Laser-based fibre-optic sensor for measurement of surface properties

This project deals with the design and development of an optoelectronic sensor system and its possible use in online applications. There are two different configurations of this sensor a sensor for surface roughness and another for defect detection. In each configuration the mechanical and optical design are almost identical - optical fibres convey light to and from a surface Light source driving circuits and photodetection circuits were developed for each sensor Data acquisition and analysis algorithms were developed for each sensor. The defect sensor detects through holes and blind holes in sample plates of the following materials brass, copper, stainless steel, and polycarbonate Edge detection is achieved through the development of a photoelectric sensor system that senses the proximity of a surface within a certain displacement range using a multimode laser diode light source emitting at 1300 nm. This sensor uses a voltage cut-off system to avoid the effects of light source intensity variation, vibration, surface roughness and other causes of variable reflectivity in online measurement of engineering surfaces. The through holes had 2 mm diameter and the blind holes had 3 mm diameter and a depth of 0 6 mm. A spatial resolution of approximately 100 (Jim was achieved - the diameter of the collecting fibre’s core. Surface roughness is estimated between 0 025 \im and 0 8 \im, average surface roughness, through a light scattering technique Specular reflectivity was measured at incident angles of 45° and 60°. The causes of error, noise and drift are investigated for this system and recommendations are made to account for these problems. A carrier frequency system using an electronically modulated LED light source was implemented to improve the noise rejection of the system Digital signal processing system was implemented to digitally filter the acquired signal

Creep monitoring using permanently installed potential drop sensors

Creep is the primary life limiting mechanism of static high temperature, high pressure power station components. Creep state evaluation is currently achieved by surface inspection of microstructure during infrequent outages; a methodology which is laborious, time consuming and considered inadequate. The objective of this work is to develop a monitoring technique that is capable of on-load creep damage monitoring. A continuous update of component integrity will enable better informed, targeted inspections and outage maintenance providing increased power generation availability. A low-frequency, permanently installed potential drop system has been previously developed and will be the focus of this thesis. The use of a quasi-DC inspection frequency suppresses the influence of the electromagnetic skin effect that would otherwise undermine the stability of the measurement in the ferromagnetic materials of interest; the use of even low frequency measurements allows phase sensitive detection and greatly enhanced noise performance. By permanently installing the electrodes to the surface of the component the resistance measurement is sensitive to strain. A resistance - strain inversion is derived and validated experimentally; the use of the potential drop sensor as a robust, high temperature strain gauge is therefore demonstrated. The strain rate of a component is known to be an expression of the creep state of the component. This concept was adopted to develop an interpretive framework for inferring the creep state of a component. It is possible to monitor the accumulation of creep damage through the symptomatic relative increase in strain rate. By taking the ratio of two orthogonal strain measurements, instability and drift common to both measurements can be effectively eliminated; an important attribute considering the necessity to monitor very low strain rates over decades in time in a harsh environment. A preliminary study of using the potential drop technique for monitoring creep damage at a weld has been conducted. Welds provide a site for preferential creep damage accumulation and therefore will frequently be the life limiting feature of power station components. The potential drop technique will be sensitive to both the localised strain that is understood to act as precursor to creep damage at a weld and also the initiation and growth of a crack. Through the course of this project, two site trials have been conducted in power stations. A measurement system and high temperature hardware that is suitable for the power station environment has been developed. The focus of this thesis is the effective transfer of the technique to industry; the realisation of this is detailed in the final chapter.Open Acces

Radio frequency atomic magnetometer for applications in magnetic induction tomography

No abstract available.No abstract available

A Machine Learning approach for damage detection and localisation in Wind Turbine Gearbox Bearings

Increasing demand for renewable sources requires more cost-effective solutions to mitigate the cost of maintenance and produce more energy. Preventive maintenance is the most normally adopted scheme in industry for maintenance but despite being well accepted has severe limitations. Its inability to intelligently schedule maintenance at the right time and prevent unexpected breakdowns are the main downsides of this approach and consequently leads to several problems such as unnecessary maintenances. This strategy does not justify the additional costs and thereby represents a negative aspect for renewable energy resource companies that try to generate cost-competitive energy. These challenges are progressively leading towards the predictive maintenance approach to overcome these aforementioned issues. Wind Turbine Gearbox Bearings have received a lot of attention due to the high incidence failure rates provoked by the harsh operational and environmental conditions. Current techniques only reach a level one of diagnostics commonly known as the Novelty Detection stage and normally requires the expertise of a skilled operator to interpret data and infer damage from it. A data-driven approach by using Machine Learning methods has been used to tackle the damage detection and location stage in bearing components. The damage location was performed by using non-destructive methods such as the Acoustic Emission technique — these measurements were used as features to locate damage around the bearing component once the damage was detected. The implementation of this stages also led to the exploration of damage generation due to overload defects and proposed a methodology to simulate these defects in bearings — the study of this concept was implemented in a scaled-down experiment where damage detection and localisation was performed. Due to the importance of the implementation of a damage location stage, damage in AE sensors was also explored in this work. Features extracted from impedance curves allowed to train Machine Learning methods to trigger a novelty when a bonding scenario occurred. This ultimately allowed the identification of unhealthy sensors in the network that could potentially generate spurious results in the damage predictions stage

Ultrasonic sensor platforms for non-destructive evaluation

Robotic vehicles are receiving increasing attention for use in Non-Destructive Evaluation (NDE), due to their attractiveness in terms of cost, safety and their accessibility to areas where manual inspection is not practical. A reconfigurable Lamb wave scanner, using autonomous robotic platforms is presented. The scanner is built from a fleet of wireless miniature robotic vehicles, each with a non-contact ultrasonic payload capable of generating the A0 Lamb wave mode in plate specimens. An embedded Kalman filter gives the robots a positional accuracy of 10mm. A computer simulator, to facilitate the design and assessment of the reconfigurable scanner, is also presented. Transducer behaviour has been simulated using a Linear Systems approximation (LS), with wave propagation in the structure modelled using the Local Interaction Simulation Approach (LISA). Integration of the LS and LISA approaches were validated for use in Lamb wave scanning by comparison with both analytical techniques and more computationally intensive commercial finite element/diference codes. Starting with fundamental dispersion data, the work goes on to describe the simulation of wave propagation and the subsequent interaction with artificial defects and plate boundaries. The computer simulator was used to evaluate several imaging techniques, including local inspection of the area under the robot and an extended method that emits an ultrasonic wave and listens for echos (B-Scan). These algorithms were implemented in the robotic platform and experimental results are presented. The Synthetic Aperture Focusing Technique (SAFT) was evaluated as a means of improving the fidelity of B-Scan data. It was found that a SAFT is only effective for transducers with reasonably wide beam divergence, necessitating small transducers with a width of approximately 5mm. Finally, an algorithm for robot localisation relative to plate sections was proposed and experimentally validated

Assembling Single RbCs Molecules with Optical Tweezers

Optical tweezer arrays are useful tools for manipulating single atoms and molecules. An exciting avenue for research with optical tweezers is using the interactions between polar molecules for quantum computation or quantum simulation. Molecules can be assembled in an optical tweezer array starting from pairs of atoms. The atoms must be initialised in the relative motional ground state of a common trap. This work outlines the design of a Raman sideband cooling protocol which is implemented to prepare an 87-Rubidium atom in the motional ground state of an 817 nm tweezer, and a 133-Caesium atom in the motional ground state of a 938 nm tweezer. The protocol circumvents strong heating and dephasing associated with the trap by operating at lower trap depths and cooling from outside the Lamb-Dicke regime. By analysing several sources of heating, we design and implement a merging sequence that transfers the Rb atom and the Cs atom to a common trap with minimal motional excitation. Subsequently, we perform a detailed characterisation of AC Stark shifts caused by the tweezer light, and identify several situations in which the confinement of the atom pair influences their interactions. Then, we demonstrate the preparation of a molecular bound state after an adiabatic ramp across a magnetic Feshbach resonance. Measurements of molecular loss rates provide evidence that the atoms are in fact associated during the merging sequence, before the magnetic field ramp. By preparing a weakly-bound molecule in an optical tweezer, we carry out important steps towards assembling an array of ultracold RbCs molecules in their rovibrational ground states