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1 – 10 of 416Crystallization is the process widely used for components separation and solids purification. The systems for crystallization process evaluation applied so far, involve numerous…
Abstract
Purpose
Crystallization is the process widely used for components separation and solids purification. The systems for crystallization process evaluation applied so far, involve numerous non-invasive tomographic measurement techniques which suffers from some reported problems. The purpose of this paper is to show the abilities of three-dimensional Electrical Capacitance Tomography (3D ECT) in the context of non-invasive and non-intrusive visualization of crystallization processes. Multiple aspects and problems of ECT imaging, as well as the computer model design to work with the high relative permittivity liquids, have been pointed out.
Design/methodology/approach
To design the most efficient (from a mechanical and electrical point of view) 3D ECT sensor structure, the high-precise impedance meter was applied. The three types of sensor were designed, built, and tested. To meet the new concept requirements, the dedicated ECT device has been constructed.
Findings
It has been shown that the ECT technique can be applied to the diagnosis of crystallization. The crystals distribution can be identified using this technique. The achieved measurement resolution allows detecting the localization of crystals. The usage of stabilized electrodes improves the sensitivity of the sensor and provides the images better suitable for further analysis.
Originality/value
The dedicated 3D ECT sensor construction has been proposed to increase its sensitivity in the border area, where the crystals grow. Regarding this feature, some new algorithms for the potential field distribution and the sensitivity matrix calculation have been developed. The adaptation of the iterative 3D image reconstruction process has also been described.
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Juliana Padilha Leitzke and Hubert Zangl
This paper aims to present an approach based on electrical impedance tomography spectroscopy (EITS) for the determination of water and ice fraction in low-power applications such…
Abstract
Purpose
This paper aims to present an approach based on electrical impedance tomography spectroscopy (EITS) for the determination of water and ice fraction in low-power applications such as autarkic wireless sensors, which require a low computational complexity reconstruction approach and a low number of electrodes. This paper also investigates how the electrode design can affect the reconstruction results in tomography.
Design/methodology/approach
EITS is performed by using a non-iterative method called optimal first order approximation. In addition to that, a planar electrode geometry is used instead of the traditional circular electrode geometry. Such a structure allows the system to identify materials placed on the region above the sensor, which do not need to be confined in a pipe. For the optimization, the mean squared error (MSE) between the reference images and the obtained reconstructed images was calculated.
Findings
The authors demonstrate that even with a low number of four electrodes and a low complexity reconstruction algorithm, a reasonable reconstruction of water and ice fractions is possible. Furthermore, it is shown that an optimal distribution of the sensor electrodes can help to reduce the MSE without any costs in terms of computational complexity or power consumption.
Originality/value
This paper shows through simulations that the reconstruction of ice and water mixtures is possible and that the electrode design is a topic of great importance, as they can significantly affect the reconstruction results.
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Cara Greta Kolb, Maja Lehmann, Johannes Kriegler, Jana-Lorena Lindemann, Andreas Bachmann and Michael Friedrich Zaeh
This paper aims to present a requirements analysis for the processing of water-based electrode dispersions in inkjet printing.
Abstract
Purpose
This paper aims to present a requirements analysis for the processing of water-based electrode dispersions in inkjet printing.
Design/methodology/approach
A detailed examination of the components and the associated properties of the electrode dispersions has been carried out. The requirements of the printing process and the resulting performance characteristics of the electrode dispersions were analyzed in a top–down approach. The product and process side were compared, and the target specifications of the dispersion components were derived.
Findings
Target ranges have been identified for the main component properties, balancing the partly conflicting goals between the product and the process requirements.
Practical implications
The findings are expected to assist with the formulation of electrode dispersions as printing inks.
Originality/value
Little knowledge is available regarding the particular requirements arising from the systematic qualification of aqueous electrode dispersions for inkjet printing. This paper addresses these requirements, covering both product and process specifications.
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Yishou Wang, Zhibin Han, Tian Gao and Xinlin Qing
The purpose of this study is to develop a cylindrical capacitive sensor that has the advantages of high resolution, small size and designability and can be easily installed on…
Abstract
Purpose
The purpose of this study is to develop a cylindrical capacitive sensor that has the advantages of high resolution, small size and designability and can be easily installed on lubricant pipeline to monitor lubricant oil debris.
Design/methodology/approach
A theoretical model of the cylindrical capacitive sensor is presented to analyze several parameters’ effectiveness on the performance of sensor. Numerical simulations are then conducted to determine the optimal parameters for preliminary experiments. Experiments are finally carried out to demonstrate the detectability of developed capacitive sensors.
Findings
It is clear from experimental results that the developed capacitive sensor can monitor the debris in lubricant oil well, and the capacitance values increase almost linearly when the number and size of debris increase.
Research limitations/implications
There is lot of further work to do to apply the presented method into the application. Especially, it is necessary to consider several factors’ influence on monitoring results. These factors include the flow rate of the lubricant oil, the temperature, the debris distribution and the vibration. Moreover, future work should consider the influence of the oil degradation to the capacitance change and other contaminations (e.g. water and dust).
Practical implications
This work conducts a feasibility study on application of capacitive sensing principle for detecting debris in aero engine lubricant oil.
Originality/value
The novelty of the presented capacitance sensor can be summarized into two aspects. One is that the sensor structure is simple and characterized by two coaxial cylinders as electrodes, while conventional capacitive sensors are composed of two parallel plates as electrodes. The other is that sensing mechanism and physical model of the presented sensor is verified and validated by the simulation and experiment.
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Manju Priya Arthanarisamy Ramaswamy and Suja Palaniswamy
The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG)…
Abstract
Purpose
The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.
Design/methodology/approach
DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.
Findings
The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.
Originality/value
Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.
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