Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

Effect of crack depth and specimen width on fracture toughness of a carbon steel in the ductile-brittle transition region

The effects of crack depth (a/W) and specimen width W on the fracture toughness and ductile±brittle transition have been investigated using three-point bend specimens. Finite element analysis is employed to obtain the stress-strain fields ahead of the crack tip. The results show that both normalized crack depth (a/W) and specimen width (W) affect the fracture toughness and ductile±brittle fracture transition. The measured crack tip opening displacement decreases and ductile±brittle transition occurs with increasing crack depth (a/W) from 0.1 to 0.2 and 0.3. At a fixed a/W (0.2 or 0.3), all specimens fail by cleavage prior to ductile tearing when specimen width W increases from 25 to 40 and 50 mm. The lower bound fracture toughness is not sensitive to crack depth and specimen width. Finite element analysis shows that the opening stress in the remaining ligament is elevated with increasing crack depth or specimen width due to the increase of in-plane constraint. The average local cleavage stress is dependent on both crack depth and specimen width but its lower bound value is not sensitive to constraint level. No fixed distance can be found from the cleavage initiation site to the crack tip and this distance increases gradually with decreasing inplane constraint.

Effect of constraint on ductile crack growth and ductile-brittle fracture transition of a carbon steel

Ductile-brittle fracture transition was investigated using compact tension (CT) specimens from -70oC to 40oC for a carbon steel. Large deformation finite element analysis has been carried out to simulate the stable crack growth in the compact tension (CT, a/W=0.6), three point-point bend (SE(B), a/W=0.1) and centre-cracked tension (M(T), a/W=0.5) specimens. Experimental crack tip opening displacement (CTOD) resistance curve was employed as the crack growth criterion. Ductile tearing is sensitive to constraint and tearing modulus increases with reduced constraint level. The finite element analysis shows that path-dependence of J-integral occurs from the very beginning of crack growth and ductile crack growth elevates the opening stress on the remaining ligament. Cleavage may occur after some ductile crack growth due to the increase of opening stress. For both stationary and growing cracks, the magnitude of opening stress increases with increasing in-plane constraint. The ductile-brittle transition takes place when the opening stress ahead of the crack tip reaches the local cleavage stress as the in-plane constraint of the specimen increases.

Experimental studies on comparison of microwave curing and thermal curing of epoxy resins used for alternative mould materials

In this present work attempts have been made to study the glass transition temperature of alternative mould materials by using both microwave heating and conventional oven heating. In this present work three epoxy resins, namely R2512, R2515 and R2516, which are commonly used for making injection moulds have been used in combination with two hardeners H2403 and H2409. The magnetron microwave generator used in this research is operating at a frequency of 2.45 GHz with a hollow rectangular waveguide. In order to distinguish the effects between the microwave and conventional heating, a number of experiments were performed to test their mechanical properties such as tensile and flexural strengths. Additionally, differential scanning calorimeter technique was implemented to measure the glass transition temperature on both microwave and conventional heating. This study provided necessary evidences to establish that microwave heated mould materials resulted with higher glass transition temperature than the conventional heating. Finally, attempts were also made to study the microstructure of microwave-cured materials by using a scanning electron microscope in order to analyze the morphology of cured specimens.