From a damage detection point of view, SHM methods could be divided into two general categories. First category includes methods which can only determine whether or not damage is present in the entire structure. These methods are referred to as ‘‘global health monitoring’’ methods. Second category includes techniques to measure the state of stress, locate damage and evaluate its size. These methods are ‘‘local health monitoring’’ methods (Chang, Flatau and Liu, 2003).
At present, traditional non-destructive techniques including visual inspection, radiography and eddy current are used to inspect aerospace structures. Acousto-Ultrasonics and guided Ultrasonic waves are developed recently by the use of optical fibre and piezoelectric sensors for damage detection (Staszewski, Boller and Tomlinson, 2004; Chang, Flatau and Liu, 2003). These techniques need the large mass and power required to have an effective damage monitoring system for aerospace vehicles (Mancini, Tumino and Gaudenzi, 2006;
Chang, Flatau and Liu, 2003). Other methods are based on magnetic field, X-ray or thermal principles (Auweraer and Peeters, 2003). Tap tests are also used in civil infrastructure, which include bridges and buildings, to determine if voids or de-bonding exist in the structure. However, tap tests are limited to finding voids near the surface, de-bonding of wraps and significant cracks (Chang, Flatau and Liu, 2003). These technologies are followed by advanced signal processing technologies like neural networks or wavelets which make the damage detection easier. The advantages of these methods include reduced life cycle costs, reduced inspection/maintenance effort, improved performance, improved high rate operator availability, extended life of structures and improved safety (Staszewski, Boller and Tomlinson, 2004).
Traditional methods are time consuming and expensive (Staszewski, Boller and Tomlinson, 2004; Chang, Flatau and Liu, 2003). They also need human interaction and sometimes factors like loss of alertness or fatigue of operator affect the results (Staszewski, Boller and Tomlinson, 2004). In addition these human-based inspection processes are very costly (Auweraer and Peeters, 2003). Therefore, the need for a structural health monitoring system which can reliably and accurately locate the damage in a structure and specify its size and
12 location still exists. Such an in-situ monitoring system should be smart and functional while the structure is in service to alert the operator in the early stages of damage. Such methods which are based on new sensor technologies are in development stages (Staszewski, 2000).
One of these emerging methods is based on strain distribution in the structure (Kesavan, John and Herszberg, 2008a, 2008b). Strain is one of the most important mechanical parameters in SHM systems. By monitoring strain changes in structures, factors that could cause structural failures such as excessive loading, vibration, foundation damages, crack development and environmental aging can be detected (Tata et al., 2009). Different types of sensors are used for detecting strain distribution in structures , for example, strain gauges (Kesavan, John and Herszberg, 2008a, 2008b) or fibre Bragg grating strain sensors (Silva-Munoz and Lopez-Anido, 2009; Li et al., 2006). There are several significant researches about strain-based methods in SHM. Different structural configurations especially T-joint structures have been investigated because of their use in maritime structures (Silva-Munoz and Lopez-Anido, 2009). Different types of defects have been investigated in composite structures using this technique, such as delamination (Kesavan, John and Herszberg, 2008a, 2008b; Zhou and Sim, 2009), crack (Silva-Munoz and Lopez-Anido, 2009) and de-bonding (Li et al., 2006). On the other hand, the importance of an optimized strain sensor network is noticeable (Kesavan, John and Herszberg, 2008a, 2008b; Silva-Munoz and Lopez-Anido, 2009; Tata et al., 2009).
Vibration based method is another relatively new and emerging area of research within SHM. Great deal of work with several different approaches has been done using this method. These works include both traditional methods and modern methods (Oruganti et al., 2008). Traditional methods have different disadvantages such as dependence on experiments for measuring mode shape and damping, dependence on the properties of individual structures and not being sensitive to initial damage (Yan et al., 2007). On the other hand, modern-type methods including Wavelet analysis, Genetic algorithm (GA) and Artificial Neural Network (NN) have their own disadvantages. For example, reliance on environmental excitation, being sensitive to noise and not having a specific damage index (Yan et al., 2007). Therefore, more research is needed to make the use of these techniques in aerospace structures possible. Although these methods are more reliable than other techniques, a practical SHM system which could be able to monitor a structure during work and detect its defects precisely needs more developed techniques.
13 On the other hand, several works have been done regarding Time-Reversal Concept (TRC) and its applications in different areas of study especially in medical purposes (Wang, Rose and Chang, 2004; Fink, 1999). There are also few researches regarding the use of TRC in monitoring the structure online (Wang, Rose and Chang, 2004; Fink, 1999). Piezoelectric transducers are being used in SHM methods like TRC because of their ability to act as both sensor and actuator (Wang, Rose and Chang, 2004; Mancini, Tumino and Gaudenzi, 2006).
However, there are several complications for using TRC in SHM such as determining the exact size of defect (Wang, Rose and Chang, 2004) which is an important issue in SHM. A significant effort should be done to improve its reliability and extend its applications.
Furthermore, there is a need for optimizing the number of sensors (/actuators) and their configuration in the structure. Overcoming such problems could help to develop the use of TRC in monitoring the health of aerospace structures.
Optical fibre and piezoelectric sensors are suitable for embedded monitoring systems (Staszewski, 2000). Optical fibre sensor arrays have the ability to both monitor crack growth and delamination under a bonded repair (Jones and Galea, 2002). However, an experimental, analytical and FE modelling has been done on the effect of embedded optical fibres on strength of carbon epoxy composites (Hadzic, John and Herszberg, 1999) which shows that optical fibres reduce the strength of material if their positional spatial density goes beyond a certain amount. In addition, optical fibres need expensive interrogation equipment, have limited strain range, are brittle and it is difficult to replace or repair a fibre (Mancini, Tumino and Gaudenzi, 2006; Chuang, Thomson and Bridges, 2005).
According to Staszewski (2000), none of the damage monitoring techniques will alone be able of meeting all the specification requirements for monitoring aerospace structures. Even if all the benefits of existing methods are considered, there are still major issues to be solved. These techniques are costly, complicated, in some cases they need complex signal processing and require advanced technology for manufacturing them, and could not locate initial damage in all cases. Most importantly, all the techniques mentioned above use wired sensors. These sensors have many disadvantages such as the need for installation during construction. Wires also limit structure’s functionality; increase the system complexity and the overall weight of the structure. Therefore, the number of sensors that could be applied is limited (Chang, Flatau and Liu, 2003; Choi, Choi and Cha, 2008; Jia et al., 2006). Hence, a structural health monitoring system able to work wirelessly is required to achieve a comprehensive and practical monitoring technology.
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