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1 – 10 of over 1000Rainald Löhner and Fernando Camelli
Develop a method for the optimal placement of sensors in order to detect the largest number of contaminant release scenarios with the minimum amount of sensors.
Abstract
Purpose
Develop a method for the optimal placement of sensors in order to detect the largest number of contaminant release scenarios with the minimum amount of sensors.
Design/methodology/approach
The method considers the general sensor placement problem. Assuming a given number of sensors, every release scenario leads to a sensor input. The data recorded from all the possible release scenarios at all possible sensor locations allow the identification of the best or optimal sensor locations. Clearly, if only one sensor is to be placed, it should be at the location that recorded the highest number of releases. This argument can be used recursively by removing from further consideration all releases already recorded by sensors previously placed.
Findings
The method developed works well. Examples showing the effect of different wind conditions and release locations demonstrate the effectiveness of the procedure.
Practical implications
The method can be used to design sensor systems for cities, subway stations, stadiums, concert halls, high value residential areas, etc.
Originality/value
The method is general, and can be used with other physics‐based models (puff, mass‐conservation, RANS, etc.). The investigation also shows that first‐principles CFD models have matured sufficiently to be run in a timely manner on PCs, opening the way to optimization based on detailed physics.
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Masoud Seyed Sakha and Hamid Reza Shaker
One of the fundamental problems in control systems engineering is the problem of sensors and actuators placement. Decisions in this context play a key role in the success of…
Abstract
Purpose
One of the fundamental problems in control systems engineering is the problem of sensors and actuators placement. Decisions in this context play a key role in the success of control process. The methods developed for optimal placement of the sensors and actuators are known to be computationally expensive. The computational burden is significant, in particular, for large-scale systems. The purpose of this paper is to improve and extend the state-of-the-art methods within this field.
Design/methodology/approach
In this paper, a new technique is developed for placing sensor and actuator in large-scale systems by using restricted genetic algorithm (RGA). RGA is a kind of genetic algorithm which is developed specifically for sensors and actuator placement.
Findings
Unlike its other counterparts, the proposed method not only supports unstable systems but also requires significantly lower computations. The numerical investigations have confirmed the advantages of the proposed methods which are clearly significant, in particular, in dealing with large-scale unstable systems.
Originality/value
The proposed method is novel, and compared to the methods which have already been presented in literature is more general and numerically more efficient.
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Djamila Cherid, Nouredine Bourahla, Mohamed Said Laghoub and Anis Mohabeddine
Despite the fast progress in structural health monitoring (SHM), the efficient use in practice of emerging techniques for large civil engineering structures is still a challenge…
Abstract
Purpose
Despite the fast progress in structural health monitoring (SHM), the efficient use in practice of emerging techniques for large civil engineering structures is still a challenge. This paper outlines a practical framework to optimize both the number and the locations of sensors to measure frequency response functions (FRFs) that will be processed and used to predict the location and the damage level in a model of an existing suspension bridge.
Design/methodology/approach
Sensors number and placement (SNPO) procedure is proposed and carried out on a 3D FE model of the 502 m long Oued Dib suspension bridge (Algeria) to determine the degrees of freedom (DOFs) that will receive the sensors. For this purpose, accessible candidate positions on the model are first determined and then reduced by taking the DOFs with the lowest values of the Fisher information matrix (FIM) associated with each of the DOFs taken individually. A genetic algorithm with an objective function equal to the square root of the sum of the squares of the non-diagonal elements of the MAC matrix and a mutation function that allows increasing and decreasing the number of the chromosomes (sensors) of the individuals showed stable convergence to optimal solutions. FRFs at sensor positions generated from the 3D FE model and altered with artificial noise to simulate experimental conditions have been used to constitute a database to train and test a feed-forward neural network.
Findings
A framework for SHM integrating a genetic algorithm to optimize both the number and placement of the sensors on the structure.
Research limitations/implications
The procedure can be applied only for single predefined/potential damage detection.
Practical implications
The evidence from this study suggests that the proposed procedure provides a consistent framework to implement a SHM scheme for existing large infrastructures.
Social implications
Vital infrastructures require special structural protection that can be achieved through effective SHM. This study contributes to the deployment of SHM for existing civil engineering structures.
Originality/value
In addition to the integrated SHM framework proposed in this study, the latter includes an efficient genetic algorithm capable to optimize both the number and the placement of the sensors.
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Roman Ruzek, Martin Kadlec, Konstantinos Tserpes and Evaggelos Karachalios
Compression is critical loading condition for composite airframes. Compression behaviour of structures with or without damages is a weak point for composite fuselage panels. This…
Abstract
Purpose
Compression is critical loading condition for composite airframes. Compression behaviour of structures with or without damages is a weak point for composite fuselage panels. This is one of the reasons for need of continuous in-service health monitoring of composite structures. The purpose of this paper is to characterize the compression panel behaviour on the base of a developed and implemented structural health monitoring (SHM) system.
Design/methodology/approach
The SHM system based on fibre optic Bragg grating (FOBG) sensors and standard resistance strain gauges (SGs) was placed onto/into (embedded or bonded) three stiffened carbon fibre reinforced polymer (CFRP) fuselage panels. The FOBG sensor system was used to monitor the structural integrity of the reference, impacted, and fatigued panels under compression loading. Both barely visible impact damage and visible impact damage were created to evaluate their influence on the panel behaviour. The functionality of the SHM system was verified through mechanical testing.
Findings
Experimental data showed the presence of impact damages significantly changes the buckling modes development and deformation behaviour of the panels. Some differences between the optical and SG sensors during buckling were observed. The buckling waves and failure development were very well indicated during loading by all sensors located on the panel surface but not by the embedded sensors. Good agreement between the data from the SGs and FOBG sensors was achieved for all sensors placed on the stringers, which did not buckle. The good reliability of FOBG sensors during the fatigue and static testing up to panel failure was verified.
Originality/value
The paper gives information about different buckling behaviour of CFRP fuselage stiffened panels in compression. The paper gives detailed information about measured signals from different sensors based on their location on/in the panel structure for realistic loading scenario of composite aerostructures. The paper gives an integrated overview of sensors placement considering possibilities to predicate structure behaviour.
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Peng Li, Yuhua Wang, Jingru Hu and Jianmin Zhou
– The purpose of this study which resulted in this work is to propose an optimization method of sensors distribution for structural impact localization.
Abstract
Purpose
The purpose of this study which resulted in this work is to propose an optimization method of sensors distribution for structural impact localization.
Design/methodology/approach
This paper presents a multi-objective optimization study of a novel sensors distribution technique, where two optimization objective functions are considered: sensors number and sensors location optimization performance index. In addition, the finite element analysis, the time-frequency transform and the principal component analysis are combined to quantize the above objective functions. The non-dominated sorting genetic algorithm II (NSGA-II) is used to acquire Pareto solutions.
Findings
The effectiveness of this method is validated through a prototype laboratory called the piezoelectric intelligent structure where promising results are obtained.
Originality/value
An optimization method of this novel sensors distribution technique is built and produced a set of efficiency solutions for the real-world problem of impact localization where two conflicting objectives are involved.
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Yuyu Hao, Shugang Li and Tianjun Zhang
This paper aims to propose a deployment optimization and efficient synchronous acquisition method for compressive stress sensors used by stress distribution law research based on…
Abstract
Purpose
This paper aims to propose a deployment optimization and efficient synchronous acquisition method for compressive stress sensors used by stress distribution law research based on the genetic algorithm and numerical simulations. The authors established a new method of collecting the mining compressive stress-strain distribution data to address the problem of the number of sensors and to optimize the sensor locations in physical similarity simulations to improve the efficiency and accuracy of data collection.
Design/methodology/approach
First, numerical simulations were used to obtain the compressive stress distribution curve under specific mining conditions. Second, by comparing the mean square error between a fitted curve and simulation data for different numbers of sensors, a genetic algorithm was used to optimize the three-dimensional (3D) spatial deployment of sensors. Third, the authors designed an efficient synchronous acquisition module to allow distributed sensors to achieve synchronous and efficient acquisition of hundreds of data points through a built-in on-board database and a synchronous sampling communication structure.
Findings
The sensor deployment scheme was established through the genetic algorithm, A synchronous and selective data acquisition method was established for reduced the amount of sensor data required under synchronous acquisition and improved the system acquisition efficiency. The authors obtained a 3D compressive stress distribution when the advancement was 200 m on a large-scale 3D physical similarity simulation platform.
Originality/value
The proposed method provides a new optimization method for sensor deployment in physical similarity simulations, which improves the efficiency and accuracy of system data acquisition, providing accurate acquisition data for experimental data analysis.
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The purpose of this study is to monitor the progress of construction activities in an automated way by using sensor-based technologies for tracking multiple resources that are…
Abstract
Purpose
The purpose of this study is to monitor the progress of construction activities in an automated way by using sensor-based technologies for tracking multiple resources that are used in building construction.
Design/methodology/approach
An automated on-site progress monitoring approach was proposed and a proof-of-concept prototype was developed, followed by a field experimentation study at a high-rise building construction site. The developed approach was used to integrate sensor data collected from multiple resources used in different steps of an activity. It incorporated the domain-specific heuristics that were related to the site layout conditions and method of activity.
Findings
The prototype estimated the overall progress with 95% accuracy. More accurate and up-to-date progress measurement was achieved compared to the manual approach, and the need for visual inspections and manual data collection from the field was eliminated. Overall, the field experiments demonstrated that low-cost implementation is possible, if readily available or embedded sensors on equipment are used.
Originality/value
Previous studies either monitored one particular piece of equipment or the developed approaches were only applicable to limited activity types. This study demonstrated that it is technically feasible to determine progress at the site by fusing sensor data that are collected from multiple resources during the construction of building superstructure. The rule-based reasoning algorithms, which were developed based on a typical work practice of cranes and hoists, can be adapted to other activities that involve transferring bulk materials and use cranes and/or hoists for material handling.
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Riyaz Ali Shaik and Elizabeth Rufus
This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused.
Abstract
Purpose
This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused.
Design/methodology/approach
Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose.
Findings
LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction.
Research limitations/implications
The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing.
Practical implications
Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely.
Social implications
LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace.
Originality/value
This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.
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Dhanalakshmi M., Nagarajan T. and Vijayalakshmi P.
Dysarthria is a neuromotor speech disorder caused by neuromuscular disturbances that affect one or more articulators resulting in unintelligible speech. Though inter-phoneme…
Abstract
Purpose
Dysarthria is a neuromotor speech disorder caused by neuromuscular disturbances that affect one or more articulators resulting in unintelligible speech. Though inter-phoneme articulatory variations are well captured by formant frequency-based acoustic features, these variations are expected to be much higher for dysarthric speakers than normal. These substantial variations can be well captured by placing sensors in appropriate articulatory position. This study focuses to determine a set of articulatory sensors and parameters in order to assess articulatory dysfunctions in dysarthric speech.
Design/methodology/approach
The current work aims to determine significant sensors and parameters associated using motion path and correlation analyzes on the TORGO database of dysarthric speech. Among eight informative sensor channels and six parameters per channel in positional data, the sensors such as tongue middle, back and tip, lower and upper lips and parameters (y, z, φ) are found to contribute significantly toward capturing the articulatory information. Acoustic and positional data analyzes are performed to validate these identified significant sensors. Furthermore, a convolutional neural network-based classifier is developed for both phone-and word-level classification of dysarthric speech using acoustic and positional data.
Findings
The average phone error rate is observed to be lower, up to 15.54% for positional data when compared with acoustic-only data. Further, word-level classification using a combination of both acoustic and positional information is performed to study that the positional data acquired using significant sensors will boost the performance of classification even for severe dysarthric speakers.
Originality/value
The proposed work shows that the significant sensors and parameters can be used to assess dysfunctions in dysarthric speech effectively. The articulatory sensor data helps in better assessment than the acoustic data even for severe dysarthric speakers.
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The paper presents the analysis of magnetic field that surrounds the power transformer after it has been switched off. The purpose of this paper is to determine the possibility of…
Abstract
Purpose
The paper presents the analysis of magnetic field that surrounds the power transformer after it has been switched off. The purpose of this paper is to determine the possibility of defining the residual fluxes in the legs of the transformer based on the measurement of this field. It was also intended to determine the type and the location of magnetic sensors.
Design/methodology/approach
Numerical analysis of the magnetic field was performed. A three-dimensional model of the transformer’s magnetic core was created in the Flux 3D simulation program. The analysis was concerned with an oil-filled transformer and a dry transformer. The magnetic field of Earth was taken into account.
Findings
The research has shown that magnetic induction of the leakage field produced by residual magnetization of the core is comparable to the magnetic induction of the Earth’s field. It was also found that the measurement of the magnetic induction should be performed as close as possible to the core. The interior of the tank turned out to be a convenient space for the placement of the sensors.
Research limitations/implications
The influence of external ferromagnetic objects, and devices generating magnetic field, on the measurement was not considered. It should be taken into account in the future work.
Originality/value
On the basis of the analysis, it was proposed to measure the magnetic induction vector of the leakage field at three points. The sensors should be placed in front of the columns at a position that is half of their height. The measurement can be performed with satisfactory accuracy by sensors located on the surface of the windings.
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