Innovative Smart Drilling with Critical Event Detection and Material Classification

Material Classification By Drilling

Underground coal mining is one of the most dangerous occupations. Years of effort have been dedicated to researching methods of characterizing mine roof and floor for improving the mining environment. This research investigates using a neural network to classify rock strata based on the physical parameters of a roof bolting drill. This paper presents our methodology, as well as early results ba...

Acoustic Event Detection and Classification

Acoustic Event Detection and Classification in Smart-room Environments: Evaluation of Chil Project Systems

The identification of acoustic events that are produced in a meeting room environment may help to detect and describe the human and social activity that takes place in the room. In the framework of the CHIL project, three different sites have developed and tested several preliminary systems for acoustic event classification (AEC) and acoustic event detection (AED). A primary AED evaluation task...

Drilling Damage in Composite Material

The characteristics of carbon fibre reinforced laminates have widened their use from aerospace to domestic appliances, and new possibilities for their usage emerge almost daily. In many of the possible applications, the laminates need to be drilled for assembly purposes. It is known that a drilling process that reduces the drill thrust force can decrease the risk of delamination. In this work, ...

Shadow-insensitive Material Detection/classification with Atmospherically Corrected Hyperspectral Imagery

Hyperspectral imaging (HSI) from airborne or space-based platforms, currently conducted mainly in the 0.4 2.5 μm wavelength region, is a valuable technique for detection and classification of materials and objects on the Earth's surface. In a typical analysis, the spectral radiance data are "corrected" or compensated for the atmospheric and illumination conditions to yield spectral reflectance,...