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Mean Linear Dendrite Spacing for Cast Alloys

Accurate and repeatable DAS measurement techniques for alloy microstructures using image analysis. MLDS (Mean Linear Dendrite Spacing) is an approach based on an image analysis routine which automatically detects dendrites, superimposes a set of concentric circles and exports measurements of overlapped features. Read more about the new automated method of measuring microstructural fineness available in Clemex Vision.

Mean linear dendrite spacing for cast alloys

Accurate, reproducible and consistent

The new automated method for measuring micro structural fineness using image analysis allows increased data collection, better measurement representation, and less measurement process time.

MLDS

Increased data collection

MLDS is an approach based on an image analysis routine which automatically detects dendrites, superimposes a set of concentric circles and exports measurements of overlapped features.

Mean linear dendrite spacing for cast alloys

Better measurement representation

Circles are segmented and measured in a way that is universal for all microscope magnifications and camera combinations. The use of a single routine for different situations minimizes operator errors.

Results

Less measurement process time

The automated method has been proved to be 16 times faster than the traditional manual method. Furthermore, increased data collection produces a statistically significant result.

Traditional SDAS method Fineness in hypoeutectic metallic alloys, like hypoeutectic Al-Si based casting alloys, has traditionally been quantified by measuring the spacing between secondary dendrite arms (SDAS). The manual SDAS method involves capturing images from a sample and annotating a number of secondary dendrite arms with direct measurement tools. The length distribution of these manual measurements is updated instantaneously in the results panel of the software and can be exported for further processing using a Linear Intercept Method macro to obtain DAS.

Traditional SDAS method

Learn more about MLDS

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