Data Acquisition Solutions

Data Acquisition (DAQ) is the process of sampling of real world physical conditions and conversion of the resulting samples into digital numeric values that can be manipulated by a computer. Data acquisition and Data Acquisition Systems (DAS) typically involves the conversion of analog waveforms into digital values for processing. The components of data acquisition systems include:

  • Signals
  • Sensors
  • Actuators
  • Signal Conditioning
  • Data Acquisition Devices
  • Application Software

The purpose of data acquisition is to measure an electrical or physical phenomenon such as voltage, current, temperature, pressure, or sound. PC-based data acquisition uses a combination of modular hardware, application software, and a computer to take measurements. While each data acquisition system is defined by its application requirements, every system shares a common goal of acquiring, analyzing, and presenting information.


Source

Data acquisition begins with the physical phenomenon or physical property to be measured. Examples of this include temperature, 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 sensor, which is a type of transducer, is a device that converts a physical property into a corresponding electrical signal or, in many cases, into a corresponding electrical characteristic that can easily be converted to electrical signal.

The ability of a data acquisition system to measure differing properties depends on having sensors that are suited to detect the various properties to be measured. There are specific sensors for many different applications. DAQ systems also employ various signal conditioning techniques to adequately modify various different electrical signals into voltage that can then be digitized using an Analog-to-Digital Converter (ADC).


Signals

The appropriate transducers convert physical phenomena into measurable signals. However, different signals need to be measured in different ways. For this reason, it is important to understand the different types of signals and their corresponding attributes. Signals can be categorized into two groups:

  • Analog Signals: An analog signal can be at any value with respect to time. A few examples of analog signals include voltage, temperature, pressure, sound, and load. The three primary characteristics of an analog signal include level, shape, and frequency.

  • Level: Because analog signals can take on any value, the level gives vital information about the measured analog signal. The intensity of a light source, the temperature in a room, and the pressure inside a chamber are all examples that demonstrate the importance of the level of a signal. When measuring the level of a signal, the signal generally does not change quickly with respect to time. The accuracy of the measurement, however, is very important. A DAQ system that yields maximum accuracy should be chosen to aid in analog level measurements.

    1. Shape: Some signals are named after their specific shape - sine, square, sawtooth, and triangle. The shape of an analog signal can be as important as the level, because by measuring the shape of an analog signal, you can further analyze the signal, including peak values, DC values, and slope. Signals where shape is of interest generally change rapidly with respect to time, but system accuracy is still important. The analysis of heartbeats, video signals, sounds, vibrations, and circuit responses are some applications involving shape measurements.

    2. Frequency: All analog signals can be categorized by their frequency. Unlike the level or shape of the signal, frequency cannot be directly measured. The signal must be analyzed using software to determine the frequency information. This analysis is usually done using an algorithm known as the Fourier Transform. When frequency is the most important piece of information, it is important to consider including both accuracy and acquisition speed. Although the acquisition speed for acquiring the frequency of a signal is less than the speed required for obtaining the shape of a signal, the signal must still be acquired fast enough that the pertinent information is not lost while the analog signal is being acquired. The condition that stipulates this speed is known as the Nyquist Sampling Theorem. Speech analysis, telecommunication, and earthquake analysis are some examples of common applications where the frequency of the signal must be known.

  • Digital Signals: A digital signal cannot take on any value with respect to time. Instead, a digital signal has two possible levels: high and low. Digital signals generally conform to certain specifications that define characteristics of the signal. Digital signals are commonly referred to as transistor-to-transistor logic (TTL). TTL specifications indicate a digital signal to be low when the level falls within 0 to 0.8 V, and the signal is high between 2 to 5 V. The useful information that can be measured from a digital signal includes the state and the rate.

    1. State: Digital signals cannot take on any value with respect to time. The state of a digital signal is essentially the level of the signal - on or off, high or low. Monitoring the state of a switch - open or closed - is a common application showing the importance of knowing the state of a digital signal.

    2. Rate: The rate of a digital signal defines how the digital signal changes state with respect to time. An example of measuring the rate of a digital signal includes determining how fast a motor shaft spins. Unlike frequency, the rate of a digital signal measures how often a portion of a signal occurs. A software algorithm is not required to determine the rate of a signal.

Signal Conditioning

Sometimes transducers generate signals too difficult or too dangerous to measure directly with a DAQ device. For instance, when dealing with high voltages, noisy environments, extreme high and low signals, or simultaneous signal measurement, signal conditioning is essential for an effective DAQ system. Signal conditioning maximizes the accuracy of a system, allows sensors to operate properly, and guarantees safety.

It is important to select the right hardware for signal conditioning. Signal conditioning is offered in both modular and integrated forms. Signal conditioning accessories can be used in a variety of applications including:

  • Amplification
  • Attenuation
  • Isolation
  • Bridge completion
  • Simultaneous sampling
  • Sensor excitation
  • Multiplexing

When providing a client with a Data Acquisition Solution, 21 CTI's experts weigh in all the components (Signals, Sensors, Signal Coniditioning, etc.), the environmental conditions, and the client's needs and goals, to provide a complete solution which meets or exceeds the customer's expectations.

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