21 research outputs found
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Structuring Data for Intelligent Predictive Maintenance in Asset Management
Predictive maintenance (PdM) within asset management improves savings in operational cost, productivity, and safety management capabilities. While PdM can be administered using various methods, growing interest in Arti cial Intelligence (AI) has lead to current state of the art PdM relying on machine learning (ML) technology. Like other tools used in PdM for asset management, standards for applying ML technology for PdM are required. This work introduces a standard of practice in regards to usage of asset data to develop ML analytic tools for PdM. It provides a standard method for ensuring asset data is in a form conducive to ML algorithms, and ensuring retention of asset information necessary for optimum PdM during the data transform. In the ML domain, it has been proven through research initiatives that the data structure used to train and test ML algorithms has a great impact on their performance and accuracy. Using poorly trained models for estimation due to improper data usage, can leave some AI-based PdM tools vulnerable to high rates of inaccurate estimations. Thus, leading to value loss during an asset's life cycle.This research was supported by
the Australian Government Research Training Program Scholarship,
American Australian Association Education Fund Fellowship, National
GEM Consortium, Sustain-Owner (Sustainable Design and
Management of Industrial Assets through Total Value and Cost of
Ownership), a project sponsored by the EU Framework Programme
Horizon 2020, MSCA-RISE-2014: Marie Sk lodowska-Curie Actions
Research and Innovation Staff Exchange (Rise) (grant agreement
number 645733 Sustain-owner H2020-MSCA-RISE-2014
Hidden cusps
International audienceThis paper investigates a situation pointed out in a recent paper, in which a non-singular change of assembly mode of a planar 2-RPR-PR parallel manipulator was realized by encircling a point of multiplicity 4. It is shown that this situation is, in fact, a non-generic one and gives rise to cusps under a small perturbation. Furthermore , we show that, for a large class of singularities of multiplicity 4, there are only two types of stable singularities occurring in a small perturbation: these two types are given by the complex square mapping and the quarto mapping. Incidentally , this paper confirms the fact that, generically, a local non-singular change of solution must be accomplished by encircling a cusp point
Requirements and Limitations of Thermal Drones for Effective Search and Rescue in Marine and Coastal Areas
Search and rescue (SAR) is a vital line of defense against unnecessary loss of life. However, in a potentially hazardous environment, it is important to balance the risks associated with SAR action. Drones have the potential to help with the efficiency, success rate and safety of SAR operations as they can cover large or hard to access areas quickly. The addition of thermal cameras to the drones provides the potential for automated and reliable detection of people in need of rescue. We performed a pilot study with a thermal-equipped drone for SAR applications in Morecambe Bay. In a variety of realistic SAR scenarios, we found that we could detect humans who would be in need of rescue, both by the naked eye and by a simple automated method. We explore the current advantages and limitations of thermal drone systems, and outline the future path to a useful system for deployment in real-life SAR
Sensor requirements for tyre force estimation applications to off-highway mining trucks
The tyre force components acting at the tyre road interface of an off-highway mining truck are estimated using an Extended Kalman filter (EKF). The EKT combines an 11 dof dynamic model of the truck with inertial sensor measurements from the truck sprung and un-sprung bodies. The tyre force estimates have been compared with the actual tyre forces from an advanced virtual truck model
Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks
Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters
Multivariable stability of force-reflecting teleoperation: Structures of finite and infinite zeros
Stabilizing impacts in force-reflecting teleoperation using distance-to-impact estimates
A simple approach to invariant hybrid control
We give a geometrical description of Raibert and Craig's hybrid force/position control method. Our description is coordinate free, hence answering the criticism of the original work that it was not transformation invariant. However, our approach is very simple and avoids the complications introduced in [5]. This simplification is achieved by recognising that velocity screws and wrenches are different geometrical objects and then keeping them separate throughout the discussion. So we do not use any metric properties of the screw space of infinitesimal rigid body motions. Rather, we employ the duality between the vector space of screws and the linear functionals on them. We give several examples and show how changes of coordinates should be handled
Why the mining industry needs a reference architecture for automation initiatives
Automation is increasingly seen by the mining industry as a lever to reduce costs and improve safety. The deployment and integration of technology in mining is today usually done by adopting bespoke solutions where opportunities are identified. There is limited attention given to the broader needs that might be relevant in a complete mine-wide automation solution. The missing overarching plan for integrating and deploying autonomous systems is what is referred to in other industries as a reference architecture. This paper presents a broad evaluation of the challenge of developing a reference architecture for mining automation. The concept of a reference architecture for mining is first investigated by reviewing analogous efforts undertaken in other industries. These efforts are subsequently evaluated against the unique requirements of the mining industry. A set of generalised mining automation architectural models are presented as an indicative representation of the peculiar challenges that must be confronted by such an artefact. The paper concludes with a summary of the core challenges identified around creating a reference architecture for mining automation and suggestions on how these challenges might be addressed. © 2013 IEEE