Turbine systems play a crucial role in the production of wind energy. According to Star (2001), wind is currently the fastest growing renewable source of energy in the world. Nevertheless, the industry is still experiencing untimely turbine-related problems that result in increases in the cost of energy. With the increase in the size and installation of offshore turbines, these failures become considerably costly (Allemang, De Clerck, Niezrecki, & Blough, 2012). Thus, there is necessary for the industry to increase the reliability of turbines and to reduce downtime. In order to comprehend the premature failures of turbines and propose probable improvements, concerned bodies, such as the National Renewable Energy Laboratory, have initiated a conglomerate called the Gearbox Reliability Collaborative (GRC). Such consortiums aim at ensuring the reliability of turbine systems in the production of energy and other area of usage. It is through these groupings that the involved parties are able to come up with gearbox design, manufacture and maintenance techniques that have a common goal of improving reliability and extending the lifetime of turbines (Askeland, Fulay, & Bhattacharya, 2009). Condition Monitoring (CM) is one of the areas under research in the energy industry. It can substantially assist the industry in achieving the common objective of the improved turbine uptime. This is because it facilitates the best operation and maintenance practices. In other words, condition monitoring can target almost all its key subsystems, such as nacelle, blades, drivetrain, tower, and foundation. In this regard, the paper discusses condition-monitoring techniques used to detect on the turbine blades. The techniques discussed by the paper include: ultrasonic, thermo graphic, radiograph, and full matrix capture. Also, the paper discusses the blade characteristics that determine the appropriate technique in detecting defects. Notably, it will be of great significance to discuss the problems, such as corrosion and crack, that cause turbine malfunctions.
Condition Monitoring Techniques and their Characteristics
Condition Monitoring is mainly implemented using an integrated approach by coordinating various commercial equipment suppliers (Cho, Bode, & Kim, 2010). It takes an integrated approach since no single technique can offer reliable and comprehensive solutions needed by the energy industry. The figure below shows the setup of the condition monitoring system. This system was designed in order to provide reliable diagnostics whenever a turbine drivetrain components start to fail. The stress represents the Acoustic Emission technique that covers the frequency range that lies above 20 kHz (Donachie & Donachie, 2002). According to Star (2001), the inline particle counts represent the number of ferrous particles present in the main loop. The offline oil condition sensor measures the total ferrous debris in parts per million (ppm), oil quality in customized scale, and relative humidity in as a percentage. Various dynamometer tests have the same setup with very small and minor differences (Ghali, 2010).
Ultrasonic Flaw Detector
The flaw detection is the most common and oldest application of ultrasonic testing (Ghali, 2010). Since the 1940s, the principals of physics that explain the sound wave propagation through solids have been deployed in detecting hidden crack, porosity, voids, and internal discontinuities in metals, composites, plastics, and ceramics (Ginley & Cahen, 2011). According to Star (2001), sound waves of high frequency reflect from defects in various predictable ways. Such sound waves produce characteristic echo patterns, which can be recorded and displayed by the portable devices. Ultrasonic testing is entirely safe and nondestructive, and it is a well-known detection method in various manufacturing, the service and processing industry, particularly in applications integrating structural and weld metals (Ghali, 2010).
The use of ultrasonic in detecting flaws in turbine blades borrows much from physics of sound waves. According to Star (2001), sound waves refer to organized mechanical waves that travel through solid, liquid or gas substances that act as media. These waves travel through a certain medium at a particular speed and in a foreseeable direction. In addition, when the waves bump into a boundary having a different middling, they will undergo reflection according to certain principles of physics. It is these principles of physics that motivate the ultrasonic flaw detection. According to Star (2001), all sound waves oscillate at a given frequency that can be experienced as a pitch in an acquainted range of a noticeable sound. The normal frequency of human hearing spans to an extreme of 20 kHz; while the common of ultrasonic defect applications use frequencies that range from 500 kHz to 10 MHz (Donachie & Donachie, 2002). Sound waves do not travel effectively via other ordinary gases at frequencies in the range of megahertz, though it travels freely via most engineering materials. The speed at which sound waves travel changes based on the medium. The density of the medium and its elastic properties affect the speed of sound energy and various sound waves travel at the dissimilar velocities (Katherine & Miller, 2008). According to Star (2001), any form of waves travels has a related wavelength, which is the distance from one consistent point to another in the wave cycle.
Sound waves travelling in solids take various modes of propagation defined by the motion involved (Ginley & Cahen, 2011). For instance, shear and longitudinal waves are the most popular modes used in the ultrasonic detection. Additionally, plate and surface waves are also used in some occasions. A motion of particle perpendicular to the direction of wave propagation describes longitudinal waves. A motion of particle vertical to the bearing of wave propagation characterizes a shear or transverse wave. Star (2001) views a plate wave as a multifaceted vibration mode in thin plates with a wavelength of less than one. Sound waves can undergo conversions from one state to another. Shear waves are commonly generated in test materials, including turbine blades, by bringing together longitudinal waves at the chosen points (Woldman & Frick, 2000). Star (2001) also points out that sound energy at ultrasonic frequencies can help detect flaws in the turbine blades. At such frequencies, the sound energy is guiding and the beams deployed for detection. The angle of incidence equals the angle of reflection in scenarios where sound reflects off a boundary (Totten, Westbrook, & Shah, 2003).