Acoustic Tomography for Detecting a Hot Spot in Grain Bulk

A hot spot is a localized high temperature zone in a grain bulk and normally spoilage begins in this location. Acoustic temperature tomography for detecting a hot spot in grain bulk is investigated. The region monitored is assumed to be square and divided into 400 pixels. 16 sound sources/receivers are set on its periphery. An acoustic temperature field reconstruction algorithm based on inverse multiquadrics approximation and truncated singular value decomposition is proposed. Using this algorithm, 400 temperature field models with a hot spot positioned at the midpoint of each pixel in turn have been reconstructed from exact or perturbed time-of-flight data. Reconstruction results indicate that the algorithm proposed is good at reconstructing hot spot temperature, especially at reconstructing hot spot position. Thus it is expected to be used in detecting hot spots in grain bulk.