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Traditionally, to check weld quality, destructive (the dominant method at industry until now) and non-destructive tests are used on randomly sampled work pieces at the production site. These processes tend to be predominantly off-line or end-of-line processes. The objective of the force-based weld monitoring algorithm is to classify the weld status, i.e. cold, normal and expulsion, by using non-intrusive force sensor. It is composed mainly from two sub-algorithms: expulsion and normal welds detection. This algorithm has been tested on medium frequency direct current (MFDC) constant current (CC) control. The results were as follows: the percentage of the false alarm (I) type-1 error is the lowest for cold welds case at 3.6%, 11.0% for normal welds and 21.7% for expulsion welds. As for the failed alarm (β) type-2 error, the lowest percentage is for expulsion welds 1.9%, 3.4% for cold welds and 16.5% for normal welds.
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Banna et al. (2011) studied this question.
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