Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Unraveling unstructured process models

A BPMN model is well-structured if splits and joins are always paired into single-entry-single-exit blocks. Well-structuredness is often a desirable property as it promotes readability and makes models easier to analyze. However, many process models found in practice are not well-structured, and it is not always feasible or even desirable to restrict process modelers to produce only well-structured models. Also, not all processes can be captured as well-structured process models. An alternative to forcing modelers to produce well-structured models, is to automatically transform unstructured models into well-structured ones when needed and possible. This talk reviews existing results on automatic transformation of unstructured process models into structured ones.

Energy-based nonlinear control of ship roll gyro-stabiliser with precession angle constraints

In this paper, we consider a passivity-based approach for the design of a control law of multiple ship-roll gyro-stabiliser units. We extend previous work on control of ship roll gyro-stabilisation by considering the problem within a nonlinear framework. In particular, we derive an energy-based model using the port-Hamiltonian theory and then design an active precession controller using passivity-based control interconnection and damping assignment. The design considers the possibility of having multiple gyro-stabiliser units, and the desired potential energy of the system (in closed loop) is chosen to behave like a barrier function, which allows us to enforce constraints on the precession angle of the gyros.

Regulation and integral control of an underactuated robotic system using IDA-PBC with dynamic extension

This paper proposes a method for design of a set-point regulation controller with integral action for an underactuated robotic system. The robot is described as a port-Hamiltonian system, and the control design is based on a coordinate transformation and a dynamic extension. Both the change of coordinates and the dynamic extension add extra degrees of freedom that facilitate the solution of the matching equation associated with interconnection and damping assignment passivity-based control designs (IDA-PBC). The stability of the controlled system is proved using the closed loop Hamiltonian as a Lyapunov candidate function. The performance of the proposed controller is shown in simulation.

Manoeuvring control of underactuated surface vessels using manifold regulation for Port-Hamiltonian systems

This paper considers the manoeuvring of underactuated surface vessels. The control objective is to steer the vessel to reach a manifold which encloses a waypoint. A transformation of configuration variables and a potential field are used in a Port-Hamiltonian framework to design an energy-based controller. With the proposed controller, the geometric task associated with the manoeuvring problem depends on the desired potential energy (closed-loop) and the dynamic task depends on the total energy and damping. Therefore, guidance and motion control are addressed jointly, leading to model-energy-based trajectory generation.

Culture makes you stronger : Aboriginal women’s voices from the South Coast of NSW

This paper will describe a community based research project examining the health and wellbeing of a sample of Aboriginal women in Australia, and present preliminary findings of a community needs analysis. The Shoalhaven Koori Women’s Study (SKWS) is being led by an Aboriginal woman based within Waminda, an Aboriginal women’s community controlled service located on the South Coast of NSW. The community needs analysis is the first stage of the SKWS, and aims to explore Aboriginal women’s perceptions and experiences of wellness and wellbeing, including issues related to their personal strengths, health and social priorities, support needs and that of their families. Thirty Aboriginal women were interviewed using a survey that included closed and open ended questions. Methods used to administer the survey included yarning and Dadirri (deep listening), two valid and culturally safe approaches for data collection with Aboriginal people. Adopting these approaches ensured Aboriginal protocols were maintained and upheld throughout the research process. This enabled scientific rigour while also ensuring activities were culturally safe. Key findings of the survey will be presented, and how Waminda is modifying service delivery to better respond to the health and social priorities of Aboriginal women in the Shoalhaven region will be discussed. Community feedback of survey results will occur to validate the analysis from the community perspective.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Dictionary learning and sparse coding on Grassmann manifolds : an extrinsic solution

Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of linear subspaces, which form Riemannian structures known as Grassmann manifolds. To this end, we propose to embed Grassmann manifolds into the space of symmetric matrices by an isometric mapping, which enables us to devise a closed-form solution for updating a Grassmann dictionary, atom by atom. Furthermore, to handle non-linearity in data, we propose a kernelised version of the dictionary learning algorithm. Experiments on several classification tasks (face recognition, action recognition, dynamic texture classification) show that the proposed approach achieves considerable improvements in discrimination accuracy, in comparison to state-of-the-art methods such as kernelised Affine Hull Method and graph-embedding Grassmann discriminant analysis.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Port-Hamiltonian theory of motion control for marine craft

Port-Hamiltonian Systems (PHS) have a particular form that incorporates explicitly a function of the total energy in the system (energy function) and also other functions that describe structure of the system in terms of energy distribution. For PHS, the product of the input and output variables gives the rate of energy change. This type of systems have the property that under certain conditions on the energy function, the system is passive; and thus, stable. Therefore, if one can design a controller such that the closed-loop system retains - or takes - a PHS form, such closed-loop system will inherit the properties of passivity and stability. In this paper, the classical model of marine craft is put into a PHS form. It is shown that models used for positioning control do not have a PHS form due to a kinematic transformation, but a control design can be done such that the closed-loop system takes a PHS form. It is further shown how integral action can be added and how the PHS-form can be exploited to provide a procedure for control design that ensures passivity and thus stability.

Control design for positioning of underwater vehicles with control allocation

In this paper, we address the control design problem of positioning of over-actuated underwater vehicles. The proposed design is based on a control architecture with combined position and velocity loops and a control tuning method based on the decoupled models. We derive analytical tuning rules based on requirements of closed-loop stability, positioning performance, and the vehicle velocity dynamic characteristics. The vehicle modelling is considered from force to motion with appropriate simplifications related to low-speed manoeuvring hydrodynamics and vehicle symmetry. The control design is considered together with a control allocation mapping. This approach makes the control tuning independent of the characteristics of the force actuators and provides the basis for control reconfiguration in the presence of actuator failure. We propose an anti-wind-up implementation of the controller, which ensures that the constraints related to actuation capacity are not violated. This approach simplifies the control allocation problem since the actuator constraints are mapped into generalised force constraints.

Long-term stability of adipose tissue generated from a vascularized pedicled fat flap inside a chamber

Background Numerous studies demonstrate the generation and short-term survival of adipose tissue; however, long-term persistence remains elusive. This study evaluates long-term survival and transferability of de novo adipose constructs based on a ligated vascular pedicle and tissue engineering chamber combination. Methods Defined adipose tissue flaps were implanted into rats in either intact or perforated domed chambers. In half of the groups, the chambers were removed after 10 weeks and the constructs transferred on their vascular pedicle to a new site, where they were observed for a further 10 weeks. In the remaining groups, the tissue construct was observed for 20 weeks inside the chamber. Tissue volume was assessed using magnetic resonance imaging and histologic measures, and constructs were assessed for stability and necrosis. Sections were assessed histologically and for proliferation using Ki-67. Results At 20 weeks, volume analysis revealed an increase in adipose volume from 0.04 ± 0.001 ml at the time of insertion into the chambers to 0.27 ± 0.004 ml in the closed and 0.44 ± 0.014 ml in the perforated chambers. There was an additional increase of approximately 10 to 15 percent in tissue volume in flaps that remained in chambers for 20 weeks, whereas the volume of the transferred tissue not in chambers remained unaltered. Histomorphometric assessment of the tissues documented no signs of hypertrophy, fat necrosis, or atypical changes of the newly generated tissue. Conclusion This study presents a promising new method of generating significant amounts of mature, vascularized, stable, and transferable adipose tissue for permanent autologous soft-tissue replacement.

Modeling and sensorless direct torque and flux control of a dual-airgap axial flux permanent-magnet machine with field-weakening operation

This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.

International hermelin brain tumor symposium on matricellular proteins in normal and cancer cell-matrix interactions

The second of the Hermelin Brain Tumor Center Symposia was held once again at Henry Ford Hospital in Detroit, Michigan on October 24th and 25th, 2003. A public conference was held on the 24th while a closed-door session took place on the 25th. The purpose of these symposia is to bring together experts in a particular field of study with the aim to share information with each other and the public, but then to meet privately to present novel data, hold discussions, and share concepts. While the interaction is intended to benefit all involved, the incentive is the expectation that the shared information will aid researchers at the Hermelin Brain Tumor Center in their quest to identify potential therapeutic targets and explore translational therapeutic strategies for the treatment of patients suffering nervous system tumors...

Optimising the cell source and biomaterials for the generation of vascularized adipose tissue in vivo

We initially described a rat chamber model with an inserted arteriovenous pedicle which spontaneously generates 3-dimensional vascularized connective tissue (Tanaka Y et al., Br J Plast Surg 2000; 53: 51-7). More recently we have developed a murine chamber model containing reconstituted basement membrane (Matrigel®) and FGF-2 that generates vascularized adipose tissue in vivo (Cronin K et al., Plast Reconstr Surg 2004; in press). We have extended this work to assess the cellular and matrix requirements for the Matrigel®- induced neo-adipogenesis. We found that chambers sealed to host fat were unable to grow new adipose tissue. In these chambers the Matrigel® became vascularized with maximal outgrowth of vessels extending to the periphery at 6 weeks. A small amount of adipose tissue was found adjacent to the vessels, most likely arising from periadventitial adipose tissue. In contrast, chambers open to interaction with endogenous adipose tissue showed abundant new fat, and partial exposure to adjacent adipose tissue clearly showed neo-adipogenesis only in this area. Addition of small amounts of free fat to the closed chamber containing Matrigel® was able to induce neo-adipogenesis. Addition of small pieces of human fat also caused neo-adipogenesis in immunocompromised (SCID) mice. Also, we found Matrigel® to induce adipogenesis of Lac-Z-tagged (Rosa-26) murine bone marrow-derived mesenchymal stem cells, and cells similar to these have been isolated from human adipose tissue. Given that Matrigel® is a mouse product and cannot be used in humans, we have started investigating alternative matrix scaffolds for adipogenesis such as the PDA-approved PLGA, collagen and purified components derived from Matrigel®, such as laminin-1. The optimal conditions for adipogenesis with these matrices are still being elucidated. In conclusion, we have demonstrated that a precursor cell source inside the chamber is essential for the generation of vascularized adipose tissue in vivo. This technique offers unique potential for the reconstruction of soft tissue defects and may enable the generation of site-specific tissue using the correct microenvironment.