scholarly journals Drone-Based Vibration Monitoring and Assessment of Structures

2021 ◽  
Vol 11 (18) ◽  
pp. 8560
Author(s):  
Sabrina Carroll ◽  
Joud Satme ◽  
Shadhan Alkharusi ◽  
Nikolaos Vitzilaios ◽  
Austin Downey ◽  
...  
Keyword(s):  
Impulse Response Function ◽  
Unmanned Aircraft ◽  
Vibration Monitoring ◽  
The Novel ◽  
Civil Structures ◽  
External Power ◽  
Novel Method ◽  
Aircraft System ◽  
Sensor Package ◽  
Dynamic Signature

This paper presents a novel method of procuring and processing data for the assessment of civil structures via vibration monitoring. This includes the development of a custom sensor package designed to minimize the size/weight while being fully self-sufficient (i.e., not relying on external power). The developed package is delivered to the structure utilizing a customized Unmanned Aircraft System (UAS), otherwise known as a drone. The sensor package features an electropermanent magnet for securing it to the civil structure while a second magnet is used to secure the package to the drone during flight. The novel B-Spline Impulse Response Function (BIRF) technique was utilized to extract the Dynamic Signature Response (DSR) from the data collected by the sensor package. Experimental results are presented to validate this method and show the feasibility of deploying the sensor package on structures and collecting data valuable for Structural Health Monitoring (SHM) data processing. The advantages and limitations of the proposed techniques are discussed, and recommendations for further developments are made.

Multiple view anomaly detection in images from UAS structure inspection using CNNs

2019 ◽  
Author(s):  
Paul Debus ◽  
Christian Benz ◽  
Volker Rodehorst
Keyword(s):  
Anomaly Detection ◽  
Unmanned Aircraft ◽  
Data Sets ◽  
Great Success ◽  
Imaging Geometry ◽  
Large Structures ◽  
3D Geometry ◽  
Novel Method ◽  
Aircraft System ◽  
Rich Data

<p>A novel method for automated anomaly detection in images acquired in structure inspection based on unmanned aircraft system (UAS) by means of deep learning is proposed. Using UAS in the inspection of large structures, rich data sets are produced, that can be used to support human inspectors. The image positions and orientations can automatically be reconstructed using structure from motion (SfM). A photogrammetric reconstruction of the 3D geometry is an established method for the analysis of deformations of structures. On this basis, a convolutional neural network (CNN) can be used to detect anomalies, such as cracks in the acquired images. While recently CNNs have been implemented with great success, the detection can further be improved by fusing the obtained results using geometry information gathered from photogrammetric reconstruction. The method leverages the imaging geometry reconstructed using SfM to significantly reduce the error rate of the network. The proposed method applies a fusion mechanism on detected anomalies in adjacent images to improve the detection performance.</p>

A novel method for the determination of linting propensity of paper

TAPPI Journal ◽  
2012 ◽  
Vol 11 (10) ◽  
pp. 9-17
Author(s):  
ALESSANDRA GERLI ◽  
LEENDERT C. EIGENBROOD
Keyword(s):  
Ash Content ◽  
The Novel ◽  
Offset Printing ◽  
Excellent Correlation ◽  
End Conditions ◽  
Bottom Side ◽  
Novel Method ◽  
Total Fraction

A novel method was developed for the determination of linting propensity of paper based on printing with an IGT printability tester and image analysis of the printed strips. On average, the total fraction of the surface removed as lint during printing is 0.01%-0.1%. This value is lower than those reported in most laboratory printing tests, and more representative of commercial offset printing applications. Newsprint paper produced on a roll/blade former machine was evaluated for linting propensity using the novel method and also printed on a commercial coldset offset press. Laboratory and commercial printing results matched well, showing that linting was higher for the bottom side of paper than for the top side, and that linting could be reduced on both sides by application of a dry-strength additive. In a second case study, varying wet-end conditions were used on a hybrid former machine to produce four paper reels, with the goal of matching the low linting propensity of the paper produced on a machine with gap former configuration. We found that the retention program, by improving fiber fines retention, substantially reduced the linting propensity of the paper produced on the hybrid former machine. The papers were also printed on a commercial coldset offset press. An excellent correlation was found between the total lint area removed from the bottom side of the paper samples during laboratory printing and lint collected on halftone areas of the first upper printing unit after 45000 copies. Finally, the method was applied to determine the linting propensity of highly filled supercalendered paper produced on a hybrid former machine. In this case, the linting propensity of the bottom side of paper correlated with its ash content.

Review of Unmanned Aircraft System (UAS)

2013 ◽  
Author(s):  
Suraj G. Gupta ◽  
Mangesh Ghonge ◽  
Pradip M. Jawandhiya
Keyword(s):  
Unmanned Aircraft ◽  
Unmanned Aircraft System ◽  
Aircraft System

scholarly journals REMAXINT: a two-mode clustering-based method for statistical inference on two-way interaction

2021 ◽  
Author(s):  
Zaheer Ahmed ◽  
Alberto Cassese ◽  
Gerard van Breukelen ◽  
Jan Schepers
Keyword(s):  
Null Hypothesis ◽  
Type I Error ◽  
Type I ◽  
The Novel ◽  
Simulation Studies ◽  
Test Statistic ◽  
Clustering Model ◽  
Novel Method ◽  
Main Effects ◽  
Empirical Case Studies

AbstractWe present a novel method, REMAXINT, that captures the gist of two-way interaction in row by column (i.e., two-mode) data, with one observation per cell. REMAXINT is a probabilistic two-mode clustering model that yields two-mode partitions with maximal interaction between row and column clusters. For estimation of the parameters of REMAXINT, we maximize a conditional classification likelihood in which the random row (or column) main effects are conditioned out. For testing the null hypothesis of no interaction between row and column clusters, we propose a $$max-F$$ m a x - F test statistic and discuss its properties. We develop a Monte Carlo approach to obtain its sampling distribution under the null hypothesis. We evaluate the performance of the method through simulation studies. Specifically, for selected values of data size and (true) numbers of clusters, we obtain critical values of the $$max-F$$ m a x - F statistic, determine empirical Type I error rate of the proposed inferential procedure and study its power to reject the null hypothesis. Next, we show that the novel method is useful in a variety of applications by presenting two empirical case studies and end with some concluding remarks.

scholarly journals Interrogating the Egypto-Sudanic Arabic Connection

Languages ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 123
Author(s):  
Thomas A. Leddy-Cecere
Keyword(s):  
The Novel ◽  
Present Contribution ◽  
Phonological Processes ◽  
Verbal Inflection ◽  
Segmental Phonology ◽  
Language Data ◽  
History Of ◽  
Novel Method ◽  
Dialect Classification ◽  
Arabic Speaking

The Arabic dialectology literature repeatedly asserts the existence of a macro-level classificatory relationship binding the Arabic speech varieties of the combined Egypto-Sudanic area. This proposal, though oft-encountered, has not previously been formulated in reference to extensive linguistic criteria, but is instead framed primarily on the nonlinguistic premise of historical demographic and genealogical relationships joining the Arabic-speaking communities of the region. The present contribution provides a linguistically based evaluation of this proposed dialectal grouping, to assess whether the postulated dialectal unity is meaningfully borne out by available language data. Isoglosses from the domains of segmental phonology, phonological processes, pronominal morphology, verbal inflection, and syntax are analyzed across six dialects representing Arabic speech in the region. These are shown to offer minimal support for a unified Egypto-Sudanic dialect classification, but instead to indicate a significant north–south differentiation within the sample—a finding further qualified via application of the novel method of Historical Glottometry developed by François and Kalyan. The investigation concludes with reflection on the implications of these results on the understandings of the correspondence between linguistic and human genealogical relationships in the history of Arabic and in dialectological practice more broadly.

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