Roger Dixon

Active vibration control for marine applications

Abstract A major problem, in isolating large marine machinery rafts, is how best to mitigate against the effects of excited resonances. These generate large forces on the hull and produce undesirable characteristic signatures. The paper describes the development of a new hybrid active/passive mounting system that has the potential to eradicate such signatures by making use of digitally controlled actuators that ignore local displacements while controlling the response of the structures rigid body modes. Also described in the paper is a method that has been developed for damping flexural modes of vibration in the receiving structure. This further reduces the levels of vibration by directly tackling the mechanism by which the effect of small forces is amplified. The active damping method has recently been successfully demonstrated on a full-scale vessel and a number of key results obtained in the development process are presented.

The ALSTOM benchmark challenge on gasifier control

Abstract Integrated gasification combined cycle power plants are being developed around the world to provide environmentally clean and efficient power generation from coal. As part of the UKs Clean Coal Power Generation Group, ALSTOM (formerly GEC ALSTHOM) has undertaken a detailed feasibility study on the development of a small-scale prototype integrated plant (PIP), based on the air-blown gasification cycle. In pursuit of this goal the ALSTOM Power Technology Centre (formerly the GEC ALSTHOM Mechanical Engineering Centre) has produced a comprehensive dynamic model and control philosophy for the PIP. The gasifier is one component of the model which, being a highly coupled multi-variable system with five inputs (coal, limestone, air, steam and char extraction) and four outputs (pressure, temperature, bed mass and gas quality), has been found to be particularly difficult to control. For this reason the gasifier, together with its associated control specification, operating constraints and various disturbance characteristics, has been selected as the subject for this control challenge. This paper provides a brief background to the problem and describes the control specification and closed-loop tests to be performed.

Model-based condition monitoring at the wheel–rail interface

The dynamics of a rail vehicle is driven by the interaction between the wheel and rail. Any change to, for example, the shape of the wheel–rail profile or the contact adhesion conditions will change the response of the vehicle. The condition monitoring challenge is to interpret these changes into useful condition information. This paper presents the ongoing research into model-based condition monitoring at the wheel–rail interface applied to two applications: (i) wheel–rail profile estimation; and (ii) low adhesion detection. The wheel–rail profile estimation was carried out on a linearised simulation model that included a nonlinear conicity function. This function could be successfully estimated by also estimating the lateral track irregularities and giving the Kalman Filter self-updating information about the shape of the conicity function. The low adhesion detection was carried out on a complex nonlinear half vehicle model that included saturating contact force equations. The contact forces could be estimated by considering the half vehicle floating on a set of contact forces. Low adhesion conditions can be implied by the relative magnitudes of these contact forces.

Multi-objective optimal-tuning proportional-integral controller design for the ALSTOM gasifier problem

Abstract This paper presents a proportional-integral (PI) controller design approach using multi-objective optimization which addresses the ALSTOM benchmark challenge on gasifier control. The non-linear gasifier has been linearized about three operating points. The design aim is to satisfy a set of specifications on the system outputs, inputs and input rates when a step disturbance is applied to the system. The parameters of the multiple-input multiple-output (MIMO) PI controller are selected to satisfy a set of multi-objective performance criteria, which are formulated from the system specifications. Simulation results are presented which demonstrate the performance of the controller at the three operating points.

Contact Force Estimation in the Railway Vehicle Wheel-Rail Interface

Abstract Increased patronage of railways in the UK in the past 20 years has put demands on rolling stock to operate at peak availability with reduced time available for maintenance. One possible tool to enable this is the use of real time fault detection and diagnosis on board railway vehicles to detect faulty components and provide information about the current running condition of the system. This paper discusses the development of one such technique for the estimation of creep forces of the wheel-rail contact. Real time knowledge of which could be used to predict wear of the wheel tread and rail head, predict the formation of rolling contact fatigue, and identify any areas of low adhesion present on the network. The paper covers development of a full vehicle nonlinear contact mechanics model, development of the Kalman-Bucy filter estimation technique and how the technique will be developed and validated in the future.

The automation of piling rig positioning using satellite GPS

The paper is divided in two parts. Part one describes the Stent Automatic Pile Positioning and Recording system (SAPPAR) which was launched in November 1994. The system utilises a Trimble satellite global positioning system (GPS) to assist rig drivers in accurately positioning the rig over a pile position without the need for setting out. Advantages of the system include: cost savings by removing the need for site survey staff; faster set-up times over pile positions; increased accuracy — the system can reliably position the rig to within ± 25 mm; removal of problems resulting from damage to setting out pins; constant monitoring of pile position; and Links to CAD for data input and as-built drawings. Part two describes a further development of the system in collaboration with Lancaster University and Casagrande, the Italian rig manufacturer. The aim of the research is to fully automate the final positioning process. This represents one of the first uses of GPS for real-time automation. The system hardware components include: ultra-compact PC1O4 processor cards for a compact and robust embedded system; minimum sensing on the rig to minimise cost and maximise robustness; and limit sensors to facilitate on-board safety. The control algorithms were developed on a fifth-scale model in the laboratory using an innovative and new approach to the design of model based control systems. The importance of careful consideration of safety issues is stressed and conclusions are drawn based on the early findings from preliminary field trials.

Optimization of reliability and maintenance of liquefaction system on FLNG terminals using Markov modelling

Purpose – The purpose of this paper is to optimize system redundancy and maintenance intervals of a propane pre-cooled mixed refrigerant (C3MR) liquefaction process on floating liquefied natural gas (FLNG) export platforms. Design/methodology/approach – The reliability modeling is based on the time-dependent Markov approach. Four different system options are studied, with various degree of redundancy. Failures in the liquefaction system usually lead to shutdown the whole LNG production plant. The associated shutdown cost is compared with the cost of introducing redundancy and the cost of onboard maintenance. To ensure a high profitability, a model for maintenance optimization is utilized and applied to the main unit of the C3MR liquefaction system to minimize the onboard maintenance cost. Findings – The results indicated that the introduction of a second liquefaction system (as a standby unit) is the best option for liquefaction plant in terms of reliability and cost. This will substantially reduce the un...

Adhesion estimation at the wheel–rail interface using advanced model-based filtering

The railway industry in the UK is currently expanding the use of condition monitoring of railway vehicles. These systems can be used to improve maintenance procedures or could potentially be used to monitor current vehicle running conditions without the use of cost prohibitive sensors. This paper looks at a novel method for the online detection of areas of low adhesion in the wheel/rail contact that cause significant disruption to the running of a network, particularly in the autumn season. The proposed method uses a Kalman–Bucy filter to estimate the creep forces in the wheel–rail contact area; post-processing is then applied to provide information indicative of the actual adhesion level. The algorithm uses data that, in practice, would be available from a set of modest cost inertial sensors mounted on the vehicle bogie and wheel-sets. The efficacy of the approach is demonstrated using simulation data from a nonlinear dynamic model of the vehicle and its track interface.

Modelling of High Redundancy Actuation Utilising Multiple Moving Coil Actuators

This paper presents the modelling of a moving coil actuator for use as an element in a High Redundancy Actuator (HRA). A single element model is derived from first principles and verified using experimental data. This model is subsequently used to describe an approach to deriving models of multi-element HRAs and determine the effect of a variety of faults, chosen to be appropriate for the electro-magnetic technology, on the behaviour of multi-element assemblies.

Real Time Detection of Low Adhesion in the Wheel/Rail Contact

Condition monitoring of railway vehicles has been highlighted by the railway industry as a key enabling technology for future system development. The primary uses for this could be the improvement of maintenance procedures and/or the identification of high-risk vehicle running conditions. Advanced processing of signals means these tasks could be accomplished without the use of cost prohibitive sensors. This paper presents a system for the on-board detection of low-adhesion conditions during the normal operation of a railway vehicle. Two different processing methods are introduced. The first method is a model-based approach that uses a Kalman–Bucy filter to estimate creep forces, with subsequent post processing for interpretation into adhesion levels. The second non model-based method targets the assessment of relationships between vehicle dynamic responses to observe any behavioural differences as a result of an adhesion-level change. Both methods are evaluated in specific case studies using a British Rail (BR) Mark 3 coach, inclusive of a BR BT-10 bogie, and a generic modern passenger vehicle based on a contemporary bogie design. These vehicles were chosen as typical application opportunities within the UK. The results are validated with data generated by the multi-body simulation software VAMPIRE® for realistic data inputs, representing a key scientific achievement.