An overview of wireless networks in control and monitoring

This paper provides an overview of the current field in wireless networks for monitoring and control. Alternative wireless technologies are introduced, together with current typical industrial applications. The focus then shifts to wireless Ethernet and the specialised requirements for wireless networked control systems (WNCS) are discussed. This is followed by a brief look at some current WNCS research, including reduced communication control.

The design and performance of a 2.5-GHz telecommand link for wireless biomedical monitoring

This paper details the implementation and operational performance of a minimum-power 2.45-GHz pulse receiver and a companion on-off keyed transmitter for use in a semi-active duplex RF biomedical transponder. A 50-Ohm microstrip stub-matched zero-bias diode detector forms the heart of a body-worn receiver that has a CMOS baseband amplifier consuming 20 microamps from +3 V and achieves a tangential sensitivity of -53 dBm. The base transmitter generates 0.5 W of peak RF output power into 50 Ohms. Both linear and right-hand circularly polarized Tx-Rx antenna sets were employed in system reliability trials carried out in a hospital Coronary Care Unit, For transmitting antenna heights between 0.3 and 2.2 m above floor level, transponder interrogations were 95% reliable within the 67-m-sq area of the ward, falling to an average of 46 % in the surrounding rooms and corridors. Overall, the circular antenna set gave the higher reliability and lower propagation power decay index.

Purification of imidazolium ionic liquids for spectroscopic applications

Ionic liquids are often contaminated by colored impurities. These impurities can be problematic for spectroscopic studies or for monitoring organic reactions by UV/Vis spectroscopy. The effect of different purification methods on the optical quality of colored ionic liquids was studied and compared. Yellowish ionic liquids can partially be decolorized by treatment with active charcoal or by recrystallization. Our experiments show column liquid chromatography is not always a good technique to prepare spectrograde imidazolium halide ionic liquids. Colorless and UV-transparent ionic liquids were synthesized by a method that can exclude the need for further purification steps. (c) 2005 Elsevier B.V. All rights reserved.

Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Home-Based Monitoring and Assessment of Parkinson's Disease

As a clinically complex neurodegenerative disease, Parkinson's disease (PD) requires regular assessment and close monitoring. In our current study, we have developed a home-based tool designed to monitor and assess peripheral motor symptoms. An evaluation of the tool was carried out over a period of ten weeks on ten people with idiopathic PD. Participants were asked to use the tool twice daily over four days, once when their medication was working at its best (

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

The inferential monitoring of the screw disturbance torque to predict process fluctuations in polymer extrusion

Polymer extrusion is one of the major methods of processing polymer materials and advanced process monitoring is important to ensure good product quality. However, commonly used process monitoring devices, e.g. temperature and pressure sensors, are limited in providing information on process dynamics inside an extruder barrel. Screw load torque dynamics, which may occur due to changes in solids conveying, melting, mixing, melt conveying, etc., are believed to be a useful indicator of process fluctuations inside the extruder barrel. However, practical measurement of the screw load torque is difficult to achieve. In this work, inferential monitoring of the screw load torque signal in an extruder was shown to be possible by monitoring the motor current (armature and/or field) and simulation studies were used to check the accuracy of the proposed method. The ability of this signal to aid identification and diagnosis of process issues was explored through an experimental investigation. Power spectral density and wavelet frequency analysis were implemented together with a covariance analysis. It was shown that the torque signal is dominated by the solid friction in the extruder and hence it did not correlate well with melting fluctuations. However, it is useful for online identification of solids conveying issues.

Fluidised bed characterisation using Raman spectroscopy: Applications to pharmaceutical processing

This study investigates a model system for potential pharmaceutical materials in fluidised bed processes. In particular, this study proposes a novel use of Raman spectroscopy, which allows in situ measurement of the composition of the material within the fluidised bed in three spatial dimensions and as a function of time. This is achieved by recording Raman spectra from specific volumes of space. The work shows that Raman spectroscopy can be used to provide 3D maps of the concentration and chemical structure of the particles in a fluidised bed within a relatively short (120 s) time window. At the most basic level the technique measures particle density via the intensity of the Raman spectra, however this could be used. More importantly the data are also rich in spectroscopic information on the chemical structure of the fluidised particles which is useful either for monitoring a given granulation process or more generally for the analysis of the dynamics of the airflow if the data were incorporated into an appropriate model. The technique has the potential to give detailed in situ information on how the structure and composition of the granules/powders within the fluidised bed (dryer or granulator) vary with the position and evolve with time. (c) 2007 Elsevier Ltd. All rights reserved.

Monitoring the moisture transport in building stones using fibre optic relative humidity sensors

Weathering of stone is one of the major reasons for the damage of stone masonry structures and it takes place due to interlinked chemical, physical and biological processes in stones. The key parameters involved in the deterioration processes are temperature, moisture and salt. It is now known that the sudden variations in temperature and moisture greatly accelerate the weathering process of the building stone fabric. Therefore, in order to monitor these sudden variations an effective and continuous monitoring system is needed. Furthermore, it must consist of robust sensors which are accurate and can survive in the harsh environments experienced in and around masonry structures. Although salt penetration is important for the rate of deterioration of stone masonry structures, the processes involved are much slower than the damage associated with temperature and moisture variations. Therefore, in this paper a novel fibre optic temperature cum relative humidity sensor is described and its applicability in monitoring building stones demonstrated. The performance of the sensor is assessed in an experiment comprising wetting and drying of limestone blocks. The results indicate that the novel fibre optic relative humidity sensor which is tailor made for applications in masonry structures performed well in wetting and drying tests, whilst commercial capacitance based sensors failed to recover during the drying regime for a long period after a wetting regime. That is, the fibre optic sensor has the capability to measure both sorption and de-sorption characteristics of stone blocks. This sensor is used in a test wall in Oxford and the data thus obtained strengthened the laboratory observations.

Microneedle-Mediated Minimally Invasive Patient Monitoring

Background: The emerging field of microneedle-based minimally invasive patient monitoring and diagnosis is reviewed. Microneedle arrays consist of rows of micron-scale projections attached to a solid support. They have been widely investigated for transdermal drug and vaccine delivery applications since the late 1990s. However, researchers and clinicians have recently realized the great potential of microneedles for extraction of skin interstitial fluid and, less commonly, blood, for enhanced monitoring of patient health.

Methods: We reviewed the journal and patent literature, and summarized the findings and provided technical insights and critical analysis.

Results: We describe the basic concepts in detail and extensively review the work performed to date.

Conclusions: It is our view that microneedles will have an important role to play in clinical management of patients and will ultimately improve therapeutic outcomes for people worldwide.

Choosing and using diversity indices: Insights for ecological applications from the German Biodiversity Exploratories

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D1), Simpson's dominance (D2), Simpson's evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.

Wearable inkjet-printed antenna performance for medical applications at 868/915 MHz

The use of biosensors attached to the body for health monitoring is now readily accepted, and the merits of such systems and their potential impact on healthcare receive much attention. Wearable medical systems used in clinical applications to monitor vital signs must be comfortable to wear, yet have robust performance to ensure reliable communications links. Additionally, and vital to the success of these innovations, is that these solutions are disposable to avoid risk of patient infection and this means that they must be ultra-low cost. Antennas optimized for printing using conductive inks offer new exciting advances in making a truly disposable solution.

Python PSS/E Simulation to Test Efficacy of Proposed PMU Based WAMS and Potential WAMPAC Applications

A PSS/E 32 model of a real section of the Northern Ireland electrical grid was dynamically controlled with Python 2.5. In this manner data from a proposed wide area monitoring system was simulated. The area is of interest as it is a weakly coupled distribution grid with significant distributed generation. The data was used to create an optimization and protection metric that reflected reactive power flow, voltage profile, thermal overload and voltage excursions. Step changes in the metric were introduced upon the operation of special protection systems and voltage excursions. A wide variety of grid conditions were simulated while tap changer positions and switched capacitor banks were iterated through; with the most desirable state returning the lowest optimization and protection metric. The optimized metric was compared against the metric generated from the standard system state returned by PSS/E. Various grid scenarios were explored involving an intact network and compromised networks (line loss) under summer maximum, summer minimum and winter maximum conditions. In each instance the output from the installed distributed generation is varied between 0 MW and 80 MW (120% of installed capacity). It is shown that in grid models the triggering of special protection systems is delayed by between 1 MW and 6 MW (1.5% to 9% of capacity), with 3.5 MW being the average. The optimization and protection metric gives a quantitative value for system health and demonstrates the potential efficacy of wide area monitoring for protection and control.