Data acquisition

Data acquisition is the process of

values for processing. The components of data acquisition systems include:

• electrical signals
  .
• Signal conditioning circuitry, to convert sensor signals into a form that can be converted to digital values.
• Analog-to-digital converters, to convert conditioned sensor signals to digital values.

Data acquisition applications are usually controlled by

.

There are also open-source software packages providing all the necessary tools to acquire data from different, typically specific, hardware equipment. These tools come from the scientific community where complex experiment requires fast, flexible, and adaptable software. Those packages are usually custom-fit but more general DAQ packages like the Maximum Integrated Data Acquisition System can be easily tailored and are used in several physics experiments.

History

In 1963, IBM produced computers that specialized in data acquisition. These include the IBM 7700 Data Acquisition System, and its successor, the IBM 1800 Data Acquisition and Control System. These expensive specialized systems were surpassed in 1974 by general-purpose S-100 computers and data acquisition cards produced by Tecmar/Scientific Solutions Inc. In 1981 IBM introduced the IBM Personal Computer and Scientific Solutions introduced the first PC data acquisition products.^{[1][2][3][4][5]}

Methodology

Sources and systems

Data acquisition begins with the

to be measured. Examples of this include temperature, vibration, light intensity, gas pressure, fluid flow, and force. Regardless of the type of physical property to be measured, the physical state that is to be measured must first be transformed into a unified form that can be sampled by a data acquisition system. The task of performing such transformations falls on devices called sensors. A data acquisition system is a collection of software and hardware that allows one to measure or control the physical characteristics of something in the real world. A complete data acquisition system consists of DAQ hardware, sensors and actuators, signal conditioning hardware, and a computer running DAQ software. If timing is necessary (such as for event mode DAQ systems), a separate compensated distributed timing system is required.

A

differential signals

. Once digitized, the signal can be encoded to reduce and correct transmission errors.

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 (

can be used.

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 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.

Today, signals from some sensors and Data Acquisition Systems can be streamed via Bluetooth.

DAQ device drivers

DAQ

are needed for the DAQ hardware to work with a PC. The device driver performs low-level register writes and reads on the hardware while exposing API for developing user applications in a variety of programs.

Input devices

• 3D scanner
• Analog-to-digital converter
• Time-to-digital converter

Hardware

• Computer Automated Measurement and Control (CAMAC)
• Industrial Ethernet
• Industrial USB
• LAN eXtensions for Instrumentation
• Network interface controller
• PCI eXtensions for Instrumentation
• VMEbus
• VXI

DAQ software

Specialized DAQ software may be delivered with the DAQ hardware. Software tools used for building large-scale data acquisition systems include

.

See also

• Black box
• Data collection (synonym)
• Data logger
• Data storage device
• Data science
• Sensor
• Signal processing
• Transducer

References

Further reading

Wikimedia Commons has media related to Data acquisition.

• Simon McBeath (2002). Competition Car Data Logging: A Practical Handbook. J. H. Haynes & Co.
  ISBN 978-1-85960-653-7
  .
• Simon S. Young (2001). Computerized Data Acquisition and Analysis for the Life Sciences. Cambridge University Press.
  ISBN 978-0-521-56570-7
  .
• W. R. Leo (1994). Techniques for Nuclear and Particle Physics Experiments. Springer.
  ISBN 978-3-540-57280-0
  .
• V. Gonzalez (2012). Data Acquisition in Particle Physics Experiments. InTech.
  ISBN 978-953-51-0713-2
  .
• Charles D. Spencer (1990). Digital Design for Computer Data Acquisition. Cambridge University Press.
  ISBN 978-0-521-37199-5
  .
• B.G. Thompson & A. F. Kuckes (1989). IBM-PC in the laboratory. Cambridge University Press.
  ISBN 978-0-521-32199-0
  .
• Buddy Fey (1996). Data Power: Using Racecar Data Acquisition. Towery Pub.
  ISBN 978-1-881096-01-6
  .
• Francesco Fornetti (2013). Instrumentation Control, Data Acquisition and Processing with MATLAB. Explore RF Ltd.
  ISBN 978-0957663503
  .
• Tomaž Kos, Tomaž Kosar, and Marjan Mernik. Development of data acquisition systems by using a domain-specific modeling language. Computers in Industry, 63(3):181–192, 2012. [1]
  doi:10.1016/j.compind.2011.09.004