Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

Sources, Fate and Transformation of Organic Matter in Wetlands and Estuaries

Dissolved organic matter (DOM) is a complex mixture of organic compounds and represents the largest reservoirs of carbon (C) on earth. Particulate organic matter (POM) is another important carbon component in C cycling and controls a variety of biogeochemical processes. Estuaries, as important interfaces between land and ocean, play important roles in retaining and transforming such organic matter (OM) and serve as both sources and sinks of DOM and POM. There is a diverse array of both autochthonous and allochthonous OM sources in wetland/estuarine ecosystems. A comprehensive study on the sources, transformation and fate of OM in such ecosystems is essential in advancing our understanding of C cycling and better constraining the global C budget. In this work, DOM characteristics were investigated in different estuaries. Dissolved organic matter source strengths and dynamics were assessed in a seagrass-dominated subtropical estuarine lagoon. DOM dynamics controlled by hydrology and seagrass primary productivity were confirmed, and the primary source of DOM was quantified using the combination of excitation emission matrix fluorescence with parallel factor analysis (EEM-PARAFAC) and stable C isotope analysis. Seagrass can contribute up to 72% of the DOM in the study area. The spatial and temporal variation of DOM dynamics was also studied in a freshwated dominated estuary fringed with extensive salt marshes. The data showed that DOM was primarily derived from freshwater marshes and controlled by hydrology while salt marsh plants play a significant role in structuring the distribution patterns of DOM quality and quantity. The OM dynamics was also investigated in a mangrove-dominate estuary and a comparative study was conducted between the DOM and POM pools. The results revealed both similarity and dissimilarity in DOM and POM composition. The dynamics of both OM pools are largely uncoupled as a result of source differences. Fringe mangrove swamps are suggested to export similar amounts of DOM and POM and should be considered as an important source in coastal C budgets. Lastly, chemical characterizations were conducted on the featured fluorescence component in OM in an attempt to better understand the composition and origins of the specific PARAFAC component. The traditionally defined ‘protein-like’ fluorescence was found to contain both proteinaceous and phenolic compounds, suggesting that the application of this parameter as a proxy for amino acid content and bioavailability may be limited.