Abstract
In this introduction article, we present a brief overview of industrial process tomography. This will start by linking between the concept of industrial process tomography and super-sensing. This will follow with a brief introduction to various process tomography systems and in particular electrical tomography methods.
This article is part of the themed issue ‘Supersensing through industrial process tomography’.
Keywords: industrial process tomography, super-sensing, electrical tomography
1. Process monitoring and super-sensing
Super-sensing by means of industrial process tomography tools allows us to see inside a process [1,2]. This is done through non-invasive and non-intrusive measurements that have high spatial and temporal resolution and that use analysis methods that together constitute the theory of tomographic imaging. There have been exciting developments in this area over the past few years, which have led to many new commercial opportunities. Further development will make these technologies widely used in more and more manufacturing processes, leading to cost-effective, energy-efficient and more importantly more sustainable processes. It is well understood that a new scientific direction is needed to capitalize on past progress and to enable future developments. Industrial process tomography can now be better understood by the concept of super-sensing. The terminology of super-sensing in this special issue is a first step to bringing various disciplines in this field together by means of multi-dimensional sensing and analysis.
2. Tomographic imaging
Tomography is a technique that creates a cross-sectional or volumetric image of the internal physical properties of an object. Tomography is imaging of the body or object by exposing it to a penetrating wave. There are three main elements to tomography: the source of the wave, detectors to absorb the wave and the image construction algorithm. The emitted and received wave varies depending on the medium to which it is exposed; the variation in the signal is used to construct an image. The two main categories are ‘hard-field tomography’ and ‘soft-field tomography’ (figure 1). There are several examples of each of these types of tomography. Hard-field tomography includes X-ray tomography, ultrasound tomography, hydraulic tomography, gamma-ray tomography and magnetic resonance imaging (MRI). Soft-field tomography includes electrical impedance tomography (EIT), electrical capacitance tomography (ECT), magnetic induction tomography (MIT) and optical tomography. Hard-field tomography has different characteristics from soft-field tomography. One of the ways in which they differ is that in hard-field tomography, such as X-ray, the path of the transmitting signal is in a straight line pattern, and the only factor that can affect the signal strength is the material along that path, regardless of the position of the material. For soft-field tomography, such as MIT and EIT, there are other factors that can influence the transmitting signal, such as the distribution of the electrical parameters (conductivity and permeability) inside and outside the measuring region and especially the lines between the source and the detector [3]. This presents some difficulty when computing the image reconstruction algorithm for soft-field tomography. At the same time, there are extensive similarities in the fundamentals of the mathematics of imaging in both hard-field and soft-field tomographies [4,5].
Figure 1.
Classification of tomography. (Online version in colour.)
Both soft-field and hard-field tomographies are part of the industrial process tomography methods. Table 1 [6] summarizes a number of existing tomography techniques with their characteristics and suitable applications.
Table 1.
| tomography technique | characteristics | applications | |
|---|---|---|---|
| electromagnetism | gamma-ray | radioactive source, fast scanning | industrial and medical imaging |
| (hard field) | |||
| X-ray | high resolution, mechanically scanned, radiation confinement | industrial and medical imaging | |
| UV, optical | fast, optical access | microstructure and medical monitoring | |
| millimetre wave | system component emerging | air traffic monitoring | |
| electromagnetism | microwave | fast, moderate resolution | thermal mapping of reactor, breast |
| (soft field) | (wavelength dependence) | cancer imaging | |
| capacitive (ECT) | low resolution, contactless | passive electrical property imaging, in processes and materials | |
| impedance (EIT) | fast, low cost | medical, industrial and geophysical applications | |
| inductance (MIT) | contactless, low cost | medical and industrial imaging | |
| nuclear particle | positron emission | similar to computed tomography reconstruction, functional imaging | medical imaging |
| neutron | high resolution, radioactive source | microstructure, industrial imaging | |
| others | MRI | high resolution, soft-tissue imaging | medical and industrial imaging |
| ultrasound | high resolution | medical and industrial imaging | |
| thermal conduction | slow, soft field | industrial |
(a). Electrical tomography
Electrical tomography uses the electrical properties of the medium to construct an image. The conductivity, electric field and magnetic field vary depending on the medium. The system responds rapidly and is relatively inexpensive compared with other methods, such as X-rays; also, it is not harmful. The downside of electrical tomography is its low resolution and complicated image construction algorithm. Electrical tomography has numerous applications, such as investigating rocks in geology and investigating wear on pipelines and fluid flow in industrial processes. The different sensing techniques for electrical tomography are presented in table 2.
Table 2.
Electrical tomography techniques [6]. (Online version in colour.)
 |
As an example, EIT is a tomographic imaging system that is capable of providing high temporal resolution with low spatial resolution. The system operates by injecting constant current between two pairs of electrodes and measuring the potential difference on the remaining electrodes. The potential difference is dependent upon the conductivity of the object. Figure 2 shows the EIT measurement principle. The hardware consists of electrodes, data acquisition and software to create images; a test phantom (figure 2b,c) is often used to verify EIT imaging. Figure 2c shows an EIT image of electrical conductivity variation due to the presence of a plastic bottle in a conductive saline background. After verifying a process tomography system in laboratory-based phantom studies, the system goes through field studies with real industrial process monitoring [1].
Figure 2.
An EIT measurement principle (V 1) is measured after current (I) has been injected (a). Typically, phantoms are used for proof-of-principle and reconstructed images (b,c). (Online version in colour.)
3. Conclusion
The super-sensing measurements are techniques that are providing spatially and temporally aware information about the inside of industrial processes. The field of research is in a transition period of going from a tool for R&D engineers to a monitoring tool for the production line. Research in the field has increased very rapidly in the past few years, mainly due to higher computing power, which has allowed multi-dimensional imaging to be carried out in near real time. Commercial companies are near to developing real-time three-dimensional imaging, which was unthinkable a decade ago. Superior algorithms and computational enhancement have played a key role in bringing this field to the point that it can lead to successful commercial development. This special issue highlights some of the recent progress and opens up a new frontier.
Competing interests
I declare I have no competing interests.
Funding
I received no funding for this paper.
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