Evolving techniques for characterising and monitoring the stability of infrastructure slopes

Landslides and debris flows, commonly triggered by rainfall, pose a geotechnical risk causing disruption to transport routes and incur significant financial expenditure. With infrastructure maintenance budgets becoming ever more constrained, this paper provides an overview of some of the developing methods being implemented by Queen’s University, Belfast in collaboration with the Department for Regional Development to monitor the stability of two distinctly different infrastructure slopes in Northern Ireland. In addition to the traditional, intrusive ground investigative and laboratory testing methods, aerial LiDAR, terrestrial LiDAR, geophysical techniques and differential Global Positioning Systems have been used to monitor slope stability. Finally, a comparison between terrestrial LiDAR, pore water pressure and soil moisture deficit (SMD) is presented to outline the processes for a more informed management regime and to highlight the season relationship between landslide activity and the aforementioned parameters.

Time-lapse Monitoring of the Slopes of a Heritage Earthwork by Means of Near-surface Seismic Techniques

A significant portion of UK’s infrastructures earthworks was built more than 100 years ago, without modern construction standards: poor maintenance and the change of precipitations pattern experienced in the past decades are currently compromising their stability, leading to an increasing number of failures. To address the need for a reliable and time-efficient monitoring of earthworks at risk of failure we propose here the use of two established seismic techniques for the characterization of the near surface, MASW and P-wave refraction. We have regularly collected MASW and P-wave refraction data, from March 2014 to February 2015, along 4 reduced-scale seismic lines located on the flanks of a heritage railway embankment located in Broadway, SW of England. We have observed a definite temporal variability in terms of phase velocities of SW dispersion curves and of P-wave travel times. The accurate choice of ad-hoc inversion strategies has allowed to reconstruct reliable VP and VS models through which it is potentially possible to track the temporal variations of geo-mechanical properties of the embankment slopes. The variability over time of seismic data and seismic velocities seems to correlate well with rainfall data recorded in the days immediately preceding the date of acquisition.

Process monitoring approach using fast moving window PCA

This paper introduces a fast algorithm for moving window principal component analysis (MWPCA) which will adapt a principal component model. This incorporates the concept of recursive adaptation within a moving window to (i) adapt the mean and variance of the process variables, (ii) adapt the correlation matrix, and (iii) adjust the PCA model by recomputing the decomposition. This paper shows that the new algorithm is computationally faster than conventional moving window techniques, if the window size exceeds 3 times the number of variables, and is not affected by the window size. A further contribution is the introduction of an N-step-ahead horizon into the process monitoring. This implies that the PCA model, identified N-steps earlier, is used to analyze the current observation. For monitoring complex chemical systems, this work shows that the use of the horizon improves the ability to detect slowly developing drifts.

Microporation Techniques for Enhanced Delivery of Therapeutic Agents

Perhaps the greatest barrier to development of the field of transmembrane drug delivery is that only a limited number of drugs are amenable to administration by this route. The highly lipophilic nature and barrier function of the uppermost layer of the skin, the stratum corneum, for example, restricts the permeation of hydrophilic, high molecular weight and charged compounds into the systemic circulation. Other membranes in the human body can also present significant barriers to drug permeation. In order to successfully deliver hydrophilic drugs, and macromolecular agents of interest, including peptides, DNA and small interfering RNA, many research groups and pharmaceutical companies Worldwide are focusing on the use of microporation methods and devices. Whilst there are a variety of microporation techniques, including the use of laser, thermal ablation, electroporation, radiofrequency, ultrasound, high pressure jets, and microneedle technology, they share the common goal of enhancing the permeability of a biological membrane through the creation of transient aqueous transport pathways of micron dimensions across that membrane. Once created, these micropores are orders of magnitude larger than molecular dimensions and, therefore, should readily permit the transport of hydrophilic macromolecules. Additionally, microporation devices also enable minimally-invasive sampling and monitoring of biological fluids. This review deals with the innovations relating to microporation-based methods and devices for drug delivery and minimally invasive monitoring, as disclosed in recent patent literature. © 2010 Bentham Science Publishers Ltd.

Application of Geophysical Techniques in Identifying Illegally Buried Toxic Waste

Ground-penetrating radar (GPR) is a rapid geophysical technique that we have used to assess four illegally buried waste locations in Northern Ireland. GPR allowed informed positioning of the less-rapid, if more accurate use of electrical resistivity imaging (ERI). In conductive waste, GPR signal loss can be used to map the areal extent of waste, allowing ERI survey lines to be positioned. In less conductive waste the geometry of the burial can be ascertained from GPR alone, allowing rapid assessment. In both circumstances, the conjunctive use of GPR and ERI is considered best practice for cross-validation of results and enhancing data interpretation.

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.

Developing a simple, rapid method for identifying and monitoring jellyfish aggregations from the air

Within the marine environment, aerial surveys have historically centred on apex predators, such as pinnipeds, cetaceans and sea birds. However, it is becoming increasingly apparent that the utility of this technique may also extend to subsurface species such as pre-spawning fish stocks and aggregations of jellyfish that occur close to the surface. In light of this, we tested the utility of aerial surveys to provide baseline data for 3 poorly understood scyphozoan jellyfish found throughout British and Irish waters: Rhizostoma octopus, Cyanea capillata and Chrysaora hysoscella. Our principal objectives were to develop a simple sampling protocol to identify and quantify surface aggregations, assess their consistency in space and time, and consider the overall applicability of this technique to the study of gelatinous zooplankton. This approach provided a general understanding of range and relative abundance for each target species, with greatest suitability to the study of R. octopus. For this species it was possible to identify and monitor extensive, temporally consistent and previously undocumented aggregations throughout the Irish Sea, an area spanning thousands of square kilometres. This finding has pronounced implications for ecologists and fisheries managers alike and, moreover, draws attention to the broad utility of aerial surveys for the study of gelatinous aggregations beyond the range of conventional ship-based techniques.

Rapid construction of arch bridges using the innovative FlexiArch

Masonry arches are strong, durable, aesthetically pleasing and largely maintenance free, yet since 1900 there has been a dramatic decline in their use. However, designers, contractors and clients now have access to a new method of constructing arches incorporating precast concrete voussoirs interconnected via polymeric reinforcement and a concrete screed. No centring is necessary, as the FlexiArch, when it is lifted, transforms under the forces of gravity into the desired arch shape. After discussing general aspects of innovation, the basic concept of the arch bridge system is presented along with technological advances since it was patented. Experiences gained from building over 40 FlexiArch bridges in the UK and Ireland and from model and full-scale tests carried out to validate the system during installation and in service are described. Thus under load the system behaves like a traditional masonry arch and existing analysis methods can be used for design and assessment.

A novel method of embedding distributed optical fiber sensor for structural health monitoring

A distributed optical fiber sensor based on Brillouin scattering (BOTDR or BOTDA) can measure and monitor strain and temperature generated along optical fiber. Because it can measure in real-time with high precision and stability, it is quite suitable for health monitoring of large-scale civil infrastructures. However, the main challenge of applying it to structural health monitoring is to ensure it is robust and can be repaired by adopting a suitable embedding method. In this paper, a novel method based on air-blowing and vacuum grouting techniques for embedding long-distance optical fiber sensors was developed. This method had no interference with normal concrete construction during its installation, and it could easily replace the long-distance embedded optical fiber sensor (LEOFS). Two stages of static loading tests were applied to investigate the performance of the LEOFS. The precision and the repeatability of the LEOFS were studied through an overloading test. The durability and the stability of the LEOFS were confirmed by a corrosion test. The strains of the LEOFS were used to evaluate the reinforcing effect of carbon fiber reinforced polymer and thereby the health state of the beams.

Fibre-optic strain sensor system with temperature compensation for arch bridge condition monitoring

This paper presents an innovative sensor system, created specifically for new civil engineering structural monitoring applications, allowing specially packaged fiber grating-based sensors to be used in harsh, in-the-field measurement conditions for accurate strain measurement with full temperature compensation. The sensor consists of two fiber Bragg gratings that are protected within a polypropylene package, with one of the fiber gratings isolated from the influence of strain and thus responding only to temperature variations, while the other is sensitive to both strain and temperature. To achieve this, the temperature-monitoring fiber grating is slightly bent and enclosed in a metal envelope to isolate it effectively from the strain. Through an appropriate calibration process, both the strain and temperature coefficients of each individual grating component when incorporated in the sensor system can be thus obtained. By using these calibrated coefficients in the operation of the sensor, both strain and temperature can be accurately determined. The specific application for which these sensors have been designed is seen when installed on an innovative small-scale flexi-arch bridge where they are used for real-time strain measurements during the critical installation stage (lifting) and loading. These sensors have demonstrated enhanced resilience when embedded in or surface-mounted on such concrete structures, providing accurate and consistent strain measurements not only during installation but subsequently during use. This offers an inexpensive and highly effective monitoring system tailored for the new, rapid method of the installation of small-scale bridges for a variety of civil engineering applications.

Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

Micro-Environmental monitoring of temperature and moisture changes in building stone

The monitoring of temperature and moisture changes in response to different micro-environment of building stones is essential to understand the material behaviour and the degradation mechanisms. From a practical point of view, having a continuous and detailed understanding of micro-environmental changes in building stones helps to assist in their maintenance and repair strategies. Temperature within the stone is usually monitored by means of thermistors, whereas wide ranges of techniques are available for monitoring the moisture. In the case of concrete an electrical resistance method has previously been used as an inexpensive tool for monitoring moisture changes. This paper describes the adaptation of this technique and describes its further development for monitoring moisture movement in building stones.
In this study a block of limestone was subjected to intermittent infrared radiation with programmed cycles of ambient temperature, rainfall and wind conditions in an automated climatic chamber. The temperature and moisture changes at different depths within the stone were monitored by means of bead thermistors and electrical resistance sensors. This experiment has helped to understand the thermal conductivity and moisture transport from surface into deeper parts of the stone at different simulated extreme climatic conditions. Results indicated that variations in external ambient conditions could substantially affect the moisture transport and temperature profile within the micro-environment of building stones and hence they could have a significant impact on stone decay.

Electrical Based Sensors and Remote Monitoring System for Assessing the Corrosion Related Activity in Concrete at Hangzhou Bay Bridge

Concrete structures in marine environments are subjected to cyclic wetting and drying, corrosion of reinforcement due to chloride ingress and biological deterioration. In order to assess the quality of concrete and predict the corrosion activity of reinforcing steel in concrete in this environment, it is essential to monitor the concrete continuously right from the construction phase to the end of service life of the structure. In this paper a novel combination of sensor techniques which are integrated in a sensor probe is used to monitor the quality of cover concrete and corrosion of the reinforcement. The integrated sensor probe was embedded in different concrete samples exposed to an aggressive marine environment at the Hangzhou Bay Bridge in China. The sensor probes were connected to a monitoring station, which enabled the access and control of the data remotely from Belfast, UK. The initial data obtained from the monitoring station reflected the early age properties of the concretes and distinct variations in these properties were observed with different concrete types.

An Integrated Sensing System for Monitoring the Corrosion Activity in Concrete Blocks Exposed at Hangzhou Bay Bridge

This paper discusses the importance of integrated sensing systems comprising techniques that give different types of data from a structure exposed to the marine environment so that its service life could reliably be predicted. For this purpose, a novel sensor combination was designed and installed in concrete panels which were exposed to Hangzhou Bay Bridge in China. The integrated sensor probe was used to monitor the cover concrete as well as the reinforcement. The sensor probes were connected to a monitoring station, which enabled access and control of the data remotely from Belfast, UK. The initial data obtained from the monitoring station gives interesting information on the early age properties of concrete and distinct variations in these properties with different types of concrete. This paper also reports the variation in electrical properties of different concrete samples and environmental data in response to the marine exposure condition at Hangzhou bay bridge.