scholarly journals Concrete Crack Detection and Monitoring Using a Capacitive Dense Sensor Array

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1843 ◽  
Author(s):  
Jin Yan ◽  
Austin Downey ◽  
Alessandro Cancelli ◽  
Simon Laflamme ◽  
An Chen ◽  
...  
Keyword(s):  
Fiber Optics ◽  
Concrete Beam ◽  
Crack Detection ◽  
Low Cost ◽  
Fatigue Cracks ◽  
Concrete Structures ◽  
Structural Safety ◽  
Small Scale ◽  
Sensing Skin ◽  
Post Tensioned

Cracks in concrete structures can be indicators of important damage and may significantly affect durability. Their timely identification can be used to ensure structural safety and guide on-time maintenance operations. Structural health monitoring solutions, such as strain gauges and fiber optics systems, have been proposed for the automatic monitoring of such cracks. However, these solutions become economically difficult to deploy when the surface under investigation is very large. This paper proposes to leverage a novel sensing skin for monitoring cracks in concrete structures. This sensing skin is constituted of a flexible electronic termed soft elastomeric capacitor, which detects a change in strain through changes in measured capacitance. The SEC is a low-cost, durable, and robust sensing technology that has previously been studied for the monitoring of fatigue cracks in steel components. In this study, the sensing skin is introduced and preliminary validation results on a small-scale reinforced concrete beam are presented. The technology is verified on a full-scale post-tensioned concrete beam. Results show that the sensing skin is capable of detecting, localizing, and quantifying cracks that formed in both the reinforced and post-tensioned concrete specimens.

scholarly journals Crack Detection of Reinforced Concrete Structures Based on BOFDA and FBG Sensors

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Qinghua Zhang ◽  
Ziming Xiong
Keyword(s):  
Reinforced Concrete ◽  
Concrete Beam ◽  
Crack Detection ◽  
Concrete Structures ◽  
Lower Surface ◽  
Reinforced Concrete Beam ◽  
Sensor Data ◽  
Reinforced Concrete Structures ◽  
Surface Cracks ◽  
Fbg Sensors

Reinforced concrete structural elements, as an important component of buildings and structures, require inspection for the purposes of crack detection which is an important part of structural health monitoring. Now existing crack detection methods usually use a single technology and can only detect internal or external cracks. In this paper, the authors propose a new sensing system combining BOFDA (Brillouin optical frequency-domain analysis) and FBG (fiber Bragg grating) technology, which are used to detect internal and surface cracks and their development in reinforced concrete structures, and an attempt is made to estimate the width of surface cracks. In these experiments, a special reinforced concrete beam structure was designed by the author for crack detection under load. Four continuous distributed optical fibers are fixed on the steel skeleton, which is located within the reinforced concrete beam. Three FBG sensors are fixed on the lower surface of the beam, near its centre. By analysing the sensor data, it can be found that the BOFDA-distributed fiber can be used to detect internal cracking before surface cracking, and the difference between scans can be used to judge the time of onset of internal cracking, but the relative error in position is about 5%, while the FBG sensor can detect the cracking time of microcracks on the lower surface in near-real-time and can be used to calculate the crack width. Through the experiment, it is found that if the combination of BOFDA and FBG technology is adopted, we can initially use the strain data obtained by multiple groups of BOFDA monitoring to predict the general location of the internal cracks, then to monitor the exact location of the surface cracks by FBG in the medium term, and to estimate the width of the final expansion of the cracks finally.

Effects of Aggregate Size on Concrete Shear Strength

2014 ◽  
Vol 970 ◽  
pp. 143-146
Author(s):  
Lau Teck Leong ◽  
Chen Zhe ◽  
Abdullahi Ali Mohamed ◽  
Wee Kang Choong
Keyword(s):  
Shear Strength ◽  
Reinforced Concrete ◽  
Concrete Beam ◽  
Concrete Structures ◽  
Aggregate Size ◽  
Shear Behaviour ◽  
Maximum Aggregate Size ◽  
Small Scale ◽  
Reinforced Concrete Structures ◽  
Normal Concrete

In view of the importance of the applicability of small-scale beam specimens in replicating the shear behaviour of prototype reinforced concrete structures, this study was conducted on beam specimens cast with micro-concrete having scaled aggregates (maximum sizes: 10mm, 5mm, and 2mm) to investigate whether the use of micro-concrete impose any reduction in their shear strength. The results indicate the maximum aggregate size (s) has negligible effects on concrete shear strength, and the micro-concrete beam specimens replicate the shear behaviour of normal concrete.

Fatigue crack detection method using analysis of vibration signal

2017 ◽  
Vol 1 (20) ◽  
pp. 63-74 ◽  
Author(s):  
Arkadiusz Rychlik ◽  
Krzysztof Ligier
Keyword(s):  
Crack Detection ◽  
Fatigue Cracks ◽  
Fatigue Cracking ◽  
Vibration Signal ◽  
Technical Condition ◽  
Visual Methods ◽  
Signal Characteristics ◽  
Fatigue Crack Detection ◽  
Sample Structure ◽  
Change Identification

This paper discusses the method used to identify the process involving fatigue cracking of samples on the basis of selected vibration signal characteristics. Acceleration of vibrations has been chosen as a diagnostic signal in the analysis of sample cross section. Signal characteristics in form of change in vibration amplitudes and corresponding changes in FFT spectrum have been indicated for the acceleration. The tests were performed on a designed setup, where destruction process was caused by the force of inertia of the sample. Based on the conducted tests, it was found that the demonstrated sample structure change identification method may be applied to identify the technical condition of the structure in the aspect of loss of its continuity and its properties (e.g.: mechanical and fatigue cracks). The vibration analysis results have been verified by penetration and visual methods, using a scanning electron microscope.

Tools of Transformation: Appropriate Technology in U.S. Countercultural Literature

2012 ◽  
Vol 44 (2) ◽  
pp. 75-93
Author(s):  
Peter Mortensen
Keyword(s):  
Low Cost ◽  
Appropriate Technology ◽  
Small Scale ◽  
Environmental Transformation ◽  
Buckminster Fuller ◽  
1960S And 1970S ◽  
The 1960S ◽  
Environmentally Sound ◽  
User Friendly ◽  
Second Wave

This essay takes its cue from second-wave ecocriticism and from recent scholarly interest in the “appropriate technology” movement that evolved during the 1960s and 1970s in California and elsewhere. “Appropriate technology” (or AT) refers to a loosely-knit group of writers, engineers and designers active in the years around 1970, and more generally to the counterculture’s promotion, development and application of technologies that were small-scale, low-cost, user-friendly, human-empowering and environmentally sound. Focusing on two roughly contemporary but now largely forgotten American texts Sidney Goldfarb’s lyric poem “Solar-Heated-Rhombic-Dodecahedron” (1969) and Gurney Norman’s novel Divine Right’s Trip (1971)—I consider how “hip” literary writers contributed to eco-technological discourse and argue for the 1960s counterculture’s relevance to present-day ecological concerns. Goldfarb’s and Norman’s texts interest me because they conceptualize iconic 1960s technologies—especially the Buckminster Fuller-inspired geodesic dome and the Volkswagen van—not as inherently alienating machines but as tools of profound individual, social and environmental transformation. Synthesizing antimodernist back-to-nature desires with modernist enthusiasm for (certain kinds of) machinery, these texts adumbrate a humanity- and modernity-centered post-wilderness model of environmentalism that resonates with the dilemmas that we face in our increasingly resource-impoverished, rapidly warming and densely populated world.

scholarly journals Development of a simplified gas ultracleaning process: experiments in biomass residue-based fixed-bed gasification syngas

2021 ◽  
Author(s):  
Christian Frilund ◽  
Esa Kurkela ◽  
Ilkka Hiltunen
Keyword(s):  
Activated Carbons ◽  
Low Cost ◽  
Fixed Bed ◽  
Carbonyl Sulfide ◽  
Gas Analysis ◽  
Small Scale ◽  
Cleaning Process ◽  
Medium Temperature ◽  
Gas Cleaning ◽  
Adsorption Affinity

AbstractFor the realization of small-scale biomass-to-liquid (BTL) processes, low-cost syngas cleaning remains a major obstacle, and for this reason a simplified gas ultracleaning process is being developed. In this study, a low- to medium-temperature final gas cleaning process based on adsorption and organic solvent-free scrubbing methods was coupled to a pilot-scale staged fixed-bed gasification facility including hot filtration and catalytic reforming steps for extended duration gas cleaning tests for the generation of ultraclean syngas. The final gas cleaning process purified syngas from woody and agricultural biomass origin to a degree suitable for catalytic synthesis. The gas contained up to 3000 ppm of ammonia, 1300 ppm of benzene, 200 ppm of hydrogen sulfide, 10 ppm of carbonyl sulfide, and 5 ppm of hydrogen cyanide. Post-run characterization displayed that the accumulation of impurities on the Cu-based deoxygenation catalyst (TOS 105 h) did not occur, demonstrating that effective main impurity removal was achieved in the first two steps: acidic water scrubbing (AWC) and adsorption by activated carbons (AR). In the final test campaign, a comprehensive multipoint gas analysis confirmed that ammonia was fully removed by the scrubbing step, and benzene and H2S were fully removed by the subsequent activated carbon beds. The activated carbons achieved > 90% removal of up to 100 ppm of COS and 5 ppm of HCN in the syngas. These results provide insights into the adsorption affinity of activated carbons in a complex impurity matrix, which would be arduous to replicate in laboratory conditions.

Deep Learning based Thermal Crack Detection on Structural Concrete Exposed to Elevated Temperature

2021 ◽  
pp. 136943322098663
Author(s):  
Diana Andrushia A ◽  
Anand N ◽  
Eva Lubloy ◽  
Prince Arulraj G
Keyword(s):  
Deep Learning ◽  
Crack Detection ◽  
Detection Method ◽  
Concrete Structures ◽  
Vital Role ◽  
Subjective Knowledge ◽  
Thermal Cracks ◽  
Reinforced Cement ◽  
Novel Method ◽  
Human Inspection

Health monitoring of concrete including, detecting defects such as cracking, spalling on fire affected concrete structures plays a vital role in the maintenance of reinforced cement concrete structures. However, this process mostly uses human inspection and relies on subjective knowledge of the inspectors. To overcome this limitation, a deep learning based automatic crack detection method is proposed. Deep learning is a vibrant strategy under computer vision field. The proposed method consists of U-Net architecture with an encoder and decoder framework. It performs pixel wise classification to detect the thermal cracks accurately. Binary Cross Entropy (BCA) based loss function is selected as the evaluation function. Trained U-Net is capable of detecting major thermal cracks and minor thermal cracks under various heating durations. The proposed, U-Net crack detection is a novel method which can be used to detect the thermal cracks developed on fire exposed concrete structures. The proposed method is compared with the other state-of-the-art methods and found to be accurate with 78.12% Intersection over Union (IoU).

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