Data acquisition involves sampling signals from the physical world, converting the analog signals to digital numeric values, and processing the data with a computer. Key aspects of data acquisition systems include transducers that sense physical variables and convert them to electrical signals, signal conditioning to prepare analog signals for analog-to-digital conversion, analog-to-digital converters that change analog signals to digital values, sampling the signals at a sufficient rate to avoid aliasing, and using DAQ software and hardware to interface with a computer for processing, analyzing, storing and displaying the acquired data.

2. Data acquisition is the process of sampling
signals that measure real world physical
conditions and converting the resulting
samples into digital numeric values that can
be manipulated by a computer. Data
acquisition systems (abbreviated with the
acronym DAQ) typically convert analog
waveforms into digital values for processing.

3.  Sense physical variables (use of
transducers)
 Condition the electrical signal to make it
readable by an A/D board
 Convert the signal into a digital format
acceptable by a computer
 Process, analyze, store, and display the
acquired data with the help of software

5.  Physical system:
This term refers to the all physical phenomena that are to be
measured. Temperature, pressure, light, force, displacement, and level
all these can be included as the physical quantity that we measure
directly with the help of sensors and transducers.
 Transducer and actuators:
This is the section which converts sensed physical quantity to its
equivalent electrical signal. A transducer converts temperature,
pressure, level, length, position, etc. into voltage, current, frequency,
pulses or other signals.
An actuator is a device that activates process control equipment by
using pneumatic, hydraulic or electrical power. For example, a valve
actuator opens and closes a valve to control fluid rate.

6.  Signal conditioning:
Electrical signals are conditioned so they can be used
by an analog input board. Signal conditioning circuits
improve the quality of signals generated by
transducers before they are converted into digital
signals by the PC's data-acquisition hardware. The
following features may be available:
› Amplification
› Isolation
› Filtering
› Linearization

7. Amplification
One of the most common signal conditioning functions is amplification. For maximum resolution, the
voltage range of the input signals should be approximately equal to the maximum input range of the
A/D converter. Amplification expands the range of the transducer signals so that they match the input
range of the A/D converter. For example, a x10 amplifier maps transducer signals which range from 0
to 1 V into the range 0 to 10 V before they go into the A/D converter. Amplifiers increase voltage level
to better match the analog-to-digital converter (ADC) range, thus increasing the measurement
resolution and sensitivity. In addition, using external signal conditioners located closer to the signal
source, or transducer, improves the measurement signal-to-noise ratio by magnifying the voltage level
before it is affected by environmental noise.
Isolation
Isolated signal conditioning devices pass the signal from its source to the measurement device
without a physical connection by using transformer, optical, or capacitive coupling techniques. In
addition to breaking ground loops, isolation blocks high-voltage surges and rejects high common-
mode voltage and thus protects both the operators and expensive measurement equipment.
Filtering
Filters reject unwanted noise within a certain frequency range. Oftentimes, low pass filters are used to
block out high-frequency noise in electrical measurements, such as 60 Hz power. Another common
use for filtering is to prevent aliasing from high-frequency signals. This can be done by using an
antialiasing filter to attenuate signals above the Nyquist frequency.
Linearization
Linearization is necessary when sensors produce voltage signals that are not linearly related to the
physical measurement. Linearization is the process of interpreting the signal from the sensor and can
be done either with signal conditioning or through software. Thermocouples are the classic example
of a sensor that requires linearization.

8.  Analog to digital converter:
Analog to digital (A/D) conversion changes analog
voltage or current levels into digital information. The
conversion is necessary to enable the computer to
process or store the signals.

9. The resolution of the converter indicates the number of
discrete values it can produce over the range of analog
values. The values are usually stored electronically in
binary form, so the resolution is usually expressed in bits.
In consequence, the number of discrete values available,
or "levels", is a power of two. For example, an ADC with a
resolution of 8 bits can encode an analog input to one in
256 different levels, since 28 = 256. The values can
represent the ranges from 0 to 255 (i.e. unsigned integer)
or from −128 to 127 (i.e. signed integer), depending on
the application.
Resolution can also be defined electrically, and expressed
in volts. The minimum change in voltage required to
guarantee a change in the output code level is called
the least significant bit (LSB) voltage.
Resolution

10. Sampling
In signal processing, sampling is the reduction of a continuous signal to a discrete
signal. A common example is the conversion of a sound wave (a continuous signal) to a
sequence of samples (a discrete-time signal).A sample refers to a value or set of values
at a point in time and/or space. A sampler is a subsystem or operation that extracts
samples from a continuous signal. A theoretical ideal sampler produces samples
equivalent to the instantaneous value of the continuous signal at the desired points.
The analog signal is continuous in time and it is necessary to convert this to a flow of
digital values. It is therefore required to define the rate at which new digital values are
sampled from the analog signal. The rate of new values is called the sampling rate or
sampling frequency of the converter.
A continuously varying band limited signal can be sampled (that is the signal values at
intervals of time T, the sampling time, are measured and stored) and then the original
signal can be exactly reproduced from the discrete-time values by
an interpolation formula. The accuracy is limited by quantization error. However, this
faithful reproduction is only possible if the sampling rate is higher than twice the
highest frequency of the signal.

11. Aliasing
If the digital values produced by the ADC are, at some later stage in the system,
converted back to analog values by a digital to analog converter or DAC, it is desirable
that the output of the DAC be a faithful representation of the original signal. If the
input signal is changing much faster than the sample rate, then this will not be the
case, and spurious signals called aliases will be produced at the output of the DAC. The
frequency of the aliased signal is the difference between the signal frequency and the
sampling rate. For example, a 2 kHz sine wave being sampled at 1.5 kHz would be
reconstructed as a 500 Hz sine wave. This problem is called aliasing.
To avoid aliasing, the input to an ADC must be low-pass filtered to remove frequencies
above half the sampling rate. This filter is called an anti aliasing filter, and is essential
for a practical ADC system that is applied to analog signals with higher frequency
content.

12.  Computer:
This is the final or ultimate section that actually
produces the output in digital format. In A/D converter
section the signal already gets transformed into
digitized form that can be understood by the computer.
Now we can access the output through some
hardware and soft wares.

13. DAQ Hardware
DAQ hardware is what usually interfaces between the signal and a PC. It could be in
the form of modules that can be connected to the computer's ports
(parallel, serial, USB, etc.) or cards connected to slots (S-100 Bus, Apple Bus,
ISA, MCA, PCI, PCI-E, etc.) in the motherboard. DAQ cards often contain multiple
components (multiplexer, ADC, DAC, TTL-IO, high speed timers, RAM). These are
accessible via a bus by a microcontroller, which can run small programs. A controller
is more flexible than a hard wired logic, yet cheaper than a CPU so that it is
permissible to block it with simple polling loops. For example: Waiting for a trigger,
starting the ADC, looking up the time, waiting for the ADC to finish, move value to
RAM, switch multiplexer, get TTL input, let DAC proceed with voltage ramp. Many
times reconfigurable logic is used to achieve high speed for specific tasks and digital
signal processors are used after the data has been acquired to obtain some results.
The fixed connection with the PC allows for comfortable compilation and debugging.
Using an external housing a modular design with slots in a bus can grow with the
needs of the user. Not all DAQ hardware has to run permanently connected to a PC,
for example intelligent stand-alone loggers and oscilloscopes, which can be operated
from a PC, yet they can operate completely independent of the PC.

14. DAQ Software
DAQ software is needed in order for the DAQ hardware to
work with a PC. It generates a complete DAQ, analysis, and
display system. Data acquisition applications are controlled by
software programs developed using various general purpose
programming languages such as BASIC,C, Fortran, Java, Lisp,
Pascal. Specialized software tools used for building large-scale
data acquisition systems include EPICS. Graphical
programming environments include ladder logic, Visual
C++, Visual Basic, and LabVIEW. It does not require
programming.