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  • chapterNo Access

    A New Technique for the Design of Acoustic Matching Layers for Piezocomposite Transducers

    At present a lot of piezoelectric broad band ultrasonic transducers for both, medical and NDE purposes, use as active material piezoelectric ceramic composites. A lot of scientific and technological research has been devoted to the optimisation of piezocomposite materials, in order to increase the transducer band and efficiency. In a typical transducer based on piezocomposites the active material is mounted on a soft lossy backing and one matching layer is placed on the front, radiating face of the transducer with the aim to match the acoustic impedance of the medium and to enlarge the bandwidth. In this paper an optimisation work is shown to demonstrate that a composite configuration can be used in the matching layer, in order to improve the efficiency and the band of the transducer. An approximated two–dimensional analytical model has been used to optimise the design of a composite–structured matching layer in the case of 2–2 composites, obtaining different results for the polymer and piezoceramic composite phases; a design technique is suggested in order to improve the transducer performance. With the aim to verify the proposed design criterion, a transducer prototype, based on a 2–2 piezocomposite, with a composite matching layer was realised. On this sample we measured the electrical input impedance and the insertion loss and we compared the obtained results with those of a transducer classically matched to the load. The obtained results confirm the computed improvements in the transducer performance and justify the proposed design approach.

  • chapterNo Access

    Lateral Resolution Enhancement of Ultrasound Images Using Neural Networks

    Spatial resolution in modern ultrasound imaging systems is limited by the high cost of large aperture transducer arrays, which means large number of transducer elements and electronic channels. A new technique to enhance the lateral resolution of pulse-echo imaging system is presented. The method attempts to build an image which could be obtained with a transducer array aperture larger than that physically available. We consider two images obtained imaging the same object with two different apertures, the full aperture and a sub aperture, of the same transducer. A suitable artificial neural network (ANN) is trained to reproduce the relationship between the image obtained with the transducer full aperture and the image obtained with a sub aperture. After a suitable training, the network is able to produce images with almost the same resolution of the full aperture transducer, but using a reduced number of real transducer elements. All the computations are carried out on envelope-detected decimated images: the overall computational cost is low and the method is suitable for real time applications. The proposed method was applied on experimental data obtained with the ultrasound synthetic aperture focusing technique (SAFT), giving quite promising results. Real-time implementation on a modern full digital echographic system is currently being developed.

  • chapterNo Access

    LOCALIZATION OF SENSOR NETWORKS USING ULTRASOUNDS AND RADIO FREQUENCY

    A very efficient localization system, capable to localize multiple identical sensor nodes (SNs), based on mixed acoustic and radio frequency communication is proposed. The remote devices are identical in the sense that each remote device emits signals that are indistinguishable from each other, i.e. there is not any identification code. A set of beacons emits a sequence of acoustic pulses in the space region containing the sensor nodes. When impinged by the acoustic wave front, each sensor node, independently from each other, sends back a radio frequency (RF) acknowledge signal to a central information processor (CIP) or radio base. The radio base, knowing the positions of the acoustic beacons and the time of arrival of the acknowledge signals, computes the positions of the sensor nodes with a suitable algorithm, identifying and discarding possible false signals due to echoes and environmental noise.