• Journal of Drive and Control
• /
• v.19 no.3
• /
• pp.16-22
• /
• 2022

Crushers are equipment that crush natural stones, to produce aggregates used at construction sites. As the crusher proceeds, the inner liner becomes worn, causing the size of the aggregate produced to gradually increase. The vision sensor-based aggregate analysis system analyzes the size and distribution of aggregates in production, in real time through image analysis. This study developed an algorithm that can segmentate aggregates in images in real time. using image preprocessing technology combining various filters and morphology techniques, and aggregate region characteristics such as convex hull and concave hull. We applied the developed algorithm to fine aggregate, intermediate aggregate, and thick aggregate images to verify their performance.

• Structural Monitoring and Maintenance
• /
• v.5 no.2
• /
• pp.313-323
• /
• 2018

The presence of water inside concrete structures is an essential condition for the deterioration of the structures. The free water in the concrete pores and micro-cracks is the culprit for the durability related problems, such as alkali-aggregate reaction, carbonation, freeze-thaw damage, and corrosion of steel reinforcement. To ensure the integrity and safe operation of the concrete structures, it is very important to monitor water seepage inside the concrete. This paper presents the experimental investigation of water seepage monitoring in a concrete slab using piezoelectric-based smart aggregates. In the experimental setup, an $800mm{\times}800mm{\times}100mm$ concrete slab was fabricated with 15 SAs distributed inside the slab. The water seepage process was monitored through interrogating the SA pairs. In each SA pair, one SA was used as actuator to emit harmonic sine wave, and the other was used as sensor to receive the transmitted stress wave. The amplitudes of the received signals were able to indicate the water seepage process inside the concrete slab.

• Computers and Concrete
• /
• v.23 no.6
• /
• pp.399-408
• /
• 2019

Structural health monitoring is important for the safety of lives and asset management. In this study, numerical models were developed for the piezoresistive behavior of smart concrete based on finite element (FE) method. Finite element models were calibrated with experimental data collected from compression test. The compression test was performed on smart concrete cube specimens with 75 mm dimensions. Smart concrete was made of cement CEM II 42.5 R, silica fume, fine and coarse crushed limestone aggregates, brass fibers and plasticizer. During the compression test, electrical resistance change and compressive strain measurements were conducted simultaneously. Smart concrete had a strong linear relationship between strain and electrical resistance change due to its piezoresistive function. The piezoresistivity of the smart concrete was modeled by FE method. Twenty-noded solid brick elements were used to model the smart concrete specimens in the finite element platform of Ansys. The numerical results were determined for strain induced resistivity change. The electrical resistivity of simulated smart concrete decreased with applied strain, as found in experimental investigation. The numerical findings are in good agreement with the experimental results.

• Smart Structures and Systems
• /
• v.24 no.4
• /
• pp.541-552
• /
• 2019

Construction development and greenhouse gas emissions have globally required a strategic management to take some steps to stain and maintain the environment. Nowadays, recycled aggregates, in particular ceramic waste, have been widely used in concrete structures due to the economic and environmentally friendly solution, requiring the knowledge of recycled concrete. Also, one of the materials used as a substitute for concrete cement is wollastonite mineral to decrease carbon dioxide (CO2) from the cement production process by reducing the concrete consumption in concrete. The purpose of this study is to investigate the effect of wollastonite on the mechanical properties and durability of conventional composite concrete, containing recycled aggregates such as compressive strength, tensile strength (Brazilian test), and durability to acidic environment. On the other hand, in order to determine the strength and durability of the concrete, 5 mixing designs including different wollastonite values and recovered aggregates including constant values have been compared to the water - cement ratio (w/c) constant in all designs. The experimental results have shown that design 5 (containing 40% wollastonite) shows only 6.1% decrease in compressive strength and 4.9% decrease in tensile strength compared to the control plane. Consequently, the use of wollastonite powder to the manufacturing of conventional structural concrete containing recycled ceramic aggregates, in addition to improving some of the properties of concrete are environmentally friendly solutions, providing natural recycling of materials.

• Journal of Korea Multimedia Society
• /
• v.17 no.4
• /
• pp.458-465
• /
• 2014

In this paper, we propose a strategy to distribute the energy consumption over the network. The proposed strategy is based on geographic routing. We use a smart base station that maintains the residual energy and location information of sensor nodes and selects a head node and an anchor node using this information. A head node gathers and aggregates data from the sensor nodes in a target region that interests the user. An anchor node then transmits the data that was forwarded from the head node back to the smart base station. The smart base station extends network lifetime by selecting an optimal head node and an optimal anchor node. We simulate the proposed protocol and compare it with the LEACH protocol in terms of energy consumption, the number of dead nodes, and a distribution map of dead node locations.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.28 no.1
• /
• pp.24-31
• /
• 2024

Mortar has been applied in most previous studies on 3D concrete printing. In such cases, however, the economic efficient cannot help decreasing due to higher binder contents and larger amount of fine aggregates. In order to enhance the applicability of 3D printing technology to construction industry, therefore, 3D concrete printing technology utilizing coarse aggregates needs to be developed further. This study aims at proposing the mix design process of concrete containing coarse aggregates for 3D printing. Based on extensive literature review and experimental studies, the mix proportion suitable for 3D printing has been derived, and the extrudability of concrete with coarse aggregates has been verified through 3D printing tests. The primary variable of the extrudability tests was the contents of viscosity modifying agent (VMA), and the extrudability was quantitatively evaluated by measuring dimensions, distribution of aggregates, and surface quality of 3D-printed filaments. The test results showed that the dimensional suitability and surface quality were improved as the VMA contents were larger, and the coarse aggregates were evenly distributed in the section of filament regardless of the VMA contents. Based on the test results, the mix design process for concrete containing coarse aggregates for 3D printing has been proposed.

• Smart Structures and Systems
• /
• v.20 no.2
• /
• pp.175-180
• /
• 2017

The load-carrying capacity and structural behavior of concrete-filled steel tube (CFST) structures is highly influenced by the grouting compactness in the steel tube. Due to the invisibility of the grout in the steel tube, monitoring of the grouting progress in such a structure is still a challenge. This paper develops an active sensing approach with combined piezoceramic-based smart aggregates (SA) and piezoceramic patches to monitor the grouting compactness of CFST bridge structure. A small-scale steel specimen was designed and fabricated to simulate CFST bridge structure in this research. Before casting, four SAs and two piezoceramic patches were installed in the pre-determined locations of the specimen. In the active sensing approach, selected SAs were utilized as actuators to generate designed stress waves, which were detected by other SAs or piezoceramic patch sensors. Since concrete functions as a wave conduit, the stress wave response can be only detected when the wave path between the actuator and the sensor is filled with concrete. For the sake of monitoring the grouting progress, the steel tube specimen was grouted in four stages, and each stage held three days for cement drying. Experimental results show that the received sensor signals in time domain clearly indicate the change of the signal amplitude before and after the wave path is filled with concrete. Further, a wavelet packet-based energy index matrix (WPEIM) was developed to compute signal energy of the received signals. The computed signal energies of the sensors shown in the WPEIM demonstrate the feasibility of the proposed method in the monitoring of the grouting progress.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.4
• /
• pp.62-69
• /
• 2023

This study investigated the electromechanical properties of cement based smart repair materials (SRMs) according to the different amounts of fine steel slag aggregates (FSSAs). SRMs can self-diagnose the quality of repairing and self-sense the damage of repaired zone. The replacement ratios of FSSAs to sand for SRMs were 0% (FSSA00), 25% (FSSA25), and 50% (FSSA50) by sand weight. The electrical resistivity of SRMs generally decreased as the compressive stress of SRMs increased: the electrical resistivity of FSSA25 at the age of 7 hours decreased from 78.16 to 63.68 kΩ-cm as the compressive stress increased from 0 to 22.37 MPa. As the replacement ratio of FSSAs by weight of sand increased from 0% to 25%, the stress sensitivity coefficient (SSC) of SRM at the age of 7 h increased from 0.471 to 0.828 %/MPa owing to the increased number of partially conductive paths in the SRMs. However, as the replacement ratio of FSSAs further increased up to 50%, the SSC decreased from 0.828 to 0.649 %/MPa because some of the partially conductive paths changed to continued conductive ones. SRMs are expected to self-sense the quality and future damage of repaired zone only by measuring the electrical resistivity of the repaired zone in addition to fast recovery in the mechanical resistance of structures.

• Smart Structures and Systems
• /
• v.22 no.4
• /
• pp.425-432
• /
• 2018

Predicting the compressive strength of concrete has been considered as the initial phase across the cement production processing. The current study has focused on the integration of the concrete compressive strength in 28 days with the mix of the major oxides and fine aggregates as an experimental formula through the use of two types of Portland cement resulting the compressive strength of the concrete highly dependent on time.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.6
• /
• pp.255-266
• /
• 2022

The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.