Strain Gauge | Data Acquisition and Conversion | Analog Signal Processing

 Strain Gauge

What is Strain Guage?

Strain Gauge is basically a sensor used for the measurement of various physical parameters like stress, strain etc.

The working principle of strain gauge is based on Piezoresistive Effect. That’s why it is also often called Piezoresistive Gauge

When a metal conductor is stretched or compressed, the dimension of conductor changes. Change in dimension means change in radius and length of the conductor.

Since the resistance of conductor is directly proportional to its length and inversely proportional to its area of cross-section, therefore a change in dimension of conductor will cause a change in the resistance.

Also, it has been observed that the resistivity of conductor also changes due to strain in the conductor. This change in resistivity of due to strain is called Piezoresistive Effect.

Gauge Factor

Gauge Factor is defined as the ratio of per unit change in resistance to the per unit change in length. This can be mathematically written as,

Gf = (ΔR / R) / (ΔL / L)

Where ΔR / R = Per unit change in resistance

ΔL / L = Per unit change in len

Gf = Gauge Factor

 

As strain of an elastic material is defined as the per unit change in length, therefore Strain, ε = Change in Length / Original Length

= ΔL / L

Hence, Gauge Factor, Gf = ε(ΔR / R)

 

Data Acquisition and Conversion 

What is Data Acquisition and Conversion?

Data acquisition and conversion systems are used to acquire analog signals from one or more sources and convert these signals into digital form for analysis or transmission by end devices such as digital computers, recorders, or communications networks.

The analog signal inputs to data acquisition systems are most often generated from sensors and transducers which convert real-world parameters such as pressure, temperature, stress or strain, flow, etc, into equivalent electrical signals.

The electrically equivalent signals are then converted by the data acquisition system and are then utilized by the end devices in digital form.

The basic components required for the acquisition and conversion of analog signals into equivalent digital form are the following: • Analog Multiplexer and Signal Conditioning • Sample/Hold Amplifier

•   Analog-to-Digital Converter

•   Timing or Sequence Logic

Typically, today’s data acquisition systems contain all the elements needed for data acquisition and conversion, except perhaps, for input filtering and signal conditioning prior to analog multiplexing.

The analog signals are time multiplexed by the analog multiplier; the multiplexer output signal is then usually applied to a very-linear fast-settling differential amplifier and/or to a fast-settling low aperture sample/hold.

The sample/hold is programmed to acquire and hold each multiplexed data sample which is converted into digital form by an A/D converter.

The converted sample is then presented at the output of the A/D converter in parallel and serial digital form for further processing by the end devices.

Analog Signal Processing

What is Analog Signal Processing?

Analog signal processing is a type of signal processing conducted on continuous analog signals by some analog means (as opposed to the discrete digital signal processing where the signal processing is carried out by a digital process).

"Analog" indicates something that is mathematically represented as a set of continuous values. This differs from "digital" which uses a series of discrete quantities to represent signal. Analog values are typically represented as a voltage, electric current, or electric charge around components in the electronic devices. An error or noise affecting such physical quantities will result in a corresponding error in the signals represented by such physical quantities.

Signal processing is an electrical engineering subfield that focuses on analysing, modifying, and synthesizing signal such as sound, images, and biological measurements. Signal processing techniques can be used to improve transmission, storage efficiency and subjective quality and to also emphasize or detect components of interest in a measured signal.