The main objective of this paper is a feasibility Study for measuring tensile forces in the steel wire which are widely used in various types of prestressed structures. A steel wire serves as a load-bearing element, and electromagnetic-acoustic transducers are used to excite and detect resonant vibrational modes. The results show a promising feasibility on measurement of tensile forces in the steel wire.

After analyzing the evaluation details of the durability items of the concrete retaining wall for a certain period, the problems were identified. The lack of competency and lack of institutional skills of participating engineers have been analyzed as the main factors, and the improvement of technical and institutional aspects is required.

This paper presents an automated determination technique of optimal subset sizes for digital image correlation (DIC) analysis of speckle patterned images. The smaller subset size would typically have the higher DIC accuracy with respect to local minute deformation, but insufficient speckle pattern information within the excessively small often augment DIC errors due to lack of correlation features. Therefore, optimal subset size determination is crucial for the precise DIC analysis. To automate the optimal subset size determination process, first, the reference and test speckle pattern images are obtained from the target structure surface with a certain time interval. Then, an initial seed point which will be used for the subset center point is assigned on the reference speckle pattern image. Subsequently, normalized cross correlation (NCC) between the reference and test images is performed by increasing subset sizes from the seed point. Next, the matching distance between the two images is calculated using the maximum correlation coefficient. As the subset size increases, the matching distance between the two subsets converges a certain value. It physically means that the sufficient correlation features will be included in the subset. Finally, the optimal subset size can be determined by selecting the minimum subset size where the matching distance value starts to be converged. The proposed technique is experimentally validated using an aluminium plate with sprayed speckle pattern.

recently, information about buried objects has been needed for redevelopment and reorganization of the complicated urban environment. Accidents caused by pipeline damages, such as gas lines, communication lines and underground electric power lines, are results of loss of people and property. Therefore, information on underground obscured material is essential for safety and construction progress. GPR (Ground Penetrating Radar) investigation has advantages of high resolution, ease of utilization and strong electromagnetic noise when using high frequency. However, the GPR detection data image is not visible and has a problem that it is interpreted differently according to the skill of the inspector. Therefore, this study was conducted to verify the visualization of detection data using computer vision based on GPR detection data. Canny edge and Harris corner detection were applied to the GPR image data to detect the hyperbolic shape. By using this to increase the visibility, it will contribute to the reliable result in the buried detection.

Pavement condition deteriorates due to various environmental issues. This can be seen on the pavement surface as a form of distress. A crack can be considered as a typical form of pavement distress in which it may reveal a critical condition of the road. Therefore, automatic and accurate detection of pavement crack and segmentation are crucial for pavement condition assessment and maintenance.

The evaluation for the status and levels of tension acting on a cable supported structure has been a issue due to the structural stability. Each of strands comprising that structures is adopted prestress, the tension level of the strand during the operation is a significant factor for structural integrity of the system. However, a suitable alternative for measurement of tension acting on a strand is not proposed, as well as conservative assessment of cable system is bing adopted in industrial application. Thus, in this paper, a new method is proposed for measurement of tensile forces in a strand using guided waves. This method use a dispersion characteristic of guided waves with variation of stiffness between each of wires. Proposed method is experimentally verified by some experiments using a seven-wire strand.

The purpose of this research is to develop nondestructive equipment using magnetic flux leakage(MFL) principle and to confirm the accuracy of the equipment. The equipment consist of a magnetization part, a sensor part, and a data storage part. The parameters of specimens for equipment verification are the length and the area of flaws. It was confirmed that the equipment accurately probed the locations of the flaws in the specimens, and grout had little effect on the results of the test.

This paper proposes a deep learning-based underground object classification technique incorporated with phase analysis of ground penetrating radar (GPR) for enhancing the underground object classification capability. Deep convolutional neural network (CNN) using the combination of the B- and C-scan images has recently emerged for automated underground object classification. However, it often leads to misclassification because arbitrary underground objects may have similar signal features. To overcome the drawback, the combination of B- and C-scan images as well as phase information of GPR are simultaneously used for CNN in this study, enabling to have more distinguishable signal features among various underground objects. The proposed technique is validated using in-situ GPR data obtained from urban roads in Seoul, South Korea. The validation results show that the false alarm is significantly reduced compared to the CNN results using only B- and C-scan images.

Ground penetrating radar (GPR) is a typical sensor system for underground objects detection area. The multichannel GPR devices can give more detail and informative three-dimensional (3D) data for classification underground objects. Spatial information of underground objects can be well characterized in the three-dimensional GPR block data which consists of several B-scan and C-scan data. In this article underground object classification method is proposed by using 3D GRP data. Deep learning technique is recently being adopted into this field due to its powerful image classification capacity. The 3D GRP block data is then used to train deep three-dimensional convolution neural network (3D CNN). The proposed method successfully classifies cavity, pipe, manhole and subsoils having small false positive errors. The suggested method is experimentally validated by area data collected on urban roads in Seoul, South Korea.

The current fire-damage inspection and safety diagnosis has not developed from the labour and time-consuming method. Data collected through traditional safety inspection and survey methods are less quantitative and causes irregularity to the database; thus data becomes impractical for long-term maintenance and analysis. Data by 3D Scanning are more precise and quantitative in calculating the damages by a fire, the amount to repair and reinforce; furthermore, in evaluating the safety of the structure.

The damage detection method of blade systems largely depends on the personal ability of an inspector using a camera. Thus, this paper proposes a deep learning-based detection method that can rapidly and reliably identify and evaluate the damages on the blades.

Magnetic sensing NDE(non-destructive evaluation) method was applied to detect local damages at the steel chain of the escalator. To verify the feasibility of the magnetic sensing based chain inspection method, a magnetic sensor head was fabricated to adapt to the target chain. The fabricated sensor head scanned the notch damaged chain specimen to measure the magnetic flux signals. After obtaining signal, a series of signal processing process including pick picking and enveloping process based on Hilbert transform (HT) was performed to detect the damaged point by clarifying the signal.

Recently, due to advancement in construction techniques, structures are being constructed much faster than before. Therefore, structures such as cable stayed bridges and suspension bridges, must be inspected regularly to assure their main elements (i.e., load carrying cables) are healthy and sound. Structures can be tested using conventional nondestructive testing methods such as magnetic flux leakage (MFL), eddy current testing, acoustic emission and etc. In this study, it was tried to detect cross sectional reduction in steel rod using a time dependent numerical simulation of coil sensor based on MFL principle.

If deposits occur around the dam, it is possible to suspect the erosion of the internal material of the dam. Piping can occur if the dam internal material is eroded, and such piping can be a serious safety hazard for the dam. XRD and XRF were performed on the investigated sediments and dam core materials. XRD and XRF were carried out to confirm the constituent minerals and chemical composition of the samples. This method can be applied to detect the possibility of erosion of the material constituting the dam.

In this investigation, the reservoir stability was reviewed using hydrological and physical examination. The results of the review showed that, Both sites were analyzed to lack embankment height and sidewall height in the event of flooding, and it was considered that measures to increase stability should be established in the future by adding more dam cest and increasing side wall of a spill way. In addition, analysis and research will be necessary for other reservoir deteriorated in the future.

In this study, fatigue cracks in welled joints of gusset plate at the lower flange of the plate girder bridge, field measurements were carried out and their test results were analyzed. Results obtained are summarized as follows. The proposed the reliability of the reinforcement effect by comparing the maximum stress value with the limit of the fatigue detailed category E.

This study introduces the experimental relation between impedance frequency and applied stress level on a wire. The impedance of a stressed wire in the range of frequency from DC to 5M Hz is examined for three different applied stress conditions. It is confirmed that the impedance of a wire is inversely proportional to applied stress rate for most frequency range. Also, some impedance peaks are observed at certain specific frequency regions.

This research aims to detect delamination-like damage from asphalt-concrete interface using contactless ultrasonic technique. FEM simulation and experiments demonstrate that surface waves and S mode are strongly present when there is delamination-like damage. It is believed that the measurement of S mode by non-contact ultrasonic system will allow one to determine the existence of delamination-like damage from bridge decks.

In this study, non-destructive methods were applied to detect cavities behind face-slab of concrete-faced rockfill dam (CFRD). This study reviewed the effectiveness of the field IE, MASW, MIRA shear wave tomography and GPR findings. IR techniques also reviewed as an additional method of exploration to reinforce the proposed methods of exploration. Among previous methods, IE exploration was concluded most appropriate as an efficient way to detect cavity of the CFRD. Nevertheless, additional reinforcement investigation is required because the result of a single exploration is difficult to reduce the uncertainty.

In this study, we analyze the policy related to building safety diagnosis and maintenance management and suggest improvement direction of system for building diagnosis. The US has various test methods and laws and regulations standardized on wide territory, so it is excellent in responding to changes in regulations. In the UK, the technology of the building diagnosis related field is advanced through systematic efforts of diagnosis and maintenance of the building. Therefore, it is necessary to establish and revitalize regulations related to building diagnosis and maintenance management, to revise the laws and regulations of related institutions, and to systematically cultivate manpower through specialized agencies related to diagnosis and maintenance.