measurements basic principle of measurements part 1: basic principle of measurements 10/11/2015

MeasuremeMeasurementsnts

Part 1: Basic Principle of Basic Principle of Measurements Measurements

04/19/23 www.notesht.com 1

Basic components in a measurement system

Basic components in a measurement system are shown below:

It is also important to mention that a power supply is an important element for the entire system.

Amplification and Conditioning


INSTRUMENTATION CHARACTERISTICS

• Shows the performance of instruments to be used.

• Divided into two categories: static and dynamic characteristics.

• Static characteristics refer to the comparison between steady output and ideal output when the input is constant.

• Dynamic characteristics refer to the comparison between instrument output and ideal output when the input changes.


STATIC CHARACTERISTICS

1. ACCURACY

– Accuracy is the ability of an instrument to show the exact reading.

– Always related to the extent of the wrong reading/non accuracy.

– Normally shown in percentage of error which of the full scale reading percentage.


2. PRECISION

• An equipment which is precise is not necessarily accurate.

• Defined as the capability of an instrument to show the same reading when used each time (reproducibility of the instrument).




Example :X : resultCentre circle : true value

XXXXXXXXXX

XXXXXX

X X

X

x xHigh accuracy, high precision

Low accuracy, high precision

Low accuracy, low precision


Accuracy vs Precision

High Precision, but low accuracy.

There is a systematic error.


Accuracy vs Precision (Cont)

High accuracy means that the mean is close to the true value, while high precision means that the standard deviation σ is small.


3. TOLERANCE

• Closely related to accuracy of an equipment where the accuracy of an equipment is sometimes referred to in the form of tolerance limit.

• Defined as the maximum error expected in an instrument.

• Explains the maximum deviation of an output component at a certain value.



4. RANGE OF SPAN

• It defines the maximum and minimum values of the inputs or the outputs for which the instrument is recommended to use.

• For example, for a temperature measuring instrument the input range may be 100-500 oC and the output range may be 4-20 mA.



5. BIAS

• Constant error which occurs during the measurement of an instrument.

• This error is usually rectified through calibration.

Example :

A weighing scale always gives a bias reading. This equipment always gives a reading of 1 kg even without any load applied. Therefore, if A with a weight of 70 kg weighs himself, the given reading would be 71 kg. This would indicate that there is a constant bias of 1 kg to be corrected.



6. LINEARITY

• Maximum deviation from linear relation between input and output.

• The output of an instrument has to be linearly proportionate to the measured quantity.

• Normally shown in the form of full scale percentage (% fs).

• The graph shows the output reading of an instrument when a few input readings are entered.

• Linearity = maximum deviation from the reading of x and the straight line.



Linearity

OutputReadings

Measured Quantity


7. SENSIVITY

• Defined as the ratio of change in output towards the change in input at a steady state condition.

• Sensitivity (K) = Δθο

Δθi

Δθο : change in output; Δθi : change in input

Example 1:

The resistance value of a Platinum Resistance Thermometer changes when the temperature increases. Therefore, the unit of sensitivity for this equipment is Ohm/°C.



8. DEAD SPACE / DEAD BAND

• Defined as the range of input reading when there is no change in output (unresponsive system).

Dead Space

OutputReading

MeasuredVariables

- +



9. RESOLUTION

• The smallest change in input reading that can be traced accurately.

• Given in the form ‘% of full scale (% fs)’.

• Available in digital instrumentation.



10. THRESHOLD

• When the reading of an input is increased from zero, the input reading will reach a certain value before change occurs in the output.

• The minimum limit of the input reading is ‘threshold’.



DYNAMIC CHARACTERISTICS

• Explains the behaviour system of instruments system when the input signal is changed.

• Depends on a few standard input signals such as ‘step input’, ‘ramp input’ dan ‘sine-wave input’.



Step Input

• Sudden change in input signal from steady state.

• The output signal for this kind of input is known as ‘transient response’.

Input

Time



Ramp Input• The signal changes linearly.

• The output signal for ramp input is ‘ramp response’.

Input

Time



Sine-wave Input• The signal is harmonic.

• The output signal is ‘frequency response’.

Input

Time


Response time

One would like to have a measurement system with fast response.

In other words, the effect of the measurement system on the measurement should be as small as possible.


EXAMPLE OF DYNAMIC CHARACTERISTICS

Response from a 2nd order instrument:Output

100%

90%

10%

trTime


EXAMPLE OF DYNAMIC CHARACTERISTICS

Response from a 2nd order instrument:

1. Rise Time ( tr )• Time taken for the output to rise from

10% to 90 % of the steady state value.

2. Settling time (ts)• Time taken for output to reach a

steady state value.


Sensor Performance Characteristics Transfer Function:

The functional relationship between physical input signal and electrical output signal. Usually, this relationship is represented as a graph showing the relationship between the input and output signal, and the details of this relationship may constitute a complete description of the sensor characteristics. For expensive sensors which are individually calibrated, this might take the form of the certified calibration curve.

Sensitivity:

The sensitivity is defined in terms of the relationship between input physical signal and output electrical signal. The sensitivity is generally the ratio between a small change in electrical signal to a small change in physical signal. As such, it may be expressed as the derivative of the transfer function with respect to physical signal. Typical units : Volts/Kelvin. A Thermometer would have "high sensitivity" if a small temperature change resulted in a large voltage change.

Span or Dynamic Range:

The range of input physical signals which may be converted to electrical signals by the sensor. Signals outside of this range are expected to cause unacceptably large inaccuracy. This span or dynamic range is usually specified by the sensor supplier as the range over which other performance characteristics described in the data sheets are expected to apply.


Sensor Performance Characteristics Accuracy:

Generally defined as the largest expected error between actual and ideal output signals. Typical Units : Kelvin. Sometimes this is quoted as a fraction of the full scale output. For example, a thermometer might be guaranteed accurate to within 5% of FSO (Full Scale Output)

Hysteresis:

Some sensors do not return to the same output value when the input stimulus is cycled up or down. The width of the expected error in terms of the measured quantity is defined as the hysteresis. Typical units : Kelvin or % of FSO

Nonlinearity (often called Linearity):

The maximum deviation from a linear transfer function over the specified dynamic range. There are several measures of this error. The most common compares the actual transfer function with the `best straight line', which lies midway between the two parallel lines which encompasses the entire transfer function over the specified dynamic range of the device. This choice of comparison method is popular because it makes most sensors look the best.


Sensor Performance Characteristics Noise:

All sensors produce some output noise in addition to the output signal. The noise of the sensor limits the performance of the system based on the sensor. Noise is generally distributed across the frequency spectrum. Many common noise sources produce a white noise distribution, which is to say that the spectral noise density is the same at all frequencies. Since there is an inverse relationship between the bandwidth and measurement time, it can be said that the noise decreases with the square root of the measurement time.

Resolution:

The resolution of a sensor is defined as the minimum detectable signal fluctuation. Since fluctuations are temporal phenomena, there is some relationship between the timescale for the fluctuation and the minimum detectable amplitude. Therefore, the definition of resolution must include some information about the nature of the measurement being carried out.

Bandwidth:

All sensors have finite response times to an instantaneous change in physical signal. In addition, many sensors have decay times, which would represent the time after a step change in physical signal for the sensor output to decay to its original value. The reciprocal of these times correspond to the upper and lower cutoff frequencies, respectively. The bandwidth of a sensor is the frequency range between these two frequencies.


measurements basic principle of measurements part 1: basic principle of measurements 10/11/2015

Documents

instrument output

output reading

output range

ideal output

output component

steady output

static characteristics

high precisionlow accuracy