Novel approaches for maintenance management on wind turbines
- Autores: Raúl Ruiz-de-la-Hermosa González-Carrato
- Directores de la Tesis: Fausto Pedro García Márquez (dir. tes.)
- Lectura: En la Universidad de Castilla-La Mancha ( España ) en 2014
- Idioma: español
- Tribunal Calificador de la Tesis: Diego José Pedregal Tercero (presid.), José Ignacio Castillo Manzano (secret.), M.Ph. Papaelias (voc.)
- Programa de doctorado: Programa de Doctorado en Ciencias y Tecnologías aplicadas a la Ingeniería Industrial por la Universidad de Castilla-La Mancha
- Materias:
- Enlaces
- Tesis en acceso abierto en: TESEO
- Resumen
The renewable energy industry is in a constant improvement in order to cover the current demands. Companies are competing to take advantage of any evolving opportunity presented. Nowadays one of those remarkable competitive advantages focuses on maintenance management and some terms such as operating and maintenance costs, availability, reliability, safety, lifetime, etc. emerge.
Wind turbines (WT) are one of the fastest growing sources of renewable energy production. The number of WTs and their complexity has increased in recent years, reducing the reliability of systems and raising the maintenance costs due to the occurrence of non-monitored failures. There are case studies that present specific faults and consequent maintenance activities on WTs but they depend on the model considered, the geographic and environmental changes that occur in different wind farms, etc.
Techniques such as condition monitoring (CM) are employed to detect and identify these failures/faults at earlier stages, maximising the productivity performance, minimising possible downtimes of the WT, and increasing the reliability, availability, maintainability and safety (RAMS) levels.
CM is implemented from basic operations of the equipment to study. The system provides the “condition”, the state of a characteristic parameter that represents the health of the component(s) being monitored. Reliable data acquisition can be achieved with the optimal type and placement of sensors as well as employing the appropriate number of them. Conditioning also reduces the susceptibility to interferences during the features transport. Data processing, sorting and manipulation according to the objectives pursued, are usually performed by a digital signal processor. Then it can be shown via a screen display, stored or transmitted to another system.
As part of some fault detection and diagnosis (FDD) approaches, features are extracted via CM. FDD is based on different methods employed to obtain the information needed from these features. For example, the most used technique for CM in WTs is vibration, while the most studied components are mechanical components such as gearboxes, blades or bearings.
FDD relies on the number and type of sensors used and the processing and simplification methods employed to extract the information from the signals. Once information is obtained, an electronic measuring system provides the suitable data to an observer or other technical control systems. Therefore the three main block functions in a measurement system are data acquisition, data processing and data distribution. The information about the variables measured is turned into an electrical signal. The main advantages offered by these FDD systems are: The prediction, reduction and elimination of downtimes.
The reduction of energy, maintenance and operating costs.
The use of monitoring alert notifications.
