D.A. Manolas, I. Borchers and D.T. Tsahalis
Active noise control (ANC) became in the last decade a very popular technique for controlling low‐frequency noise. The increase in its popularity was a consequence of the rapid…
Abstract
Active noise control (ANC) became in the last decade a very popular technique for controlling low‐frequency noise. The increase in its popularity was a consequence of the rapid development in the fields of computers in general, and more specifically in digital signal processing boards. ANC systems are application specific and therefore they should be optimally designed for each application. Even though the physical background of the ANC systems is well‐known and understood, tools for the optimization of the sensor and actuator configurations of the ANC system based on classical optimization methods do not perform as required. This is due to the nature of the problem that allows the calculation of the effect of the ANC system only when the sensor and actuator configurations are specified. An additional difficulty in this problem is that the sensor and the actuator configurations cannot be optimized independently, since the effect of the ANC system is directly involved in the combined sensor and actuator configuration. For the solution of this problem several intelligent techniques were applied. In this paper the successful application of a genetic algorithm, an optimization technique that belongs to the broad class of evolutionary algorithms, is presented.
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D.T. Tsahalis, S.K. Katsikas and D.A. Manolas
In order to achieve maximum noise reduction inside an aircraft cabin through the use of an active noise control system (ANCS), it is important that the number and positions of the…
Abstract
In order to achieve maximum noise reduction inside an aircraft cabin through the use of an active noise control system (ANCS), it is important that the number and positions of the sensors for monitoring the noise field; the control system for driving the actuators; and the number and positions of the actuators that generate the secondary noise field, which partially cancels the primary noise field, must be optimally determined. An optimization strategy for the positioning of the actuators, based on genetic algorithms (GA), is presented, assuming a fixed sensor configuration and a given control system. The application of the developed GA to a propeller aircraft is also discussed. The work presented was performed under the CEC BRITE/EURAM‐Aeronautics project “ASANCA”, in which a demonstrator ANCS was developed.
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T.P. Gialamas, D.A. Manolas and D.T. Tsahalis
In the present paper a weighted residual formulation of wave propagation through a porous material for a three‐dimensional case, based on the theoretical formulation of Zwikker…
Abstract
In the present paper a weighted residual formulation of wave propagation through a porous material for a three‐dimensional case, based on the theoretical formulation of Zwikker and Kosten for sound propagation in porous material, is described. Based on this formulation, a MATLAB code was developed which simulates an experimental configuration that consists of: a double wall cavity, formed by two parallel aluminum panels; and a reverberation room. A loudspeaker is placed on the reverberation room to provide the acoustical excitation of the double wall set‐up. The results which are obtained from the MATLAB code, in terms of the sound pressure level (SPL) in the double wall cavity and the displacement of the two panels, are compared with the corresponding experimental ones for the cases of air and thermal insulation material being the medium filling the double wall cavity.
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G.A. Efthimeros, D.I. Photeinos, Z.G. Diamantis and D.T. Tsahalis
This paper presents the optimization of the design of a railway wheel in terms of the wheel's sound power levels emission, with respect to its geometrical properties. To this end…
Abstract
This paper presents the optimization of the design of a railway wheel in terms of the wheel's sound power levels emission, with respect to its geometrical properties. To this end, a simplified finite element method (FEM) model of the wheel was employed, that did not include the interaction of the wheel and rail or the influence of the braking system that is assembled on the wheel. The objective of the optimization method was to find a design of the selected railway wheel, which without the use of damping or tuning devices, emits less vibration/noise compared to the original design. The optimization method used, was based on genetic algorithms (GAs). GAs are a robust optimization method that performs regardless of the optimization problem. The GA‐based optimization method that is presented in this paper, utilized ANSYS running in batch mode for the calculation of the objective function values of the population of each generation.
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Pascal Mognol, Denis Lepicart and Nicolas Perry
To discuss integration of the rapid prototyping environmental aspects with the primary focus on electrical energy consumption.
Abstract
Purpose
To discuss integration of the rapid prototyping environmental aspects with the primary focus on electrical energy consumption.
Design/methodology/approach
Various manufacturing parameters have been tested on three rapid prototyping systems: Thermojet (3DS), FDM 3000 (Stratasys) and EOSINT M250 Xtended (EOS). The objective is to select sets of parameters for reduction of electrical energy consumption. For this, a part is manufactured in several orientations and positions in the chamber of these RP systems. For each test, the electrical power is noted. Finally, certain rules are proposed to minimize this electrical energy consumption during a job.
Findings
It is important to minimize the manufacturing time but there is no general rule for optimization of electrical energy consumption. Each RP system must be tested with energy consumption considerations under the spotlight.
Research limitations/implications
The work is only based on rapid prototyping processes. The objective is to take into consideration the complete life‐cycle of a rapid prototyped part: manufacturing of raw material as far as reprocessing of waste.
Practical implications
Reduction of electrical energy consumption to complete a job.
Originality/value
Currently, environmental aspects are not well studied in rapid prototyping.
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H.S. Kumar, P. Srinivasa Pai and Sriram N. S
The purpose of this paper is to classify different conditions of the rolling element bearing (REB) using vibration signals acquired from a customized bearing test rig.
Abstract
Purpose
The purpose of this paper is to classify different conditions of the rolling element bearing (REB) using vibration signals acquired from a customized bearing test rig.
Design/methodology/approach
An effort has been made to develop health index (HI) based on singular values of the statistical features to classify different conditions of the REB. The vibration signals from the normal bearing (N), bearing with defect on ball (B), bearing with defect on inner race (IR) and bearing with defect on outer race (OR) have been acquired from a customized bearing test rig under variable load and speed conditions. These signals were subjected to “modified kurtosis hybrid thresholding rule” (MKHTR)-based denoising. The denoised signals were decomposed using discrete wavelet transform. A total of 17 statistical features have been extracted from the wavelet coefficients of the decomposed signal.
Findings
Singular values of the statistical features can be effectively used for REB classification.
Practical implications
REB are critical components of rotary machinery right across the industrial sectors. It is a well-known fact that critical bearing failures causes major breakdowns resulting in untold and most expensive downtimes that should be avoided at all costs. Hence, intelligently based bearing failure diagnosis and prognosis should be an integral part of the asset maintenance and management activity in any industry using rotary machines.
Originality/value
It is found that singular values of the statistical features exhibit a constant value and accordingly can be assigned to each type of bearing fault and can be used for fault characterization in practical applications. The effectiveness of this index has been established by applying this to data from Case Western Reserve University data base which is a standard bench mark data for this application. HIs minimizes the computation time when compared to fault diagnosis using soft computing techniques.
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Yen-Ning Su, Chia-Cheng Hsu, Hsin-Chin Chen, Kuo-Kuang Huang and Yueh-Min Huang
This study aims to use sensing technology to observe the learning status of learners in a teaching and learning environment. In a general instruction environment, teachers often…
Abstract
Purpose
This study aims to use sensing technology to observe the learning status of learners in a teaching and learning environment. In a general instruction environment, teachers often encounter some teaching problems. These are frequently related to the fact that the teacher cannot clearly know the learning status of students, such as their degree of learning concentration and capacity to absorb knowledge. In order to deal with this situation, this study uses a learning concentration detection system (LCDS), combining sensor technology and an artificial intelligence method, to better understand the learning concentration of students in a learning environment.
Design/methodology/approach
The proposed system uses sensing technology to collect information about the learning behavior of the students, analyzes their concentration levels, and applies an artificial intelligence method to combine this information for use by the teacher. This system includes a pressure detection sensor and facial detection sensor to detect facial expressions, eye activities and body movements. The system utilizes an artificial bee colony (ABC) algorithm to optimize the system performance to help teachers immediately understand the degree of concentration and learning status of their students. Based on this, instructors can give appropriate guidance to several unfocused students at the same time.
Findings
The fitness value and computation time were used to evaluate the LCDS. Comparing the results of the proposed ABC algorithm with those from the random search method, the algorithm was found to obtain better solutions. The experimental results demonstrate that the ABC algorithm can quickly obtain near optimal solutions within a reasonable time.
Originality/value
A learning concentration detection method of integrating context-aware technologies and an ABC algorithm is presented in this paper. Using this learning concentration detection method, teachers can keep abreast of their students' learning status in a teaching environment and thus provide more appropriate instruction.
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José Alexandre Matelli, Jonny C. Silva and Edson Bazzo
The purpose of this paper is twofold: to analyze the computational complexity of the cogeneration design problem; to present an expert system to solve the proposed problem…
Abstract
Purpose
The purpose of this paper is twofold: to analyze the computational complexity of the cogeneration design problem; to present an expert system to solve the proposed problem, comparing such an approach with the traditional searching methods available.
Design/methodology/approach
The complexity of the cogeneration problem is analyzed through the transformation of the well-known knapsack problem. Both problems are formulated as decision problems and it is proven that the cogeneration problem is np-complete. Thus, several searching approaches, such as population heuristics and dynamic programming, could be used to solve the problem. Alternatively, a knowledge-based approach is proposed by presenting an expert system and its knowledge representation scheme.
Findings
The expert system is executed considering two case-studies. First, a cogeneration plant should meet power, steam, chilled water and hot water demands. The expert system presented two different solutions based on high complexity thermodynamic cycles. In the second case-study the plant should meet just power and steam demands. The system presents three different solutions, and one of them was never considered before by our consultant expert.
Originality/value
The expert system approach is not a “blind” method, i.e. it generates solutions based on actual engineering knowledge instead of the searching strategies from traditional methods. It means that the system is able to explain its choices, making available the design rationale for each solution. This is the main advantage of the expert system approach over the traditional search methods. On the other hand, the expert system quite likely does not provide an actual optimal solution. All it can provide is one or more acceptable solutions.
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Liang Yan, Lei Zhang, Zongxia Jiao, Hongjie Hu, Chin-Yin Chen and I-Ming Chen
Force output is extremely important for electromagnetic linear machines. The purpose of this study is to explore new permanent magnet (PM) array and winding patterns to increase…
Abstract
Purpose
Force output is extremely important for electromagnetic linear machines. The purpose of this study is to explore new permanent magnet (PM) array and winding patterns to increase the magnetic flux density and thus to improve the force output of electromagnetic tubular linear machines.
Design/methodology/approach
Based on investigations on various PM patterns, a novel dual Halbach PM array is proposed in this paper to increase the radial component of flux density in three-dimensional machine space, which in turn can increase the force output of tubular linear machine significantly. The force outputs and force ripples for different winding patterns are formulated and analyzed, to select optimized structure parameters.
Findings
The proposed dual Halbach array can increase the radial component of flux density and force output of tubular linear machines effectively. It also helps to decrease the axial component of flux density and thus to reduce the deformation and vibration of machines. By using analytical force models, the influence of winding patterns and structure parameters on the machine force output and force ripples can be analyzed. As a result, one set of optimized structure parameters are selected for the design of electromagnetic tubular linear machines.
Originality/value
The proposed dual Halbach array and winding patterns are effective ways to improve the linear machine performance. It can also be implemented into rotary machines. The analyzing and design methods could be extended into the development of other electromagnetic machines.
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A numerical method is developed for steady and unsteady turbulent flows with significant regions of separation. A finite element formulation of the Navier‐Stokes equations with a…
Abstract
A numerical method is developed for steady and unsteady turbulent flows with significant regions of separation. A finite element formulation of the Navier‐Stokes equations with a modified Baldwin‐Lomax eddy viscosity closure is used. The method of averaging is employed to obtain a periodic solution of unsteady flow. The formulation is tested on a problem of flow over a backward‐facing step and the results are compared with experimental and other numerical results. The gross features of both steady and unsteady flows are reasonably well predicted by the numerical analysis, at least for the limited range of parameters tested so far.