A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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Subject: search.filters.subject.Acoustic Emission

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    THERMODYNAMIC AND INFORMATION ENTROPY-BASED PREDICTION AND DETECTION OF FATIGUE FAILURES IN METALLIC AND COMPOSITE MATERIALS USING ACOUSTIC EMISSION AND DIGITAL IMAGE CORRELATION
    (2021) Karimian, Seyed Fouad; Modarres, Mohammad; Bruck, Hugh A.; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Although assumed to be identical, manufactured components always present some variability in their performance while in service. This variability can be seen in their degradation path and time to failure as they are tested under identical conditions. In engineering structures and some components, fatigue is among the most common degradation mechanisms and has been under extensive study over the past century. A common characteristic of the fatigue life models is to rely on some observable or measurable markers of damage, such as crack length or modulus reduction. However, these markers become more pronounced and detectable toward the end of the component or structure’s life. Therefore, more advanced techniques would be needed to better account for a structure's fatigue degradation. Several methods based on non-destructive testing techniques have developed over the past decades to decrease the uncertainty in fatigue degradation assessments. These methods seek to exploit the data collected by sensors during the operational life of a structure or component. Hence, the assessment of the health state can be constantly updated based on the operational conditions that allow for condition-based monitoring and maintenance. However, these methods are mostly context-dependent and limited to specific experimental conditions. Therefore, a method to effectively characterize and measure fatigue damage evolution at multiple length scales based on the fundamental concept of entropy is studied in this dissertation. The two entropic-based indices used are: Thermodynamic entropy, and, Information entropy.The objectives of this dissertation are to develop new methods for fatigue damage detection and failure prediction in metallic and FRP laminated composite materials by using AE and DIC techniques and converting them to information and thermodynamic entropy gains caused by fatigue damage. 1. Develop and experimentally validate fatigue damage detection, failure prediction, and prognosis approaches based on the information entropy of AE signal waveforms in both metallic and FRP laminated composite materials. 2. Develop and experimentally validate fatigue damage detection, failure prediction, and prognosis approaches based on thermodynamic entropy using the DIC technique in both metallic and FRP laminated composite materials. 3. Develop a framework for RUL estimation of metallic and FRP laminated composite structures based on the two entropic measures.
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    ACOUSTIC EMISSION-BASED STRUCTURAL HEALTH MANAGEMENT AND PROGNOSTICS SUBJECT TO SMALL FATIGUE CRACKS
    (2014) Keshtgar, Azadeh; Modarres, Mohammad; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    One of the major concerns in structural health management (SHM) is the early detection of growing crack. Using this, future consequential damage due to crack propagation can be reduced or eliminated by scheduling maintenance which can prevent costly downtime. Early crack detection can also be used to predict the remaining useful life of a system. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks during SHM and prognosis. The research presented in this dissertation focuses on the structural health monitoring using AE. In this research a correlation between AE signal characteristics and crack growth behavior is established, and a probabilistic model of fatigue crack length distribution based on certain AE signal features is developed. In order to establish the AE signal feature versus the fatigue crack growth model and study the consistency and accuracy of the model, several standard fatigue experiments have been performed using standard test specimens subjected to cyclic loading with different amplitude and frequencies. Bayesian analysis inference is used to estimate the parameters of the model and associated model error. The results indicate that the modified AE crack growth model could be used to predict the crack growth rate distribution at different test conditions. In the second phase of this research, an AE signal analysis approach was proposed in order to detect the time of crack initiation and assess small crack lengths, which happen during the early stages of damage accumulation. Experimental investigation from uniform cyclic loading tests indicated that initiation of crack could be identified through the statistical analysis of AE signals. A probabilistic AE-based model was developed and the uncertainties of the model were assessed. In addition, a probabilistic model validation approach was implemented to validate the results. The developed models were properly validated and the results were accurate. It was shown that the updated model can be used for detection of crack initiation as well as prediction of small crack growth in early stages of propagation. It was found that the novel AE monitoring technique facilitates early detection of fatigue crack, allows for the original life predictions to be updated and helps to extend the service life of the structure. Finally, a quantification framework was proposed to evaluate probability of failure of structural integrity using the observed initial crack length. The outcome of this research can be used to assess the reliability of structural health by estimating the probability density function of the length of a detected crack and quantifying the probability of failure at a specified number of cycles. The proposed method has applications in on-line monitoring and evaluation of structural health and shows promise for use in fatigue life assessment.
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    FATIGUE CRACK MONITORING WITH COUPLED PIEZOELECTRIC FILM ACOUSTIC EMISSION SENSORS
    (2013) Zhou, Changjiang; Zhang, Yunfeng; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Fatigue-induced cracking is a commonly seen problem in civil infrastructures reaching their original design life. A number of high-profile accidents have been reported in the past that involved fatigue damage in structures. Such incidences often happen without prior warnings due to lack of proper crack monitoring technique. In order to detect and monitor the fatigue crack, acoustic emission (AE) technique, has been receiving growing interests recently. AE can provide continuous and real-time monitoring data on damage progression in structures. Piezoelectric film AE sensor measures stress-wave induced strain in ultrasonic frequency range and its feasibility for AE signal monitoring has been demonstrated recently. However, extensive work in AE monitoring system development based on piezoelectric film AE sensor and sensor characterization on full-scale structures with fatigue cracks, have not been done. A lack of theoretical formulations for understanding the AE signals also hinders the use of piezoelectric film AE sensors. Additionally, crack detection and source localization with AE signals is a very important area yet to be explored for this new type of AE sensor. This dissertation presents the results of both analytical and experimental study on the signal characteristics of surface stress-wave induced AE strain signals measured by piezoelectric film AE sensors in near-field and an AE source localization method based on sensor couple theory. Based on moment tensor theory, generalized expression for AE strain signal is formulated. A special case involving the response of piezoelectric film AE sensor to surface load is also studied, which could potentially be used for sensor calibration of this type of sensor. A new concept of sensor couple theory based AE source localization technique is proposed and validated with both simulated and experimental data from fatigue test and field monitoring. Two series of fatigue tests were conducted to perform fatigue crack monitoring on large-scale steel test specimens using piezoelectric film AE sensors. Continuous monitoring of fatigue crack growth in steel structures is demonstrated in these fatigue test specimens. The use of piezoelectric film AE sensor for field monitoring of existing fatigue crack is also demonstrated in a real steel I-girder bridge located in Maryland. The sensor couple theory based AE source localization is validated using a limited number of piezoelectric film AE sensor data from both fatigue test specimens and field monitoring bridge. Through both laboratory fatigue test and field monitoring of steel structures with active fatigue cracks, the signal characteristics of piezoelectric film AE sensor have been studied in real-world environment.