LIBRARY ı6ıul 0) - Cranfield University

The same approaches used for seam tracking are normally applied for joint
recognition. Through the analysis of laser range data or a laser stripe image it is
possible to determine the geometry of the joint, the presence of gap, misalignments,
and to provide the control system with error signals necessary for the adaptation of
the welding parameters, in order to maintain the desired weld quality.
Changes in joint geometry can be detected by analysing the variation in the
welding current and voltage waveforms. With this in mind, Ogunbiyi [ref. 51]
proposed a through-the-arc model to predict gap size during welding, without
weaving. Through-the-arc gap detection techniques with torch weaving have been
studied by Davis [ref. 151]. Both research works show that through-the-arc gap
detection is possible. However, the proposed method was not robust enough for
accurately measuring the joint gap.
Z. 6.1.5 Weld recognition
Weld recognition is a form of adaptive control which recognises variations in
the geometry (including penetration depth) of the weld or weldpool being made and
instructs the welding equipment to take the appropriate corrective action [ref. 58].
The weld recognition techniques also make use of through-the-arc sensing and
optical sensing. The arc sensor approaches are based on empirical models developed
to predict the weld geometry from the welding current and voltage and travel speed
[ref. 54].
The optical systems on the other hand, can be used to view the weld pool as
well as the bead profile in order to generate control actions to compensate for any
occurring problems [refs. 11,152].
For weld recognition as well as for joint recognition, artificial intelligence such
as neural networks and fuzzy logic have been utilised. These techniques have been
specially applied for image processing and visual inspection [ref. 153].
Other methods of sensing the weld include infrared backface sensing (used for
penetration control), front face light sensing and voltage oscillation, which are used to
detect the oscillation frequency of the pool (used for penetration control), ultrasonic
penetration control, radiographic sensing, thermographic sensing and hybrid systems.
All these sensing methods have been discussed by Norrish [ref. 3].
2.6.2 Data acquisition system
VanDoren [ref. 155] defines a data acquisition system as an electronic
instrument, or group of interconnected electronic hardware items, dedicated to
measurement and quantization of analog signals for digital analysis or processing.
Data acquisition systems offer specialised computer programs written to
digitise, store and analyze the input data normally obtained by using appropriate
sensors [refs 154,156].
Such systems usually consist of three main blocks [ref. 157].
" measurement hardware, consisting mainly of sensors and signal
conditioning hardware.
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