measured numbers use a measuring tool and require estimation.
Chapter-1_Mechanical Measurement and Metrologysudhanvavk
This document outlines the objectives and content of a course on instrumentation. The course aims to teach students about advances in technology and measurement techniques. It will cover various flow measurement techniques. The course outcomes are listed, along with the cognitive level and linked program outcomes for each. The teaching hours for each unit are provided. The document gives an overview of the course content and blueprint of marks for the semester end exam. It provides details on the units to be covered, including measuring instruments, transducers and strain gauges, measurement of force, torque and pressure, and more.
Static and dynamic characteristics of instrumentsfreddyuae
Static characteristics describe an instrument's performance when measuring quantities that remain constant or vary slowly. They include properties like linearity, sensitivity, resolution, repeatability, hysteresis, and environmental effects. Dynamic characteristics describe how the instrument responds when the measured quantity varies rapidly over time. Instruments can be modeled as a series of blocks, each with their own static and dynamic transfer functions. The overall static and dynamic responses are obtained by multiplying the individual block transfer functions. Characterizing both the static and dynamic behavior is important for understanding an instrument's performance.
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.
The static characteristics are defined for the instruments which measure quantities which do not vary with time. ... The accuracy of a measurement indicates the nearness to the actual/true value of the quantity. 7. 2.Sensitivity Sensitivity is the ratio of change in output of an instrument to the change in input.
This document discusses different types of electrodes used to measure electrical activity in the body. It describes various classifications of transducers including passive vs active, absolute vs relative, direct vs complex, analog vs digital, and primary vs secondary. It also explains different electrode principles such as capacitive, inductive, and resistive. The document outlines types of electrodes like surface electrodes, needle electrodes, and microelectrodes and provides examples of each. It discusses factors to consider when selecting a transducer and electrodes used to measure specific physiological variables.
This course is electronics based course dealing with measurements and instrumentation designed for students in Physics Electronics, Electrical and Electronics Engineering and allied disciplines. It is a theory course based on the use of electrical and electronics instruments for measurements. The course deals with topics such as Principle of measurements, Errors, Accuracy, Units of measurements and electrical standards, , introduction to the design of electronic equipment’s for temperature, pressure, level, flow measurement, speed etc
Electronics measurement and instrumentation pptImranAhmad225
This document defines key concepts in measurement and instrumentation. It discusses the definition of metrology and engineering metrology. Measurement is defined as the process of numerical evaluation of a dimension or comparison to a standard. Some key methods of measurement discussed are direct, indirect, comparative, coincidence, contact, deflection, and complementary methods. The document also discusses units and standards, characteristics of measuring instruments like sensitivity, readability, range, accuracy, and precision. It defines uncertainty and errors in instruments.
This document discusses sources of error in measurement and the importance of accuracy. It explains that random errors can cause inconsistent readings and averaging repeated measurements can reduce these errors. Common sources of error include instrument errors, non-linear relationships in instruments, errors from reading scales incorrectly, environmental factors, and human errors. Taking the average of multiple readings eliminates random variations between readings and provides a more accurate result.
1) The document discusses measurement and error in engineering. It covers characteristics of measuring instruments such as accuracy, precision, sensitivity, and error.
2) Accuracy refers to how close a measurement is to the true value, while precision refers to the reproducibility of measurements. Systematic errors can be corrected, while random errors average out over multiple trials.
3) Significant figures indicate the precision of a measurement. The number of significant figures retained in calculations is determined by the least precise measurement.
Measurement errors, Statistical Analysis, UncertaintyDr Naim R Kidwai
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
Systematic and random errors in measurement.pptxLalitKishore18
This document discusses different types of errors that can arise in measurement in physics experiments. It describes systematic errors, which are consistent biases in measurements, and random errors, which cause scattered readings. Systematic errors cannot be reduced by taking multiple readings, but may be reduced by improving techniques. Random errors can be decreased by taking the average of several readings. The document provides examples of different systematic and random errors and how to combine the uncertainties from multiple measurements to determine the total uncertainty.
Thermocouples are temperature measurement devices that produce a voltage when two different conductors contact each other at different temperatures. The voltage is proportional to the temperature difference and relies on the Seebeck effect where a temperature gradient along conductors generates an electric current. Common thermocouple types use different metal combinations like chromel-iron and alumel-constantan wired into a circuit to measure temperature in various applications such as steel production, gas appliances, and vacuum gauges.
Ammeter, voltmeter, wattmeter, power factor meterHome
What is Ammeter, its working principle and its three Ammeter method. What is Voltmeter, working principle and three Voltmeter Method. Watt meter and its working principle.
A transducer is a device that converts one form of energy to another. The document discusses different types of transducers including active and passive transducers. It describes various transducers such as thermocouples, LVDTs, RVDTs, and capacitive transducers. Capacitive transducers can be used to measure variables like pressure, displacement, force, and liquid level by detecting changes in capacitance. The document provides details on the operating principles, advantages, and disadvantages of these transducers.
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.
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.
The instrument which gives output that varies continuously as quantity to be measured is known as analog instrument.
The instrument which gives output that varies in discrete steps and only has finite number of values is known as digital instrument.
The presentation explain principal, working and construction and application of Potentiometer it is useful for senior secondary students of Indian school
Analytical instrumentation provides qualitative and quantitative information about the composition of samples. It comprises four basic elements - a chemical information source, transducers, signal conditioners, and a display system. The document discusses analytical methods, selecting an appropriate method, understanding the measurement process, uses of microcomputers, Beer-Lambert law, spectroscopy, radiation sources, optical fibers, monochromators, and detectors.
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.
The document discusses accuracy and precision in measurement. It defines accuracy as how close a measurement is to the actual value, which depends on the person measuring. Precision refers to how finely tuned or close together measurements are, which depends on the measuring tool. Accuracy and precision are demonstrated through shooting at a target, where accuracy is hitting the bullseye and precision is a tight grouping of shots. Exact numbers come from counting or defined relationships, while measured numbers use a measuring tool and require estimation.
Chapter-1_Mechanical Measurement and Metrologysudhanvavk
This document outlines the objectives and content of a course on instrumentation. The course aims to teach students about advances in technology and measurement techniques. It will cover various flow measurement techniques. The course outcomes are listed, along with the cognitive level and linked program outcomes for each. The teaching hours for each unit are provided. The document gives an overview of the course content and blueprint of marks for the semester end exam. It provides details on the units to be covered, including measuring instruments, transducers and strain gauges, measurement of force, torque and pressure, and more.
Static and dynamic characteristics of instrumentsfreddyuae
Static characteristics describe an instrument's performance when measuring quantities that remain constant or vary slowly. They include properties like linearity, sensitivity, resolution, repeatability, hysteresis, and environmental effects. Dynamic characteristics describe how the instrument responds when the measured quantity varies rapidly over time. Instruments can be modeled as a series of blocks, each with their own static and dynamic transfer functions. The overall static and dynamic responses are obtained by multiplying the individual block transfer functions. Characterizing both the static and dynamic behavior is important for understanding an instrument's performance.
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.
The static characteristics are defined for the instruments which measure quantities which do not vary with time. ... The accuracy of a measurement indicates the nearness to the actual/true value of the quantity. 7. 2.Sensitivity Sensitivity is the ratio of change in output of an instrument to the change in input.
This document discusses different types of electrodes used to measure electrical activity in the body. It describes various classifications of transducers including passive vs active, absolute vs relative, direct vs complex, analog vs digital, and primary vs secondary. It also explains different electrode principles such as capacitive, inductive, and resistive. The document outlines types of electrodes like surface electrodes, needle electrodes, and microelectrodes and provides examples of each. It discusses factors to consider when selecting a transducer and electrodes used to measure specific physiological variables.
This course is electronics based course dealing with measurements and instrumentation designed for students in Physics Electronics, Electrical and Electronics Engineering and allied disciplines. It is a theory course based on the use of electrical and electronics instruments for measurements. The course deals with topics such as Principle of measurements, Errors, Accuracy, Units of measurements and electrical standards, , introduction to the design of electronic equipment’s for temperature, pressure, level, flow measurement, speed etc
Electronics measurement and instrumentation pptImranAhmad225
This document defines key concepts in measurement and instrumentation. It discusses the definition of metrology and engineering metrology. Measurement is defined as the process of numerical evaluation of a dimension or comparison to a standard. Some key methods of measurement discussed are direct, indirect, comparative, coincidence, contact, deflection, and complementary methods. The document also discusses units and standards, characteristics of measuring instruments like sensitivity, readability, range, accuracy, and precision. It defines uncertainty and errors in instruments.
This document discusses sources of error in measurement and the importance of accuracy. It explains that random errors can cause inconsistent readings and averaging repeated measurements can reduce these errors. Common sources of error include instrument errors, non-linear relationships in instruments, errors from reading scales incorrectly, environmental factors, and human errors. Taking the average of multiple readings eliminates random variations between readings and provides a more accurate result.
1) The document discusses measurement and error in engineering. It covers characteristics of measuring instruments such as accuracy, precision, sensitivity, and error.
2) Accuracy refers to how close a measurement is to the true value, while precision refers to the reproducibility of measurements. Systematic errors can be corrected, while random errors average out over multiple trials.
3) Significant figures indicate the precision of a measurement. The number of significant figures retained in calculations is determined by the least precise measurement.
1) The document discusses various concepts related to measurement principles including accuracy, precision, resolution, sensitivity and error.
2) It describes different types of errors like gross error, systematic error and random error. Systematic error includes instrumental, environmental and observational errors.
3) Accuracy refers to the closeness of a measurement to the true value. Precision refers to the consistency of repeated measurements. Accuracy and precision are related but distinct measures of measurement quality.
Errors occur in measurement due to factors like parallax error, calibration error, damage to the device, and limits of the measurement device. There are three types of errors - gross errors due to human mistakes, systematic errors related to the instrument or environment, and random errors from unknown factors. Statistical analysis of experimental data involves calculating values like the mean, range, standard deviation, and variance to quantify the dispersion of measurements from the mean value.
The document discusses the key characteristics and performance parameters of measuring instruments. It describes:
1) Static characteristics relate to constant or slowly varying inputs over time and include parameters like accuracy, precision, resolution, sensitivity, and linearity.
2) Dynamic characteristics relate to rapidly varying inputs over time and are represented by differential equations.
3) Measuring instruments are evaluated based on both their static and dynamic characteristics, with static characteristics being most important for time-independent signals.
R = R0(1 + α(t - 20))
- The resistance (R) of a copper wire is calculated using a formula that relates it to the resistance at 20°C (R0), the coefficient of resistance (α), and the temperature (t).
- R0 is given as 6Ω with an uncertainty of ±0.3%.
- To determine the uncertainty in R, the uncertainties in R0, α, and t must be determined and propagated through the equation using partial derivatives.
- The overall uncertainty in R combines the individual uncertainties from each variable according to the propagation of uncertainty formula.
This document provides an overview of standards of measurement and discusses key concepts:
- Standards are classified as primary or secondary, with primary standards defining fundamental units and secondary standards calibrated against primary standards.
- Standard units discussed include the meter (length), kilogram (mass), second (time), Kelvin (temperature), candela (light intensity), mole (amount of substance), and ampere (electric current).
- Random and systematic errors are defined, with random errors averaging out over repeated measurements but systematic errors requiring correction. Significant figures and calculating relative/absolute errors are also covered.
This document discusses error analysis and significant figures in measurements. It defines absolute and relative errors, and explains that random errors can be estimated by taking multiple measurements and calculating their standard deviation. Systematic errors result from flaws in the measurement process. The document also provides rules for propagating errors through calculations based on measured values. Measurements should be reported with a number of significant figures consistent with their estimated error.
nstrumentation is the art of science of measurement and control. It is an applied
science that deals with analysis and design of systems for measurement purposes such as
quantify or expressing a variable numerically, determine or ascertain the value
(magnitude) of some particular phenomena, indicate record, register, signal, or perform
some operation on the value it has determined. Measurement is the process of quantifying
input quantity.
The role of measurement in ones country development particularly in the
advancement of science and technology is huge; this is because of the need or eagerness
for understanding of events or physical phenomenon.
The document defines key concepts in measurement systems including accuracy, precision, calibration, sensitivity, hysteresis, repeatability, linearity, and loading effect. It discusses measurement errors like gross errors, systematic errors from instruments and environment, and random errors. The significance of measurement and standardized units is explained. Transducers are defined as devices that convert one form of energy to another, and are classified as primary or secondary and by physical phenomena like electrical, mechanical, or electronic. Measurement systems have detecting elements, transducers, intermediate devices, and terminating devices like oscilloscopes.
This document defines key terms related to instruments and measurement:
- Accuracy refers to how close a measurement is to the true value. It is limited by the instrument's least count.
- Calibration establishes the relationship between instrument readings and measured quantities by comparing to standard instruments.
- Sensitivity is the ratio of change in the instrument reading to the change in the measured quantity. It quantifies how responsive the instrument is.
- Threshold refers to the minimum quantity needed for the instrument to provide a detectable reading.
This document discusses different methods that manufacturers use to specify accuracy in pressure instruments like transducers and transmitters. It explains that accuracy statements can vary between manufacturers and some methods are more conservative than others. The key components of an accuracy statement like linearity, hysteresis, repeatability, and temperature effects are defined. The document recommends that engineers understand how the accuracy is derived and tested to ensure the instrument will meet requirements, as not all accuracy statements provide the same level of information. Root sum squared and best fit straight line specifications are less conservative and may omit important error sources.
The document discusses various methods of measurement used in mechanical engineering. It describes 6 main methods: direct, indirect, comparative, coincidence, deflection, and complementary. The direct method involves measuring a quantity directly using instruments like calipers or micrometers. The indirect method measures related quantities using transducers. Other methods compare an unknown quantity to a standard, detect small differences through alignment, indicate values through deflection, or determine a quantity by combination with a known value. The document also defines key terms in measurement like accuracy, precision, sensitivity, and calibration, and discusses sources of error.
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.
This document provides an introduction to electronic measurements and instrumentation. It discusses typical measurement system architecture including sensors, signal conditioners, analog-to-digital converters, and data storage. It also describes the basic functions of instrumentation systems for indicating, recording, and controlling measurements. Finally, it outlines some key performance characteristics of instruments such as accuracy, resolution, sensitivity, and error analysis.
This document discusses key concepts in analytical chemistry including accuracy, precision, mean, and standard deviation. It defines accuracy as closeness to the true value and notes that perfect accuracy is impossible due to errors. Precision refers to the agreement between repeated measurements and does not ensure accuracy if systematic errors are present. The mean is used to estimate the true value and standard deviation measures the dispersion of results. Good precision alone does not guarantee good accuracy as systematic errors can bias results while maintaining precision.
This document provides an overview of mechanical measurement and metrology. It defines key terms like hysteresis, linearity, resolution, and drift. It discusses the need for measurement, static performance characteristics of instruments like repeatability and accuracy. It also describes the components of a generalized measurement system including the primary sensing element, variable conversion element, data processing element and more. Finally, it covers topics like errors in measurement, objectives of measurement and metrology, and elements that can affect a measuring system.
This document discusses the characteristics of measuring instruments, dividing them into static and dynamic characteristics. Static characteristics describe instruments that measure non-fluctuating quantities, and include scale range, accuracy, precision, error, calibration, resolution, threshold, sensitivity, repeatability, reproducibility, readability, linearity, drift, and hysteresis. Dynamic characteristics apply to instruments that measure fluctuating quantities over time, and consist of speed of response, measuring lag, fidelity, and overshoot.
Diploma sem 2 applied science physics-unit 1-chap 2 error sRai University
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.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Accuracy precision - resolution
1. Accuracy, precision & resolution
Quantities can't be determined with absolute certainty. Measurement tools and systems have always
some tolerance and disturbances that will introduce a degree of uncertainty. In addition, also the
distinctiveness is a limiting factor.
The following terminology is often used in relation to the measurement uncertainty:
Accuracy: The error between the real and measured value.
Precision: The random spread of measured values around the average measured values.
Resolution: The smallest to be distinguished magnitude from the measured value.
In practice these terms are often confused. This article discusses these concepts.
Measurement uncertainty
Measurement uncertainties can be divided into systematic and random measurement errors. The
systematic errors are caused by abnormalities in gain and zero settings of the measuring equipment
and tools. The random errors caused by noise and induced voltages and/or currents.
Definition accuracy and precision
Often the concepts accuracy and precision are used interchangeably; they are regarded as
synonymous. These two terms, however, have an entirely different meaning. The accuracy indicates
how close the measured value is from its actual value, i.e. the deviation between the measured and
actual values. Precision refers to the random spread of the measured values.
Fig. 1: Definitions uncertainties. On the left a series of measurements. On the right the values are
plotted in a histogram.
When a number of measurements is done to a stable voltage or other parameter, the measured
values will show a certain variation. This is caused by thermal noise in the measuring circuit of the
measuring equipment and the measurement set-up. The left graph in Figure 1 shows these
variations.
Histogram
The measured values can be plotted in a histogram as shown in Figure 1. The histogram shows how
often a measured value occurs. The highest point of the histogram, this is the measured value that
2. has been most frequently measured, indicates the mean value. This is indicated by the blue line in
both graphs. The black line represents the real value of the parameter. The difference between the
average measured value and real value is the accuracy. The width of the histogram indicates the
spread of individual measurements. This distribution of measurements is called accuracy.
Use the correct definition
Accuracy and precision thus have a different meaning. It is therefore quite possible that a
measurement is very precise but not accurate. Or conversely, a very accurate measurement, but not
precise. In general, a measurement is considered valid if both the measurement is precise as well
accurate.
Accuracy
Accuracy is an indication of the correctness of a measurement. Because at a single measurement the
precision affects also the accuracy, an average of a series of measurements will be taken.
The uncertainty of measuring instruments is usually given by two values: uncertainty of reading and
uncertainty over the full scale. These two specifications together determine the total measurement
uncertainty.
These values for the measurement uncertainty is specified in percent or in ppm (parts per million)
relative to the current national standard. 1 % corresponds to 10000 ppm.
The specified uncertainty is quoted for specified temperature ranges and for certain time period
after calibration. Please also note that at different ranges other uncertainties may apply.
Fig. 2: Uncertainty of 5 % reading and a read value of 70 V.
Uncertainty relative to reading
3. An indication of a percentage deviation without further specification also refers to the reading.
Tolerances of voltage dividers, the exact gain and absolute deviation of the readout and digitization
cause this inaccuracy.
A voltmeter which reads 70,00 V and has a "±5 % reading" specification, will have an uncertainty
of 3,5 V (5 % of 70 V) above and below. The actual voltage will be between 66,5 en 73,5 volt.
Fig. 3: Uncertainty of 3 % full scale in the 100 V range.
Uncertainty relative to full scale
This type of inaccuracy is caused by offset errors and linearity errors of amplifiers. And with
instruments that digitizes signals, by the non-linearity of the conversion and the uncertainty in AD
converters. This specification refers to the full-scale range that is used.
A voltmeter may have a specification "3 % full scale". If during a measurement the 100 V range is
selected (= full scale), then the uncertainty is 3 % of 100 V = 3 V regardless of the voltage
measured.
If the readout in this range 70 V, then the real voltage is between 67 and 73 volts.
Figure 3 makes clear that this type of tolerance is independent of the reading. Would a value of 0 V
being read; in this case would the voltage in reality between -3 and +3 volts.
Full scale uncertainty in digits
Often give digital multimeter the full-scale uncertainty in digits instead of a percentage value.
A digital multimeter with a 3½ digit display (range -1999 t / m 1999), the specification can read
"+ 2 digits". This means that the uncertainty of the display is 2 units. For example: if a 20 volt range
is chosen (± 19.99), than the full scale uncertainty is ±0.02 V. The display shows a value of 10.00
than the actual value shall be between 9.98 and 10.02 volts.
4. Fig. 4: Total uncertainty of 5 % reading and 3 % full-scale on a 100 V range and a reading of 70 V.
Calculation of measurement uncertainty
The specification of the tolerance of the reading and the full scale together determine the total
measurement uncertainty of an instrument. In the following calculation example the same values are
used as in the examples above:
Accuracy: ±5 % reading (3 % full scale)
Range: 100 V, Reading: 70 V
The total measurement uncertainty is now calculated as follows:
[equ. 1]
In this situation, a total uncertainty of 7.5 V up and down. The real value should be between 62.5
and 77.5 volts. Figure 4 shows this graphically.
The percentage uncertainty is the relationship between reading and uncertainty. In the given
situation this is:
[equ. 2]
Digits
A digital multimeter can hold a specification of "±2.0 % rdg, + 4 digits. This means that 4 digits
have to be added to the reading uncertainty of 2 %. As an example again a 3½ digit digital readout.
This will read 5.00 V in while the 20 V range is selected. 2 % of the reading would mean an
uncertainty of 0.1 V. Add to this the inaccuracy of the digits (= 0.04 V). The total uncertainty is
therefore 0.14 V. The real value should be between 4.86 and 5.14 volts.
5. Cumulative uncertainty
Often only the uncertainty of the measuring instrument is taken into account. But also must be
looked after the additional measurement uncertainty of the measurement accessories if these are
used. Here are a couple of examples:
Increased uncertainty when using probe 1:10
When a 1:10 is used, not only the measurement uncertainty of the instrument must take into
account. Also the input impedance of the used instrument and the resistance of the probe, who make
together a voltage divider, shall influence the uncertainty.
Fig. 5: A 1:1 probe attached to an oscilloscope.
Figure 5 shows schematically an oscilloscope with a 1:1 probe. If we consider this probe as ideal
(no series resistance), the voltage applied to the probe is offered directly at the input of the
oscilloscope. The measurement uncertainty is now only determined by the tolerances in the
attenuator, amplifier and further processing, and is specified by the manufacturer.
(The uncertainty is also influenced by the resistance network that forms the internal resistance Ri.
This is included in the specified tolerances.)
Fig. 6: A 1:10 probe connected to an oscilloscope introduces an additional uncertainty.
Figure 6 shows the same scope, but now a 1:10 probe is connected to the input. This probe has an
internal series resistance Rp and together with the input resistance of the oscilloscope Ri will this
form a voltage divider. The tolerance of the resistors in the voltage divider will cause it's own
uncertainty.
The tolerance of the input resistance of the oscilloscope can be found into the specifications. The
tolerance of the series resistance Rp of the probe is not always given. However, the system
uncertainty stated by the combination of the oscilloscope probe with a specified type oscilloscope
will be known. If the probe is used with another type than the prescribed oscilloscope, the
measurement uncertainty is undetermined. This must always be avoided.
6. Suppose that an oscilloscope has a tolerance of 1.5 % and a 1:10 probe is used with a system
uncertainty of 2.5 %. These two specifications can be multiplied together to obtain total reading
uncertainty:
[equ. 3]
Measuring with a shunt resistor
Fig. 7: Increases of uncertainty when using a shunt resistor.
To measure currents an external shunt resistor is often used. The shunt has a certain tolerance that
affects the measurement.
The specified tolerance of the shunt resistor refers to the reading uncertainty. To find the total
uncertainty, the tolerance of the shunt and the reading uncertainty of the measuring instrument are
multiplied together:
[equ. 4]
In this example, the total reading uncertainty is 3.53 %.
The resistance of the shunt is temperature dependent. The resistance value is specified for a given
temperature. The temperature dependence is often expressed in ppm/°C.
As an example the calculating of the resistance value at ambient temperature (Tamb) of 30 °C. The
shunt has a specification: R=100 Ω @ 22 °C (respectively Rnom & Tnom), and a temperature
dependence of 20 ppm/°C.
[equ. 5]
The current flowing through the shunt causes dissipation of energy in the shunt and this will result
in rising of the temperature and therefore a change in resistance value. The change in resistance
value due to the current flow is dependent on several factors. For very accurate measurements the
shunt must be calibrated at a flow resistance and environmental conditions in which these will be
used.
7. Precision
The term precision is used to express the random measurement error. The random nature of the
deviations of the measured value is mostly of thermal origin. Because of the arbitrary nature of this
noise it's not possible to give an absolute error. The precision gives only the probability that the
measurement value is between given limits.
Fig. 8: Probability distribution for μ=2 en σ=1.
Gaussian distribution
Thermal noise has a Gaussian or normal distribution. This is described by the following equation:
[equ. 6]
Here is μ the mean value and σ indicates the degree of dispersion and corresponds to the RMS value
of the noise signal. The function provides a probability distribution curve as shown in Figure 8
where the mean value μ 2 is and the effective noise amplitude σ 1.
Table 1:
Probability Values
Border Chance
0,5·σ 38.3 %
0,674·σ 50.0 %
1·σ 68.3 %
2·σ 95.4 %
3·σ 99.7 %
Probability table
Table 1 lists some chance values expressed at a certain limit. As seen, the probability that a
measured value is within ±3·σ is 99.7 %.
Improving precision
The precision of a measurement can be improved by oversampling or filtering. The individual
measurements are averaged out so that the noise quantity is greatly reduced. The spread of the
measured values is hereby also reduced. With oversampling or filtering must be taken into account
that this may reduce the bandwidth.
8. Resolution
The resolution of a measurement system is the smallest yet to distinguish different in values. The
specified resolution of an instrument has no relation to the accuracy of measurement.
Digital measuring systems
A digital system converts an analog signal to a digital equivalent with an AD converter. The
difference between two values, the resolution, is therefore always equal to one bit. Or in the case of
a digital multimeter, this is 1 digit.
It's also possible to express the resolution in other units than bits. As an example a digital
oscilloscope which has an 8 bit AD converter. If the vertical sensitivity is set to 100 mV/div and the
number of divisions is 8, the total range will be 800 mV. The 8 bits represent 28
= 256 different
values. The resolution in volts is then 800 mV / 256 = 3125 mV.
Analog measuring systems
In the case of analog measuring instruments where the measured value is displayed in a mechanical
way, such as a moving-coil meter, it's difficult to give an exact number for the resolution. Firstly,
the resolution is limited by the mechanical hysteresis caused by friction of the bearings of the
needle. On the other hand, resolution is determined by the observer, making this a subjective
evaluation.