Advanced digital signal processing for condition monitoring for rotative electrical machines

The production of electric energy from wind technology has experience great advances in the later years. It is estimated that the potential of wind energy in the world is between 20.000 x 106 and 50.000 x 106 MWh/year, whereas the energy consumption is about 15.000 x 106 MWh/year.

According to the International Energy Agency (IEA), a net wind capacity of 40.68 GW was added in 2014 by the IEA Wind member countries 39% more than the capacity added in 2013, with a total installed wind capacity of 314.72 GW. The IEA estimates that in 2050 12% of electric energy will be produced by the wind energy industry. The global electric car stock surpassed 2 million vehicles in 2016 with a growth of 60% with respect to 2010. It is expected a great increase of Electrical Vehicles (EVs) by 2030. All this data show the importance of the wind energy at the present time, not only form a quantitative aspect, but also since it is a renewable energy, local and clean, that improves the energy independence. Furthermore both the wind energy and the electrical vehicle contribute to climate change mitigation. Problems such as the evaluation of the wind energy potential, location, wind turbines design, topology of the drive, integration of the wind energy in the grid, among others, caught the attention of a huge number of researchers.

This PhD opportunity focuses on the productivity of wind turbines and electrical vehicles by detecting faults at the early stages. Hence the downtimes and maintenance cost are reduced.

The main goal of this PhD is to develop new diagnostic techniques for the early diagnosis of failures in electrical machines fed by variable speed drives. The techniques which are intended to be developed are based on the monitoring of electric and magnetic magnitudes such as line current, electric power, magnetic flux, etc., which are easily accessible, for analysis by adequate signal processing tools.

It is intended to develop diagnostic methods optimised for wind turbines and electrical vehicles. Their working conditions imply that the speed and load regimes are always in transient state. Furthermore, both the wind turbine generators and electrical vehicle motors are fed by variable speed drives. It is also intended that the proposed methodologies can be integrated in the predictive maintenance system of wind farms and in the diagnosis system of electrical vehicles.

Academic qualifications

A first-class honours degree, or a distinction at master level, or equivalent achievements in Electrical Engineering.

English language requirement

If your first language is not English, comply with the University requirements for research degree programmes in terms of English language.

Application process

Prospective applicants are encouraged to contact the supervisor, Dr. Francisco Vedreño Santos (F.VedrenoSantos@napier.ac.uk) to discuss the content of the project and the fit with their qualifications and skills before preparing an application. 

The application must include: 

Research project outline of 2 pages (list of references excluded). The outline may provide details about

• Background and motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
• Research questions or
• Methodology: types of data to be used, approach to data collection, and data analysis methods.
• List of references

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Recent and complete curriculum vitae. The curriculum must include a declaration regarding the English language qualifications of the candidate.
• Supporting documents will have to be submitted by successful candidates.
• Two academic references (but if you have been out of education for more than three years, you may submit one academic and one professional reference), on the form can be downloaded here.

Applications can be submitted here.

Download a copy of the project details here.