The Pearl Banks inspection: April, 1970

The last major pearl fishery in the Gulf of Mannar was held in February-March, 1958, when about 4.5 million oysters were collected from the south-west Cheval Paar by dredging. (Sivalingam 1961). Subsequently, two smaller fisheries, one in 1960 and another in 1961 took place. In these two fisheries one million oysters and four hundred thousand oysters respectively were collected from the Cheval paar by dredging. (De Fonselm 1953). Inspections of the Banks were carried out in 1962, 1963, 1964 and 1965. (Balasuriya 1964 and Silva 1965 and 66). Since then inspections were not possible due to one of two reasons or both the non-availability of operational dredges and a suitable vessel for this type of work.The "Pesalai" a 235-ton stern trawler was made available by the Ceylon Fisheries Corporation management for the 1970 inspection. Two new 6-foot dredges turned out by the Government Factory were also available for this work. However, the survey was limited to 3 days-the period for which the vessel had been released. It was further limited to those areas of the banks over 6 fathoms in depth because of the risk in operating a large vessel in shallower depths.

An aerial survey for surface tuna resources in the seas around Ceylon

An aerial survey of the off shore range around Ceylon, for a quick evaluation of the potential surface tuna resources, for commercial exploitation, was organised by Mr. Manuel R. Cintas of Ocean Blazer Inc. (Commercial tuna), San Diego, California and his associate Mr. R. Perera. The organisers offered, through the Hon'ble Minister of Fisheries, to take an officer of the Fisheries Research Station, Ceylon, as an observer and the author participated in that capacity. Dr. V. Arkely served as the photographer. The survey period was within the South-West monsoon season and extremely bad weather with high speed winds were experienced particularly off the North-West and South coasts. Except during these two trips, an average altitude of 1,000 ft. and a flying speed of 110-115 m.p.h. were maintained. The program was to cover the off shore range between 15 miles and 50 miles, from shore. The total number of hours of flying was eighteen. Details of the flight plan are shown in figure 1.

Design considerations for a micro aerial vehicle aerodynamic characterization facility at the University of Florida research and engineering education facility

This paper describes the design considerations for a proposed aerodynamic characterization facility (ACF) for micro aerial vehicles (MAVs). This is a collaborative effort between the Air Force Research Laboratory Munitions Directorate (AFRL/MN) and the University of Florida Research and Engineering Education Facility (UF/REEF). The ACF is expected to provide a capability for the characterization of the aerodynamic performance of future MAVs. This includes the ability to gather the data necessary to devise control strategies as well as the potential to investigate aerodynamic 'problem areas' or specific failings. Since it is likely that future MAVs will incorporate advanced control strategies, the facility must enable researchers to critically assess such novel methods. Furthermore, the aerodynamic issues should not be seen (and tested) in isolation, but rather the facility should be able to also provide information on structural responses (such as aeroelasticity) as well as integration issues (say, thrust integration or sensor integration). Therefore the mission for the proposed facility ranges form fairly basic investigations of individual technical issues encountered by MAVs (for example an evaluation of wing shapes or control effectiveness) all the way to testing a fully integrated vehicle in a flight configuration for performance evaluation throughout the mission envelope.

Detection of large-scale concrete columns for automated bridge inspection

There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame. This is because manually inspecting bridges is a time-consuming and costly task, and some state Departments of Transportation (DOT) cannot afford the essential costs and manpower. In this paper, a novel method that can detect large-scale bridge concrete columns is proposed for the purpose of eventually creating an automated bridge condition assessment system. The method employs image stitching techniques (feature detection and matching, image affine transformation and blending) to combine images containing different segments of one column into a single image. Following that, bridge columns are detected by locating their boundaries and classifying the material within each boundary in the stitched image. Preliminary test results of 114 concrete bridge columns stitched from 373 close-up, partial images of the columns indicate that the method can correctly detect 89.7% of these elements, and thus, the viability of the application of this research.

Large Scale Column Detection for Bridge Inspection

Manually inspecting bridges is a time-consuming and costly task. There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame as some state DOTs cannot afford the essential costs and manpower. This paper presents a novel method that can detect bridge concrete columns from visual data for the purpose of eventually creating an automated bridge condition assessment system. The method employs SIFT feature detection and matching to find overlapping areas among images. Affine transformation matrices are then calculated to combine images containing different segments of one column into a single image. Following that, the bridge columns are detected by identifying the boundaries in the stitched image and classifying the material within each boundary. Preliminary test results using real bridge images indicate that most columns in stitched images can be correctly detected and thus, the viability of the application of this research.

Machine Vision Enhanced Post-Earthquake Inspection and Rapid Loss Estimation

Manual inspection is required to determine the condition of damaged buildings after an earthquake. The lack of available inspectors, when combined with the large volume of inspection work, makes such inspection subjective and time-consuming. Completing the required inspection takes weeks to complete, which has adverse economic and societal impacts on the affected population. This paper proposes an automated framework for rapid post-earthquake building evaluation. Under the framework, the visible damage (cracks and buckling) inflicted on concrete columns is first detected. The damage properties are then measured in relation to the column's dimensions and orientation, so that the column's load bearing capacity can be approximated as a damage index. The column damage index supplemented with other building information (e.g. structural type and columns arrangement) is then used to query fragility curves of similar buildings, constructed from the analyses of existing and on-going experimental data. The query estimates the probability of the building being in different damage states. The framework is expected to automate the collection of building damage data, to provide a quantitative assessment of the building damage state, and to estimate the vulnerability of the building to collapse in the event of an aftershock. Videos and manual assessments of structures after the 2009 earthquake in Haiti are used to test the parts of the framework.

Machine Vision Enhanced Post-earthquake Inspection

Camera motion estimation is one of the most significant steps for structure-from-motion (SFM) with a monocular camera. The normalized 8-point, the 7-point, and the 5-point algorithms are normally adopted to perform the estimation, each of which has distinct performance characteristics. Given unique needs and challenges associated to civil infrastructure SFM scenarios, selection of the proper algorithm directly impacts the structure reconstruction results. In this paper, a comparison study of the aforementioned algorithms is conducted to identify the most suitable algorithm, in terms of accuracy and reliability, for reconstructing civil infrastructure. The free variables tested are baseline, depth, and motion. A concrete girder bridge was selected as the "test-bed" to reconstruct using an off-the-shelf camera capturing imagery from all possible positions that maximally the bridge's features and geometry. The feature points in the images were extracted and matched via the SURF descriptor. Finally, camera motions are estimated based on the corresponding image points by applying the aforementioned algorithms, and the results evaluated.

An analytical model for guided wave inspection optimization for prismatic structures of any cross section.

This paper presents an analytical modeling technique for the simulation of long-range ultrasonic guided waves in structures. The model may be used to predict the displacement field in a prismatic structure arising from any excitation arrangement and may therefore be used as a tool to design new inspection systems. It is computationally efficient and relatively simple to implement, yet gives accuracy similar to finite element analysis and semi-analytical finite element analysis methods. The model has many potential applications; one example is the optimization of part-circumferential arrays where access to the full circumference of the pipe is restricted. The model has been successfully validated by comparison with finite element solutions. Experimental validation has also been carried out using an array of piezoelectric transducer elements to measure the displacement field arising from a single transducer element in an 88.9-mm-diameter pipe. Good agreement has been obtained between the two models and the experimental data.