Aggregates such as sand gravel and crushed rock are used all over the world in the construction of buildings, bridges, roads, railways and so on. Once quarried, samples are currently analysed and graded manually in order to determine their properties and suitability for differing applications.
The 3D shape and size and the composition of aggregates materials are central to their performance in construction applications. The compositional analysis of aggregates is presently undertaken by trained geologist in what is an expensive, time-consuming and often subjective manual task. The development of robust, automated techniques that can establish the properties of an aggregates sample offers several benefits, such as: better quality control through a more reliable, objective means of classification; business agility benefits attained through a reduction in the lead time required to determine the properties of a particular aggregates source; and efficiency and environmental benefits attained through more efficient use of aggregates in composites such as concrete and asphalt.
Fig. 1: LabVIEW and iMAQ Vision are used to extract accurate 3D morphological data from aggregate samples. Prototype 1 in UWE, Bristol.
A bench-top device, (shown in Fig 1), was developed that uses laser triangulation to recover three-dimensional data from aggregate particles as they pass along a moving conveyor, as shown in fig 2. In order to meet the user specified requirement of analyzing at least 200 particles per hour, high speed digital cameras were used with a high bandwidth interface to enable frame rates of up to 120 frames per second to be acquired. The careful design of the system, incorporating the two registered cameras, minimised any data occlusion. In this way a dense 'cloud' of accurate three-dimensional data points was recovered for each aggregate particle.
Fig. 2: Acquiring a typical particle cross-section.
Novel techniques were used to classify the particle size and shape properties based on the acquired cloud of 3D data, accurately representing the visible surfaces of the particles.
Code was developed to extract particle principal dimensions, i.e. length, width and height. Also, an algorithm for measuring the angularity/roundness of the particles was developed, using a novel morphological opening operation based on an ellipsoidal structuring element that is adaptively generated according to the size and aspect ratios of each individual particle. This effectively mimicked the natural wear process by which particles become rounded, thus providing a direct and geometrically meaningful measure of angularity. A 'virtual sieving' algorithm was also developed able to provide a useful means of converting three-dimensional particle sizes into the one-dimensional particle sieve sizes as widely used in industry.
Field trials showed that typical frame rates of approximately 80Hz could easily be achieved in practice, which, based on an average particle length of 16mm, allowed the analysis of approximately 450 particles per hour at an accuracy of ±0.1mm. The system therefore met the user throughput specification. The recovery of particle length, width and height measures in themselves are of little use to aggregate producers and consumers. However, particle size distributions, recovered using the virtual sieve, on the other hand, are critically important from an industrial perspective and the ability to automatically recover sieve size without undertaking manual sieving offers significant commercial value. This first prototype, built at UWE in Bristol, UK, as part of a EUREKA project, has now been upgraded and supplied with an automatic particle feeder, the software expanded and calculations and reporting added that are directed towards the construction industry and preparations done for the inclusion of the compositional analysis tools, again.
The work resulted in a patent application and the development of a commercial system.