Brian S. Hoyle

Process tomography using ultrasonic sensors

The use of ultrasonic transducers for process tomography is in its infancy relative to many other techniques, in particular considering the widespread use of ultrasonic transducers in a variety of non-tomographic sensing applications. This review deals with the background sensing principles of ultrasound transducers employed in tomography, their associated advantages and their difficulties, including the critical time required for data collection, and implications for multiple projection tomography. The theoretical and basic practical implementation of tomography systems using ultrasonic transducers is then considered. Finally a review is included of research investigations into the use of ultrasonic-based process tomography systems.

Design and application of a multi-modal process tomography system

This paper presents a design and application study of an integrated multi-modal system designed to support a range of common modalities: electrical resistance, electrical capacitance and ultrasonic tomography. Such a system is designed for use with complex processes that exhibit behaviour changes over time and space, and thus demand equally diverse sensing modalities. A multi-modal process tomography system able to exploit multiple sensor modes must permit the integration of their data, probably centred upon a composite process model. The paper presents an overview of this approach followed by an overview of the systems engineering and integrated design constraints. These include a range of hardware oriented challenges: the complexity and specificity of the front-end electronics for each modality; the need for front-end data pre-processing and packing; the need to integrate the data to facilitate data fusion; and finally the features to enable successful fusion and interpretation. A range of software aspects are also reviewed: the need to support differing front-end sensors for each modality in a generic fashion; the need to communicate with front-end data pre-processing and packing systems; the need to integrate the data to allow data fusion; and finally to enable successful interpretation. The review of the system concepts is illustrated with an application to the study of a complex multi-component process.

Electrical Impedance Spectroscopy Sensing for Industrial Processes

A sensing method is presented which offers major potential benefits for industrial processes. The method, developed from electrical spectroscopy, aims to discriminate between the component materials in a process and, with calibration data, identify specific materials; for example in batch chemical reactors for the manufacture of pharmaceutical products. The method addresses the key design need to complete a sensing operation within a temporal window that allows for the process dynamics. Two key system requirements are considered. First, a review is included of candidate excitation signals, in terms of the major parameters of interest, for the relevant frequency range. Second, the acquisition of the corresponding response signals and the extraction of the spectroscopic data from which the materials of interest may be identified. This is based upon an algorithm which is introduced based on the wavelet transform. The composite method is illustrated in trials using a process impedance simulation model and experimental tests on a crystallization process. This paper offers conclusions for applications of the fast sensing method to characterize different process (and other) materials.

Simulations for parallel processing of ultrasound reflection-mode tomography with applications to two-phase flow measurement

An evaluation of the application of a parallel-processing array to the measurement of two-phase flow, such as bubbly oil flow through a pipe, in real-time is described. Pulse-echo ultrasound tomography is used to generate a cross-sectional image of the flow that forms the basis for the deduction of flow parameters, such as the void fraction. The tomographic algorithm used is backprojection adapted for execution on an array of parallel-processing devices. It is shown that real-time reconstruction is feasible using the concepts of parallel processing. Different sensor arrangements were investigated by computer simulation. It is shown that a special multisegment sensor results in a significant improvement in signal-to-noise ratio and image quality and that the reconstructed image benefits from the concurrent activation of multiple receivers per transmitted pulse. The findings may also be useful for nondestructive testing and medical applications.<<ETX>>

Ultrasound process tomography system for hydrocyclones

The implementation of a laboratory-based ultrasound tomography system to an industrial process application is not straightforward. In the present work, a tomography system with 16 transducers has been applied to an industrial 50 mm hydrocyclone to visualize its air-core size and position. Hydrocyclones are used to separate fine particles from a slurry. The efficiency of the separation process depends on the size of the air core within the cyclone. If the core is too large due to spigot wear, there will be a detrimental effect on the slurry throughput. Conversely, if the throughput is increased to an extent where the air core becomes unstable or disappears, the particle separation will no longer take place, and the processed batches may become contaminated. Ultrasound tomography presents a very good tool with which to visualize the size, position and movement of the air core and monitor its behaviour under varying input parameters. Ultimately, it could be used within this application both to control the input flow rate depending on the air core size and to detect spigot wear. This paper describes the development of an ultrasonic tomography system applied to an instrumented hydrocyclone. Time-of-flight data are captured by a dedicated acquisition system that pre-processes the information using a DSP and transfers the results to a PC via a fast serial link. The hardware of the tomography system is described, and cursory results are presented in the form of reconstructed images of the air core within the hydrocyclone.

Wideband electrical impedance tomography

This paper addresses the augmentation of a conventional single frequency electrical impedance tomography (EIT) system to form a wideband EIT system. This extends the system to provide spectral information, but with the essential capability to match process dynamics. The underlying opportunity for this study is that process materials may show considerable change in their electrical properties in response to an injected signal over a wide frequency range. This concept is used in the paper to demonstrate the construction of tomographic images for a range of frequency bands that can provide a deeper understanding and interpretation of a process under investigation. This paper describes a trial simulation of this approach and an experimental study. To provide measurements over the required frequency range a linear chirp is used as the excitation signal. Corresponding peripheral measurements have been synthesized using a 2D model in association with the EIDORS forward solver. The measurements are then analysed using an algorithm based on the wavelet transform to reveal spectral band datasets. In the presented feasibility trial a single-channel EIT chirp excitation was implemented, in essence simulating a real-time parallel data collection system, through the use of pseudo-static tests on foodstuff materials. The experimental data were then analysed and tomographic images were reconstructed using the frequency-banded data. The qualitative feasibility results illustrate the promise of this composite approach in exploiting sensitivity to variations over a wide frequency range. They indicate that the described method can augment an EIT sensing procedure to support spectroscopic analysis of the process materials.

Mobility AT: The Batcane (UltraCane)

The use of the long cane by visually impaired people as an obstacle detector is long standing. More recently the basic cane design has been equipped with laser or ultrasound transmitters and sensors and an interpretive human interface to improve its effectiveness, the objective being to allow safe travel by a visually impaired person. This chapter reports an important case study of the steps involved indeveloping an advanced technology obstacle avoidance cane that used bat echolocation signal processing techniques and ultrasonic technology. The final cane design is now marketed worldwide as the UltraCane™.

Model-based parameterisation of a hydrocyclone air-core

An important metric for the accurate control of a hydrocyclone is the diameter of its air-core. Ultrasonic data from a 16-transducer, 1.5 MHz pulse-echo tomographic system are analysed to determine the variation of the air-core diameter with various operating conditions. The back-projection image reconstruction method is not accurate enough for this task. Sub-millimetre accuracy is obtained, however, by applying a combination of signal processing and model-based reconstruction, using the fact that there is a small variation in the air-core boundary position. The findings correspond well to the results obtained from X-ray and electrical resistance modalities.

Determination of multi-component flow process parameters based on electrical capacitance tomography data using artificial neural networks

Artificial neural networks (ANNs) have been used to investigate their capabilities at estimating key parameters for the characterization of flow processes, based on electrical capacitance-sensed tomographic (ECT) data. The estimations of the parameters are made directly, without recourse to tomographic images. The parameters of interest include component height and interface orientation of two-component flows, and component fractions of two-component and three-component flows. Separate multi-layer perceptron networks were trained with patterns consisting of pairs of simulated ECT data and the corresponding component heights, interface orientations and component fractions. The networks were then tested with patterns consisting of unlearned simulated ECT data of various flows and with real ECT data of gas–water flows. The neural systems provided estimations having mean absolute errors of less than 1% for oil and water heights and fractions and less than 10° for interface orientations. When tested with real plant ECT data, the mean absolute errors were less than 4% for water height, less than 15° for gas–water interface orientation and less than 3% for water fraction, respectively. The results demonstrate the feasibility of the application of ANNs for flow process parameter estimations based upon tomography data.

Ultrasound reflection tomography for industrial processes

Abstract The use of ultrasound reflection mode tomography has mainly been investigated with a reduced number of transducers, often just two. In a typical configuration one sensor is stationary while a second sensor is rotated around a circular arc taking a number of tomographic measurements which are used to reconstruct an image. While this arrangement allows measurements to be made from a large number of positions around an object (sometimes over 100 positions), it is not fast enough to provide the real-time information which is required by many industrial processes. This work describes an ultrasound reflection mode system with a circular array of 36 transducers that is able to generate reconstructed images at an average of 30 frames per second. To achieve this speed of image reconstruction an intensive use of processing resources is required. A parallel processor array is employed for the reconstruction of the image frames and the data acquisition is assisted by a dedicated digital signal processor (DSP). The results obtained by this system in the form of images of test objects, with a resolution of 100 × 100 pixels, show that reasonably good results can be obtained with ultrasonic tomography systems in the explored configuration.